Hierarchical Reinforcement Learning with Automatic Curriculum Generation for Unmanned Combat Aerial Vehicle Tactical Decision-Making in Autonomous Air Combat by Yang Li, Wenhan Dong, Pin Zhang, Hengang Zhai, Guangqi Li

“…Additionally, the visual analysis of UCAVs’ flight logs validates the learned hierarchical decision-making process, showcasing the interplay between tactical selection and manoeuvring execution. This research provides novel methodologies combining hierarchical reinforcement learning with tactical domain knowledge for the autonomous decision-making of UCAVs in complex air combat scenarios.…”
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Evaluating the effect of digital elevation model resolution in lahar hazard simulations: insights from the 1877 Cotopaxi scenario, Ecuador by Francisco J. Vasconez, Francisco J. Vasconez, Jeremy C. Phillips, S. Daniel Andrade, Mark J. Woodhouse

“…This work provides a quantitative framework to guide DEM selection, balancing computational efficiency with predictive fidelity in lahar hazard assessment.…”
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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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Model of the Connecting Optimal Number of Heat Consumers by Sergey M. Terekhov, Vladimir A. Nemtinov, Kirill S. Kornilov

“…Directions of further study of increasing the efficiency of heat supply systems and integrating the presented mathematical model with modern software complexes are determined.…”
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Indium Imidazo[4,5,-<i>b</i>]porphyrins as Photocatalysts for Oxidation of Sulfides by Inna A. Abdulaeva, Mikhail A. Filatov, Azhar Kechiche, Alla Bessmertnykh-Lemeune

“…The heterogenized complex enables selective synthesis of sulfoxides under “green” conditions; however, it is prone to leaching into the solution when irradiated with both blue and red LEDs.…”
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Dynamic path planning of UAV with least inflection point based on adaptive neighborhood A* algorithm and multi-strategy fusion by Longyan Xu, Mao Xi, Ren Gao, Ziheng Ye, Zaihan He

“…Abstract Planning a safe and efficient global path in a complex three-dimensional environment is a complex and challenging optimization task. …”
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A computational time integrator for heat and mass transfer modeling of boundary layer flow using fuzzy parameters by Muhammad Shoaib Arif, Wasfi Shatanawi, Yasir Nawaz

“…It is imperative to comprehend the mechanics of heat and mass transfer to enhance aeronautical technology, forecast weather, and design thermal systems that are more efficient. Modelling and simulating these flows with precision is indispensable. …”
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EDHD-FG-XGBoost: Entropy-driven high-dimensional feature gain XGBoost model for short-term wind power prediction and application by Xing Liu, Xingyu Mou, Ying Zhang, Hui Chen, Xin Wang, Xihao Sun, Chengcheng Wang, Ruixiang Shong, Yunfeng Li

“…Wind power prediction is critical for the efficient utilization of wind energy and the stable operation of power grids. …”
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A Systematic Review of the Advances and New Insights into Copy Number Variations in Plant Genomes by Saimire Silaiyiman, Jiaxuan Liu, Jiaxin Wu, Lejun Ouyang, Zheng Cao, Chao Shen

“…The advancement in sequencing technologies has made the detection and analysis of CNVs more efficient, not only revealing their crucial roles in plant disease resistance, adaptability, and growth development, but also demonstrating broad application potential in crop improvement, particularly in selective breeding and genomic selection. …”
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Purification of Monoclonal Antibodies Using Chromatographic Methods: Increasing Purity and Recovery by Elnazalsadat Jafarzadeh Chehraghi, Parvin Akbarzadehlaleh, Karim Shamsasenjan

“…The purification of mAbs is a crucial stage in production, ensuring the elimination of impurities for a top-quality, safe, and efficient final product. Chromatographic methods including affinity chromatography, ion exchange chromatography, and hydrophobic interaction chromatography (HIC) are commonly utilized to selectively capture and purify mAbs from complex mixtures by exploiting their unique properties, such as antigen-binding specificity or their surface charge and hydrophobicity. …”
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Adaptively evolved human oral actinomyces‐sourced defensins show therapeutic potential by Shunyi Zhu, Bin Gao, Yoshitaka Umetsu, Steve Peigneur, Ping Li, Shinya Ohki, Jan Tytgat

“…Signatures of natural selection were detected in defensins from the actinomyces colonized in human oral cavity and ruminant rumen and dental plaque, highlighting their role in adaptation to complex multispecies bacterial communities. …”
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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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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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Bone scintigraphy based on deep learning model and modified growth optimizer by Omnia Magdy, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed A. Ewees, Ahmed Elgarayhi, Mohammed Sallah

“…Abstract Bone scintigraphy is recognized as an efficient diagnostic method for whole-body screening for bone metastases. …”
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Distributed Denial of Services (DDoS) attack detection in SDN using Optimizer-equipped CNN-MLP. by Sajid Mehmood, Rashid Amin, Jamal Mustafa, Mudassar Hussain, Faisal S Alsubaei, Muhammad D Zakaria

“…These models have got a complex optimizer installed on them to decrease the false positive or DDoS case detection efficiency. …”
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Strategizing AI in Healthcare: A Multidimensional Blueprint for Transformative Decision-Making in Clinical Settings by Simon Martina, Kamin Stefan, Hamper Andreas, Wittenberg Thomas, Schmitt-Rüth Stephanie

“…By creating a comprehensive categorization system, we attempt to navigate the complex array of possible AI applications within the field of healthcare, hence enabling the identification, selection, and advancement of AIdriven initiatives. …”
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NORMALISATION OF THE DRIVE PRECISION OF METAL-CUTTING MACHINES by Irina A. Klenova, Dmitry A. Rudikov, Svetlana N. Kholodova

“…Methods The accuracy of established modes of operation is a key determinant on which the efficiency of cutting operations depends. In order to determine and evaluate drive errors in metal-cutting machines, three methods were proposed: direct measurement of the frequencies of the series, calculations using kinematic balance equations and summation of individual components. …”
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The evolving role of programming and LLMs in the development of self-driving laboratories by John R. Kitchin

“…Machine learning and automation are transforming scientific research, yet the implementation of self-driving laboratories (SDLs) remains costly and complex, and it remains difficult to learn how to use these facilities. …”
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Diagnostics of the enterprise’s business potential by A.A.

“…The grouping of diagnostic methods was carried out in accordance with the goals of the diagnosis (diagnostics of the strategic perspective of development; diagnostics of competitiveness; diagnostics of the components of business potential; diagnostics of the possibility of the onset of a financial crisis), which contributes to increasing the efficiency of its implementation. It has been proven that achieving the goal and solving the tasks of diagnosing business potential is possible due to: the formation of reliable information support; successful selection of diagnostic methods; analytical substantiation of the conclusion regarding the state and opportunities of business potential; development and implementation of measures to improve the existing situation; conducting control over the implementation of measures.…”
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