Developing a semi-automated technique of surface water quality analysis using GEE and machine learning: A case study for Sundarbans by Sheikh Fahim Faysal Sowrav, Sujit Kumar Debsarma, Mohan Kumar Das, Khan Mohammad Ibtehal, Mahfujur Rahman, Noshin Tabassum Hridita, Atika Afia Broty, Muhammad Sajid Anam Hoque

“…The predictive framework leverages Google Earth Engine (GEE) and AutoML, utilizing deep learning libraries to create dynamic, adaptive models that enhance prediction accuracy. …”
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Primer on machine learning applications in brain immunology by Niklas Binder, Ashkan Khavaran, Roman Sankowski

“…Newly developed foundation models present exciting opportunities for uncovering gene expression programs and predicting genetic perturbations. …”
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Equity Impacts of Transportation Improvements On Core and Peripheral Cities by Shlomo Bekhor, Eran Leck, Daniel Gat

“…The aim of this paper is to assess the short-term impact of transportation improvements on the reduction of socio-economic disparities between core and peripheral cities. …”
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Time-Series Mapping of PM10 Concentration Using Multi-Gaussian Space-Time Kriging: A Case Study in the Seoul Metropolitan Area, Korea by No-Wook Park

“…To account for the spatiotemporal autocorrelation structures of monitoring data and to model the uncertainties attached to the prediction, conventional multi-Gaussian kriging is extended to the space-time domain. …”
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Gradients in signal complexity of sleep-wake intracerebral EEG. by Giridhar Kalamangalam, Ioan Mircea Chelaru, Abbas Babajani-Feremi

“…Spatial variation in the morphology of the electroencephalogram (EEG) over the head is classically described. …”
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DEIKSIS PERSONA, RUANG, DAN WAKTU DALAM NOVEL HELLO KARYA TERE LIYE by Husnawati, Nyoman Sudika, Irma Setiawan

“…The study focuses on three types of deixis: person deixis, spatial deixis, and temporal deixis. Data collection was carried out using the listening and note-taking method, then analyzed using the Miles and Huberman model, which includes data reduction, data presentation, and conclusion drawing. …”
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Asthma prevalence and risk factors in Poonch and Rajouri districts, India: an epidemiological and geospatial analysis by Arshad Ahmed, Kheraj, Jorge Rocha, Alireza Mohammadi

“…To determine asthma risk factors, we applied a binary logistic regression model (BLRM), with model fit assessed via pseudo-R² and Hosmer-Lemeshow tests, and predictive accuracy evaluated through receiver operating characteristic (ROC) curve analysis. …”
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Improvement of SAM2 Algorithm Based on Kalman Filtering for Long-Term Video Object Segmentation by Jun Yin, Fei Wu, Hao Su, Peng Huang, Yuetong Qixuan

“…The Kalman filter models object motion using physical constraints to predict trajectories and dynamically refine segmentation states, mitigating positional drift during occlusions or velocity changes. …”
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Cerebral gray matter volume identifies healthy older drivers with a critical decline in driving safety performance using actual vehicles on a closed-circuit course by Handityo Aulia Putra, Kaechang Park, Kaechang Park, Fumio Yamashita

“…The Random Forest model demonstrated high accuracy and specificity, but moderate precision and recall, limiting immediate real-world application.DiscussionWhile regional GM volume shows promise for identifying older drivers at risk of critical DSP decline, predictive performance remains suboptimal for practical implementation. …”
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BLVQE: Blind Laparoscopic Video Quality Evaluator using spatio-temporal interdependency and textural cues by Sria Biswas, Rohini Palanisamy

“…These feature vectors are used for end-to-end training of an LSTM framework for frame quality predictions. The training and validation loss curves of the model saturate around 50 epochs, indicating prediction proficiency. …”
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Mapping Soil Organic Matter in Black Soil Cropland Areas Using Remote Sensing and Environmental Covariates by Yu Zhang, Chong Luo, Wenqi Zhang, Zexin Wu, Deqiang Zang

“…Combining three types of environmental covariates such as drainage, climate and topography, the study area was categorized into dry field and paddy field. Then, the SOM prediction model was constructed using random forest regression method and the accuracy of different strategies was evaluated by 10-fold cross-validation. …”
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The Combination Application of FY-4 Satellite Products on Typhoon Saola Forecast on the Sea by Chun Yang, Bingying Shi, Jinzhong Min

“…Effective comprehensive application of satellite products will inevitably improve numerical weather prediction. FengYun-4 (FY-4) series satellites can provide not only radiance data but also retrieval data with high temporal and spatial resolutions. …”
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Seasonal El Niño‐Southern Oscillation and Indian Ocean Dipole Dependencies of Methane Emissions From Wetlands by Tingting Zhu, Yanlian Zhou, Weimin Ju

“…This study underscored the pronounced temporal and spatial variability of CH4 emission anomalies under ENSO and IOD phases, which would improve the accuracy of predictive CH4 models and inform strategies for mitigating climate change.…”
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Spatiotemporal dynamics of ecological quality and its drivers in Shanxi Province and its planned mining areas by Lulu Chen, Huabin Chai, Weibing Du, Zengzeng Lian, Yu Wang, Chunyi Li, Lailiang Cai, Lei Zhang

“…The GWR model further reveals spatial heterogeneity in these relationships, uncovering localized effects, spatial gradient patterns, and clustering phenomena. …”
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ST-AGRNN: A Spatio-Temporal Attention-Gated Recurrent Neural Network for Traffic State Forecasting by Jian Yang, Jinhong Li, Lu Wei, Lei Gao, Fuqi Mao

“…Firstly, in terms of spatial correlation, some models only consider the road network structure information, and ignore the relative location relationships between nodes. …”
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Organoid‐Guided Precision Medicine: From Bench to Bedside by Boqiang Tao, Xiaolan Li, Ming Hao, Tian Tian, Yuyang Li, Xiang Li, Chun Yang, Qirong Li, Qiang Feng, Hengzong Zhou, Yicheng Zhao, Dongxu Wang, Weiwei Liu

“…For instance, patient‐derived tumor organoids preserve tumor heterogeneity and genomic profiles, serving as predictive platforms for individualized chemotherapy responses. …”
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The Potential of Informal Green Space (IGS) in Enhancing Urban Green Space Accessibility and Optimization Strategies: A Case Study of Chengdu by Yu Zou, Liwei Zhang, Wen Huang, Jiao Chen

“…The findings indicate that (1) IGS in the narrow sense constitute 21.2% of the overall green spaces within the study area, resulting in a reduction of the Gini coefficient by 0.103; (2) IGS in the broad sense, including public affiliated green spaces, shows an even more positive effect on improving the equity of green space supply, with a reduction of the Gini coefficient by 0.28; (3) there exists great spatial disparity in accessibility improvement effect by different types of IGS, so public policies must be customized to reflect local circumstances, taking into account the practicality and associated costs of management and maintenance of various IGS as well as accessibility enhancement; (4) certain older residential areas may not be amenable to effective enhancement through the use of IGS alone, and these should then adopt a multidimensional greening strategy such as green-roof. …”
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Multiscale exploration of spatiotemporal dynamics and decoupling effects of carbon emissions in China by Chong Liu, Xiaoman Wang, Haiyang Li

“…This paper combined energy consumption data with nighttime light data and adopted a spatial autocorrelation, variation coefficient (VC), and decoupling model to study the spatiotemporal dynamics and decoupling effect of CE at the three administrative scales of provinces, prefecture-level cities, and counties in China from 2000 to 2020. …”
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Attention residual network for medical ultrasound image segmentation by Honghua Liu, Peiqin Zhang, Jiamin Hu, Yini Huang, Shanshan Zuo, Lu Li, Mailan Liu, Chang She

“…Finally, the predictive efficacy of the model was evaluated using publicly accessible breast ultrasound and thyroid ultrasound data. …”
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SAL Method Applied in Grid Forecasting Product Verification with Three-Source Fusion Product by Debin Su, Jinhua Zhong, Yunong Xu, Linghui Lv, Honglan Liu, Xingang Fan, Lin Han, Fuzeng Wang

“…Therefore, forecasters can better understand the model prediction effect and what needs to be improved.…”
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