A large-scale study of academic specialization and sex effects on Corsi block performance by Sergey Malykh, Anna Pavlova, Artem Malykh, Timofey Adamovich, Tatiana Tikhomirova

“…The results highlight the importance of considering both cognitive and contextual factors in the assessment of spatial working memory.…”
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A topological approach to understanding crack initiation and propagation in carbon fiber reinforced polymer composites under an opening load by Mayrene Uy, Daiki Kido, Masao Kimura

“…From a materials perspective, this methodology allows integration of not just crack length but also 3D crack shape into predictive models, offering valuable insights for optimizing the performance and extending the lifetime of carbon fiber/epoxy composites.…”
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Comparing US state resident IQ, socioeconomic status, and racial-ethnic composition as predictors of state violent crime rates by Stewart J. H. McCann

“…Generally, the results underline the importance of evaluating potential crime rate predictors in a multiple regression model rather than testing their predictive capacities only as single variables.…”
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Forest Fire Hazard Assessment using Remote Sensing Data and Machine Learning, Case Study of Jijel, Algeria by Matougui Zakaria, Zouidi Mohamed

“…Evaluation metrics such as Receiver Operating Characteristic Area Under the Curve, F1 score and accuracy, supported by repeated cross-validation, were used to gauge performance. Both models performed well (with an average area under the curve of 0.977 and 0.984, respectively), with HGB maintaining a marginal but consistent advantage over KNN, with relatively low standard deviations, suggesting stability in its predictive capability. …”
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A Comprehensive Dataset of Surface Water Quality Spanning 1940-2023 for Empirical and ML Adopted Research by Md. Rajaul Karim, M. M. Mahbubul Syeed, Ashifur Rahman, Khondkar Ayaz Rabbani, Kaniz Fatema, Razib Hayat Khan, Md Shakhawat Hossain, Mohammad Faisal Uddin

“…This dataset can support meta-analysis of water quality models and can facilitate Machine Learning (ML) based data and model-driven investigation of the spatial and temporal drivers and patterns of surface water quality at a cross-regional to global scale.…”
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Network-based multi-omics integrative analysis methods in drug discovery: a systematic review by Wei Jiang, Weicai Ye, Xiaoming Tan, Yun-Juan Bao

“…Future developments should focus on incorporating temporal and spatial dynamics, improving model interpretability, and establishing standardized evaluation frameworks.…”
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MeDML: Med-Dynamic Meta Learning - A multi-layered representation to identify provider fraud in healthcare by Nitish Kumar, Deepak Chaurasiya, Alok Singh, Siddhartha Asthana, Kushagra Agarwal, Ankur Arora

“…We test the dynamically generated meta embedding using various downstream models and show that it outperforms all baseline algorithms for provider fraud prediction task.…”
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Cross-modal interactive and global awareness fusion network for RGB-D salient object detection. by Runqing Li, Ling Yu, Zijian Jiang, Fanglin Niu

“…It outperforms salient object detection methods that rely solely on RGB images by leveraging the geometric morphology and spatial layout information from depth images. However, the existing RGB-D detection model still encounters difficulties in accurately recognising and highlighting salient objects when facing complex scenes containing multiple or small objects. …”
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Beyond surveys: high-resolution mapping of rural wealth in China using satellite and street view imagery by Weipan Xu, Qiumeng Li, Yaofu Huang, Yu Gu, Xun Li

“…Centered on the intelligent interpretation of rural housing features, we extract wealth-related visual elements from imagery and regress them against benchmark survey-based household wealth indicators to develop a high-accuracy township-level wealth prediction model (R² = 71%). This model is used to generate a nationwide, township-scale rural household wealth map. …”
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Optimization for Metro Operation Scheme of Suburban Lines: A New Method for Dealing with the Imbalanced Passenger Flow by Xiaobing Ding, Gan Shi, Jiangang Jin, Lixing Yang, Zhigang Liu

“…Finally, a set of numerical experiments with operation data from Shanghai Metro Line 16 are conducted to verify the performance and effectiveness of the proposed model and algorithm. The experimental results show that the proposed approach can effectively realize the collaborative optimization of passenger OD prediction, train proportion, stop scheme, and travel time, so as to provide decision-making support and method guidance for the optimization of metro organizations in megacities.…”
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Design of vehicle data engine system based on big data platform and intelligent perception by CHEN Xijun

“…To this end, a set of vehicle data engine system was designed based on the big data platform and intelligent perception to clean and integrate the operation data of the traction, braking, door, network and LCU systems for the spatial and temporal alignment of data. In addition, data analysis strategy model was developed by means of drag and drop based on the canvas components to carry out multidimensional data analysis, make decisions, monitor the working process, identify hidden troubles and give early warning, and make life predictions, replacing the repetitive and complex manual operation. …”
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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…Finally, ResNet50 is selected as the backbone network, and a custom loss function is designed specifically for grasp detection tasks, which significantly enhances the model’s ability to predict feasible grasp boxes. The proposed G-RCenterNet algorithm is embedded into a robotic grasping system, where a structured light depth camera captures target images, and the grasp detection network predicts the optimal grasp box. …”
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Ecological Zoning Based on Suitability Evaluation of Ecological Product Development from the Value-Risk-Cost-Demand Perspective by Ming Gao, Pei Du, Xinxin Zhou, Zhenxia Liu, Wen Luo, Zhaoyuan Yu, Linwang Yuan

“…The findings suggest that the integrated assessment model proposed in this study has produced more reasonable outcomes in terms of spatial layout, land use area, reduction of fragmentation and ecological risk. …”
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Digitalizing metallic materials from image segmentation to multiscale solutions via physics informed operator learning by Shahed Rezaei, Kianoosh Taghikhani, Alexandre Viardin, Reza Najian Asl, Ali Harandi, Nikhil Vijay Jagtap, David Bailly, Hannah Naber, Alexander Gramlich, Tim Brepols, Mustapha Abouridouane, Ulrich Krupp, Thomas Bergs, Markus Apel

“…Abstract Fast prediction of microstructural responses based on realistic material topology is vital for linking process, structure, and properties. …”
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Fusion ConvLSTM-Net: Using Spatiotemporal Features to Increase Residential Load Forecast Horizon by Abhishu Oza, Dhaval K. Patel, Bryan J. Ranger

“…We evaluated the model against several benchmark neural network models by: 1) testing different forecast window sizes ranging from 1.5 to 24 hours, 2) assessing model performance across multiple households, and 3) performing large-scale forecasting by aggregating predictions from 100 households. …”
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Federated Knowledge Distillation With 3D Transformer Adaptation for Weakly Labeled Multi-Organ Medical Image Segmentation by Tareq Mahmod AlZubi, Hamza Mukhtar

“…To address these challenges, we propose the Federated 3D Knowledge Distillation Network (Fed3D-KDNet), a hybrid federated learning (FL) framework that integrates both global and local knowledge distillation mechanisms. Our model adapts the Segment Anything Model (SAM) for volumetric medical imaging by introducing architectural enhancements, including 3D spatial feature adapters and an Auto Prompt Generator (APG), to optimize spatial representation and reduce reliance on manually crafted prompts. …”
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Identification of matrix stiffness-related molecular subtypes in HCC via integrating multi-omics analysis and machine learning algorithms by Hanqi Li, Jiayi Zhang, Yu Shi, Huanhuan Wang, Ruida Yang, Shaobo Wu, Yue Li, Xue Yang, Qingguang Liu, Liankang Sun

“…PPARG, the key gene with the greatest contribution to the model, was selected for validation. Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) analyses assessed matrix stiffness activity scores across different cell subgroups and examined PPARG spatial localization within tissues. …”
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Toward Accurate Physics‐Based Specifications of Neutral Density Using GNSS‐Enabled Small Satellites by Eric K. Sutton, Jeffrey P. Thayer, Marcin D. Pilinski, Shaylah M. Mutschler, Thomas E. Berger, Vu Nguyen, Dallas Masters

“…Simultaneously, a new era of CubeSat constellations is set to provide data with which to calibrate our upper‐atmosphere models at higher spatial resolution and temporal cadence. …”
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Losartan as a mechanotherapeutic adjuvant: Remodeling the breast tumor microenvironment to improve treatment efficacy. by Mutaz Dwairy, Alaa Yehya, Feras M Mohammad, Hiba Alzoubi

“…Furthermore, tumor cell concentration decreased by 88%, reflecting the drug's dual anti-proliferative and pro-apoptotic effects. Spatial analyses revealed heterogeneity in stiffness reduction and drug response, emphasizing the importance of tumor geometry and perfusion. …”
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Comparer les tempêtessur le temps long en quantifiant les dommages : proposition d’un nouvel outil by Emmanuelle Athimon, Mohamed Maanan, Pierre Pouzet

“…By combining the estimation of the importance of the damage and the spatial framework, this method leads to a “reasoned” coding, less subjective, with reduction of the risks of over or underestimate. …”
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