Integration of Carbon Nanotubes into Manganese Dioxide Nanorods for Enhanced Enzymeless Electrochemical Glucose Sensing with High Sensitivity and Selectivity by Khawtar Hasan Ahmed, Alonso Moreno Zuria, Mohamed Mohamedi

“…These factors enable more efficient, scalable, and durable sensors with better sensitivity, stability, and affordability for real-time glucose monitoring. …”
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Crayfish optimization based pixel selection using block scrambling based encryption for secure cloud computing environment by Vikas K. Soman, V. Natarajan

“…The Crayfish Optimization algorithm is used to select the most suitable pixels for steganography, ensuring that the secret image is embedded in a way that minimizes detection. …”
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SCM-DL: Split-Combine-Merge Deep Learning Model Integrated With Feature Selection in Sports for Talent Identification by Didem Abidin, Muhammed G. Erdem

“…The SCM-DL integrated with the RFE_DTC feature selection method achieved the highest performance for six features, yielding an accuracy rate of 97.40% and a Matthews Correlation Coefficient performance rate of 96.6%. …”
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A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping by Radhwan A. Saleh, Ahmed M. Al-Areeq, Amran A. Al Aghbari, Mustafa Ghaleb, Mohammed Benaafi, Nabil M. Al‑Areeq, Baqer M. Al-Ramadan

“…Then, the Memo Search Algorithm (MSA), a metaheuristic approach is proposed to efficiently reduce feature space. Through comprehensive comparisons with established algorithms such as the Artificial Bee Colony (ABC) and Gray Wolf Optimizer (GWO), MSA refined the selection, identifying 'elevation’ and 'distance to streams’ as optimal factors. …”
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Identifying the Challenges of the Processes of Introducing and Commercializing Domestic Medical Equipment to the Market by Shahnaz Seyedi Dolatabad, Hessam Zandhessami, Hamed Afshari, Shirin Jalalinia

“…Conclusion: The research results showed that the process faces major challenges such as complexity of implementation steps, time-consuming nature, high costs, lack of transparency, and lack of coordination between regulatory agencies. …”
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An Effective and Interpretable Sleep Stage Classification Approach Using Multi-Domain Electroencephalogram and Electrooculogram Features by Xin Xu, Bei Zhang, Tingting Xu, Junyi Tang

“…Recent research efforts on automated sleep staging have focused on complex deep learning architectures that have achieved modest improvements in classification accuracy but have limited real-world applicability due to the complexity of model training and deployment and a lack of interpretability. …”
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Enhancing credit card fraud detection: highly imbalanced data case by Dalia Breskuvienė, Gintautas Dzemyda

“…It has been specifically designed to efficiently process and analyze vast and complex datasets commonly encountered in the financial sector, showcasing adaptability to the dynamic nature of big data environments. …”
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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

“…However, creating diversity, selecting genotypes, and studying different traits will help scientists in this direction. …”
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TCR-engaging scaffolds selectively expand antigen-specific T-cells with a favorable phenotype for adoptive cell therapy by Marco Donia, Özcan Met, Julie Westerlin Kjeldsen, Sine Reker Hadrup, Inge Marie Svane, Arianna Draghi, Anders Handrup Kverneland, Christina Heeke, Siri Amanda Tvingsholm, Marcus Svensson Frej, Vibeke Mindahl Rafa, Ulla Kring Hansen, Maria Ormhøj, Alexander Tyron, Agnete W P Jensen, Mohammad Kadivar, Amalie Kai Bentzen, Kamilla K Munk, Gitte N Aasbjerg, Jeppe S H Ternander, Tripti Tamhane, Christian Schmess, Samuel A. Funt, Søren Nyboe Jakobsen

“…The resulting T-cell products were assessed for phenotypic and functional characteristics.Results We identified an optimal Ag-scaffold for expansion of T-cells for ACT, carrying pMHC and interleukin-2 (IL-2) and IL-21, with which we efficiently expanded both virus-specific and tumor-specific CD8+ T cells from peripheral blood of healthy donors and patients, respectively. …”
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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

“…However, most EEG-based machine learning diagnostic studies focus on boosting classification accuracy through complex algorithms and small, homogenous datasets. …”
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Balancing cleaner energy and geopolitical interests in the complex transition of the European electricity mix: from Fukushima to the Ukraine war by Marcio Cataldi, Nieves Espinosa, Sonia Jerez, Juan Pedro Montávez, Larissa Haringer Martins Da Silveira, Jairton Dupont, Marcos Alexandre Teixeira

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PROBLEMS OF FORMATION OF FINANCIAL-INVESTMENT PROJECTION OF A BALANCED SCORECARD IN VALUE-BASED ENTERPRISES OF MINING-METALLURGICAL COMPLEX by S. Faizova, M. Ivanova, S. Sannikova, O. Varyanichenko

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AutoML based workflow for design of experiments (DOE) selection and benchmarking data acquisition strategies with simulation models by Xukuan Xu, Donghui Li, Jinghou Bi, Michael Moeckel

“…Results obtained from electrical circuit models with varying complexity show that not all AL sampling strategies outperform conventional DOE strategies, depending on the available data volume, the complexity of the dataset, and data uncertainties. …”
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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

“…The concept of explainable artificial intelligence was adopted by incorporating permutation feature importance ranking and Shapley Additive explanations values to identify the feature set that optimized a model's performance while reducing computational complexity. The proposed explainable artificial intelligence feature selection method was compared to conventional feature selection techniques, including mutual information, chi-square coefficient, maximal information coefficient, Fisher separation criterion and variance thresholding. …”
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Minimum Critical Test Scenario Set Selection for Autonomous Vehicles Prior to First Deployment and Public Road Testing by Balint Toth, Zsolt Szalay

“…By addressing the need for a structured and efficient scenario selection method, this work supports the advancement of systematic safety assurance for autonomous vehicles and provides a scalable solution for authorities and vehicle testing companies.…”
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Dynamic response and discrimination of gaseous sarin using a boron‐difluoride complex film‐based fluorescence sensor by Zhijie Zhou, Lei Zhang, Lingya Peng, Yingjie Li, Xiaolin Zhu, Yidi Wu, Zebiao Qiu, Gang He, Molin Qin, Haonan Peng, Yu Fang

“…Abstract This study presents a novel boron‐difluoride complex‐based fluorescent nanofilm sensor capable of detecting sarin vapors in the environment by reporting an output fluorescence signal. …”
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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

“…Early detection is paramount as it significantly improves survival rates and reduces the complexity and cost of treatment. Machine learning has revolutionized this field, providing more precise, efficient, and personalized diagnostic methods. …”
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THE PROBLEM OF PATIENT-FOCUSED INNOVATION OF TOOTH-TECHNICAL MATERIALS SCIENCE IN THE CONTEXT OF INCREASING THE EFFICIENCY OF THE DENTAL TREATMENT by І.V. Yanіshen, O. L. Fedotov

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BlueRecording: A pipeline for the efficient calculation of extracellular recordings in large-scale neural circuit models. by Joseph James Tharayil, Jorge Blanco Alonso, Silvia Farcito, Bryn Lloyd, Armando Romani, Elvis Boci, Antonino Cassara, Felix Schürmann, Esra Neufeld, Niels Kuster, Michael Reimann

“…As the size and complexity of network simulations accessible to computational neuroscience grows, new avenues open for research into extracellularly recorded electric signals. …”
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Optimizing precision farming: enhancing machine learning efficiency with robust regression techniques in high-dimensional data by Nour Hamad Abu Afouna, Majid Khan Majahar Ali

“…To overcome these obstacles, reducing retraining time and resolving the complexity issue is essential for improving the machine learning algorithm’s performance, scalability, and efficiency, especially when dealing with large or high-dimensional datasets. …”
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