Optimizing T cell transduction: a novel transduction device for efficient and scalable gene delivery by Kang-Zheng Lee, Tan Dai Nguyen, Dan Liu

“…Results TransB demonstrated up to 1-fold decrease in processing time, 3-fold reduction in viral vector consumption, and 0.7-fold increase in transduction efficiency compared to 24—well plate method for donor T cell transduction in studies evaluating its impact on transduction process. …”
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Development of an Optimal Machine Learning Model to Predict CO₂ Emissions at the Building Demolition Stage by Gi-Wook Cha, Choon-Wook Park

“…It enables efficient data collection and processing and provides scalability for various analytical approaches compared to the existing life cycle assessment (LCA) approach. …”
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Travel Time Prediction in a Multimodal Freight Transport Relation Using Machine Learning Algorithms by Nikolaos Servos, Xiaodi Liu, Michael Teucke, Michael Freitag

“…We apply the ML algorithms extremely randomized trees (ExtraTrees), adaptive boosting (AdaBoost), and support vector regression (SVR) to this problem because of their ability to deal with low data volumes and their low processing times. …”
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Transformer-based ensemble model for dialectal Arabic sentiment classification by Omar Mansour, Eman Aboelela, Remon Talaat, Mahmoud Bustami

“…Sentiment analysis is crucial for assessing public sentiment toward specific issues; however, applying it to dialectal Arabic presents considerable challenges in natural language processing. The complexity arises from the language’s intricate semantic and morphological structures, along with the existence of multiple dialects. …”
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Design of an Efficient Model for Psychological Disease Analysis and Prediction Using Machine Learning and Genomic Data Samples by Alparthi Kumuda, Saroj Kumar Panigrahy

“…The two central components of the PDMLG model include the Genomic Fusion Model, which uses ensemble learning techniques like Random Forest, Gradient Boosting, and Neural Networks, and Deep Learning Model of Convolutional and Recurrent Neural Networks in processing genomic sequence data samples. …”
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An Integrated Strategy for Interpretable Fault Diagnosis of UAV EHA DC Drive Circuits Under Early Fault and Imbalanced Data Conditions by Yang Li, Zhen Jia, Jie Liu, Kai Wang, Peng Zhao, Xin Liu, Zhenbao Liu

“…The optimal weak learner selection for the high-performance boosting integrated learner is identified through comparative validation. …”
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Evaluating sentiment analysis models: A comparative analysis of vaccination tweets during the COVID-19 phase leveraging DistilBERT for enhanced insights by Renuka Agrawal, Mehuli Majumder, Ishita Yadav, Nandini Taneja, Safa Hamdare, Preeti Hemnani

“…This study investigates public sentiment toward COVID-19 vaccinations by analyzing Twitter data using advanced machine learning (ML) and natural language processing (NLP) techniques. Recognizing social media as a valuable source for gauging public opinion during health crises, the research aims to inform policies on content moderation and misinformation control. • Comparative Analysis of Embedding Techniques and ML Models: The study evaluates two embedding techniques—TF-IDF and Word2Vec—across five ML models: LinearSVC, Random Forest, Gradient Boosting Machine (GBM), XGBoost, and AdaBoost. • The models were tested using two training-testing splits (70–30 and 80–20) to assess their performance on noisy, unlabeled, and imbalanced sentiment data. • Utilization of DistilBERT for Pseudo-Labeling: To enhance labeling accuracy, DistilBERT was employed for pseudo-labeling, capturing semantic nuances often missed by traditional ML techniques. …”
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The crosstalk between dendritic cells, cytokine-induced killer cells and cancer cells from the perspective of combination therapy by Assel Issabekova, Marzhan Zhumabekova, Madina Zhunussova, Vyacheslav Ogay

“…DCs integrate multiple environmental signals by efficiently processing tumour-associated antigens (TAAs) and migrating to draining lymph nodes (dLNs), where they present foreign antigens to T cells for priming. …”
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A Content Dissemination Technique Based on Priority to Improve Quality of Service of Vehicular Ad Hoc Networks by Muhammad Ayaz, Jawaid Iqbal, Muhammad Adnan, Saddam S. Hussain, Amerah Alabrah, Noor Ul Amin, Suheer Al-Hadhrami, Sk. Md. Mizanur Rahman

“…Therefore, in this paper, we propose a content dissemination technique based on priority for boosting the service requirements of NDN-based cloud and mobile IoT nodes in the VANETs. …”
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Nanoscale Strain Mapping in SIMOX 3-D Sculpted Silicon Waveguides Using Tip-Enhanced Raman Spectroscopy by Huashun Wen, Yuefeng Ji, Bahram Jalali

“…Strain in silicon plays a significant role in exploring electro-optical material, boosting transistor performance, tuning birefringence of optical silicon waveguides, and so on. …”
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Advancements in Poly(ionic liquid) composites with carbon nanomaterials by Hui Li, Jie Gao, Zhiyong Li, Yan Zhang, Jun Zhang, Shiguo Zhang

“…A thorough understanding of the physical and chemical properties of PILs is crucial for tailoring composite materials to specific applications, enhancing processing capabilities, and boosting performance. This article reviews recent advancements in PIL composites incorporating carbon nanomaterials and outlines future challenges in their development.…”
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Predicting adverse drug reactions in oncology: A critical review of machine learning approaches and future directions by Abid Yahya, Phatsimo Lobelo, Afiya Eram, Sana Althaf Hussain, Irfan Anjum Badruddin, Lory Liza D. Bulay-og, Dionel O. Albina

“…We go over a variety of methods for utilizing both structured and unstructured clinical data, such as supervised, unsupervised, and deep learning models in addition to natural language processing (NLP) strategies. Strong performance has been demonstrated by ensemble techniques like Random Forest and Gradient Boosting, while deep neural networks allow for sophisticated feature extraction, albeit with interpretability issues. …”
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Examining the Influence of Website Quality on Citizen’s E-Loyalty in Domestic Tourism in Jordan: The Role of E-Trust and E-Satisfaction by Nour Qatawneh, Raghed Alkhasawneh, Abraham Althonayan, Abeer Altarawneh

“…The survey questionnaire was adopted as a main strategy to collect and analyze primary data and to investigate the relationships between variables. Statistical processing was applied using IBM SPSS version 22 package and Amos version 25 for path analysis as the main statistical software package. …”
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Eco-friendly green synthesised nano iron particles from weed leaf extract: a potential nutritional source for enhancing the germination and yield of aerobic rice by Akshay Kumar Kurdekar, Jayadeva H. Marulappa, Manjanagouda S. Sannagoudar, Kamala Bai Suresh, Sathish Ayyappa, Viresh Kumargoud, Vinay Kumar Manjunath, Eman A. Mahmoud, Hosam O. Elansary

“…Further synthesised nanoiron was used as a seed priming and folair application for boosting the germination of aerobic rice.…”
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The Influence of Oil Types and Their Flow Rates on the Flow Corrosion Risk of REAC Systems by Huayu WEN, Yejiang HONG, Rui LI, Xiaofei LIU

“…To mitigate corrosion risks, it is recommended to moderately increase the VGO content during crude oil processing while simultaneously boosting either the diesel content or injection water volume.…”
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An Autonomous Drone for Avalanche Search and Rescue: Integrating ArduPilot and Tracking-Beacon Detection by Jedrzej Stasik, Tomasz Szandala

“…By bridging advanced aerial robotics with practical rescue operations, this study delivers a vital technological advancement, significantly boosting the effectiveness and safety of mountain rescue missions. …”
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Calculation of hydrogen dispersion in cushion gases using machine learning by Ali Akbari, Mehdi Maleki, Yousef Kazemzadeh, Ali Ranjbar

“…Existing experimental and numerical methods for predicting hydrogen dispersion coefficients (KL) are often limited by high costs, lengthy processing times, and insufficient accuracy in dynamic reservoir conditions. …”
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Modeling methylene blue removal using magnetic chitosan carboxymethyl cellulose multiwalled carbon nanotube composite with genetic algorithms and regression techniques by Mahmood Yousefi, Saeid Fallahizadeh, Yosra Maleki, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…Genetic Algorithm and other statistically advanced techniques such as Gradient Boosting Regressor, and Maximum Likelihood Estimation were used to extract the necessary process parameters and the factors that posed a major impact on the adsorption efficiency. …”
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Radiomics-based machine learning for automated detection of Pneumothorax in CT scans. by Hanieh Alimiri Dehbaghi, Karim Khoshgard, Hamid Sharini, Samira Jafari Khairabadi, Farhad Naleini

“…The used machine learning algorithms are Gradient Tree Boosting (GBM), eXtreme Gradient Boosting (XGBoost), and Light GBM. …”
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Credit Scoring on Cash Flow Table with Machine Learning: XGBoost Approach by Güner Altan, Server Demirci

“…In this context, banks put companies through a credit evaluation process before loaning to them, and the most important leg of this process is undoubtedly the credit score analysis. …”
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