Identifying Priority Areas for the Indian Leopard (Panthera pardus fusca) Within a Shared Landscape by Aparna Kolekar, Kimberley Hockings, Kristian Metcalfe, Sanjay Gubbi

“…Environment variables were chosen to reflect land use, climatic, topographic, and human disturbances that could affect habitat selection at a resolution of 0.1 km2. The mean ensemble model was projected to the state of Karnataka. Habitat selection predicted by the ensemble model was driven by proximity to forest cover and rocky outcrops, higher precipitation, and negatively by distance to cropland and roads. …”
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Vision transformer-based diagnosis of lumbar disc herniation with grad-CAM interpretability in CT imaging by Qingsong Chu, Xingyu Wang, Hao Lv, Yao Zhou, Ting Jiang

“…The performance of the model was further validated via gradient-weighted class activation mapping (Grad-CAM), providing interpretable insights into the regions of the CT scans that contributed to the model predictions. …”
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Estimating canopy height in tropical forests: Integrating airborne LiDAR and multi-spectral optical data with machine learning by Brianna J. Pickstone, Hugh A. Graham, Andrew M. Cunliffe

“…Overall, this study reveals that the inclusion of PlanetScope and the application of more complex CNN models is not necessary for canopy height predictions in tropical forests, as open-access optical data combined with simpler tree-based models, such as RF, demonstrate comparable performance.…”
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Carbonate Seismic Facies Analysis in Reservoir Characterization: A Machine Learning Approach with Integration of Reservoir Mineralogy and Porosity by Papa Owusu, Abdelmoneam Raef, Essam Sharaf

“…This comparative ML, which was leveraged with seismic resolution data preconditioning, predicted geologically plausible seismic facies, i.e., seismic facies with spatial continuity, consistent morphology across seismic bands, and two ML algorithms. …”
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BathyFormer: A Transformer-Based Deep Learning Method to Map Nearshore Bathymetry with High-Resolution Multispectral Satellite Imagery by Zhonghui Lv, Julie Herman, Ethan Brewer, Karinna Nunez, Dan Runfola

“…The model learns to predict water depths by analyzing the spectral signatures and spatial patterns present in the multispectral imagery. …”
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Evaluating the impact of watershed management on surface soil moisture in the Kulfo watershed, Ethiopia by Aklilu Assefa Tilahun, Wondafrash Atnafu Zewde, Bizuayehu Abera Ersuncho

“…The results revealed strong agreement between the SSM predicted by the model and the SSM observed on the ground. …”
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A Multidimensional Analysis Approach Toward Sea Cliff Erosion Forecasting by Maria Krivova, Michael J. Olsen, Ben A. Leshchinsky

“…This outcome is contingent on the condition that the time between the epochs used for prediction and the forecasted epochs does not increase.…”
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Quantitative Rockfall Hazard Assessment of the Norwegian Road Network and Residences at an Indicative Level from Simulated Trajectories by François Noël, Synnøve Flugekvam Nordang

“…It details how the temporal hazard component, related to the likelihood of failure, can be distributed spatially using simulated trajectories. The method can be applied with results from any process-based software and combined with various prediction methods of the temporal aspect, although this aspect is not the primary focus. …”
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A linear perception-action mapping accounts for response range-dependent biases in heading estimation from optic flow. by Qi Sun, Ling-Hao Xu, Alan A Stocker

“…This simple perception-action model accurately predicts participants' estimates both in terms of mean and variance across all experimental conditions. …”
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Stress generation, relaxation and size control in confined tumor growth. by Huaming Yan, Daniel Ramirez-Guerrero, John Lowengrub, Min Wu

“…Our study provides insight on how the biophysical properties of the tumor and host microenvironment, mechanical feedback control and diffusion-limited differential growth act in concert to regulate spatial patterns of stress and growth. When the tumor is stiffer than the host, our model predicts tumors are more able to change their size and mechanical state autonomously, which may help to explain why increased tumor stiffness is an established hallmark of malignant tumors.…”
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The trans-european catchment area of common noctule bats killed by wind turbines in France by Maela Merlet, David X. Soto, Laurent Arthur, Christian C. Voigt

“…We analysed stable hydrogen isotopes in the fur keratin of 60 common noctule bats ( Nyctalus noctula ) killed by wind turbines during summer migration in four regions of France to predict their geographic origin using models based on precipitation isoscapes. …”
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Increased thermal suitability elevates the risk of dengue transmission across the mid hills of Nepal. by Bipin Kumar Acharya, Laxman Khanal, Meghnath Dhimal

“…In this study, we utilized Moderate Resolution Imaging Spectroradiometer (MODIS) satellite land surface temperature (LST) data (MOD11A2) and a temperature-dependent mechanistic model (R0) to predict the monthly suitability for dengue transmission in Nepal from 2001 to 2020 for both mosquito vectors, Aedes aegypti and Ae. albopictus. …”
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Color polymorphic carnivores have faster speciation rates by Moritz M. Heuer, Klaus Fischer, Laura Tensen

“…Therefore, other selective forces than spatial niche segregation, such as predator-prey coevolution, may contribute to color polymorphism in wild carnivores.…”
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OSMlanduse a dataset of European Union land use at 10 m resolution derived from OpenStreetMap and Sentinel-2 by Michael Schultz, Hao Li, Zhaoyan Wu, Daniel Wiell, Michael Auer, Zipf Alexander

“…These labels served as training data for a classification model, predicting land use in remaining areas. Country-specific deep learning convolutional neural networks and Sentinel-2 feature space composites of 2020 at 10 m resolution were employed. …”
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A novel dual-branch network for comprehensive spatiotemporal information integration for EEG-based epileptic seizure detection. by Xiaobing Deng

“…To improve the lives of these patients, it is necessary to develop accurate methods to predict seizures. Electroencephalography (EEG), as a non-invasive and real-time technique, is crucial for the early diagnosis of epileptic seizures by monitoring abnormal brain activity associated with seizures. …”
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Geography is a stronger predictor of diversification of monogenean parasites (Platyhelminthes) than host relatedness in characin fishes of Middle America. by Fernando Alda, Edgar F Mendoza-Franco, William Hanson-Regan, Ruth G Reina, Eldredge Bermingham, MarkE Torchin

“…At this taxonomical scale, host-switching is mediated by the geographical proximity of potential hosts, underscoring the importance of spatial factors in parasite evolution.…”
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RGB-D Image Saliency Detection Based on Multi-branch Backbone Supervised Network by WANG Wei-bing, ZHANG Xiao-zhuo, DENG Qiang

“…Each fusion group is supervised by the upper level fusion result and truth map, and finally the predicted saliency map is obtained iteratively. Experiments on four representative data sets show that compared with the current advanced RGB-D image saliency detection model. …”
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Studying and Analyzing Regional Inequalities (case study: cities of Ardabil province, Iran 2006 – 2011) by Bahram Imani, Roghayyeh Farshi, Reza Hashemi Masoomabad

“…In this study, to show the inequality between different cities in Ardebil province, 60 developmental indicators in different sections including health care, social, educational, cultural and infrastructural sections have been analyzed through VIKOR model. …”
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A Multi-Modal Attentive Framework That Can Interpret Text (MMAT) by Vijay Kumari, Sarthak Gupta, Yashvardhan Sharma, Lavika Goel

“…The proposed model uses the dynamic pointer network instead of classification for iterative answer prediction with a focal loss function to overcome the class imbalance problem. …”
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Estimation of long-term gridded cloud radiative kernel and radiative effects based on cloud fraction by X. Liu, T. He, Q. Wang, X. Xiao, Y. Ma, Y. Wang, S. Luo, L. Du, Z. Wu, Z. Wu

“…By leveraging the correlation between the top-of-atmosphere (TOA) shortwave radiative parameters and surface radiation, combined with high-precision fused CF datasets from multiple satellite sources, we construct a CF-dependent model to refine DSSR estimates. Based on this model, we construct GCF-CRKs using the CF as the sole perturbation parameter to isolate the CF CRE. …”
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