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Background The European Union (EU) faces many health-related challenges. Burden of diseases information and the resulting trends over time are essential for health planning. This paper reports estimates of disease burden in the EU and individual 27 EU countries in 2019, and compares them with those in 2010.Methods We used the Global Burden of Disease 2019 study estimates and 95% uncertainty intervals for the whole EU and each country to evaluate age-standardised death, years of life lost (YLLs), years lived with disability (YLDs) and disability-adjusted life years (DALYs) rates for Level 2 causes, as well as life expectancy and healthy life expectancy (HALE).Results In 2019, the age-standardised death and DALY rates in the EU were 465.8 deaths and 20,251.0 DALYs per 100,000 inhabitants, respectively. Between 2010 and 2019, there were significant decreases in age-standardised death and YLL rates across EU countries. However, YLD rates remained mainly unchanged. The largest decreases in age-standardised DALY rates were observed for HIV/AIDS and sexually transmitted diseases and transport injuries (each -19%). Diabetes and kidney diseases showed a significant increase for age-standardised DALY rates across the EU (3.5%). In addition, mental disorders showed an increasing age-standardised YLL rate (14.5%).Conclusions There was a clear trend towards improvement in the overall health status of the EU but with differences between countries. EU health policymakers need to address the burden of diseases, paying specific attention to causes such as mental disorders. There are many opportunities for mutual learning among otherwise similar countries with different patterns of disease. center dot This article, systematically analysing GBD 2019 study estimates, presents an overview of the state of health in the European Union in 2019, compared to 2010.center dot There was an improvement in the overall health status of the EU, despite substantial differences between Member States.center dot Cardiovascular diseases and neoplasms are the major contributors to the overall burden of diseases in the EU in 2019.center dot The age-standardised rate of years lived with disability due to mental disorders has been increasing and is expected to increase even more because of the COVID-19 pandemic.center dot This report provides a framework upon which to base further region- and country-specific health policies and interventions, to support health planning and priority setting.

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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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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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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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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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Background The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic; characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic; and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings In 2019, at the onset of the COVID-19 pandemic, US$9 center dot 2 trillion (95% uncertainty interval [UI] 9 center dot 1-9 center dot 3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7 center dot 3 trillion (95% UI 7 center dot 2-7 center dot 4) in 2019; 293 center dot 7 times the $24 center dot 8 billion (95% UI 24 center dot 3-25 center dot 3) spent by low-income countries in 2019. That same year, $43 center dot 1 billion in development assistance was provided to maintain or improve health. The pandemic led to an unprecedented increase in development assistance targeted towards health; in 2020 and 2021, $1 center dot 8 billion in DAH contributions was provided towards pandemic preparedness in LMICs, and $37 center dot 8 billion was provided for the health-related COVID-19 response. Although the support for pandemic preparedness is 12 center dot 2% of the recommended target by the High-Level Independent Panel (HLIP), the support provided for the health -related COVID-19 response is 252 center dot 2% of the recommended target. Additionally, projected spending estimates suggest that between 2022 and 2026, governments in 17 (95% UI 11-21) of the 137 LMICs will observe an increase in national government health spending equivalent to an addition of 1% of GDP, as recommended by the HLIP. Interpretation There was an unprecedented scale-up in DAH in 2020 and 2021. We have a unique opportunity at this time to sustain funding for crucial global health functions, including pandemic preparedness. However, historical patterns of underfunding of pandemic preparedness suggest that deliberate effort must be made to ensure funding is maintained.

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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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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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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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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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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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Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

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Background: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk–outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings: Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01–4·94) deaths and 105 million (95·0–116) DALYs for both sexes combined, representing 44·4% (41·3–48·4) of all cancer deaths and 42·0% (39·1–45·6) of all DALYs. There were 2·88 million (2·60–3·18) risk-attributable cancer deaths in males (50·6% [47·8–54·1] of all male cancer deaths) and 1·58 million (1·36–1·84) risk-attributable cancer deaths in females (36·3% [32·5–41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6–28·4) and DALYs by 16·8% (8·8–25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9–42·8] and 33·3% [25·8–42·0]). Interpretation: The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Funding: Bill & Melinda Gates Foundation. © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

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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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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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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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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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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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Due to the wide worldwide spread the COVID-19 pandemic has reached at the beginning of 2020, many countries have imposed strict measures of social distancing, the result of which was a sudden shift towards the online environment for most institutions of each state. This study explores students' perception of the quality of online education during the COVID-19 pandemic, right after the shift from traditional face-to-face learning to online education. Using an online questionnaire, feedback from the respondents regarding their perception of online education, sources of information used and preventive behavior is collected. A total of 238 students from different levels and fields participated in the study which concludes with a general opinion reflecting that although in favor of online education, students are unsure if the quality of it matches the quality of the traditional face-to-face education.

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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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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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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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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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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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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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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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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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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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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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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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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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The paper deals with the cellulase-mediated hydrolysis applied to several residual biomass resulting after extraction of biologically active principles from three medicinal plants: Melissa officinalis L., Melilotus officinalis L., Viola tricolor L. The yield of hydrolysis to hexoses was determined based on the amount of free glucose in the reaction mixture identified by spectrophotometric analysis, and total conversion of biomass residues was calculated. It was found that biomass resulted from Viola tricolor L. exhibits best glucose amount (10.35%) after 1 h of enzymatic hydrolysis, while that sourced from Melissa officinalis L. gives the highest total conversion of solid biomass (82.13%).

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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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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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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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The paper summarises the results of the 478 projects from the FP7-ENVIRONMENT proiect, DANube macroregion: Capacity building and Excellence in River Systems (basin, delta and sea) DANCERS database considering different attributes recorded for these projects. An analysis is performed on the recorded data and the significant characteristics are presented. The analysis performs a research output assessment in order to quantify the success of the projects. Trends are identified not only by thematic area and region of implementation, but also by coordinating country region and level of financing. A need to homogenising the level of financing as well as the level of funding efforts among the EU Strategy for the Danube Region (EUSDR) countries and not only, transpires at the end of the analysis. A concentrated effort towards inter and intra disciplinary collaboration as well as within and between institutional collaboration and knowledge sharing is also apparent.

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High Performance Computing applications on Cloud are of significance because of cost-effectiveness and elasticity. Reliability analysis of HPC applications on Cloud is an important areof study to better utilize infrastructure while dealing fault tolerant issues in a Cloud environment. In this work, we present a reliability model of a Cloud system under four scenarios: 1) Hardware components fail independently and software components fail independently; 2) software components fail independently and hardware components are correlated in failure; 3) correlated software failure and independent hardware failure; 4) dependent software and hardware failures. Moreover, we propose an optimal checkpoint placement technique based on reliability information for each scenario. Results show that if failure of the nodes and/or software in the system possesses a degree of dependency, the system becomes less reliable, which means that the failure rate increases and the mean time to failure decreases. Also, an increase in the number of nodes decreases there liability of the system. Moreover, the optimal checkpoint interval decreases when the reliability of the system decreases.

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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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Purpose - The purpose of this paper is to develop and empirically test a new framework that shows how different signals of movie quality along with key control variables affect consumers' post-consumption evaluations, critics' reviews (CR), and movie box office revenues. Design/methodology/approach - The data set consists of a sample of 332 movies released between 2000 and 2008. Regression was used to test the study hypotheses. Findings - The results suggest that the three signals of movie quality exhibit different effects on three movie performance measures. Of the three cues, the peripheral quality signal is positive related to movie box, moviegoers' evaluations (ME), and CR. Furthermore, star performance quality is positive related to both ME and CR. Surprisingly, overall quality signal does not display any influence on movie performances. Research limitations/implications - The primary limitation is the use of cross-sectional study design and future research should apply for time-series technique to test the relationships between movie quality signals and movie performances. Practical implications - The findings suggest that consumers and critics evaluate movie qualities based on various movie quality signals. Furthermore, the characteristics of movies also have mixed impacts on movie performances. Movie studios may take these findings into account to produce better movies. Originality/value - This study proposes and empirically tests the impacts of three groups of movie signals peripheral quality signal, star performance quality signal, and overall quality signal on motion picture performance. This study contributes to service quality literature and signal theory by categorizing different Academy Awards into three groups of quality signals and by empirically testing the proposed relationships.

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Given that the reliability of a very large-scaled system is inversely related to the number of computing elements, fault tolerance has become a major concern in high performance computing including the most recent deployments with graphic processing units (GPUs). Many fault tolerance strategies, such as the checkpoint/restart mechanism, have been studied to mitigate failures within such systems. However, fault tolerance mechanisms generate additional costs and these may cause a significant performance drop if it is not used carefully. This paper presents a novel fault tolerance scheduling model that explores the interplay between the GPGPU application performance and the reliability of a large GPU system. This work focuses on the checkpoint scheduling model that aims to minimize fault tolerance costs. Additionally, a GPU performance analysis is conducted. Furthermore, the effect of a checkpoint/restart mechanism on the application performance is thoroughly studied and discussed.

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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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A high-performance computing (HPC) system, which is composed of a large number of components, is prone to failure. To maximize HPC system utilization, one should understand the failure behavior and the reliability of the system. Studies in the literature show that the time to failure of a node is best described by a Weibull distribution. In this study, we consider, without loss of generality, the Weibull as the distribution of time to failure and develop a reliability model for a system of k nodes where nodes can fail simultaneously. From this model, we develop expressions for the probability of failure of the system at any time t, for the failure rate, and for the mean time to failure. Also, we validate the model by using failure data from the Blue Gene/L logs obtained from the Lawrence Livermore National Laboratory. Results show that if failures of the components (nodes) in the system possess a degree of dependency, the system becomes less reliable, which means that the failure rate increases and the mean time to failure decreases. Also, an increase in the number of nodes decreases the reliability of the system.

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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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An improved biointerface was developed, dynamic layer-by-layer self-assembly surface (d-LbL), and utilized as a biologically-active substrate for platelet adhesion and aggregation. Possible clinical applications for this research include improved anti-coagulation surfaces. This work demonstrated the functionality of d-LbL biointerfaces in the presence of platelet-rich-plasma (PRP) with the addition of 20 mu M adenosine diphosphate (ADP), a thrombus activator. The surface morphology of the experimental control, plain PRP, was compared to PRP containing additional ADP (PRP + ADP) and resulted in an expected increase of platelet adhesions along the fibrinogen d-LbL substrate. The d-LbL process was used to coat glass slides with fibrinogen, Poly (sodium 4-styrene-sulfonate), and Poly (diallydimethlyammonium chloride). Slides were exposed to PRP under flow and static conditions with and without 20 mu M of ADP. Fluorescence microscopy (FM), phase contrast microscopy (PCM), atomic force microscopy (AFM), and field emission-scanning electron microscopy (FE-SEM) were used to evaluate platelet adhesions under the influence of varied shear conditions. PCM images illustrated differences between the standard LbL and d-LbL substrates. FM images provided percent surface coverage values. For high-shear conditions, percent surface coverage values increased when using ADP whereas plain PRP exposure displayed no significant increase. AFM scans also displayed higher mean peak height values and unique surface characteristics for PRP + ADP as opposed to plain PRP. FE-SEM images revealed platelet adhesions along the biointerface and unique characteristics of the d-LbL surface. In conclusion, PRP + ADP was more effective at increasing platelet aggregation, especially under high shear conditions, providing further validation of the improved biointerface.

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With virtualization technology, Cloud computing utilizes resources more efficiently. A physical server can deploy many virtual machines and operating systems. However, with the increase in software and hardware components, more failures are likely to occur in the system. Hence, one should understand failure behavior in the Cloud environment in order to better utilize the cloud resources. In this work, we propose a reliability model and estimate the mean time to failure and failure rate based on a system of k nodes and s virtual machines under four scenarios. Results show that if the failure of the hardware and/or the software in the system exhibits a degree of dependency, the system becomes less reliable, which means that the failure rate of the system increases and the mean time to failure decreases. Additionally, an increase in the number of nodes decreases the reliability of the system. © 2013 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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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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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 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.