Modeling Particle Transport in Astrophysical Outflows and Simulations of Associated Emissions from Hadronic Microquasar Jets by D. A. Papadopoulos, O. T. Kosmas, S. Ganatsios

“…Then, we concentrate on predictions of the associated emissions, focusing on detectable high-energy neutrinos and γ-rays originated from the extragalactic M33 X-7 system, which is an X-ray binary discovered in 2006, located in the neighboring galaxy Messier 33, and has not yet been modeled in detail. …”
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Parametric optimization of the slot waveguide characteristics using a machine-learning approach by Yadvendra Singh, Suraj Jena, Harish Subbaraman

“…In the present work, we combine machine learning (ML) algorithms and finite element simulation to predict the power confinement ( $$\hbox {P}_{conf}$$ ) and mode effective index ( $$\hbox {n}_{eff}$$ ) of slot waveguides with respect to geometric parameters such as gap, slab width, and slab height. …”
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Research on the Location-Routing Optimization of International Freight Trains Considering the Implementation of Blockchain by Zhichao Hong, Hao Shen, Wenjie Sun, Jin Zhang, Hongbin Liang, Gang Zhao

“…This algorithm is based on opposition-based learning and its dominant strength. …”
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SAFE-CAST: secure AI-federated enumeration for clustering-based automated surveillance and trust in machine-to-machine communication by Yusuf Kursat Tuncel, Kasım Öztoprak

“…The results show significant improvements in energy efficiency (21.6% reduction), throughput (14.5% increase), security strength (15.3% enhancement), latency (33.9% decrease), and packet loss rate (12.9% reduction) compared to state-of-the-art approaches. …”
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A Method of Intelligent Driving-Style Recognition Using Natural Driving Data by Siyang Zhang, Zherui Zhang, Chi Zhao

“…Finally, a comparative evaluation of SVM, Random Forest, and KNN recognition indicates the superiority of the SVM algorithm and highlights the effectiveness of dimensionality reduction in optimizing characteristic parameters. …”
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Residential Building Renovation Considering Energy, Carbon Emissions, and Cost: An Approach Integrating Machine Learning and Evolutionary Generation by Rudai Shan, Wanyu Lai, Huan Tang, Xiangyu Leng, Wei Gu

“…Using the heuristic optimization algorithm and entropy-weighted method, the framework achieved average energy savings of 56.62%, a reduction in carbon emissions of 51.60%, and a 24.27% decrease in life-cycle costs. …”
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Subspace-based local compilation of variational quantum circuits for large-scale quantum many-body simulation by Shota Kanasugi, Yuichiro Hidaka, Yuya O. Nakagawa, Shoichiro Tsutsui, Norifumi Matsumoto, Kazunori Maruyama, Hirotaka Oshima, Shintaro Sato

“…Here, we propose a hybrid quantum-classical algorithm, called local subspace variational quantum compilation (LSVQC), for compiling the time-evolution operator of quantum many-body systems. …”
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Optimizing ML models for cybercrime detection: balancing performance, energy consumption, and carbon footprint through multi-objective optimization by Romil Rawat

“…The research utilizes the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), a multi-objective evolutionary algorithm (MOEA), to reduce data dimensionality and identify key features for traffic analysis related to global human trafficking (HTr). …”
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Kun–Qi birth cohort (KQBC) study for the incidence, aetiology and risk factors of chronic kidney disease in Chinese children: a cohort profile by Yan Ma, Xingdong Chen, Jie Wei, Li Guo, Jian Huang, Li Xie, Lei Chen, Ping Lu, Wei Sun, Wei Shi, Feng Ding, Liping Zhang, Yue Zhang, Linlin Zhang, Rui Song, Yi Huang, Jun Shen, Hong Xu, Zhigang Chen, Qian Shen, Ying Ma, Yiwen Zhang, Hongxia Li, Yihui Zhai, Biao Xu, Xian Zhou, Jun Sun, Bing Wu, Rui Su, Xiaoyan Yu, Jianhong Zhu, Yihong Huang, Ling Gong, Nana Wu, Jingjing Sun, Tianyi Liu, He Yuan, Yiwen Shen, Jiaojiao Liu, Xia Han, Juanjuan Wu, Yinghua Sun, Suxiang Xu, Qinyi Zhang, Na Xie, Jianfeng Ji, Weizhi Mo, Yuanxin Liu, Xinghua Shi, Wanshan Qiu, Jiapeng Mi, Juhua Yan, Minghui Zhu, Pei Feng, Wenqian Sheng, Mingqin Tai, Chunqin Zhou, Qian Jin, Chengyu Gu, Xiujuan Huang, Qinfang Qian, Yixin Cao, Haochen Shen, Ziwen Xue, Yucui Ma, Juan Tian, Yingdan Zhang, Weiyuan Zhuang, Kaiqun Yang, Xiaohui Shen, Yanwei Gu, Beibei Shi, Chenhong Pan, Hongmei Zhou, Xiuchen Zhang, Meihua Tang, Kaixuan Gu, Hongping Liu, Yuanxian Li

“…We aim to develop multimodal risk prediction models by integrating genomics and artificial intelligence algorithms. …”
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Identification and validation of a KRAS-macrophage-associated gene signature as prognostic biomarkers and potential therapeutic targets in melanoma by Beichen Cai, Beichen Cai, Beichen Cai, Qian Lin, Qian Lin, Qian Lin, Ruonan Ke, Ruonan Ke, Ruonan Ke, Jiaqi Yu, Jiaqi Yu, Jiaqi Yu, Lu Chen, Lu Chen, Xuejun Ni, Xuejun Ni, Hekun Liu, Xiuying Shan, Xiuying Shan, Biao Wang, Biao Wang, Biao Wang

“…The KMPAG gene signature presents a novel prognostic tool, offering insights into personalized treatment strategies and predictive biomarkers for immunotherapy in SKCM. Further exploration of CLEC4A’s role in melanoma progression may provide new therapeutic avenues for targeted intervention.…”
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Insights into Nitrogen-Associated Protein 50 (NAP50) as a Tyrosyl–DNA Phosphodiesterase in Dinoflagellates by Lu Tang, Nora Fung-Yee Tam, Winnie Lam, Thomas Chun-Hung Lee, Steven Jing-Liang Xu, Fred Wang-Fat Lee

“…The three-dimensional structure and biological functions of NAP50 are predicted using deep learning algorithms. Based on evolutionary relationships and functional predictions, NAP50 may play a role in repairing plastid DNA damage and potentially contribute to the transcription of plastid genes in dinoflagellates.…”
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FAULT DIAGNOSIS NEW METHOD OF ROLLING BEARING BASED ON ADAPTIVE REDUNDANT LIFTING SCHEME PACKET by XIAO ShunGen, SONG MengMeng, LAI LianFeng

“…Aiming at feature identification of weak signal for rolling bearing fault,an adaptive redundant lifting scheme packet（ ARLSP） diagnostic method of undecimated operation was proposed to solve the faults distortion that caused by traditional wavelet packet or lifting wavelet transform using sample operation.ARLSP was based on the principle of lifting scheme.Initial undecimated prediction and update operator were calculated by Lagrange interpolating subdivision,and then constructed an ARLSP decomposition and reconstruction algorithm.Simulation signals were tried out by denoising and anti frequency aliasing,results show that ARLSP method was superior to the traditional wavelet packet in denoising capabilities,and there are no frequency aliasing.Moreover,taking an experiment on an asynchronous motor,the vibration signals of the rolling bearings 6205 under conditions of no fault,the inner ring fault,outer ring fault and rolling fault were measured.ARLSP method has been successfully used to extract characteristic frequency and frequency multiplication for various faults,and has got a higher diagnostic accuracy than traditional wavelet packet.…”
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Deepfake Dilemmas: Imagine Tomorrow’s Surveillance Society through Three Scenarios by Fatma Doğan Akkaya

“…Moving beyond technical considerations, the research employs social prediction methods to explore three potential future scenarios involving deepfake avatars: seamless integration that facilitates self-expression but complicates digital identity control; pervasive algorithmic surveillance that exacerbates social control and privacy issues; and the concept of ghost avatars, that is, digital representations that function as commodities or tools of resistance. …”
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Speculation resource provisioning in high-performance computing by Leena Sri, Balaji Narayanan

“…As an attempt to quantify resource allocation we use two level adaptive prediction mechanism to check the computational patterns of past resource allocation to the future requirement. …”
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THE PROBATION OFFICER AS AN AUTHORITY OF CRIMINAL ENFORCEMENT LAW. DEVELOPMENT PROSPECTS IN THE LIGHT OF MODERN TECHNOLOGIES by Tomasz Kalisz

“…Among the advantages are cost efficiency, increased work effectiveness, better prediction of recidivism risk, optimized resource use, individualized approach, and easier communication and collaboration. …”
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Load Reconstruction Technique Using D-Optimal Design and Markov Parameters by Deepak K. Gupta, Anoop K. Dhingra

“…Inverse Markov parameters are computed from the forward Markov parameters using a linear prediction algorithm and have the roles of input and output reversed. …”
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Motion Object Detection Model for Electronic Referee Scoring in Table Tennis Events. by Xiaoke Li, Lili Guo

“…In the simulation test, the model achieved the best trajectory prediction accuracy in both complete video images and partially missing information video images. …”
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Integration Research of Pantograph-Catenary Detection System for Intelligent Operation and Maintenance of Heavy-haul Locomotive by Jiejun LYU, Hongjun HE, Congjian JIANG

“…The test showed that the systems can realize on-line detection, fault diagnosis, intelligent prediction,emergency treatment and pantograph health management of pantograph-catenary system, improve the online detection and evaluation effect of pantograph-catenary system, and ensure the safety and reliability of line traction power supply.…”
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Design and Application of Digital Twin-Based Brain Control System by Yinan Wang, Hongyang Jin, Zongwei Yao, Zhiyong Chang, Deping Wang

“…Digital twin (DT) technology, with its ultra-high-fidelity simulation and prediction capabilities, virtual–real interaction mapping, and autonomous feedback regulation, offers a novel approach to addressing these issues. …”
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Research and application of intelligent learning path optimization based on LSTM-Transformer model by Jinling Wang, Wandong Chai

“…Based on this, this study proposes a hypothesis: the intelligent learning path optimization strategy based on the LSTM-Transformer model can achieve accurate prediction and personalized optimization of learners' learning paths with the help of deep learning technology. …”
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