Evaluation of PM2.5 Surface Concentrations Simulated by NASA’s MERRA Version 2 Aerosol Reanalysis over India and its Relation to the Air Quality Index by Chimurkar D. Navinya, V. Vinoj, Satyendra K. Pandey

“…While the Central Pollution Control Board (CPCB) measured exceedances of the national ambient air quality standards (NAAQS) on 34% of the days, MERRA-2’s prediction was only 11%, and its estimate of the annual average PM2.5 concentration across all of the sites was also negatively biased, by ~27 µg m−3. …”
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The impact of dietary fiber on colorectal cancer patients based on machine learning by Xinwei Ji, Lixin Wang, Pengbo Luan, Jingru Liang, Weicai Cheng

“…Machine learning-based CRC prediction models hold clinical value.…”
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Toward the Development of Large-Scale Word Embedding for Low-Resourced Language by Shahzad Nazir, Muhammad Asif, Shahbaz Ahmad Sahi, Shahbaz Ahmad, Yazeed Yasin Ghadi, Muhammad Haris Aziz

“…While this process represents the extracted features of corpus on vector space that enables to perform the NLP tasks such as summary generation, text simplification, next sentence prediction, etc. There exist some approaches for word embedding that consider co-occurrence and word frequency, such as Matrix Factorization, skip-gram, hierarchical-structure regularizer, and noise contrastive estimation. …”
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Rapid Hip Osteoarthritis Development in a Patient with Anterior Acetabular Cyst with Sagittal Alignment Change by Yasuhiro Homma, Tomonori Baba, Nobuhiko Sumiyoshi, Hironori Ochi, Hideo Kobayashi, Mikio Matsumoto, Takahito Yuasa, Kazuo Kaneko

“…The recognition of sagittal alignment changes and anterior acetabular cyst may play important role in prediction and prevention of the rapid hip osteoarthritis development similar to RDC.…”
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A structural health monitoring data reconstruction method based on VMD and SSA-optimized GRU model by Xiaoliang Jia, Guoyan Zhang, Zhiqiang Wang, Huacong Li, Jing Hu, Songlin Zhu, Caiwei Liu

“…Abstract In the field of Structural Health Monitoring (SHM), complete datasets are fundamental for modal identification analysis and risk prediction. However, data loss due to sensor failures, transmission interruptions, or hardware issues is a common problem. …”
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A Multiplex High-Resolution Melting (HRM) assay to differentiate Fusarium graminearum chemotypes by Lovepreet Singh, Milton T. Drott, Hye-Seon Kim, Robert H. Proctor, Susan P. McCormick, J. Mitch Elmore

“…We applied machine learning-based linear discriminant analysis (LDA) to automate the classification of chemotypes from the HRM data, achieving a prediction accuracy of over 99%. The assay is sensitive, with a limit of detection below 0.02 ng of fungal DNA. …”
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Digital Image Correlation and Reliability-Based Methods for the Design of Structural Beams Made from Recycled Concrete Using Aggregates from Precast Rejects by Jorge López-Rebollo, Evelio Teijón-López-Zuazo, Roberto García-Martin, Luis Javier Sánchez-Aparicio, Diego González-Aguilera

“…All the beams showed behaviour within the predicted range: around 49.7 kN maximum load and just over 9.3 mm maximum deflection. …”
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Enhancement of Aeroengine Combustion Chamber Air Cooling Holes Design for Emission Reduction and Pattern Factor Control by Masoud Hajivand

“…The results of a comprehensive numerical analysis of temperature uniformity and NOx and CO emission predictions in an aeroengine annular combustor liner, conducted by geometrical modifications through design changes in primary cooling air, including effusion cooling holes, are shown in the paper. …”

Tracking of Blood Pressure in Children and Adolescents in Germany in the Context of Risk Factors for Hypertension by Giselle Sarganas, Angelika Schaffrath Rosario, Claudia Niessner, Alexander Woll, Hannelore K. Neuhauser

“…BP in childhood is the strongest independent predictor of future BP but its predictive value is limited.…”
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FABP6 Expression Correlates with Immune Infiltration and Immunogenicity in Colorectal Cancer Cells by Wenping Lian, Zhongquan Wang, Yajie Ma, Yalin Tong, Xinyu Zhang, Huifang Jin, Shuai Zhao, Ruijing Yu, Shaotan Ju, Xinyun Zhang, Xiaona Guo, Tao Huang, Xianfei Ding, Mengle Peng

“…In addition, the constructed model effectively predicted the survival of CRC patients treated with and without immunotherapy. …”
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Meteorological Issues and Technological Progress in the Development of New Energy Systems by Yanbo SHEN

“…Developing meteorological forecast correction and power prediction models for wind and solar power generation stations, based on the principle of applying a tailored policy to each station, will be a crucial strategy for enhancing forecast accuracy. …”
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Study on the Creep Constitutive Model of a Sandstone Rock under the Water-Rock Interaction by Zuosen Luo, Zuoxiang Zhu, Jianlin Li, Lehua Wang, Qiao Jiang, Jingyu Zhang, Eleyas Assefa, Huafeng Deng

“…Moreover, the strong correlations between the predicted results and the experimental results show the effectiveness of the modified model to scrutinize the nonlinear creep behavior of sandstone rock. …”
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Selection of In Vivo Relevant Dissolution Test Parameters for the Development of Cannabidiol Formulations with Enhanced Oral Bioavailability by Nathan Koch, Quentin Bourcy, Olivier Jennotte, Patrice Chiap, Anna Lechanteur, Jean-Michel Cardot, Brigitte Evrard

“…Neutral media enabled a relatively good prediction of the extent of absorption observed in vivo, whereas the rate of absorption was more complicated to predict. …”
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Recent changes in ENSO’s impacts on the summertime circumglobal teleconnection and mid-latitude extremes by Shankai Tang, Shaobo Qiao, Bin Wang, Fei Liu, Xian Zhu, Taichen Feng, Guolin Feng, Wenjie Dong

“…Abstract The boreal summer circumglobal teleconnection (CGT) provides a primary predictability source for mid-latitude Northern Hemisphere climate anomalies and extreme events. …”
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Artificial intelligence and machine learning in mobile apps for mental health: A scoping review. by Madison Milne-Ives, Emma Selby, Becky Inkster, Ching Lam, Edward Meinert

“…The mobile apps investigated incorporated different artificial intelligence and machine learning techniques for a variety of purposes (risk prediction, classification, and personalisation) and aimed to address a wide range of mental health needs (depression, stress, and suicide risk). …”
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Fast Dynamic Time Warping and Hierarchical Clustering with Multispectral and Synthetic Aperture Radar Temporal Analysis for Unsupervised Winter Food Crop Mapping by Hsuan-Yi Li, James A. Lawarence, Philippa J. Mason, Richard C. Ghail

“…Thus, the development of a robust but intelligent unsupervised classification model is attractive for the long-term and sustainable prediction of agricultural yields. Here, we propose FastDTW-HC, a combination of Fast Dynamic Time Warping (DTW) and Hierarchical Clustering (HC), as a significantly improved method that requires no ground truth input for the classification of winter food crop varieties of barley, wheat and rapeseed, in Norfolk, UK. …”
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Risk factor assessment of prediabetes and diabetes based on epidemic characteristics in new urban areas: a retrospective and a machine learning study by Li Xu, Xiangcheng Sun, Ning Wang, Yiyi Wang, Yan Li, Chuan Zhang

“…After the model was trained, the precision and recall rate of the prediction reached 0.76 and 0.86, respectively, with an F1 score of 0. 81. …”
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Error Correction of Meteorological Data Obtained with Mini-AWSs Based on Machine Learning by Ji-Hun Ha, Yong-Hyuk Kim, Hyo-Hyuc Im, Na-Young Kim, Sangjin Sim, Yourim Yoon

“…Severe weather events occur more frequently due to climate change; therefore, accurate weather forecasts are necessary, in addition to the development of numerical weather prediction (NWP) of the past several decades. A method to improve the accuracy of weather forecasts based on NWP is the collection of more meteorological data by reducing the observation interval. …”
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Machine Learning-Based Classification and Statistical Analysis of Liver Cancer: A Comprehensive Study of Model Performance and Clinical Significance by Pratyush Kumar MAHARANA, Tapan Kumar BEHERA, Pradeep Kumar NAIK

“…Conclusion: After performing the complete process, we conclude that the extra tree classifier out of 17 models is the most suitable machine learning algorithm for liver cancer prediction. …”
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Estimation level of public welfare on the basis of methods of intellectual analysis by S. Kozlovskyi, L. Nikolenko, O. Peresada, O. Pokhyliuk, O. Yatchuk, N. Bolgarova, O. Kulhanik

“…Developed mathematical model for assessment of the level of public welfare of Ukraine and made a prediction of the indicator by 2024 on the basis of the above indices. …”
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