Quality Assessment of MRI-Radiomics-Based Machine Learning Methods in Classification of Brain Tumors: Systematic Review by Shailesh S. Nayak, Saikiran Pendem, Girish R. Menon, Niranjana Sampathila, Prakashini Koteshwar

“…Machine learning algorithms such as deep learning networks, support vector machines, random forests, and logistic regression were applied to develop predictive models. Conclusions: The present study indicates high accuracies in glioma classification, outperforming traditional imaging methods and inexperienced radiologists in some cases. …”
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Spatio-Temporal Characteristics and Driving Forces of Landscape Ecological Risks in Highly Urbanized Areas: A Case Study of Suzhou City by Lingyue LU, Dawei SHAO, Dianming WU

“…Low-risk and lower-risk zones are predominant, and the spatial heterogeneity of risk zones across all levels appears to be increasing. …”
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Binocular Vision-Based Target Detection Algorithm by Huiguo Zhang

“…The former can effectively balance the positive and negative samples to avoid over-learning of easy-to-classify samples during the training process; the latter successfully solves the problem of the failure of the detection method when there is no intersection between the prediction frame and the real detection frame, which significantly improves the robustness of the model. …”
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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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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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Current Bioinformatics Tools in Precision Oncology by Tesfaye Wolde, Vipul Bhardwaj, Vijay Pandey

“…Further integration of artificial intelligence with machine learning approaches improves predictive modeling and diagnostic accuracy. Spatial omics technologies correlate molecular signatures within tumor microenvironments, guiding treatment strategies. …”
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SODU2-NET: a novel deep learning-based approach for salient object detection utilizing U-NET by Hyder Abbas, Shen Bing Ren, Muhammad Asim, Syeda Iqra Hassan, Ahmed A. Abd El-Latif

“…Finally, the architecture has been improved by adding a residual block at the encoder end, which is responsible for both saliency prediction and map refinement. The proposed network is designed to learn the transformation between input images and ground truth, enabling accurate segmentation of salient object regions with clear borders and accurate prediction of fine structures. …”
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Cannabis pollen dispersal across the United States by Manu Nimmala, Shane D. Ross, Hosein Foroutan

“…As a step towards assessing hemp cross-pollination risk, this study characterizes the seasonal and spatial patterns in windborne hemp pollen dispersal spanning the conterminous United States (CONUS). …”
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Space Deficits in Parkinson’s Disease Patients: Quantitative or Qualitative Differences from Normal Controls? by D. Natsopoulos, M.-S. Bostantzopoulou, Z. Katsarou, G. Grouios, G. Mentenopoulos

“…Twenty-seven patients with idiopathic Parkinson's disease (PD) and the same number of normal controls (NCs) were studied on a test battery including five conceptual categories of spatial ability. The two groups of subjects were matched for age, sex, years of education, socioeconomic status and non-verbal (Raven Standard Progressive Matrices) intelligence. …”
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Nondestructive estimation of leaf chlorophyll content in banana based on unmanned aerial vehicle hyperspectral images using image feature combination methods by Weiping Kong, Weiping Kong, Lingling Ma, Huichun Ye, Huichun Ye, Jingjing Wang, Chaojia Nie, Binbin Chen, Xianfeng Zhou, Wenjiang Huang, Zikun Fan

“…We concluded that the nonlinear Gaussian process regression model with the VIs and TFs-PC1 combination selected by maximal information coefficient as input achieved the highest accuracy in LCC prediction for banana, with the highest R2 of 0.776 and lowest RMSE of 2.04. …”
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Deep Learning-Based Infrared Image Segmentation for Aircraft Honeycomb Water Ingress Detection by Hang Fei, Hongfu Zuo, Han Wang, Yan Liu, Zhenzhen Liu, Xin Li

“…Through rigorous experimentation, our model surpasses existing benchmarks, yielding a commendable 22.44% reduction in computational effort and a substantial 38.89% reduction in parameter count. …”
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Toward a Multidecadal SAR Analysis of Sea Ice Types in the Atlantic Sector of the Arctic Ocean by Wenkai Guo, Jack Landy, Johannes Lohse, Anthony P. Doulgeris, Malin Johansson, Torbjorn Eltoft, Polona Itkin, Shiming Xu

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Urban expansion, economic development, and carbon emissions: Trends, patterns, and decoupling in mainland China’s provincial capitals (1985–2020) by Jiahui Zhao, Wei Chen, Zixuan Liu, Wei Liu, Keyan Li, Bei Zhang, Yonggen Zhang, Le Yu, Tetsuro Sakai

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The Integration of Land Use Planning and the Varied Responses of Coupled Human–Natural Systems: A Case Study of Changning County in Southwest China by Yanlan Xie, Xiaobo Liu, Xiaoshuang Zhuo, Shaoyao Zhang, Hao Zhang

“…The results are as follows: (1) The TG was classified into five categories that were stratified according to the coupling intensity and orientation of the socioeconomic system and natural ecosystems in Changning County. (2) The transition type with the most complex socio-ecological coupling was the type of semi-socioeconomic process–semi-natural ecological process, occupying 32.6% (309.4 km²) of the county’s total area in 2000 and demonstrating the most pronounced spatial dynamics, exhibiting a reduction of 78.6 km² during the study period. (3) Negative impacts on TG dynamics were observed for the conversion of ecological space into agricultural production space (<i>p</i> < 0.01; R² > 0.24) and the dynamic degree of PLE transformations (<i>p</i> < 0.01; R² > 0.13). (4) The impacts of trends in PLE on the TG varied significantly across temporal phases, whereas the CONTAG index exhibited consistently non-significant effects throughout all study periods. …”
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Mitigating Risks in Hospital Facilities—An Analysis of the Relationship Between Healthcare Risks and the Built Environment: A Literature Review and Survey in the Italian Scenario by Beatrice Pattaro, Michele Dolcini, Andrea Brambilla, Stefano Capolongo

“…The results reveal critical gaps in implementation, particularly in spatial flexibility, environmental monitoring, and antimicrobial surfaces. …”
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High-Speed Railway Planning for Sustainable Development: The Role of Length Between Conventional Line and Straight Length by Francesco Russo, Corrado Rindone, Giuseppe A. Maiolo

“…The research problem that arises is to analyze the high-speed lines built in order to verify, given a pair of extreme terminals, how much the length is reduced by passing from a conventional line to a high-speed line, and to verify how this length is getting closer and closer to the distance as the crow flies. The reduction of spatial distance produces direct connections between two territories, making the railway system (HSR) more competitive compared to other transport alternatives (e.g., air travel). …”
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Dynamic land use efficiency and human-land relationship in traditional industrial cities by Xianglong Kong, Xianglong Kong, Yutong Wu, Peng Cui, Yiwen Sun, Guangpu Wei

“…Studying the dynamic land utilization efficiency during urbanization is crucial for understanding the human-land relationship in cities facing economic decline.MethodsUsing land utilization and population data from 2000 to 2020, a dynamic land utilization efficiency index was developed to identify patterns in land utilization dynamics at the district and county level and assess the coordination of human-land relationships at the municipal level. The spatial structural relationships among districts and counties are analysed using the Getis-Ord Gi* statistical model, while the co ordination mechanisms of human-land interactions are explored through the Kaya identity and the Logarithmic Mean Divisia Index (LMDI).ResultsThe results demonstrate that 40.9% of counties suffer from low land utilization efficiency. 57.6% of cities experience simultaneous population decline and expansion of urban-rural construction land. …”
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Evolutionary Patterns of Collagen Fiber Arrangement and Calcification in Atherosclerosis by Chunyang Ma, Zhenzhen Jia, Shuaiyin Liu, Xiangyi Liao, Hongyan Kang, Xufeng Niu, Yubo Fan

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RT-DETR-EVD: An Emergency Vehicle Detection Method Based on Improved RT-DETR by Jun Hu, Jiahao Zheng, Wenwei Wan, Yongqi Zhou, Zhikai Huang

“…Specifically, compared to the baseline RT-DETR-r18 model, RT-DETR-EVD reduces parameter count to 14.5 M (a 27.1% reduction), lowers floating-point operations (FLOPs) to 49.5 G (a 13.2% reduction), and improves precision by 0.5%. …”
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Structure and oxygen saturation recovery of sparse photoacoustic microscopy images by deep learning by Shuyan Zhang, Jingtan Li, Lin Shen, Zhonghao Zhao, Minjun Lee, Kun Qian, Naidi Sun, Bin Hu

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