Driving Safety Analysis Using Grid-Based Water-Filled Rut Depth Distribution by Jiao Yan, Hongwei Zhang, Bing Hui

“…In addition, the influence of the water depth difference between the left and right ruts on the driving safety is quantitatively analyzed, and a safety prediction model for the water-filled rut is established. …”
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MPAR-RCNN: a multi-task network for multiple person detection with attribute recognition by S. Raghavendra, S. K. Abhilash, Venu Madhav Nookala, Jayashree Shetty, Praveen Gurunath Bharathi

“…The integration of object detection and attribute recognition typically relies on approaches such as dual-stage networks, where accurate predictions depend on advanced feature extraction techniques, such as Region of Interest (RoI) pooling. …”
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Hybrid breeding boosted molecular genetics in rye by R. Schlegel

“…Those marker-assisted approaches became the basis of recent hybrid breeding of rye. Prediction of hybrid performance can also be improved significantly by marker-assisted selection and genomic selection based on genomewide marker data. …”
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Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence by Yi-Ming Chen, Tzu-Hung Hsiao, Ching-Heng Lin, Yang C. Fann

“…Deep learning techniques have significantly advanced variant calling, pathogenicity prediction, splicing analysis, and MHC-peptide binding predictions in genetics. …”
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Daily Functionality of People with Low Vision: The Impact of Visual Acuity, Depression, and Life Orientation—A Cross-Sectional Study by Mara Gkioka, Stavroula Almpanidou, Niki Lioti, Diamantis Almaliotis, Vasileios Karampatakis

“…Optimism as a personality characteristic did not factor into the prediction model for daily functionality, but it showed a strong correlation with lower levels of depressive symptoms. …”
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Classifying Dementia Using Local Binary Patterns from Different Regions in Magnetic Resonance Images by Ketil Oppedal, Trygve Eftestøl, Kjersti Engan, Mona K. Beyer, Dag Aarsland

“…Diagnosis can be demanding and MR imaging may aid as a noninvasive method to increase prediction accuracy. We explored the use of 2D local binary pattern (LBP) extracted from FLAIR and T1 MR images of the brain combined with a Random Forest classifier in an attempt to discern patients with Alzheimer's disease (AD), Lewy body dementia (LBD), and normal controls (NC). …”
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A neural network design for black-box identification of converter impedance models in arbitrary operating conditions by CHEN Bing, ZHAO Chongbin, JIANG Qirong, WANG Xu, WANG Fangming

“…In the model verification phase, the network is fed with set operating conditions, achieving highly accurate identification of stable operating conditions and offline prediction.…”
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Neural Plastic Effects of Cognitive Training on Aging Brain by Natalie T. Y. Leung, Helena M. K. Tam, Leung W. Chu, Timothy C. Y. Kwok, Felix Chan, Linda C. W. Lam, Jean Woo, Tatia M. C. Lee

“…This pattern of findings is consistent with the prediction and the principle of experience-dependent neuroplasticity. …”
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Driver’s Lane Selection Model Based on Phase-Field Coupling and Multiplayer Dynamic Game with Incomplete Information by Xiaoyuan Wang, Fang Wang, Dong Kong, Yaqi Liu, Liping Liu, Chen Chen

“…Intelligent driving is an effective means to achieve the active safety of automobile, and the accurate prediction of vehicle group situation is the premise to achieve the intelligent driving of vehicle. …”
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Mechanical Behavior of High-Strength Bolted Joints Fabricated from Fire-Resistant Steel at Elevated Temperatures by Yuedong Wang, Xiaorun Li, Peng Liu, Changdong Wu, Chuhan Liu, Lijing Zeng, Wentao He, Tiantian Yin

“…In addition, reduction factors of the tensile strength (KN) and slip strength (KS) for both fire-resistant bolt specimens and ordinary high-strength bolt specimens decrease with the increase in temperature, especially in the case of elevated temperatures ranging from 400°C to 700°C. Prediction models with different reliability degrees are proposed to calculate the degradation of tensile strength under elevated temperatures, which has the potential to be used for the fire-resistant design of steel connections and structures.…”
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Nondestructive Testing on Ancient Wooden Components Based on Shapley Value by Li-hong Chang, Xiao-hong Chang, Hao Chang, Wei Qian, Li-ting Cheng, Xiao-li Han

“…This method can improve the prediction accuracy of internal defects in ancient buildings and provide effective data support for practical engineering repair and reinforcement schemes.…”
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Estimation of translational importance of mammalian mRNA nucleotide sequence characteristics based on ribosome profiling data by O. A. Volkova, Yu. V. Kondrakhin, R. N. Sharipov

“…Now it seems to be possible to reveal translationally important mRNA parameters and predict translation efficiency based on their nucleotide sequences. …”
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Ultrasonographic evaluation of the thorax in dogs with tick paralysis by Erdem Gülersoy, Canberk Balıkçı, İsmail Günal, Adem Şahan, Esma Kısmet

“…Thus, the aim of this study is to describe thoracic ultrasonography lesions in dogs with tick paralysis and to identify potential patterns that could aid in diagnosis and prognosis prediction. The animal material consisted of 58 dogs in total, 10 of which were healthy and 48 of which were suspected to be affected by tick paralysis. …”
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Few-Shot Graph Anomaly Detection via Dual-Level Knowledge Distillation by Xuan Li, Dejie Cheng, Luheng Zhang, Chengfang Zhang, Ziliang Feng

“…In our approach, we initially train a teacher model to generate prediction distributions as soft labels, capturing the entropy of uncertainty in the data. …”
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Diagnostic value of multi-parameter ultrasound evaluation in sepsis complicated by acute kidney injury by Liu Wang, Xiang Wang

“…Additionally, logistic regression analysis was conducted to determine the influencing factors of sepsis complicated with AKI. The prediction value was evaluated using a receiver operating characteristic (ROC) curve.Results In the AKI group, creatinine, CysC, urea, MPUS score, RPT, and RI values were significantly higher, while the 24-h urine volume was lower than those in the non-injury group (p < 0.01). …”
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Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma by Mengmeng Hua, Tao Li

“…Abstract To integrate machine learning and multiomic data on lactylation-related genes (LRGs) for molecular typing and prognosis prediction in lung adenocarcinoma (LUAD). LRG mRNA and long non-coding RNA transcriptomes, epigenetic methylation data, and somatic mutation data from The Cancer Genome Atlas LUAD cohort were analyzed to identify lactylation cancer subtypes (CSs) using 10 multiomics ensemble clustering techniques. …”
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Permeability Enhancement Technology for Soft and Low-Permeability Coal Seams Combined with Hydraulic Perforation and Hydraulic Fracturing by Zhengjie Shang, Zhaofeng Wang, Zhiheng Cheng, Hongbing Wang, Liang Chen, Lei Li, Jianhua Fu, Hao Liu

“…The gas pressure in the No. 21 coal seam decreased from 1.1 MPa to 0.4 MPa, and the gas content decreased from 15.96 m3/t to 5.6 m3/t. All outburst prediction indexes measured on site did not exceed their respective limits. …”
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Dynamic Warping Network for Semantic Video Segmentation by Jiangyun Li, Yikai Zhao, Xingjian He, Xinxin Zhu, Jing Liu

“…Furthermore, we introduce the temporal consistency loss including the feature consistency loss and prediction consistency loss to explicitly supervise the warped features instead of simple feature propagation and fusion, which guarantees the temporal consistency of video segmentation. …”
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Local-Global and Multi-Scale (LG-MS) Mixer Architecture for Long-Term Time Series Forecasting by Zhennan Peng, Boyong Gao, Ziqi Xia, Jie Liu

“…To capture a more comprehensive effective information within the components, we then utilize a customized patch-based triple attention local-global information extractor that models both temporal feature information and variable dependencies, alongside an MLP-based feature interaction iterator facilitating interactions among multi-scale information to guide macro-level predictions. Finally, we integrate the predictions from the multi-scale sequences to leverage their complementary advantages. …”
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Du mythe de l’efficience des marchés au krach by David Bourghelle, Pauline Hyme

“…This kind of rationality is entirely directed toward the prediction of what the dominant opinion of the market, in the form of the price, will be. …”
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