Temporal causal inference with stochastic audiovisual sequences. by Shannon M Locke, Michael S Landy

“…A unified percept was affected by click-flash pattern similarity and the maximum temporal offset between individual clicks and flashes, but not on the proportion of synchronous click-flash pairs. …”
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«Obscenities give rise to thugs»: Obscene vocabulary in the practice of the poet Vsevolod Nekrasov (based on archive materials) by E. N. Penskaya

“…Without claiming to generalize, this material is focused on identifying patterns and searching for possible algorithms for classifying such phenomena. …”
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Reassortment Dynamics: Phylogeography and Evolution of H4N9 Influenza Viruses by Nataliia A. Bobrova, Ekaterina D. Lisenenkova, Ekaterina S. Avsievich, Olga N. Mityaeva, Pavel Yu Volchkov, Andrey A. Deviatkin

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Robust development of data-driven models for methane and hydrogen mixture solubility in brine by Kashif Saleem, Abhinav Kumar, K. D. V. Prasad, Ahmad Alkhayyat, T. Ramachandran, Protyay Dey, Navdeep Kaur, R. Sivaranjani, I. B. Sapaev, Mehrdad Mottaghi

“…In this paper, we aim to form robust data-driven intelligent algorithms founded on various machine learning methods of Support Vector Machine, Random Forest, AdaBoost, Decision Tree, K-nearest Neighbors, Multilayer Perceptron Artificial Neural Network and Convolutional Neural Network to model solubility of hydrogen/methane blend in brine under realistic conditions of underground hydrogen storage projects by utilizing an experimental dataset collected from the existing body of published research. …”
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Prediction of obesity levels based on physical activity and eating habits with a machine learning model integrated with explainable artificial intelligence by Yasin Görmez, Fatma Hilal Yagin, Burak Yagin, Yalin Aygun, Hulusi Boke, Georgian Badicu, Matheus Santos De Sousa Fernandes, Abedalrhman Alkhateeb, Mahmood Basil A. Al-Rawi, Mohammadreza Aghaei, Mohammadreza Aghaei

“…The results also highlighted age, weight, height and specific food patterns as key predictors of obesity. In terms of interpretability, LIME showed superior in fidelity, whereas SHAP showed improved sparsity and consistency across models, facilitating a comprehensive understanding of trait importance.ConclusionThis research demonstrates that ML algorithms, when integrated with XAI technologies, can accurately predict obesity levels and explain important contributing risk factors. …”
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Leveraging environmental microbial indicators in wastewater for data-driven disease diagnostics by Gayatri Gogoi, Gayatri Gogoi, Sarangthem Dinamani Singh, Sarangthem Dinamani Singh, Devpratim Koch, Devpratim Koch, Emon Kalyan, Rashmi Rani Boro, Aradhana Devi, Hridoy Jyoti Mahanta, Hridoy Jyoti Mahanta, Pankaj Bharali, Pankaj Bharali

“…Unsupervised learning algorithms, including K-means and K-medoid clustering, were employed to categorize the data into four distinct clusters, revealing patterns of viral positivity and environmental conditions.ResultsCluster analysis indicated that seasonal variations and water quality characteristics significantly influenced SARS-CoV-2 positivity rates. …”
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Integrative analysis of RNA-Seq data and machine learning approaches to identify Biomarkers for Rhizoctonia solani resistance in sugar beet by Bahman Panahi, Mahdi Hassani, Nahid Hosseinzaeh Gharajeh

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Progress and trends on machine learning in proteomics during 1997-2024: a bibliometric analysis by Chao Tan, Hao Liu, Zhen Zhang, Xinyu Liu, Yinquan Ai, Xiumin Wu, Enlin Jian, Yongyan Song, Jin Yang

“…Thematic clustering revealed key research foci, including deep learning algorithms, protein–protein interaction prediction, and integrative multi-omics analysis. …”
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Production monitoring and machine tracking in underground mines based on a collision avoidance system: A case study by Artur Skoczylas, Natalia Duda-Mróz, Wioletta Koperska, Paweł Stefaniak, Paweł Śliwiński

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MLRec: A Machine Learning-Based Recommendation System for High School Students Context of Bangladesh by Momotaz Begum, Mehedi Hasan Shuvo, Jia Uddin

“…Social media and mobile devices, commonly referred to as socimedevices, have become integral to students’ daily lives, influencing both their academic performance and overall well-being. Depending on usage patterns, these technologies can positively or negatively impact students’ education. …”
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Identification of anaerobic bacterial strains by pyrolysis-gas chromatography-ion mobility spectrometry by Tim Kobelt, Jonas Klose, Rumjhum Mukherjee, Rumjhum Mukherjee, Martin Lippmann, Szymon P. Szafranski, Szymon P. Szafranski, Meike Stiesch, Meike Stiesch, Stefan Zimmermann

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The Genetic Puzzle of the Stress-Induced Cardiomyopathy (Takotsubo Syndrome): State of Art and Future Perspectives by Domenico Lio, Letizia Scola, Giusi Irma Forte, Loredana Vaccarino, Manuela Bova, Patrizia Di Gangi, Giorgia Santini, Daniela di Lisi, Cristina Madaudo, Giuseppina Novo

“…The lack of a clear Mendelian inheritance pattern suggests a multifactorial etiology and pathogenesis, likely involving complex gene–environment interactions and a polygenic background. …”
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Comprehensive Survey of Big Data Mining Approaches in Cloud Systems by Zainab Salih Ageed, Subhi R. M. Zeebaree, Mohammed Mohammed Sadeeq, Shakir Fattah Kak, Hazha Saeed Yahia, Mayyadah R. Mahmood, Ibrahim Mahmood Ibrahim

“…This will assist in the investigation of computational capacity as well as new knowledge in this area. The patterns of using big data were compared in about fifteen articles. …”
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Role of Artificial Intelligence and Machine Learning to Create Predictors, Enhance Molecular Understanding, and Implement Purposeful Programs for Myocardial Recovery by Frederick M. Lang, Benjamin C. Lee, Dor Lotan, Mert. R. Sabuncu, Veli K. Topkara

“…By identifying novel patterns in high-dimensional data, artificial intelligence (AI) and machine learning (ML) algorithms can enhance the identification of key predictors and molecular drivers of myocardial recovery. …”
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FD-GRNet: A Dendritic-Driven GRU Framework for Advanced Stock Market Prediction by Tongyan Liu, Jiayi Li, Zihang Zhang, Hang Yu, Shangce Gao

“…Future research will focus on optimizing the model for broader time series forecasting applications.…”
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MetS: an interactive application to identify metabolites in liquid chromatography-mass spectrometry experiments with data independent acquisition by Daniel Estevan Garcia-Niño, Liliana Lopez-Kleine, Federico Roda-Fornaguera

“…The application supports filtering, correlation analysis, and similarity scoring algorithms to match DIA data to user-provided metabolite mass-to-charge ratios and fragmentation patterns. …”
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Augmenting TikTok shop adoption: The mediating role of Key Opinion Consumers (KOCs) in live streaming, video content, and Artificial Intelligence (AI) recommendations by Minh Thi Hong Le, Hieu Ngoc Minh Pham, Ly Thi Truc Nguyen, Thuy Thi Xuan Le, Suong Thi Mai Nguyen

“…The findings indicate that KOCs play a crucial role in mediating TikTok use patterns and uptake. This research enhances the comprehension of media use within the framework of uses and gratification, both in terms of theoretical and empirical aspects.…”
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Application of Machine Learning Models in Optimizing Wastewater Treatment Processes: A Review by Florin-Stefan Zamfir, Madalina Carbureanu, Sanda Florentina Mihalache

“…Thus, this paper identifies gaps in the current research, discusses ML and DL algorithms in the context of optimizing wastewater treatment processes, and identifies future directions for optimizing these processes through data-driven methods. …”
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Integrating sensor networks to facilitate efficient energy management for smart grids by Arpita Nath Baruah, Malatesh S. Akkur, Jyoti Seth, Jaymeel Shah

“…Organizations are implementing Smart Energy Management Systems (SEMS) to regulate energy consumption patterns and respond to energy-saving instructions due to rising energy prices and demand. …”
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Can the number of confirmed COVID-19 cases be predicted more accurately by including lifestyle data? An exploratory study for data-driven prediction of COVID-19 cases in metropolit... by Sungwook Jung

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