Specificity, propagation, and memory of pericentric heterochromatin by Katharina Müller‐Ott, Fabian Erdel, Anna Matveeva, Jan‐Philipp Mallm, Anne Rademacher, Matthias Hahn, Caroline Bauer, Qin Zhang, Sabine Kaltofen, Gunnar Schotta, Thomas Höfer, Karsten Rippe

“…From the experimental data, we developed a predictive mathematical model that explains how chromatin‐bound SUV39H1/2 complexes act as nucleation sites and propagate a spatially confined PCH domain with elevated histone H3 lysine 9 trimethylation levels via chromatin dynamics. …”
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The Impacts of Reservoir Heterogeneities on the CO₂-Enhanced Oil Recovery Process—A Case Study of Daqingzijing Block in Jilin Oilfield, China by Zetang Li, Tianfu Xu, Hailong Tian, Ruosheng Pan

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Observed Tightening of Tropical Ascent in Recent Decades and Linkage to Regional Precipitation Changes by Hui Su, Longtao Wu, Chengxing Zhai, Jonathan H. Jiang, J. David Neelin, Yuk L. Yung

“…Abstract Climate models predict that the tropical ascending region should tighten under global warming, but observational quantification of the tightening rate is limited. …”
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The potential spatiotemporal distribution patterns of Avena nuda and Avena sativa from global perspective provide new insights for the cultivation of commonly cultivated oats by Huanhuan Lu, Yuying Zheng, Ting Zhao, Liuban Tang, Fan Zhang, Wengang Xie

“…This study comprehensively collected the geographic distribution and environmental data of A. nuda and A. sativa from global regions, the ensembled niche and Marxan model were used to predict the potential spatiotemporal distribution and planting pattern of commonly cultivated oats, and further explore the environmental factors that affected the spatial distribution and genetic diversity pattern. …”
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Estimation of Soil Organic Carbon Content of Grassland in West Songnen Plain Using Machine Learning Algorithms and Sentinel-1/2 Data by Haoming Li, Jingyao Xia, Yadi Yang, Yansu Bo, Xiaoyan Li

“…Nine experiments were conducted under three variable scenarios to select the optimal model. We used this optimal model to achieve high-precision predictions of SOC content. …”
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Design of vehicle data engine system based on big data platform and intelligent perception by CHEN Xijun

“…To this end, a set of vehicle data engine system was designed based on the big data platform and intelligent perception to clean and integrate the operation data of the traction, braking, door, network and LCU systems for the spatial and temporal alignment of data. In addition, data analysis strategy model was developed by means of drag and drop based on the canvas components to carry out multidimensional data analysis, make decisions, monitor the working process, identify hidden troubles and give early warning, and make life predictions, replacing the repetitive and complex manual operation. …”
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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…Finally, ResNet50 is selected as the backbone network, and a custom loss function is designed specifically for grasp detection tasks, which significantly enhances the model’s ability to predict feasible grasp boxes. The proposed G-RCenterNet algorithm is embedded into a robotic grasping system, where a structured light depth camera captures target images, and the grasp detection network predicts the optimal grasp box. …”
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Spatiotemporal wind speed forecasting using conditional local convolution and multidimensional meteorology features by Meng Wang, Juanle Wang, Mingming Yu, Fei Yang

“…While recent deep learning models have improved prediction accuracy, they often assume uniform influence weight structure, limiting model effectiveness. …”
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Fusion ConvLSTM-Net: Using Spatiotemporal Features to Increase Residential Load Forecast Horizon by Abhishu Oza, Dhaval K. Patel, Bryan J. Ranger

“…We evaluated the model against several benchmark neural network models by: 1) testing different forecast window sizes ranging from 1.5 to 24 hours, 2) assessing model performance across multiple households, and 3) performing large-scale forecasting by aggregating predictions from 100 households. …”
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Enhancing Situational Awareness of Helicopter Pilots in Unmanned Aerial Vehicle-Congested Environments Using an Airborne Visual Artificial Intelligence Approach by John Mugabe, Mariusz Wisniewski, Adolfo Perrusquía, Weisi Guo

“…To this end, we aim to combine the strengths of both spatial and temporal deep learning models and classic computer stereo vision to (1) estimate the depth of UAVs, (2) predict potential collisions with other UAVs in the sky, and (3) provide alerts for the pilot with regards to the drone that is likely to collide. …”
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SA-I Mechanoreceptor Position in Fingertip Skin May Impact Sensitivity to Edge Stimuli by Gregory J. Gerling

“…The second result was that both models were equally capable of predicting the spatial structure within the in vivo neural responses, and therefore the addition of intermediate ridges did not help in differentiating the indenters. …”
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Exploring Shared Bicycle Travel Patterns from a Multidimensional Spatiotemporal Interaction Perspective Based on Tensor Decomposition: A Case Study of Central Shenzhen Area by Zheng Jixiang, Tao Haiyang, Zhuo Li, Shi Yufei, Bao Han, Huang Runjie

“…Initially, we used statistical methods to conduct an exploratory analysis of the data, uncovering the temporal, spatial, and Origin-Destination (OD) flow characteristics of urban cycling. …”
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Depression restoration in university students: Data-driven insights across three types of campus greennessOSF by Chaoyi Cui, Qianchen He, Huiming Liu

“…The data allow for a robust investigation into how different campus spatial configurations and green space attributes—such as accessibility, quality, and visual appeal—relate to student mental well-being. …”
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The Effects of Climate Change on Human Behavior and Stress by Mitra Sadat Fathifard, Fateme Javid, Abbas Rahdan

“…All processes and data analysis in GIS environment were assessed using the Inverse Distance Weighting (IDW) statistical model, which predicts the spatial structure of unknown points based on the correlation between measured points. …”
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Study on Dynamic Disaster in Steeply Deep Rock Mass Condition in Urumchi Coalfield by Xing-Ping Lai, Mei-Feng Cai, Fen-Hua Ren, Peng-Fei Shan, Feng Cui, Jian-Tao Cao

“…The stress-lever-rotation-effect (SLRE) model of fault-like mobilization was proposed preliminarily. …”
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Assessing Rainfall Erosivity with Artificial Neural Networks for the Ribeira Valley, Brazil by Reginald B. Silva, Piero Iori, Cecilia Armesto, Hugo N. Bendini

“…Soil loss is one of the main causes of pauperization and alteration of agricultural soil properties. Various empirical models (e.g., USLE) are used to predict soil losses from climate variables which in general have to be derived from spatial interpolation of point measurements. …”
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Simulated Directional Wave Spectra of the Wind Sea and Swell under Typhoon Mangkhut by Yu Yan, Mengxi Hu, Yugen Ni, Chunhua Qiu

“…A third-generation wave model is driven by the synthetic wind field combined with the revised Holland wind and surface wind product from the National Centers for Environmental Prediction (NCEP). …”
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A novel method for grading urban socio-economic development levels based on NTL data and Landsat data by Xiang Hua, Jiehai Cheng, Yuke Meng, Rongji Luo

“…Experimental results demonstrate that the proposed hybrid model achieves strong performance in predicting urban socio-economic development levels, with an accuracy of 86.2%. …”
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DMLU-Net: A Hybrid Neural Network for Water Body Extraction from Remote Sensing Images by Ziqiang Xu, Mingfeng Li, Haixiang Guo

“…To tackle these challenges, in this study, we present DMLU-Net, a U-shaped neural network integrated with a dynamic multi-kernel large-scale attention mechanism. The model employs a dynamic multi-kernel large-scale attention module (DMLKA) to enhance cross-scale feature capture; a spectral–spatial attention module (SSAM) in the decoder to boost water region sensitivity; and a dynamic upsampling module (DySample) in the encoder to restore image details. …”
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Design and parameter identification of the wireless torque test system for hybrid vehicles by LI Jie, ZHOU Yijian, GENG Chong, PANG Jinlu

“…These results validate the reliability of the test data and provide an effective data foundation for the accurate torque model prediction.…”
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