Effect of nuclear medium on the spatial distribution of pions by Satyajit Puhan, Navpreet Kaur, Arvind Kumar, Suneel Dutt, Harleen Dahiya

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Importance of Considering Seasonality in Tick Activity When Assessing Spatial Expansion Potential: A Case Study on Haemaphysalis longicornis by Younjung Kim, Raphaëlle Métras

“…In this study, we mapped the spatial expansion risk of H. longicornis in North America and Europe by training a habitat suitability model with its occurrence data from East Asia and Oceania. …”
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Spatial distribution of acute myeloid leukaemia in Denmark by Rikke Hedegaard Jensen, Christian Teglgaard, Lars Hernández Nielsen, Lise Dueholm Bertelsen, Heidi Søgaard Christensen, Martin Bøgsted, Marianne Tang Severinsen

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Urban air pollution and spatial strategic response by Chuyi Fang, Yuqing Zhao

“…We first develop a theoretical model in which environmental standards function as strategic complements, predicting that a prefecture’s pollution control efforts are positively influenced by those of neighboring regions. …”
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Evaluating logistic regression and geographically weighted logistic regression models for predicting orange-fleshed sweet potato adoption intention in Benin by Idrissou Ahoudou, Nicodeme V. Fassinou Hotegni, Charlotte O. A. Adjé, Tania L. I. Akponikpè, Dêêdi E. O. Sogbohossou, Nadia Fanou Fogny, Françoise Assogba Komlan, Ismail Moumouni-Moussa, Enoch G. Achigan-Dako

“…The GWLR model excels in elucidating the spatial nuances of diverse factors, offering a promising avenue for more reliable predictions for OFSP adoption.…”
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Spatial analysis of prehospital emergency medical services accessibility: a comparative evaluation of the GAUSS-probability two-step floating catchment area model in Handan City by Feng Tian, Feng Tian, Feng Tian, Saicong Lu, Saicong Lu, Saicong Lu, Zhenjie Yang, Tingting Zhao, Tingting Zhao, Tingting Zhao, Penghui Li, Penghui Li, Penghui Li, Haifang Zhang

“…In this study, the GAUSS-Probability Two-step Floating Catchment Area (GP2SFCA) method was applied to evaluate the spatial distribution of access to prehospital EMS in Handan City and to assess accessibility differences by comparing it with various models.ResultsThe results demonstrated that the GP2SFCA model achieved significantly improved performance, with an average correlation coefficient of 0.7017, indicating a notably higher predictive accuracy. …”
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Assessing Coincidence of Satellite Acquisitions and Flood Events to Predict Suitability for Flood Map Synthesis by Lyle Prince, Riley C. Hales, Kel N. Markert, E. James Nelson, Gustavious P. Williams, Daniel P. Ames, Hyongki Lee, Amirhossein Rostami

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Air pollution’s numerical, spatial, and temporal heterogeneous impacts on childhood hand, foot and mouth disease: a multi-model county-level study from China by Zhangying Tang, Qi Sun, Jay Pan, Mingyu Xie, Zhoufeng Wang, Xiaojun Lin, Xiuli Wang, Yumeng Zhang, Qingping Xue, Yanchen Bo, Jinfeng Wang, Xin Liu, Chao Song

“…Conclusions This study underscores the nuanced and three-perspective heterogeneous influences of air pollution on HFMD in small areas, emphasizing the need for differentiated, localized, and time-sensitive prevention and control strategies to enhance the precision of dynamic early warnings and predictive models for HFMD and other infectious diseases, particularly in the fields of environmental and spatial epidemiology.…”
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A Review of Wind Power Prediction Methods Based on Multi-Time Scales by Fan Li, Hongzhen Wang, Dan Wang, Dong Liu, Ke Sun

“…Common classification angles of wind power prediction methods are outlined. By synthesizing existing approaches through multi-time scales, from the ultra-short term and short term to mid-long term, the review further deconstructs methods by model characteristics, input data types, spatial scales, and evaluation metrics. …”
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MODEL SPACE TIME AUTOREGRESSIVE INTEGRATED (STARI) UNTUK DATA DEBIT AIR SUNGAI CITARUM DI PROVINSI JAWA BARAT by Mutik Alawiyah, Dianne Amor Kusuma, Budi Nurani Ruchjana

“…The spatial lag used in this study was the spatial lag of order 2, so the Citarum river water discharge could be predicted with the STARI model. …”
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Unmanned Aerial Vehicles Applicability to Mapping Soil Properties Under Homogeneous Steppe Vegetation by Azamat Suleymanov, Mikhail Komissarov, Mikhail Aivazyan, Ruslan Suleymanov, Ilnur Bikbaev, Arseniy Garipov, Raphak Giniyatullin, Olesia Ishkinina, Iren Tuktarova, Larisa Belan

“…We used an area in the Eurasian steppe zone (Republic of Bashkortostan, Russia) covered with the <i>Stipa</i> vegetation type as a test plot, and collected 192 soil samples from it. We estimated the models using a cross-validation approach and spatial prediction uncertainties. …”
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Using Temporal Deep Learning Models to Estimate Daily Snow Water Equivalent Over the Rocky Mountains by Shiheng Duan, Paul Ullrich, Mark Risser, Alan Rhoades

“…To train the DL models, Snow Telemetry (SNOTEL) station‐based SWE observations are used as the prediction target. …”
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Multi-scenario land use change simulation and spatial-temporal evolution of carbon storage in the Yangtze River Delta region based on the PLUS-InVEST model. by Jingru Zhou, Verner Carl Johnson, Jingchao Shi, Mou Leong Tan, Fei Zhang

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Spatial-temporal patterns and predictors of timing and inadequate antenatal care utilization in Zambia: A Generalized Linear Mixed Model (GLMM) investigation from 1992 to 2018. by Samson Shumba, Isaac Fwemba, Violet Kaymba

“…Predictors of inadequate utilisation of ANC were identified through the multilevel generalised linear model. Spatial effects were modeled using Quantum Geographic Information System (QGIS) version 3.34.1 to develop univariate choropleth maps. …”
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Spatial-and-local-aware deep learning approach for Ground-Level NO2 estimation in England with multisource data from satellite-based observations and chemical transport models by Siying Wang, Shuangyin Zhang, Dawei Wang, Weifeng Li

“…The prediction model achieved R2 values of 0.914, 0.919, and 0.887 for 2019, 2020, and 2021, respectively, and performed well in urban regions. …”
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Predicting Wheat Potential Yield in China Based on Eco-Evolutionary Optimality Principles by Shen Tan, Shengchao Qiao, Han Wang, Sheng Chang

“…However, most existing crop models for wheat PY rely on type-specific parameters that describe wheat traits, which often require calibration and, in turn, reduce prediction confidence when applied across different spatial or temporal scales. …”
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Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer by Zhenwei Wang, Zhihong Dai, Yuren Gao, Zhongxiang Zhao, Zhen Li, Liang Wang, Xiang Gao, Qiuqiu Qiu, Xiaofu Qiu, Zhiyu Liu

“…Abstract Prostate cancer (PCa) remains a leading cause of cancer-related mortality, necessitating robust prognostic models and personalized therapeutic strategies. This study integrated bulk RNA sequencing, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics to construct a prognostic model based on genes shared between ferroptosis and fatty acid metabolism (FAM). …”
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Constraint-incorporated deep learning model for predicting heat transfer in porous media under diverse external heat fluxes by Ziling Guo, Hui Wang, Huangyi Zhu, Zhiguo Qu

“…The temperature field within porous media is considerably affected by different boundary conditions, and effective thermal conductivity varies with spatial structure morphologies. At present, traditional prediction methods for the temperature field are expensive and time consuming, particularly for large structures and dimensions, whereas deep learning surrogate models have limitations related to constant boundary conditions and two-dimensional input slices, lacking the three-dimensional topology and spatial correlations. …”
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Spatiotemporal Characteristics, Causes, and Prediction of Wildfires in North China: A Study Using Satellite, Reanalysis, and Climate Model Datasets by Mengxin Bai, Peng Zhang, Pei Xing, Wupeng Du, Zhixin Hao, Hui Zhang, Yifan Shi, Lulu Liu

“…Finally, we developed a prediction model for burned areas, leveraging the strong correlation between the FFMC and burned areas. …”
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Near real-time LOD prediction using ConvLSTM model through integrating IGS rapid LOD and effective angular momentum by Kehao Yu, Xiaoya Wang, Zhao Li, Jian Wang, Lihua Li, Weiping Jiang, Kai Yang, Jingwen Long, Yunzhao Li

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