Preparation of land subsidence susceptibility map using machine learning methods based on decision tree (case study: Isfahan–Borkhar) by Negar Ghasemi, Iman Khosravi, Ali Bahrami

“…InSAR techniques allow for high-precision measurements of surface deformation across large areas, making them invaluable in understanding and modeling subsidence patterns. When combined with machine learning approaches, these technologies offer even greater potential for developing predictive models and susceptibility maps, enabling proactive risk management. …”
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Regulation of MAP2, GFAP, and calcium in the CA3 Region Following Kainic Acid Exposure to  organotypic hippocampal slice culture [version 3; peer review: 2 approved] by Aulanni'am Aulanni'am, Kusworini Handono, Ettie Rukmigarsari, Hidayat Sujuti, Machlusil Husna

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Metabolomics and network analysis reveal the mechanism of Salvia miltiorrhiza bunge extract in ameliorating cognitive dysfunction in sleep-deprived rats by Meiya Zhang, Xirui Huang, Mengxiang Dai, Shunbo Zhang, Chao Yin, Qiuyun You

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Assemblies, synapse clustering, and network topology interact with plasticity to explain structure-function relationships of the cortical connectome by András Ecker, Daniela Egas Santander, Marwan Abdellah, Jorge Blanco Alonso, Sirio Bolaños-Puchet, Giuseppe Chindemi, Dhuruva Priyan Gowri Mariyappan, James B Isbister, James King, Pramod Kumbhar, Ioannis Magkanaris, Eilif B Muller, Michael W Reimann

“…To rise to this challenge, we endowed an existing large-scale cortical network model, incorporating data-constrained dendritic processing and multi-synaptic connections, with a calcium-based model of functional plasticity that captures the diversity of excitatory connections extrapolated to in vivo-like conditions. …”
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Residual attention based multi-label learning for apple leaf disease identification by Changjian Zhou, Zhenyuan Zhao, Wenzhuo Chen, Yuquan Feng, Jia Song, Wensheng Xiang

“…Built upon an attention based multi-label learning framework, the channel and spatial attention mechanisms are investigated and embedded in residual network for multi-label disease prediction, which takes advantage of channel-wise and spatial-wise attention weights. …”
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Multi-omics Analysis of Histone-related Genes in Osteosarcoma: A Multidimensional Integrated Study Revealing Drug Sensitivity and Immune Microenvironment Characteristics by Yang Yang MD, Xinqiao Tang MD, Zhong Liu MD

“…Based on nine histone modification-related genes, we constructed an efficient prognostic model (AUC values of 0.713, 0.845, and 0.888 for 1-, 3-, and 5-year predictions, respectively), which was validated in an external cohort (AUC = 0.808). …”
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Statistical Analysis of High-Resolution Coherent Monopulse Radar Sea Clutter by Hong Zhu, Qingping Wang, Ning Tai, Jingjian Huang, Naichang Yuan

“…Finally, we perform a spectral analysis, highlighting the temporal and spatial variabilities of Doppler spectra. It is found that the individual Doppler spectra in all three channels can be represented by Gaussian-shaped power spectral densities, and their centroid and width can be modeled as two separate stage linear functions of spectrum intensity.…”
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A 3 h, 1 km surface soil moisture dataset for the contiguous United States from 2015 to 2023 by H. Yang, J. Yang, T. E. Ochsner, E. S. Krueger, M. Xu, C. B. Zou

“…In this study, we developed a new 3 h, 1 km spatially seamless SSM dataset spanning 2015 to 2023, covering the entire contiguous United States (CONUS), using a spatio-temporal fusion model. …”
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Surface Defect Detection Algorithm for Wind Turbine Blades Based on HSCA-YOLOv7 by Bing LI, Yunshan BAI, Kuan ZHAO, Congbin GUO, Yongjie ZHAI

“…The focal EIoU loss function is used to solve the problem that the length and width of the prediction box are wrongly amplified and improve the positioning ability of the model for blade defects. …”
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Coordinate Attention Filtering Depth-Feature Guide Cross-Modal Fusion RGB-Depth Salient Object Detection by Lingbing Meng, Mengya Yuan, Xuehan Shi, Qingqing Liu, Le Zhange, Jinhua Wu, Ping Dai, Fei Cheng

“…Second, a dense decoder guidance module is proposed to recover the spatial details of salient objects. Furthermore, a context-aware content module is proposed to extract rich context information, which can predict multiple objects more completely. …”
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Inorganic carbon assimilation by planktonic community in Santos Basin, Southwestern Atlantic Ocean by Deborah S. Kutner, Jeff S. Bowman, Flávia M. P. Saldanha-Corrêa, Mateus G. Chuqui, Pedro M. Tura, Daniel L. Moreira, Frederico P. Brandini, Camila N. Signori

“…Rates were analyzed using statistical tests to verify spatial differences between groups of samples and generalized linear models to identify correlations with environmental variables (temperature, salinity, density, mixed layer depth, dissolved oxygen, nitrite, nitrate, silicate, phosphate, turbidity, CDOM, and phycoerythrin and chlorophyll-a concentrations). …”
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Climate change enhances soil fauna population and biomass in grasslands of the Loess Plateau by Xi Yang, Ming’an Shao, Tongchuan Li

“…Conservatively estimated, the number of soil fauna on the Loess Plateau exceeds 4 × 1015, with the estimated total biomass of 4 × 106 t, equivalent to 2 Mt carbon. In addition, model predictions indicate that soil fauna populations and biomass of grassland in the Loess Plateau increased 27% and 29%, from 2000 to 2022. …”
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Inorganic carbon assimilation by planktonic community in Santos Basin, Southwestern Atlantic Ocean by Deborah S. Kutner, Jeff S. Bowman, Flávia M. P. Saldanha-Corrêa, Mateus G. Chuqui, Pedro M. Tura, Daniel L. Moreira, Frederico P. Brandini, Camila N. Signori

“…Rates were analyzed using statistical tests to verify spatial differences between groups of samples and generalized linear models to identify correlations with environmental variables (temperature, salinity, density, mixed layer depth, dissolved oxygen, nitrite, nitrate, silicate, phosphate, turbidity, CDOM, and phycoerythrin and chlorophyll-a concentrations). …”
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Data fusion-based improvements in empirical regression and machine learning for global daily ∼ 8 km resolution sea surface nitrate estimation and interpretation by Aifen Zhong, Difeng Wang, Fang Gong, Jingjing Huang, Zhuoqi Zheng, Xianqiang He, Qing Zhang, Qiankun Zhu

“…Here we aim to enhance the accuracy and spatial resolution of SSN retrievals by developing improved regression and machine learning models, enabling the generation of global daily ∼ 8 km SSN products from satellite and model data. …”
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Weed Types and Dynamics Associations with Catena Landscape Positions: Smallholder Farmers’ Knowledge and Perception in Zimbabwe by Justin Chipomho, Simbarashe Tatsvarei, Cosmas Parwada, Arnold Bray Mashingaidze, Joyful T. Rugare, Stanford Mabasa, Regis Chikowo

“…The data were coded and processed using the CSPro software package, and then analysed using the SPSS program. Factors that predicted the spatial distribution of weeds were determined using a binary logistic model. …”
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Influence of Clouds and Aerosols on Solar Irradiance and Application of Climate Indices in Its Monthly Forecast over China by Shuting Zhang, Xiaochun Wang

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Estimating Geographical Variation in the Risk of Zoonotic Plasmodium knowlesi Infection in Countries Eliminating Malaria. by Freya M Shearer, Zhi Huang, Daniel J Weiss, Antoinette Wiebe, Harry S Gibson, Katherine E Battle, David M Pigott, Oliver J Brady, Chaturong Putaporntip, Somchai Jongwutiwes, Yee Ling Lau, Magnus Manske, Roberto Amato, Iqbal R F Elyazar, Indra Vythilingam, Samir Bhatt, Peter W Gething, Balbir Singh, Nick Golding, Simon I Hay, Catherine L Moyes

“…<h4>Methodology/principal findings</h4>A total of 439 records of P. knowlesi infections in humans, macaque reservoir and vector species were collated. To predict spatial variation in disease risk, a model was fitted using records from countries where the infection data coverage is high. …”
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Mapping global leaf inclination angle (LIA) based on field measurement data by S. Li, S. Li, S. Li, H. Fang, H. Fang

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Estimation of nitrogen uptake, biomass, and nitrogen concentration, in cover crop monocultures and mixtures from optical UAV images by Paolo Dal Lago, Nikolaos Vavlas, Lammert Kooistra, Gerlinde B. De Deyn

“…This study provides a basis for spatially predicting key CC traits using UAV optical data.…”
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HMGB1 Inhibition Alleviates Chronic Nonbacterial Prostatitis by Suppressing M1 Polarization of Macrophages by Zhou J, Ding L, Chen J, Chen C, Jiang P, Mei Z, Jiang Q, Hua X

“…Co-immunofluorescence was used to analyze the functional phenotype of macrophages and spatial localization of HMGB1 in prostate of EAP mice. …”
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