Towards an intelligent integrated methodology for accurate determination of volume percentages in three-phase flow systems by Abdullah M. Iliyasu, Mohammad Sh. Daoud, Ahmed Sayed Salama, John William Grimaldo Guerrero, Kaoru Hirota

“…Abstract Accurate determination of volume percentages in three-phase fluids is paramount for the success of various industrial processes, ranging from oil and gas production to chemical engineering. …”
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Robust fault detection in electrochemical energy storage systems under label noise: applications to lithium-ion batteries and transformer windings by Tao He, Wei Liu, Xin Wu, Yu Wei

“…The results demonstrate that the rectification framework significantly improves classification accuracy across both Support Vector Machine (SVM) and Extreme Learning Machine (ELM) classifiers. …”
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Pioneering CPMI framework for accurate state-of-health assessment in Lithium ion battery power management using FBG sensors by Taher M. Ghazal, Ali Q. Saeed, Mosleh M. Abualhaj, Taj-Aldeen Naser Abdali, Munir Ahmad

“…The proposed system employs a support vector-based classification algorithm that categorizes operational states based on FBG sensor data streams, identifying deviations from optimal temperature and voltage ranges. …”
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Ensemble Learning-Based Metamodel for Enhanced Surface Roughness Prediction in Polymeric Machining by Elango Natarajan, Manickam Ramasamy, Sangeetha Elango, Karthikeyan Mohanraj, Chun Kit Ang, Ali Khalfallah

“…Second, a regressor (Support Vector Regressor or XGBoost, selected based on performance) predicts Ra within each regime, utilizing the classifier’s output as an additional feature. …”
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History Matching of a Channelized Reservoir Using a Serial Denoising Autoencoder Integrated with ES-MDA by Sungil Kim, Baehyun Min, Seoyoon Kwon, Min-gon Chu

“…It does this through encoding and decoding processes using the noise realizations as inputs and the original realizations as outputs of the SDAE. …”
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Genome editing in mouse spermatogonial stem cell lines targeting the Tex15 gene using CRISPR/Cas9 by Suheyla Yeşilbostan, Suheyla Yeşilbostan, Mustafa Yenal Akkurt, Sinan Özkavukçu, Sinan Özkavukçu, Oǧuz Kul, Bengi Çınar

“…CRISPR/Cas9-mediated DNA endonuclease technology has been extensively utilized to introduce targeted genomic mutations for investigating biological processes across various cell types and organisms. …”
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Theoretical background for the bionic substantiation of parameters of the stubble cultivator working bodies by L. F. Babitsky, I. V. Sobolevsky, V. A. Kuklin

“…The optimal curvilinear shape of the working surface made in the form of a logarithmic spiral, is characterized by a constant value of the angle between the normal and the radius vector, and the value of this angle, equal to the angle of internal friction of the soil φ2, will ensure the sliding of the soil and plant residues with minimal energy consumption. …”
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Whole Genome Sequencing Reveals Clade‐Specific Genetic Variation in Blacklegged Ticks by Jacob Cassens, Adela S. Oliva Chávez, Danielle M. Tufts, Jianmin Zhong, Christopher Faulk, Jonathan D. Oliver

“…ABSTRACT Ticks and tick‐borne pathogens represent the greatest vector‐borne disease threat in the United States. …”
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Machine learning with analysis-of-variance-based method for identifying rice varieties by Nabin Kumar Naik, M. Venkata Subbarao, Prabira Kumar Sethy, Santi Kumari Behera, Gyana Ranjan Panigrahi

“…Implementing this methodology in real-world scenarios could significantly enhance the efficiency and accuracy of the rice variety identification processes, benefiting both producers and consumers.…”
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Machine Learning Strategies for Forecasting Mannosylerythritol Lipid Production Through Fermentation: A Proof-of-Concept by Carolina A. Vares, Sofia P. Agostinho, Ana L. N. Fred, Nuno T. Faria, Carlos A. V. Rodrigues

“…Fermentations are complex and often unpredictable processes. However, fermentation-based bioprocesses generate large volumes of data that are currently underexplored. …”
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Effects of Motor Preparation on Walking Ability in Active Ankle Dorsiflexion by Hiroki Ito, Hideaki Yamaguchi, Ryosuke Yamauchi, Ken Kitai, Kazuhei Nishimoto, Takayuki Kodama

“…Conclusions: These findings highlight that the motor preparation processes of the brain during active ankle dorsiflexion are involved in walking ability and can be used to predict it. …”
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Machine Learning-Based Normal White Blood Cell Multi-Classification Optimization by Taeyeon Gil, Sukjun Lee, Onseok Lee

“…Among the five multiple classifiers, the support vector machine achieved the highest accuracy of 97.36% and was chosen for WBC classification. …”
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Incorporating phylogenetic metrics of biodiversity to refine Lyme disease risk models by Shannon Summers, Grace Shaw, Andrea Swei

“…Few studies have examined the relationship between phylogenetic diversity and disease transmission, particularly in vector‐borne transmission systems. This study seeks to quantify phylogenetic diversity in the western United States Lyme disease system, where the causal agent Borrelia burgdorferi is vectored by the western black‐legged tick, Ixodes pacificus. …”
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Evaluating machine learning algorithms for energy consumption prediction in electric vehicles: A comparative study by Izhar Hussain, Kok Boon Ching, Chessda Uttraphan, Kim Gaik Tay, Adil Noor

“…This research examined the performance of eleven machine learning models for this purpose: Ridge Regression, Lasso Regression, K-Nearest Neighbors, Gradient Boosting, Support Vector Regression, Multi-Layer Perceptron, XGBoost, CatBoost, LightGBM, Gaussian Processes for Regression(GPR) and Extra Trees Regressor, considering real historical data from Colorado. …”
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Research progress and considerations for thalassemia gene therapy by GAO Xinjie, LIU Yan, WANG Dawei

“…This article summarizes the marketed products and research progress in clinical trials, aiming to analyze the respective advantages and limitations of these two approaches, and discusses the effectiveness and safety of current gene therapies for β-thalassemia, as well as the future directions for associated technologies, including ex vivo HSC expansion with maintenance of stemness and vector-mediated in vivo gene modification. In terms of clinical translational medicine, this article provides in-depth insights into promising solutions for contemporary challenges confronted in clinical trials, including process development challenges, clinical trial conduct, regulatory approval processes, commercialization and payment systems.…”
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Bidimensional Increment Entropy for Texture Analysis: Theoretical Validation and Application to Colon Cancer Images by Muqaddas Abid, Muhammad Suzuri Hitam, Rozniza Ali, Hamed Azami, Anne Humeau-Heurtier

“…To further validate our results, we employ a support vector machine model, utilizing multiscale entropy values as feature inputs. …”
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Identification of potential shared core biomarkers in type 2 diabetes and sarcopenia by Ping Zhang, Yijun Du, Xing Zhong, Yue Wang, Tianrong Pan

“…Key modules in each condition highlighted 30 shared genes, which were enriched in biological processes and pathways related to metabolic and immune functions. …”
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The Institution of Mediation in the Legislation of the Republic of Kazakhstan: Prospects for Regional Adaptation by N. S. Chimarov, S. Yu. Chimarov

“…Using the example of a legal system integrated into the single social and economic space of the EAEU, but nevertheless differing in content from Russian legislation, to determine a promising vector for the development of the region (and thus the domestic regulatory framework) in matters of mediation.Tasks. …”
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MapReduce based big data framework using associative Kruskal poly Kernel classifier for diabetic disease prediction by R. Ramani, S. Edwin Raja, D. Dhinakaran, S. Jagan, G. Prabaharan

“…Recent trendy applications of Artificial Intelligence are Machine Learning (ML) algorithms, which have been extensively utilized for processes like pattern recognition, object classification, effective prediction of disease etc. …”
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Enhanced EEG signal classification in brain computer interfaces using hybrid deep learning models by Abir Das, Saurabh Singh, Jaejeung Kim, Tariq Ahamed Ahanger, Anil Audumbar Pise

“…The BCI architecture processes electroencephalography signals through three critical stages: data pre-processing, feature extraction, and classification. …”
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