DIGITAL TWINS AND THEIR APPLIANCE IN TRANSPORT ECONOMICS by O. N. Rimskaya, I. V. Anokhov

“…The consequence of this is the emergence of digital twins that allow modeling and predicting the behavior of both individual processes and enterprises as a whole.The aim of the article is to investigate the process of digitalization in the transport industry. …”
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Leveraging Feature Fusion of Image Features and Laser Reflectance for Automated Fish Freshness Classification by Caner Balım, Nevzat Olgun, Mücahit Çalışan

“…This work presents an original contribution by demonstrating, for the first time, the effectiveness of combining low-cost laser sensing and deep visual features for freshness prediction, with potential for real-time mobile deployment.…”
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CALCULATION OF WEIGHT COEFFICIENTS IN CONTINUOUS PARTICLE FILTER by K. A. Rybakov

“…In addition, it is planned to develop algorithms for predicting the states of stochastic diffusion and jump-diffusion systems based on the calculation of weight coefficients in the particle filter considered in this article.…”
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The siRNA Non-seed Region and Its Target Sequences Are Auxiliary Determinants of Off-Target Effects. by Piotr J Kamola, Yuko Nakano, Tomoko Takahashi, Paul A Wilson, Kumiko Ui-Tei

“…These observations may prove useful as parameters for off-target prediction algorithms and improve siRNA 'specificity' design rules.…”
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A Comparison of the Impacts of Radiosonde and AMSU Radiance Observations in GSI Based 3DEnsVar and 3DVar Data Assimilation Systems for NCEP GFS by Govindan Kutty, Xuguang Wang

“…The impact of observations can be dependent on many factors in a data assimilation (DA) system including data quality control, preprocessing, skill of the model, and the DA algorithm. The present study focuses on comparing the impacts of observations assimilated by two different DA algorithms. …”
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Accounting Management and Optimizing Production Based on Distributed Semantic Recognition by Ruina Guo, Shu Wang, Guangsen Wei

“…Additionally, a semantic recognition module is introduced to process the voice signals and generate prediction results. By leveraging extensive accounting management and production data for learning and analysis, the algorithm automatically uncovers patterns and laws within the data, extracting valuable information. …”
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Energy‐based PINNs for solving coupled field problems: Concepts and application to the multi‐objective optimal design of an induction heater by Marco Baldan, Paolo Di Barba

“…Eventually, the ePINN predicts the temperature field within the graphite plate.…”
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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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Artificial intelligence-assisted diagnosis and prognostication in low ejection fraction using electrocardiograms in inpatient department: a pragmatic randomized controlled trial by Dung-Jang Tsai, Chin Lin, Wei-Ting Liu, Chiao-Chin Lee, Chiao-Hsiang Chang, Wen-Yu Lin, Yu-Lan Liu, Da-Wei Chang, Ping-Hsuan Hsieh, Chien-Sung Tsai, Yuan-Hao Chen, Yi-Jen Hung, Chin-Sheng Lin

“…Secondary outcomes included echocardiogram utilization rates, positive predictive value for low EF detection, and cardiology consultation rates. …”
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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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