How Gait Nonlinearities in Individuals Without Known Pathology Describe Metabolic Cost During Walking Using Artificial Neural Network and Multiple Linear Regression by Arash Mohammadzadeh Gonabadi, Farahnaz Fallahtafti, Judith M. Burnfield

“…Six nonlinear metrics—Lyapunov Exponents based on Rosenstein’s algorithm (LyER), Detrended Fluctuation Analysis (DFA), the Approximate Entropy (ApEn), the correlation dimension (CD), the Sample Entropy (SpEn), and Lyapunov Exponents based on Wolf’s algorithm (LyEW)—were utilized to predict the metabolic cost during walking. …”
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Glucagon-like peptide-1 receptor agonist use prior to spinal surgery results in reduced postoperative length of stay: A propensity-score matched analysis by Samuel N. Goldman, BS, Kyle Mani, BE, Thomas Scharfenberger, BS, Emily Kleinbart, BA, Aaron T. Hui, BS, Rafael De la Garza Ramos, MD, Mitchell S. Fourman, MD, MPhil, Ananth S. Eleswarapu, MD

“…GLP-1 RA use was associated with a significant reduction in median postoperative LOS (3 days vs. 4 days; p = 0.036), particularly among patients undergoing lumbar fusion. …”
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Associations of choroid plexus volume with white matter hyperintensity volume and susceptibility and plasma amyloid markers in cerebral small vessel disease by Pengcheng Liang, Meng Li, Yiwen Chen, Zhenyu Cheng, Na Wang, Yuanyuan Wang, Nan Zhang, Yena Che, Jing Li, Changhu Liang, Lingfei Guo

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A Universal Tire Detection Method Based on Improved YOLOv8 by Chi Guo, Mingxia Chen, Junjie Wu, Haipeng Hu, Luobing Huang, Junjie Li

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Modeling, Validation and Analysis of the Performance of Direct Air-Cooling Condensers for Mountainous Terrain by Xubo Lu, Hongyi Chen, Jingyao Wang, Huimin Wei, Xiaoze Du

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Research on the Method of Coke Optical Tissue Segmentation Based on Adaptive Clustering by Huaiguang Liu, Liheng Zhang, Shiyang Zhou, Li Fang

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Methods to Quantitatively Evaluate the Effect of Shale Gas Fracturing Stimulation Based on Least Squares by DENG Cai, SUN Kexin, WEN Huan, HU Chaolang

“…Advanced optimization algorithms were employed to efficiently address both the fitting and calculation tasks. …”
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POSSIBILITIES OF CARIES PROGNOSIS IN CHILDREN OF SCHOOL-AGE ACCORDING TO DATA GAINED FROM THEM AND THEIR PARENTS QUESTIONNAIRE by L.F. Kaskova, T.B. Mandziuk, L.P. Ulasevych, L.D. Korovina, M.A. Sadovski

“…Therefore, the purpose of our study was to identify the possibility of predicting caries in preschool children according to questionnaires of surveyed children and their parents. …”
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Understanding students’ sentiment from feedback with a new feature selection and semantics networks by Tran Anh Tuan, Dao Thi Thanh Loan, Nichnan Kittiphattanabawon

“… Sentiment analysis of students’ feedback using machine learning algorithms has emerged as a valuable tool for understanding students’ sentiments and improving educational outcomes. …”
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Hybrid PI and Fuzzy Logic Control for Energy Optimization in Train Operations by Hwan-Hee Cho, Jae-Won Kim, Min-Sup Song, Chi-Myeong Yun, Gyu-Jung Cho, Zhongbei Tian

“…This paper presents a Fuzzy logic-based train control algorithm designed to enhance energy efficiency across a complete railway route. …”
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Modelling and simulation of the block pouring construction system considering spatial–temporal conflict of construction machinery in arch dams by Zhipeng Liang, Jiayao Peng, Chunju Zhao, Huawei Zhou, Dongfeng Li, Yihong Zhou, Quan Liu, Xiaodong Li, Cheng Zhang, Fang Wang

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Cluster-based RSU deployment strategy for vehicular ad hoc networks with integration of communication, sensing and computing by Xinrui Gu, Shengfeng Wang, Zhiqing Wei, Zhiyong Feng

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A reputation-based dynamic reorganization scheme for blockchain network sharding by Shuhui Zhang, Hanwen Tian, Lianhai Wang, Shujiang Xu, Wei Shao

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Modeling of settlement of shallow-founded rocking structures using explainable physics-guided machine learning by Sivapalan Gajan, Christopher Kantor

“…SHAP analysis reveals that the PGML model predictions and their dependency on input features are consistent with the existing domain knowledge, and that the inclusion of physics in PGML models help improve the prediction accuracy, especially in cases where other input features fail to capture the combined complex interaction among the variables involved.…”
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A Comparative study of the Envisaged and Definite Stock Prices of BSE SMEs Using RNN during the COVID-19 Pandemic by S. Kaur, A. Munde, A. K. Goyal

“…The stock market is unstable, but the use of machine learning algorithms allows to predict its future dynamics before spending. …”
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Development of standard fuel models in boreal forests of Northeast China through calibration and validation. by Longyan Cai, Hong S He, Zhiwei Wu, Benard L Lewis, Yu Liang

“…Understanding the fire prediction capabilities of fuel models is vital to forest fire management. …”
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Resolving the conformational ensemble of a membrane protein by integrating small-angle scattering with AlphaFold. by Samuel Eriksson Lidbrink, Rebecca J Howard, Nandan Haloi, Erik Lindahl

“…Several strategies have recently been developed to drive the machine learning algorithm AlphaFold2 (AF) to sample multiple conformations, but it is more challenging to a priori predict what states are stabilized in particular conditions and how the transition occurs. …”
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Explainable post hoc portfolio management financial policy of a Deep Reinforcement Learning agent. by Alejandra de-la-Rica-Escudero, Eduardo C Garrido-Merchán, María Coronado-Vaca

“…In this work, driven by the motivation of making DRL explainable, we developed a novel Explainable DRL (XDRL) approach for PM, integrating the Proximal Policy Optimization (PPO) DRL algorithm with the model agnostic explainable machine learning techniques of feature importance, SHAP and LIME to enhance transparency in prediction time. …”
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Clinical interpretation of variants identified in RNU4ATAC, a non-coding spliceosomal gene. by Clara Benoit-Pilven, Alicia Besson, Audrey Putoux, Claire Benetollo, Clément Saccaro, Justine Guguin, Gabriel Sala, Audric Cologne, Marion Delous, Gaetan Lesca, Richard A Padgett, Anne-Louise Leutenegger, Vincent Lacroix, Patrick Edery, Sylvie Mazoyer

“…As RNU4ATAC has a single non-coding exon, the bioinformatic prediction algorithms assessing the effect of sequence variants on splicing or protein function are irrelevant, which makes variant interpretation challenging to molecular diagnostic laboratories. …”
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Screening for MicroRNA combination with engineered exosomes as a new tool against osteosarcoma in elderly patients by Jiyu Han, Jiyu Han, Zitong Zhao, Yanhong Wang, Yanhong Wang, Tao Yu, Daqian Wan, Daqian Wan

“…Next, we used FunRich software to predict the up-stream transcription factors (TFs) of differentially expressed miRNAs (DE-miRNAs). …”
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