Assessment of left and right ventricular diastolic and systolic functions using two-dimensional speckle-tracking echocardiography in patients with coronary slow-flow phenomenon. by Yonghuai Wang, Chunyan Ma, Yan Zhang, Zhengyu Guan, Shuang Liu, Yuling Li, Jun Yang

“…However, current clinical practice tends to underestimate the impact of CSFP due to the yet unknown effect on the cardiac function. This study was performed to evaluate left ventricular (LV) and right ventricular (RV) diastolic and systolic functions, using two-dimensional (2D) longitudinal strain and strain rate, in patients with CSFP, and to determine the relationships between the thrombolysis in myocardial infarction (TIMI) frame count (TFC) and LV and RV diastolic and systolic functions.…”
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A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein by Bahareh Behkamal, Fatemeh Asgharian Rezae, Amin Mansoori, Rana Kolahi Ahari, Sobhan Mahmoudi Shamsabad, Mohammad Reza Esmaeilian, Gordon Ferns, Mohammad Reza Saberi, Habibollah Esmaily, Majid Ghayour-Mobarhan

“…In this study, we implemented a machine learning (ML)-based predictive framework to identify MetS using serum liver function tests—Alanine Transaminase (ALT), Aspartate Aminotransferase (AST), Direct Bilirubin (BIL.D), Total Bilirubin (BIL.T)—and high-sensitivity C-reactive protein (hs-CRP). …”
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Magnetic Field Distribution and Signal Decay in Functional MRI in Very High Fields (up to 9.4 T) Using Monte Carlo Diffusion Modeling by Bernd Michael Mueller-Bierl, Kamil Uludag, Philippe L. Pereira, Fritz Schick

“…Extravascular signal decay rate R2 or R2∗ as a function of blood oxygenation, geometry, and field strength was calculated using a Monte Carlo (MC) algorithm for a wider parameter range than hitherto by others. …”
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Out-of-Step Protection for a Synchronous Generator via Energy Function-Based Stability Assessment Using a Single Local Speed Measurement by Jongju Kim

“…By employing individual machine energy functions, this approach establishes a theoretical foundation for determining synchronization thresholds from the perspective of a single generator. …”
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Sex differences in functioning and disability among adults with cardiometabolic multimorbidity using Canadian longitudinal study on aging data: A cross-sectional study by Nicole I. Ketter, Isabelle Rash, Michelle C. Yang, Sarah Park, Brodie M. Sakakibara

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Conditional Moment Closure Modelling of a Lifted H2/N2 Turbulent Jet Flame Using the Presumed Mapping Function Approach by Ahmad El Sayed, Roydon A. Fraser

“…A lifted hydrogen/nitrogen turbulent jet flame issuing into a vitiated coflow is investigated using the conditional moment closure (CMC) supplemented by the presumed mapping function (PMF) approach for the modelling of conditional mixing and velocity statistics. …”
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Evaluating Activity and Chronicity Indices in Lupus Nephritis Using the Recent NIHModified Activity Index Scores: A Comprehensive Correlation Analysis with Renal Function by Rabia Saleem, Humaira Nasir, Zafar Ali, Kanza Huma Zia, Anum Iqtidar, Nadia Hassan

“…Objective: To study the correlation between activity and chronicity indices in renal biopsies and renal functions among lupus nephritis patients. Study Design: Prospective cross-sectional study. …”
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Determining Eustachian Tube Function in Mucosal Ear Disease Using Cost-Effective, Consistent, Constant, Convenient Tests: A Hospital Based Study by Sphoorthi Basavannaiah

“…Objective: Using a range of methods, the aim of this study was to measure the patency of the eustachian tube for its effectiveness in all cases of mucosal ear disease. …”
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Single-stage separation and quantitation of anionic and cationic forms of transition metals from environmental water using organo-functionalized ordered mesoporous silica by Natalia Kobylinska

“…To reused of adsorbents during four-five cycles with high adsorption capacity using HNO3 solution (1 M). At the same time, the surface area and concentration (∼4 %) of functional groups on the surface of the adsorbents unchanged after four regeneration cycles. …”
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Voice-Based Emotion Identification Based on Mel Frequency Cepstral Coefficient Feature Extraction Using Self-Organized Maps and Radial Basis Function by Asrivatun Nikmah, Auli Damayanti, Edi Winarko

“…The stages of voice-based emotion identification, including the feature extraction stage using the mel frequency cepstral coefficient, produce coefficient values, which will be used in the identification stage using the Self Organized Maps method on the Radial Basis Function.…”
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A Panel of Three MicroRNA Signatures as a Potential Biomarker for CRC Screening Based on Stages and Functional Prediction Using Bioinformatic Analysis by Syarah Syamimi Mohamed, Azmir Ahmad, Nurul Syakima Ab Mutalib, Tengku Ahmad Damitri Al-Astani Tengku Din, Md Salzihan Md Salleh, Andee Dzulkarnaen Zakaria, Zaidi Zakaria

“…Although miRNAs appear to be promising screening biomarkers, functional prediction analysis is required to shed light on their role in CRC tumorigenesis. …”
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Enabling dual-functionality material for effective anionic and cationic dye removal by using Nb2O5/MgAl-LDH nanocomposites by Tarmizi Taher, Zhongliang Yu, Elisabeth Kartini Arum Melati, Andika Munandar, Rizky Aflaha, Kuwat Triyana, Yudha Gusti Wibowo, Khairurrijal Khairurrijal, Aldes Lesbani, Aditya Rianjanu

“…These findings offer a promising alternative for fabricating dual-functional adsorbents, enhancing the effectiveness of dye removal in wastewater treatment technologies.…”
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Kinetic Modeling of Deep Oxidative Desulfurization over Functionalized UiO-66 from a Model Fuel Using Complex Reaction Theory by Bijan Barghi, Tanel Mõistlik, Deniss Panov, Anastassia Raag, Oliver Järvik, Allan Niidu

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The effect of physical exertion exercises using electrical muscle stimulation on the development of some physical and functional characteristics of women aged (40-45) years by Zuhad Fawzi, Dr. Mawahib Hameed

“…Exercise physical exertion using electrical muscle stimulation has a positive effect on the development of some physical and functional characteristics of women aged (40-45) years …”
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Eco-Friendly Dyeing and Functional Finishing of Organic Cotton Using Optimized Oolong Tea Stems (Agricultural Waste) Through Response Surface Methodology by Huiya Xu, Chen Yang, Ha-young Song

“…Furthermore, under these conditions, the color fastness and functional performance of dyed organic cotton were compared with and without chitosan as a mordant. …”
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Efficacy of Psyllaephagus pistaciae (Hymenoptera: Encyrtidae) as a Biocontrol Agent against Agonoscena pistaciae (Hemiptera: Aphalaridae) using age-specific functional response by Hamid Rahimzadeh Behzadi, Mahdi Ziaaddini, Mohammad Amin Jalali, Fateme Ranjbar

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Evaluation of the impact of the distance determination function on the results of optimization of the geographical placement of renewable energy sources-based generation using a metaheuristic algorithm by Andrei M. Bramm, Stanislav A. Eroshenko

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Advanced ENF Region Classification Using UniTS-SinSpec: A Novel Approach Integrating Sinusoidal Activation Function and Spectral Attention by Yujin Li, Tianliang Lu, Gaojun Zeng, Kai Zhao, Shufan Peng

“…The model integrates the sinusoidal activation function and spectral attention mechanism while also redesigning the model framework. …”
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Diagnostic potential of salivary microbiota in persistent pulmonary nodules: identifying biomarkers and functional pathways using 16S rRNA sequencing and machine learning by Xiao Zeng, Qiong Ma, Chun-Xia Huang, Jun-Jie Xiao, Xi Fu, Yi-Feng Ren, Yu-Li Qu, Hong-Xia Xiang, Mao Lei, Ru-Yi Zheng, Yang Zhong, Ping Xiao, Xiang Zhuang, Feng-Ming You, Jia-Wei He

“…Additionally, the PICRUSt2 algorithm was used to predict the microbial functions. Results The salivary microbial composition in pPNs group showed significantly lower α- and β-diversity compared to healthy controls. …”
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A machine learning model for predicting worsening renal function using one‐year time series data in patients with type 2 diabetes by Mari Watanabe, Shu Meguro, Kaiken Kimura, Michiaki Furukoshi, Tsuyoshi Masuda, Makoto Enomoto, Hiroshi Itoh

“…We created predictive models for patients’ primary endpoints using time series data of various variables over the input period. …”
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