Efficient purification of CrocinI from saffron stigmas using antisolvent precipitation to implications for food technology by Elmira Fotouhi, Fateme Mirzajani, Hassan Rezadoost, Mohammad Hooshyari Ardakani

“…By utilizing antisolvent precipitation, the method offers a cost-effective, straightforward approach for enriching crocins, especially thermally sensitive crocin-I, without the need for complex heating or cooling systems. This method was a straightforward and efficient means of boosting the yield of very pure crocins, offering a scalable and practicable answer to the challenges of saffron extraction and purification.…”
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Multicomponent thiolactone-based ionizable lipid screening platform for efficient and tunable mRNA delivery to the lungs by Álvaro Peña, Juan Heredero, Beatriz Blandín, Elena Mata, Diego De Miguel, Alfonso Toro, Teresa Alejo, Diego Casabona, Alexandre López, Ana Gallego-Lleyda, Esther Pérez-Herrán, Juan Martínez-Oliván, Javier Giménez-Warren

“…Abstract Ionizable lipids are essential components of lipid nanoparticles (LNPs) for efficient mRNA delivery. However, designing them for high protein expression, endosomal escape, and organ targeting is challenging due to complex structure-activity relationships. …”
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Sample-Efficient Multi-Agent DQNs for Scalable Multi-Domain 5G+ Inter-Slice Orchestration by Pavlos Doanis, Thrasyvoulos Spyropoulos

“…For (ii), we explore multi-agent DQN algorithms that can reduce action space complexity by orders of magnitude compared to standard DQN. …”
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COMPLEX ASSESSMENT OF RISK FACTORS FOR PRECISE CHOICE OF REVASCULARIZATION STRATEGY IN ST ELEVATION MYOCARDIAL INFARCTION AND MULTIVESSEL CORONARY DISEASE by R. S. Tarasov, V. I. Ganyukov, E. S. Kagan, O. L. Barbarash, L. S. Barbarash

“…Invention of the model of differentiated strategy selection of revascularization in acute myocardial infarction with ST elevation (STEMI) and multivessel disease (MVD).Material and methods. …”
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High-entropy alloys catalyzing polymeric transformation of water pollutants with remarkably improved electron utilization efficiency by Ziwei Yao, Yidi Chen, Xiaodan Wang, Kunsheng Hu, Shiying Ren, Jinqiang Zhang, Zhao Song, Nanqi Ren, Xiaoguang Duan

“…The unique non-mineralization regime remarkably reduces PMS consumption and achieves a high electron utilization efficiency of up to 213.4%. Further DFT calculations and experimental analysis reveal that Fe and Co in HEA-NPs act as the primary catalytic sites to complex with PMS for activation, while Ni, Cu, and Pd serve as charge mediators to facilitate electron transfer. …”
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Flood risk mapping and performance efficiency evaluation of machine learning algorithms: Best practice in northern Iran by M. Shirmohammadi, M. Shirmohammadi, S. Pirasteh, W. Li, D. Mafi-Gholami

“…For the analysis, we selected a comprehensive set of environmental and geographical parameters influencing flood susceptibility. …”
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Optimizing HVAC&R System Efficiency and Comfort Levels Using Machine Learning-Based Control Methods by Suroor M. Dawood, Raad Z. Homod, Alireza Hatami

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Strain promoted azide alkyne cycloaddition, an efficient surface functionalization strategy for microRNA magnetic separation by Djamila Kechkeche, Sirine El Mousli, Claire Poujouly, Emilie Secret, Vincent Dupuis, Isabelle Le Potier, Marie-Emmanuelle Goriot, Julien Siracusa, Sébastien Banzet, Jean Gamby, Jean-Michel Siaugue

“…Capture of the targeted miRNA by magnetic separation was then studied in buffered model media and in complex biological media. This study showed that MNP allowed magnetically-assisted extraction of target miRNA with good hybridization yields, even in biological media for which the capture capacity was preserved at around 75 %, with rapid kinetics and satisfactory selectivity.…”
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Constrained search space selection based optimization approach for enhanced reduced order approximation of interconnected power system models by Bala Bhaskar Duddeti, Asim Kumar Naskar, V. P. Meena, Jitendra Bahadur, Ibrahim A. Hameed

“…Abstract Metaheuristic search-based optimization strategies have recently emerged to obtain approximated models for interconnected complex power systems. However, these algorithms are frequently criticized for randomly selecting lower and upper search space boundaries and taking longer to simulate. …”
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RLEAFS: Reinforcement Learning-Based Energy Aware Forwarding Strategy for NDN-Based IoT Networks by Naeem Ali Askar, Adib Habbal

“…Our Strategy integrates Q learning algorithm into path selection procedure, focusing on minimizing energy consumption and extending network lifetime while maintaining efficient data delivery. …”
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Developing a hybrid machine learning model for employee turnover prediction: Integrating LightGBM and genetic algorithms by Hojat Talebi, Amid Khatibi Bardsiri, Vahid Khatibi Bardsiri

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Selection Method and Application of Dual-Mode TBM in Composite Strata: A Case Study of Shenzhen Metro Line 14 by Jizheng Huang, Xiaoyue Kang, Gaoyu Ma, Fan Chen, Shimin Wang, Renbin Luo

“…While dual-mode TBM selection requires comprehensive consideration of the combined effects of efficiency, duration, and cost related to the distribution of different strata. …”
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Coupled intelligent prediction model for medium- to long-term runoff based on teleconnection factors selection and spatial-temporal analysis. by Jintao Li, Ping Ai, Chuansheng Xiong, Yanhong Song

“…For instance, the RF-MLPR model achieved a 3.7%-6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R2 value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
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Optimization of Rockburst Grade Prediction Model Based on Multidimensional Feature Selection: Integrated Learning and Index System Correlation Analysis by Jiayang Chen, Xuebin Xie

“…The six-dimensional system in both types of systems can balance the performance and complexity and is the optimal choice for engineering applications. …”
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Integration of the analytic hierarchy process and Monte Carlo feature selection for a spatiotemporal weighting scheme in meteorological drought monitoring by Muhammad Hamza, Rizwan Niaz, Ibrahim Ali H Nafisah, Luca Di Persio, Abdulkareem M. Basheer, Mohammed M. A. Almazah

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Consistency and Stability in Feature Selection for High-Dimensional Microarray Survival Data in Diffuse Large B-Cell Lymphoma Cancer by Kazeem A. Dauda, Rasheed K. Lamidi

“…High-dimensional survival data, such as microarray datasets, present significant challenges in variable selection and model performance due to their complexity and dimensionality. …”
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Lung and Colon Cancer Classification Using Multiscale Deep Features Integration of Compact Convolutional Neural Networks and Feature Selection by Omneya Attallah

“…The experimental results exhibited outstanding performance, attaining 99.8% classification accuracy with cubic SVM classifiers employing merely 50 ANOVA-selected features, exceeding the performance of individual CNNs while markedly diminishing computational complexity. …”
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Efficient Access to New Thienobenzo-1,2,3-Triazolium Salts as Preferred Dual Cholinesterase Inhibitors by Milena Mlakić, Maja Sviben, Ana Ratković, Anamarija Raspudić, Danijela Barić, Ivana Šagud, Zlata Lasić, Ilijana Odak, Irena Škorić

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Enhanced framework for credit card fraud detection using robust feature selection and a stacking ensemble model approach by Rahul Kumar Gupta, Asmaul Hassan, Samir Kumar Majhi, Nikhat Parveen, Abu Taha Zamani, Raju Anitha, Binayak Ojha, Abhinav Kumar Singh, Debendra Muduli

“…With the increase in online payment volumes, conventional fraud detection technologies are increasingly confronted by the complexity of fraudulent strategies that require intelligent and scalable alternatives. …”
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Criteria Analysis for the Selection of a Generative Artificial Intelligence Tool for Academic Research Based on an Improved Group DEMATEL Method by Constanta Zoie Radulescu, Marius Radulescu

“…Generative Artificial Intelligence (GenAI) tools are transforming academic research by significantly enhancing efficiency, accuracy, and productivity. However, selecting the most appropriate GenAI tool requires careful evaluation of multiple, interdependent criteria. …”
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