Interpretable machine learning model of effective mass in perovskite oxides with cross-scale features by Changjiao Li, Zhengtao Huang, Hua Hao, Zhonghui Shen, Guanghui Zhao, Ben Xu, Hanxing Liu

“…However, previous works were mainly devoted to algorithm improvement, while the essential multi-scale characteristics are not well addressed. …”
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Rapid Discrimination for Traditional Complex Herbal Medicines from Different Parts, Collection Time, and Origins Using High-Performance Liquid Chromatography and Near-Infrared Spec... by Haiyan Fu, Yao Fan, Xu Zhang, Hanyue Lan, Tianming Yang, Mei Shao, Sihan Li

“…As an effective method, the fingerprint technique, which emphasized the whole compositions of samples, has already been used in various fields, especially in identifying and assessing the quality of herbal medicines. …”
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Predicting mechanical properties of low-alloy steels using features extracted from Electron Backscatter Diffraction characterization by Yu Li, Jingxiao Zhao, Xiucheng Li, Zhao Xing, Qiqiang Duan, Xiaojun Liang, Xuemin Wang

“…Machine learning (ML) approaches have recently been increasingly employed to establish quantitative relationships between material composition, processing, microstructure, and properties. …”
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Single-walled carbon nanotubes sensors: Preparation and bio-application advances by Xiaotong Chen, Difan Wang, Wenshuo Ding, Hengchang Zang, Lian Li

“…Combining these technologies with microfluidic platforms and machine learning algorithms further broadens the application areas of sensors and enhances their analytical performance and usefulness in complex biological systems. …”
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Decoding the diagnostic biomarkers of mitochondrial dysfunction related gene variants in pediatric T cell acute lymphoblastic leukemia by Yunfeng Lu, Xi Yang, Liying Liu, Xiaojun Sun, Xiuli Li, Ping Zhao, Guotao Guan, Yunpeng Dai

“…The intersection of LASSO regression and RF algorithms highlighted two pivotal genes: RNLS and ULK1. …”
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Machine learning-based prediction of scale formation in produced water as a tool for environmental monitoring by Arash Tayyebi, Ali Alshami, Erfan Tayyebi, Ademola Owoade, MusabbirJahan Talukder, Nadhem Ismail, Zeinab Rabiei, Xue Yu, Glavic Tikeri

“…We used a database comprised of 2313 quality data points from different locations in the Bakken Shale Play, including values such as ionic compositions, pH, and the saturation index of the potential mineral scales in PW at 60°F and 60 psi to train the ML algorithms and identify what scale will likely form in the PW. …”
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A machine-learning approach for predicting butyrate production by microbial consortia using metabolic network information by Claudia Silva-Andrade, Sergio Hernández, Pedro Saa, Ernesto Perez-Rueda, Daniel Garrido, Alberto J. Martin

“…The performance of the algorithms was evaluated using k-fold cross-validation and new experimental data, displaying a Pearson correlation coefficient exceeding 0.75 for the predicted and observed butyrate production in two bacteria consortia. …”
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Development and validation of machine learning models for predicting low muscle mass in patients with obesity and diabetes by Jiaying Ge, Siqi Sun, Jiangping Zeng, Yujie Jing, Huihui Ma, Chunhua Qian, Ran Cui, Shen Qu, Hui Sheng

“…Predictive models were developed using logistic regression, random forest, and other algorithms, with feature selection via LASSO regression. …”
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A statistical and machine learning approach for monthly precipitation forecasting in an Amazon city by Ewerton Cristhian Lima de Oliveira, Eduardo Costa de Carvalho, Edmir dos Santos Jesus, Rafael de Lima Rocha, Rafael de Lima Rocha, Helder Moreira Arruda, Ronnie Cley de Oliveira Alves, Ronnie Cley de Oliveira Alves, Renata Gonçalves Tedeschi

“…Besides the use of algorithms, another evaluation was conducted on Feature Composition based on statistical methods to investigate the impact of variables on the prediction.ResultsThe results obtained in our investigation indicate that the vector autoregressive moving average with exogenous regressors (VARMAX) model achieved the best performance in rainfall forecasting, with an average root mean square error (RMSE) of 9.1833 in time series cross-validation, outperforming the other models.DiscussionThe climate-driven patterns directly influenced the performance of the rainfall forecasting models evaluated in this study. …”
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Using composable NFTs and blockchain for the creation of EV battery digital passports with sustainability and traceability features by Haya R. Hasan, Khaled Salah, Ahmad Mayyas, Ahmad Musamih, Ibrar Yaqoob, Mohammed Omar, Raja Jayaraman

“…Digital passports have emerged to track a product’s lifecycle, composition, certifications, origin, and recyclability. …”
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Cognitive weaknesses or impairments on the NIH toolbox cognition battery in children and adolescents: base rates in a normative sample and proposed methods for classification by Nathan E. Cook, Nathan E. Cook, Nathan E. Cook, Grant L. Iverson, Grant L. Iverson, Grant L. Iverson, Grant L. Iverson, Justin E. Karr

“…The sample included the following racial and ethnic composition: 58.1% White, 17.8% Black or African American, 16.8% Hispanic, 1.7% Asian, 3.1% multiracial and ethnic identities, and 2.6% not provided. …”
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Mapping dominant plant communities in the degraded Zoige swamp using Sentinel-1/2 imagery and its implications for vegetation restoration by Guoying Zhang, Chuanpeng Zhao, Mingming Jia, Rong Zhang, Hou Jiang, Zongming Wang

“…Then, we applied the random forest (RF) algorithm to identify three plant communities dominated by Kobresia, Carex, and Blysmus in the degraded Zoige swamp. …”
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Entire aerial-aquatic trajectory modeling and optimization for trans-medium vehicles by Teng Long, Nianhui Ye, Baoshou Zhang, Jingliang Sun, Renhe Shi

“…Rather than directly optimizing by a heuristic algorithm, a multi-surrogate cooperative sampling-based optimization method is proposed to alleviate the computational complexity of the entire trajectory optimization problem. …”
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Spectral Fingerprinting of Tencha Processing: Optimising the Detection of Total Free Amino Acid Content in Processing Lines by Hyperspectral Analysis by Qinghai He, Yihang Guo, Xiaoli Li, Yong He, Zhi Lin, Hui Zeng

“…The quality and flavor of tea leaves are significantly influenced by chemical composition, with the content of free amino acids serving as a key indicator for assessing the quality of Tencha. …”
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Molecular features and diagnostic modeling of synovium- and IPFP-derived OA macrophages in the inflammatory microenvironment via scRNA-seq and machine learning by Chao Lin, Yue Wan, Yong Xu, Qingsong Zou, Xiaoxiao Li

“…Machine learning (ML) algorithms identified feature genes of OA-macrophages. …”
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Unveiling new insights into migraine risk stratification using machine learning models of adjustable risk factors by Yu-Chen Liu, Ye-Hai Liu, Hai-Feng Pan, Wei Wang

“…Second, we trained ensemble machine learning (ML) algorithms that incorporated these factors, with Shapley Additive exPlanations (SHAP) value analysis quantifying predictor importance. …”
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Methodology сomparative statistical analysis of Russian industry based on cluster analysis by Sergey S. Shishulin

“…The resulting clusters are uniform in composition and meaningfully interpreted: the first cluster includes countries with low rates of output of the extractive industry relative to the cumulative output of the economy, with a sufficiently high value of this indicator in other sectors. …”
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System aspects of management technology for scientific and educational services by A. A. Zatsarinnyy, A. P. Shabanov

“…The method, used in this technology, to provide consumers with scientific and educational services in the form of business services in accordance with the concept of IT service management ensures universality of approach to create the knowledge base and algorithms to use the knowledge for managing IT infrastructure support of business services, and to manage business services. …”
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CyberDART: A Corporate Federation System for Mitigating Email Threats by Szymon Stryczek, Mikolaj Gwiazdowicz, Janusz Gozdecki, Katarzyna Kosek-Szott, Norbert Rapacz, Jacek Rzasa, Szymon Szott, Marek Natkaniec

“…We demonstrate that CyberDART clearly improves spam detection over traditional methods, e.g., with 20 cooperating organizations, over 50% more spam is detected. …”
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A Detection and Cover Integrated Waveform Design Method with Good Correlation Characteristics and Doppler Tolerance by Haoting Guo, Fulai Wang, Nanjun Li, Zezhou Wu, Chen Pang, Lei Zhang, Yongzhen Li

“…The gradient descent algorithm is used to solve the model, and the optimized waveform with low sidelobe characteristics and multiple false target interference abilities is obtained. …”
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