Effect of Social Sustainability on Supply Chain Resilience Before, During, and After the COVID-19 Pandemic in Mexico: A Partial Least Squares Structural Equation Modeling and Evolu... by Miguel Reyna-Castillo, Alejandro Santiago, Ana Xóchitl Barrios-del-Ángel, Francisco Manuel García-Reyes, Fausto Balderas, José Ignacio Anchondo-Pérez

“…This work starts from an epistemological premise, in which non-parametric statistical methodologies and mathematical analytics are complementary perspectives to comprehensively understand the same social phenomenon. Second-generation predictive statistics, such as the PLS-SEM algorithm, have demonstrated robustness in treating multivariate social information, making it feasible to prepare data for knowledge transfer with mathematical techniques specialized for fuzzy data. …”
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Lightweight defocus deblurring network for curved-tunnel line scanning using wide-angle lenses by Shaojie Qin, Taiyue Qi, Xiaodong Huang, Xiao Liang

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The effectiveness of complex therapy in the treatment of nonspecific vaginitis in women of reproductive age by O.D. Ryazanova, G.I. Reznichenko

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Effects of magnesium deficiency on stress manifestations in women of reproductive age with nonspecific vaginitis by O. D. Riazanova, Н. I. Reznichenko

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Integrating Single‐Cell Transcriptomics and Machine Learning to Define an ac4C Gene Signature in Lung Adenocarcinoma by Yuan Wang, Wei Su, Guangyao Zhou, Yijie Wang, Chunnuan Wu, Pengpeng Zhang, Lianmin Zhang

“…Ten machine learning algorithms were applied to develop and validate an ac4C‐related gene signature (ARGSig) for prognosis prediction across multiple independent cohorts. …”
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Research on the Movement Patterns of Bed-load Streaky Structure Transport and the Mechanism of Fluid-solid Coupling by YAO Jiateng, XIE Xiaoxi, WANG Hao, ZHAO Lin, XIE Haonan, ZHEN Rongtian

“…Based on the located centroids and vector velocities of bedload particles, the Kalman filter algorithm was employed to calculate both measured and predicted values under the given conditions. …”
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Digital Eversion of a Hollow Structure: An Application in Virtual Colonography by Jun Zhao, Liji Cao, Tiange Zhuang, Ge Wang

“…Together with other techniques, digital eversion may help improve screening, diagnosis, surgical planning, and medical education. Two eversion algorithms are proposed and evaluated in numerical simulation to demonstrate the feasibility of the approach.…”
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Intelligent recognition of tobacco leaves states during curing with deep neural network by Qiang Xu, Yanling Zhang, Aiguo Wang, Guangqing Chen, Xianjie Cai, Shuoye Zhou, Junying Li, Baofeng Jin, Ding Yan, Jiajie Huang, Zuxiao Chen, Heng Zhang, Jianwei Wang, Weimin Guo, Jianjun Liu

“…Then, an efficient deep learning method was proposed based on this dataset to enhance the predictive performance.ResultsThe prediction accuracy achieved for the yellowing degree, browning degree, and drying degree were 83.0%, 90.5%, and 75.6% respectively. …”
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Optimal design of high‐performance rare‐earth‐free wrought magnesium alloys using machine learning by Shaojie Li, Zaixing Dong, Jianfeng Jin, Hucheng Pan, Zongqing Hu, Rui Hou, Gaowu Qin

“…Abstract In this study, a small dataset of 370 datapoints of Mg alloys are selected for machine learning (ML), in which each datapoint includes five rare‐earth‐free alloying elements (Ca, Zn, Al, Mn and Sn), three extrusion parameters (extrusion speed, temperature and ratio), and three mechanical properties (yield strength [YS], ultimate tensile strength [UTS] and elongation [EL]). The ML algorithms, including support vector machine regression (SVR), artificial neural network, and other three methods, are employed, and the SVR has the best performance in predicting mechanical properties based on the components, and process parameters, with the mean absolute percentage error of YS, UTS, and EL being 6.34%, 4.19%, and 13.64% in the test set, respectively. …”
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Development and optimization of an electrohydrodynamic dehydrator using ANN-GA for improved energy performance by Chakrit Suvanjumrat, Klar Kongsarai, Piyamon Phong-arom, Namnguen Chumphong, Machimontorn Promtong, Jetsadaporn Priyadumkol

“…Furthermore, an integrated ANN–genetic algorithm (ANN-GA) approach was established to optimize the drying parameters, aiming to maximize drying kinetics and minimize SEC. …”
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Multiphysics Feature-Based State-of-Energy Estimation for LiFePO4 Batteries Using Bidirectional Long Short-Term Memory and Particle Swarm-Optimized Kalman Filter by Zhengpu Wu, Xu He, Haisen Chen, Lu Lv, Jiuchun Jiang, Lujun Wang

“…State-of-energy (SOE) estimation helps to enhance the safety of battery operation and predict vehicle range. However, the voltage plateau of the LiFePO4 (LFP) battery presents a significant challenge for SOE estimation. …”
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Advancing Leaf Nutritional Characterization of Blueberry Varieties Adapted to Warm Climates Enhanced by Proximal Sensing by Sérgio H. G. Silva, Marcelo C. Berardo, Lucas R. Rosado, Renata Andrade, Anita F. S. Teixeira, Mariene H. Duarte, Fernanda A. Bócoli, Marco A. C. Carneiro, Nilton Curi

“…Nutrient content was statistically compared per leaf moisture condition (fresh or dry) with ICP results and used to differentiate the varieties via the random forest algorithm. P and Zn contents (ICP) in leaves were different among varieties. …”
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A federated LSTM network for load forecasting using multi-source data with homomorphic encryption by Mengdi Wang, Rui Xin, Mingrui Xia, Zhifeng Zuo, Yinyin Ge, Pengfei Zhang, Hongxing Ye

“…To further enhance security, the homomorphic encryption (HE) using Paillier algorithm was introduced during the federated process. …”
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Transabdominal ultrasound for the characterization and follow-up of cystic pancreatic lesions by Julian Seelig, Maria Heni, Max Seitzinger, Kien Vu Trung, Jürgen Feisthammel, Marcus Hollenbach, Robert Henker, Albrecht Hoffmeister, Jonas Rosendahl, Valentin Blank, Thomas Karlas

“…Cross-method morphological assessments were analysed, and a patient-specific algorithm for selecting the appropriate monitoring method was developed. …”
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Filamentary Hierarchies and Superbubbles. I. Characterizing Filament Properties across a Simulated Spiral Galaxy by Rachel Pillsworth, Erica Roscoe, Ralph E. Pudritz, Eric W. Koch

“…By adapting the FilFinder algorithm of E. W. Koch & E. W. Rosolowsky, we extract over 500 filaments ranging up to 10 kpc in scale, to derive the probability distribution functions for filament masses and lengths, magnetic field orientations, and the gravitational stability and fragmentation patterns of filaments. …”
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A Clinical Validation of a Diagnostic Test for Esophageal Adenocarcinoma Based on a Novel Serum Glycoprotein Biomarker Panel: PromarkerEso by Jordana Sheahan, Iris Wang, Peter Galettis, David I. Watson, Virendra Joshi, Michelle M. Hill, Richard Lipscombe, Kirsten Peters, Scott Bringans

“…A panel of glycoproteins: alpha-1-antitrypsin, alpha-1-antichymotrypsin, complement C9 and plasma kallikrein, were combined with clinical factors (age, sex and BMI) in an algorithm to categorize the samples by the risk of EAC. …”
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Power System Reliability Assessment with Quantification of Demand Response Uncertainty Based on Advanced Sigmoid Cloud Model by Bo Hu, Yue Sun, Wei Huang, Changzheng Shao, Tao Niu, Xin Cheng, Kaigui Xie

“…Finally, a reliability assessment framework for a composite power system is developed considering the uncertain price-based DR model and a k-means algorithm is used to accelerate the assessment process. …”
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CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…By analysing data from sensors and system logs, ML algorithms can identify patterns indicative of faults or inefficiencies, such as shading, soiling, or equipment malfunctions, often before they become serious issues. …”
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Prognosticating salvage stereotactic radiosurgery outcomes in relapsed primary central nervous system lymphoma: A machine learning-driven decision tree analysis by Huili Zhao, Shenao Zhang, Lang Chen, Xin Liu, Aihong Cao, Peng Du

“…The cohort was randomly divided into training and validation sets (7:3 ratio). The C5.0 algorithm was employed to develop a decision tree model for predicting treatment response. …”
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Assessment of MGMT promoter methylation status in glioblastoma using deep learning features from multi-sequence MRI of intratumoral and peritumoral regions by Xuan Yu, Jing Zhou, Yaping Wu, Yan Bai, Nan Meng, Qingxia Wu, Shuting Jin, Huanhuan Liu, Panlong Li, Meiyun Wang

“…The area under the receiver operating characteristic curve (AUC) was employed to assess predictive performance. Results The ROI-based models of intratumoral and peritumoral regions, utilizing deep learning algorithms on multi-sequence MRI, were capable of predicting MGMT promoter methylation status in glioblastoma patients. …”
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