Intelligent design of Fe–Cr–Ni–Al/Ti multi-principal element alloys based on machine learning by Kang Xu, Zhengming Sun, Jian Tu, Wenwang Wu, Huihui Yang

“…This study proposes an innovative intelligent optimization algorithm (OA) to refine feature selection in machine learning (ML) models, targeting the prediction of ultimate tensile strength (UTS) and fracture elongation (FE) in MPEAs. …”
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THE ROLE OF INNOVATION IN THE SUCCESSION OF FAMILY BUSINESSES by Boglárka Tóth

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Application of machine learning algorithm to predict the behavior of stocks marketed in Brazil by Gabriel Donadio Costa, Rogério João Lunkes

“…In contrast, the model including the combination of technical and fundamental variables revealed an average accuracy of 70,7 % on 5 folds, which was supported by the literature that indicates that hybrid models can provide greater accuracy and lower volatility. In addition, results exceed the accuracy of previous studies (e.g. …”
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Identifying Key Factors for Predicting the Age at Peak Height Velocity in Preadolescent Team Sports Athletes Using Explainable Machine Learning by Nikolaos-Orestis Retzepis, Alexandra Avloniti, Christos Kokkotis, Maria Protopapa, Theodoros Stampoulis, Anastasia Gkachtsou, Dimitris Pantazis, Dimitris Balampanos, Ilias Smilios, Athanasios Chatzinikolaou

“…Independent sample <i>t</i>-tests on these selected factors confirmed their significance in distinguishing between the two classes. …”
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Prediction model of middle school student performance based on MBSO and MDBO-BP-Adaboost method by Rencheng Fang, Tao Zhou, Baohua Yu, Zhigang Li, Long Ma, Tao Luo, Yongcai Zhang, Xinqi Liu

“…Based on this motivation, this paper proposes an improved Binary Snake Optimizer (MBSO) as a wrapped feature selection model, taking the Mat and Por student achievement data in the UCI database as an example, and comparing the MBSO feature selection model with other feature methods, the MBSO is able to select features with strong correlation to the students and the average number of student features selected reaches a minimum of 7.90 and 7.10, which greatly reduces the complexity of student achievement prediction. …”
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Validation and Optimization of PURE Ribosome Display for Screening Synthetic Nanobody Libraries by Bingying Liu, Daiwen Yang

“…Background/Objectives: PURE (Protein synthesis Using Recombinant Elements), an ideal system for ribosome display, has been successfully used for nanobody selection. However, its limitations in nanobody selection, especially for synthetic nanobody libraries, have not been clearly elucidated, thereby restricting its utilization. …”
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Evidence for Significant Skew and Low Heritability of Competitive Male Mating Success in the Yellow Fever Mosquito Aedes aegypti by Claudia A. S. Wyer, Vladimir Trajanovikj, Brian Hollis, Alongkot Ponlawat, Lauren J. Cator

“…These findings enhance our understanding of sexual selection in this species and have important implications for mass‐release programmes that rely on the release of competitive males.…”
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Genotypic and Phenotypic Association of Agronomic Features in Triticale Genotypes under Drought Stress Conditions by Hassan Basiri, Omid Alizadeh, Forud Bazrafshan, Mehdi Zare, Mohammad Yazdani

“…In the current study, different triticale genotypes produced by domestic scientists were cultivated and tested under different irrigation conditions to consider the possibility of introducing new cultivars resistant to drought stress and changing environmental conditions. In addition, the relationship between morphological and agronomic traits related to seed yield was evaluated in this research using some advanced statistical methods to find possible traits suitable for indirect selection. …”
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Local Ancestry and Adaptive Introgression in Xiangnan Cattle by Huixuan Yan, Jianbo Li, Kunyu Zhang, Hongfeng Duan, Ao Sun, Baizhong Zhang, Fuqiang Li, Ningbo Chen, Chuzhao Lei, Kangle Yi

“…In addition, the considerable introgression from banteng and gaur also contributed to the rapid adaptation of Xiangnan cattle to the environment of Southern China. …”
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Effect of micrografting technique on growth and cold resistance of tea (Camellia sinensis) plant by Yaohua Cheng, Mengling Lin, Hongying Wang, Ziwen Zhou, Linxin Long, Qi Yang, Qiuyan Ban, Xianchen Zhang, Yeyun Li

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Evolutionary trajectory estimation via replication simulation of coronavirus spike gene based on random mutation and similarity-based selection by Min Chan Kim, Hye Ji Jung, Seong Sik Jang, Van Thi Lo, Hye Kwon Kim

“…The model-generated intermediate spike sequences exhibited similarities to real-world evolutionary patterns, including B, B.1.2, B.1.160, B.1.398, B.1.1.529, and BA.1 lineages. Additionally, the approach replicated the divergent evolutionary outcomes of PEDV subjected to distinct selection regimes (with and without trypsin treatment). …”
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Associations among MHC genes, latitude, and avian malaria infections in the rufous‐collared sparrow (Zonotrichia capensis) by Juan Rivero de Aguilar, Omar Barroso, Elisa Bonaccorso, Hector Cadena, Lucas Hussing, Josefina Jorquera, Javier Martinez, Josué Martínez‐de la Puente, Alfonso Marzal, Fabiola León Miranda, Santiago Merino, Nubia E. Matta, Marilyn Ramenofsky, Ricardo Rozzi, Carlos E. Valeris‐Chacín, Rodrigo A. Vásquez, Juliana A. Vianna, John C. Wingfield

“…We detected between 1–4 (MHC‐I) and 1–6 (MHC‐II) amino acidic alleles per individual, with signs of positive selection. We obtained generalized additive mixed models to explore the associations between MHC‐I and MHC‐II diversity and latitude. …”
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Integrated feature selection-based stacking ensemble model using optimized hyperparameters to predict breast cancer with smart web application by Rajib Kumar Halder, Marzana Akter Lima, Mohammed Nasir Uddin, Md.Aminul Islam, Adri Saha

“…Significantly, our feature selection process involves three methodologies: filter, wrapper, and embedded methods. …”
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Comparison of machine learning models for mucopolysaccharidosis early diagnosis using UAE medical records by Aamna AlShehhi, Hiba Alblooshi, Ruba Fadul, Natnael Tumzghi, Amal Al Tenaiji, Mariam Al Harbi, Fatma Al-Jasmi

“…Using nested cross-validation, we trained different feature selection algorithms in combination with various ML algorithms and evaluated their performance with multiple evaluation metrics. …”
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Genomic insights into the mechanisms of body size evolution in Serpentes by Tian Xia, Shengyang Zhou, Zhihao Zhang, Xiaoyang Wu, Xibao Wang, Jianqun Ding, Lei Zhang, Guolei Sun, Xiufeng Yang, Xiaodong Gao, Honghai Zhang

“…Immune system-related genes, including those involved in antigen processing and presentation, similarly showed signatures of expansion and adaptive evolution, highlighting strengthened immune defenses in large-bodied snakes. Additionally, key candidate genes, such as YAP1, PLAG1, MGAT1 and SPRY1, exhibited both strong selection signals and correlation signals, and are functionally involved in developmental pathways critical for growth regulation. …”
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Influence of intercritical annealing temperature on TRIP/TWIP effect of retained austenite and tensile deformation mechanism of IQ&P steel by Shaolong Zhang, Wen Zhou, Feng Hu, Kaiming Wu, Serhii Yershov

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Agromorphological Evaluation of Elite Lines of Native Tomato (<i>Solanum lycopersicum</i> L.) from Central and Southern Mexico by María Concepción Valencia-Juárez, Enrique González-Pérez, Salvador Villalobos-Reyes, Carlos Alberto Núñez-Colín, Jaime Canul-Ku, José Luis Anaya-López, Elizabeth Chiquito-Almanza, Ricardo Yáñez-López

“…Lines JCM-17, JMC-10, and JCM-01 were the most selectable lines according to the ESIM values. The morphological variation found and the characteristics with higher selection values identified may be valuable for optimizing the tomato genetic improvement process in general.…”
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A data-centric and interpretable EEG framework for depression severity grading using SHAP-based insights by Anruo Shen, Jingnan Sun, Xiaogang Chen, Xiaorong Gao

“…Methods We proposed a data-centric, interpretable framework for EEG-based depression severity grading. A hybrid feature selection method was used, combining p-value and SHapley Additive exPlanations (SHAP) methods to select features that are both independently significant and jointly informative. …”
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Landscape genetics highlights species-specific ecological influences on gene flow in highland frog populations from northeastern Brazil by José Henrique de Andrade Lima, Marco Katzenberger, Marcelo Gehara, Pedro Ivo Simões

“…These findings suggest that both selective and neutral mechanisms contribute to genetic variation. …”
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ML-CKDP: Machine learning-based chronic kidney disease prediction with smart web application by Rajib Kumar Halder, Mohammed Nasir Uddin, Md. Ashraf Uddin, Sunil Aryal, Sajeeb Saha, Rakib Hossen, Sabbir Ahmed, Mohammad Abu Tareq Rony, Mosammat Farida Akter

“…The proposed model involves a comprehensive data preprocessing protocol, converting categorical variables to numerical values, imputing missing data, and normalizing via Min-Max scaling. Feature selection is executed using a variety of techniques including Correlation, Chi-Square, Variance Threshold, Recursive Feature Elimination, Sequential Forward Selection, Lasso Regression, and Ridge Regression to refine the datasets. …”
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