FORECASTING OF POTATO YIELD ESTIMATION BY SATELLITE BASED REMOTE SENSING TECHNIQUE by Mohammad Mukhlesur Rahman, Mohammad Amirul Islam, Md. Golam Mahboob, Nur Mohammad, Istiak Ahmed

“…The goal of the study was to construct a remotely sensed yield prediction model that used the high spatial resolution of Sentinel 2A and Landsat 8 satellite images to forecast potato yield one month ahead of harvest. …”
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Bye-bye, Local-in-matter-density Bias: The Statistics of the Halo Field Are Poorly Determined by the Local Mass Density by Deaglan J. Bartlett, Matthew Ho, Benjamin D. Wandelt

“…Many models predict halos purely from the local Eulerian matter density, yet bias models in perturbation theory require other local properties. …”
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LSTA-CNN: A Lightweight Spatiotemporal Attention-Based Convolutional Neural Network for ASD Diagnosis Using EEG by Jing Li, Xiangwei Jia, Xinghan Chen, Gongfa Li, Gaoxiang Ouyang

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Supply and demand flow patterns and optimization of food ecosystem services in China’s Yangtze River Delta by Xiaoling Qiu, Xiaoling Qiu, Xinmei Wang, Xinmei Wang, Zeni Wang, Zeni Wang, Wei He, Wei He

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Transport equity assessment based on accessibility disparities in terms of multi-job opportunities across Beijing by Zhengbing Liu, Zhonglei Yu

“…Using the bivariate local spatial autocorrelation model to reveal the relationship between provision of accessibility and the population quantity of different groups in regions based on different transport modes. …”
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Artificial Intelligence for Organoids Multidimensional Assessment by Yulin Mo, Jian Wang, Huijian Yang, Long Bai, Ke Xu, Jiacan Su

“…ABSTRACT Organoids are tissue analogues formed through in vitro three‐dimensional culture of stem cells, possessing specific spatial structures. Organoids have become integral to various biomedical fields, including disease pathogenesis, model construction, regenerative and precision medicine, drug screening, tissue and organ development, toxicology, and pathological analysis. …”
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Estimation of Vehicle Dynamic Response from Track Irregularity Using Deep Learning Techniques by Fei Yang, Xiaoli Hao, Hang Zhang, Jie Jiang, Zhixing Fan, Zilong Wei

“…This paper proposes a deep learning model to predict vehicle responses (e.g., vertical wheel-rail forces, wheel unloading rate, and car body vertical acceleration) using deep learning techniques. …”
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Quantitative Evaluation for Reinforcement Effect of Auxiliary Steel Beams Based on Running Safety and Dynamic Response by Gong Kai, Liu Linya, Xiang Jun, Yang Haiming, Yu Cuiying

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A low illumination target detection method based on a dynamic gradient gain allocation strategy by Zhiqiang Li, Jian Xiang, Jiawen Duan

“…Firstly, efficient multi-scale feature fusion is performed by using a new neck structure in the original model so that it can fully exchange high-level semantic information and low-level spatial information. …”
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MACHINE LEARNING TECHNIQUES IN DETERMINING LAND SUITABLE FOR CEREAL CROPS IN IKERE EKITI, EKITI STATE, SOUTHWESTERN NIGERIA. by Ijaware Victor Ayodele, Kehinde Ruth Aniyikaye

“…Moreover, these data were processed with the aid of ArcGIS 10.7 Software and Machine Learning algorithm was used in predicting areas suitable for cereals crops. Results: The results revealed significant spatial variations in land suitability across Ikere Ekiti, with the machine learning models successfully identifying highly suitable zones for cereals crops. …”
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Investigating socioeconomic deprivation and antibiotic prescribing among older medicare patients using an instrumental variable approach by Mayar Al Mohajer, David Slusky, David Nix, Catia Nicodemo

“…The IV analysis then examined the relationship between predicted SDI and antibiotic days supplied (ln). Linear regression models estimated associations between SDI and its components, and antibiotic days supplied, adjusting for prescriber, beneficiary, and geographic factors. …”
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Minimizing Air Traffic Disruption from Uncontrolled Space Debris Reentries by Irina Beatrice Stefanescu, Cristian Emil Constantinescu, Octavian Thor Pleter

“…We propose utilizing dynamic airspace allocation techniques, using information derived by enhanced reentry prediction models and real-time tracking. Transforming the spatial problem of airspace closures into a temporal one, the study demonstrates the feasibility of confining closures to dynamically moving zones with minimal disruption. …”
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Pothole Detection and Assessment on Highways Using Enhanced YOLO Algorithm With Attention Mechanisms by Rufus Rubin, Chinnu Jacob, Sumod Sundar, Gabriel Stoian, Daniela Danciulescu, Jude Hemanth

“…The improved YOLO model, along with spatial and channel attention mechanisms, focuses on relevant regions and refines important features specific to pothole areas. …”
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Using fishery-related data, scientific expertise, and machine learning to improve marine habitat mapping in northeastern Mediterranean waters by Loukas Katikas, Sofia Reizopoulou, Paraskevi Drakopoulou, Vassiliki Vassilopoulou

“…A validation dataset and georeferenced data from previous studies were used to compare the accuracy and predictive performance of the models. Using this approach, the Saronikos Gulf was enriched with five more habitat types than visualised in the EMODnet portal, which also filled habitat gaps in areas where no data existed. …”
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GCN-Former: A Method for Action Recognition Using Graph Convolutional Networks and Transformer by Xueshen Cui, Jikai Zhang, Yihao He, Zhixing Wang, Wentao Zhao

“…The model integrates the Transformer architecture with traditional GCNs, leveraging the Transformer’s powerful capability for handling long-sequence data and the effective capture of spatial dependencies by GCNs. …”
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Blind Direction-of-Arrival Estimation with Uniform Circular Array in Presence of Mutual Coupling by Song Liu, Lisheng Yang, Shizhong Yang, Qingping Jiang, Haowei Wu

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A Two-Step Reconstruction Framework for Mapping Seamless All-Weather Daily Evapotranspiration Using Thermal Infrared Data by Gengle Zhao, Long Zhao, Lisheng Song, Hua Wu, Qiaoyun Xie, Shaomin Liu, Kejia Xue, Sinuo Tao, Penghai Wu, Lingfeng Zhang

“…ET has conventionally been generated using thermal infrared-based models, cloud contamination of satellite data could prohibit accurate estimates of spatial continuous daily ET. …”
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Airborne sound insulation performance of lightweight double leaf walls with different stud types by Hequn Min, Bo Wang, Ting Qu

“…To support performance-based design workflows, this paper presents an analytical model based on sound transmission path decoupling, enabling architects to quickly predict the STL of commonly used lightweight double leaf wall types, including wooden, steel, and acoustical stud constructions. …”
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Assessing climate-driven phenological responses of tomato crops under future climate change trajectories: A Central India perspective by Pashupati Nath Singh, Prashant K. Srivastava, Bhawana Sharma, R.K. Mall

“…Model performance showed robust agreement with observed yields (R = 0.78), with validation metrics—MAE = 5.9, RMSE = 6.93, and Bias = -1.43—demonstrating consistent predictive accuracy with slight underestimation. …”
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Pooled error variance and covariance estimation of sparse in situ soil moisture sensor measurements in agricultural fields in Flanders by M. G. A. Hendrickx, M. G. A. Hendrickx, J. Vanderborght, J. Vanderborght, P. Janssens, P. Janssens, P. Janssens, S. Bombeke, E. Matthyssen, A. Waverijn, J. Diels, J. Diels

“…These results demonstrate that the common assumption of uncorrelated random errors to determine parameter and model prediction uncertainty is not valid when measurements from sparse in situ soil moisture sensors are used to parameterize soil hydrological models. …”
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