Innovative Damage Assessment of Endodontic Instruments Based on Digital Image Stacking by Raúl Argüello-Sánchez, Ivette Alejandra Calderón-Alday, Antonio Hernández-Morales, Benjamín Gonzalo Rodríguez-Méndez, Diego Medina-Castro, Régulo López-Callejas, Carlo Eduardo Medina-Solís

“…Conventional scanning electron microscopy (SEM) has been the gold standard for this purpose; however, its limited accessibility and complex sample preparation protocols hinder its routine use in clinical settings. …”
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Parameter sensitivity analysis for diesel spray penetration prediction based on GA-BP neural network by Yifei Zhang, Gengxin Zhang, Dawei Wu, Qian Wang, Ebrahim Nadimi, Penghua Shi, Hongming Xu

“…The GA-BP neural network was selected for its ability to optimize neural network weights and thresholds, thereby improving model convergence and avoiding local minima, which are common challenges in complex, non-linear problems such as spray prediction. …”
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Phenothiazine-Based Nanoaggregates: Dual Role in Bioimaging and Stem Cell-Driven Photodynamic Therapy by Eleonora Calzoni, Alessio Cesaretti, Nicolò Montegiove, Maria Luisa Valicenti, Francesco Morena, Rajneesh Misra, Benedetta Carlotti, Sabata Martino

“…However, a significant obstacle for PDT is the need to selectively deliver photosensitizers to disease sites while minimizing systemic side effects. …”
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Experimental and Numerical Study on Flow and Heat Transfer Characteristics of Additively Manufactured Triply Periodic Minimal Surface (TPMS) Heat Exchangers for Micro Gas Turbine by Xiyuan Su, Yueliang Zhang, Yu Rao, Kirttayoth Yeranee, Xintong Wang

“…This paper proposes two compact, efficient, and lightweight heat exchangers based on triply periodic minimal surfaces (TPMSs). …”
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Advanced evaluation of performance of machine learning models for soapstock splitting optimisation under uncertainty by Bartosz Szeląg, Krzysztof Barbusiński, Michał Stachura, Przemysław Kowal, Adam Kiczko, Eldon R. Rene

“…The objective was to evaluate and select the modeling approaches based on (i) data availability, (ii) model complexity, (iii) predictive accuracy, and (iv) sensitivity to input uncertainty. …”
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A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images by Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza, Jamel Baili, Dina Abdulaziz AlHammadi, Hee-Chan Cho, Byoungchol Chang

“…Future work will explore its adaptability to additional datasets and optimize its computational complexity for broader deployment.…”
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Sustainable planning of solar plants: bibliometry and integration of GIS-multicriteria methods by Gustavo Leite Gonçalves, Lucia Maria de Araujo Lima Gaudencio, Rui de Oliveira, Ruth Silveira do Nascimento

“…In summary, the examined methodological model proves effective for selecting locations for solar plant installation and operation sustainably and efficiently. …”
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Navigating challenges in pediatric trial conduct: integrating bayesian sequential design with semiparametric elicitation for handling primary and secondary endpoints by Danila Azzolina, Ileana Baldi, Silvia Bressan, Mohd Rashid Khan, Liviana Da Dalt, Dario Gregori, Paola Berchialla

“…The study focuses on efficiently handling primary and secondary endpoints, a critical aspect often overlooked in pediatric trials. …”
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Anchored atomic Ru-O4 architecture enables ultra-effective Fe(VI) activation via avoiding Fe(VI) self-decay for water purification by Yundan Chen, Xiaofei Ge, Jun Li, Zishuai Bill Zhang, Zhenshan Li

“…Compared with other typical transition metal single-atom catalysts, RuGN exhibits moderate interactions with Fe(VI) and thus facilitates the electron transfer via Ru-O-Fe coordination to activate Fe(VI) for efficient CIP degradation. The RuGN/Fe(VI) system resists interference from background substances coexisting in water, achieving efficient CIP degradation under complex water chemistry conditions and in real water samples. …”
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IoT-Edge Hybrid Architecture with Cross-Modal Transformer and Federated Manifold Learning for Safety-Critical Gesture Control in Adaptive Mobility Platforms by Xinmin Jin, Jian Teng, Jiaji Chen

“…The system maintains industrial-grade safety certification with energy-efficient computation. Bridging adaptive mechanics with edge intelligence, this research pioneers a sustainable IoT-edge paradigm for smart mobility, harmonizing real-time responsiveness, ecological sustainability, and scalable deployment in complex urban ecosystems.…”
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Construction of intelligent gymnastics teaching model based on neural network and artificial intelligence by Guanxi Fan, Yu Wang, Tongling Wang, Dapeng Yang

“…The study offers strong technical support for the intelligent development of gymnastics education. By automatically detecting and analyzing movements, the model can deliver real-time feedback to both teachers and students, helping learners master skills more efficiently and improve performance.…”
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Multi-layer robotic controller for enhancing the safety of mobile robot navigation in human-centered indoor environments by Karameldeen Omer, Karameldeen Omer, Andrea Monteriù

“…The “online” control layer integrates a human-in-the-loop strategy, where the human operator detects missing obstacles or approaching danger through a user interface and sends a trigger to the robot’s controller. …”
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CFTformer: End-to-End Cross-Frame Multi-Object Tracking With Transformer by Abdollah Amirkhani, Seyed Alireza Khoshnevis

“…Traditional MOT methods typically rely on motion-based and appearance-based similarity information to associate detections across frames. However, the new transformer attention-based approach to MOT has removed the need for complex post-processing steps, such as graph optimization, allowing for end-to-end query tracking across frames. …”
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Frequency of dyspnea related to intake of ticagrelor or clopidogrel in patients with chronic coronary syndrome undergoing coronary intervention by Dunya Habeeb Shnain, Ghassan Mohammed Mahmood, Sara Omar Ahmed

“…In patients with chronic coronary syndrome, ticagrelor decreases cardiovascular events more efficiently than clopidogrel. In several studies investigating novel P2Y12 inhibitors dyspnea has been detected. …”
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Effects of psychological interventions on anxiety in athletes: a meta-analysis based on controlled trials by Houchen Li, Qingqiong Yang, Bin Wang

“…ObjectivesAnxiety is a prevalent psychological challenge in elite sports and complex training environments. This meta-analysis systematically evaluated the effects of psychological interventions on athletes’ anxiety levels.MethodsA systematic review and meta-analysis were conducted in accordance with PRISMA guidelines. …”
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Designing the outsourcing model in central government organizations by Mahnaz Moradi, Morteza Ghasemi, Maryam Majidi, Gholamreza Amjadi

“…These changes have led to increasing competition, complexity, dynamism and environmental uncertainty. …”
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In Silico Design of Dual Estrogen Receptor and Hsp90 Inhibitors for ER-Positive Breast Cancer Through a Mixed Ligand/Structure-Based Approach by Gabriele La Monica, Federica Alamia, Alessia Bono, Francesco Mingoia, Annamaria Martorana, Antonino Lauria

“…Traditional endocrine therapies, including aromatase inhibitors, selective estrogen receptor degraders/antagonists (SERDs), and selective estrogen receptor modulators (SERMs), have improved outcomes for metastatic ER+ breast cancer. …”
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Characterization of an unusual SARS-CoV-2 main protease natural variant exhibiting resistance to nirmatrelvir and ensitrelvir by Dipendra Bhandari, Oksana Gerlits, Stephen Keable, Leighton Coates, Annie Aniana, Rodolfo Ghirlando, Nashaat T. Nashed, Andrey Kovalevsky, John M. Louis

“…Structural differences in four inhibitor complexes of MProD48Y/ΔP168 compared to wild-type are described. …”
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Quantum-Inspired Hyperheuristic Framework for Solving Dynamic Multi-Objective Combinatorial Problems in Disaster Logistics by Kassem Danach, Hassan Harb, Louai Saker, Ali Raad

“…Disaster logistics presents a highly complex decision-making challenge under conditions of uncertainty, where the timely and efficient allocation of scarce resources is essential to minimize human suffering. …”
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Enhanced Workload Prediction in Data Centers Using Two-Stage Decomposition and Hybrid Parallel Deep Learning by Dalal Alqahtani, Hamidreza Imani, Tarek El-Ghazawi

“…Workload prediction is one of the most basic requirements in developing cost and energy-efficient Cloud Data Centers (CDCs). Most traditional approaches have suffered from noise and failed to capture the complex dynamic patterns in workload data, reducing their accuracy. …”
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