Urban pertussis epidemiological patterns in a highly vaccinated megacity: Policy impacts and control strategies in Chongqing, China, 2005-2024 by Rui Shen, Jiawei Xu, Yugang Li, Jianxing Yu, Na Sun, Zilu Xu, Xueying Xu, Xiao Liu, Yang Liu, Bosong Li, Li Qi, Luzhao Feng

“…Methods: Using population-based surveillance data (2005-2024) from Chongqing (population 32.1 million; DTP3 coverage >97%), we conducted hierarchical Bayesian spatial modeling and age-structured Susceptible-Infected-Recovered-Vaccinated transmission analysis. …”
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A Novel Dual-Stream Attention-Based Hybrid Network for Solar Power Forecasting by Rafiq Asghar, Michele Quercio, Lorenzo Sabino, Assia Mahrouch, Francesco Riganti Fulginei

“…Subsequently, the predictive accuracy of the developed model is compared with three single and five hybrid deep learning models. …”
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Lip-Reading Classification of Turkish Digits Using Ensemble Learning Architecture Based on 3DCNN by Ali Erbey, Necaattin Barışçı

“…While LSTM models are effective in processing temporal data, 3DCNN-based models, which can process both spatial and temporal information, achieved higher accuracy in this study. …”
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Synergistic Semantic Segmentation and Height Estimation for Monocular Remote Sensing Images via Cross-Task Interaction by Xuanang Peng, Shixin Wang, Futao Wang, Jinfeng Zhu, Suju Li, Longfei Liu, Zhenqing Wang

“…However, due to factors such as complex semantic categories and the inconsistent spatial scales of remotely sensed images, existing multi-task learning methods often fail to achieve better results on these two tasks. …”
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Geochemical Influences on Carbon Nanotubes Transport in Subsurface Environments: Integrating Millifluidics, Spectral Induced Polarization, and Machine Learning by Yixin Yang, Pengfei Liu, Kexin Chen, Sheng Zhou, Longlong Meng, Chi Zhang, Junnan Cao, Bate Bate

“…SIP detected real‐time retention by chargeability (R2 = 0.82–0.96), while a DNN decoded SIP signals to predict spatially resolved CNT deposition (R2 = 0.926), outperforming phenomenological Cole‐Cole modeling. …”
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A Novel Monitoring Method of Wind-Induced Vibration and Stability of Long-Span Bridges Based on Permanent Scatterer Interferometric Synthetic Aperture Radar Technology by Jiayue Ma, Xiaojun Xue, Guoliang Zhi, Haoyang Zheng, Hanqing Zhu

“…Experimental results demonstrate that this method offers precise, real-time monitoring of wind-resistant stability. By leveraging the spatial accuracy and long-term monitoring capability of PS-InSAR, along with the time-series forecasting strength of ARMA models, the method enables data-driven analysis of bridge vibrations. …”
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Deep learning-based action recognition for analyzing drug-induced bone remodeling mechanisms by Li Qinsheng, Li Ming, Li Yuening, Zhao Xiufeng

“…Our framework leverages graph neural networks (GNNs) to model the spatial and temporal dependencies of multi-scale biological data, combined with a dynamic signal propagation model to identify key molecular interactions driving bone remodeling. …”
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The effects of seasonal human mobility and Aedes aegypti habitat suitability on Zika virus epidemic severity in Colombia. by Brandon Lieberthal, Brian Allan, Sandra De Urioste-Stone, Andrew Mackay, Aiman Soliman, Shaowen Wang, Allison M Gardner

“…Our research uses the novel approach of combining geographical modeling of mosquito presence with network modeling of human mobility to offer a comprehensive simulation environment for Zika virus epidemics that considers a substantial number of spatial and temporal factors compared to the literature. …”
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DTCMMA: Efficient Wind-Power Forecasting Based on Dimensional Transformation Combined with Multidimensional and Multiscale Convolutional Attention Mechanism by Wenhan Song, Enguang Zuo, Junyu Zhu, Chen Chen, Cheng Chen, Ziwei Yan, Xiaoyi Lv

“…Experiments on multiple wind-farm datasets and energy-related datasets demonstrate that DTCMMA outperforms mainstream methods such as Transformer, iTransformer, and TimeMixer in long-sequence forecasting tasks, achieving improvements in MSE performance by 34.22%, 2.57%, and 0.51%, respectively. The model’s training speed also surpasses that of the fastest baseline by 300%, significantly improving both prediction accuracy and computational efficiency. …”
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Spatiotemporal Dynamics and Driving Mechanisms of Ecosystem Services in the Beijing–Tianjin–Hebei Urban Agglomeration: Implications for Sustainable Land Use Planning by Shuanqging Sheng, Jinchuan Huang

“…This study unveils the spatial heterogeneity of ecosystem services and their driving mechanisms in the context of urbanization, offering valuable insights to inform regional ecological conservation and sustainable development policies.…”
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Computational principles of neural adaptation for binaural signal integration. by Timo Oess, Marc O Ernst, Heiko Neumann

“…The circuit incorporates an adaptation mechanism operating at the synaptic level based on local inhibitory feedback signals. The model's predictive power is demonstrated in various simulations replicating physiological data. …”
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Spatio-Temporal Variation and Drivers of Land-Use Net Carbon Emissions in Chengyu Urban Agglomeration, China by Wen Wang, Xin Wang, Li Wang, Zhihua Zhang, Daren Lyu

“…In this study, the land-use net carbon emissions (LCN) calculation and evaluation model was built based on the perspective of land-use change. …”
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Machine Learning and Spatio Temporal Analysis for Assessing Ecological Impacts of the Billion Tree Afforestation Project by Kaleem Mehmood, Shoaib Ahmad Anees, Sultan Muhammad, Fahad Shahzad, Qijing Liu, Waseem Razzaq Khan, Mansour Shrahili, Mohammad Javed Ansari, Timothy Dube

“…A predictive model for the Normalized Difference Vegetation Index (NDVI), supported by SHAP analysis, identified soil moisture and precipitation as primary drivers of vegetation growth, with the ANN model achieving an R2 of 0.8556 and an RMSE of 0.0607 on the testing dataset. …”
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On the division of things into immovable and movable by Nikolić Dušan Ž.

“…In this context, it should be noted that apart from the GPS, there are also precise digital programs and models that enable predictive land mapping (digital land surface models for predictive mapping). …”
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Enhancing Road Scene Segmentation With an Optimized DeepLabV3+ by Zhe Ren, Libao Wang, Tianming Song, Yihang Li, Jian Zhang, Fengfeng Zhao

“…Semantic segmentation, as a dense predictive task, is inevitably affected by various external factor, making common road image semantic segmentation models unable to meet dual demands of high accuracy and real-time performance in unstructured road scenarios. …”
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Analysis and Optimization of Soil Nail Parameters in a Deep Foundation Pit of Silty Clay Based on Response Surface Methodology by FAN Cheng, WANG Zi-yuan, QI Peng-fei, ZHANG Hong-bin, ZHANG Tiao-tiao

“…In the combined effect of support parameters, the soil nail length and spacing have the greatest impact on the safety factor. The predictive model established by the response surface method can provide the best optimization scheme. …”
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Artificial intelligence and machine learning to enhance critical mineral deposit discovery by Rhys S. Davies, McLean Trott, Jaakko Georgi, Alexander Farrar

“…Broader adoption of statistical methods, integrated spatial models, and innovative data preparation techniques can address the inconsistencies in exploration datasets. …”
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Local response to global risk: a case study of risk perception and communication on Chinese social media regarding Fukushima’s treated radioactive water discharge by Chenxi Sun, Qingliu Ren, Yuejing Ge

“…Three key findings emerge: (1) Temporal dynamics dominate public engagement, with attention peaking within two weeks post-discharge before gradually declining, while fear persists as the predominant emotion despite diminishing anger responses; (2) Coastal regions demonstrate heightened participation due to geographic proximity and seafood consumption patterns, though risk perception shows no consistent spatial gradient; (3) Socioeconomic factors - particularly education levels and seafood consumption - significantly predict communication intensity, whereas economic indicators like per capita GDP show limited influence. …”
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Optimization of an aircraft flight trajectory in the GLONASS dynamic accuracy field by O. N. Skrypnik, N. G. Arefyeva, R. O. Arefyev

“…The accuracy field of the satellite navigation systems can be characterized by the geometric factor (spatial, horizontal and vertical). The geometric factor of the satellite navigation system is determined by the relative position of the consumer and the satellites upon which the navigation problem is solved, and is a deterministic value. …”
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Enhanced characterization of hydraulic conductivity via standard penetration test for sandy soils and weathered rocks by Wanhyuk Seo, Eomzi Yang, Tae Sup Yun

“…This approach significantly enhances spatial and depth-wise characterization of subsurface K, offering a practical solution for groundwater flow modeling and geotechnical design with improved resolution.…”
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