Area Size Research Articles

2D Nitrogen-Doped Graphene Materials for Noble Gas Separation.

Noble gases, notably xenon, play a pivotal role in diverse high-tech applications. However, manufacturing xenon is an inherently challenging task, due to its unique properties and trace abundance in the Earth's atmosphere. Consequently, there is a pressing need for the development of efficient methods for the separation of noble gases. Using mild fluorographene chemistry, nitrogen-doped graphene (GNs) materials are synthesized with abundant aromatic regions and extensive nitrogen doping within the vacancies and holes of the aromatic lattice. Due to the organized interlayer "nanochannels", nitrogen functional groups, and defects within the two-dimensional (2D)structures, GNs exhibits effective selectivity for Xe over Kr at low pressure. This enhanced selectivity is attributed to the stronger binding affinity of Xe to GN compared to Kr. The adsorption is governed by London dispersion forces, as revealed by theoretical calculations using symmetry-adapted perturbation theory (SAPT). Investigation of other GNs differing in nitrogen content, surface area, and pore sizes underscores the significance of nitrogen functional groups, defects, and interlayer nanochannels over thesurface area in achieving superior selectivity. This work offers a new perspective on the design and fabrication of functionalized graphene derivatives, exhibiting superior noble gas storage and separation activity exploitable in gas production technologies.

Developing a Model to Study Walking and Public Transport to Attractive Green Spaces for Equitable Access to Health and Socializing Opportunities as a Response to Climate Change: Testing the Model in Pu’er City, China

Green space is not always equitably located in cities, and the attractiveness of green space varies, leaving some residents with easy access to high-quality parks and others with little or no access or access to under-maintained parks. To remedy these inequities, this study identified attractive and well-utilized recreational green spaces and developed a model to measure the likelihood of using these recreational green spaces (PSG). The goal was to reduce the travel time and cost of walking or using public transportation to get to green spaces and to design all green spaces to be attractive. The data come from the perspective of the city’s public transportation system and residents’ personal choices. First, the attractiveness of recreational green spaces was calculated from big data on the geolocation of cell phones, measuring the level of provision of recreational green spaces and the trip rates of urban residents. After that, the travel cost to reach recreational green space in residential areas was calculated according to residents’ travel habits. Finally, the probability of all recreational green spaces in the city being used was calculated by combining the population size of residential areas. Taking Pu’er City in China as an example, the attractiveness and utilization rates of recreational green spaces were calculated by PSG, and the results of the study showed that the probability of residents choosing to use the recreational green spaces that are closer to the residential area, with a larger population capacity, and with a higher attractiveness is the highest. The results of the study help promote equitable access to health and socialization opportunities for individuals and communities, thereby promoting environmental justice to help mitigate and respond to climate change.

Extraction of methamphetamine and pseudoephedrine by modified graphene oxide solid phase extraction method coupled to HPLC-UV in urine sample.

Methamphetamine, pseudoephedrine, and related drugs are among the first drugs used for the stimulation of the central nervous system. In this study, two adsorbents based on graphene oxide (GO) were synthesized and used for the analysis of methamphetamine and pseudoephedrine. The prepared nano-adsorbents based on GO in this study were coated by polyaniline (PANI) and Fe3O4/C-nanodot/GO (magnetic adsorbent). The average size of nanoparticles (GO/PANI) was 18.43nm. The specific surface area and pore size diameter of Fe3O4/C-nanodot/GO were 22.71 m2 g- 1 and 15.23nm, respectively. Experimental variables affecting the extraction efficiency of the analytes such as pH of the sample solution, amount of adsorbent, extraction time, and type of eluents were investigated and optimized by response surface methodology. Under optimum conditions, GO/PANI and Fe3O4/C-nanodot/GO were considered appropriate solid phase extraction adsorbents for HPLC-based analyses of the studied drugs in human urine samples. However, GO/Fe3O4 nano adsorbent (Fe3O4/C-nanodot/GO) showed superior working condition than GO/PANI. The validated proposed analytical methods can be used for the quantitative determination of methamphetamine and pseudoephedrine in actual samples.

Accumulation of Spherical Microplastics in Earthworms Tissues-Mapping Using Raman Microscopy

The presence of microplastics in the environment is now becoming a challenge for many scientific disciplines. Molecular diversity and spatial migration make it difficult to find plastic-free areas. Their negative, often toxic, effects affect plants and animals to varying degrees, causing many biochemical disorders, species degradation, and population changes. This study aimed to determine the possibility of accumulation of spherical low-density polyethylene particles of 38–63 µm (38–45 µm 1.00 g/cm3, and 53–63 µm 1.00 g/cm3) with fluorescent properties in muscle tissues of the cosmopolitan earthworm species Lumbricus terrestris, exposed to plastic contained in the soil at a concentration of 0.1% dry weight for 3 months. Analysis of the tissues by Raman microscopy included the estimation of mapping area size, sampling density, accumulation time, spectra, laser line, and laser power to detect plastic in the samples effectively. Our results demonstrate the ability of low-density polyethylene microparticles to accumulate in earthworm tissues and are presented graphically for the mapping area and images with plastic detection sites marked. In addition, this article highlights the potential of using Raman microscopy for research in the field of tissue analysis.

A 3D modelling approach to measuring structural characteristics of bird nest interiors

Abstract Nests are considered extended phenotypes of animals with potentially serious fitness consequences for the survival of offspring. Therefore, nest characteristics may contain valuable information about the underlying ecological and evolutionary mechanisms shaping animal reproduction. However, we currently lack efficient tools to archive nests and measure their characteristics, particularly concerning enclosed nests. Here we developed a step‐by‐step protocol of a 3D modelling approach to measure structural characteristics of nest interiors using the enclosed, dome‐shaped nests of Asian house martins as a test system. We first created the replicas of nest interiors using polyurethane (‘physical replicas’), from which 3D models were constructured using Metashape software (‘digital replicas’). We then estimated the volume and entrance area size of the digital replicas of nest interior using Metashape. To verify that the digital replicas preserve the structural characteristics of the physical replicas, we measured the volume and entrance area size of the physical replicas with Archimedes' drainage method and ImageJ, respectively. We then compared the manual measurements of the physical replicas to the values estimated from digital replicas. The estimates on the interior volume and entrance area size of 50 Asian house martin nests were nearly identical between physical and digital replicas. These results verified that the digital replicas are as reliable as the physical replicas for measuring structural characteristics of nest interior. Our 3D modelling approach allows for easy archiving as digital replicas of nest interiors endure preservation over time much better than actual nest specimens. Furthermore, digital replicas can be shared via internet and analysed for different aspects of morphometrics at any time by anyone. Overall, this tool should facilitate research on the ecology and evolution of animals in relation to nest construction.

Development, characterization, and comparison of chitosan microparticles as a carrier system for black bean protein hydrolysates with antioxidant capacity.

Peptides in black bean protein hydrolysates (BPHs) exert antioxidant capacity. However, peptides are prone to degradation during processing and digestion. Chitosan (Ch) can protect them and provide a delayed release. This work develops and compares two drying methods producing porous structured Ch microparticles (MPs) as carriers for antioxidant BPH. Ch gels were obtained by ionic gelation and dried by supercritical CO2 solvent displacement or fast-freeze-drying methods. The resulting aerogels and fast-freeze-dried MPs were structurally characterized, and their swelling and release profiles were obtained at pH 1.2 and 7.4. The antioxidant capacity of systems was determined by 2,2'-azino-bis(3-ethyl-benzthiazoline-6-sulphonic acid) (ABTS) and superoxide radical assays. The results showed BPH-Ch best complexation conditions occurring at a pH of 4.5 and a 4:1 BPH/Ch ratio. The particle size of the complex was 1047.6nm, and the entrapment efficiency and loading capacity were 28.2% and 54.3%, respectively. At pH 1.2 and 7.4, the release rate of BPH was lower in aerogel than in fast-freeze-dried MPs. Besides, entrapment BPH in Ch significantly reduced the ABTS antioxidant activity IC50 from 35.1µM Trolox equivalents (TE)/mg to 250.7 and 406.2µM TE/mg for Ch fast-freeze-dried and aerogels, respectively. Superoxide radical inhibition IC50 ranged from 74.6 to 92.9mM ascorbic acid equivalents/mg in the different samples. BPH-loaded aerogels presented lower specific surface area (94.7 vs. 138.6m2/g, p<0.05) and higher average pore size (26.4 vs. 19.8nm) than Ch aerogels. Ch aerogel is a promising carrier for delaying the release of common bean antioxidant peptides useful for developing functional foods. PRACTICAL APPLICATION: This novel system could act as an ingredient to incorporate antioxidant compounds in different formats to develop delayed-release nutraceuticals and functional foods, such as bakery, dairy products, or beverages. Along, antioxidant peptide-loaded aerogels could be used as a slow-release system for compounds acting as natural preserving antioxidants for food applications such as raw meat products or high-fat foods.

Impact analysis of particle sphericity on the properties of porous materials via particle packing method for hydrogen fuel and electrolysis cells

This study focuses on the impacts of particle's sphericity on the properties of porous materials crucial to electrochemical devices. Three-dimensional structures with spherical and cylindrical particles were generated to simulate porous granular and fibrous materials. The constructed particle geometries are as follows: a sphere and cylinders with different aspect ratios (height-to-diameter) of 0.1, 0.5, 1.0, 2.5, 5.0, 10, and 20. Every model exhibits a porosity of 0.500 ± 0.001 to exclude the effects of porosity. The structures were binarized with 200×200×200 dimensionless voxels, which were analyzed with the specific surface area, grain and pore size distributions, geometrical tortuosity, conductivity, and diffusivity across the through- and in-planes. As a result, the particle geometry significantly impacts on tortuosity, conductivity, and diffusivity, with the absolute value of Spearman's correlation coefficient of up to 1. It may imply the necessity to consider particle geometry as an ex-situ characterization for better electrochemical performance.

Agmatine: An Emerging Approach for Neuroprotection in Recurrent Ischemic Stroke Events in a Murine Model.

This study investigates the effect of agmatine on reducing mortality, neurobehavioral alterations, infarct size, and expression of pro-inflammatory cytokines in mice subjected to bilateral carotid thrombosis. Under pentobarbital anesthesia, the left common carotid artery was exposed to 6% FeCl3. Thirty-two days later, the same procedure was performed on the right common carotid artery. Subsequently, Agmatine (100 mg/kg) was administered 15 min after the second procedure, and in another experimental group, the dose of Agmatine was repeated at 72 h. Administration of agmatine extended survival in ischemic animals up to 72 h for the single-dose group and up to 96 h for the repeated-dose group, without significant increases in neurological deficits or infarct area size. This neurobehavioral effect was also observed in sham animals treated with agmatine. In ischemic animals, agmatine administration improved digging behavior and reduced recovery times, consistently shorter in those animals treated with repeated doses. RT-PCR analyses revealed a positive regulation of the cytokine IL-1β in agmatine-treated animals, which has been associated with recovery stages. The results suggest that the observed effect may be attributed to the multiple interactions of agmatine with ischemic cascade events, highlighting its anti-inflammatory role.

Unmasking population undercounts, health inequities, and health service access barriers across Indigenous populations in urban Ontario.

Our Health Counts (OHC) methods are designed to address gaps in urban-based Indigenous health information. In partnership with local Indigenous health service providers, we have successfully implemented OHC in six Ontario cities. The aim of this study is to summarize findings regarding Indigenous population undercount, health inequities, and health service access barriers across study sites. We estimated Indigenous population size using OHC census participation survey responses and a multiplier approach. Health inequities between Indigenous populations and overall populations in each city were examined using respondent-driven sampling (RDS), adjusted OHC survey results, and existing public data. Measures included health status outcomes; determinants of health; barriers to health service access, including discrimination by health service providers; and unmet health needs. Indigenous social networks were strong and extensive, and the urban populations demonstrate resilience and cultural continuity across multiple measures. Self-reported rates of census participation for Indigenous populations were markedly lower than those for the general population in each city, and OHC Indigenous population size estimates were consistently 2‒4 times higher than reported in the census. Indigenous to general population health inequities cut across measures of chronic disease, determinants of health, and unmet health needs. Indigenous populations experienced multiple barriers to health services access, including racial discrimination by health service providers. The Canadian census appears to markedly underestimate Indigenous population size in urban areas. Indigenous health inequities and service access barriers are striking and cross-cutting. Timely adaptation of health policies, services, and funding allocations in response to these findings is recommended.

3Density estimation using spatial capture‐recapture analyses: application to vaccination of prairie dogs against sylvatic plague

AbstractPrairie dogs are notoriously difficult to enumerate, with previously methods including visual counts, mark‐resight, burrow counts, and catch per unit effort. Unlike those methods, spatial capture‐recapture (SCR) analyses allow for formal estimation of density along with associated estimates of uncertainty, detection probability, and the size of the average area over which an individual was detected during the study period (referred to as an activity center). Using SCR analyses, we compared density estimates as part of a field trial evaluating the effectiveness of an oral sylvatic plague vaccine in black‐tailed prairie dogs (Cynomys ludovicianus), Gunnison's prairie dogs (C. gunnisoni), white‐tailed prairie dogs (C. leucurus), and Utah prairie dogs (C. parvidens) at 11 study areas in the western United States. The study was designed as a matched pairs analysis that included 27 individual paired plots (54 plots), each consisting of a plot treated with vaccine baits and a plot treated with placebo baits. Overall, we captured &gt;3,000 individuals each year on these plots, and recapture rates ranged from 5–87%. For black‐tailed prairie dogs, density estimates ranged from 2.7 individuals/ha (95% CI = 2.2–3.3/ha) to 77.3/ha (63.2–94.4/ha), and for Gunnison's prairie dogs, estimates ranged from 11.7/ha (10.6–12.8/ha) to 15.4/ha (14.4–16.7/ha). White‐tailed prairie dogs were at their lowest density (3.3/ha, 95% CI = 2.9–3.8/ha) during the first year of the study and their highest density (14.5/ha; 13.5–15.6/ha) during the last year of the study. Utah prairie dog density estimates ranged from a low of 4.0/ha (95% CI = 3.55–4.6/ha) to a high of 20.8/ha (16.8–25.8/ha). Best‐fitting models of prairie dog density indicated increasing patterns of density over time on most study plots, negative effects of plague, and positive effects of vaccination. Finally, we found low correlations between catch per unit effort estimates from previous published literature at these sites and our densities estimates. Spatial capture‐recapture estimates allowed us to consistently compare treatment effects across space and time, although some exceptions are noted where we observed significant movement between plots within a pair (3 pairs) and when trapping effort between plots or years was not consistent.

Nanomaterial Texture-Based Machine Learning of Ciprofloxacin Adsorption on Nanoporous Carbon

Drug substances in water bodies and groundwater have become a significant threat to the surrounding environment. This study focuses on the ability of the nanoporous carbon materials to remove ciprofloxacin from aqueous solutions under specific experimental conditions and on the development of the mathematical model that would allow describing the molecular interactions of the adsorption process and calculating the adsorption capacity of the material. Thus, based on the adsorption measurements of the 87 carbon materials, it was found that, depending on the porosity and pore size distribution, adsorption capacity values varied between 55 and 495 mg g−1. For a more detailed analysis of the effects of different carbon textures and pores characteristics, a Quantitative nano-Structure–Property Relationship (QnSPR) was developed to describe and predict the ability of a nanoporous carbon material to remove ciprofloxacin from aqueous solutions. The adsorption capacity of potential nanoporous carbon-based adsorbents for the removal of ciprofloxacin was shown to be sufficiently accurately described by a three-parameter multi-linear QnSPR equation (R2 = 0.70). This description was achieved only with parameters describing the texture of the carbon material such as specific surface area (Sdft) and pore size fractions of 1.1–1.2 nm (VN21.1–1.2) and 3.3–3.4 nm (VN23.3−3.4) for pores.

Application of Modified Silica as an Efficient Slow-Release Carrier Medium: A Review

The use of mesoporous material as a carrier is increasingly gaining significant attention in recent years. The carrier often exists in the form of organic polymers, including chitosan and starch-g-poly (L-lactide), as well as inorganic substances, namely zeolites, sulfur, and silica. In this context, silica has the greatest abundance in nature and is extensively applied as a carrier medium due to its high selectivity, excellent regeneration ability, and environmental friendliness. However, this material shows some limitations, such as high surface tension and large inter-particle bonding forces, which can be addressed through modifications of the surface area and pore size by adding surfactants. The modifications will transform silica into a mesoporous structure, suitable for use as a slow-release carrier in various applications, including catalysts, sensors, adsorbents, chromatography, drug delivery systems, and intelligent corrosion inhibitors.

Reaction-diffusion for fish populations with realistic mobility

Nonlinear reaction-diffusion equations, with Fisher logistic growth and constant diffusion coefficient, have been used in fisheries research to estimate sustainable harvesting rates and critical domain sizes of no-take areas. However, constant diffusivity in a population density corresponds to standard Brownian motion of individuals, with a normal distribution for displacement over a fixed time interval. For available good data sets on mobile fish populations, the distribution is certainly not normal. The data can be fitted with a long-tailed stable Lévy distribution that results from diffusion by fractional Laplacian. Exact multidimensional solutions are developed here for realistic Fisher–Kolmogorov–Petrovski-Piscounov models with diffusion by fractional Laplacian. These can also account for a delay in the reaction term. It is then shown how to modify critical domain sizes of protected areas with Dirichlet and Robin boundary conditions for populations.

Exploring the impact on contact adhesion layer properties in numerical simulations.

This paper presents a comprehensive investigation into the impact of key parameters on contact adhesion layer properties using numerical simulations, addressing fundamental questions in contact mechanics. Aiming to explore interfacial penetration and contact pressure dynamics between a wavy punch and an adhesive-coated body, the study focuses on the influence of adhesive layer thickness, elasticity modulus, and punch geometry on mechanical behavior. The study includes the application of Green's function to address deficiencies in existing models, revealing how contact stiffness, influenced by the flexibility relationship between the coating and substrate, affects the size of the contact area. Finally, conclusions are drawn that adjusting coating factors can induce full contact conditions. Quantitative analysis shows a 2.23-fold increase in load-bearing capacity with a 2 mm increase in adhesive layer thickness, and a 23-fold increase with a toughness ratio rise from 0.1 to 5. These findings are recommended for optimizing adhesive layer properties, contributing to advancements in materials science and innovation.

The occurrence of atrioventricular nodal reentrant tachycardia requires not only the electrophysiological substrate but also the electro-anatomical characteristics in the triangle of Koch

Abstract Background Some patients do not develop atrioventricular nodal reentrant tachycardia (AVNRT) clinically despite having the electrophysiological substrate for AVNRT; however, the cause remains unclear. Recently, the conduction to the slow pathway has been reported to be visualized using high-density mapping in the triangle of Koch (ToK) during sinus rhythm. Purpose To investigate whether the conduction to the slow pathway is associated with the occurrence of AVNRT. Methods We studied 83 patients (55 males, 67 ± 13 years, 10 with typical AVNRT, 66 atrial fibrillation; AF, 5 atrioventricular reentrant tachycardia; AVRT, and 2 Atrial Flitter) who received electrophysiological test and high-density mapping in the ToK during sinus rhythm. The conduction pattern to the slow pathway, rotating around the end (pivot point: PP) of the functional block line (FBL), was evaluated using the Advisor HD Grid mapping catheter. Results 10 out of 10 AVNRT (100%), 17 of 66 AF (26%), and 1 of 4 AVRT showed PP and FBL (p&amp;lt;0.0001). 21 out of 21 (10 AVNRT and 11 AF) with the jump-up phenomenon in atrioventricular conduction indicated PP and FBL (100%), meanwhile 7 of 62 without jump-up phenomenon showed PP and FBL (11%) (p&amp;lt;0.0001). Among patients (10 AVNRT and 9 AF) who had the electrophysiological substrate for AVNRT (jump-up phenomenon and retrograde ventriculoarterial conduction), patients with AVNRT had a longer distance from PP to the tricuspid annulus; TA (16.9mm vs, 13.4mm, p=0.0116) than patients with non-AVNRT. There were no differences in the length of FBI, distance and conduction time from His to PP, distance and conduction time from PP to CS ostial, and the area size of ToK. All AVNRT patients underwent linear ablation from PP to TA and showed loss of atrial potential in the region between PP, TA, and His, AVNRT was no longer provoked, and in 8 out of 10 patients, a jump-up phenomenon disappeared. Conclusion Patients with AVNRT showed a functional block line and a longer distance from the pivot point to the tricuspid annulus. The occurrence of AVNRT requires not only the electrophysiological substrate but also the electro-anatomical characteristics, especially in the triangle of Koch.

DMA‐Net: A dual branch encoder and multi‐scale cross attention fusion network for skin lesion segmentation

AbstractAutomatic segmentation of skin lesion is an important step in computer‐aided diagnosis. However, due to the significant variations in the size and shape of the lesion areas, as well as the low contrast with normal skin tissue, the boundaries are not clearly distinguishable, leading to a high possibility of incorrect segmentation. Therefore, this task is highly challenging. To overcome these difficulties, this paper proposes a medical image segmentation architecture named dual branch encoder and multi‐scale cross attention fusion network, which includes a dual‐branch encoder based on convolutional neural network and an improved channel‐enhanced Mamba to comprehensively extract local and global information from dermoscopy images. Additionally, to enhance the feature interaction and fusion of local and global information, a multi‐scale cross attention fusion module is adopted to cross‐merge features in different directions and at different scales, maximizing the advantages of the dual‐branch encoder and achieving precise segmentation of skin lesions. Extensive experiments are conducted on three public skin lesion datasets: ISIC‐2018, ISIC‐2017, and ISIC‐2016, to verify the effectiveness and superiority of the proposed method. The dice similarity coefficient scores on the three datasets reached 81.77%, 81.68% and 85.60%, respectively, surpassing most state‐of‐the‐art methods.

Preparation of monolithic silica HPLC columns with truss-structured skeletons and embedded surfactant-templated mesopores

AbstractMonolithic macro/mesoporous silica gels have been prepared via a sol-gel process using triblock copolymer Pluronic P123 (EO20PO70EO20) as a structure-directing agent. In this synthesis, P123 not only induces phase separation to form macroporous structure but also acts as a supramolecular template to form mesopores with precisely controlled shape and size. Obtained was a monolithic silica composed of continuous truss-like columnar skeletons in which cylindrical mesopores are arranged in a 2D-hexagonal symmetry. These monolithic silica gels have extremely high porosity approaching 90% and exhibited high specific surface area and sharp pore size distribution as revealed by N2 sorption measurements. Combinations of the initial composition and the post-gelation treatment on wet gels allowed the control of physical properties of meso- and macropore structures. The monolithic HPLC columns prepared using these silica gels surface-modified by ODS (octadecylsilyl) ligands gave as many as 140,000 theoretical plates/m for the separation of alkylbenzenes in a reversed-phase mode. Very weak dependence of height equivalent to theoretical plate, H, on the mobile phase velocity was also recognized in comparison with conventional particle-packed columns. Graphical Abstract

Analysis of airtightness performance of residential areas in Mediterranean climate: Balıkesir houses

Airtightness is one of the crucial physical characteristics of building envelope that affect the building thermal performance and energy consumption. The airtightness of the building is influenced by the quality of workmanship and various design parameters such as window/wall ratio, type of joinery, size of the usage area, wall material, and thermal insulation on the external wall. In this study aiming to determine the airtightness performance of buildings in the Mediterranean climate of Balıkesir houses, airtightness conditions of 43 different houses were determined by blower door test measurement. The air exchange rate (n50) values of 43 houses/residences were obtained between 1.94 and 49.02 h−1 and compared with the current various standards. The effect level of the design parameters on the air tightness of the building envelope was obtained as a result of the analysis performed with analysis of variance and post hoc methods. According to the analysis, joinery type was the most effective design parameter in terms of airtightness, followed by usage area and transparency of facades. The result will help in deciding on the design parameters affecting the airtightness of the building envelope for energy efficiency in the Mediterranean climate.

Habitat Fragmentation Affects Richness—A View Through a Metacommunity Lens

Habitat fragmentation is often assumed to negatively impact species diversity because smaller, more isolated populations on smaller habitat patches are at a higher extinction risk. However, some empirical and theoretical studies suggest that landscapes with numerous small habitat patches may support higher species richness, although the circumstances remain elusive. We used an agent-based metacommunity model to investigate this and simulate landscapes of the same total area but diverse patch sizes. Our model, as generic and unbiased by specific assumptions as possible, aimed to explore which circumstances may be more conducive to supporting higher biodiversity. To this end, most parameters and behaviors were random. The model included generalized species traits, dispersal, and interactions to explore species richness dynamics in fragmented landscapes of distinct patch sizes. Our results show that landscapes with many small patches maintain higher species richness than those with fewer large patches. Moreover, the relationship between patch connectivity and species richness is more pronounced in landscapes with smaller patches. High connectivity in these landscapes may support species diversity by preventing local extinctions and facilitating recolonization. In contrast, connectivity is less significant in large-patch landscapes, where generalist species dominate. The findings highlight the complex interplay between patch size quality, connectivity, species traits, and diverse interactions among species in determining species richness. We suggest the patterns produced by the model represent null predictions and may be useful as a reference for a diversity of more specialized questions and predictions. These insights may also have specific implications for conservation strategies, suggesting that maintaining a mosaic of small, well-connected patches could enhance biodiversity in fragmented landscapes.

Deep Learning Approaches for Wildfire Severity Prediction: A Comparative Study of Image Segmentation Networks and Visual Transformers on the EO4WildFires Dataset

This paper investigates the applicability of deep learning models for predicting the severity of forest wildfires, utilizing an innovative benchmark dataset called EO4WildFires. EO4WildFires integrates multispectral imagery from Sentinel-2, SAR data from Sentinel-1, and meteorological data from NASA Power annotated with EFFIS data for forest fire detection and size estimation. These data cover 45 countries with a total of 31,730 wildfire events from 2018 to 2022. All of these various sources of data are archived into data cubes, with the intention of assessing wildfire severity by considering both current and historical forest conditions, utilizing a broad range of data including temperature, precipitation, and soil moisture. The experimental setup has been arranged to test the effectiveness of different deep learning architectures in predicting the size and shape of wildfire-burned areas. This study incorporates both image segmentation networks and visual transformers, employing a consistent experimental design across various models to ensure the comparability of the results. Adjustments were made to the training data, such as the exclusion of empty labels and very small events, to refine the focus on more significant wildfire events and potentially improve prediction accuracy. The models’ performance was evaluated using metrics like F1 score, IoU score, and Average Percentage Difference (aPD). These metrics offer a multi-faceted view of model performance, assessing aspects such as precision, sensitivity, and the accuracy of the burned area estimation. Through extensive testing the final model utilizing LinkNet and ResNet-34 as backbones, we obtained the following metric results on the test set: 0.86 F1 score, 0.75 IoU, and 70% aPD. These results were obtained when all of the available samples were used. When the empty labels were absent during the training and testing, the model increased its performance significantly: 0.87 F1 score, 0.77 IoU, and 44.8% aPD. This indicates that the number of samples, as well as their respectively size (area), tend to have an impact on the model’s robustness. This restriction is well known in the remote sensing domain, as accessible, accurately labeled data may be limited. Visual transformers like TeleViT showed potential but underperformed compared to segmentation networks in terms of F1 and IoU scores.