Quantitative Vulnerability Assessment of Buildings Exposed to Landslides Under Extreme Rainfall Scenarios by Guangming Li, Dong Liu, Mengjiao Ruan, Yuhua Zhang, Jun He, Zizheng Guo, Haojie Wang, Mengchen Cheng

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Ordinal METAR Cloud Cover Classification in Sentinel-2 Satellite Data by Markus Gotz, Erik Wessel, Ugur Cayoglu, Babak Jahani, Charlotte Debus, Jan Cermak, Achim Streit

“…This work proposes a novel approach for predicting cloud cover in global satellite images by leveraging ordinal point labels from ground-based weather stations, rather than relying on spatially resolved cloud masks, and demonstrates the effectiveness of this approach using a rank loss-based convolutional neural network of the EfficientNet family. …”
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A strontium (87Sr/86Sr) isoscape of Southern Ethiopia: implications for hominin land use and faunal mobility patterns by Seminew Asrat, Seminew Asrat, Francesco Lucchini, Mary Anne Tafuri, Caterina Aureli, Marina Gallinaro, Andrea Zerboni, Marianna Fusco, Enza E. Spinapolice

“…The results show that our novel baseline isoscape displayed heterogeneous 87Sr/86Sr isotope ratios in both the measured and predicted values (ranging from 0.703 to 0.712), consistent with geological units, with an accurate model performance evaluated through Leave-One-Out Cross-Validation (LOOCV) technique. …”
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Using satellite-based Sun-induced chlorophyll fluorescence and spectral reflectance for improving terrestrial CO2 flux estimates of India by Aparnna Ravi, Dhanyalekshmi Pillai, Christoph Gerbig, Stephen Sitch, Sönke Zaehle, Vishnu Thilakan, Chandra Sekhar Jha, Thara Anna Mathew

“…We improve these model predictions by additionally using satellite-based solar-induced chlorophyll fluorescence (SIF), soil temperature , and soil moisture specific to the vegetation classes of the domain. …”
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Rice Disease Detection: TLI-YOLO Innovative Approach for Enhanced Detection and Mobile Compatibility by Zhuqi Li, Wangyu Wu, Bingcai Wei, Hao Li, Jingbo Zhan, Songtao Deng, Jian Wang

“…Finally, this study adopted the WIoUv3 loss function and added a dynamic non-monotonic aggregation mechanism to the standard IoU calculation to more accurately evaluate and penalize the difference between the predicted and actual bounding boxes, thus improving the robustness and generalization ability of the model. …”
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Gait-based Parkinson’s disease diagnosis and severity classification using force sensors and machine learning by Navita, Pooja Mittal, Yogesh Kumar Sharma, Anjani Kumar Rai, Sarita Simaiya, Umesh Kumar Lilhore, Vimal Kumar

“…The proposed dual-stage model utilized a hypertuned Random Forest Tree (RFT) to classify the subjects into PD and non-PD classes at Stage 1 and a hypertuned Ensemble Regressor (ER) to predict the severity of illness at Stage 2. …”
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Harnessing InSAR and Machine Learning for Geotectonic Unit-Specific Landslide Susceptibility Mapping: The Case of Western Greece by Stavroula Alatza, Alexis Apostolakis, Constantinos Loupasakis, Charalampos Kontoes, Martha Kokkalidou, Nikolaos S. Bartsotas, Georgios Christopoulos

“…The gradient-boosted decision tree was employed in the landslide susceptibility mapping. The model was trained on three geotectonic units and five prefectures of Western Greece and performed well in predicting landslide events. …”
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Multi‑feature geological hazard susceptibility assessment by integrating improved ResNet and transfer learning: A case study of the Loess Plateau in Northern Shaanxi by Hao Cheng, Chong Xu, Rong Guo, Hai-kun Jing, Zeng-lin Hong, Feng-chen Fu, Ruo-shu Li

“…This study addressed the issues of insufficient feature utilization, poor spatial coherence, and weak generalization in conventional models for Geological hazard susceptibility assessment (GHSA) on the Loess Plateau in Northern Shaanxi. …”
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Atmospheric Deposition of Phosphorus to the Everglades: Concepts, Constraints, and Published Deposition Rates for Ecosystem Management by Garth W. Redfield

“…With better sampling methods and more long-term monitoring data, the importance of atmospheric P deposition in ecosystem dynamics and management can be better understood and predicted.…”
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Segmentation of the iliac crest from CT-data for virtual surgical planning of facial reconstruction surgery using deep learning by Stefan Raith, Tobias Pankert, Jônatas de Souza Nascimento, Srikrishna Jaganathan, Florian Peters, Mathias Wien, Frank Hölzle, Ali Modabber

“…In all cases, the bones were identified as contiguous objects in the correct spatial orientation. The geometries of the iliac crests were consistently and completely recognized on both sides without any gaps. …”
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Studying attention to IPCC climate change maps with mobile eye-tracking. by Doga Gulhan, Bahador Bahrami, Ophelia Deroy

“…This study examines trends in visual attention to climate change predictions in world maps using mobile eye-tracking while participants engage with the visualisations. …”
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High temperatures will likely limit establishment success of the Brazilian peppertree thrips, Pseudophilothrips ichini (Thysanoptera: Phlaeothripidae) in the USA, despite variation... by Nathan Harms, Megann Harlow, Ian Knight, Aaron Schad

“…We measured upper limit of chill injury zone (ULCIZ) and lower limit of thermal injury zone (LLTIZ) in the laboratory under multiple combinations of temperature and exposure duration then modeled spatial variation in survival based on detailed weather data over 20 years. …”
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Distribution of different plant life forms on tropical islands: patterns and underlying mechanisms by Chengfeng Yang, Jingyan Zhao, Shengzhuo Huang, Shurong Zhou, Yikang Cheng

“…The structural equation model (SEM) revealed that island area, isolation, and climatic factors directly affect the richness and abundance of trees but not shrubs. …”
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The Role of [18F]FDG PET Imaging for the Assessment of Pulmonary Lymphangitic Carcinomatosis: A Comprehensive Narrative Literature Review by Francesco Dondi, Pietro Bellini, Michela Cossandi, Luca Camoni, Roberto Rinaldi, Gian Luca Viganò, Francesco Bertagna

“…Emerging digital PET/CT systems, with enhanced spatial resolution, may improve the detection of focal PLC and reduce false negatives. …”
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Microenvironment-confined kinetic elucidation and implementation of a DNA nano-phage with a shielded internal computing layer by Decui Tang, Shuoyao He, Yani Yang, Yuqi Zeng, Mengyi Xiong, Ding Ding, Weijun Wei, Yifan Lyu, Xiao-Bing Zhang, Weihong Tan

“…However, it is quite difficult to involve nanobodies into molecular computation with programmed recognition order because of the “always-on” response mode and the inconvenient molecular programming. Here we propose a spatial segregation-based molecular computing strategy with a shielded internal computing layer termed DNA nano-phage (DNP) to program nanobody into DNA molecular computation and build a series of kinetic models to elucidate the mechanism of microenvironment-confinement. …”
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Automatic Endoscopic Navigation for Monocular Depth and Ego-Motion Estimation in Wireless Capsule Endoscopy Through Transformer Network by Junjun Huang, Tianran He, Juan Xu, Weiting Wu, Wei Wu

“…To address these issues, we introduce a novel self-supervised neural network framework that integrates a dual-attention mechanism within a modified ResNet. This model simultaneously predicts depth maps and ego-motion from monocular GI images, without requiring ground truth depth data. …”
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Combining Sentinel-2 Data and Risk Maps to Detect Trees Predisposed to and Attacked by European Spruce Bark Beetle by Per-Ola Olsson, Pengxiang Zhao, Mitro Müller, Ali Mansourian, Jonas Ardö

“…The European spruce bark beetle is a major disturbance agent in Norway spruce forests in Europe, and with a changing climate it is predicted that damage will increase. To prevent the bark beetle population buildup, and to limit further spread during outbreaks, it is crucial to detect attacked trees early. …”
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Major depressive disorder on a neuromorphic continuum by Jiao Li, Zhiliang Long, Gong-Jun Ji, Shaoqiang Han, Yuan Chen, Guanqun Yao, Yong Xu, Kerang Zhang, Yong Zhang, Jingliang Cheng, Kai Wang, Huafu Chen, Wei Liao

“…However, interindividual variations suggest that depression may be conceptualized as a “continuum,” rather than as a “category.” We use a Bayesian model to decompose structural MRI features of MDD patients from a multisite cross-sectional cohort into three latent disease factors (spatial pattern) and continuum factor compositions (individual expression). …”
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Direct Estimation of Forest Aboveground Biomass from UAV LiDAR and RGB Observations in Forest Stands with Various Tree Densities by Kangyu So, Jenny Chau, Sean Rudd, Derek T. Robinson, Jiaxin Chen, Dominic Cyr, Alemu Gonsamo

“…Then we train a deep learning model on annotations derived from MCWS to make crown predictions on UAV red, blue, and green (RGB) tiles. …”
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Foreign object detection for mining conveyor belts based on YOLOv5n-CND by SUN Aoran, ZHAO Peipei, YANG Di, ZHANG Junyi, YU Hongjian

“…The mAP@0.5 and mAP@0.5:0.95 of YOLOv5n-CND were 2.6% and 3.4% higher than YOLOv5n, and 1.7% and 3.8% higher than YOLOv5s-CBAM, respectively. Although the model’s parameter count slightly increased compared to the YOLOv5n model, it was still lower than that of other models. …”
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