Gentle Introduction to Artificial Intelligence for High-School Students Using Scratch by Julian Estevez, Gorka Garate, Manuel Grana

“…In this paper we focus on innovative ways to introduce high school students to the fundamentals and operation of two of the most popular AI algorithms. We describe the elements of a workshop where we provide an academic use-create-modify scaffolding where students work on the Scratch partial coding of the algorithms so they can explore the behavior of the algorithm, gaining understanding of the underlying computational thinking of AI processes. …”
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Toward precision oncology in LUAD: a prognostic model using single-cell sequencing and WGCNA based on a disulfidptosis relative gene signature by Panpan Li, Han Zhang, Limin Sun, Xiaojuan Wu

“…Gene expression in single cell RNA sequencing (scRNA-seq) data was assessed using the AUcell algorithm. In the TCGA [LUAD] dataset, disulfidptosis-related enrichment scores were calculated using ssGSEA, and core gene sets were identified through the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm. …”
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Ways to improve the diagnosis and treatment of interstitial lung disease associated with systemic sclerosis in the Siberian Federal District (materials of the advisory board of rhe... by L. I. Alekseeva, S. A. Terpigorev, E. V. Zonova, L. M. Kudelya, N. M. Babadaeva, A. V. Teteneva, A. A. Kondrashov, D. N. Orlov, T. V. Raskina, O. N. Anoshenkova, Yu. P. Chasovskikh, T. V. Kropotina, A. B. Opongosheva, N. V. Yudina, N. G. Ganyukova

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A CT-based machine learning model for using clinical-radiomics to predict malignant cerebral edema after stroke: a two-center study by Lingfeng Zhang, Gang Xie, Yue Zhang, Yue Zhang, Junlin Li, Junlin Li, Wuli Tang, Wuli Tang, Ling Yang, Ling Yang, Kang Li

“…PurposeThis research aimed to create a machine learning model for clinical-radiomics that utilizes unenhanced computed tomography images to assess the likelihood of malignant cerebral edema (MCE) in individuals suffering from acute ischemic stroke (AIS).MethodsThe research included 179 consecutive patients with AIS from two different hospitals. …”
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A global comparison of social media bot and human characteristics by Lynnette Hui Xian Ng, Kathleen M. Carley

“…Social media bots took the world by storm when social-cybersecurity researchers realized that social media users not only consisted of humans, but also of artificial agents called bots. …”
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An Analysis of the Vocational-Educational Problematics for Substantiating Production Specialist Competencies by V. E. Steinberg, L. V. Vakhidova, E. M. Gabitova

“…The methodology was designed for the differentiation, specification and justification of relevant specialised competencies, which complement universal and general professional competencies documented in educational standards.Methodology and research methods. …”
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Psychogenic overeating: problems of classification, diagnosis, approaches to psychotherapy (literature review) by T. A. Karavaeva, M. V. Fomicheva

“…In the article, we analyze the diagnosis of psychogenic overeating (ICD-10), consider the problem of its diagnostic criteria, similarities and differences with the diagnosis of binge-eating disorder (DSM-V), which complicate the work of researchers. We are looking at the need to differentiate the different types of binge eating disorder. …”
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Machine-learning aided calibration and analysis of porous media CFD models used for rotating packed beds by Ahmed M. Alatyar, Abdallah S. Berrouk

“…The proposed research is an attempt to advance the state-of-the-art of the numerical modelling of RPB by combining Computational Fluid Dynamics and Machine Learning approaches. …”
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Developing a cost-effective tool for choke flow rate prediction in sub-critical oil wells using wellhead data by Zhiwei Xun, Farag M. A. Altalbawy, Prakash Kanjariya, R. Manjunatha, Debasish Shit, M. Nirmala, Ajay Sharma, Sarbeswara Hota, Shirin Shomurotova, Fadhil Faez Sead, Hojjat Abbasi, Mohammad Mahtab Alam

“…Gradient boosting machine (GBM) models were optimized using advanced algorithms like self-adaptive differential evolution (SADE), evolution strategy (ES), Bayesian probability improvement (BPI), and Batch Bayesian optimization (BBO). …”
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Semi-Implicit Numerical Integration of Boundary Value Problems by Maksim Galchenko, Petr Fedoseev, Valery Andreev, Endre Kovács, Denis Butusov

“…The numerical solution to boundary differential problems is a crucial task in modern applied mathematics. …”
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Enhancing Visual Perception in Sports Environments: A Virtual Reality and Machine Learning Approach by Taiyang Wang, Peng Luo, Sihan Xia

“…Understanding how environmental factors and emotional experiences influence sports perceptions is essential for advancing public health research and guiding optimal design interventions. …”
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Digital Synthesis of Sound Generated by Tibetan Bowls and Bells by Andrzej GOŁAŚ, Roman FILIPEK

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Comparison of light gradient boosting and logistic regression for interactomic hub genes in Porphyromonas gingivalis and Fusobacterium nucleatum-induced periodontitis with Alzheime... by Pradeep Kumar Yadalam, Shubhangini Chatterjee, Prabhu Manickam Natarajan, Carlos M. Ardila, Carlos M. Ardila

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DANGO: An MS data annotation tool for glycolipidomics by Masaaki Matsubara, Mayumi Ishihara, Michael Tiemeyer, Kazuhiro Aoki, René Ranzinger

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Analysing Time Series of Land Subsidence in the West of Tehran Province (Shahriar Plain) and its Relation to Groundwater Discharge by InSAR Technique by Ramin Papi, ُSara Attarchi, Masoud Soleimani

“…The Small BAseline Subset (SBAS) algorithm was applied to analyze the time series of land surface displacement and to generate the mean displacement velocity map. …”
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Evaluation of Modified Reflection Symmetry Decomposition Polarization Features for Sea Ice Classification by Tianlang Lan, Chengfei Jiang, Xiaofan Luo, Wentao An

“…The study data included three types of sea surface: open water (OW), young ice (YI), and first-year ice (FYI). In this research, backscattering coefficients were combined with FD, H/A/α, and MRSD polarization features to create eight feature combinations for comparative analysis. …”
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A recurrence model for non-puerperal mastitis patients based on machine learning. by Gaosha Li, Qian Yu, Feng Dong, Zhaoxia Wu, Xijing Fan, Lingling Zhang, Ying Yu

“…Currently, there is a lack of recurrence models for non-puerperal mastitis. The aim of this research is to create and validate a recurrence model using machine learning for patients with non-puerperal mastitis.…”
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Riemannian Manifolds for Biological Imaging Applications Based on Unsupervised Learning by Ilya Larin, Alexander Karabelsky

“…Like many researchers in this field, we note that obtaining high-quality latent representations for phase-contrast or bright-field images opens new frontiers for creating large visual-language models. …”
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Machine-learning assisted discovery unveils novel interplay between gut microbiota and host metabolic disturbance in diabetic kidney disease by I-Wen Wu, Yu-Chieh Liao, Tsung-Hsien Tsai, Chieh-Hua Lin, Zhao-Qing Shen, Yun-Hsuan Chan, Chih-Wei Tu, Yi-Ju Chou, Chi-Jen Lo, Chi-Hsiao Yeh, Chun-Yu Chen, Heng-Chih Pan, Heng-Jung Hsu, Chin-Chan Lee, Mei-Ling Cheng, Wayne Huey-Herng Sheu, Chi-Chun Lai, Huey-Kang Sytwu, Ting-Fen Tsai

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Poisson random measure noise-induced coherence in epidemiological priors informed deep neural networks to identify the intensity of virus dynamics by Saima Rashid, Ayesha Siddiqa, Fekadu Tesgera Agama, Nazeran Idrees, Mohammed Shaaf Alharthi

“…Compartmental models have estimates of parameter complications, whereas machine learning algorithms struggle to understand MPV’s progression and lack elucidation. …”
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