Landscapes, habitat, and migratory behaviour: what drives the summer movements of a Northern viper? by Chloe R. Howarth, Christine A. Bishop, Karl W. Larsen

“…Migratory distance was best predicted by two top models: terrain and combined effects (including terrain, physiology, and vegetation factors). …”
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Exploring Transfer Learning for Anthropogenic Geomorphic Feature Extraction from Land Surface Parameters Using UNet by Aaron E. Maxwell, Sarah Farhadpour, Muhammad Ali

“…Semantic segmentation algorithms, such as UNet, that rely on convolutional neural network (CNN)-based architectures, due to their ability to capture local textures and spatial context, have shown promise for anthropogenic geomorphic feature extraction when using land surface parameters (LSPs) derived from digital terrain models (DTMs) as input predictor variables. …”
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Descriptive epidemiology of Lassa fever, its trend, seasonality, and mortality predictors in Ebonyi State, South- East, Nigeria, 2018—2022 by Adanna Ezenwa-Ahanene, Adetokunbo T. Salawu, Ayo S. Adebowale

“…Lassa fever showed a seasonal trend across the years. The quadratic model provided the best fit for predicting Lassa fever cumulative cases (R2 = 98.4%, P-value < 0.05). …”
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Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability by Danish Raza, Hong Shu, Muhsan Ehsan, Hong Fan, Kamal Abdelrahman, Hasnat Aslam, Abdul Quddoos, Rana Waqar Aslam, Majid Nazeer, Mohammed S. Fnais, Azeem Sardar

“…Third, population dynamics were examined by applying an exponential growth model to forecast population growth and predict food demand. …”
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AGW-YOLO-Based UAV Remote Sensing Approach for Monitoring Levee Cracks by HU Weibo, ZHOU Shaoliang, ZHAO Erfeng, ZHAO Xueqiang

“…Subsequently, the center pixel coordinates of the bounding boxes predicted by the detection model were integrated with the yaw angle data recorded in the UAV's flight logs to construct an Euler angle rotation matrix. …”
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AUTOMATIC PALM COUNTING DENGAN METODE TEMPLATE MATCHING (STUDI KASUS DI UNIVERSITAS SAMUDRA) by Agusman, Iswahyudi, Iwan saputra

“…The use of this technology is expected to be a model that can be implemented in various other educational institutions.…”
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Monsoonal influence on particulate organic carbon variability through satellite data analysis by C.K. Tito, D.G. Bengen, T. Prartono, A. Damar, A.J. Wahyudi

“…This study aims to examine the spatial and temporal distribution of particulate organic carbon and to model its variance within Jakarta Bay, contributing to a deeper understanding of organic carbon dynamics in coastal ecosystems.METHODS: Monthly moderate-resolution imaging spectroradiometer satellite data for surface particulate organic carbon and chlorophyll-a during 2011 to 2023 periods were collected. …”
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Control Performance and Preliminary Application Investigation of Novel Rotational Impact Dampers by SHEN Junjie, WANG Jingjing

“…Following the verification of the effectiveness of the numerical model and the correctness of the theoretical model, the numerical model of the RID was used for subsequent numerical simulation research. …”
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Hypervelocity Stars Trace a Supermassive Black Hole in the Large Magellanic Cloud by Jiwon Jesse Han, Kareem El-Badry, Scott Lucchini, Lars Hernquist, Warren Brown, Nico Garavito-Camargo, Charlie Conroy, Re’em Sari

“…The predicted spatial and kinematic distributions of the simulated HVSs are remarkably similar to the observed distributions. …”
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Environmental factors influencing the odds of livestock predations by wolves in North–Eastern Italy across 10 years: a network analysis approach by Marcello Franchini, Salvatore Raniolo, Mirco Corazzin, Maurizio Ramanzin, Giulia Della Longa, Paolo Zanghellini, Natalia Bragalanti, Stefano Bovolenta

“…Large–scale data accessible to public institutions can help predict the temporal and spatial evolution of livestock predations by wolves. …”
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Characterization of 2D precision and accuracy for combined visual-haptic localization by Madeline Fischer, Umberto Saetti, Martine Godfroy-Cooper, Douglas Fischer

“…Overall, the lack of improvement in precision for bimodal cueing relative to the best unimodal cueing modality, vision, is in favor of sensory combination rather than optimal integration predicted by the Maximum Likelihood Estimation (MLE) model. …”
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Structure-guided deep learning for back acupoint localization via bone-measuring constraints by Yulong Wang, Tian Lan, Wenjian Dou, Zhi Chen, Song Zhang, Gong Chen, Gong Chen

“…The method employs an HRFormer backbone network combined with a Structure-Guided Keypoint Estimation Module (SG-KEM) and a structure-constrained loss function, ensuring anatomically consistent predictions within a standardized spatial coordinate system to improve accuracy across diverse body types. …”
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Rapid Disaster Data Dissemination and Vulnerability Assessment through Synthesis of a Web-Based Extreme Event Viewer and Deep Learning by P. Shane Crawford, Mohammad A. Al-Zarrad, Andrew J. Graettinger, Alexander M. Hainen, Edward Back, Lawrence Powell

“…Extracted building images were used to train a deep learning neural network to predict whether a building was elevated or nonelevated. …”
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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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Plasma-wall interaction impact of the ITER re-baseline by R.A. Pitts, A. Loarte, T. Wauters, M. Dubrov, Y. Gribov, F. Köchl, A. Pshenov, Y. Zhang, J. Artola, X. Bonnin, L. Chen, M. Lehnen, K. Schmid, R. Ding, H. Frerichs, R. Futtersack, X. Gong, G. Hagelaar, E. Hodille, J. Hobirk, S. Krat, D. Matveev, K. Paschalidis, J. Qian, S. Ratynskaia, T. Rizzi, V. Rozhansky, P. Tamain, P. Tolias, L. Zhang, W. Zhang

“…Boundary plasma (SOLPS-ITER) and integrated core–edge (JINTRAC) simulations, including W erosion and transport, clearly indicate the tendency for a self-regulating W sputter source in limiter configurations and highlight the importance of on-axis electron cyclotron power deposition to prevent W core accumulation in the early current ramp phase. These predicted trends are found experimentally in dedicated W limiter start-up experiments on the EAST tokamak. …”
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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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Possible Systematic Rotation in the Mature Stellar Population of a z = 9.1 Galaxy by Tsuyoshi Tokuoka, Akio K. Inoue, Takuya Hashimoto, Richard S. Ellis, Nicolas Laporte, Yuma Sugahara, Hiroshi Matsuo, Yoichi Tamura, Yoshinobu Fudamoto, Kana Moriwaki, Guido Roberts-Borsani, Ikkoh Shimizu, Satoshi Yamanaka, Naoki Yoshida, Erik Zackrisson, Wei Zheng

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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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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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