Multifunctional Hierarchical Metamaterials: Synergizing Visible-Laser-Infrared Camouflage with Thermal Management by Shenglan Wu, Hao Huang, Zhenyong Huang, Chunhui Tian, Lina Guo, Yong Liu, Shuang Liu

“…Furthermore, the RSHM demonstrates exceptional incident angle and polarization stability, maintaining robust performances even under complex detection conditions. This design is easy to expand relative to other frequency bands of the electromagnetic spectrum and holds significant potential for applications in military camouflage, energy-efficient buildings, and optical devices.…”
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A Novel Approach for Rapid Detection of Forest Degradation and Diseases Through Anomaly Analysis of Sentinel-2 Spectral Data by Sofiia Drozd, Nataliia Kussul, Hanna Yailymova

“…The aim of this study was to develop an accessible and reliable technique that could match the performance of more complex algorithms while using minimal computational resources. …”
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Quantum key distribution through quantum machine learning: a research review by Krupa Purohit, Ajay Kumar Vyas

“…QML algorithms improve the key generation of QKD, by improving quantum state selection and reducing measurements. This also allows them to increase efficiency because it identifies trends in errors and applies corrections, making quantum cryptography a more dependable option. …”
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Enhancing biometric identification using 12-lead ECG signals and graph convolutional networks by Maram Al Alfi, Pedro Peris-Lopez, Carmen Camara

“…The GCN model is trained on this graph, enabling it to learn complex patterns for user identification efficiently.ResultsExperimental results demonstrate that the proposed GCN-MI model achieves 100% accuracy with a 5-layer architecture at a k-fold of 75, outperforming conventional approaches that require less training data.DiscussionThis work introduces several innovations: the integration of MI indices enhances feature selection, improving model robustness and efficiency; the graph-based learning framework effectively captures both spatial and statistical relationships within ECG data, leading to higher classification accuracy; the proposed approach offers a scalable and real-time biometric authentication system suitable for applications in finance, healthcare, and personal device access. …”
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Machine Learning with Administrative Data for Energy Poverty Identification in the UK by Lin Zheng, Eoghan McKenna

“…Energy poverty continues to be a critical challenge, and this requires efficient and scalable identification methods to support targeted interventions. …”
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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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Advances in Waste Plastic Recycling via Photocatalytic and Electrocatalytic Reforming by Xinjia MIAO, Haihong ZHONG, Weiting YANG, Yongjun FENG, Zhongmin SU

“…However, the large-scale implementation of photocatalytic and electrocatalytic reforming still faces several challenges, including low catalytic efficiency, limited product selectivity, and complex separation and purification processes. …”
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Protective mechanism of weathering steel rust layers in atmospheric environments and their stabilization treatment technologies by Junyi GAO, Weichen XU, Binbin ZHANG, Canming LI, Guobao LI, Baorong HOU

“…Most alloying elements enhance the protective properties of rust layers by improving their compactness, stability, and ionic selectivity. Research into evaluating the corrosion resistance of rust layers has now expanded to include artificial intelligence, advanced sensors, and big data technologies, making studies more dynamic and efficient. …”
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Towards the Optimization of Apodized Resonators by Ana Valenzuela-Pérez, Carlos Collado, Jordi Mateu

“…To address this, we extend a previously published model (named the Quasi-3D model), which employs the Transmission Line Matrix (TLM) method, enabling efficient simulations of complex geometries with more precise meshing. …”
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Inverse-design topology optimization of magnonic devices using level-set method by Andrey A. Voronov, Marcos Cuervo Santos, Florian Bruckner, Dieter Suess, Andrii V. Chumak, Claas Abert

“…While promising for analog, Boolean, and neuromorphic computing, current implementations face memory limitations that hinder the design of complex systems. This study presents a level-set parameterization method for topology optimization, combined with an adjoint-state approach for memory-efficient simulation of magnetization dynamics. …”
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Modern opportunities of therapeutic treatment of allergic conjunctivitis. A review by D. Yu. Maychuk

“…Its efficacy is the same or even higher than that of cromoglycate and azelastine. 20 clinical studies (more than 1200 patients) revealed that levocabastine eye drops are effective, work quickly and have good tolerability. This drug is efficient in allergic conjunctivitis treatment and acute infectious conjunctivitis complex therapy.…”
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ENQUIRE automatically reconstructs, expands, and drives enrichment analysis of gene and Mesh co-occurrence networks from context-specific biomedical literature. by Luca Musella, Alejandro Afonso Castro, Xin Lai, Max Widmann, Julio Vera

“…The accelerating growth of scientific literature overwhelms our capacity to manually distil complex phenomena like molecular networks linked to diseases. …”
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Optimization of Bolted Steel T-Stub Connection Based on Nonlinear Finite Element Analysis Using Genetic Algorithm by Péter Grubits, Tamás Balogh, Majid Movahedi Rad

“…However, steel connections remain inherently complex due to nonlinear behavior, cost considerations, and code compliance, framing the design process as a discrete structural optimization problem. …”
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Beyond Snippet Assistance: A Workflow-Centric Framework for End-to-End AI-Driven Code Generation by Vladimir Sonkin, Cătălin Tudose

“…However, these tools primarily assist with isolated coding tasks and lack a structured approach to automating complex, multi-step software development workflows. …”
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Obstacle Avoidance Control of Autonomous Undersea Vehicle Based on DVFH+ in Ocean Current Environment by Zhongben ZHU, Jiahao ZHANG, Yifan XUE, Hongde QIN

“…This enabled the calculation of the planning instructions based on environmental characteristics around AUVs, ensuring the efficiency and safety of navigation. Simulation experiments using the REMUS 100 AUV model show that DVFH+ can provide a smoother and more feasible obstacle avoidance route, making it suitable for AUV obstacle avoidance in complex environments while effectively preventing issues such as detouring and planning failure caused by improper threshold settings in the original algorithm.…”
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Enhanced futures price-spread forecasting based on an attention-driven optimized LSTM network: integrating an improved grey wolf optimizer algorithm for enhanced accuracy by Yongli Tang, Zhenlun Gao, Zhongqi Cai, Jinxia Yu, Panke Qin

“…Financial market prediction faces significant challenges due to the complex temporal dependencies and heterogeneous data relationships inherent in futures price-spread data. …”
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Iridium porphyrin-catalysed asymmetric carbene insertion into primary N-adjacent C–H bonds with TON over 1000000 by Zong-Rui Li, Kun Zhan, Yi-Jie Wang, Liang-Liang Wu, Guo-Lin Lu, Hao-Yang Wang, Xiao-Long Wan, Zhen-Jiang Xu, Kam-Hung Low, Chi-Ming Che

“…Abstract Selective functionalization of ubiquitous C-H bonds in organic molecules provides a straightforward and efficient approach to construct complex molecules with fewer synthetic steps and high atom economy, thus promoting more sustainable and economical chemical synthesis. …”
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SP-RF-ARIMA: A sparse random forest and ARIMA hybrid model for electric load forecasting by Kamran Hassanpouri Baesmat, Farhad Shokoohi, Zeinab Farrokhi

“…Accurate Electric Load Forecasting (ELF) is crucial for optimizing production capacity, improving operational efficiency, and managing energy resources effectively. …”
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Toward Trustworthy Machine Learning for Daily Sediment Modeling in the Riverine Systems: An Integrated Framework With Enhanced Uncertainty Quantification and Interpretability by Z. J. Yue, N. N. Wang, B. D. Xu, X. Huang, D. M. Yang, H. B. Xiao, Z. H. Shi

“…To achieve trustworthy ML for riverine sediment timeseries predictions, this study proposes an integrated ML framework, enhancing key steps: feature selection, UQ, and interpretation. Lagged hydro‐environmental variables are incorporated via rigorous feature selection. …”
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Prioritizing simulation-based stress tests to assess the resilience of transport systems: a computation-free methodology by Hossein Nasrazadani, Maria Nogal, Bryan T. Adey, Stergios A. Mitoulis

“…It enables infrastructure managers to efficiently screen and rank stress tests, optimizing the selection process to maximize insights into system resilience while minimizing computational demands. …”
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