Mapping the global distribution of livestock. by Timothy P Robinson, G R William Wint, Giulia Conchedda, Thomas P Van Boeckel, Valentina Ercoli, Elisa Palamara, Giuseppina Cinardi, Laura D'Aietti, Simon I Hay, Marius Gilbert

“…The Gridded Livestock of the World (GLW) database, produced in 2007, provided modelled livestock densities of the world, adjusted to match official (FAOSTAT) national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 5×5 km at the equator). …”
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Tensor network analysis of the maple-leaf antiferromagnet spangolite by Philipp Schmoll, Harald O. Jeschke, Yasir Iqbal

“…Experimental measurements revealed a non-magnetic ground state at T ~ 8 K with magnetic properties dominated by dimerization. We propose a spatially anisotropic Heisenberg model for the Cu2+ spin-1/2 degrees of freedom on this geometrically frustrated and effectively two-dimensional maple-leaf lattice, featuring five symmetry inequivalent couplings with ferromagnetic bonds on hexagons and antiferromagnetic triangular bonds. …”
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Assessing climate risks from satellite imagery with machine learning: A case study of flood risks in Jakarta by Jeasurk Yang, Donghyun Ahn, Junbeom Bahk, Sungwon Park, Nurrokhmah Rizqihandari, Meeyoung Cha

“…Results confirm that our model can assess climate risks in a granular scale and further capture potential risks in the marginalized areas (e.g., slums) that were previously hard to predict. …”
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Gaze Estimation Based on a Multi-Stream Adaptive Feature Fusion Network by Changli Li, Enrui Tong, Kao Zhang, Nenglun Cheng, Zhongyuan Lai, Zhigeng Pan

“…The concatenated high-dimensional and fused low-dimensional features are processed through fully connected layers to predict the final gaze direction. Extensive experiments on the EYEDIAP, MPIIFaceGaze, and Gaze360 datasets validate the superiority of the proposed method.…”
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Investigation of the dynamic charge transport behaviours under electron beam irradiation of advanced insulation materials for aerospace applications by Guangyu Sun, Xiong Yang, Wentong An, Kun Huang, Xiaogang Qin, Baipeng Song, Guanjun Zhang

“…The model reveals the spatial–temporal evolutions of the current, charge density, and electric field distribution. …”
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MIAU: An analysis-ready dataset on presence-only and presence-absence data of Neotropical carnivores (Mammalia, Carnivora) from 2000 to 2021 by Florencia Grattarola, Kateřina Tschernosterová, Petr Keil

“…These data can be used for large-scale species distribution models, calculation of population trends, extinction risk analyses and educational purposes.…”
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Estimating the impact of interventions against COVID-19: From lockdown to vaccination. by James Thompson, Stephen Wattam

“…Our model predicts far fewer cases and deaths than the equivalent equation-based SEIR model. …”
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Pan-cancer analysis uncovered the prognostic and therapeutic value of disulfidptosis by Yiwei Zhang, Zihua Li, Hengli Lu, Zongrui Jiang, Yixian Song, Zhanhui Ye, Chenzheng Gu, Kequan Chen, Anquan Shang

“…The nomogram based on the DRGs Score model could accurately predict the prognosis of patients with pan-cancer. …”
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Tier‐1 and Tier‐2A Scenario Parameterisation and Example Calculations ‐ In Support of the Revision of the Guidance Document on Persistence in Soil under Council Directive 91/414/EE... by European Food Safety Authority

“…The aim of this scheme is to assess such Predicted Environmental Concentrations (PEC), chosen to be the 90th spatial percentile, resulting from the use of the plant protection product. …”
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The Reshaping and Effect Evaluation of Immersive Communication on Museum Cultural Experience by Huang Gang, Zhong Junjie

“…With the development of digital technology, immersive communication technologies such as virtual reality, augmented reality, etc. have gradually become important tools for innovative exhibitions and educational models in museums. Through multi-sensory interactive experiences, immersive communication not only breaks the spatial and exhibit limitations of traditional museums, but also enhances audience participation and emotional resonance, promoting the depth and breadth of cultural experiences. …”
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Estimates of Effective Number of Breeders Identify Drivers of Decline in Mid‐Atlantic Brook Trout Populations by Zachary L. Robinson, Jason A. Coombs, Mark Hudy, Keith H. Nislow, Andrew R. Whiteley

“…Our results are consistent with presently observed and predicted future impacts of climate change on populations of this cold‐water fish. …”
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A novel fusion of Sentinel-1 and Sentinel-2 with climate data for crop phenology estimation using Machine Learning by Shahab Aldin Shojaeezadeh, Abdelrazek Elnashar, Tobias Karl David Weber

“…The spatio-temporal analysis of the model predictions demonstrates its transferability across different spatial and temporal context of Germany. …”
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Study of Shale Gas Source Rock S-Wave Structure Characteristics via Dense Array Ambient Noise Tomography in Zhangjiakou, China by Si Chen, Zhanwu Lu, Haiyan Wang, Qingyu Wu, Wei Cai, Guowei Wu, Guangwen Wang

“…Employing a binary stratigraphic model, the study predicted shale content based on the velocity structure, with predictions exhibiting a moderate correlation (correlation coefficient of 0.58) with empirical data. …”
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Explainable artificial intelligence with temporal convolutional networks for adverse weather condition detection in driverless vehicles by Samah Alzanin

“…The CapsNet model is employed for feature extraction to recognize spatial hierarchies and capture intricate patterns from complex visual data. …”
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Ecological network construction and land degradation risk identification in the Yellow River source area by Haoxiang Zhang, Qian Song, Shiru Wang, Jianyun Zhao, Wenming Gao

“…Based on ordered weighted average operator, morphological spatial pattern analysis, ecological sensitivity, circuit theory, CA-Markov model, kernel density analysis, and other methods, this study aims to consider the positive and negative connections of the network thus constructing the ecological and risk network and predicting the potential risk areas in the future. …”
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Investigation on the early pressure load characteristics of bubbles in near-field underwater explosion with condensed-phase CL-20 explosive detonation by Yi Hao, Zhenxin Sheng, Bo Yan, Teng Xie, Lunping Zhang, Haibin Mao, Jun Yu

“…Validation against 1D detonation wave tests confirms the accuracy of our burn model. Numerical simulations of cylindrical and spherical CL-20 charges under near-field conditions show good agreement with the experimental data, highlighting the model’s precision in predicting shock wave propagation and interface motion. …”
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Study on the Risk of Urban Population Exposure to Waterlogging in Huang-Huai Area Based on Machine Learning Simulation Analysis—A Case Study of Xuzhou Urban Area by Shuai Tong, Jiuxin Wang, Jiahui Qin, Xiang Ji, Zihan Wu

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Enhanced Blood Loss Quantification Using a Novel Multi-Wavelength Imaging Approach by Ara Abigail E. Ambita, Laura T. David, Catherine Sim Co, Prospero C. Naval

“…Lastly, an individualized interpretation for each surgical test gauze is provided, a useful tool to understand how the machine learning model predicts the absorbed blood volume.…”
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Enhancing Clear Radiance Generation for Geostationary Hyperspectral Infrared Sounder Using High Temporal Resolution Information by Di Di, Jun Li, Zhenglong Li, Jing Zheng, Xinya Gong

“…Abstract With high spatio‐temporal resolution geostationary hyperspectral infrared sounder (GeoHIS) observations, monitoring, and predicting rapidly changing weather events are expected to be improved with continuous information of 3D weather cube. …”
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Projecting Large Fires in the Western US With an Interpretable and Accurate Hybrid Machine Learning Method by Fa Li, Qing Zhu, Kunxiaojia Yuan, Fujiang Ji, Arindam Paul, Peng Lee, Volker C. Radeloff, Min Chen

“…Abstract More frequent and widespread large fires are occurring in the western United States (US), yet reliable methods for predicting these fires, particularly with extended lead times and a high spatial resolution, remain challenging. …”
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