Sugar Maple Litter Decay Rates Are Reduced More Strongly by Drought Than by American Beech Proliferation in the Understory by William F. J. Parsons, Claudele Ghotsa Mekontchou, Audrey Maheu, David Rivest

“…Mass loss did not change with mesh size in a consistent manner over 90 days (initial prediction: L > M > S). We estimated k‐values (year−1) by extending the linearized exponential decay model to 12 Proliferation‐Exclusion‐Species combinations. …”
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Analysis on the Spatiotemporal Characteristics of the Postearthquake Reconstruction Efficiency of the Extremely Earthquake-Stricken Areas by the Wenchuan Earthquake Based on the DE... by Pin Lv, Bin Liu, Mingkang Yuan, Suyue Han, Di Zhang, Lv Zhang

“…In 2011, the reconstruction efficiency basically returned the areas to preearthquake levels, and there was a small fluctuation in efficiency due to the effects of earthquake-induced hazards and the reduction of external forces. Spatially, the reconstruction efficiencies of the 10 extremely stricken areas do not show a “convergence effect,” and the reconstruction efficiencies were closely related to the characteristics of the resources in the extremely stricken areas. …”
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Quantitative 3D reconstruction of viral vector distribution in rodent and ovine brain following local delivery by Roberta Poceviciute, Kenneth Mitchell, Angeliki Maria Nikolakopoulou, Suehyun K. Cho, Xiaobo Ma, Phillip Chen, Samantha Figueroa, Ethan J. Sarmiento, Aryan Singh, Oren Hartstein, William G. Loudon, Florent Cros, Alexander S. Kiselyov

“…This pipeline, which combined existing and newly developed machine-learning and other computational tools, effectively removed false positive artifacts abundant in large-scale images of uncleared tissue sections, and subsampling adequately predicted the dispersion of model viral vectors from the point of local drug delivery. …”
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Statistics and behavior of clinically significant extra-pulmonary vein atrial fibrillation sources: machine-learning-enhanced electrographic flow mapping in persistent atrial fibri... by Peter Ruppersberg, Steven Castellano, Philip Haeusser, Kostiantyn Ahapov, Melissa H. Kong, Stefan G. Spitzer, Stefan G. Spitzer, Georg Nölker, Andreas Rillig, Tamas Szili-Torok

“…Notably, the majority of significant sources were not continuously active; however, when these sources switched “ON,” the spatial variability of AF cycle lengths in the respective atrium decreased by more than 50%, suggesting an entraining effect.ConclusionsBy systematically optimizing the EGF Model's hyperparameters based on clinical outcomes, we reliably detect and target key AF sources that, when ablated, improve procedural success. …”
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Changing grizzly bear space use and functional connectivity in response to human disturbance in the southern Canadian Rocky Mountains by Eric C. Palm, Clayton D. Apps, Tal Avgar, Melanie Dickie, Bruce N. McLellan, Joseph M. Northrup, Michael A. Sawaya, Julie W. Turner, Jesse Whittington, Erin L. Landguth, Katherine A. Zeller, Clayton T. Lamb

“…Our study builds upon existing work simulating animal space use from fitted iSSFs by incorporating individual‐level variation into population‐level simulations and by fitting functional responses that help capture broad‐scale variation in behavior and improve model transferability to new areas. Our results provide insights into grizzly bear movement and connectivity in an area of high conservation importance, and our predictive maps can be used to directly inform transboundary management actions and conservation planning.…”
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Ecosystem services thresholds and interconnected feedback loops in the vulnerable Tarim River Basin: Confronting climate and vegetation transformations by Chun Luo, Xiaofei Ma, Yonghui Wang, Wei Yan, Yonglong Han, Wei Yu, Binbin Fan

“…Ecological thresholds play a key role in understanding ecosystem stability and vulnerability, and in predicting the impacts of future environmental changes. …”
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Neonatal and perinatal mortality in the urban continuum: a geospatial analysis of the household survey, satellite imagery and travel time data in Tanzania by Lenka Benova, Claudia Hanson, Aliki Christou, Aline Semaan, Peter M Macharia, Jessie Pinchoff, Andrea B Pembe

“…Travel time to the nearest hospital was modelled using least-cost path algorithm for each cluster. …”
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Chaperonin containing TCP1 subunit 5 as a novel pan-cancer prognostic biomarker for tumor stemness and immunotherapy response: insights from multi-omics data, integrated machine le... by Jiajun Li, Nuo Xu, Leyin Hu, Jiayue Xu, Yifan Huang, Deqi Wang, Feng Chen, Yi Wang, Jiani Jiang, Yanggang Hong, Huajun Ye

“…Furthermore, CCT5-high tumors exhibited immune-cold phenotypes, with reduced TILs and CD8⁺ T cell activity. The CCT5.Sig model, based on genes co-expressed with CCT5, achieved superior predictive accuracy for ICB response (AUC = 0.82 in validation and 0.76 in independent testing), outperforming existing pan-cancer signatures. …”
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Patterns and drivers of water-land resources nexus in arid inland river basins of northwestern China by Lingge Wang, Wei Liu, Qi Feng, Zhenliang Yin, Rui Zhu, Meng Zhu, Jutao Zhang, Yuanyuan Xue, Zexia Chen, Xuejiao Li

“…In this study, we evaluated and predicted water and land resource dynamics by combining the soil quality index function with MCE-CA-Markov and SWAT models. …”
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Design and Development of a Side Spray Device for UAVs to Improve Spray Coverage in Obstacle Neighborhoods by Fanrui Kong, Baijing Qiu, Xiaoya Dong, Kechuan Yi, Qingqing Wang, Chunxia Jiang, Xinwei Zhang, Xin Huang

“…The error between the predicted values of the relational model and the field experiment results was less than 15%. …”
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Chondroitin Sulfate as a Lysosomal Enhancer Attenuates Lipid-Driven Inflammation via Lipophagy and Mitophagy by Ting Sun, Huimin Lv, Huarong Shao, Xiuhua Zhang, Anqi Wang, Wei Zhang, Fei Liu, Peixue Ling

“…By employing subcellular imaging and organelle-specific labeling techniques, we demonstrate that CS restores lysosomal acidification in a NASH model, enabling the reduction of lipid droplets via lysosomal–lipid droplet fusion. …”
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Analysis of the Role of Key Actors (Public and Private) in the Regeneration of Urban Neighborhoods (Case Study: Sarab Neighborhood of Mashhad) by Zohreh Fanni, Nasim Niknami, Sajad Saeedi

“…To identify and formulate regeneration strategies for urban neighborhoods, the SWOT model was used. To rank the output strategies of the model, the QSPM model was used in the framework of internal and external position evaluation. …”
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HIBRID: histology-based risk-stratification with deep learning and ctDNA in colorectal cancer by Chiara M. L. Loeffler, Hideaki Bando, Srividhya Sainath, Hannah Sophie Muti, Xiaofeng Jiang, Marko van Treeck, Nic Gabriel Reitsam, Zunamys I. Carrero, Asier Rabasco Meneghetti, Tomomi Nishikawa, Toshihiro Misumi, Saori Mishima, Daisuke Kotani, Hiroya Taniguchi, Ichiro Takemasa, Takeshi Kato, Eiji Oki, Yuan Tanwei, Wankhede Durgesh, Sebastian Foersch, Hermann Brenner, Michael Hoffmeister, Yoshiaki Nakamura, Takayuki Yoshino, Jakob Nikolas Kather

“…Circulating tumor DNA (ctNDA) detects molecular residual disease (MRD), but lacks spatial and tumor microenvironment information. Here, we develop a deep learning (DL) model to predict disease-free survival from hematoxylin & eosin stained whole slide images in stage II-IV colorectal cancer. …”
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Monitoring and Mapping a Decade of Regenerative Agricultural Practices Across the Contiguous United States by Matthew O. Jones, Gleyce Figueiredo, Stephanie Howson, Ana Toro, Soren Rundquist, Gregory Garner, Facundo Della Nave, Grace Delgado, Zhuang-Fang Yi, Priscilla Ahn, Samuel Jonathan Barrett, Marie Bader, Derek Rollend, Thaïs Bendixen, Jeff Albrecht, Kangogo Sogomo, Zam Zam Musse, John Shriver

“…Monitor incorporates three datasets: CropID, a deep learning transformer model using Sentinel-2 and USDA Cropland Data Layer (CDL) data from 2018 to 2023 to predict annual crop types; the living root data, which use Normalized Difference Vegetation Index (NDVI) data to determine cover crop presence through regional parameterization; and residue cover (RC) data, which uses the Normalized Difference Tillage Index (NDTI) and crop residue cover (CRC) index to assess tillage intensity. …”
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Identifying key drivers of heatwaves: A novel spatio-temporal framework for extreme event detection by J. Pérez-Aracil, C. Peláez-Rodríguez, Ronan McAdam, Antonello Squintu, Cosmin M. Marina, Eugenio Lorente-Ramos, Niklas Luther, Verónica Torralba, Enrico Scoccimarro, Leone Cavicchia, Matteo Giuliani, Eduardo Zorita, Felicitas Hansen, David Barriopedro, Ricardo García-Herrera, Pedro A. Gutiérrez, Jürg Luterbacher, Elena Xoplaki, Andrea Castelletti, S. Salcedo-Sanz

“…Heatwaves (HWs) are extreme atmospheric events that produce significant societal and environmental impacts. Predicting these extreme events remains challenging, as their complex interactions with large-scale atmospheric and climatic variables are difficult to capture with traditional statistical and dynamical models. …”
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The fungal collaboration gradient drives root trait distribution and ecosystem processes in a tropical montane forest by M. Dantas de Paula, T. Reichert, L. F. Lugli, E. McGale, K. Pierick, K. Pierick, J. P. Darela-Filho, L. Langan, J. Homeier, J. Homeier, A. Rammig, T. Hickler, T. Hickler

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Automatic MRI Lymph Node Annotation From CT Labels by Souraja Kundu, Yuji Iwahori, M. K. Bhuyan, Manish Bhatt, Boonserm Kijsirikul, Aili Wang, Akira Ouchi, Yasuhiro Shimizu

“…Experiments show 2.19% and 4.08% MSE reductions, 5.40% and 3.28% SSIM improvements, 29.85% and 3.82% NCC increases for cross-modality and mono-modality registration, respectively, along with a 36.7% training speedup over state-of-the-art translation-based registration models. …”
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WetCH₄: a machine-learning-based upscaling of methane fluxes of northern wetlands during 2016–2022 by Q. Ying, Q. Ying, B. Poulter, J. D. Watts, K. A. Arndt, A.-M. Virkkala, L. Bruhwiler, Y. Oh, Y. Oh, B. M. Rogers, S. M. Natali, H. Sullivan, A. Armstrong, A. Armstrong, E. J. Ward, E. J. Ward, L. D. Schiferl, C. D. Elder, C. D. Elder, O. Peltola, A. Bartsch, A. R. Desai, E. Euskirchen, M. Göckede, B. Lehner, M. B. Nilsson, M. Peichl, O. Sonnentag, E.-S. Tuittila, T. Sachs, T. Sachs, A. Kalhori, M. Ueyama, Z. Zhang, Z. Zhang

“…The most important predictor<span id="page2508"/> variables included near-surface soil temperatures (top 40 cm), vegetation spectral reflectance, and soil moisture. Our results, modeled from 138 site years across 26 sites, had relatively strong predictive skill, with a mean <span class="inline-formula"><i>R</i>²</span> of 0.51 and 0.70 and a mean absolute error (MAE) of 30 and 27 nmol m<span class="inline-formula">⁻²</span> s<span class="inline-formula">⁻¹</span> for daily and monthly fluxes, respectively. …”
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Analysis of antibiotic use and access to drugs among poultry farmers in Kenya by Dishon M. Muloi, Mitchelle R. Kasudi, Maurice K. Murungi, Eugine Lusanji Ibayi, Samuel Kahariri, Charity Karimi, Max Korir, Bridgit Muasa, Damaris Mwololo, Romona Ndanyi, Robert Ndungi, Jane Njiru, Ruth Omani, Rose Owada, Sylvia Omulo, Allan Azegele, Eric M. Fèvre

“…Spatial maps suggests both risks and opportunities for antibiotic access and veterinary care.…”
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Typology of the "Internal Form-Structure" Drawing upon Argan\'s Formal Approach (Case Study: Historical Bridge-Caravanserai in Iran) by Paryia Pourmohammadi, Farshad Mafakher, Asghar Saed Samiei, Mehrdad Matin

“…Being the most prevailing type, the first one includes spatial components (rooms) at the columns of the bridge, categorized in two groups based on the number of levels (one- and two-story). …”
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