Deciphering the Social Vulnerability of Landslides Using the Coefficient of Variation-Kullback-Leibler-TOPSIS at an Administrative Village Scale by Yueyue Wang, Xueling Wu, Guo Lin, Bo Peng

“…By comparing the actual losses incurred per unit area from landslides, it is found that the social vulnerability results predicted by the <i>CV-KL-TOPSIS</i> model are more consistent with the actual survey results. …”
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The Role of Parental Education, Intelligence, and Personality on the Cognitive Abilities of Gifted Children by Lina Pezzuti, Morena Farese, James Dawe, Marco Lauriola

“…Several studies have indicated that parental education predicts children’s intelligence. In contrast, fewer studies have simultaneously analyzed the role of parental intelligence, education, and personality in shaping their children’s giftedness. …”
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Using unmanned aerial vehicles to estimate body volume at scale for ecological monitoring by Thomas C. Stone, Katrina J. Davis

“…Abstract Demographic data are essential to construct mechanistic models to understand how populations change over time and in response to global threats like climate change. …”
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Evolution of the ecological security pattern of the Yellow River Basin based on ecosystem services: a case study of the Shanxi section, China by Jinfang Wang, Zhihong Lv, Zhilei Zhen, Qian Wu

“…Identifying and evaluating the ecological security pattern (ESP) of region can provide a solid foundation for optimizing regional ecosystem elements and improving regional ecological security. The PLUS model, InVEST model, and circuit theory were used to analyze the ecosystem services and ESP of the Shanxi section of the Yellow River Basin (SYRB) between 2005 and 2035. …”
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Basin-wide and coastal modes of north tropical Atlantic variability have distinct impacts on hurricanes by Yi Liu, Michael J. McPhaden, Wenju Cai, Yu Zhang, Jiuwei Zhao, Hyacinth C. Nnamchi, Xiaopei Lin, Ziguang Li, Jun-Chao Yang

“…Here we use observations and model outputs over the past several decades to determine whether there exists inherent diversity in north tropical Atlantic surface temperature spatial structures and impacts. …”
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Multi-scale convolutional neural networks (CNNs) for landslide inventory mapping from remote sensing imagery and landslide susceptibility mapping (LSM) by Baoyi Zhang, Jiacheng Tang, Yuke Huan, Lei Song, Syed Yasir Ali Shah, Lifang Wang

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RainHCNet: Hybrid High-Low Frequency and Cross-Scale Network for Precipitation Nowcasting by Lei Wang, Zheng Wang, Wenjun Hu, Cong Bai

“…RainHCNet incorporates a hybrid channel&#x2013;spatial attention mechanism to effectively capture low-frequency information, overcoming the limitations of traditional CNN-based methods that are unable to model global dependencies. …”
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Numerical simulation of UGS facilities rebuilt from oil reservoirs based on the coupling of seepage and temperature fields by HE Haiyan, LIU Xianshan, GENG Shaoyang, SUN Junchang, SUN Yanchun, JIA Qian

“…The model is solved discretely using the Finite Volume Method（FVM）, with a Two-Point Flux Approximation（TPFA） scheme for spatial discretization and a backward （implicit） Euler scheme for temporal discretization. …”
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On the Brink: Mapping the Last Strongholds of the Critically Endangered Flapper Skate (Dipturus intermedius) by Sophie L. Loca, Patrick C. Collins, Amy Garbett, Ryan McGeady, James Thorburn, Chris McGonigle

“…Location The NE Atlantic shelf region. A Bayesian spatial binomial GAMM was used to model the distribution of flapper skate across the NE Atlantic shelf. …”
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Spatiotemporal dataset of dengue influencing factors in Brazil based on geospatial big data cloud computing by Qixu Zhu, Zhichao Li, Jinwei Dong, Ping Fu, Qu Cheng, Jun Cai, Helen Gurgel, Linsheng Yang

“…Addressing this challenge necessitates the efficient data integration methods and the assembly of multi-factorial datasets to aid public health authorities in understanding dengue transmission mechanisms and improving risk prediction models. In response, we developed a population-weighted dataset of 12 dengue risk factors, covering 558 microregions in Brazil over 1252 epidemiological weeks from 2001 to 2024. …”
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Kernel density change: A new bitemporal lidar metric for directly mapping wildland fire fuel consumption by Michael J. Campbell, Andrew T. Hudak, T. Ryan McCarley, Benjamin C. Bright, Philip E. Dennison

“…In this study, we compared MFLC to a new modeling approach that directly predicts consumption from a suite of bitemporal point cloud structural change metrics. …”
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Digital twin and contact analysis of ultra-long distance coiled tubing operation structures [version 2; peer review: 1 approved, 2 approved with reservations] by Wenlan Wei, Jiarui Cheng, Hao Qu, Maliang Wang, Wenyuan Wang

“…Results The research results show that the digital twin coiled tubing and contact algorithm can effectively predict the contact state of coiled tubing operations; the verification model shows that the contact algorithm can accurately analyze the contact state of different well trajectories. …”
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Deep Learning-Based MRI Brain Tumor Segmentation With EfficientNet-Enhanced UNet by Pradeep Kumar Tiwary, Prashant Johri, Alok Katiyar, Mayur Kumar Chhipa

“…Experimental findings in brain tumor segmentation tasks show that the proposed model achieves performance on par with or better than recent CNN or Transformer models. …”
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Climate-driven hydrological sensitivity in Estonian catchments: a northern temperate perspective by Oliver Koit, Joonas Pärn, Marlen Hunt, Siim Tarros, Elve Lode, Pamela Abreldaal

“…Key findings include diverse catchment sensitivities to groundwater recharge, the role of baseflow in streamflow stabilization, the memory effect in catchment responses, and insights from the flow duration curve on flow variability and extremes. The LightGBM model, predicting focus parameters, highlights the critical influence of air temperature and snowpack on streamflow characteristics. …”
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A Shared Control Method of Multiobjective Motion Fusion for Surgical Robot by Xilin Xiao, Xiaojian Li, Hangjie Mo, Yudong Shi, Jing Fang, Ling Li, Bo Ouyang, Shanlin Yang

“…In addition, a state feedback mechanism with prediction and evaluation model is developed to balance the control inputs of different control objectives. …”
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Variations in Bedrock and Vegetation Cover Modulate Subsurface Water Flow Dynamics of a Mountainous Hillslope by S. Uhlemann, L. Peruzzo, C. Chou, K. H. Williams, S. Wielandt, C. Wang, N. Falco, Y. Wu, B. Carr, P. Meldrum, J. Chambers, B. Dafflon

“…Abstract Predicting the hydrological response of watersheds to climate disturbances requires a detailed understanding of the processes connecting hillslopes and streams. …”
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Plasmodium vivax malaria endemicity in Indonesia in 2010. by Iqbal R F Elyazar, Peter W Gething, Anand P Patil, Hanifah Rogayah, Elvieda Sariwati, Niken W Palupi, Siti N Tarmizi, Rita Kusriastuti, J Kevin Baird, Simon I Hay

“…Detailed understanding of the contemporary spatial distribution of this parasite is needed to combat it. …”
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Brittleness evaluation of main coal seams in Permian Taiyuan-Shanxi formations, Baode block, Ordos Basin: based on a convolutional neural network method by Qingfeng ZHANG, Ziling LI, Jikun ZHANG, Shuai HAO, Xiaoguang SUN, Yanjie SHANG, Yun ZUO

“…Both seams exhibited similar spatial distributions, with low brittleness values in the central and southeastern parts of the study area. …”
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Computational analysis of the functional impact of MHC-II-expressing triple-negative breast cancer by Yang Cui, Weihang Zhang, Xin Zeng, Yitao Yang, Sung-Joon Park, Kenta Nakai, Kenta Nakai

“…Remarkably, we identified a prognostic signature comprising 40 significant genes in the MHC-II-expressing tumors in which machine leaning models with the signature successfully predicted patient survival outcomes and the degree of immune infiltration. …”
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Local Diversity-Guided Weakly Supervised Fine-Grained Image Classification Method by Yuebo Meng, Xianglong Luo, Hua Zhan, Bo Wang, Shilong Su, Guanghui Liu

“…To address this problem, we propose a weakly supervised fine-grained classification network model with Local Diversity Guidance (LDGNet). We designed a Multi-Attention Semantic Fusion Module (MASF) to build multi-layer attention maps and channel–spatial interaction, which can effectively enhance the semantic representation of the attention maps. …”
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