A Study on the Timing Sensitivity of the Transient Dose Rate Effect on Complementary Metal-Oxide-Semiconductor Image Sensor Readout Circuits by Yanjun Fu, Zhigang Peng, Zhiyong Dong, Pei Li, Yuan Wei, Dongya Zhang, Yinghong Zuo, Jinhui Zhu, Shengli Niu

“…The results show that, under low dose rates, the CIS readout circuit can still perform data acquisition and digital processing, with the photoelectric signal exhibiting some sensitivity to the occurrence moment. …”
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Integrating HEC-RAS, GIS, and LISREL for assessing and enhancing urban building resilience against flood threats: Comprehensive model and analysis by Faraz Estelaji, Rahim Zahedi, Arash Gitifar, Alireza Naseri, Mohammad Hossein Yari, Bita Rouhi Asl, Bita Abedi

“…By overlaying vulnerable gravity centers with flood-prone regions, building resilience components are computed through structural factor analysis and LISREL modeling. …”
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Flood potential and near real-time inundation analysis through geospatial approaches in Shah Alam, Malaysia by Minhaz Farid Ahmed, Bijay Halder, Liew Juneng, Mazlin Bin Mokhtar, Adam Narashman Leeonis

“…To create a mapping of Shah Alam’s flood potential, the Analytic Hierarchy Process (AHP) and Fuzzy-AHP methods were applied with the twelve criteria. …”
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Optimizing image capture for low-light widefield quantitative fluorescence microscopy by Zane Peterkovic, Avinash Upadhya, Christopher Perrella, Admir Bajraktarevic, Ramses E. Bautista Gonzalez, Megan Lim, Kylie R. Dunning, Kishan Dholakia

“…An example is the optical redox ratio, which is computed from autofluorescence intensity to measure metabolism. …”
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A Novel PCR-Based Tool to Trace Oenological <i>Saccharomyces cerevisiae</i> Yeast by Monitoring Strain-Specific Nucleotide Polymorphisms by Anna Baldisseri, Davide Santinello, Sara Granuzzo, Martina Frizzarin, Fabio De Pascale, Geppo Sartori, Paolo Antoniali, Stefano Campanaro, Raffaele Lopreiato

“…To ensure consistent quality and process efficiency, wineries commonly employ selected starter strains. …”
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Predicting Atmospheric Dispersion of Industrial Chemicals Using Machine Learning Approaches by Maria Valle, Jairo A. Cardona, Cesar Viloria-Nunez, Christian G. Quintero M.

“…Dimensionality reduction methods, such as principal component analysis and correlation-based dimensionality reduction, were implemented to improve computational efficiency, reduce data noise, and maintain essential information. …”
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Influence of carbon on the rheology and additive manufacturability of Ti-6Al-4V powders by Apratim Chakraborty, Manvinder Lalh, Étienne Martin, Heidar Karimialavijeh, Adam Bejarano, Andrew Wessman, Yu Zou, Mahdi Habibnejad-Korayem

“…Blend quality was assessed chemically and visually via computed tomography and scanning electron microscopy. …”
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Outlook on human-centred design in industry 5.0: towards mass customisation, personalisation, co-creation, and co-production by Nastaran Hasani, Abbas Hosseini, Yasaman Ashjazadeh, Victoria Diederichs, Salar Ghotb, Mariapaola Riggio, Eric Hansen, Vahid Nasir

“…Furthermore, it investigates the role of technological enablers (artificial intelligence, digital twins, computational design, digital fabrication, robotics, augmented/virtual reality), in facilitating communication and collaboration throughout the design process from observation and ideation to prototyping and testing. …”
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Expansion of Output Spatial Extent in the Wavenumber Domain Algorithms for Near-Field 3-D MIMO Radar Imaging by Yifan Gong, Limin Zhai, Yan Jia, Yongqing Liu, Xiangkun Zhang

“…Due to the limited computational resources of the miniaturized MIMO microwave camera, real-time processing of a large amount of 3-D echo data requires an imaging algorithm that has both real-time performance and large output spatial extent. …”
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Two-layer asynchronous distributed optimal voltage control for VSC-HVDC-connected large-scale wind farm clusters by Fuyan Liu, Feifan Shen, Pan Hu, HeSong Cui, Sheng Huang, Ji Zhang, Xia Ma, Kun He

“…The results showed that the proposed scheme could improve the computation efficiency without affecting the original problem’s optimality, while also exhibiting enhanced robustness and environmental adaptability.…”
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Vibration–Collision Coupling Modeling in Grape Clusters for Non-Damage Harvesting Operations by Baocheng Xu, Jizhan Liu, Yucheng Jin, Kaiyu Yang, Shengyi Zhao, Yun Peng

“…In the table grape production process, issues such as berry detachment and damage caused by cluster vibrations and berry collisions are significant challenges. …”
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Unraveling Nature’s Pharmacy: Transforming Medicinal Plants into Modern Therapeutic Agents by Natalia Vaou, Chrysoula (Chrysa) Voidarou, Georgios Rozos, Chrysa Saldari, Elisavet Stavropoulou, Georgia Vrioni, Athanasios Tsakris

“…This review explores the potential of NPs in the process of drug discovery and development, placing emphasis on the blend of traditional knowledge with modern drug discovery techniques. …”
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Energy-Efficient Deep Learning for Cloud Detection Onboard Nanosatellite by Imane Khalil, Amina Daghouri, Mohammed Alae Chanoui, Zouhair Guennoun, Adnane Addaim

“…However, energy consumption remains a critical consideration for onboard processing, particularly in nanosatellites where resource constraints are significant. …”
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MagneticPillars++: Efficient LiDAR Odometry Via Deep Frame-To-Keyframe Point Cloud Registration by Kai Fischer, Martin Simon, Stefan Milz, Patrick Mäder

“…However, due to its distance-based processing nature, ICP relies on an accurate pose initialization while implicating increased computational complexity with a growing number of points. …”
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ReScConv-xLSTM: An improved xLSTM model with spatiotemporal feature extraction capability for remaining useful life prediction of Aero-engine by Mingxing Huang, Lanying Yang, Gang Jiang, Xingan Hao, Hong Lu, Hang Luo, Peng Wang, Jinyang Li

“…Although deep learning models based on LSTM and Transformer have achieved significant results in this field, these models typically only extract temporal features, neglecting spatial features, and struggle with parallel computation, leading to a bottleneck in RUL prediction performance. …”
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Improving Railway Track Detection With a Mixed-Modality Deep Learning Approach by Wichian Ooppakaew, Jakkrit Onshaunjit, Saifun Khrueakhrai, Jakkree Srinonchat

“…Despite the increased computational parameters, the improved models paradoxically enable quicker processing across all models.…”
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Hydroxyapatite-reinforced chitosan film on PEO-treated aluminum alloys for enhanced corrosion resistance by Yang Li, Shuyan Yang, Yong Wan

“…The composite coatings were constructed by depositing HAP-reinforced chitosan films onto PEO-pretreated aluminum alloy via a dipping–pulling process. Comprehensive characterization—including spectroscopic, microscopic, electrochemical, and computational techniques such as FTIR and molecular dynamics (MD) simulations—was conducted to evaluate their structure and performance. …”
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Day–Night Energy-Constrained Path Planning for Stratospheric Airships: A Hybrid Level-Set Particle Swarm Optimization (LS-PSO) Framework in Dynamic Flows by Cheng Liu, Xiang Li, Jinggang Miao, Yu Feng, Chunjiang Bian

“…The results demonstrate that our path planning methodology provides a computationally efficient and optimal energy–time solution for autonomous stratospheric airships, while conforming to reachability and strict nighttime energy constraints.…”
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Investigating banks’ social media content and consumer reactions with machine learning by Gombos Nóra, Julianna, Vlaszov Artúr, Bíró-Szigeti Szilvia, Molontay Roland

“…Design/methodology/approach: – Text and image analysis of the Twitter accounts available to the public was performed using different natural language processing methods (topic analysis, sentiment analysis), computer vision techniques (object detection, optical character recognition, image captioning), and statistical and machine learning models (linear and logistic regression, Catboost). …”
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Evaluation of GSJ intrusive rocks JG1, JG2, JG3, JG1a, and JGb1 by an objective outlier rejection statistical procedure by Mirna Guevara, Surendra P. Verma, Fernando Velasco-Tapia

“…New concentration mean values and other statistical parameters were computed from final normal distributions. Although 23% of mean concentration values were practically identical to those reported in earlier literature, 67% differ by about 1% to 20%. …”
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