Delineation of future urban growth boundaries on the Qinghai-Xizang Plateau by integrating socioeconomic development and ecosystem services conservation by Qiaoxian Bai, Zhifeng Liu, Binghua Gong, Shuhui Liu, Xufeng Mao, Chunyang He

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Using New York City’s Geographic Data in an Innovative Application of Generative Adversarial Networks (GANs) to Produce Cooling Comparisons of Urban Design by Yuanyuan Li, Lina Zhao, Hao Zheng, Xiaozhou Yang

“…This model can rapidly generate visual LST predictions under various configuration scenarios. …”
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Temporal Stability of Plant Species α-Diversity in Alpine Grasslands of the Tibetan Plateau and Their Implications for Biodiversity Conservation by Tianyu Li, Wei Sun, Shaowei Li, Erfu Dai, Gang Fu

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Autonomous inverse encoding guides 4D nanoprinting for highly programmable shape morphing by Shuaiqi Ren, Zhiang Zhang, Ruokun He, Jiahao Fan, Guangming Wang, Hesheng Wang, Bing Han, Yong-Lai Zhang, Zhuo-Chen Ma

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Assessing the declining trend in soil erodibility across China: A comparison of conventional and digital K-factor maps by Zhiyuan Tian, Yan Zhao, Longxi Cao, Yuan Zhao, Yin Liang

“…A digital K-factor map at the 250 m spatial resolution was generated by calculating the K values from soil survey points as training data and using environmental information as predictive variables. …”
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Interpretable machine learning analysis of environmental characteristics on bacillary dysentery in Sichuan Province by Yao Zhang, Qiao-Lin Wang, Wei Peng, Meng-Yuan Zhang, Yao Qin, Lun Zhang, Rong-Jie Wei, Dian-Ju Kang

“…Additionally, precipitation displayed a U-shaped relationship with BD risk in both the Subtropical Semi-Humid and Plateau Cold Climate Zones.ConclusionThis study developed a climate zone-specific predictive model for BD, systematically evaluating the interactions between environmental factors and BD dynamics. …”
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Facial Anatomy Teaching for Aesthetic Surgery: Using 3-dimensional Photogrammetry and Immersive Virtual Reality by Sara M. Hussein, MD, Andrew F. Emanuels, MD, Luciano César P.C. Leonel, PhD, Nirusha Lachman, PhD, Maria Peris Celda, MD, PhD, Jonathan M. Morris, MD, Eric M. Sheahan, BA, Erick O. Martinez, BFA, Christian R. Hanson, BA, Basel A. Sharaf, MD, DDS, FACS

“…Although cadaveric dissection remains a valuable teaching tool, its accessibility is limited by cost, ethical concerns, and the lack of structured curricula, making it less feasible for ongoing surgical education. To address these limitations, this article introduced a novel educational approach that integrates 3D photogrammetry and virtual reality technology into the surgical anatomy curriculum for craniofacial and aesthetic surgery. …”
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DWE: Research on Water Quality Inversion and Scalability in Small Watersheds Using UAV Remote Sensing Data by Hao Li, Zhijun Xie, Xing Jin, Changchun Peng, Cheng Ren, Yunfei Mao, Kefan Zhou, Yingying Li

“…The results show that the DWE model based on optimal features has high accuracy and robustness in WQP prediction, with coefficients of determination (<inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>) of 0.8472, 0.8547, 0.8973, and 0.8393 for chlorophyll a (Chl-a), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP), respectively, which improved the prediction accuracy by nearly 30% compared with the traditional inversion model. …”
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Envisioning urban environments resilient to vector-borne diseases: a protocol to study dengue in Vietnam by Praveen Kumar, Thanh H. Nguyen, Phong V.V. Le, Jinhui Yan, Lei Zhao, Brian F. Allan, Andrew W. Taylor-Robinson

“…Coupled with human population distribution (density, locations), atmospheric conditions (air temperature, precipitation), and hydrological conditions (soil moisture distribution, ponding persistence in topographic depressions), modeling has improved predictive ability for infection rates. …”
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High-resolution Annual Dynamic dataset of Curve Number from 2008 to 2021 over Conterminous United States by Qiong Wu, John J. Ramirez Avila, Jia Yang, Cunxiong Ji, Shanmin Fang

“…Abstract The spatial distribution and data quality of curve number (CN) values determine the performance of hydrological estimations. …”
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Simulation and Numerical Analysis of Energy-and-Ecological Compatibility of Indoor Plant Lighting by S. A. Rakutko, E. N. Rakutko

“…Theoretically, possible reduction of losses in the source of electrical power is 22 percent, in the optical part – 14 percent; in spatial fl ow distribution – 16 percent; in surface fl ow distribution – 10 percent. …”
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Spatiotemporal DeepWalk Gated Recurrent Neural Network: A Deep Learning Framework for Traffic Learning and Forecasting by Jian Yang, Jinhong Li, Lu Wei, Lei Gao, Fuqi Mao

“…Three publicly available datasets with different time granularities of 15, 30, and 60 min are used to validate the short- and long-time prediction effect of this model. The results show that the ST-DWGRU model significantly outperforms the state-of-the-art baselines.…”
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Hyperspectral Image Change Detection Method Based on the Balanced Metric by Xintao Liang, Xinling Li, Qingyan Wang, Jiadong Qian, Yujing Wang

“…In the testing phase, the prediction map is generated by simple thresholding of distance maps. …”
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Assessing particulate matter (PM2.5) concentrations and variability across Maharashtra using satellite data and machine learning techniques by Ganesh Machhindra Kunjir, Suvarna Tikle, Sandipan Das, Masud Karim, Sujit Kumar Roy, Uday Chatterjee

“…In this context, the present study aims to predict PM2.5 concentrations across Maharashtra, India, for the year 2023, employing machine learning models to improve spatial and temporal air quality assessments. …”
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Estimating spatiotemporal patterns of deaths by COVID-19 outbreak on a global scale by Fernanda Valente, Marcio Poletti Laurini

“…Based on the measures of dispersion of the models’ prediction in relation to observed deaths, it is possible to note that the models with spatial component are significantly superior to the univariate model.Conclusion The findings suggested that the spatial dynamics have an important role in the COVID-19 epidemic process since the results provided evidence that spatiotemporal models are more accurate to estimate the general patterns of the occurrence of deaths related to COVID-19.…”
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Decision support system for Lespedeza cuneata production and quality evaluation: a WebGIS dashboard approach to precision agriculture by Sudhanshu S. Panda, Aftab Siddique, Thomas H. Terrill, Ajit K. Mahapatra, Eric Morgan, Andres A. Pech-Cervantes, Jan A. van Wyk

“…The model incorporates multi-criteria environmental parameters, including soil characteristics, topography, and climate variability, to generate spatially explicit recommendations. …”
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The Analysis of Downscaling Results of Weather Parameters for Iran Future by Maryam Bayatvarkeshi, rojin fasihi

“…The purpose of this research is to predict the weather parameters changes under different scenario of LARS- WG downscaling model over the country in future. 2-Materials and Methods In this study, the effect of climate change on temperature, solar radiation and precipitation, as the most important parameters of country in future years, were evaluated. …”
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Explainable AI-driven assessment of hydro climatic interactions shaping river discharge dynamics in a monsoonal basin by Prashant Parasar, Akhouri Pramod Krishna

“…The main findings of this study are (1) KAN demonstrated high predictive performance with root mean squared error (RMSE) values ranging from 42.7 to 58.3 m3/s, Nash–Sutcliffe efficiency (NSE) between 0.80 and 0.87, mean absolute error (MAE) between 28.9 to 52.7 and R2 values between 0.84 and 0.90 across stations. (2) SHAP based feature contribution analysis identified Relative humidity (hurs), specific humidity (huss), and temperature (tas) as key predictors, while (pr) showed limited contribution due to spatial inherent inconsistencies in GCM precipitation data. (3) The bootstrapped SHAP distributions highlighted substantial variability in feature importance, particularly for humidity variables, revealing station specific uncertainty patterns in model interpretation. (4) The KAN framework results indicate strong temporal alignment and physical realism, confirming KAN’s robustness in capturing seasonal discharge dynamics and extreme flow events under monsoon influence environments. (5) In this study KAN with SHAP (SHapley additive exPlanations) is implemented for hydrological modeling under monsoon-influenced and data-limited regions such as SRB, offering improved accuracy, functional precision and efficiency compared to traditional models. …”
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Analyses of biomarkers for tremor using local field potentials recorded from deep brain stimulation electrodes in the thalamus by Karthik Kumaravelu, Stephen L. Schmidt, Yi Zhao, Allison Vittert, Brandon D. Swan, Chintan S. Oza, Jennifer J. Peters, Kyle T. Mitchell, Dennis A. Turner, Warren M. Grill

“…Then, we simulated the effects of DBS and spatial distribution of tremor cells on calculated LFPs in a TH model. …”
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Effect of fibroblast heterogeneity on prognosis and drug resistance in high-grade serous ovarian cancer by Tingjie Wang, Lingxi Tian, Bing Wei, Jun Li, Cuiyun Zhang, Ruitao Long, Xiaofei Zhu, Yougai Zhang, Bo Wang, Guangbo Tang, Jun Yang, Yongjun Guo

“…Finally, we constructed a panel of 24 genes through statistical modeling that correlate with CXCL12-positive fibroblasts and can predict both prognosis and the response to chemotherapy in HGSOC patients. …”
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