Individual differences in discourse management by Derya Çokal, Jason Bishop, Jacopo Torregrossa, Clare Patterson, Martine Grice, Simon Wehrle, Maria Lialiou, Sophie Repp, Heiko Seeliger, Sonja Eisenbeiß, Klaus von Heusinger, Kai Vogeley, Petra B. Schumacher

“…We propose that a model of discourse management is comprised of three primary components that interact synergistically: (i) dynamicity, (ii) predictability, and (iii) meta-representationality. Cognitive functions play a pivotal role in the underlying processes, contributing to the development and unfolding of discourse. …”
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Artificial intelligence-assisted nursing interventions in psychiatry for oral cancer patients: A concise narrative review by Abdulmalik Fareeq Saber, Sirwan Khalid Ahmed, Safin Hussein, Karzan Qurbani

“…AI-driven tools, such as predictive models, natural language processing, and mobile applications, provide novel means of early disease detection, risk assessment, personalized care planning, and real-time patient support. …”
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Exploring the potential of AI-driven food waste management strategies used in the hospitality industry for application in household settings by Quintana M. Clark, Disha Basavaraja Kanavikar, Jason Clark, Patrick J. Donnelly

“…The hospitality industry, particularly hotels and restaurants, has implemented AI technologies through companies like Leanpath, Winnow, and Kitro, which use real-time data and predictive analytics to monitor, categorize, and reduce food waste. …”
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Mathematical Modeling and Analysis of Wear Behavior of AlTiN Coating on Titanium Alloy (Ti-6Al-4V) by P. Sivaprakasam, A. Kirubel, G. Elias, P. Maheandera Prabu, P. Balasubramani

“…The present work attempts to carry out empirical modeling to predict output response on WML and COF. Desirability-based optimization technique was employed to obtain minimum WML and COF. …”
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The L-shaped association between body roundness index and all-cause mortality in osteoporotic patients: a cohort study based on NHANES data by Ziyao Ding, Ziyao Ding, Ziyao Ding, Wenbo Li, Wenbo Li, Wenbo Li, Haixu Qi, Haixu Qi, Haixu Qi, Tianci Fang, Qirui Zhu, Qirui Zhu, Qirui Zhu, Xinzhe Qu, Xinzhe Qu, Changchang Chen, Jun Sun, Jun Sun, Yong Pang

“…PurposeThis study aims to investigate the relationship between the body roundness index (BRI) and overall mortality rates in individuals with osteoporosis (OP), utilizing information sourced from the NHANES database, in order to assess BRI’s capability as an indicator for predicting mortality risk.MethodsData from NHANES (2005 to 2010, 2013–2014, and 2017–2018) were analyzed, including 1,596 osteoporotic individuals aged 50 and above. …”
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Microarchitecture Parameters Describe Bone Structure and Its Strength Better Than BMD by Tomasz Topoliński, Adam Mazurkiewicz, Stanislaw Jung, Artur Cichański, Krzysztof Nowicki

“…Some papers have shown that bone mineral density (BMD) may not be accurate in predicting fracture risk. Recently microarchitecture parameters have been reported to give information on bone characteristics. …”
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Bridging the gap: aligning physical work capacity testing with actual endurance performance in military settings by Jan Drozd, Jiří Neubauer, Jiří Sekanina, Marek Sedlačík

“…In many armed forces, including the Czech Republic’s, the Physical Working Capacity at a heart rate of 170 beats per minute (PWC 170) test is used to predict performance on the 12-min Cooper run, a widely accepted measure of endurance. …”
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Exploration of novel NSM methods to achieve stronger FRPs with minimal epoxy by Wei Sun, Handong Yan, Jianli Yin, Xinan Zhu, Tiejiong Lou, Haifeng Li

“…The findings were then utilized to calibrate numerical models, which could be directly integrated into equilibrium equations to predict the load-deflection responses for the concrete elements strengthened with NSM methods. …”
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Exploring the role of Energy Communities: A Comprehensive Review by M. Asim Amin, Renato Procopio, Marco Invernizzi, Andrea Bonfiglio, Youwei Jia

“…In contrast, supervised and unsupervised approaches are essential in predicting tasks. Based on the existing knowledge, the present study can conclude that ML-based solution methods are of significant importance for developing an effective energy decentralization platform.…”
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An adjustable acoustic metamaterial cell using a magnetic membrane for tunable resonance by Alicia Gardiner, Roger Domingo-Roca, James F. C. Windmill, Andrew Feeney

“…A functionally superparamagnetic membrane—devised to facilitate the fabrication process by eliminating magnetic poling requirements—is engineered using stereolithography, and its mechanical and acoustic properties are experimentally measured using laser Doppler vibrometry and electret microphone testing, with a mathematical model developed to predict the cell response. It is demonstrated that an adjustable magnetic acoustic metamaterial can be fabricated at ultra-subwavelength dimensions ( $$\le \lambda$$ ≤ λ /77.5), exhibiting adjustable resonance from 88.73 to 86.63 Hz. …”
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Improved Rifamycin B Production by Nocardia mediterranei MTCC 14 under Solid-State Fermentation through Process Optimization by Basavaraj M. Vastrad, Shivayogeshwar E. Neelagund, Sudhir R. Iiger, Ajeet M. Godbole, Venkatrao Kulkarni

“…At these optimum production parameters, the maximum yield of rifamycin B obtained experimentally (9.87 g/kgds dry sunflower oil cake) was found to be very close to its predicted value of 10.35 g/kgds dry sunflower oil cake. …”
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Application of a Plug-and-Play Immunogenicity Assay in Cynomolgus Monkey Serum for ADCs at Early Stages of Drug Development by Montserrat Carrasco-Triguero, Helen Davis, Yuda Zhu, Daniel Coleman, Denise Nazzal, Paul Vu, Surinder Kaur

“…Immunogenicity assessment during early stages of nonclinical biotherapeutic development is not always warranted. It is rarely predictive for clinical studies and evidence for the presence of anti-drug antibodies (ADAs) may be inferred from the pharmacokinetic (PK) profile. …”
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A digital twin framework with MobileNetV2 for damage detection in slab structures by Huong Duong Nguyen, Huan Nguyen, Xiaohong Gao

“…There is more than 80% accuracy for predicting the damaged location and its severity. The success of using MobileNetV2 and transfer learning helps to improve the methods further on mobile devices and the potential for more applications. …”
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Relationship between Prolactin Plasma Levels and White Matter Volume in Women with Multiple Sclerosis by L. De Giglio, F. Marinelli, L. Prosperini, G. M. Contessa, F. Gurreri, M. C. Piattella, F. De Angelis, V. T. Barletta, V. Tomassini, P. Pantano, C. Pozzilli

“…Moreover, PRL levels predicted changes in WMV (Beta: 984, p=0.034). Conclusions. …”
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Rapid analysis of temperature fields in electronic enclosures based on the finite difference thermal resistance network method by Xiaoyue Zhang, Yinmo Xie, Bing Liu, Yingze Meng, Kewei Sun, Guangsheng Wu, Jianyu Tan

“…This model can provide a valuable reference for future thermal design and temperature field predictions.…”
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Experimental studies on mix design and properties of ceramic-glass geopolymer mortars using response surface methodology by Meysam Pourabbas Bilondi, Vahideh Ghaffarian, Mahdi Amiri Daluee, Reyhaneh Pakizehrooh, Saeed Hosseini Tazik, Alireza Behzadian, Mojtaba Zaresefat

“…Compressive strengths were measured at 3 and 28 days, and regression models were developed to predict these outcomes. The relationships between compressive strength, flexural strength, and ultrasonic pulse velocity (UPV) were also analyzed. …”
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Error Data Analytics on RSS Range-Based Localization by Shuhui Yang, Zimu Yuan, Wei Li

“…The significance of our discovery has two folds: First, we present a general expression for localization error data analytics, which can explain and predict the accuracy of range-based localization algorithms; second, the further study on the general analytics expression and its minimum can be used to optimize current localization algorithms.…”
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Metasurface-enabled multifunctional single-frequency sensors without external power by Masaya Tashiro, Kosuke Ide, Kosei Asano, Satoshi Ishii, Yuta Sugiura, Akira Uchiyama, Hiroki Wakatsuchi

“…Moreover, we provide a method for predicting physical parameters via the machine learning-based approach of random forest regression. …”
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Decoding the brain-machine interaction for upper limb assistive technologies: advances and challenges by Sutirtha Ghosh, Rohit Kumar Yadav, Sunaina Soni, Shivangi Giri, Shivangi Giri, Suriya Prakash Muthukrishnan, Lalan Kumar, Lalan Kumar, Shubhendu Bhasin, Sitikantha Roy

“…Further, the variability in predictive EEG patterns across individuals necessitates personalized tuning to improve BMI efficiency. …”
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Strength and durability of concrete with bentonite clay and quarry dust by Muhammad Umar, Hui Qian, M. Nasir Ayaz Khan, Muhammad Shahid Siddique, Hamad Almujibah, Ali. E. A. Elshekh, Maaz Osman Bashir, Nikolai Ivanovich Vatin

“…The quadratic model of RSM indicated that a combination of 10.29% bentonite clay, 7.20% quarry dust, and 8.19% fine aggregate replacement yielded the highest strength. Predictive and experimental results demonstrated strong agreement. …”
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