Simultaneous multislice cardiac multimapping based on locally low-rank and sparsity constraints by Yixin Emu, Yinyin Chen, Zhuo Chen, Juan Gao, Jianmin Yuan, Hongfei Lu, Hang Jin, Chenxi Hu

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A multi-species corridor between the Andean Amazonian and Amazon floodplain landscapes: prioritizing ecological connectivity areas for jaguar and threatened ungulates in the north-... by Federico Mosquera-Guerra, Sebastian Barreto, Juan D. Palencia-Rivera, Alexander Velásquez-Valencia, Hugo Mantilla-Meluk, Gustavo A. Bruges-Morales, Alex M. Jiménez-Ortega, Fernando Trujillo, Dolors Armenteras-Pascual

“…In recent decades, the Amazon forest system has experienced accelerated transformation due to deforestation, forest fires, extensive cattle ranching, and road infrastructure development, leading to degraded natural habitats and reduced connectivity among populations of large mammals in areas ecologically important for these species. …”
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Machine Learning-Based Objective Evaluation Model of CTPA Image Quality: A Multi-Center Study by Sun Q, Liu Z, Ding T, Shi C, Hou N, Sun C

“…Qihang Sun,1 Zhongxiao Liu,1 Tao Ding,1 Changzhou Shi,2 Nailong Hou,2 Cunjie Sun1 1Department of Medical Imaging, the Affiliated Hospital of Xuzhou Medical University, Xuzhou, People’s Republic of China; 2School of Medical Imaging, Xuzhou Medical University, Xuzhou, People’s Republic of ChinaCorrespondence: Cunjie Sun, Affiliated Hospital of Xuzhou Medical University, No. 99 West Huaihai Road, Quanshan District, Xuzhou City, Jiangsu Province, 221006, People’s Republic of China, Tel +8618052268897, Email cunjiesxyfy@163.comPurpose: This study aims to develop a machine learning-based model for the objective assessment of CT pulmonary angiography (CTPA) image quality.Patients and Methods: A retrospective analysis was conducted using data from 99 patients who underwent CTPA between March 2022 and January 2023, alongside two public datasets, FUMPE (21 cases) and CAD-PE (30 cases). …”
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Local power flow control by L. M. Chetochnikova, N. I. Smolentsev, N. V. Tomskich, D. A. Gimgina, D. A. Lavrentieva

“…It is noted that for the implementation of such a large-scale  task,  the  "road  map"  "Energynet"  of  the  National  Technology  Initiative  was developed,  among  the  main  directions  of  which  are  the  digitalization  of  the  infrastructure  of distribution  networks  and  the  deep  decentralization  of  electricity  production.  …”
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COSMIC’s Large-scale Search for Technosignatures during the VLA Sky Survey: Survey Description and First Results by C. D. Tremblay, J. Sofair, L. Steffes, T. Myburgh, D. Czech, P. B. Demorest, R. A. Donnachie, A. W. Pollak, M. Ruzindana, Siemion A. P. V., S. S. Varghese, S. Z. Sheikh

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Detecting Planetary Oblateness in the Era of JWST: A Case Study of Kepler-167e by Quanyi Liu, Wei Zhu, Yifan Zhou, Zhecheng Hu, Zitao Lin, Fei Dai, Kento Masuda, Sharon X. Wang

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Rooting depth projections of global plant functional types and driving factors analysis based on a hybrid modeling framework by Qinggong Han, Bo Liu, Yunuo Liu, Jielin Zhang, Yongxia Ding, Shouzhang Peng

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All-fiber three-wavelength laser for functional photoacoustic microscopy by Mingxuan Yang, Zheng Qu, Mohammadreza Amjadian, Xu Tang, Jiangbo Chen, Lidai Wang

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Exploring Protein Conformational Changes Using a Large‐Scale Biophysical Sampling Augmented Deep Learning Strategy by Yao Hu, Hao Yang, Mingwei Li, Zhicheng Zhong, Yongqi Zhou, Fang Bai, Qian Wang

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The Regional Differentiation on the Spatial Distribution and Influencing Factors of Potential Landslides Across the Entire Loess Plateau, China, Based on InSAR and Subregion XGBoos... by Zhuo Jiang, Chaoying Zhao, Xiaojie Liu, Guoqiang Shi, Ming Yan, Qin Zhang, Jianbing Peng

“…The influencing factors can be divided into two categories, those with spatial heterogeneity (i.e., elevation, fault, and road) and those without spatial heterogeneity (i.e., rain, river, and NDVI). …”
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Analysis of world experience in the use of artificial intelligence in traffic control systems at various levels by D. V. Navoi, D. V. Kapski, N. A. Filippova, I. N. Pugachev

“…The article discusses the use of various mathematical methods for these purposes when modeling transport processes and systems, including taking into account the development of artificial intelligence algorithms, so that when making decisions on traffic control, one can have reliable forecast indicators obtained from adequate models. …”
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The NavINST Dataset for Multi-Sensor Autonomous Navigation by Paulo Ricardo Marques De Araujo, Eslam Mounier, Qamar Bader, Emma Dawson, Shaza I. Kaoud Abdelaziz, Ahmed Zekry, Mohamed Elhabiby, Aboelmagd Noureldin

“…It offers rich, multi-sensor data ideal for developing and validating robust algorithms for autonomous vehicles. …”
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Spatiotemporal Changes in the Urban Heat Island Intensity of Distinct Local Climate Zones: Case Study of Zhongshan District, Dalian, China by Jun Han, Jiatong Liu, Liang Liu, Yuanzhi Ye

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Modelling geographical accessibility to urban centres in Kenya in 2019. by Peter M Macharia, Eda Mumo, Emelda A Okiro

“…<h4>Methods</h4>Urban centres were mapped from the 2019 Kenya population census and combined with spatial databases of road networks, elevation, land use and travel barriers within a cost-friction algorithm to compute travel time. …”
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Can Machine Learning Enhance Computer Vision-Predicted Wrist Kinematics Determined from a Low-Cost Motion Capture System? by Joel Carriere, Michele L. Oliver, Andrew Hamilton-Wright, Calvin Young, Karen D. Gordon

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Rapid Damage Assessment and Bayesian-Based Debris Prediction for Building Clusters Against Earthquakes by Xiaowei Zheng, Yaozu Hou, Jie Cheng, Shuai Xu, Wenming Wang

“…Finally, with the structural response data of maximum floor displacement, a surrogate model for rapidly calculating seismic responses of structures is developed based on the XGBoost algorithm, achieving R² > 0.99 for floor displacements and R² = 0.989 for maximum inter-story drift ratio (MIDR) predictions. …”
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REAL-TIME SIMULATIVE MODELING FOR GEAR CHANGE CONTROL STRATEGY RESEARCH by A. A. Filimonov, V. A. Kusyak

“…It allows adequately to react to structure reorganization and parameter change of the dynamic system at an application of external disturbances from the road and a driver. A peculiar feature of the developed software that is an opportunity of real-time modeling. …”
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An enhanced method of CNNs by incorporating the clustering-guided block for concrete crack recognition by Hui Li, Chenyu Liu, Ning Zhang, Wei Shi

“…These enhancements mark a significant advancement in developing accurate algorithms based on deep neural networks for identifying concrete crack edges reliably. …”
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Multiobjective Optimization of Turbine Coolant Collection/Distribution Plenum Based on the Surrogate Model by Junsheng Chai, Zhenyu Wang, Xuanling Zhao, Chunhua Wang

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Retrieval of Dissolved Oxygen Concentrations in Fishponds in the Guangdong–Hong Kong–Macao Greater Bay Area Using Satellite Imagery and Machine Learning by Keming Mao, Dakang Wang, Shirong Cai, Tao Zhou, Wenxin Zhang, Qianqian Yang, Zikang Li, Xiankun Yang, Lorenzo Picco

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