Nanosurface‐Reconstructed Fuel Electrode by Selective Etching for Highly Efficient and Stable Solid Oxide Cells by Yueyue Sun, Jun Zhou, Jiaming Yang, Dragos Neagu, Zhengrong Liu, Chaofan Yin, Zixuan Xue, Zilin Zhou, Jiajia Cui, Kai Wu

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LIPUS Responsive Dopamine-Modified PVDF Piezoelectric Nanofiber Membrane for Full-Thickness Skin Wound Healing by Zhang Z, Liu L, Wang H, Xie W, Zhai W, Wen L, Zhang B, Liu K, Zhang X, Liu S, Huang L, Li D, Zhou Y

“…In vivo, the DA/PVDF+LIPUS group exhibited significantly higher wound healing rates, with improved epidermal regeneration, collagen fiber deposition and remodeling, and enhanced blood vessel and skin appendage formation.Conclusion: DA modification enhances the piezoelectric properties of PVDF membranes, boosting cell adhesion and promoting dermal and vascular regeneration. …”
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Machine learning and artificial intelligence in type 2 diabetes prediction: a comprehensive 33-year bibliometric and literature analysis by Mahreen Kiran, Ying Xie, Nasreen Anjum, Graham Ball, Barbara Pierscionek, Duncan Russell

“…Ensemble methods (e.g., Random Forest, Gradient Boosting) and deep learning models (e.g., Convolutional Neural Networks) dominate recent advancements. …”
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Pasteurized waste milk vs. milk replacer at the same crude protein:metabolizable energy ratio with different energy sources (fat vs. lactose) to pre-weaning Holstein calves: Effect... by Shahryar Kargar, Borhan Moradi, Meysam Kanani, Marzia Albenzio, Mariangela Caroprese, Mohammad Javad Zamiri, Ícaro Rainyer Rodrigues de Castro, Marcos Inácio Marcondes

“…The type and pasteurization process of liquid feed are among the most variable feeding practices affecting calves' growth and health. …”
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Proposal for Using AI to Assess Clinical Data Integrity and Generate Metadata: Algorithm Development and Validation by Caroline Bönisch, Christian Schmidt, Dorothea Kesztyüs, Hans A Kestler, Tibor Kesztyüs

“…In addition, embedded in the process of integrating care data into a medical data integration center (MeDIC), metadata relevant to this clinical data was stored, considering factors such as data granularity and quality metrics. …”
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Mitochondrial insights: key biomarkers and potential treatments for diabetic nephropathy and sarcopenia by Yi Wei Chen, Shan He, Yu Wang, Lian Ying Hu, Qin Kai Chen, Si Yi Liu

“…Using Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine (SVM), Extreme Gradient Boosting (XGB), and Random Forest (RF) algorithms, we identified three key mitochondrial hub genes. …”
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Effects of intercropping with legume forage on the rhizosphere microbial community structure of tea plants by Yuhang Jiang, Yuhang Jiang, Yuhang Jiang, Xiaoqin Lin, Wenxiong Lin, Wenxiong Lin

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Machine learning approaches for predicting frailty base on multimorbidities in US adults using NHANES data (1999–2018) by Teng Li, Xueke Li, Haoran XU, Yanyan Wang, Jingyu Ren, Shixiang Jing, Zichen Jin, Gang chen, Youyou Zhai, Zeyu Wu, Ge Zhang, Yuying Wang

“…And in machine learning process, feature selection for the frailty prediction model involved three algorithms. …”
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Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese or... by Caumette, Cécile, Diatta, Paterne, Piry, Sylvain, Chapuis, Marie-Pierre, Faye, Emile, Sigrist, Fabio, Martin, Olivier, Papaïx, Julien, Brévault, Thierry, Berthier, Karine

“…We then developed a flexible analysis pipeline centred on a recent machine learning algorithm, which allows the combination of gradient boosting and grouped random effects models or Gaussian processes, to hierarchize the effects of multi-scale environmental variables on the onset of annual BD population growth in orchards. …”
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From traditional medicine to modern medicine: the importance of TCM regulatory science (TCMRS) as an emerging discipline by Hua Hua, Jian-Yuan Tang, Jun-Ning Zhao, Ting Wang, Jun-Hua Zhang, Jiang-Yong Yu, Chang-Ming Yang, Yan-Ling Ai, Qiao-Xian Luo

“…These efforts are essential for promoting the high-quality development of the TCM industry and boosting its international influence and presence.…”
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Easy Data Augmentation untuk Data yang Imbalance pada Konsultasi Kesehatan Daring by Anisa Nur Azizah, Misbachul Falach Asy'ari, Ifnu Wisma Dwi Prastya, Diana Purwitasari

“…Then, the experiments investigate our augmentation process using classifiers of Random Forest, Naïve Bayes, and boosting-based methods like XGBoost and ADABoost, which resulted in an average accuracy increase of 0.63. …”
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A Magnetic Photocatalytic Composite Derived from Waste Rice Noodle and Red Mud by Qing Liu, Wanying Ying, Hailing Gou, Minghui Li, Ke Huang, Renyuan Xu, Guanzhi Ding, Pengyu Wang, Shuoping Chen

“…This study is the first to convert two waste materials, waste rice noodles (WRN) and red mud (RM), into a low-cost, high-value magnetic photocatalytic composite. WRN was processed via a hydrothermal method to produce a solution containing carbon quantum dots (CQDs). …”
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Weaning performance prediction in lactating sows using machine learning, for precision nutrition and intelligent feeding by Jiayi Su, Xiangfeng Kong, Wenliang Wang, Qian Xie, Chengming Wang, Bie Tan, Jing Wang

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Functionalization of biochar using SDS/SAP nanomicelles enhanced its immobilization capacity for dyes and heavy metals in water by Kun Tian, Chunping Li, Huiming Liu, Lianchun Wang

“…The adsorption behavior of SDMBC for MB show that process was found to be spontaneous, propitious, endothermic, the adsorption isotherms fitted Freundlich models well, pseudo-second-order best describes kinetics adsorption, suggesting that the process is multi-layer chemical adsorption. …”
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Capturing cell heterogeneity in representations of cell populations for image-based profiling using contrastive learning. by Robert van Dijk, John Arevalo, Mehrtash Babadi, Anne E Carpenter, Shantanu Singh

“…CytoSummaryNet offers a straightforward post-processing step for single-cell profiles that can significantly boost retrieval performance on image-based profiling datasets.…”
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THE POSITION OF AGRICULTURE, AGRO-FOOD SYSTEM AND NATIONAL ECONOMY by Daniela SIMTION

“…Modernization of agriculture had the effect of income transfers to other sectors and the boost of overall economic development but also led to a relative decline of agriculture in favour of the food industry. …”
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Navigating the AI Energy Challenge: A Sociotechnical Framework and Strategic Solutions for Sustainable Artificial Intelligence by Liu Xiaoyang

“…Comprehensive case analyses reveal critical leverage points where targeted interventions boost performance while significantly reducing energy consumption. …”
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Equivalent method for DFIG wind farms based on modified LightGBM considering voltage deep drop faults by Xuecheng Liu, Peixiao Fan, Jun Yang, Song Ke, Binyu Ma, Yangzhou Pei, Jian Xu

“…First, the low voltage ride through process of wind turbines is analysed, with particular consideration given to the scenario of partial wind turbines tripping off due to voltage deep drop faults in the wind farm. …”
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Development and validation of machine learning-derived frailty index in predicting outcomes of patients undergoing percutaneous coronary intervention by John T.Y. Soong, L.F. Tan, Rodney Y.H. Soh, W.B. He, Andie H. Djohan, H.W. Sim, T.C. Yeo, H.C. Tan, Mark Y.Y. Chan, C.H. Sia, M.L. Feng

“…Logistic regression model and Extreme Gradient Boosting (XGBoost) machine learning model were constructed to identify predictors of adverse clinical outcomes post PCI. …”
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New Maps of Lunar Surface Oxide Abundances and Mg# Using an Optimized Ensemble Learning Algorithm by Chaofa Bian, Kefei Zhang, Yunzhao Wu, Suqin Wu, Yu Lu, Yabo Duan, Huajing Wu, Zhenxing Zhao, Wei Wu

“…Among the models tested, the SXL algorithm (stacking of support vector machine regression, extreme gradient boosting, and linear regression), which was selected from a stack of 2 or 3 out of six typical algorithms, achieved the highest inversion accuracy. …”
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