Load aggregator adjustable capability forecasting based on graph convolution neural network by DONG Lingrui, WU Binyuan

“…Through the message transmission process on the graph, the response characteristics of different clusters could be shared, and both the historical data of the targeted node and other nodes are effectively used to improve the prediction accuracy from both spatial and temporal aspects. …”
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Long-term exposure to PM2.5 and cardiorespiratory mortality: an ecological small-area study in five cities in Colombia by Diana Marín, Víctor Herrera, Juan Gabriel Piñeros-Jiménez, Oscar Alberto Rojas-Sánchez, Sonia C. Mangones, Yurley Rojas, Jhon Cáceres, Dayana M. Agudelo-Castañeda, Néstor Y. Rojas, Luis Carlos Belalcazar-Ceron, Jonathan Ochoa-Villegas, María Leonor Montes-Mejía, Veronica Maria Lopera-Velasquez, Sanit María Castillo-Navarro, Alexander Torres-Prieto, Jill Baumgartner, Laura A. Rodríguez-Villamizar

“…Cardiorespiratory mortality spatially clustered in some Colombian cities and was associated with long-term exposure to PM2.5 in urban areas where the LUR models had the highest predictive accuracy. …”
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The effect of nutrient transport downstream on food web stability in an experimental freshwater meta-ecosystem by Xueqi Wang, Megan Braun, Ella McGuigan, Kevin S. McCann, Robert H. Hanner, John M. Fryxell

“…Recent spatial nutrient transport theory suggests that accumulation of nutrients downstream in riverine systems can amplify the magnitude of phytoplankton and zooplankton blooms and/or lead to competitive replacement of phytoplankton by less edible species, such as cyanobacteria. …”
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A Review of Artificial Intelligence and Deep Learning Approaches for Resource Management in Smart Buildings by Bibars Amangeldy, Timur Imankulov, Nurdaulet Tasmurzayev, Gulmira Dikhanbayeva, Yedil Nurakhov

“…This review shows that AI-driven controllers—especially deep-reinforcement-learning agents—deliver median energy savings of 18–35% for HVAC and other major loads, consistently outperforming rule-based and model-predictive baselines. The evidence further reveals a rapid diversification of methods: graph-neural-network models now capture spatial interdependencies in dense sensor grids, federated-learning pilots address data-privacy constraints, and early integrations of large language models hint at natural-language analytics and control interfaces for heterogeneous IoT devices. …”
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Daily-scale dataset of highly dynamic water of Poyang Lake by Yuqing Wang, Shuai Wang, Tingsong Gong, Haifeng Tian, Yaochen Qin, Yijie Ma, Xueyue Liang, Jie Pei, Li Wang

“…Finally, we realized the spatial inversion of the predicted area and constructed a daily-scale water dataset of Poyang Lake (2016–2021). …”
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Space Deficits in Parkinson’s Disease Patients: Quantitative or Qualitative Differences from Normal Controls? by D. Natsopoulos, M.-S. Bostantzopoulou, Z. Katsarou, G. Grouios, G. Mentenopoulos

“…Twenty-seven patients with idiopathic Parkinson's disease (PD) and the same number of normal controls (NCs) were studied on a test battery including five conceptual categories of spatial ability. The two groups of subjects were matched for age, sex, years of education, socioeconomic status and non-verbal (Raven Standard Progressive Matrices) intelligence. …”
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Toward a Multidecadal SAR Analysis of Sea Ice Types in the Atlantic Sector of the Arctic Ocean by Wenkai Guo, Jack Landy, Johannes Lohse, Anthony P. Doulgeris, Malin Johansson, Torbjorn Eltoft, Polona Itkin, Shiming Xu

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Urban expansion, economic development, and carbon emissions: Trends, patterns, and decoupling in mainland China’s provincial capitals (1985–2020) by Jiahui Zhao, Wei Chen, Zixuan Liu, Wei Liu, Keyan Li, Bei Zhang, Yonggen Zhang, Le Yu, Tetsuro Sakai

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The effect of slab touchdown on anticrack arrest in propagation saw tests by P. L. Rosendahl, J. Schneider, G. Bobillier, F. Rheinschmidt, B. Bergfeld, A. van Herwijnen, P. Weißgraeber

“…<p>Understanding crack phenomena in the snowpack and their role in avalanche formation is imperative for hazard prediction and mitigation. Many studies have explored how structural properties of snow contribute to the initial instability of the snowpack, focusing particularly on failure initiation within weak snow layers and the onset of crack propagation. …”
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Measured spectrum environment map dataset with multi-radiation sources in urban scenariosMendeley Data by Haotian Zou, Qiuming Zhu, Qianhao Gao, Jie Wang, Zhipeng Lin, Yang Huang, Qihui Wu, Weizhi Zhong

“…Its applications include the verification of spectrum map completion algorithms, wireless channel modelling, deep learning-driven signal prediction, and the optimization of Wi-Fi/cellular networks.…”
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Condition monitoring of heterogeneous landslide deformation in spatio-temporal domain using advanced graph attention network by Huajin Li, Yu Zhu, Qiang Xu, Ran Tang, Chuanhao Pu, Yusen He

“…Field observations reveal that deformation processes are typically uneven and heterogeneously distributed across slope bodies, creating dynamic uncertainties that challenge prediction models. This research aims to develop an enhanced spatial-temporal monitoring system capable of capturing these complex deformation patterns. …”
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Conv1D-GRU-Self Attention: An Efficient Deep Learning Framework for Detecting Intrusions in Wireless Sensor Networks by Kenan Honore Robacky Mbongo, Kanwal Ahmed, Orken Mamyrbayev, Guanghui Wang, Fang Zuo, Ainur Akhmediyarova, Nurzhan Mukazhanov, Assem Ayapbergenova

“…It achieved an accuracy of 98.6%, precision of 98.63%, recall of 98.6%, F1-score of 98.6%, and an ROC-AUC of 0.9994, indicating strong predictive capability even with imbalanced data. In addition to centralized training, the model was tested under cooperative, node-based learning conditions, where each node independently detects anomalies and contributes to a collective decision-making framework. …”
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Evolutionary Patterns of Collagen Fiber Arrangement and Calcification in Atherosclerosis by Chunyang Ma, Zhenzhen Jia, Shuaiyin Liu, Xiangyi Liao, Hongyan Kang, Xufeng Niu, Yubo Fan

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Structure and oxygen saturation recovery of sparse photoacoustic microscopy images by deep learning by Shuyan Zhang, Jingtan Li, Lin Shen, Zhonghao Zhao, Minjun Lee, Kun Qian, Naidi Sun, Bin Hu

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Citizen-led initiatives and hydro-meteorological risks reduction: Who is implementing nature-based solutions? by Yaw Agyeman Boafo, Kirk B. Enu, Kofi Dua Agyei, Jude Dokbila Kolog

“…This study surveyed 1286 respondents across the dense Greater Accra Metropolitan Area (GAMA) and the rapidly growing Greater Kumasi Metropolitan Area (GKMA) in Ghana to map citizen-led initiatives and identify factors influencing NbS adoption using a multinomial logit model. The results show that GAMA residents predominantly rely on non-structural measures, such as temporary relocation and water conservation, reflecting spatial constraints and dense urban form. …”
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Estimating comprehensive growth index for drip-irrigated spring maize in junggar basin via satellite imagery and machine learning by Mingjie Ma, Jinghua Zhao, Tingrui Yang, Feng Liu, Yingying Yuan, Shijiao Ma, Zikang Chang

“…Shapley analysis scientifically demonstrated that RDVI was the most influential factor in the SSA-RF model's CGI predictions in total stage. Additionally, the study generated field-scale CGI spatiotemporal distribution maps, revealing the temporal and spatial variation patterns of crop growth. …”
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Photon–photon chemical thermodynamics of frequency conversion processes in highly multimode systems by Huizhong Ren, Georgios G. Pyrialakos, Qi Zhong, Fan O. Wu, Mercedeh Khajavikhan, Demetrios N. Christodoulides

“…Abstract Frequency generation in highly multimode nonlinear optical systems is inherently a complex process, giving rise to an exceedingly convoluted landscape of evolution dynamics. While predicting and controlling the global conversion efficiencies in such nonlinear environments has long been considered impossible, here, we formally address this challenge even in scenarios involving a very large number of spatial modes. …”
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Analysis of Dust Storm Intensity over Baghdad City by Asmaa K. Hammoodi, Ahmed S. Hassan, Jasim H. Kadhum, Xiu-Qun Yang

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Evaluation of Solar Energy Performance in Green Buildings Using PVsyst: Focus on Panel Orientation and Efficiency by Seyed Azim Hosseini, Seyed Alireza Mansoori Al-yasin, Mohammad Gheibi, Reza Moezzi

“…Energy outputs derived from spreadsheet-based models and PVSyst simulations were compared to validate results. …”
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Beacon2Science: Enhancing STEREO/HI Beacon Data With Machine Learning for Efficient CME Tracking by J. Le Louëdec, M. Bauer, T. Amerstorfer, J. A. Davies

“…However, previous work concluded that CME arrival prediction based on beacon data could not achieve the same accuracy as with high‐resolution science data due to data gaps and lower quality. …”
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