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Recent European guidelines support the use of recycled and biodegradable packaging for food applications. The approval of such packaging must not alter food's taste or be harmful to health. In this work, PLA pellets were subjected to a post-consumer contamination procedure, washing process, and mechanical recycling, under common conditions of the recycling industry. HS-SPME-GC-MS and HS-SPME-GC-O-MS methods were used to detect volatile compounds and off-odor profiles. 33 different volatile compounds were identified in all samples. Intentionally added and non-intentionally added substances (IAS and NIAS) were identified, including benzaldehyde, benzyl alcohol, and dimethyl-1,4-dioxane-2,5-dione. The relationship between the formation of different NIAS and the PLA recycling process steps was determined. 14 different odor compounds such as benzyl alcohol, benzaldehyde, nonanal, decanal, dodecanal, 2,3-dimethylnaphthalene and 2,4-di-tert-butylphenol were detected and classified into 4 aroma groups (Toasted, Flower, Green and Chemical). The results obtained are essential for the food safety of recycled plastic material for food contact.

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Network biology is a powerful framework for studying the structure, function, and dynamics of biological systems, offering insights into the balance between health and disease states. The field is seeing rapid progress in all of its aspects: data availability, network synthesis, network analytics, and impactful applications in medicine and drug development. We review the most recent and significant results in network biomedicine, with a focus on the latest data, analytics, software resources, and applications in medicine. We also discuss what in our view are the likely directions of impactful development over the next few years.

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Introduction The current experiment investigated the multifaceted effects induced by microplastics and the statin Lipitor on marine benthic nematodes.Methods The nematodes were exposed to a single polystyrene and polyvinyl chlorides (both at 1 mg.kg-1 Dry Weight) and two Lipitor concentrations (0.1 and 1 mg.l-1), as well as to a mixture of both types of pollutants, for 30 days.Results The results highlighted a significant decrease in the abundance, individual biomass, and diversity of nematodes directly with the addition of polyvinyl chlorides and/or Lipitor. These treatments induced a greater mortality rate among microvores and diatom feeders compared to other feeding types of nematodes.Discussion The nematofauna underwent a strong restructuring phase following exposure to microplastics and Lipitor when added alone, leading to the disappearance of sensitive species and their replacement by more tolerant taxa. The toxicity of Lipitor is attenuated by the physical bonding with polystyrene when added to a mixture and has no negative effect on marine nematode species.

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In samples of Artemisia campestris (AC), Artemisia herba-alba (AHA) and Salvia jordanii (SJ) essential oils, up to 200 distinct volatile compounds were identified. Using headspace solid-phase microextraction combined with gas chromatography-olfactometry-mass spectrometry (HS-SPME-GC-O-MS), different panelists detected 52 of these compounds. This study offers the most detailed analysis of bioactive compound profiles conducted so far. The most abundant compounds identified were curcumene, making up 12.96% of AC, and camphor, constituting 21.67% of AHA and 19.15% of SJ. The compounds with the highest odor activity value (OAV) were (E,Z)-2,4-nonadienal (geranium, pungent), 3-nonenal (cucumber) and 2-undecenal (sweet) in AC, AHA and SJ, respectively. AHA essential oil showed significant antioxidant activity (IC50 = 41.73 +/- 4.14 mg/g) and hydroxyl radical generation (hydroxylation percentage = 29.62 +/- 3.14), as assessed by the diphenylpicrylhydrazyl (DPPH) method. In terms of oxygen radical absorbance capacity (ORAC), the strongest antioxidant activity was obtained for SJ essential oil (antioxidant activity of the essential oils, AOX = 337.49 +/- 9.87).

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We define the jump complexity of a finite automaton with translucent letters as a function that computes the smallest upper bound on the number of jumps needed by the automaton in order to accept each word of length n, for any positive integer n. We prove that a sufficient condition for a finite automaton with translucent letters to accept a regular language is to have a jump complexity bounded by a constant. Along the same lines, we show that there are languages which require a jump complexity in Omega(n) of any finite automaton with translucent letters accepting one of these languages. We also show that there exist nondeterministic finite automata with translucent letters of jump complexity in O(log n) and O(root n) that accept non-regular languages. Several open problems and directions for further developments are finally discussed.

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Logical modeling is a powerful tool in biology, offering a system-level understanding of the complex interactions that govern biological processes. A gap that hinders the scalability of logical models is the need to specify the update function of every vertex in the network depending on the status of its predecessors. To address this, we introduce in this paper the concept of strong regulation, where a vertex is only updated to active/inactive if all its predecessors agree in their influences; otherwise, it is set to ambiguous. We explore the interplay between active, inactive, and ambiguous influences in a network. We discuss the existence of phenotype attractors in such networks, where the status of some of the variables is fixed to active/inactive, while the others can have an arbitrary status, including ambiguous.

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We consider networks whose nodes host splicing processors, that is processors that are able to simulate the DNA recombination by splicing. Several topologies for the underlying graph of these networks are investigated. More precisely, we show that each network of splicing processors with some underlying graph can be directly converted into an equivalent network having an underlying graph of a different topology. Several common topologies are considered: full-mesh, star, grid, and wheel (ring-star). We also investigate the time and size complexity of each of these simulations.

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We consider networks whose nodes host splicing processors, that is processors that are able to simulate the DNA recombination by splicing. Several topologies for the underlying graph of these networks are investigated. More precisely, we show that each network of splicing processors with some underlying graph can be directly converted into an equivalent network having an underlying graph of a different topology. Several common topologies are considered: full-mesh, star, grid, and wheel (ring-star). We also investigate the time and size complexity of each of these simulations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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Motivated by the need of reducing the huge amount of data navigating simultaneously through a network of polarized splicing processors, we look to the possibility of introducing probabilities which theoretically could decrease this amount, at a price of some loss of certainty. We imagined two possible situations regarding the splicing step: to associate either fixed or dynamically computed probabilities with splicing rules in every node. Similarly to the splicing step, two situations could be considered for the communication step depending on the way the probabilities are associated: statically or dynamically. We believe that this new feature together with the communication protocol based on polarization might facilitate software simulations or hardware implementations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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BACKGROUND: Formalin-fixed, paraffin-embedded (FFPE) tissue slides are routinely used in cancer diagnosis, clinical decision-making, and stored in biobanks, but their utilization in Raman spectroscopy-based studies has been limited due to the background coming from embedding media.METHODS: Spontaneous Raman spectroscopy was used for molecular fingerprinting of FFPE tissue from 46 patient samples with known methylation subtypes. Spectra were used to construct tumor/non-tumor, IDH1WT/IDH1mut, and methylation-subtype classifiers. Support vector machine and random forest were used to identify the most discriminatory Raman frequencies. Stimulated Raman spectroscopy was used to validate the frequencies identified. Mass spectrometry of glioma cell lines and TCGA were used to validate the biological findings.RESULTS: Here we develop APOLLO (rAman-based PathOLogy of maLignant glioma) - a computational workflow that predicts different subtypes of glioma from spontaneous Raman spectra of FFPE tissue slides. Our novel APOLLO platform distinguishes tumors from nontumor tissue and identifies novel Raman peaks corresponding to DNA and proteins that are more intense in the tumor. APOLLO differentiates isocitrate dehydrogenase 1 mutant (IDH1mut) from wildtype (IDH1WT) tumors and identifies cholesterol ester levels to be highly abundant in IDHmut glioma. Moreover, APOLLO achieves high discriminative power between finer, clinically relevant glioma methylation subtypes, distinguishing between the CpG island hypermethylated phenotype (G-CIMP)-high and G-CIMP-low molecular phenotypes within the IDH1mut types.CONCLUSIONS: Our results demonstrate the potential of label-free Raman spectroscopy to classify glioma subtypes from FFPE slides and to extract meaningful biological information thus opening the door for future applications on these archived tissues in other cancers.

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We propose a simulation of an arbitrary network of evolutionary processors by a network having a special underlying graph, namely a wheel (ring-star) graph. This work continues a series of papers devoted to simulations between networks of evolutionary processors with various topologies. Somehow unexpected, the simulation is time complexity preserving at the price of a much larger network.

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Sycamore is a valuable tree not only economically but also ecological and culturally. Even though it has a vigorous regeneration system from its stump, its coppice management has triggered limited formal investigations. Therefore, the present study focused on finding the most suitable coppice strategy for achieving ground coverage and biomass, as well as developing growth and yield models for sycamore maples. Using a series of eight measurements spanning twenty-one years, starting from age six, we found that single-shoot coppices provided superior yields for height than seed-managed trees up to age twelve and up to age twenty for DBH. The coppice trees outperformed the seed trees up to age 10. The yield of DBH and the height for single-shoots and seed-managed trees were described by parsimonious formulations, namely the Schumacher model for DBH and the square root for height. The relationship of DBH-height exhibited a clear linear form, pointing toward the main limitation of the study, namely the confinement to ages less than 20 years. Nevertheless, all the models exhibited a bias R-2 around 80%, except for the height and DBH change throughout time, which was around 67%.

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The current experiment measured the multifaceted effects of polystyrene and fluoranthene, acting alone or in a mixture on marine meiofauna, but with a special focus on nematodes' morphological and functional traits. The results showed changes in the abundances for all tested concentrations of both compounds. The nematode communities exposed to the highest concentrations of fluoranthene (30 ng.g � 1 Dry Weight (DW)) and polystyrene (100 mg.kg-1 DW) alone or in a mixture, were significantly less diverse compared to control and were associated with significant changes in the percentage of taxonomic composition and feeding-guilds. The most sensitive taxa to fluoranthene comprised epistratum feeders, whereas the nematodes mostly affected by polystyrene were omnivores-carnivores. A new functional tool, the Index of Sensitivity (IOS), proved to be reliable in depicting the changes that occurred in the taxonomic and functional features of the nematofauna.

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The present study examined the histopathological changes and some parameters of oxidative stress in the testes of the freshwater leech Limnatis nilotica, following their exposure to 50 mu g l(-1) of cadmium (Cd). The protective effects of salicylic acid (SA) in mitigating Cd-induced oxidative and histopathological injury were also investigated. We found that Cd exposure caused several histopathological changes in leech testes, such as vacuolisation of spermatogenic cysts which were strongly destroyed and disorganised. Biochemical study showed oxidative stress damage marked by a substantial increase in malondialdehyde and hydrogen peroxidase levels as well as disturbance in the activity of the leech antioxidant system. Interestingly, the testes from the Cd and SA leech-exposed group exhibited increased enzymatic and nonenzymatic antioxidant mechanism defenses, including superoxide dismutase, catalase, glutathione peroxidase, glutathione, oxidized glutathione, thiols, and ascorbic acid, in comparison with the testes of leeches exposed to Cd alone. Thus, SA supplementation considerably attenuated the histopathological lesions induced by Cd exposure, thereby restoring the normal appearance of the testes. In summary, the findings of this study indicate that SA treatment ameliorated the testicular histopathological and oxidative stress-induced damages caused by exposure to Cd through enhancing the antioxidant defense system.

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Networks of splicing processors are one of the theoretical computational models that take inspiration from nature to efficiently solve problems that our current computational knowledge is not able to. One of the issues restricting/hindering is practical implementation is the arbitrariness of the underlying graph, since our computational systems usually conform to a predefined topology. We propose simulations of networks of splicing processors having arbitrary underlying graphs by networks whose underlying graphs are of a predefined topology: complete, star, and grid graphs. We show that all of these simulations are time efficient in the meaning that they preserve the time complexity of the original network: each computational step in that network is simulated by a fixed number of computational steps in the new topologic networks. Moreover, these simulations do not modify the order of magnitude of the network size.

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The current study presents the results of an experiment carried to assess the impact of azithromycin, a COVID-19 drug, probably accumulated in marine sediments for three years, since the start of the pandemic, on benthic marine nematodes. It was explored the extent to which a common macrophyte from the Mediterranean Sea influenced the toxic impact of azithromycin on meiobenthic nematodes. Metals are known to influence toxicity of azithromycin. The nematofauna from a metallically pristine site situated in Bizerte bay, Tunisia, was exposed to two concentrations of azithromycin [i.e. 5 and 10 mu g l- 1]. In addition, two masses of the common macrophyte Posidonia oceanica [10 and 20% Dry Weight (DW)] were considered and associated with azithromycin into four possible combinations. The abundance and the taxonomic diversity of the nematode communities decreased significantly following the exposure to azithromycin, which was confirmed by the toxicokinetic data and behaving as substrate for P-glycoprotein (P-gp). The toxicity of 5 mu g l- 1 dosage of azithromycin was partially reduced at 10% DW of Posidonia and completely at 20% DW. The results showed that 5 mu g l- 1 of azithromycin can be reduced by the macrophyte P. oceanica when present in the environment at low masses as 10% DW.

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The health status of Mytilus galloprovincialis native from a polluted habitat was surveyed before and after 30 and 60 days of in situ transplantation and in vivo experiments. The results showed a reduction in filtration rate by 24 % and 45 %, respectively, after 60 days of in vivo and in situ experiments compared to the rates at polluted sites. The respiration rate reached a minimum of 0.081 & PLUSMN; 0.05 mg O2.L- 1 after 60 days of in situ transplantation. Moreover, the antioxidant activities were changed in a time-dependent manner for both transplantation conditions. The highest superoxide dismutase and catalase activities corresponded to the stressed mussels and declined by 76 % and 54 %, respectively, after 60 days of in situ transplantation. Changes in lipid peroxidation and acetylcholinesterase activity were observed in internal organs following 60 days of transplantation. At this time slot, the lowest content of metals and microplastics was also noticed.

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Simple Summary The multiple impacts of polycylic aromatic hydrocarbon on the aquatic invertebrates were rarely assessed in a chronic way and multiple-species experiments, despite the clear advantage of better mimicking natural conditions compared to traditional acute and single-species-focused toxicological experiments. The application of such an approach is essential to lower the health risks for populations that regularly consume seafood. The data presented herein supported the use of Mytilus galloprovincyalis and Ruditapes decussatus as bioindicators of phenanthrene in water and/or sediment and proved the efficacy of the biomarkers' assessment and molecular modelling in determining environmental thresholds and policies for governments. The aim of the current study was to assess the multifaceted effects of the polycylic aromatic hydrocarbon phenanthrene, mainly used in the colouring, explosive, and pharmaceutical industries, on the physiology of two bivalve species with economic value as seafood, namely, the Mediterranean mussel Mytilus galloprovincyalis and the European clam Ruditapes decussatus. The current study assessed how the phenanthrene affected several biomarkers and biometric endpoints in both bivalves, based on an in vivo experiment in silico approach. The bivalves were exposed during four time slots (i.e., 7, 15, 21, and 28 days) to two concentrations of phenanthrene in water (50 mu g/L and 100 mu g/L). For the clam R. decussatus, an additional contamination of sediment was applied due their typical benthic lifestyle (50 mu g/kg and 100 mu g/kg). The phenanthrene significantly reduced the ability of bivalves to tolerate desiccation and their Median Lethal Time, and also inhibited the activity of the enzyme acetylcholinesterase in a time-dependent manner. The activity of catalase indicated that bivalves also experienced oxidative stress during the first 21 days of the experiment. The significant decline in catalase activity observed during the last week of the experiment for the mussel M. galloprovincyalis supported a depletion of enzymes caused by the phenanthrene. The phenanthrene has also toxicokinetic and toxicodynamic properties, as assessed by the in silico approach. Overall, the results obtained suggest that the bivalves Ruditapes decussatus and M. galloprovincyalis can be used as a sentinel species in monitoring studies to assess the environmental impact of phenanthene in marine ecosystems. The significance of our findings is based on the fact that in ecotoxicology, little is known about the chronic effects, the simultaneous use of multiple species as bioindicators, and the interactions molecular modelling.

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Healthcare professionals face an ongoing challenge in managing both acute and chronic wounds, given the potential impact on patients' quality of life and the limited availability of expensive treatment options. Hydrogel wound dressings offer a promising solution for effective wound care due to their affordability, ease of use, and ability to incorporate bioactive substances that enhance the wound healing process. Our study aimed to develop and evaluate hybrid hydrogel membranes enriched with bioactive components such as collagen and hyaluronic acid. We utilized both natural and synthetic polymers and employed a scalable, non-toxic, and environmentally friendly production process. We conducted extensive testing, including an in vitro assessment of moisture content, moisture uptake, swelling rate, gel fraction, biodegradation, water vapor transmission rate, protein denaturation, and protein adsorption. We evaluated the biocompatibility of the hydrogel membranes through cellular assays and performed instrumental tests using scanning electron microscopy and rheological analysis. Our findings demonstrate that the biohybrid hydrogel membranes exhibit cumulative properties with a favorable swelling ratio, optimal permeation properties, and good biocompatibility, all achieved with minimal concentrations of bioactive agents.

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The impact of metallic nanoparticles (NPs) on the uptake and toxicity of persistent organic pollutants by marine bivalves was assessed through a comparative laboratory study by exposing mussels to polycyclic aromatic hy-drocarbon (PAHs), in the presence and absence of ZnO and TiO2 NPs. PAHs and NPs concentration was analyzed after 14 days of exposure in mussels by GC/MS and ICP/AES. Furthermore, impact on the physiology and neurotoxicity of PAHs and NPs acting alone or in mixtures were also determined. Our results confirmed the bio-uptake of PAHs and NPs by mussels. In addition, the exposure NPs-PAHs resulted in different bio-uptake profile to that of PAHs alone. The NPs and accumulation of PAHs led to disturbance of essential metals concentration and to different impact profiles in the filtration and respiration capacities as well as in the acetylcholinesterase activity. Antagonist interactions between NPs and PAHs could occur after exposure.

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Polycyclic aromatic hydrocarbons (PAHs) are toxic for humans and marine fauna alike. The current study assessed the impact of PAHs on the migratory behaviour of meiobenthic nematodes collected from the Bizerte lagoon, Tunisia. The experiment lasted for 15 days and was carried in open microcosms, which comprised a lower, contaminated and an upper, uncontaminated compartment. Three treatments were used, for each of them an untreated control was set up: sediment contaminated with chrysene (116 ng g(-1) dry weight (DW), with phenanthrene (116 ng g(-1) DW) and a mixture of both. The results showed a significant decrease in diversty and abundance in the lower, contaminated compartments compared to the upper zones. The results also highlighted that under an increased stress some species progressively increased in number, these were considered PAH-tolerant species such as Odontophora villoti, some others had an occasionally increased in number were consid-ered as opportunistic species, such as Paracomesoma dubium and the species that showed a progressive decreased in number, such as Metoncholaimus pristiurus and Steineria sp., Terschellingia. longicaudata, and Oncholaimellus sp. were classified as PAH-sensitive. Moreover, an increase in the activity of biochemical biomarkers was observed following the exposure of males and gravid females of T. longicaudata to 29, 58 and 87 ng g(-1) DW of chrysene and phenanthrene paralleled by a higher vulnerability of the latter demographic category. Besides, a significant decrease in fertility of females and an increase in pharyngeal sucking power were observed for both types of PAHs considered. The sex ratio was also significantly imbalanced in the favor of males, which suggest that chrysene and phenanthrene affect also the hormone system of T. longicaudata. The high affinities of these PAHs and their molecular interactions with both germ line development protein 3 (GLD-3) and sex-determining protein (SDP) may justify these results and explain the toxicokinetic attributes.

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This work is a survey of the main results reported for the degree of extension of two models defining non-regular languages, namely the context-free grammar and the extended automaton over groups. More precisely, we recall the main results regarding the degree on non-regularity of a context-free grammar as well as the degree of extension of finite automata over groups. Finally, we consider a similar measure for the finite automata with translucent letters and present some preliminary results. This measure could be considered for many mechanisms that extend a less expressive one. © V. Mitrana, M. Păun This work is licensed under the Creative Commons Attribution License.

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Healthcare professionals face an ongoing challenge in managing both acute and chronic wounds, given the potential impact on patients’ quality of life and the limited availability of expensive treatment options. Hydrogel wound dressings offer a promising solution for effective wound care due to their affordability, ease of use, and ability to incorporate bioactive substances that enhance the wound healing process. Our study aimed to develop and evaluate hybrid hydrogel membranes enriched with bioactive components such as collagen and hyaluronic acid. We utilized both natural and synthetic polymers and employed a scalable, non-toxic, and environmentally friendly production process. We conducted extensive testing, including an in vitro assessment of moisture content, moisture uptake, swelling rate, gel fraction, biodegradation, water vapor transmission rate, protein denaturation, and protein adsorption. We evaluated the biocompatibility of the hydrogel membranes through cellular assays and performed instrumental tests using scanning electron microscopy and rheological analysis. Our findings demonstrate that the biohybrid hydrogel membranes exhibit cumulative properties with a favorable swelling ratio, optimal permeation properties, and good biocompatibility, all achieved with minimal concentrations of bioactive agents. © 2023 by the authors.

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Cadmium (Cd) is considered as one of the most highly toxic heavy metal that is released into the environment on a large scale, and its concentrations in water have significantly increased as a result of human activities. In particular, contamination of rivers and drinking water may easily occur, especially in locations close to industry or mines. In this study, we examined the impact of Cd exposure on the body wall of the freshwater leech Limnatis nilotica at concentrations of 100, 200, and 300 µg/l. The findings showed that the exposure caused histopathological changes as well as oxidative stress (increased malondialdehyde concentrations (MDA)) and changes in antioxidant activity (superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (Gpx)). In fact, numerous histological changes were observed, such as cuticle deterioration, a marked increase in the number of secretory cells, increased mucus production, vacuolization of the epithelium, altered epithelial cell borders, and mucus cell hyperplasia. The histological results are consistent with the biochemical findings because we found that MDA levels significantly increased in a dose-dependent manner. Additionally, the Cd exposure disrupted the levels of the antioxidant levels. Indeed, SOD, CAT, and Gpx activities were increased in the group treated with the lower dose (100 g/l), whereas their levels dramatically decreased at higher Cd doses (200 and 300 g/l). Therefore, the presence of this heavy metal in freshwater habitats may have severe ecological risks that may lead to leech aquatic habitat destruction and fragmentation. © 2023, Universita degli Studi di Modena e Reggio Emilia. All rights reserved.

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Arguably the most popular remote-sensing products are classified images. However, there are no definitive procedures to assess classification accuracy that simultaneously consider resources available and field efforts. The explosive usage of unmanned aerial systems (UAS) in land surveys adds new challenges to classification assessment, as orthorectified images usually contain significant artifacts. This study aims to identify the optimal ratio between training and validation sample size within a supervised classification approach applied to UAS orthophotos. As a case study, we used a wetland area west of Portland, OR, USA, treated with various glyphosate formulations to control Phalaris arundinacea, commonly known as reed canary grass. A completely randomized design with five replications and six glyphosate formulations was used to assess P. arundinacea vigor following repeated herbicide applications. The change in P. arundinacea vitality was monitored with high-resolution four-band imagery acquired with a SlantRange 3PX camera installed on a DJI Matrice 210. The orthophotos created from images were produced with Pix4D, which was subsequently preprocessed with ERDAS Imagine 2020 to reduce the noise, shadows, and artifacts. All images were classified with the maximum likelihood classification algorithm. Simple random and stratified random sampling methods were applied to collect training and validation samples, evaluating eight ratios of training to validation samples to assess their classification accuracy. We found that increasing the training-to-validation sample size ratio enhances accuracy, with the 3:1 ratio being the most reliable in classifying P. arundinacea vigor. Our study provides evidence that image preprocessing and enhancement are essential for UAS-based imagery. © Articles by the authors; Licensee UASVM and SHST, Cluj-Napoca, Romania. The journal allows the author(s) to hold the copyright/to retain publishing rights without restriction.

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Introduction: Cannabinoids are a group of compounds that bind to cannabinoid receptors. They possess pharmacological properties like that of the plant Cannabis sativa. Gas chromatography (GC) is one of the popular chromatographic techniques that has been routinely used in the analysis of cannabinoids in different matrices.Objective: The article aims to review the literature on the application of GC-based analytical methods for the analysis of phytocannabinoids published during the period from January 2020 to August 2023.Methodology: A thorough literature search was conducted using different databases, like Web of Knowledge, PubMed, Google Scholar, and other relevant published materials including published books. The keywords used, in various combinations, with cannabinoids being present in all combinations, in the search were cannabinoids, Cannabis sativa, marijuana, analysis, GC, quantitative, qualitative, and quality control. From the search results, only the publications that incorporate the GC analysis of phytocannabinoids were reviewed, and papers on synthetic cannabinoids were excluded.Results: Since the publication of the review article on GC analysis of phytocannabinoids in early 2020, several GC-based methods for the analysis of phytocannabinoids have appeared in the literature. While simple 1D GC-mass spectrometry (MS) and GC-flame ionisation detector (FID) methods are still quite common in phytocannabinoids analysis, 2D GC-MS and GC-MS/MS are increasingly becoming popular, as these techniques offer more useful data for identification and quantification of phytocannabinoids in various matrices. The use of automation in sample preparation and the utilisation of mathematical and computational models for optimisation of different protocols have become a norm in phytocannabinoids analysis. Pre-analyses have been found to incorporate different derivatisation techniques and environmentally friendly extraction protocols.Conclusions: GC-based analysis of phytocannabinoids, especially using GC-MS, remains one of the most preferred methods for the analysis of these compounds. New derivatisation methods, ionisation techniques, mathematical models, and computational approaches for method optimisation have been introduced.

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The aquatic subterranean ecosystems represent research frontiers for ecology and conservation biology. The aquatic subterranean fauna and associated microorganisms are organised in food webs that are essential in the nutrients cycling and energy fluxes within habitats generally characterised by low resources. However, the knowledge of how these trophic networks are structured and conditioned by the interaction with surface ecosystems is scarce. Traditionally, subterranean aquatic food webs were regarded as simple and truncated because of low species diversity and abundance compared to surface. The current review provides an updated description of aquatic subterranean food webs, based on the latest findings from various types of habitats: cave streams, the hyporheic zone and phreatic aquifers, with the general conclusion that such trophic networks are much more complex and dynamic as historically believed. The energylimitation hypothesis and the bottom-up forces are increasingly recognised as the main structuring agents of the aquatic subterranean trophic networks. It is predicted that the bottom-up forces are generated by two interconnected factors: nutrients availability in water and quantity, quality and the types (i.e. surface derived photosynthetic and detrital, in some cases mixed with in situ chemosynthetically based organic matter) of basal energy input. Further recommendations for the integration of groundwater research into the current overarching concepts of surface ecology are made, given this field of science remains currently rather descriptive and less hypothesis-driven.

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We continue here the theoretical study initiated approximately twenty years ago on the possibility of using living cells for computing. In this paper, we reconsider the formal operations inspired by the intramolecular DNA rearrangements in the evolution of the macronucleus from the micronucleus in a group of ciliates. After introducing the concept of a valid string, we propose an efficient algorithm for checking this property for a given string. Then we investigate which of the considered operations preserve the property of a string to be valid. We also show that just one of the operations can be simulated by a finite transducer. The important problem regarding the order of applying the operations is then investigated showing that one operation can commute with the other two. Finally, we introduce the iterated variants and investigate a few properties. A sort of a normal form for the gene assembly in ciliates is obtained. The paper ends by a short discussion about open problems and further directions of research.

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The modernization of official statistics involves the use of new data sources, such as data collected through remote sensing. The document contains a description of how an urban green index, derived from the SDG 11.7 objective, was obtained for Romania's 41 county seat cities based on free data sets collected by remote sensing from the European and North American space agencies. The main result is represented by an estimate of the areas of surfaces covered with vegetation for the 40 county seat towns and the municipality of Bucharest, relative to the total surface. To estimate the area covered with vegetation, we used two data sets obtained by remote sensing, namely data provided by the MODIS mission, the TERRA satellite, and data provided by the Sentinel 2 mission from the Copernicus space program. Based on the results obtained, namely the surface area covered with vegetation, estimated in square kilometers, and the percentage of the total surface area or urban green index, we have created a national top of the county seat cities.

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Introduction: Cannabinoids are a group of compounds that bind to cannabinoid receptors. They possess pharmacological properties like that of the plant Cannabis sativa. Gas chromatography (GC) is one of the popular chromatographic techniques that has been routinely used in the analysis of cannabinoids in different matrices. Objective: The article aims to review the literature on the application of GC-based analytical methods for the analysis of phytocannabinoids published during the period from January 2020 to August 2023. Methodology: A thorough literature search was conducted using different databases, like Web of Knowledge, PubMed, Google Scholar, and other relevant published materials including published books. The keywords used, in various combinations, with cannabinoids being present in all combinations, in the search were cannabinoids, Cannabis sativa, marijuana, analysis, GC, quantitative, qualitative, and quality control. From the search results, only the publications that incorporate the GC analysis of phytocannabinoids were reviewed, and papers on synthetic cannabinoids were excluded. Results: Since the publication of the review article on GC analysis of phytocannabinoids in early 2020, several GC-based methods for the analysis of phytocannabinoids have appeared in the literature. While simple 1D GC–mass spectrometry (MS) and GC–flame ionisation detector (FID) methods are still quite common in phytocannabinoids analysis, 2D GC-MS and GC-MS/MS are increasingly becoming popular, as these techniques offer more useful data for identification and quantification of phytocannabinoids in various matrices. The use of automation in sample preparation and the utilisation of mathematical and computational models for optimisation of different protocols have become a norm in phytocannabinoids analysis. Pre-analyses have been found to incorporate different derivatisation techniques and environmentally friendly extraction protocols. Conclusions: GC-based analysis of phytocannabinoids, especially using GC-MS, remains one of the most preferred methods for the analysis of these compounds. New derivatisation methods, ionisation techniques, mathematical models, and computational approaches for method optimisation have been introduced. © 2023 John Wiley & Sons, Ltd.

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River restoration and biodiversity conservation programs require an in-depth knowledge of the influence that sediment composition and hydraulic stress have on invertebrate fauna composition and spatial distribution, as well as on nutrients cycling and food webs' structure and functionality. Compared to low-order streams, the traditional focus of river ecology, the knowledge of these ecosystem properties of the meanders developed along large, lowland watercourses, is currently insufficient. The present study assessed the ecological preferences and the trophic interactions of the benthic invertebrate communities inhabiting erosional and depositional banks developed within a meander of the River Danube flowing through its delta (Danube Delta, Romania). The invertebrates from two mesohabitats, the concave (i.e. erosional) and convex (i.e. depositional) banks developed in the apex region of the meander were sampled quantitatively and qualitatively, along with sediment samples for assessing the grain-size characteristics and hydrodynamic parameters (i.e., critical shear stress, the Reynolds number, the critical velocity and Shields parameter). For assessing their mesohabitat preferences, quantitative samples were taken from both banks, whereas for inferring the trophic interactions, stable isotopes of 815N and 813C were measured from qualitative samples, comprising both invertebrates and basal resources. The results showed that increased siltation with fine sediments in the depositional bank led to a community dominated by chironomids, oligochaetes and bivalves, whereas the opposite bank comprised crayfish, caddis fly larvae and amphipods with a preference for coarser sediments. The 813C of most consumers revealed that the dominant forms of carbon entries in the analysed food webs were photosynthetic based, whereas certain snails, chironomids and basal resources from the depositional bank were 13C depleted (813C: -35 to -39 %o). Such low ratios for 813C (mean < -35 %o) reflected the potential of carbon entry through the base of depositional food web as a result of methane oxidation at sediment-water interface (i.e. chemosynthesis), induced by the fine sediments deposition that could have favoured the methane production. Grazing methaneoxidising bacteria in the depositional meander bank could have provided the primary consumers with up to 50 % and the omnivores and predatory invertebrates with up to 30 % of their carbon, which could represent an important subsidy from an additional, chemosynthetic source. The impact of a supplementary carbon input was further reflected in increasing depositional food

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The present study focused on the ecological preferences of benthic macroinvertebrates regarding water flow and sediment characteristics in two submerged dunes from Danube Delta (Romania). Three hydraulic microhabitats, the stoss, trough and crest areas were sampled, along with measurements of water hydraulics, hydrology, sediment grain-size, and organic content. The results showed that the slope angles between stoss-crest and crest-trough areas are crucial in modulating local flows, sediment structure, organic content, macroinvertebrate communities, and taxonomic richness and density. As such, the stoss microhabitats are considered zones with the highest turbulence, hence driving low taxonomic richness and density compared to crest and trough microhabitats. When local environmental conditions in trough microhabitats allow the accretion of fine and organically enriched sediments, the development of maximum density for certain macroinvertebrates groups is reached. However, the benthic assemblages did not show clear preferences for certain microhabitats, suggesting ubiquitous ecologic traits, crucial for the successful colonisation of dynamic habitats, such as the submerged dunes in large rivers. The results of this study offer a better understanding on the abiotic factors driving the spatial preferences, density, and diversity of benthic macroinvertebrates in these understudied hydrogeomorphological units from large rivers.

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Networks of evolutionary processors (NEP for short) form a class of models within the new computational paradigms inspired by biological phenomena. They are known to be theoretically capable of solving intractable problems. So far, there are two main categories that differ from each other by the nature of filtering process controlling the communication step: random-context clauses or polarization. Several studies have proven that both of them are computationally complete through efficient simulations of universal computational models such as Turing machines and 2-tag systems. Nevertheless, the indirect conversion between the two network variants results in an exponential increase of the computational complexity. In this paper, we suggest a direct simulation of polarized NEP through NEP with random-context filters which incurs in lower complexity costs.

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The influence of physicochemical parameters other than the nutrients load on the community structure of phyto- and zooplankton in lowland shallow lakes is still poorly understood. In this study we investigated the structure of the plankton community in Danube Delta (Romania) and the relationships with environmental variables. Among the 206 taxa observed, 33 species were dominant. Canonical Correspondence Analysis indicated that incident light, lakes depth, surface area and water conductivity were of significant importance in controlling the variation in the structure of the plankton assemblages. The resulted models from averaging regression and cross-calibration predicted the main environmental parameters and allowed the selection of phyto and zooplankton species as potential biological indicators. Weighted averaging regression and cross-calibration generated useful models for predicting the main four investigated environmental parameters, which contribute to the selection of phyto- and zooplankton species as potential biological indicators.

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We introduce an accepting splicing system based on a type of splicing, multiple splicing, which has never considered so far for accepting systems. This type of splicing differs from the usual operation in that several (not necessarily distinct) rules can be applied simultaneously to the same string. We first consider accepting multiple splicing systems where the number of splicing sites is a predefined constant. We prove that this model is computationally complete, if the constant is 2, by simulating a 2-tag system. Moreover, we show that the simulation is time-complexity preserving, and discuss also the descriptional complexity of the accepting splicing system given by our construction. We then consider the accepting multiple splicing systems where the number of sites has either an upper bound or a lower bound. The computational power of these systems is also investigated. We finally discuss some open problems. (C) 2022 The Author(s). Published by Elsevier B.V. on behalf of King Saud University.

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The current paper estimated the physico-chemical properties of water in the Danube Delta (Romania), based on Sentinel 2 remote sensing data. Eleven sites from the Danube Delta were sampled in spring and autumn for three years (2018-2020) and 21 water physico-chemical parameters were measured in laboratory. Several families of machine learning algorithms, translated into hundreds of models with different parameterizations for each machine learning algorithm, based on remote sensing data input from Sentinel 2 spectral bands, were employed to find the best models that predicted the values measured in laboratory. This was a novel approach, reflected in the types of selected models that minimised the values of performance metrics for the tested parameters. For alkalinity, calcium, chloride, carbon dioxide, hardness, potassium, sodium, ammonium, dissolved oxygen, sulphates, and suspended matter the results were promising, with an overall percentage bias of the estimates of +/- 10% from the observed values. For copper, magnesium, nitrites, nitrates, turbidity and zinc the estimates were fairly accurate, with percentage biases in the interval +/- 10% - 20%, whereas for detergents, led, and phosphates the percentage bias was higher than 20%. Overall, the results of the current study showed fairly good estimates between remote sensing based estimates and laboratory measured values for most water physico-chemical parameters.

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The toxic effects of two commonly used glucocorticoids, the dexamethasone and prednisolone, on meiobenthic nematodes were assessed in a laboratory experiment for 30 days. Nine treatments were employed, comprised of two single and mixed concentrations of dexamethasone and prednisolone (i.e., 0.14 and 1.4 mu g center dot L-1). The exposure to both glucocorticoids showed significant effects on the abundance and taxonomic diversity of nematodes. Such changes were mainly induced by the decrease in the abundance of the species Microlaimus honestus, considered to be sensitive to prednisolone and by the increase in Enoplolaimus longicaudatus abundance, which can be considered tolerant. The exposure to these glucocorticoids also led to a decrease in 2A feeding groups, 2-4 mm body-size interval, and c-p3 life history type in most treatments, with type of life history and shape of amphids as the most relevant functional traits impacted by these two glucocorticoids. The results could also be explained by the potential antagonism between these two pharmaceuticals.

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Considering the broad impact of applied research on the economy, RDI funding evaluations are required both in terms of the number of allocated resources and the management of these resources. RDI efficacy depends on human resources productivity and the financing instruments established through national priorities. This paper offers an analysis of the RDI investments in Romania allocated through the Competitiveness Operational Programme 2014-2020, covering the European Structural and Investment Funds, namely the European regional development fund. The analysis of the funded projects highlighted the common trends among the beneficiaries of RDI projects, their options in managing resources in relation to the eligibility of costs, and their national distribution between the seven development regions of Romania. The amount of funding was discussed in terms of the smart specialization domains established by the national strategy. The conclusions of the study, correlated with the objectives set by the SNCDI 2014-2020, are relevant for the management of the future funding instruments allocated to RDI by the ERDF in the period 2021-2027.

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Since 2021, the National Evaluation exam in Romania (the exam aimed to assess 14- to 15-year-old students' knowledge at the end of lower secondary education and just before high school) has presented a novel examination structure that resembles PISA tests. The current investigation analyses the 2021 National Evaluation exam results compared to the results obtained in the previous two years (2019-2020) as an evaluation of upper education institutions' effectiveness in Romania. The results put forward the same conclusions as proposed by extant literature on Bucharest high schools. Even though the educational institutions show apparent progress and great adaptability to change, a more in-depth analysis reveals great inequality between educational institutions. As in the case of Bucharest, nationally there are only a small number of top-performing high schools in Romania, with the majority of high schools ranking in the lowest category as conceptualised in the study. The current investigation puts together a novel methodology for classification based on the main instruments proposed in literature: a letter grade classification and Turner's f-index. The results and the methodological proposal are especially relevant considering the latest PISA (2018) conclusions on Romania characterising the national educational system as underperforming.

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Membrane computing or P-systems is a subfield of natural computing, which models living systems with mathematical tools. In classical membrane-computing, cells or organs are surrounded by a simple membrane and computational events take place in either side of the membrane. We have developed a new conceptual tool to better fit P-systems to higher-order organisms, which rely on the actual membrane structure of the cell and on the biochemical reactions (rules), which take place on the membrane of different organs in our body. To demonstrate the power of this new concept, we modeled the process of maintaining normoglycemia in healthy individuals as well as in type-I and type-II diabetes patients. The main challenge was to prioritize the insulin-producing P-cells over other organs, i.e., once glucose has entered the body, it must first enter specifically into pancreatic P-cells in order to release the hormone Insulin. However, using classical membrane computing, we could not implement this hierarchy. Therefore, we chose to utilize the membrane actual physiology and add its properties to the current definitions of membrane computing. In particular, we use enzymes and protein-transporters (as well as channels) to apply algebraic rules. In addition, we show that the defined systems are universal, by simulating register machines. Thus, allowing deterministic manner operations in a non-deterministic system by giving membrane-specific rules. To our gratification, we succeeded to adequately describe the process of glucose homeostasis in health and disease while bringing the science of membrane-computing closer to the natural world. (C) 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

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The micronutrient application in agriculture takes place through soil application, foliar spraying or added as seed treatments. The latter method, the nutri-priming, is an appealing option due to the easiness in handling it, environment-friendly, cost effectiveness and efficient against multiple environmental stres-sors. To assess the feasibility of Zn-priming technique on seeds germination, two experiments were con-ducted and assessed the efficiency on the growth rate, yield and biofortification on the forage maize (Zea mays L.). The first laboratory experiment assessed the effect of Zn-priming for three-time exposures (i.e., 8, 16 and 24 h) on germination parameters. The second experiment was done in a greenhouse, by using the 10 seeds obtained from 24 h priming. Five seed pretreatments were studied (0, 0.1, 0.5,1 and 11 2 % of zinc sulfate heptahydrate (ZnSO4.7H2O)) compared to the recommended dose (5 ppm of Zn at 5-9 leaf stage) provided by soil application. The obtained results revealed that all seed priming, including hydro-priming, improve seed germination performance. Zn-priming increased the grain yield and helped to enrich the seeds in this element, especially seedlings treated with 0.5 % Zn sulphate for 24 h leading to an increase in yield by 47 % and in Zn content by 15 %. The comparison of the results from both tech-niques showed that Zn-priming could be was very effective than the traditional direct application in soil.(c) 2022 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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Control theory has seen recently impactful applications in network science, especially in connections with applications in network medicine. A key topic of research is that of finding minimal external interventions that offer control over the dynamics of a given network, a problem known as network controllability. We propose in this article a new solution for this problem based on genetic algorithms. We tailor our solution for applications in computational drug repurposing, seeking to maximize its use of FDA-approved drug targets in a given disease-specific protein-protein interaction network. We demonstrate our algorithm on several cancer networks and on several random networks with their edges distributed according to the Erdos-Renyi, the Scale-Free, and the Small World properties. Overall, we show that our new algorithm is more efficient in identifying relevant drug targets in a disease network, advancing the computational solutions needed for new therapeutic and drug repurposing approaches.

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This study was conducted to assess the impact and efficiency of the bioaugmentation as a bioremediation technique in annoying effects of a polycyclic aromatic hydrocarbon (phenanthrene) on a community of free-living nematodes from Bizerte bay (Tunisia). For this purpose, closed microcosms were exposed to three doses of phananthrene (0.1 mu g kg(-1), 1 mu g kg(-1) and 10 mu g kg(-1)), in combination or not with a strain of Shewanella oneidensis. After 40 days of the exposure, results were obtained at the numerical, taxonomic and feeding levels. The results of univariate analyses revealed significant decreases in most univariate indices for phenanthrene treated communities compared to controls, with a discernible increase in the proportion of epistrate feeders. After bioaugmentation, similar patterns were observed for univariate and multivariate analyses, with the exception of the highest treatment, which showed no difference from the controls. The results obtained showed that the bioaugmentation with Shewanellea oneidensis was highly effective in reducing the negative impact of the highest dose of phenanthrene (10 mu g kg(-1) Dry Weight) tested on meiobenthic nematodes. Furthermore, a combination of Shewanellea oneidensis and four omnivore-carnivore nematode taxa could be suggested as an effective method in the bioremediation of phenanthrene-contaminated sediment.

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In a recent study, Spencer et al. 2021, we have proposed a computational modeling framework for DNA multi strand dynamics implemented using the agent- and rule-based modeling methodology. While this modeling methodology allows for compact representations for systems with large numbers of different species and complexes, such as the case of self-assembly systems, one of its main drawbacks concerns its scalability. Since each agent is individually represented and modeled in the system, the framework becomes slow when dealing with tens- and hundreds of thousands of individual components. In this study we introduce a method to parallelize the computational modeling process by distributing it over several CPU's. We show that such multi-thread models remain equivalent to their sequential counterpart, while the speedup of the computational process can reach even a one-fold increase.

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The effects of microplastics and sorbed polycyclic aromatic hydrocarbons at community levels were rarely assessed in laboratory experiments, despite their obvious advantage in reflecting better the natural conditions compared to traditionally single species-focused toxicological experiments. In the current study, the multifaceted effects of polyvinyl chloride and chrysene, acting alone or combined, on general marine meiobenthos, but with a special focus on free-living marine nematode communities were tested in a laboratory experiment carried in microcosms. The meiobenthos was exposed to two polyvinyl chloride (5 and 10 mg.kg(-1) Dry Weight 'DW') and chrysene (37.5 and 75 ng.g(- 1) DW) concentrations, respectively, as well as to a mixture of both compounds, for 30 days. The results highlighted a significant decrease in the abundance of all meiobenthic generic groups, including nematodes, directly with increasing dosages of these compounds when added alone. The addition of chrysene adheres to microplastics, making the sediment matrix glueyer, hence inducing greater mortality among generic meiobenthic groups. Moreover, the nematofauna went through a strong restructuring phase following the exposure to both compounds when added alone, leading to the disappearance of sensitive nematodes and their replacement with tolerant taxa. However, the similarity in nematofauna composition between control and polyvinyl chloride and chrysene mixtures suggests that the toxicity of the latter could be attenuated by its physical bonding to the former pollutant. Other changes in the functional traits within the nematode communities were a decline in the fertility of females and an increase of the pharyngeal pumping power following exposure to both pollutants for the dominant species. The latter results were also supported by additional toxicokinetics analyses and in silico modeling.

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An open experimental setup was established in order to explore the toxic effects of the antidepressant paroxetine on meiobenthic nematodes. Three types of microcosms made from polyvinyl chloride tubes, each comprising two sediments compartments (upper and lower), were used in a laboratory experiment for 15 days. The experimental setup targeted the migratory behaviour of the nematofauna from the above compartments, which were exposed to paroxetine (0.4 and 40 mu g.l(-1)), towards below compartments. The univariate indices significantly decrease in the contaminated compartments compared to controls. Multivariate analyses revealed also significant taxonomic dissimilarities between contaminated and uncontaminated compartments. Furthermore, SIMPER functional outcomes highlighted a significant decrease in 2A feeding groups, 'co' tail shape, 1-2 mm interval length, 'cr' amphid shape, and c-p2 life history in contaminated compartments. Computational approach showed that paroxetine bound GLD-3 and SDP with high affinities, which together with molecular interactions and toxicokinetics satisfactorily explain the experimental results.

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Constructing a large biological model is a difficult, error-prone process. Small errors in writing a part of the model cascade to the system level and their sources are difficult to trace back. In this paper we extend a recent approach based on Event-B, a state-based formal method with refinement as its central ingredient, allowing us to validate for model consistency step-by-step in an automated way. We demonstrate this approach on a model of the heat shock response in eukaryotes and its scalability on a model of the ErbB signaling pathway. All consistency properties of the model were proved automatically with computer support.

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To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein-protein interaction (PPI) networks integrating the top-ranked host factors, the drug target proteins and directed PPI data. We analyzed the networks to identify drug targets and combinations thereof that offer efficient control over the host factors. We validated our findings against clinical studies data and bioinformatics studies. Our method offers a new insight into the molecular details of the disease and into potentially new therapy targets for it. Our approach for drug repurposing is significant beyond COVID-19 and may be applied also to other diseases.

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An experiment conducted with 'open microcosm' made by connected sedimentary compartments with different qualities was for 30 days to evaluate the migratory behaviour of nematodes as induced by exposure to pyrene. The nematofauna was collected along with sediment from a reference site in Bizerte lagoon. Following one week acclimatization period, the populated sediments were topped with azoic sediments, with a pyrene concentration of 150 mu g kg-1. The concentration of pyrene from sediments was measured on a weekly basis. A stable status of nematode assemblages was reached between the upper and lower compartments in each microcosm, whatever the treatment type. An upward exploratory phase was observed during the first two weeks within the assemblages, possibly induced by the repellent chemodetection of pyrene. This observation was confirmed by the toxicokinetic properties and molecular interactions of pyrene with the germ-line development Protein 3 and sexdetermining protein of Caenorhabditis elegans as nematode model.

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A microcosm experiment was carried out to determine how benzo(a)pyrene (BaP) may affect marine meiofauna community, with a main emphasis on nematode structure and functional traits. Three increasing concentrations of BaP (i.e. 100, 200 and 300 ng/l, respectively) were used for 30 days. The results revealed a gradual decrease in the abundance of all meiobenthic groups (i.e. nematodes, copepods, amphipods, polychaetes and oligochaetes), except for isopods. Starting at concentrations of 200 and 300 ng/l BaP, respectively, significant changes were observed at community level. At taxonomic level, the nematode communities were dominated at the start of the experiment and also after being exposed or not to BaP by Odontophora villoti, explicable through its high ecologic ubiquity and the presence of well-developed chemosensory organs (i.e. amphids), which potentially increased the avoidance reaction following exposure to this hydrocarbon. Moreover, changes in the activity of several biochemical biomarkers (i.e. catalase 'CAT', gluthatione S-transferase 'GST', and ethoxyresorufin-O-deethylase 'EROD') were observed in the nematode species Oncholaimus campylocercoides, paralleled by significant decreases in CAT activity for non-gravid females compared to controls at concentrations of 25 ng/l BaP and associated with significant increase in GST and EROD activities for both types of individuals.

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A microcosm bioassay was designed to assess the efficacy of wastewater treatment methods used in sewage plants. The taxonomic and feeding characteristics of a meiobenthic nematode assemblage from Ghar El Melh lagoon (Tunisia) were used to achieve this goal. Nematode assemblages were exposed for 30 days to untreated wastewater (UW) obtained from the sewage treatment plant of Sidi Ahmed (Tunisia) and three mixtures with treated wastewater (TW33 = 33%, TW66 = 66%, and TW100 = 100%). Concerning the nematode abundance, the exposure to either treated wastewater (TW33-100) or untreated wastewater (UW) had no significant effect. In contrast, Shannon-Wiener index and Pielou's Evenness were clearly reduced by contamination with both types of wastewater, with a more pronounced negative impact prior to treatment in the sewage plant. The multivariate analyzes revealed a change in the taxonomic composition of the nematofauna in response to the contamination by untreated or treated wastewater. The relative abundances of species in wastewater replicates compared to controls reflected this taxonomic restructuring. Finally, Ascolaimus elongatus, Terschellingia communis, and Kraspedonema octogoniata were less represented in all experimentally treated units and could be considered as 'sensitive taxa to wastewater'. While, Paracomesoma dubium, appears to be a 'tolerant and/or opportunistic' species, showing increased relative abundances under all wastewater treatments.

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We discuss in this chapter several network modelling methods and their applicability to precision medicine. We review several network centrality methods (degree centrality, closeness centrality, eccentricity centrality, betweenness centrality, and eigenvector-based prestige) and two systems controllability methods (minimum dominating sets and network structural controllability). We demonstrate their applicability to precision medicine on three multiple myeloma patient disease networks. Each network consists of protein-protein interactions (PPI) built around a specific patient's mutated genes, around the targets of the drugs used in the standard of care in multiple myeloma, and around multiple myeloma-specific essential genes. For each network, we demonstrate how the network methods we discuss can be used to identify personalized, targeted drug combinations uniquely suited to that patient. © 2020 John Wiley & Sons, Inc. All rights reserved.

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Impact on aquatic ecosystems from intensive agriculture can be mitigated through a variety of structural and management conservation practices. This article provides an overview of the main Best Management Practices (BMP) for reducing direct or indirect detrimental impact from agriculture on inland waters’ quality and ecological status. The BMP's have been shown to be more efficient compared to conventional ones and comprise a set of recommendations that should be considered carefully by environmental scientists, stakeholders, farmers and land-owners alike. © 2022 Elsevier Inc. All rights reserved

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The present study focused on the ecological preferences of benthic macroinvertebrates regarding water flow and sediment characteristics in two submerged dunes from Danube Delta (Romania). Three hydraulic microhabitats, the stoss, trough and crest areas were sampled, along with measurements of water hydraulics, hydrology, sediment grain-size, and organic content. The results showed that the slope angles between stoss-crest and crest-trough areas are crucial in modulating local flows, sediment structure, organic content, macroinvertebrate communities, and taxonomic richness and density. As such, the stoss microhabitats are considered zones with the highest turbulence, hence driving low taxonomic richness and density compared to crest and trough microhabitats. When local environmental conditions in trough microhabitats allow the accretion of fine and organically enriched sediments, the development of maximum density for certain macroinvertebrates groups is reached. However, the benthic assemblages did not show clear preferences for certain microhabitats, suggesting ubiquitous ecologic traits, crucial for the successful colonisation of dynamic habitats, such as the submerged dunes in large rivers. The results of this study offer a better understanding on the abiotic factors driving the spatial preferences, density, and diversity of benthic macroinvertebrates in these understudied hydrogeomorphological units from large rivers. © 2022, Asociacion Iberica de Limnologia. All rights reserved.

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In Northern Tunisia, seasonal streams, called wadi, are characterized by extreme hydrological and thermal conditions. These freshwater systems have very particular features as a result of their strong irregularity of flow due to limited precipitation runoff regime, leading to strong seasonal hydrologic fluctuations. The current study focused on the spatio-temporal distribution of chironomids in 28 sampling sites spread across the Northern Tunisia. By emplying PERMANOVA, the results indicated a significant spatio-temporal variation along various environmental gradients. The main abiotic factors responsible for noted differences in the spatial distribution of chironomids in wadi were the conductivity and temperature, closely followed by altitude, pH, salinity, talweg slope and dissolved oxygen, identified as such by employing distance-based linear models’ procedure. The Distance-based redundancy analysis ordination showed two main groups: the first clustered the Bizerte sites, which were characterized by high water conductivity, sodium concentration and salinity. The second main group comprised sites from the Tell zone and was characterized by low temperatures, neutral pH, low conductivity and nutrients content. The subfamily TANYPODIINAE (e.g., Prochladius sp., Prochladius choerus (Meigen, 1804) and Macropelopia sp.) was the dominant group at Tell zone, whereas species such as Diamesa starmachi (Kownacki et Kownacha, 1970) and Potthastia gaedii (Meigen, 1838) were found only in Tell Wadis. In contrast, chironomid species such as Diamesa starmachi (Kownacki et Kownacha, 1970), Potthastia gaedii (Meigen, 1838), Procladius choreus (Meigen, 1804) were specific for Tell Mountain. Cap Bon wadis region was dominated by genus Cladotanytarsus sp. The results of this survey liked the taxonomic composition of chironomid assemblages to the variation of hydromorphological and physic-chemical gradients across the northern Tunisia wadis. © 2022, Instituto Internacional de Ecologia. All rights reserved.

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We partially answer an open question on small computational devices: how many neurons are needed by a spiking neural P system with communication on request (SNQ P Systems) to achieve universality? We provide an answer in the case when the SNQ P System uses at least 5 types of spikes. Our work shows that 6 neurons are enough to achieve universality as number generators, number accepters and function computation device. We achieve this result by using only two neuron to simulate the instructions labels and one type of spike to emulate a register. (C) 2020 Elsevier B.V. All rights reserved.

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The dynamics of nucleic-acids dynamical systems is intrinsically based on local interaction. The major acting mechanisms are that of Watson-Crick complementarity on one-hand, generating binding events, and thermal energy on the other, generating random motion and un-binding. It is thus predictable that such systems can be successfully captured by computational modeling paradigms based on local interactions, such as the rule-based modeling methodology. In this research we introduce the Virtual DNA Lab (VDNA-Lab) a simulation tool which provides an easy to use graphical interface for creating, running and visualizing synthetic simulations for DNA assembly systems, such as assembly of DNA nanostructures, strand displacement cascades systems, DNA-tile assembly etc. It employs a custom designed model, implemented in the BioNetGen Language (BNGL) formalism, to capture the DNA dynamics, as well as the NFsim computational modeling engine to run simulations and generate outputs. These outputs can be visualized using the VDNA-Lab's own visualization tool, which allows also for further analysis and filtering. The software is freely available at https://github.com/Frankie-Spencer/virtual dna lab.

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Networks of splicing processors (NSP for short) embody a subcategory among the new computational models inspired by natural phenomena with theoretical potential to handle unsolvable problems efficiently. Current literature considers three variants in the context of networks managed by random-context filters. Despite the divergences on system complexity and control degree over the filters, the three variants were proved to hold the same computational power through the simulations of two computationally complete systems: Turing machines and 2-tag systems. However, the conversion between the three models by means of a Turing machine is unattainable because of the huge computational costs incurred. This research paper addresses this issue with the proposal of direct and efficient simulations between the aforementioned paradigms. The information about the nodes and edges (i.e., splicing rules, random-context filters, and connections between nodes) composing any network of splicing processors belonging to one of the three categories is used to design equivalent networks working under the other two models. We demonstrate that these new networks are able to replicate any computational step performed by the original network in a constant number of computational steps and, consequently, we prove that any outcome achieved by the original architecture can be accomplished by the constructed architectures without worsening the time complexity.

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In this paper, we propose direct simulations between a given network of evolutionary processors with an arbitrary topology of the underlying graph and a network of evolutionary processors with underlying graphs-that is, a complete graph, a star graph and a grid graph, respectively. All of these simulations are time complexity preserving-namely, each computational step in the given network is simulated by a constant number of computational steps in the constructed network. These results might be used to efficiently convert a solution of a problem based on networks of evolutionary processors provided that the underlying graph of the solution is not desired.

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To avoid the transformation of the dependent variable, which introduces bias when back-transformed, complex nonlinear forest models have the parameters estimated with heuristic techniques, which can supply erroneous values. The solution for accurate nonlinear models provided by Strimbu et al. (Ecosphere 8:e01945, 2017) for 11 functions (i.e., power, trigonometric, and hyperbolic) is not based on heuristics but could contain a Taylor series expansion. Therefore, the objectives of the present study are to present the unbiased estimates for variance following the transformation of the predicted variable and to identify an expansion of the Taylor series that does not induce numerical bias for mean and variance. We proved that the Taylor series expansion present in the unbiased expectation of mean and variance depends on the variance. We illustrated the new modeling approach on two problems, one at the ecosystem level, namely site productivity, and one at individual tree level, namely stem taper. The two models are unbiased, more parsimonious, and more precise than the existing less parsimonious models. This study focuses on research methods, which could be applied in similar studies of other species, ecosystem, as well as in behavioral sciences and econometrics.

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A microcosm experiment was carried out to provide a deeper insight into the toxic mechanisms exerted by two lipid regulator agents, as well as their interactions with the polyvinyl chloride microplastic on marine meiofauna. Two concentrations of Atorvastatin A and of Simvastatin S, (i.e., 0.6 mg.kg(-1) and 6 mg.kg(-1)), as well as a single dosage of polyvinyl chloride microplastics P at 20 mg.kg(-1), separately and their combined mixtures (AP and SP) were used on coastline dwelling marine meiofauna, with a main focus on nematodes. The results showed a significant reduction in meiofauna abundance in treatments compared to control. SIMPER analysis highlighted a significant decrease in the abundance of epigrowth feeders (2A), which possess conical (co) tails, and indistinct (id) amphideal foveas compared to control microcosms, reflected mainly in the decrease in abundance of the species Prochromadorella longicaudata. Furthermore, the contamination with microplastic affected only the omnivores-carnivores guild. Another finding of the current experiment is that the mixtures of microplastic with drugs lead to synergic interactions that increased their toxic effects on marine nematode communities.

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The current work investigated the ecotoxicological effects induced by Titanium Dioxide (TiO2) nanoparticles (NPs), used at three different concentrations (C1 = 10 mu g center dot L-1, C2 = 100 mu g center dot L-1 and C3 = 1000 mu g center dot L-1) in a laboratory experiment, on the freshwater mussel Unio ravoisieri. Biochemical analyses of gills and digestive glands revealed a stress-related disruption of the antioxidant system. The catalase activity and the rates of malonedialdehyde and hydrogen peroxide production were significantly higher in both organs following the exposure to TiO2 NPs and was concentration-dependent. In addition, based on the observed changes in acetylcholinesterase activity, it can be concluded that the disturbance threshold for the cholinergic system was less than 1 mg center dot L-1 of TiO2. Overall, the results suggest that the mussel Unio ravoisieri could be used as a sentinel species in monitoring surveys assessing the environmental impact of metallic nanoparticles in freshwater systems.

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Nowadays, polypropylene is one of the most common polymers used in the food packaging industry due to its good functionality and relatively low cost. Nevertheless, usage of plastic disposable packaging can be a generator of plastic pollution having negative environmental effects. A feasible solution for this issue would be to recycle. The polypropylene samples were submitted to two processes, forced contamination, and recycling, and they were analyzed by solid-phase microextraction gas chromatograph-olfactometry-mass spectrometry. 45 different volatile compounds were identified and 9 of them presented distinct odoriferous activities. Among them, two important markers were detected: diethyl phthalate (probably coming from the catalyst of PP polymerization, intentionally added substance (IAS)), and glycerine (a marker of non-intentionally added substances (NIAS)).

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Current advances in computational modelling and simulation have led to the inclusion of computer scientists as partners in the process of engineering of new nanomaterials and nanodevices. This trend is now, more than ever, visible in the field of deoxyribonucleic acid (DNA)-based nanotechnology, as DNA's intrinsic principle of self-assembly has been proven to be highly algorithmic and programmable. As a raw material, DNA is a rather unremarkable fabric. However, as a way to achieve patterns, dynamic behavior, or nano-shape reconstruction, DNA has been proven to be one of the most functional nanomaterials. It would thus be of great potential to pair up DNA's highly functional assembly characteristics with the mechanic properties of other well-known bio-nanomaterials, such as graphene, cellulos, or fibroin. In the current study, we perform projections regarding the structural properties of a fibril mesh (or filter) for which assembly would be guided by the controlled aggregation of DNA scaffold subunits. The formation of such a 2D fibril mesh structure is ensured by the mechanistic assembly properties borrowed from the DNA assembly apparatus. For generating inexpensive pre-experimental assessments regarding the efficiency of various assembly strategies, we introduced in this study a computational model for the simulation of fibril mesh assembly dynamical systems. Our approach was based on providing solutions towards two main circumstances. First, we created a functional computational model that is restrictive enough to be able to numerically simulate the controlled aggregation of up to 1000s of elementary fibril elements yet rich enough to provide actionable insides on the structural characteristics for the generated assembly. Second, we used the provided numerical model in order to generate projections regarding effective ways of manipulating one of the the key structural properties of such generated filters, namely the average size of the openings (gaps) within these meshes, also known as the filter's aperture. This work is a continuation of Amarioarei et al., 2018, where a preliminary version of this research was discussed.

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This paper is part of the investigation of some operations on words and languages with motivations coming from DNA biochemistry, namely three variants of hairpin completion and three variants of hairpin reduction. Since not all the hairpin completions or reductions of semilinear languages remain semilinear, we study sufficient conditions for semilinear languages to preserve their semilinearity property after applying the non-iterated hairpin completion or hairpin reduction. A similar approach is then applied to the iterated variants of these operations. Along these lines, we define the hairpin reduction root of a language and show that the hairpin reduction root of a semilinear language is not necessarily semilinear except the universal language. A few open problems are finally discussed.

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Subterranean streams represent unique heterotrophic ecosystems, usually supported by organic matter imported from the surface. Traditionally, the biological communities from subterranean streams were characterized as simple associations, with low diversity and species abundance, comprising mostly aquatic invertebrates connected by few trophic links compared with those of the surface. However, these features have not yet been described in the wider context of fluxes of energy and nutrients through food webs along a gradual switch from autotrophy (dominated by photosynthesis) towards heterotrophy (dominated by detritus) following the surface-subterranean continuum. Combining the most recent predictions of Ecological Stoichiometry and the Metabolic Theory of Ecology, this article provides a theoretical framework aiming to explain the patterns observed along the surface-subterranean continuum in streams. It is predicted that the main factors constraining the structure and functioning of communities and food webs are the decline in the quantity and diversity of basal resources along this gradient, along with nutrients availability in water that affects food quality. With increasing availability of dissolved nutrients in water, sinking-cave streams are hypothesized to fluctuate between being N and/ or P co-limited to C-limited. Combined, the quantity, quality, and diversity of basal resources regulate subterranean aquatic communities through bottom-up mechanisms, reflected in a decreased flux of macronutrients through food webs. The consequences of these bottom-up effects are decreased abundance, biomass, secondary production, consumption rate, and mean body size of communities, together with potential increases in the elemental imbalance for macronutrients, omnivory, trophic position, and niche width and overlap among aquatic consumers along the surface-subterranean continuum. The bottom-up effects induce changes in the topology of stream food webs, which become shorter, with lower trophic diversity at the base of the network, but increased connectance along this environmental gradient.

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In the current study the response of aquatic macroinvertebrate communities to multiple anthropogenic stressors in a typical lowland river that crosses pristine sectors situated toward headwaters, as well as densely populated urban areas was assessed. We wished to develop an effective bioassay procedure for assessing water and sediment quality in lotic ecosystems from Romania with the aid of macroinvertebrate organisms correlated with physicochemical parameters and pollutants in both dissolved fractions and material bonded to sediment. A fast scanning approach of the river, from springs to the mouth, was employed. We found significant changes in physicochemical parameters along a longitudinal gradient, the highest values being registered within the urban area and heavily agriculturally developed areas. The macroinvertebrates showed affinities for certain abiotic factors, emphasising their potential use for future studies as reliable ecological indicators, shaped by a synergic combination of urban effects and magnitude of type of land use.

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Many experiments cannot feasibly be conducted as factorials. Simulations using synthetically generated data are viable alternatives to such factorial experiments. The main objective of the present research is to develop a methodology and platform to synthetically generate spatially explicit forest ecosystems represented by points with a predefined spatial pattern. Using algorithms with polynomial complexity and parameters that control the number of clusters, the degree of clusterization, and the proportion of nonrandom trees, we show that spatially explicit forest ecosystems can be generated time efficiently, which enables large factorial simulations. The proposed method was tested on 1200 synthetically generated forest stands, each of 25 ha, using 10 spatial indices: Clark-Evans aggregation index; Ripley's K; Besag's L; Morisita's dispersion index; Greig-Smith index; the size dominance index of Hui; index of nonrandomness of Pielou; directional index and mean directional index of Corral-Rivas; and size differentiation index of Von Gadow. The size of individual trees was randomly generated aiming at variograms such as real forests. We obtained forest stands with the expected spatial arrangement and distribution of sizes in less than 1 h. To ensure replicability of the study, we have provided free, fully functional software that executes the stated tasks.

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The current study investigated the exposure of the Mediterranean mussel (Mytilus galloprovincialis) to gold nanoparticles decorated zinc oxide (Au-ZnO NPs) and phosphonate [Diethyl (3-cyano-1-hydroxy1-phenyl-2-methylpropyl)] phosphate (PC). The mussels were exposed to concentrations of 50 and 100 mg L-1 of both compounds alone, as well as to a mixture of both pollutants (i.e. Mix). The singular and the combined effect of each pollutant was investigated by measuring the concentration of various metals (i.e., Cu, Fe, Mn, Zn and Au) in the the digestive glands and gills of mussels, their filtration capacity (FC), respiration rate (RR) and the response of oxidative biomarkers, respectively, following 14 days of exposure. The concentrations of Cu, Fe, Mn, Zn and Au increased directly with Au-ZnO NPs in mussel tissues, but significantly only for Zn. In contrast, the mixture of Au-ZnO100 NPs and PC100 did not induce any significant increase in the content of metals in digetsve glands and gills, suggesting antagonistic interactions between contaminants. In addition, FC and RR levels decreased following exposure to AuZnO100 NPs and PC100 treatments and no significant alterations were observed after the exposure to 50 mg.L-1 of both contaminants and Mix. Hydrogen peroxide (H2O2) level, GSH/GSSG ratio, superoxide dismutase (SOD), catalase (CAT) and acetylcholinesterase (AChE) activities showed significant changes following the exposure to both Au-ZnO NPs and PC, in the gills and the digestive glands of the mussel. However, no significant modifications were observed in both organs following the exposure to Mix. The current study advances the understanding of the toxicity of NPs and phosphonates on M. galloprovincialis and sets the path for future ecotoxicological studies regarding the synergic effects of these substances on marine species. Moreover, the current experiment suggests that the oxidative stress and the neurotoxic pathways are responsive following the exposure of marine invertebrates to both nanoparticles and phosphonates, with potential antagonist interactions of these substances on the physiology of targeted species. (c) 2021 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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Motivation: There is an increasing amount of data coming from genome-wide studies identifying disease-specific survivability-essential proteins and host factors critical to a cell becoming infected. Targeting such proteins has a strong potential for targeted, precision therapies. Typically however, too few of them are drug targetable. An alternative approach is to influence them through drug targetable proteins upstream of them. Structural target network controllability is a suitable solution to this problem. It aims to discover suitable source nodes (e.g. drug targetable proteins) in a directed interaction network that can control (through a suitable set of input functions) a desired set of targets. Results: We introduce NetControl4BioMed, a free open-source web-based application that allows users to generate or upload directed protein-protein interaction networks and to perform target structural network controllability analyses on them. The analyses can be customized to focus the search on drug targetable source nodes, thus providing drug therapeutic suggestions. The application integrates protein data from HGNC, Ensemble, UniProt, NCBI and InnateDB, directed interaction data from InnateDB, Omnipath and SIGNOR, cell-line data from COLT and DepMap, and drug-target data from DrugBank.

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Subterranean streams represent unique heterotrophic ecosystems, usually supported by organic matter imported from the surface. Traditionally, the biological communities from subterranean streams were characterized as simple associations, with low diversity and species abundance, comprising mostly aquatic invertebrates connected by few trophic links compared with those of the surface. However, these features have not yet been described in the wider context of fluxes of energy and nutrients through food webs along a gradual switch from autotrophy (dominated by photosynthesis) towards heterotrophy (dominated by detritus) following the surface–subterranean continuum. Combining the most recent predictions of Ecological Stoichiometry and the Metabolic Theory of Ecology, this article provides a theoretical framework aiming to explain the patterns observed along the surface–subterranean continuum in streams. It is predicted that the main factors constraining the structure and functioning of communities and food webs are the decline in the quantity and diversity of basal resources along this gradient, along with nutrients availability in water that affects food quality. With increasing availability of dissolved nutrients in water, sinking-cave streams are hypothesized to fluctuate between being N and/ or P co-limited to C-limited. Combined, the quantity, quality, and diversity of basal resources regulate subterranean aquatic communities through bottom–up mechanisms, reflected in a decreased flux of macronutrients through food webs. The consequences of these bottom–up effects are decreased abundance, biomass, secondary production, consumption rate, and mean body size of communities, together with potential increases in the elemental imbalance for macronutrients, omnivory, trophic position, and niche width and overlap among aquatic consumers along the surface–subterranean continuum. The bottom–up effects induce changes in the topology of stream food webs, which become shorter, with lower trophic diversity at the base of the network, but increased connectance along this environmental gradient. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

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We define and investigate a complexity measure defined for extended finite automata over groups (EFA). Roughly, an EFA is a finite automaton augmented with a register storing an element of a group, initially the identity element. When a transition is performed, not only the state, but the register contents are updated. A word is accepted if, after reading completely the word, the automaton reached a final state, and the register returned to the identity element. The group memory complexity of an EFA over a group is a function from N to N which associates with each n the value 0, if there is no word of length n accepted by the automaton, or the minimal integer c such that for every word x of length n accepted by the automaton, there is a computation on x such that the number of transitions labeled by non-neutral element of the group used in that computation is at most c. We prove that a language is regular if and only if it is accepted by an EFA with a finite group memory complexity. In particular, any EFA over a group such that all its finitely generated subgroups are finite accepts a regular language. We then provide examples of EFA over some groups that accept non-regular languages and have a sublinear group memory complexity, namely a function in O(root n) or O(log n). There are non-regular languages such that any EFA over some group that accepts that language has a group memory complexity in Omega(n). (C) 2020 Elsevier Inc. All rights reserved.

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In a recent paper, using one of the algorithmic assembly formalisms of DNA nanotechnology, we proved that one tile can self-assemble length n structures and n x n squares, which are basic shapes in the study of DNA origami. This new result within a classic Tile Assembly Model (TAM) would not have been possible without the following programming topics: how can we simulate one-dimensional staged self-assembly using the signal-passing TAM, and how can we program staged self-assembly using the available software? We provide probabilistic approaches for investigating the assembly of tile-based one-dimensional structures. We obtain a probabilistic proof of Han's hook length formula in Enumerative Combinatorics. We identify algebraic and combinatorial structures underlying these algorithmic and information theory results.

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We investigate the spiking neural P systems with communication on request (SNQ P systems) that are devices in the area of neural like P systems abstracting the way in which neurons work and process information. Here we discuss the SNQ P systems using the rule application strategy as defined by Linqiang Pan and collaborators and we are able to improve their result of universality of such systems using two types of spikes. In the current work, we prove that only one type of spikes is sufficient for reaching the computational power of Turing Machines for these devices, bringing closer to implementation such a device. The result holds both in maximum parallel manner application of the rules as well as the maximum-sequentiality application of rules.

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Network controllability focuses on the concept of driving the dynamical system associated to a directed network of interactions from an arbitrary initial state to an arbitrary final state, through a well-chosen set of input functions applied in a minimal number of so-called input nodes. In earlier studies we and other groups demonstrated the potential of applying this concept in medicine. A directed network of interactions may be built around the main known drivers of the disease being studied, and then analysed to identify combinations of drug targets controlling survivability-essential genes in the network. This paper takes the next step and focuses on patient data. We demonstrate that comprehensive protein-protein interaction networks can be built around patient genetic data, and that network controllability can be used to identify possible personalised drug combinations. We discuss the algorithmic methods that can be used to construct and analyse these networks.

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We investigated the computational power of a new variant of network of splicing processors, which simplifies the general model such that filters remain associated with nodes but the input and output filters of every node coincide. This variant, callednetwork of uniform splicing processors, might be implemented more easily. Although the communication in the new variant seems less powerful, the new variant is sufficiently powerful to be computationally complete. Thus, nondeterministic Turing machines were simulated by networks of uniform splicing processors whose size depends linearly on the alphabet of the Turing machine. Furthermore, the simulation was time efficient. We argue that the network size can be decreased to a constant, namely six nodes. We further show that networks with only two nodes are able to simulate 2-tag systems. After these theoretical results, we discuss a possible software implementation of this model by proposing a conceptual architecture and describe all its components.

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The parameters of nonlinear forest models are commonly estimated with heuristic techniques, which can supply erroneous values. The use of heuristic algorithms is partially rooted in the avoidance of transformation of the dependent variable, which introduces bias when back-transformed to original units. Efforts were placed in computing the unbiased estimates for some of the power, trigonometric, and hyperbolic functions since only few transformations of the predicted variable have the corrections for bias estimated. The approach that supplies unbiased results when the dependent variable is transformed without heuristic algorithms, but based on a Taylor series expansion requires implementation details. Therefore, the objective of our study is to investigate the efficient expansion of the Taylor series that should be included in applications, such that numerical bias is not present. We found that five functions require more than five terms, whereas the arcsine, arccosine, and arctangent did not. Furthermore, the Taylor series expansion depends on the variance. We illustrated the results on two forest modeling problems, one at the stand level, namely site productivity, and one at individual tree level, namely taper. The models that are presented in the paper are unbiased, more parsimonious, and they have a RMSE comparable with existing less parsimonious models.

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How robust is a healthcare system? How does a patient navigate the system and what is the cost (e.g., number of medical services required or number of times the medical provider had to be changed to get access to the required medical services) incurred from the first symptoms to getting cured? How will it fare in the wake to a sudden epidemic or a disaster? How are all of these affected by administrative decisions such as allocating/diminishing resources in various areas or centralising services? These are the questions motivating our study on a formal prototype model for a healthcare system. We propose that a healthcare system can be understood as a distributed system with independent nodes (healthcare providers) computing according to their own resources and constraints, with tasks (patient needs) being allocated between the nodes. The questions about the healthcare system become in this context questions about resource availability and distribution between the nodes. We construct in this paper an Event-B model capturing the basic functionality of a simplified healthcare system: patients with different types of medical needs being allocated to suitable medical providers, and navigating between different providers for their turn for multi-step treatments.

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Controlling a dynamical system is the ability of changing its configuration arbitrarily through a suitable choice of inputs. It is a very well-studied concept in control theory, with wide-ranging applications in medicine, biology, social sciences and engineering. We introduce in this article the concept of controllability of reaction systems as the ability of transitioning between any two states through a suitable choice of context sequences. We show that the problem is PSPACE-hard. We also introduce a model of oncogenic signalling based on reaction systems and use it to illustrate the intricacies of the controllability of reaction systems. This study opens up a new line of research on the dynamic properties of reaction systems and it introduces a new, intricate biomedical model based on reaction systems.

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Since its introduction in the early 2000s, DNA origami had a big impact on the development of nanotechnology by gathering numerous applications. During this time, many tools were designed and used to generate arbitrary shapes capable of self-assembly which make this technique more approachable. In this paper, we have created the map of Romania at nanoscale dimensions by using a new open-source software - PERDIX. For this purpose, we used a scaffold strand with a length of 6959 nucleotides and 162 staple strands with a variable length ranging between 20 and 63 nucleotides. All the computational tools that were used in this experiment are open-source and user-friendly.

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Freshwater gammarids are known to colonise occasionally sinking-cave streams, providing contrasting morphological, life-history and ecophysiological adaptations compared to their surface conspecifics. In this study, a subterranean and a surface population of the species Gammarus balcanicus was surveyed for one year in a sinking-cave stream from the Western Carpathians (Romania). The results showed that the cave-dwelling population comprised individuals that were significantly larger compared to their surface conspecifics, had larger body-size at sexual maturity and that the females produced fewer, but larger eggs, compared to the population situated outside the cave. The trophic position and the omnivory were significantly higher for the cave-dwelling compared to surface population and the elemental imbalance for C:P molar ratios lower, but similar for C:N. However, the subterranean population did not present troglomorphic characters or longer lifespan as known for other cave-surface paired crustaceans. This, together with the rather extensive hydrological connection of the habitats, suggests active gene-flow between populations and similar response to seasonality for body-size distributions, indicating that the observed ecophysiological and life-history differences are rather the consequence of phenotypic plasticity than the result of genetic adaptation.

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Biological invasions represent a complex phenomenon driven by multiple factors. In this study, a real-time invasion process between a native (Pontastacus leptodactylus) and an invasive (Faxonius limosus) crayfish species was investigated in the Lower Danube (South-East Europe) through an interdisciplinary approach, by measuring various ecological, genetic, physiological and biometric endpoints. The results revealed that the prolonged competition in old invaded sites of the river (at least a decade) either drove the native species to extinction, or, unexpectedly, allowed its survival as highly fragmented populations. However, for the latter situation, several biological and ecological traits differed in the remnant populations: increased trophic position and elemental imbalance for two major macronutrients (C:N molar ratio), low growth, as strongly contracted trophic niche widths and low overlap degree with the invasive crayfish. The data suggest that the prolonged competition induced potential resource partitioning between species, potentially driving their coexistence, as the development of larger and heavier claws within the native males' population. On the contrary, in more recently invaded sectors of the Lower Danube (3 years), the trophic niche of the native species was significantly larger compared to old invaded sites and characterised by high level of niche overlap, indicating almost identical diet with the invasive crayfish, but characterised by the lowest trophic position compared to other invasion sectors. The genetic diversity of the native crayfish populations was strongly reduced in the invaded sectors of the river, but without signs of genetic bottleneck, which may be explained by a drift-mutational equilibrium reached as a consequence of diminishing population size. Our findings suggest strong coexistence potential in the future for both species in the Lower Danube.

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The one dimensional discrete scan statistic is considered over sequences of random variables generated by block factor dependence models. Viewed as a maximum of an 1-dependent stationary sequence, the scan statistics distribution is approximated with accuracy and sharp bounds are provided. The longest increasing run statistics is related to the scan statistics and its distribution is studied. The moving average process is a particular case of block factor and the distribution of the associated scan statistics is approximated. Numerical results are presented.

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We describe two new discrete symmetries of the inviscid Burgers (or Riemann–Hopf) equation ut+uux=0. We derived both of them using a local, formal approach of Hopf algebraic renormalization, a tool recently used in algorithmic computations. We prove that one of them is a Lie point transformation. Symmetries generate new exact solutions from the known solutions and provide useful frames of reference in the study of shock wave formation. © 2020 The Author(s)

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Freshwater gammarids are known to colonise occasionally sinking-cave streams, providing contrasting morphological, life-history and ecophysiological adaptations compared to their surface conspecifics. In this study, a subterranean and a surface population of the species Gammarus balcanicus was surveyed for one year in a sinking-cave stream from the Western Carpathians (Romania). The results showed that the cave-dwelling population comprised individuals that were significantly larger compared to their surface conspecifics, had larger body-size at sexual maturity and that the females produced fewer, but larger eggs, compared to the population situated outside the cave. The trophic position and the omnivory were significantly higher for the cave-dwelling compared to surface population and the elemental imbalance for C:P molar ratios lower, but similar for C:N. However, the subterranean population did not present troglomorphic characters or longer lifespan as known for other cave-surface paired crustaceans. This, together with the rather extensive hydrological connection of the habitats, suggests active gene-flow between populations and similar response to seasonality for body-size distributions, indicating that the observed ecophysiological and life-history differences are rather the consequence of phenotypic plasticity than the result of genetic adaptation. © 2020 Elsevier GmbH

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Biological invasions represent a complex phenomenon driven by multiple factors. In this study, a real-time invasion process between a native (Pontastacus leptodactylus) and an invasive (Faxonius limosus) crayfish species was investigated in the Lower Danube (South-East Europe) through an interdisciplinary approach, by measuring various ecological, genetic, physiological and biometric endpoints. The results revealed that the prolonged competition in old invaded sites of the river (at least a decade) either drove the native species to extinction, or, unexpectedly, allowed its survival as highly fragmented populations. However, for the latter situation, several biological and ecological traits differed in the remnant populations: increased trophic position and elemental imbalance for two major macronutrients (C:N molar ratio), low growth, as strongly contracted trophic niche widths and low overlap degree with the invasive crayfish. The data suggest that the prolonged competition induced potential resource partitioning between species, potentially driving their coexistence, as the development of larger and heavier claws within the native males’ population. On the contrary, in more recently invaded sectors of the Lower Danube (3 years), the trophic niche of the native species was significantly larger compared to old invaded sites and characterised by high level of niche overlap, indicating almost identical diet with the invasive crayfish, but characterised by the lowest trophic position compared to other invasion sectors. The genetic diversity of the native crayfish populations was strongly reduced in the invaded sectors of the river, but without signs of genetic bottleneck, which may be explained by a drift-mutational equilibrium reached as a consequence of diminishing population size. Our findings suggest strong coexistence potential in the future for both species in the Lower Danube. © 2019, Springer Nature Switzerland AG.

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This work is a survey of the most recent results regarding the computational power of the networks of bio-inspired processors whose communication is based on a new protocol called polarization. In the former models, the communication amongst processors is based on filters defined by some random-context conditions, namely the presence of some symbols and the absence of other symbols. In the new protocol discussed here, a polarization (negative, neutral, and positive) is associated with each node, while the polarization of data navigating through the network is computed in a dynamical way by means of a valuation function. Consequently, the protocol of communication amongst processors is naturally based on the compatibility between their polarization and the polarization of the data. We consider here three types of bio-inspired processors: evolutionary processors, splicing processors, and multiset processors. A quantitative generalization of polarization (evaluation sets) is also presented. We recall results regarding the computational power of these networks considered as accepting devices. Furthermore, a solution to an intractable problem, namely the 0 / 1 Knapsack problem, based on the networks of splicing processors with evaluation sets considered as problem solving devices, is also recalled. Finally, we discuss some open problems and possible directions for further research in this area.

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The construction of large scale biological models is a laborious task, which is often addressed by adopting iterative routines for model augmentation, adding certain details to an initial high level abstraction of the biological phenomenon of interest. Refitting a model at every step of its development is time consuming and computationally intensive. The concept of model refinement brings about an effective alternative by providing adequate parameter values that ensure the preservation of its quantitative fit at every refinement step. We demonstrate this approach by constructing the largest-ever refinement-based biomodel, consisting of 421 species and 928 reactions. We start from an already fit, relatively small literature model whose consistency we check formally. We then construct the final model through an algorithmic step-by-step refinement procedure that ensures the preservation of the model's fit.

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A reaction system is a modeling framework for investigating the functioning of the living cell, focused on capturing cause-effect relationships in biochemical environments. Biochemical processes in this framework are seen to interact with each other by producing the ingredients enabling and/or inhibiting other reactions. They can also be influenced by the environment seen as a systematic driver of the processes through the ingredients brought into the cellular environment. In this paper, the first attempt is made to implement reaction systems in the hardware. We first show a tight relation between reaction systems and synchronous digital circuits, generally used for digital electronics design. We describe the algorithms allowing us to translate one model to the other one, while keeping the same behavior and similar size. We also develop a compiler translating a reaction systems description into hardware circuit description using field-programming gate arrays (FPGA) technology, leading to high performance, hardware-based simulations of reaction systems. This work also opens a novel interesting perspective of analyzing the behavior of biological systems using established industrial tools from electronic circuits design.

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We propose a new variant of network of evolutionary picture processors, where the operations mask and unmask considered in [4] are replaced by the circular permutation of a row or column on the picture frontier. We propose a solution based on these networks to the picture pattern matching problem that runs in O(n + m + kl) computational steps, where the pattern is of size (k ,l) and the input picture is of size (n,m). We finally discuss how our solution may easily lead to solutions to a few further related problems on pictures.

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We define a variant of accepting splicing system that can be used as a problem solver. A condition for halting the computation on a given input as well as a condition for making a decision as soon as the computation has stopped is considered. An algorithm based on this accepting splicing system that solves a well-known NP-complete problem, namely the 3-colorability problem is presented. We discuss an efficient solution in terms of running time and additional resources (axioms, supplementary symbols, number of splicing rules. More precisely, for a given graph with n vertices and m edges, our solution runs in O (nm) time, and needs O (mn(2)) other resources. Two variants of this algorithm of a reduced time complexity at an exponential increase of the other resources are finally discussed.

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An intriguing problem in computer science is the formal description of dynamics in cell populations. We propose here a multi-agent-based model that could be used in this respect. The model proposed in this paper consists of biological entities (cells) as agents and a biochemical environment. Both are represented by multisets of symbols. The environment evolution is regulated by multiset Lindenmayer rules depending on the current state of all agents, while the evolution of each agent, which depends on the environment current state, is defined by means of multiset patterns. We discuss some algorithmic problems related to the dynamics of the proposed multi-agent model: infinite and stationary evolution, environment, and agent reachability.

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We continue the investigation of three operations on words and languages with motivations coming from DNA biochemistry, namely unbounded and bounded hairpin completion and hairpin lengthening. We first show that each of these operations can be used for replacing the third step, the most laborious one, of the solution to the CNF-SAT reported in [28]. As not all the bounded/unbounded hairpin completion or lengthening of semilinear languages remain semilinear, we study sufficient conditions for semilinear languages to preserve their semilinearity property after applying once either the bounded or unbounded hairpin completion, or lengthening. A similar approach is then started for the iterated variants of the three operations. A few open problems are finally discussed.

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We give examples of 2-parameter bounded quadratic dynamical systems with 3 finite singularities, which have at least 4 limit cycles around a singularity (in the (4,0)-configuration)-the first example of this type - and in a (3,1)-configuration. The paper mentions the Nanobiotechnological origins of these experimentally discovered systems with interesting properties.

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We give examples of 2-parameter bounded quadratic dynamical systems with 3 finite singularities, which have at least 4 limit cycles around a singularity (in the (4,0)-configuration) - the first example of this type - and in a (3,1)-configuration. The paper mentions the Nanobiotechnological origins of these experimentally discovered systems with interesting properties. © 2019 University of Kragujevac, Faculty of Science. All rights reserved.

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The Tile Assembly Model, and its many variants, is one of the most fundamental algorithmic assembly formalism within DNA nanotechnology. Most of the research in this field is focused on the complexity of assembling different shapes and patterns. In many cases, the assembly process is intrinsically deterministic and the final product is unique, while the assembly process might evolve through several possible assembly strategies. In this study we consider the controlled assembly of one dimensional tile structures according to predefined assembly graphs. We provide algorithmic approaches for developing such controlled assembly protocols, using the signal-passing Tile Assembly Model, as well as probabilistic approaches for investigating the assembly of such tile-based one-dimensional structures. As a byproduct, we build a generalized TAS (tile assembly system) which generate specific non-local non-associative algebraic computations and we assamble n x n squares using only one tile, which is a better efficiency compared to the staged assembly model. (C) 2019 The Authors. Published by Elsevier B.V.

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First-order sinking cave streams experience considerable hydrological variability, including spates and periods of base-flow during dry seasons. Early-summer flooding on a first-order stream sinking in Ciur-Ponor Cave (Romania) represented a suitable opportunity to test the response of the macroinvertebrate community and of basal food resources quantity and diversity to such a disturbance event. The invertebrate community and basal resources (i.e., woody debris, leaves, fine particulate organic matter and epilithon) were collected from three sampling sites, before and after the flood. The sampling strategy followed an up-downstream gradient of both species diversity and quantity of allochtonous organic matter decrease as the stream flows through the cave. From each sampling site, ten replicates of both the benthic community and basal resources (detritus and epilithon) were taken. Outside the cave, the spate reduced the invertebrate community density, instant secondary production, complexity and stability (measured as eco-exergy and specific eco-exergy). The epigean section of the stream is populated mainly by taxa characteristic of karst headwaters prone to floods that usually recolonize the streambed rapidly from adjacent habitats. This effect was corroborated with a subsequent increase of both the mass of fine particulate organic matter and of invertebrate density within the cave, following the aftermath of the flood. In the river stretch situated close to the entrance (100 m), where the flood carried both live and dead organic matter, the stability index showed that the complexity of the community was not severely disturbed, despite the high influx of surface-dwelling taxa and temporary increase in species richness. Further downstream, in the third sampling site (400 m from entrance), all measured endpoints indicated a change in community stability, suggesting that local spates can act as rejuvenating drivers in shaping the invertebrate community structure and functioning.

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A new biodegradable antioxidant active packaging for food applications based on antioxidants from medicinal and aromatic plants incorporated into a polylactic acid matrix was designed and developed. Melt blending processing technique was applied to prepare polylactic acid films loaded by sage and lemon balm leaves. Antioxidant properties of developed active films were investigated using the following methods: 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid), 2,2-diphenyl-1-(2,4,6-trinitrophenyl)hydrazyl and a home-made generator of hydroxyl radicals. In addition, reducing power and total phenolic content of polylactic acid films were checked. The results of antioxidant capacity showed that percentage of hydroxylation for active film with lemon balm and sage was 55.5% +/- 0.1% and 67.4% +/- 0.3%, respectively. The reducing power of active films increased 8 times in comparison to the blank samples. Moreover, extensive investigation of influence of sage and lemon balm leaves on material safety and type of migrants was performed using migration assays. The composition of both non-volatile and volatile compounds of different active packaging films was compared with neat polylactic acid film. Three different food simulants such as 95% (v/v) ethanol, 10% (v/v) ethanol and 3% (w/v) acetic acid were checked. It was shown that the addition of sage and lemon balm leaves into a polylactic acid structure decreased the migration of both linear and cyclic polylactic acid oligomers, currently not legislated by European Union. Besides, total absence or decrease of migration of volatile compounds were observed when using the active films. Both thermal and mechanical properties of films were also evaluated.

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Two complementary approaches are commonly used for analysing trophic interactions that allow inferences about consumed and assimilated resources: gut content (GCA) and stable isotope (SIA) analyses. We used these methods to assess the trophic ecology of a native (Pontastacus leptodactylus) and an invasive species (Faxonius limosus) of crayfish in the Lower Danube (Romania) by calculating five frequently used metrics (i.e. trophic position, omnivory index, elemental imbalance for C:N ratio, trophic niche width and overlap). The SIA approach indicated significantly different trophic niche widths between the crayfish species and potential resource partitioning that triggered lower niche overlap, aspects not depicted by GCA. The latter approach suggested higher omnivory indices and elemental imbalance for macronutrients, potentially because of high incidences of basal resources with low nitrogen content in the foreguts of both species. Although, as indicated by GCA, the two species seem to feed largely on the same resources, SIA suggested that the ingested food items were assimilated with differing efficiencies. These findings are of importance for studies of invasion biology, where the replacement of native species by invasive taxa is underpinned by mechanisms that should be explored by using the most appropriate approach.

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A plethora of forest models were developed by transforming the dependent variable, which introduces bias if appropriate corrections are not applied when back-transformed. Many recognized models are still biased and the original data sets are no longer available, which suggests ad hoc bias corrections. The present research presents a procedure for bias correction in the absence of needed information from summary statistics. Additionally, we developed a realistic correction of the square root transformation based on a truncated normal distribution. The transformations considered in this study are the logarithm, the square root and arcsine square root. Using simulated data we found that uncorrected back-transformation created biases by as much as 100 percent. The generated data revealed that depending on available information, that bias can still be present after correction. In addition to generated data we corrected the site index of Douglas-fir and ponderosa pine in Oregon USA, tree volume of 27 species from Romania, stand merchantable volume for longleaf pine in Louisiana and East Texas USA, and canopy fuel weight in Washington USA. Using only the available information, the unbiased back-transformed estimates can change from <= 1 percent (i.e. the site index and canopy fuel weight) to >= 1/3 (tree and stand volume).

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Numerical P systems (for short, NP systems) are distributed and parallel computing models inspired from the structure of living cells and economics. Enzymatic numerical P systems (for short, ENP systems) are a variant of NP systems, which have been successfully applied in designing and implementing controllers for mobile robots. Since ENP systems were proved to be Turing universal, there has been much work to simplify the universal systems, where the complexity parameters considered are the number of membranes, the degrees of polynomial production functions or the number of variables used in the systems. Yet the number of enzymatic variables, which is essential for ENP systems to reach universality, has not been investigated. Here we consider the problem of searching for the smallest number of enzymatic variables needed for universal ENP systems. We prove that for ENP systems as number acceptors working in the all-parallel or one-parallel mode, one enzymatic variable is sufficient to reach universality; while for the one-parallel ENP systems as number generators, two enzymatic variables are sufficient. to reach universality. These results improve the best known results that the numbers of enzymatic variables are 13 and 52 for the all-parallel and one-parallel systems, respectively.

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Advancements in information technology led environmental scientists to the illusion that efforts should be mainly focused on developing models that reduce uncertainty rather than on models adjusted to the existing uncertainty. As a result, environmental relationships are represented by non-parsimonious and suboptimal models, which in many instances could be even wrong. The objective of this research was to provide scientists focused on modeling ecosystem processes with a procedure that supplies parsimonious correct results. The procedure transforms the response variable to achieve a linear model and the normality of the residuals. After the parameters of the transformed model are estimated, the bias induced by back-transforming is corrected. We have computed the bias corrections for 11 of the most popular functions from the power, trigonometric, and hyperbolic families by considering the truncated normal distribution, when necessary. Using generated data, we have shown that the proposed procedure supplies unbiased results. We have identified a sample size artifact of data generation such that when the variance increases the truncation of distribution starts altering the corrections of predicted values, sometimes by more than 50% from the actual values. Our results indicate that uncertainty, measured by variance, impacts the analysis in a non-intuitive way when the defining domain of the response variable is restricted. The subtle way of influencing the development of complex nonlinear models by uncertainty advocates the usage of parsimonious linear models, which are less sensitive to the method of processing data. Finally, ecosystem processes should be modeled with strategies that consider not only processes and computation aspects, but also uncertainty, in particularly reducing variance to levels with no significant impact on the results.

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Background: Network controllability focuses on discovering combinations of external interventions that can drive a biological system to a desired configuration. In practice, this approach translates into finding a combined multi-drug therapy in order to induce a desired response from a cell; this can lead to developments of novel therapeutic approaches for systemic diseases like cancer. Result: We develop a novel bioinformatics data analysis pipeline called NetControl4BioMed based on the concept of target structural control of linear networks. Our pipeline generates novel molecular interaction networks by combining pathway data from various public databases starting from the user's query. The pipeline then identifies a set of nodes that is enough to control a given, user-defined set of disease-specific essential proteins in the network, i.e., it is able to induce a change in their configuration from any initial state to any final state. We provide both the source code of the pipeline as well as an online web-service based on this pipeline http://combio.abo.fi/nc/net_control/remote_call.php. Conclusion: The pipeline can be used by researchers for controlling and better understanding of molecular interaction networks through combinatorial multi-drug therapies, for more efficient therapeutic approaches and personalised medicine.

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In this paper, we consider the computational power of a new variant of networks of splicing processors in which each processor as well as the data navigating throughout the network are now considered to be polarized. While the polarization of every processor is predefined (negative, neutral, positive), the polarization of data is dynamically computed by means of a valuation mapping. Consequently, the protocol of communication is naturally defined by means of this polarization. We show that networks of polarized splicing processors (NPSP) of size 2 are computationally complete, which immediately settles the question of designing computationally complete NPSPs of minimal size. With two more nodes we can simulate every nondeterministic Turing machine without increasing the time complexity. Particularly, we prove that NPSP of size 4 can accept all languages in NP in polynomial time. Furthermore, another computational model that is universal, namely the 2-tag system, can be simulated by NPSP of size 3 preserving the time complexity. All these results can be obtained with NPSPs with valuations in the set as well. We finally show that Turing machines can simulate a variant of NPSPs and discuss the time complexity of this simulation.

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The tree species composition of a forest ecosystem is commonly represented with weights that measure the importance of one species with respect to the other species. Inclusion of weight in practical applications is difficult because of the inherent multidimensional perspective on composition. Scalar indices overcome the multidimensional challenges, and, consequently, are commonly present in complex ecosystem modeling. However, scalar indices face two major issues, namely non-uniqueness and non-measurability, which limit their ability to be generalized. The objective of this study is to identify the conditions for developing a univariate true measure of composition from weights. We argue that six conditions define a scalar measure of species mixture: (1) usefulness, (2) all species have equal importance, (3) all individuals have the same importance, (4) the measurements expressing importance of an individual are consistent and appropriate, (5) the function measuring composition is invertible, and (6) the function is a true-measure. We support our argument by formally proving all the conditions. To illustrate the applicability of the scalar measure we develop a rectilinear-based measure, and apply it in yield modeling and assessment of ecosystem dynamics. (C) 2018 Elsevier B.V. All rights reserved.

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Spiking neural P systems are a class of third generation neural networks belonging to the framework of membrane computing. Spiking neural P systems with communication on request (SNQ P systems) are a type of spiking neural P system where the spikes are requested from neighboring neurons. SNQ P systems have previously been proved to be universal (computationally equivalent to Turing machines) when two types of spikes are considered. This paper studies a simplified version of SNQ P systems, i.e. SNQ P systems with one type of spike. It is proved that one type of spike is enough to guarantee the Turing universality of SNQ P systems. Theoretical results are shown in the cases of the SNQ P system used in both generating and accepting modes. Furthermore, the influence of the number of unbounded neurons (the number of spikes in a neuron is not bounded) on the computation power of SNQ P systems with one type of spike is investigated. It is found that SNQ P systems functioning as number generating devices with one type of spike and four unbounded neurons are Turing universal.

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Recent research has revealed new applications of network control science within bio-medicine, pharmacology, and medical therapeutics. These new insights and new applications generated in turn a rediscovery of some old, unresolved algorithmic questions, this time with a much stronger motivation for their tackling. One of these questions regards the so-called Structural Target Control optimization problem, known in previous literature also as Structural Output Controllability problem. Given a directed network (graph) and a target subset of nodes, the task is to select a small (or the smallest) set of nodes from which the target can be independently controlled, i.e., it can be driven from any given initial configuration to any desired final one, through a finite sequence of input values. In recent work, this problem has been shown to be NP-hard, and several heuristic algorithms were introduced and analyzed, both on randomly generated networks, and on bio-medical ones. In this paper, we show that the Structural Target Controllability problem is fixed parameter tractable when parameterized by the number of target nodes. We also prove that the problem is hard to approximate at a factor better than O(log n).

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The aim of this paper is to discuss two possible ways of introducing some features based on probabilistic concepts and methods in networks of polarized evolutionary processors (NPEP). We associate probabilities with rules in every node such that together with the communication protocol, which is based on the compatibility between the polarization of each node and data navigating through the network, might facilitate the study of biological phenomena as well as software simulations or hardware implementations. The probability associated with rules may be a priori defined and fixed or may be computed dynamically. Probabilities will also appear when communicating data between nodes; these probabilities may be statically or dynamically defined. This note also proposes the study of the impact of these characteristics and see how these new features reduce the gap between the formal model and its practical applicability. Introducing probabilities in NPEP is aimed to decrease the exponential expansion of the number of strings which appear in the computations used to solve NP-problems in a polynomial time. A decreasing of the exponential expansion of this number is achieved with a loss of certainty of the final result which is reached with some error probability.

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This paper presents the latest trends and approaches used for constructing nanoscale structures of 2D objects through DNA folding based on the DNA origami technology developed by Rothemund. The Rothemund method has been used in the construction of various shapes, such as the development of the nanoscale structure for the United States map. Following the steps of Rothemund's technique, we simulate the construction of the Romanian map nanoscale 2D structure, embedding the number 100 into it.

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Investigation of the lake systems can provide a variety of information that can lead to the development of general concepts about how lakes function and respond to environmental changes. The purpose of this study is to assess the current classification of therapeutic lakes based on supervised learning methods applied to several biochemical characteristics of such lakes. In order to classify the therapeutic lakes in a separate class, a dataset consisting of 45 observations from 9 different basins and from three different altitude categories was analysed using clustering and classification methods.

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The TAM (Model Tile Assembly Model) is a mathematical paradigm for modeling DNA self-assembling according to various given shapes, using DNA-tiles (rectangular shape) with sticky ends on each of the four edges that bound together on various shapes desired by the researcher. Although there are various models in the literature, the focus in this manuscript is on a rule based model, specifically the authors present an overview of the one-dimensional hierarchical self-assembly model of DNA tiles. The authors also present the evolution of number of tiles in partial assemblies, the average assembly size and of the number of partial assemblies of sizes 2 through 10 over the total running time. All simulations were run using the NFSim simulator on a preset period of time.

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Salvia officinalis essential oil loaded gelatin hydrogels with improved antibacterial activity and enhanced stability was prepared by microwave-assisted polymerization method. FT-IR spectra indicated no chemical interaction between the hydrogel matrix and the essential oil functional groups. According to the swelling studies, enhanced stability in all pH media was obtained. Studying two kinetic models: Fickian transport and Schott second order kinetic model, it was demonstrated that the swelling process of the prepared hydrogels occurs after a second order kinetics. Antibacterial activity, investigated by the agar diffusion method, regarding S. aureus and E. coli is comparable to that of silver nanoparticles and twice more efficient compared to cinnamon essential oil.

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Galium verum essential oil (EO) loaded gelatin hydrogel was prepared by microwave-assisted polymerization method. FT-IR analysis indicated no chemical interaction between the hydrogel matrix and EO. Good swelling behavior, increased thermo- and mechanical-properties was attributed to the synergistic effects of the secondary structure of gelatin after gelation and intermolecular hydrogen-bonding interactions between the hydrogel matrix and EO ingredient's. Antibacterial activity was investigated by the agar diffusion method.

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this paper we present an improvement of the Segment Based Contours (SBC) method by implementing a higher order of finite difference schemes in the partial differential equation used in our mathematical model. Two methods are presented: one is a 4th order method and the other a 8th order method. The 4th order method could be applied to segment both the cDNA microarray images and the Affymetrix GeneChips, while the 8th order method could only be applied to processing the cDNA microarray images, due to the limitation of the current image resolution. Additionally, we provide both the mathematical derivations for the partial. differential equations (their 4th or 8th order approximations) as well as the validation trough simulations of the microarray images by using real images as seeds for the Nykter's 2006 methodology. We conclude by showing that both the 4th order method as well as the 8th order one are superior to the SBC and the widely used GOGAC method implemented in the Affymetrix standard processing package for microarrays. (C) 2017 Elsevier B.V. All rights reserved.

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In this paper, we consider the computational power of a new variant of networks of splicing processors in which each processor as well as the data navigating throughout the network are now considered to be polarized. While the polarization of every processor is predefined (negative, neutral, positive), the polarization of data is dynamically computed by means of a valuation mapping. Consequently, the protocol of communication is naturally defined by means of this polarization. We show that networks of polarized splicing processors (NPSP) of size 2 are computationally complete, which immediately settles the question of designing computationally complete NPSPs of minimal size. We prove that NPSP of size 4 can accept all languages in NP in polynomial time. All these results can be obtained with NPSPs with valuations in the set {-1, 0, 1} as well. We finally show that Turing machines can simulate a variant of NPSPs and discuss the time complexity of these simulations.

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In the last few decades, due to the global industrialization and population expansion the level of pollutants has largely increased, being one of the main environmental problems faced worldwide. Consequently, phytoremediation research had been gathering more and more interest. A study of data selected from Scopus is presented by the authors, identifying trends in publication number, collaboration and impact. The trends are identified at the global level followed by a discussion of how Romania performs with respect to the identified trends. When evaluating the research produced by the Romanian institutions, two characteristics are considered: phytoremediation potential of the plants in the Danube Delta and the coastal region and the phytoremediation research temporal evolution and international impact. The paper presents a quantitative analysis without adding variable weights to citations and publications based on the publications ranks offering an overview of the national research status in this research area.

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Background: According to only a handful of historical sources, Osmunda regalis, the royal fern, has been used already in the middle age as an anti-cancer remedy. To examine this ancient cancer cure, an ethanolic extract of the roots was prepared and analysed in vitro on its effectiveness against head and neck cancer cell lines. Methods: Proliferation inhibition was measured with the MTT assay. Invasion inhibition was tested in a spheroid-based 3-D migration assay on different extracellular matrix surfaces. Corresponding changes in gene expression were analysed by qRT-PCR array. Induction of apoptosis was measured by fluorescence activated cell sorting (FACS) with the Annexin V binding method. The plant extract was analysed by preliminary phytochemical tests, liquid chromatography/mass spectroscopy (LC-MS) and thin layer chromatography (TLC). Anti-angiogenetic activity was determined by the tube formation assay. Results: O. regalis extract revealed a growth inhibiting effect on the head and neck carcinoma cell lines HLaC78 and FaDu. The toxic effect seems to be partially modulated by p-glycoprotein, as the MDR-1 expressing HLaC79-Tax cells were less sensitive. O. regalis extract inhibited the invasion of cell lines on diverse extracellular matrix substrates significantly. Especially the dispersion of the highly motile cell line HlaC78 on laminin was almost completely abrogated. Motility inhibition on laminin was accompanied by differential gene regulation of a variety of genes involved in cell adhesion and metastasis. Furthermore, O. regalis extract triggered apoptosis in HNSCC cell lines and inhibited tube formation of endothelial cells. Preliminary phytochemical analysis proved the presence of tannins, glycosides, steroids and saponins. Liquid chromatography/mass spectroscopy (LC-MS) revealed a major peak of an unknown substance with a molecular mass of 864.15 Da, comprising about 50% of the total extract. Thin layer chromatography identified ferulic acid to be present in the extract. Conclusion: The presented results justify the use of royal fern extracts as an anti-cancer remedy in history and imply a further analysis of ingredients.

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Control theory is a well-established approach in network science, with applications in bio-medicine and cancer research. We build on recent results for structural controllability of directed networks, which identifies a set of driver nodes able to control an a-priori defined part of the network. We develop a novel and efficient approach for the (targeted) structural controllability of cancer networks and demonstrate it for the analysis of breast, pancreatic, and ovarian cancer. We build in each case a protein-protein interaction network and focus on the survivability-essential proteins specific to each cancer type. We show that these essential proteins are efficiently controllable from a relatively small computable set of driver nodes. Moreover, we adjust the method to find the driver nodes among FDA-approved drug-target nodes. We find that, while many of the drugs acting on the driver nodes are part of known cancer therapies, some of them are not used for the cancer types analyzed here; some drug-target driver nodes identified by our algorithms are not known to be used in any cancer therapy. Overall we show that a better understanding of the control dynamics of cancer through computational modelling can pave the way for new efficient therapeutic approaches and personalized medicine.

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We refine the modeling in the P systems area of the way bacteria transmit genetic information in bacterial colonies, specifically the conjugation process. We study this new model from the computational power perspective using methods and ideas in the area; we are able to prove the universality of these systems. We show that systems working in a homogeneous manner and using only 75 species of objects in the regions and 13 species of on-membrane objects are enough for reaching universality. The system starts in a initial state with only few (nine) bacteria needed and the bacteria from this system are homogeneous, all have the same rules.

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The (abstract) Tile Assembly Model (aTAM), is a mathematical paradigm for the study and algorithmic design of DNA self-assembly systems. It employs the use of so-called DNA tiles, which are abstractions of experimentally achievable DNA nanostructure complexes with similar inter-matching behaviours. To this day, there are about half-dozen different experimental implementations of DNA tiles and their sub-sequent algorithmic assembly into larger complexes, see e.g. Reif et al. (2012) [29]. In order to provide further insight into the assembly process, the aTAM model has been extended to a kinetic counterpart (kTAM). Although there is a wide abundance of different variants of the abstract model, e.g., stage, step, hierarchical, temperature-k, signal-passing, etc. (see e.g. Patitz (2012) [22]), numerical simulations of the kinetic counterpart have been performed only for a few types of these systems. This might be due to the fact that the numerical models and simulations of kTAM were almost exclusively implemented using classical stochastic simulation algorithms frameworks, which are not designed for capturing models with theoretically un-bounded number of species. In this paper we introduce an agent- and rule-based modelling approach for kTAM, and its implementation on NFsim, one of the available platfonris for such type of modelling. We show not only how the modelling of kTAM can be implemented, but we also explore the advantages of this modelling framework for kinetic simulations of kTAM and the easy way such models can be updated and modified. We present numerical comparisons both with classical numerical simulations of kTAM, as well as comparison in between four different kinetic variant of the TAM model, all implemented in NFsim as stand-alone rule-based models. (C) 2017 Elsevier B.V. All rights reserved.

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We extend to spiking neural P systems a notion investigated in the standard membrane systems: the language of the traces of a distinguished object. In our case, we distinguish a spike by marking it and we follow its path through the neurons of the system, thus obtaining a language. Several examples are discussed and some preliminary results about this way of associating a language with a spiking neural P system are given, together with a series of topics for further research. For instance, we show that each regular language is the morphic image of a trace language intersected with a very particular regular language, while each recursively enumerable language over the one-letter alphabet is the projection of a trace language. In all proofs we try to keep the size of used systems (number of neurons, of rules in each neuron, of spikes consumed or removed by rules) as small as possible. (C) 2016 Elsevier B.V. All rights reserved.

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Spiking neural P systems with rules on synapses (RSSN P systems, for short) are a class of distributed and parallel computation models inspired by the way in which neurons process and communicate information with each other by means of spikes, where neurons only contain spikes and the evolution rules are on synapses. RSSN P systems have been proved to be Turing universal, using the strategy that restricts all the applied rules to consume the same number of spikes from the given neuron, termed as equal spikes consumption strategy. In this work, in order to avoid imposing the equal spikes consumption restriction on the application of rules, a new strategy for rule application, termed as sum spikes consumption strategy, is considered in RSSN P systems, where a maximal set of enabled rules from synapses starting from the same neuron is nondeterministically chosen to be applied, in the sense that no further synapse can use any of its rules, and the sum of these numbers of spikes that all the applied rules consume is removed from the neuron. In this way, the proposed strategy avoids checking whether all the applied rules consume the same number of spikes from the given neuron. The computation power of RSSN P systems working in the proposed strategy is investigated, and it is proved that such systems characterize the semilinear sets of natural numbers, i.e., such systems are not universal. Furthermore, RSSN P systems with weighted synapses working in the proposed strategy are proved to be Turing universal. These results show that the weight on synapses is a powerful ingredient of RSSN P systems in terms of the computation power, which makes RSSN P systems working in sum spikes consumption strategy become universal from non-universality.

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Evaluation of funded research, by measuring the outcomes of the grants publications, journals, and citations is not always done comparatively and publicised. Bibliometric indicators were employed and applied to the 2009-2014 publications authored by academicians funded by European research grants that are indexed in the Web of Science. Citation based approaches, such as the h-index or the impact factor, have been widely used to evaluate researchers or journals. In this study we use the aforementioned H-index to evaluate the funded research grants and to provide a ranking in terms of the most successful ones. The ranking results can be used by evaluators in determining how successful an applicant has potential to be, but also by researchers to choose their publication outlets, or to pursue future collaborations.

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This paper conducts an examination of log files originating from High Performance Computing (HPC) applications with known reliability problems. The results of this study further the maturation and adoption of meaningful metrics representing HPC system and application failure characteristics. Quantifiable metrics representing the reliability of HPC applications are foundational for building an application resilience methodology critical in the realization of exascale supercomputing. In this examination, statistical inequality methods originating from the study of economics are applied to health and status information contained in HPC application log files. The main result is the derivation of a new failure index metric for HPC a normalized representation of parallel application volatility and/or resiliency to complement existing reliability metrics such as mean time between failure (MTBF), which aims for a better presentation of HPC application resilience. This paper provides an introduction to a Failure Index (FI) for HPC reliability and takes the reader through a use-case wherein the H is used to expose various run-time fluctuations in the failure rate of applications running on a collection of HPC platforms. (C) 2016 Elsevier Inc. All rights reserved.

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The Danube River-Danube Delta-Black Sea (DBS) region has witnessed major political, social and economic changes during the past three decades, which have profoundly affected the riverine, coastal and marine systems, their water management situation and the development of related research programmes. We reviewed the research activities in the DBS system of the past twenty years to determine the main funding bodies and to assess key research areas and how they varied over time and geographic region. As data basis we used a metadatabase filled with 478 projects addressing environmental and water management issues in the Danube River Basin, covering also the Danube Delta and the north-western Black Sea. As overall outcome extensive research efforts in the field of water management could be proven for the past two decades, despite the tumultuous times of political and economic transformations. One of the main findings was that EU funded projects played a key role for the development of transboundary research collaboration and were also the scientifically most productive one's. Historically, nutrient pollution was the main problem addressed, shifting to pollution in a broader sense and hydromorphological alterations in recent years. The newly arising challenges of climate change impacts and sediment management became important research questions in the last years, too. Most research was performed in the thematic field of navigation, followed by restoration and biodiversity issues. To meet all of the already

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Sustainable river basin management depends on knowledge, skills and education. The DANCERS project set out to identify feasible options for achieving education for sustainable water management across the Danube river basin, and its integration with broader education and economic development. The study traced the historic, regulatory and educational landscape of water management in the basin, contrasting it with the complex political decision-making, data-heavy decision support, learning-centred collaboration, and information-based participation that are all inherent components of Integrated Water Resource Management (IWRM). While there is a wide range of educational opportunities and mobility schemes available to individuals, there is no coherent network related to training in water management and sustainable development in the study region. Progress in addressing the multi-layered environmental challenges within the basin requires further aligning of economic, environmental and educational policies, advancing the EU Bologna Process across the region, and the development of dedicated training programmes that combine technical and relational skills. The DANCERS project identified key short and medium term needs for education and research to support progressive adoption of sustainable development, and the necessary dialogue across the public and private sectors to align policies. These include the development of new education networks for masters and PhD programmes, including joint programmes; improved access to technical training and life-long learning programmes for skills development; developing formalized and certified competency structures and associated accreditation of institutions where such skilled individuals work; and developing a co-ordinated research infrastructure and pan-basin programme for research for water management and sustainable development 2015 Elsevier B.V. All rights reserved.

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The Danube River–Danube Delta–Black Sea (DBS) region has witnessed major political, social and economic changes during the past three decades, which have profoundly affected the riverine, coastal and marine systems, their water management situation and the development of related research programmes. We reviewed the research activities in the DBS system of the past twenty years to determine the main funding bodies and to assess key research areas and how they varied over time and geographic region. As data basis we used a metadatabase filled with 478 projects addressing environmental and water management issues in the Danube River Basin, covering also the Danube Delta and the north-western Black Sea. As overall outcome extensive research efforts in the field of water management could be proven for the past two decades, despite the tumultuous times of political and economic transformations. One of the main findings was that EU funded projects played a key role for the development of transboundary research collaboration and were also the scientifically most productive one's. Historically, nutrient pollution was the main problem addressed, shifting to pollution in a broader sense and hydromorphological alterations in recent years. The newly arising challenges of climate change impacts and sediment management became important research questions in the last years, too. Most research was performed in the thematic field of navigation, followed by restoration and biodiversity issues. To meet all of the already identified and newly emerging challenges in the DBS System, cross-border and integrated (river-delta-sea) research activities are of major importance and have to be further promoted. We thus suggest drawing up a regional DBS Research Agenda linked to key challenges in water management to strengthen research collaboration and advance targeted scientific projects, an approach fostering also the scientific capacity in the region. © 2015 Elsevier B.V.

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The regional bioeconomic potential takes into consideration many sectors of the economy that use renewable biological resources. The plants are one of the main resources for the most sectors - food, health, environment, materials and energy. The assessment of bioeconomic potential involves the modeling of the biological and economical aspects. Establishing the indicators involved in the study of this aspect requires a “what we have and what we need” analysis. We started with the development of a database of plants to facilitate an easy access to information for all interested scientist from related research fields. © 2016 Vasile Goldis University Press.

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One issue that has become more important over the years is to evaluate the capability for worldwide research networks on different areas of research, especially in the areas that are identified as being worldwide significant. The study investigated the research output, citations impact and collaborations on publications listed in Scopus authored by researchers all over the world, research published between 1999-2014, selected by a group of keywords identified by authors. The results of the analysis identified an increasing trend in scientific publications starting with 2006, especially on three of the analyzed keywords. We also found differences in the citations patterns for the Black Sea and Danube Delta keywords in the contributing countries. The results of this study revealed a steady increase of the collaboration output and an increasing trend in the collaboration behavior, both at the European and national level. Additionally, at the national level the study identified the collaboration network between Romanian institutions per counties.

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We consider the discrete three dimensional scan statistics. Viewed as the maximum of an 1-dependent stationary r.v.'s sequence, we provide approximations and error bounds for the probability distribution of the three dimensional scan statistics. Importance sampling algorithm is used to obtain sharp bounds for the simulation error. Simulation results and comparisons with other approximations are presented for the binomial and Poisson models.

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In this work we describe a new segmentation technique for the Affymetrix microarray images. We prove that our method can offer better predictions on the gene levels as opposed to the standard Affymetrix segmentation implemented in the Affymetrix GeneChip Operating Software (GCOS). To check the accuracy and show the benefits of the new segmentation method we use a previously implemented methodology to simulate microarray images with realistic features. Using such an artificial image provides us with the actual levels for each spot and each gene investigated in the microarray. Using this information we then proceed to segment the same image twice (with GCOS and our new method). The two segmentations will produce two sets of gene levels that are then compared to the known gene levels (known since the moment of generating the artificial image). Using this methodology we are able to show statistically (using 50 replicates of the same steps of generating the image, segmenting, comparing the results) that in some cases our new method greatly outperforms the GCOS implemented segmentation method, while in the rest of the cases performs in similar fashion. (C) 2015 Elsevier B.V. All rights reserved.

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Galium verum, also known as Lady's Bedstraw, is a herbaceous perennial plant of the family Rubiaceae, native to Europe and Asia and used in traditional medicine as an anticancer medicine. It is used as a decoction in most traditional recipes, applied externally as well as internally. We produced a Galium verum decoction and applied it in vitro to chemosensitive (Hep-2 and HLaC79) and chemoresistant, P-glycoprotein-overexpressing (Hep2-Tax, HLaC79-Tax) laryngeal carcinoma cell lines. It could be demonstrated that Galium aqueous extract is cytotoxic for all cell lines. A detailed spheroid-based 3D invasion analysis of Hep2 and Hep2-Tax in semisolid collagen gels and on different extracellular matrix coatings was performed, which showed an inhibition of invasion by sublethal concentrations of Galium decoction and proved to be even more pronounced in the more aggressively invading chemoresistant Hep2-Tax cell line. Gelatinolytic activity of MMP-2 was downregulated in three of the four cell lines. Angiogenesis (endothelial tube formation) in contrast, was not affected by Galium aqueous extract. Gene expression array on HLaC79 and Hep2 cell lines treated with Galium decoction vs. untreated controls revealed no unique pathway activation patterns in these cells. Results are discussed with respect to the use of herbal drugs as a preventive and/or a concomitant therapeutic approach in head and neck cancer.

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The ideas expressed in this work pertain to biochemical modeling. We explore our technique, the Nondeterministic Waiting Time algorithm, for modeling molecular signaling cascades. The algorithm is presented with pseudocode along with an explanation of its implementation. We discuss several important extensions including: (i) a heap with special maintenance functions for sorting reaction waiting times, (ii) a nondeterminstic component for handling reaction competition, and (iii) a memory enhancement allowing slower reactions to compete with faster reactions. Several example systems are provided for comparisons between modeling with systems of ordinary differential equations, the Gillespie Algorithm, and our Nondeterministic Waiting Time Algorithm. Our algorithm has a unique ability to exhibit behavior similar to the solutions to systems of ordinary differential equations for certain models and parameter choices, but it also has the nondeterministic component which yields results similar stochastic methods (e.g., the Gillespie Algorithm). There are several extensions for the current work discussed at the end of the chapter.

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We consider the two-dimensional discrete scan statistic generated by a block-factor type model. Under the null hypothesis, in which the block-factor model is obtained from an i.i.d. sequence of random variables, we present an approximation for the distribution of the scan statistics and the corresponding error bounds. Numerical results are presented to evaluate the accuracy of the approximation discussed in this paper. (C) 2014 Elsevier B.V. All rights reserved.

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Simulated annealing (SA) is a heuristic technique popular in forest planning, providing solutions close to optimality in reduced computation time. The present study challenges the common approach used to establish the parameters of SA that mimic physical processes by proving that slow cooling or large initial temperatures do not necessarily lead to optimal solutions. The study has two objectives: (1) to identify the parameters (i.e., initial temperature and annealing rate) that could supply close to optimal results with reduced experimentation time and (2) to assess the impact of parameters determining SA performances. Using three forest inventory data sets from British Columbia, we investigated the influence of initial temperature, annealing rate, and numbers of runs on forest planning solutions using a replicated completely randomized design organized as a factorial experiment within a repeated-measures framework. The optimal solution seems to be little influenced by the number of runs; our findings indicate that the combination of initial temperature and rate of annealing is critical in obtaining superior results. Furthermore, the selection of the SA parameters seems to be dependent on the harvest age, which indicates that the parameters should be selected considering whether or not a stand is harvested more than once during the planning period.

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The paper studies algorithmic properties of operations with membrane proteins modeled within the framework of membrane systems (also called P systems). Membrane systems are biologically inspired models of parallel and distributed computing based on the information processing in cells and cellular membranes. We show that the computational potential of P systems with proteins on membranes is equivalent to that of parallel computing models as the alternating Turing machine or the PRAM. These abstract machines characterize by their polynomial time-bounded computations the class PSPACE, and simultaneously they serve as idealized models of real parallel machines. Therefore, this and other related results suggest the existence of a homology between the potential of silicon and biological parallel information processing. (C) 2013 Elsevier B.V. All rights reserved.

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In this paper we consider sequential SNP systems where the sequentiality of the system is induced by the max-spike: the neuron with the maximum number of spikes out of the neurons that can spike at one step will fire. This corresponds to a global view of the whole network that makes the system sequential. We continue the study in the direction of max-spike and show that systems with 132 neurons are universal. This improves a recent result in the area. © 2012 Springer-Verlag.

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A systematic use of the Monte Carlo method appeared since the early days of electronic computing and since then it is more present in different scientific research fields. Therefore, many techniques were developed based on this method and one of them is called sequential importance sampling. This technique is an adaptation of the Monte Carlo method that can be used to better extract samples form the domain using an importance weight function.

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We provide the description for the nondeterministic waiting time (NWT) algorithm, a biochemical modeling approach based on the membrane systems paradigm of computation. The technique provides a unique (different to Gillespie's algorithm or ODE modeling) perspective on the biochemical evolution of the cell. That is, depending on the reactions and molecular multiplicities of a given model, our simulator is capable of producing results comparable to the alternative techniques-continuous and deterministic or discrete and stochastic. Some results for sample models are given, illustrating the differences between the NWT algorithm, the Gillespie algorithm, and the solutions to systems of ordinary differential equations. We have previously used this simulation technique to address issues surrounding Fas-induced apoptosis in cancerous cells and so-called latent HIV-infected cells.

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The paper is a survey of the recent model of P systems with proteins on membranes introduced by Paun and Popa in 2006. This model can be viewed as an extension of the highly successful paper of (Paun and Paun 2002) describing P systems based on symport/antiport. The previous model represented an important change of direction from strings to objects in the area of P systems. The main drawback of the model from 2002 was the massive parallelism that is not seen in real life. The 2006 model was a step in controlling the parallelism the same way it is done in nature in symporters and antiporters: these processes take place through protein channels embedded at the level of the membrane which can only be used by a molecule at a time, thus yielding a sequentiality with respect to the number of such proteins embedded in the membrane.

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P systems with proteins on membranes are inspired closely by switching protein channels. This model of membrane computing using membrane division has been previously shown to solve an NP-complete problem in polynomial time. In this paper we characterize the class of problems solvable by these P systems in polynomial time and we show that it equals PSPACE. Therefore, these P systems are computationally equivalent (up to a polynomial time reduction) to the alternating Turing machine or the PRAM computer. The proof technique we employ reveals also some interesting trade-offs between certain P system properties, as antiport rules, membrane labeling by polarization or the presence of proteins. © 2010 Springer-Verlag.

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We present the Nondeterministic Waiting Time algorithm. Our technique for the simulation of biochemical reaction networks has the ability to mimic the Gillespie Algorithm for some networks and solutions to ordinary differential equations for other networks, depending on the rules of the system, the kinetic rates and numbers of molecules. We provide a full description of the algorithm as well as specifics on its implementation. Some results for two well-knownmodels are reported. We have used the algorithm to explore Fas-mediated apoptosis models in cancerous and HIV-1 infected T cells.

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We show that the absolute worst case time complexity for Hopcroft's minimization algorithm applied to unary languages is reached only for deterministic automata or cover automata following the structure of the de Bruijn words. A previous paper by Berstel and Carton gave the example of de Bruijn words as a language that requires O(n log n) steps in the case of deterministic automata by carefully choosing the splitting sets and processing these sets in a FIFO mode for the list of the splitting sets in the algorithm. We refine the previous result by showing that the Berstel/Carton example is actually the absolute worst case time complexity in the case of unary languages for deterministic automata. We show that the same result is valid also for the case of cover automata and an algorithm based on the Hopcroft's method used for minimization of cover automata. We also show that a LIFO implementation for the splitting list will not achieve the same absolute worst time complexity for the case of unary languages both in the case of regular deterministic finite automata or in the case of the deterministic finite cover automata as defined by S. Yu. Published by Elsevier B.V.

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We consider the properties of spiking neural P (SNP) systems that work in a sequential manner. These SNP systems are a class of computing devices recently introduced as a bridge between spiking neural nets and membrane computing. The general sequentiality of these systems was considered previously; now we focus on the sequentiality, induced by the spike number: at each step, the neuron with the maximum (or minimum) number of spikes among the neurons that are active (can spike) will fire. This strategy corresponds to a global view of the whole network that makes the system sequential. We study the properties of this type of a restriction (i.e. considering the case of sequentiality induced by the function maximum defined on numbers of spikes as well as the case of the sequentiality induced by the function minimum similarly defined on numbers of spikes). Several universality results are obtained for the cases of maximum and minimum induced sequentiality. (C) 2009 Elsevier B.V. All rights reserved.

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We consider the absolute worst case time complexity for Hopcroft's minimization algorithm applied to unary languages (or a modification of this algorithm for cover automata minimization). We show that in this setting the worst case is reached only for deterministic automata or cover automata following the structure of the de Bruijn words. We refine a previous result by showing that the Berstel/Carton example reported before is actually the absolute worst case time complexity in the case of unary languages for deterministic automata. We show that the same result is valid also when considering the setting of cover automata and an algorithm based on the Hopcroft's method used for minimization of cover automata. We also show that a LIFO implementation for the splitting list is desirable for the case of unary languages in the setting of deterministic finite automata.

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Computer modeling of molecular signalling cascades can provide useful insight into the underlying complexities of biological systems. We present a refined approach for the discrete modeling of protein interaction within the environment of a single cell. The technique we offer utilizes the Membrane Systems paradigm which, due to its hierarchical structure, lends itself readily to mimic the behavior of cells. Since our approach terministic ordinary differential equations techniques. We argue that our approach may outperform ordinary differential equations when modeling systems with relatively low numbers of molecules - a frequent occurrence in cellular signaling cascades. Refinements over our previous modeling efforts include the addition of nondeterminism for handling reaction competition over limited reactants, increased efficiency in the storing and storing of reaction waiting times, and modifications of the model reactions. Results of our discrete simulation of the type I and type II Fas-mediated apoptotic signaling cascade are illustrated and compared with two approaches: one based on ordinary differential equations and another based on the well-known Gillespie algorithm.

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Membrane computing is a branch of natural computing which abstracts computing models from the structure and the functioning of the living cell. The main ingredients of membrane systems, called P systems, are (i) the membrane structure, which consists of a hierarchical arrangements of membranes which delimit compartments where (ii) multisets of symbols, called objects, evolve according to (iii) sets of rules which are localised and associated with compartments. By using the rules in a nondeterministic/deterministic maximally parallel manner, transitions between the system configurations can be obtained. A sequence of transitions is a computation of how the system is evolving. Various ways of controlling the transfer of objects from one membrane to another and applying the rules, as well as possibilities to dissolve, divide or create membranes have been studied. Membrane systems have a great potential for implementing massively concurrent systems in an efficient way that would allow us to solve currently intractable problems once future biotechnology gives way to a practical bio-realization. In this paper we survey some interesting and fundamental complexity issues such as universality vs. nonuniversality, determinism vs. nondeterminism, membrane and alphabet size hierarchies, characterizations of context-sensitive languages and other language classes and various notions of parallelism.

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We consider once again the membrane systems with proteins on membranes. This model is bridging the membrane systems and brane calculi areas together, thus it is interesting to study it in more depth. We improve previous results in the area and also define a new variant of these systems based on time as the output of the computation. The new model allows (due to its flexibility) even stronger improvements with respect to the number of proteins needed to perform the computation.