Genomic Prediction of Milk Fat Percentage Among Crossbred Cattle in the Indian Subcontinent by Raghavendran Vadivel Balasubramanian, Murali Nagarajan, Marimuthu Swaminathan, Raja Angamuthu, Muralidharan Jaganadhan, Saravanan Ramasamy, Malarmathi Muthusamy, Thiruvenkadan Aranganoor Kannan, Sunday Olusola Peters

“…Genetic analysis involved 1478 animals genotyped for 49,911 SNPs after applying a rigorous quality control process, and imputation improved the accuracy of genomic data, boosting allele frequency correlation from 0.594 to 0.882. …”
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A Method for Enhancing the Traffic Situation Awareness of Vessel Traffic Service Operators by Identifying High Risk Ships in Complex Navigation Conditions by Lei Zhang, Jiahao Ge, Floris Goerlandt, Lei Du, Tuowei Chen, Tingting Gu, Langxiong Gan, Xiaobin Li

“…This approach can assist VTSOs in executing a comprehensive and targeted monitoring process encompassing macro, meso, and micro aspects, thus boosting the efficacy of ship oversight, and mitigating traffic hazards.…”
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The Manufacture and Investigation of 3D Current Collectors in a Lithium Ion Battery Obtained by Laser Powder Bed Fusion by Arseniy Repnin, Evgenii Borisov, Alexandra Kosenko, Konstantin Pushnitsa, Pavel Novikov, Anatoliy Popovich

“…The use of additive manufacturing to fabricate current collectors with increased surface area opens new opportunities for controlling electrode morphology, improving conductivity, and thereby boosting the overall performance of batteries. This can be achieved by increasing the contact area between the active mass and the current collector. …”
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Desertification Monitoring Using Machine Learning Techniques with Multiple Indicators Derived from Sentinel-2 in Turkmenistan by Arslan Berdyyev, Yousef A. Al-Masnay, Mukhiddin Juliev, Jilili Abuduwaili

“…It does this by integrating six important desertification indicators within machine learning models like random forest (RF), eXtreme Gradient Boosting (XGBoost), naïve Bayes (NB), and K-nearest neighbors (KNN). …”
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Diagnosis of epileptic seizure neurological condition using EEG signal: a multi-model algorithm by Mosleh Hmoud Al-Adhaileh, Mosleh Hmoud Al-Adhaileh, Sultan Ahmad, Alhasan A. Alharbi, Mohammed Alarfaj, Mohammed Alarfaj, Mukta Dhopeshwarkar, Theyazn H. H. Aldhyani

“…An essential step that may help clinicians identify and treat epileptic seizures is the differentiation between epileptic and non-epileptic signals by use of epileptic seizure detection categorization.MethodsIn this work, we investigated Machine learning algorithms including Random Forest, Gradient Boosting, and K-Nearest Neighbors, alongside advanced DL architectures such as Long Short-Term Memory networks and Long-term Recurrent Convolutional Networks for detecting epileptic seizures in terms of difficulties and procedures evolved depending on EEG data. …”
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Research on Reservoir Identification of Gas Hydrates with Well Logging Data Based on Machine Learning in Marine Areas: A Case Study from IODP Expedition 311 by Xudong Hu, Wangfeng Leng, Kun Xiao, Guo Song, Yiming Wei, Changchun Zou

“…This article selects six ML methods, including Gaussian process classification (GPC), support vector machine (SVM), multilayer perceptron (MLP), random forest (RF), extreme gradient boosting (XGBoost), and logistic regression (LR). …”
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Quality by design aided self-nano emulsifying drug delivery systems development for the oral delivery of Benidipine: Improvement of biopharmaceutical performance by Sheetal S. Buddhadev, Kevinkumar C. Garala, Saisivam S, Mohamed Rahamathulla, Mohammed Muqtader Ahmed, Syeda Ayesha Farhana, Ismail Pasha

“…Therefore, the development of oral S-SNEDDS of BD may be advantageous for raising BD's water solubility and expanding their releasing capabilities, thereby boosting oral absorption.…”
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PM6/L8‐BO Thin Films through Layer‐by‐Layer Engineering: Formation Mechanism, Energetic Disorder, and Carrier Mobility by Zihao Wen, Rongkun Zhou, Zilong Zheng, Yi Zhao

“…ABSTRACT Layer‐by‐layer (LBL) process has emerged as a promising method in the advancement of organic photovoltaics, emphasizing scalability and reproducibility. …”
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Group-Specific SVM With Bilevel Programming Methods for Parameter Optimization and Explainable AI in Urban Quality of Life Prediction by Gonzalo Rios-Vasquez, Hanns De La Fuente-Mella, Jose Ceroni-Diaz

“…These findings provide valuable insights for policymakers, supporting data-driven decision-making processes for urban development and resource allocation. …”
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Self-Powered Photodetectors with Ultra-Broad Spectral Response and Thermal Stability for Broadband, Energy Efficient Wearable Sensing and Optoelectronics by Peter X. Feng, Elluz Pacheco Cabrera, Jin Chu, Badi Zhou, Soraya Y. Flores, Xiaoyan Peng, Yiming Li, Liz M. Diaz-Vazquez, Andrew F. Zhou

“…This architecture facilitates plasmon-enhanced absorption and efficient charge separation via heterojunction interfaces, significantly boosting photocurrent generation across the deep ultraviolet (DUV), visible, near-infrared (NIR), and mid-infrared (MIR) spectral regions. …”
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Comparing the Performance of Automatic Milking Systems through Dynamic Testing Also Helps to Identify Potential Risk Factors for Mastitis by Stefano Milanesi, Dario Donina, Viviana Chierici Guido, Francesca Zaghen, Valerio M. Sora, Alfonso Zecconi

“…Automatic milking systems (AMSs) are revolutionizing the dairy industry by boosting herd efficiency, primarily through an increased milk yield per cow and reduced labor costs. …”
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Explainable machine learning models for identifying mild cognitive impairment in older patients with chronic pain by Xiaoang Zhang, Yuping Liao, Daying Zhang, Weichen Liu, Zhijian Wang, Yaxin Jin, Shushu Chen, Jianmei Wei

“…The dataset was randomly divided into training set and testing set, and processed by Min-Max Normalization and SMOTETomek comprehensive sampling. …”
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Grape vine (Vitis vinifera) yield prediction using optimized weighted ensemble machine learning approach by Nobin Chandra Paul, Pratapsingh S. Khapte, Navyasree Ponnaganti, Sushil S. Changan, Sangram B. Chavan, K. Ravi Kumar, Dhananjay D. Nangare, K. Sammi Reddy

“…A diverse set of machine learning (ML) models, including Random Forest (RF), Artificial Neural Network (ANN), Extreme Gradient Boosting (XgBoost), Support Vector Regression (SVR), Gaussian Process Regression (GPR), Cubist and Multivariate Adaptive Regression Splines (MARS), were employed to model the grapevine yield. …”
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A Meta-Learning-Based Ensemble Model for Explainable Alzheimer’s Disease Diagnosis by Fatima Hasan Al-bakri, Wan Mohd Yaakob Wan Bejuri, Mohamed Nasser Al-Andoli, Raja Rina Raja Ikram, Hui Min Khor, Zulkifli Tahir, The Alzheimer’s Disease Neuroimaging Initiative

“…The methodology involves training an ensemble model that integrates Random Forest, Support Vector Machine, XGBoost, and Gradient Boosting classifiers, with meta-logistic regression used for the final decision. …”
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Machine learning-based pseudo-continuous pedotransfer function for predicting soil freezing characteristic curve by Sangyeong Park, Yongjoon Choe, Hangseok Choi, Khanh Pham

“…Unfrozen water plays a crucial role in thermophysical processes occurring in frozen ground. Measurement difficulties require approximate approaches to describe the relationship between unfrozen water content (θ) and soil temperature, known as soil freezing characteristic curve (SFCC). …”
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Oversampling and undersampling for intrusion detection system in the supervisory control and data acquisition IEC 60870‐5‐104 by M. Agus Syamsul Arifin, Deris Stiawan, Bhakti Yudho Suprapto, Susanto Susanto, Tasmi Salim, Mohd Yazid Idris, Rahmat Budiarto

“…Abstract Supervisory control and data acquisition systems are critical in Industry 4.0 for controlling and monitoring industrial processes. However, these systems are vulnerable to various attacks, and therefore, intelligent and robust intrusion detection systems as security tools are necessary for ensuring security. …”
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Advancing Neurodegenerative Disease Management: Technical, Ethical, and Regulatory Insights from the NeuroPredict Platform by Marilena Ianculescu, Lidia Băjenaru, Ana-Mihaela Vasilevschi, Maria Gheorghe-Moisii, Cristina-Gabriela Gheorghe

“…Machine learning algorithms process these data flows to find patterns that point out disease evolution. …”
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The goals and selection criteria of sports scholarships: mutual benefits perceived by South African schools' by Christopher Ekron, Brendon Knott, H. Thomas R. Persson, Mogammad Sharhidd Taliep

“…While recipients gain educational and sporting opportunities, schools benefit from the athletic talent and boosts their competitive sporting edge and prestige status. …”
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Plant nickel-exclusion versus hyperaccumulation: a microbial perspective by Julie Dijoux, Sarah Gigante, Gael Lecellier, Linda Guentas, Valérie Burtet-Sarramegna

“…Ultramafic substrates also host many unique microorganisms, which are adapted to metallic environments and capable of boosting plant growth while assisting plants in acquiring essential micronutrients. …”
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Stepwise Downscaling of ERA5-Land Reanalysis Air Temperature: A Case Study in Nanjing, China by Xuelian Li, Guixin Zhang, Shanyou Zhu, Yongming Xu

“…These results generally suggest that the stepwise downscaling method can significantly improve the accuracy of air temperature downscaled from reanalysis data by adopting multiple resolutions as the intermediate downscaling process.…”
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