Rezumat

The definition of the two-dimensional discrete scan statistic with rectangular window shape is extended to a more general framework. In particular, this approach allows to introduce different shapes for the scanning window (discretized rectangle, polygon, circle, ellipse, or annulus). We provide approximation for the distribution of the scan statistic and illustrate its accuracy by conducting a numerical comparison study. The power of test based on the scan statistics is also evaluated by simulation. © Springer Science+Business Media, LLC, part of Springer Nature 2024.

Rezumat

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.

Rezumat

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.

Rezumat

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.

Rezumat

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.

Rezumat

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.

Rezumat

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.

Rezumat

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.

Rezumat

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.

Rezumat