Leveraging RAG With Transformer for Context-Based Personalized Recommendations by Faten S. Alamri, Amjad Rehman, Bayan Alghofaily, Adeel Ahmed, Khalid Saleem

“…When LLMs are trained on sparse data or lack historical information, their performance in recommendation systems can be negatively impacted. Furthermore, inference with LLMs tends to be slow due to autoregressive generation, which limits the efficiency of traditional recommendation methods. …”
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Ultrasonic welding of thermoplastic composites with woven mesh energy directors: Enhanced strength and hygrothermal resistance by Dongsheng Yue, Guoqun Zhao, Jiaying Pan, Jiaming Liu, Dong Quan

“…In ultrasonic welding of thermoplastic composites, energy directors (EDs) based on thermoplastic films often exhibit low heat generation efficiency and uneven temperature distribution at the welding interface, which negatively affect weld quality and joint strength. …”
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Comprehensive Performance Analysis for the Rotating Detonation-Based Turboshaft Engine by Zifei Ji, Ruize Duan, Renshuai Zhang, Huiqiang Zhang, Bing Wang

“…The critical compressor pressure ratio corresponding to the disappearance of specific power improvement is higher than that corresponding to the disappearance of thermal efficiency and specific fuel consumption. These critical compressor pressure ratios are positively correlated with flight altitude and negatively correlated with flight velocity. …”
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Automatic mouse ultrasound detector (A-MUD): A new tool for processing rodent vocalizations. by Sarah M Zala, Doris Reitschmidt, Anton Noll, Peter Balazs, Dustin J Penn

“…A-MUD had lower error rates than the commercial software, as it detected significantly more correct positives, and fewer false positives and false negatives. The errors generated by A-MUD were mainly false negatives, rather than false positives. …”
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IT Professionals Versus the Public: Who’s More Optimistic About AI’s Future Impacts? by Ngo Thaiduong

“…Furthermore, ITP views remain relatively stable over time compared to the public’s increasing negativity toward AI. The analysis also highlights ITPs’ stronger focus on AI-driven efficiency gains alongside a more nuanced awareness of AI’s inherent shortcomings. …”
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Reconstructing Road Roughness Profiles Using ANNs and Dynamic Vehicle Accelerations by Kais Douier, Jamil Renno, Mohammed F. M. Hussein

“…This deterioration leads to discomfort for road users as well as the generation of noise and vibrations, which negatively impact nearby structures. …”
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Advancing sustainability in EDM: A brief review of eco-friendly dielectric fluids by Abhijit Bhowmik, Raman Kumar, Ranganathaswamy M. K, Y. Karun Kumar, Parveen Kumar, Pardeep Singh Bains, Raed Hameed Alfilh, Abinash Mahapatro, Deepak Gupta, A. Johnson Santhosh

“…In EDM, material removal occurs as a result of intense heat generated by the movement of electrons from the negatively charged cathode to the positively charged anode. …”
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Optimal Dispatch of Power Grids Considering Carbon Trading and Green Certificate Trading by Xin Shen, Xuncheng Zhu, Yuan Yuan, Zhao Luo, Xiaoshun Zhang, Yuqin Liu

“…By building a deterministic optimization model, the goal of maximizing power generation profit and minimizing carbon emissions is combined in a weighted form, and the power balance, carbon quota constraint, and the proportion of renewable energy are introduced. …”
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Are Accrual Earnings Management and Real Earnings Management Related to Total Risk and Idiosyncratic Risk? by Rohmat Kunto Wijoyo, Amrie Firmansyah

“…This study suggests that accrual earnings management is negatively associated with total and idiosyncratic risk, but real earnings management is positively associated with total and idiosyncratic risk. …”
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Managing Arsenic Pollution from Soil–Plant Systems: Insights into the Role of Biochar by Qitao Su, Zhixuan Du, Xinyi Huang, Muhammad Umair Hassan, Faizah Amer Altihani

“…Biochar (BC) is a very effective amendment to remediate polluted soils and it received great attention owing to its appreciable results. Arsenic toxicity negatively affects plant morph-physiological and biochemical functioning and upsurges the generation of reactive oxygen species (ROS), which negatively affect cellular structures. …”
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PLZero: placeholder based approach to generalized zero-shot learning for multi-label recognition in chest radiographs by Chengrong Yang, Qiwen Jin, Fei Du, Jing Guo, Yujue Zhou

“…Secondly, we propose a hallucinated class generation module (HCG), which generates hallucinated classes by feature diffusion and feature fusion based on the visual and semantic features of seen classes, using these hallucinated classes as placeholders for unseen classes. …”
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Single-Shot Readout and Weak Measurement of a Tin-Vacancy Qubit in Diamond by Eric I. Rosenthal, Souvik Biswas, Giovanni Scuri, Hope Lee, Abigail J. Stein, Hannah C. Kleidermacher, Jakob Grzesik, Alison E. Rugar, Shahriar Aghaeimeibodi, Daniel Riedel, Michael Titze, Edward S. Bielejec, Joonhee Choi, Christopher P. Anderson, Jelena Vučković

“…The negatively charged tin-vacancy center in diamond (SnV^{-}) is an emerging platform for building the next generation of long-distance quantum networks. …”
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The Capacity Configuration of a Cascade Small Hydropower-Pumped Storage–Wind–PV Complementary System by Bin Li, Shaodong Lu, Jianing Zhao, Peijie Li

“…The results demonstrate that the proposed method reduces system energy deviation, improves the stability of power output and generation efficiency, and enhances the operational stability and economic performance of the system.…”
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Machine-Learning-Based Optimal Feed Rate Determination in Machining: Integrating GA-Calibrated Cutting Force Modeling and Vibration Analysis by Yu-Peng Yeh, Han-Hao Tsai, Jen-Yuan Chang

“…Machining efficiency and stability are crucial for achieving high-quality manufacturing outcomes. …”
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From invention to progress: Energy technology innovation and sustainable development in OECD economies. by Khatib Ahmad Khan, Waheed Ahmad, Azeem Oluwaseyi Zubair, Mohammad Subhan, Muhammad Ibrahim Shah

“…The OECD is one such region where aggressive funding towards equipment with high energy efficiency and the advancement of technologies for producing and consuming renewable energy are provided to advance towards sustainable development. …”
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The Role of Bioenergy in Transition to a Sustainable Bioeconomy – Study on EU Countries by Ştefan Dragoş Cîrstea, Andreea Cîrstea, Irimie Emil Popa, Gabriel Radu

“…At the same time, bioenergy positively correlates with the degree of innovation in the field or with the energy from natural gas and negatively with the economic efficiency of a state. …”
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Tradeoffs and synergies between social equity and environmental benefits in conservation by Thomas M. Neeson, Sean C. Emmons, Lauren E. Mullenbach

“…We used empirical patterns in the commonness and rarity of species to generate simulated landscapes with pre-defined correlations between biological diversity and human social diversity. …”
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Unassisted Switchable Dual‐Photoelectrode Devices Utilizing p‐n Carbon Quantum Dots as “Semiconductor Electrolytes”: Optimization Between H2O2 and Solar Electricity Production... by Hui‐Min Duan, Chen‐Guang Li, Liu‐Meng Mo, Jing‐Shuang Dang, Xiao‐Hui Jia, Jia‐Cheng Yu, Yu‐Hang Mei, Anders Thapper, Hong‐Yan Wang

“…Abstract Switchable self‐driven photoelectrochemical (PEC) devices are developed to boost H2O2 or electricity generation under visible‐light illumination, in which p‐n type carbon quantum dots (N‐CQDs) is applied as conceptually‐new “semiconductor electrolytes”. …”
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Effects of Prenatal Herbal Methionine Supplementation on Growth Indices, Onset of Puberty, Blood Metabolites, and Fertility of Alpine Doelings by Venancio Cuevas-Reyes, Jorge Flores-Sánchez, Esau Ramírez de la Cruz, Juan M. Vázquez-García, Luisa E. S. Hernández-Arteaga, Reagan Sims, Jaime M. Cavazos-Galindo, Miguel Mellado, César A. Rosales-Nieto

“…This study investigated the effects of prenatal herbal methionine supplementation on growth, puberty onset, reproductive efficiency, and blood metabolites in first-generation G1 Alpine doelings. …”
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A Physics-Guided Bayesian Neural Network for Sensor Fault Detection in Wind Turbines by MD Azam Khan, Arifur Rahman, Farhad Uddin Mahmud, Kanchon Kumar Bishnu, Hadiur Rahman Nabil, M. F. Mridha, Md. Jakir Hossen

“…Predictive maintenance is essential for ensuring the reliability and efficiency of wind energy systems. Traditional deep learning models for sensor fault detection rely solely on data-driven patterns, often lacking interpretability and robustness. …”
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