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

“…In this work, after improving the formulation of the model on particle transport within astrophysical plasma outflows and constructing the appropriate algorithms, we test the reliability and effectiveness of our method through numerical simulations on well-studied galactic microquasars as the SS 433 and the Cyg X-1 systems. …”
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Expanding kinetoplastid genome annotation through protein structure comparison. by Juan Manuel Trinidad-Barnech, José Sotelo-Silveira, Darío Fernández Do Porto, Pablo Smircich

“…Recently, significant advancements have been made in in-silico protein structure prediction and algorithms for rapid and precise large-scale protein structure comparisons. …”
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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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Blind HDR image quality assessment based on aggregating perception and inference features by Donghui Wan, Xiuhua Jiang, Qiangguo Yu

“…These gradient similarity maps and deep feature maps are subsequently aggregated for quality prediction using support vector regression (SVR). Experimental results demonstrate that the proposed method achieves outstanding performance, outperforming other state-of-the-art HDR IQA metrics.…”
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Risk Measurement of TAVR Surgical Complications Based on Unbalanced Multilabel Classification Approaches by Yue Zhang, Yuantao Xie

“…The model used in this paper bridges the gap between medical risk prediction and insurance actuarial science, provides a practical data modelling foundation and algorithmic support for the future development of post-operative complication insurance products that precisely align with clinical risk.…”
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Water Level Detection and Flood Early Warning System Using Image Processing by Muhammad Akmal Ilmi, I Komang Somawirata, Michael Ardita

“…The YOLO (You Only Look Once) algorithm is utilized for real-time object detection, such as water levels, aiming to enhance prediction accuracy. …”
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Research on Air Temperature Inversion Method Based on Land Surface Temperature of Different Land Surface Cover by Rui Fang, Xiaofang Shan, Qinli Deng

“…Due to the characteristics of the algorithms, it is recommended to prioritize random forest for prediction when the sample range covers the observed data range and to use BP neural networks when it does not. …”
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Liquid biopsy-derived extracellular vesicle protein biomarkers for diagnosis and prognostic assessment of lung squamous cell carcinoma by Sheng Ma, Na Zhao, Xin Dong, Yaru Wang, Lei Song, Ruiqi Zheng, Xiaochen Zhi, Congcong Ma, Shujun Cheng, Jie Li, Yutao Liu, Ting Xiao

“…Additionally, a prognostic prediction model for LUSC was developed using a combination of 101 machine learning algorithms. …”
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Regulatory Framework of the Conduct of Forensic Construction Examination by A. A. Revunov

“…In order to improve the current situation concerning the regulation of forensic construction and technical examinations, the following measures have been proposed: revision and improvement of their methodological, theoretical, and legal foundations, in-depth analysis of the content of urban planning legislation from the point of view of requirements mandatory for application by a forensic expertbuilder, specifying the limits of an expert’s competence, the formation of unified algorithms and forms of presenting research, the development of sub-theories on the legal and organizational support of the nonstate forensic activity, the active involvement of research institutions and higher educational institutions in the conduct of expert examinations.…”
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Expected Transmission Energy Route Metric for Wireless Mesh Senor Networks by YanLiang Jin, HuiJun Miao, Quan Ge, Chi Zhou

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Postcholecystectomy syndrome: the modern approach: resolution of Advisory council by V. T. Ivashkin, A. V. Okhlobystin, D. S. Bordin, E. Ya. Seleznyova, Yu. A. Kucheryavy, Ye. V. Bystrovskaya, O. C. Vasnev, M. F. Osipenko, G. H. Musayev, Yu. O. Shulpekova

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Pustular reaction in adult-onset immunodeficiency due to anti-interferon-gamma autoantibodies by Narachai Julanon, Pojsakorn Danpanichkul, Charoen Choonhakarn, Suteeraporn Chaowattanapanit, Siriluck Anunnatsiri, Ploenchan Chetchotisakd, Salin Kiratikanon, Rujira Rujiwetpongstorn, Napatra Tovanabutra, Siri Chiewchanvit, Romanee Chaiwarith, Phichayut Phinyo, Phichayut Phinyo, Mati Chuamanochan, Mati Chuamanochan

“…In cases where these hallmark features were absent, a predictive algorithm incorporating the presence of a concomitant infections, serum globulin concentration, and alkaline phosphatase level demonstrated robust utility in estimating the likelihood of AOID-associated pustular reaction.…”
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Discovering biomarkers associated with infiltration of CD8+ T cells and tumor-associated fibrosis in colon adenocarcinoma using single-cell RNA sequencing and gene co-expression ne... by Jinning Zhang, Jinning Zhang, Ziquan Sun, Ziquan Sun, Guodong Li, Guodong Li, Lixian Ding, Zitong Wang, Ming Liu, Ming Liu

“…We utilized univariate Cox regression and LASSO analysis to create a prognostic model. The predictive model was assessed through Kaplan-Meier analysis, and a survival prediction nomogram was created. …”
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On the Extrapolation of Generative Adversarial Networks for Downscaling Precipitation Extremes in Warmer Climates by Neelesh Rampal, Peter B. Gibson, Steven Sherwood, Gab Abramowitz

“…Abstract While deep‐learning downscaling algorithms can generate fine‐scale climate projections cost‐effectively, it is unclear how effectively they extrapolate to unobserved climates. …”
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Discordance between a deep learning model and clinical-grade variant pathogenicity classification in a rare disease cohort by Sek Won Kong, In-Hee Lee, Lauren V. Collen, Michael Field, Arjun K. Manrai, Scott B. Snapper, Kenneth D. Mandl

“…This observation underscores ongoing challenges in clinical genetics, highlighting the need for continued refinement of computational methods in variant pathogenicity prediction.…”
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Research on Resource Reservation Strategy for Edge Federation by Hengzhou Ye, Huangran Li, Jiaming Li, Qiu Lu, Gong Chen

“…Furthermore, the RRP-MADDPG strategy exhibits excellent convergence performance and outperforms both the load prediction-based reservation strategy and other similar deep reinforcement learning algorithms.…”
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Kernel Negative ε Dragging Linear Regression for Pattern Classification by Yali Peng, Lu Zhang, Shigang Liu, Xili Wang, Min Guo

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On-chip differential mode group delay manipulation based on 3D waveguides by Xiaofeng Liu, Quandong Huang, Jiaqi Ran, Jiali Zhang, Ou Xu, Di Peng, Yuwen Qin

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Integration of Accelerometers and Machine Learning with BIM for Railway Tight- and Wide-Gauge Detection by Jessada Sresakoolchai, Chayutpong Manakul, Ni-Asri Cheputeh

“…These data are processed and analyzed using supervised machine-learning algorithms to classify and predict potential tight- and wide-gauge events. …”
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An accuracy-privacy optimization framework considering user’s privacy requirements for data stream mining by Waruni Hewage, R. Sinha, M. Asif Naeem

“…Additionally, a data fitting module using kernel regression is integrated, a unique approach that predicts accuracy levels based on user-defined privacy thresholds. …”
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