Sustainable Semicrystalline/Nanocrystalline UiO-66-Type Zr-MOFs as Photodegraders of Rhodamine B by Jemal M. Yassin, Abi M. Taddesse, Manuel Sánchez-Sánchez

“…This suggests an interaction between the photocatalyst and the RhB dye, involving electron injection from RhB and the ability for ligand-to-metal charge transfer (LMCT), which enhances the efficient photocatalytic degradation of RhB. …”
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A Multi-Strategy Improved Horned Lizard Optimization Algorithm and Its Application in Engineering Optimization by Yancang Li, Jinfan Zhang, Zidong Jin, Weitao Qiao

“…These advances establish the computational efficiency and reliability of MSHLOA for engineering problems, providing a general example of an augmented meta-heuristic algorithm that offers a new, more efficient solution to engineering structural optimization problems.…”
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Alignment-free viral sequence classification at scale by Daniel J. van Zyl, Marcel Dunaiski, Houriiyah Tegally, Cheryl Baxter, Tulio de Oliveira, Joicymara S. Xavier, The INFORM Africa research study group

“…Abstract Background The rapid increase in nucleotide sequence data generated by next-generation sequencing (NGS) technologies demands efficient computational tools for sequence comparison. …”
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Low-dose computed tomography image denoising using pixel level non-local self-similarity prior with non-local means for healthcare informatics by Dawa Chyophel Lepcha, Bhawna Goyal, Ayush Dogra, Krunal Vaghela, Ashish Singh, K. S. Ravi Kumar, Durga Prasad Bavirisetti

“…Abstract Low-dose computed tomography (LDCT) has gained considerable attention for its ability to minimize patients’ exposure to radiation thereby reducing the associated cancer risks. …”
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Leveraging large language models to mimic domain expert labeling in unstructured text-based electronic healthcare records in non-english languages by Izzet Turkalp Akbasli, Ahmet Ziya Birbilen, Ozlem Teksam

“…However, the challenge of processing and accurately labeling vast amounts of unstructured data remains a critical bottleneck, necessitating efficient and reliable solutions. This study investigates the ability of domain specific, fine-tuned large language models (LLMs) to classify unstructured EHR texts with typographical errors through named entity recognition tasks, aiming to improve the efficiency and reliability of supervised learning AI models in healthcare. …”
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Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…The framework’s ability to proactively adapt to evolving access patterns while maintaining computational efficiency makes it particularly suitable for large-scale machine learning and scientific computing environments where data placement critically impacts overall system performance.…”
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ANALISIS PENGARUH RASIO KEUANGAN TERHADAP RETURN ON ASSET BANK PERKREDITAN RAKYAT PADA PT. BPR POLIN JAYA by Dedi Mulyadi, Alexander Din

“…The more efficient or small bank operating costs, the profit gained greater 5. …”
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Structure and classification of e-business models by V.О., S.V.

“…The article argues the need to use business models to ensure the sustainable and efficient functioning of modern enterprises. The business model is defined as a simplified representation of the mechanism for carrying out activities. …”
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ANALISIS PENGARUH RASIO KEUANGAN TERHADAP RETURN ON ASSET BANK PERKREDITAN RAKYAT PADA PT. BPR POLIN JAYA by Dedi Mulyadi, Alexander Din

“…The more efficient or small bank operating costs, the profit gained greater 5. …”
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Multivariate Machine Learning Model Based on YOLOv8 for Traffic Flow Prediction in Intelligent Transportation Systems by Fukui Wu, Hanzhong Tan, Linfeng Zhang, Shuangbing Wen, Tao Hu

“…Traffic flow prediction plays a crucial role in Intelligent Transportation Systems (ITS), as it substantially enhances traffic management efficiency, alleviates congestion, and improves road safety. …”
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Arrears behavior prediction of power users based on BP neural network and multi-scale feature learning: a refined risk assessment framework by Liang Yu, Yuanshen Hong, Hua Lin, Xu Jiang, Ziming Song

“…The study concludes that the effective fusion of multi-scale features not only enhances the model’s prediction performance but also strengthens its generalization ability. This method provides an advanced risk management tool for power companies, helping to increase the operational efficiency of smart grids and encouraging further research toward greater intelligence in the field.…”
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The Essence and Content of Product Distribution as an Economic Category by Viktoriia Bozhkova, Mykhailo Bilukha

“…Effective distribution not only optimizes distribution processes but also enhances the efficiency of management decisions, which helps to reduce costs and increase profitability. …”
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Solving the Black–Scholes European options model using the reduced differential transform method with powered modified log-payoff function by S.E. Fadugba, A.M. Udoye, S.C. Zelibe, S.O. Edeki, C. Achudume, A.A. Adeyanju, O. Makinde, P.A. Bankole, M.C. Kekana

“…The main motivation for this study stems from the need to develop more efficient and accurate analytical techniques for option pricing, particularly under the assumptions of the Black–Scholes framework. …”
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MDEU-Net: Medical Image Segmentation Network Based on Multi-Head Multi-Scale Cross-Axis by Shengxian Yan, Yuyang Lei, Jing Zhang, Xiao Gao, Xiang Li, Penghui Wang, Hui Cao

“…Additionally, a gated attention mechanism facilitates efficient feature fusion by selectively emphasizing key features rather than relying on simple concatenation and improves the model’s ability to capture critical details at multiple scales. …”
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Robust Predictive Current Control Using Luenberger Observer Applied to an Induction Motor for Agricultural Electrical Traction by Gabriel Caramori, Igor Oliani, Angelo S. Lunardi, Alfeu J. Sguarezi Filho

“…In agricultural electrical traction systems, they are crucial for providing reliable, efficient, and high-torque performance. Their ability to deliver consistent power at varying speeds and loads makes them ideal for such applications, where robust and low-maintenance solutions are essential for operational efficiency. …”
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Dense dynamic convolutional network for Bel canto vocal technique assessment by Zhenyi Hou, Xu Zhao, Shanggerile Jiang, Daijun Luo, Xinyu Sheng, Kaili Geng, Kejie Ye, Jiajing Xia, Yitao Zhang, Chenxi Ban, Jiaxing Chen, Yan Zou, Yuchao Feng, Xin Yuan, Guangyu Fan

“…Additionally, we employ densely connected layers to optimize the framework, enabling efficient utilization of multi-scale features across multiple dynamic convolution layers. …”
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Optimizing Virtual Power Plants with Parallel Simulated Annealing on High-Performance Computing by Ali Abbasi, Filipe Alves, Rui A. Ribeiro, João L. Sobral, Ricardo Rodrigues

“…Rigorous simulations highlight the method’s ability to reduce optimization time, maintain solution quality, and scale efficiently, facilitating real-time decision making in energy markets. …”
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Machine learning techniques in monitoring and controlling friction stir welding process: a critical review by Bhardwaj Kulkarni, Saurabh Tayde, Yashwant Chapke, Swapnil Vyavahare, Avinash Badadhe

“…Abstract The friction stir welding (FSW) technique is a solid-state joining method that presents numerous advantages compared to conventional welding techniques, including enhanced mechanical joint efficiency and the ability to join challenging materials such as aluminium and magnesium. …”
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Semantic enhancement and change consistency network for semantic change detection in remote sensing images by Zhenghao Jiang, Biao Wang, Peng Zhang, Yanlan Wu, Zhiyuan Ye, Hui Yang

“…By enhancing the model's ability to extract semantic information from complex land-cover classes, we incorporate multi-scale adaptive modules, leveraging the efficient zero-shot capability of SAM2. …”
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Directional Liquid Transport on Biomimetic Surface with Wedge-Shaped Pattern: Mechanism, Construction, and Applications by Qing’an Meng, Junjie Zhou, Jie Pang, Luofeng Wang, Kaicheng Yang, Zhangcan Li, Jiayu Xie

“…The focus on DLT is motivated by its ability to inspire efficient, energy-independent liquid transport technologies, which hold significant promise for both fundamental research and practical applications. …”
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