Pork-YOLO: Automated collection of pork quality traits by Jiacheng Wei, Xi Tang, Jinxiu Liu, Ting Luo, Yan Wu, Junhui Duan, Shijun Xiao, Zhiyan Zhang

“…Next, the StarNet backbone was integrated, employing star-shaped operations for high-dimensional feature representation while maintaining computational efficiency, along with a hierarchical convolutional structure to boost performance. …”
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Multiclass Fault Diagnosis in Power Transformers Using Dissolved Gas Analysis and Grid Search-Optimized Machine Learning by Andrew Adewunmi Adekunle, Issouf Fofana, Patrick Picher, Esperanza Mariela Rodriguez-Celis, Oscar Henry Arroyo-Fernandez, Hugo Simard, Marc-André Lavoie

“…To address these limitations, this study proposes a unified multiclass classification model that integrates traditional gas ratio features with supervised machine learning algorithms to enhance fault diagnosis accuracy. …”
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Identification of biomarkers for knee osteoarthritis through clinical data and machine learning models by Wei Chen, Haotian Zheng, Binglin Ye, Tiefeng Guo, Yude Xu, Zhibin Fu, Xing Ji, Xiping Chai, Shenghua Li, Qiang Deng

“…Similarly, in the validation dataset, these models achieved AUC values of 0.961, 0.943, 0.789, 0.957, 0.824, and 0.76. …”
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Harnessing the machine learning and nomogram models: elevating prognostication in nonmetastatic gastric cancer with “double invasion” for personalized patient care by Zhenwen Hao, Zhiming Wang, Jinfeng Ma, Yifan Li, Wenbin Zhang

“…All models showed good calibration with low integrated Brier scores (< 0.1), although there was calibration drift over time, particularly in the traditional nomogram model. …”
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Modelling soil prokaryotic traits across environments with the trait sequence database ampliconTraits and the R package MicEnvMod by Jonathan Donhauser, Anna Doménech-Pascual, Xingguo Han, Karen Jordaan, Jean-Baptiste Ramond, Aline Frossard, Anna M. Romaní, Anders Priemé

“…We created the trait sequence database ampliconTraits, constructed by cross-mapping species from a phenotypic trait database to the SILVA sequence database and formatted to enable seamless classification of environmental sequences using the SINAPS algorithm. The R package MicEnvMod enables modelling of trait – environment relationships, combining the strengths of different model types and integrating an approach to evaluate the models' predictive performance in a single framework. …”
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Ultrasound Assessment in Polycystic Ovary Syndrome Diagnosis: From Origins to Future Perspectives—A Comprehensive Review by Stefano Di Michele, Anna Maria Fulghesu, Elena Pittui, Martina Cordella, Gilda Sicilia, Giuseppina Mandurino, Maurizio Nicola D’Alterio, Salvatore Giovanni Vitale, Stefano Angioni

“…Studies on diagnostic criteria, imaging modalities, stromal assessment, and machine-learning algorithms were prioritized. Additional references were identified via citation screening. …”
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A nomogram combining clinical features, O-RADS US, and radiomics based on ultrasound imaging for diagnosing ovarian cancer by Wenting Xie, Yaoqin Wang, Zhongshi Du, Yijie Chen, Xiaohui Ke, Tingfan Wu, Zhilan Wang, Lina Tang

“…O-RADS US characteristics, radiomics score, and clinical features selected using the LASSO algorithm were used to develop O-RADS US + Radscore + Clinical, Radscore + Clinical, and O-RADS US + Clinical models, respectively. …”
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Reinforcement Learning With Deep Features: A Dynamic Approach for Intrusion Detection in IoT Networks by Mohamad Khayat, Ezedin Barka, Mohamed Adel Serhani, Farag Sallabi, Khaled Shuaib, Heba M. Khater

“…First, various preprocessing techniques such as handling missing values, outliers, and min-max scaling normalization were applied. …”
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Spatial Prediction of Soil Continuous and Categorical Properties Using Deep Learning Approaches for Tamil Nadu, India by Thamizh Vendan Tarun Kshatriya, Ramalingam Kumaraperumal, Sellaperumal Pazhanivelan, Nivas Raj Moorthi, Dhanaraju Muthumanickam, Kaliaperumal Ragunath, Jagadeeswaran Ramasamy

“…Irrespective of the algorithms and datasets, the R² and RMSE values of the pH attribute ranged from 0.15 to 0.30 and 0.97 to 1.15, respectively. …”
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Improving National Forest Mapping in Romania Using Machine Learning and Sentinel-2 Multispectral Imagery by Mohamed Islam Keskes, Aya Hamed Mohamed, Stelian Alexandru Borz, Mihai Daniel Niţă

“…This study addresses these challenges by integrating machine learning algorithms with high-resolution remotely sensed data and rigorously collected ground truth measurements to produce accurate, national-scale maps of forest attributes in Romania. …”
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Geoinformatics and Machine Learning for Shoreline Change Monitoring: A 35-Year Analysis of Coastal Erosion in the Upper Gulf of Thailand by Chakrit Chawalit, Wuttichai Boonpook, Asamaporn Sitthi, Kritanai Torsri, Daroonwan Kamthonkiat, Yumin Tan, Apised Suwansaard, Attawut Nardkulpat

“…This study analyzes 35 years (1988–2023) of shoreline changes using geoinformatics, machine learning algorithms (Random Forest, Support Vector Machine, Maximum Likelihood, Minimum Distance), and the Digital Shoreline Analysis System (DSAS). …”
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Genomic Analysis of Reproductive Trait Divergence in Duroc and Yorkshire Pigs: A Comparison of Mixed Models and Selective Sweep Detection by Changyi Chen, Yu He, Juan Ke, Xiaoran Zhang, Junwen Fei, Boxing Sun, Hao Sun, Chunyan Bai

“…Notably, 587 SNPs and 171 genes were uniquely detected by the LMM + ADDO method and not among loci detected by the top 5% of <i>F_ST</i> and θ_π values. Key candidate genes associated with litter size included <i>HSPG2</i>, <i>KAT6B</i>, <i>SAMD8</i>, and <i>LRMDA</i>, while <i>DLGAP1</i>, <i>MYOM1</i>, and <i>VTI1A</i> were associated with teat number traits. (3) Conclusions: This study demonstrates the power of integrating additive and dominant effect modeling with population genetics approaches for the detection of genomic regions under selection. …”
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Exploring the host response in infected lung organoids using NanoString technology: A statistical analysis of gene expression data. by Mostafa Rezapour, Stephen J Walker, David A Ornelles, Muhammad Khalid Khan Niazi, Patrick M McNutt, Anthony Atala, Metin Nafi Gurcan

“…To enhance the comprehensiveness of our analysis, we introduced a novel algorithm, namely MAS (Magnitude-Altitude Score). This innovative approach uniquely combines biological significance, as indicated by fold changes in gene expression, with statistical rigor, as represented by adjusted p-values. …”
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Real-Time Detection and Localization of Force on a Capacitive Elastomeric Sensor Array Using Image Processing and Machine Learning by Peter Werner Egger, Gidugu Lakshmi Srinivas, Mathias Brandstötter

“…This study presents a real-time force point detection and tracking system using a custom-fabricated soft elastomeric capacitive sensor array in conjunction with image processing and machine learning techniques. The system integrates Otsu’s thresholding, Connected Component Labeling, and a tailored cluster-tracking algorithm for anomaly detection, enabling real-time localization within 1 ms. …”
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Dehydrotanshinone II A alleviates osteoarthritis via activating PPARγ to inhibit ferroptosis in chondrocytes by Wenli Guan, Fahu Yuan, Xin Wang

“…Furthermore, the scTenifoldKnk algorithm was applied to perform a virtual knockout of PPARγ based on the GSE216651 single-cell RNA-seq dataset to explore its downstream regulatory effects. …”
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Bearing Response Prediction in Hydrothermal Aged Carbon Fiber Reinforced Epoxy Composite Joints Using Machine Learning Techniques by Mohit Kumar, Govind Vashishtha, Babita Dhiman, Sumika Chauhan

“…The predictive models find the value of 0.0081 RSME and 0.8 R2 respectively through support vector regression confirming that the predicted values lie in between the upper and lower bond.…”
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Wide-Angle Image Distortion Correction and Embedded Stitching System Design Based on Swin Transformer by Shiwen Lai, Zuling Cheng, Wencui Zhang, Maowei Chen

“…Experiments on synthetic and real-world datasets show that the method outperforms mainstream algorithms, with PSNR gains of 3.28 dB and 2.18 dB on wide-angle and fisheye images, respectively, while maintaining real-time performance. …”
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Multi-Agent Reinforcement Learning in Games: Research and Applications by Haiyang Li, Ping Yang, Weidong Liu, Shaoqiang Yan, Xinyi Zhang, Donglin Zhu

“…Building upon stochastic game and extensive-form game-theoretic frameworks, we establish a methodological taxonomy across three dimensions: value function optimization, policy gradient learning, and online search planning, thereby clarifying the evolutionary logic and innovation trajectories of algorithmic advancements. …”
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Design of Cloud-Based Complex VR 3D Scene Interaction Based on Attribute Preferences by Ze Yu Yang, Yeom Jun Young

“…This research sets a precedent for future advancements in VR environments, emphasizing the value of combining advanced algorithms to address complex challenges in immersive technology.…”
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A Dynamic Precision Evaluation System for Physical Education Classroom Teaching Behaviors Based on the CogVLM2-Video Model by Chao Liu, Fan Yang, Chengyu Ge, Zhiyu Shao

“…The platform layer manages data processing and storage, ensuring integrity and security for long-term evaluation. The model layer focuses on behavior recognition and analysis, employing advanced algorithms for precise interpretation of teaching behaviors. …”
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