Emission of Brominated Pollutants from Waste Printed Circuit Boards during Thermal Treatment: A Review by Jun Wan, Jia Sun, Xiang-Lin Zhao, An-Sheng Le, Peng-Bo Ren, Ming-Xiu Zhan, Xiao-Qing Lin, Tong Chen

“…The effects of raw materials, temperature, atmosphere, and reaction time on the emission of brominated pollutants are discussed, as are three methods of controlling the pollutants. It was found that when the temperature was controlled at 850–1200°C, the reaction time was greater than 2 s, the air flow rate was 3–4.5 m s−1, and the excess air coefficient was 1–2, the impact of pollutant emissions was relatively small. …”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…Our results indicate that the SCA-RF model achieved a superior performance with a root mean square error (RMSE) of 1.562 and a coefficient of determination (R²) of 0.987, compared to the HHO-RF model, which obtained an RMSE of 1.742 and an R² of 0.982. …”
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Toward accurate and scalable rainfall estimation using surveillance camera data and a hybrid deep-learning framework by Fiallos-Salguero Manuel, Soon-Thiam Khu, Jingyu Guan, Mingna Wang

“…The DSC–GRU model achieves high predictive performance, with coefficient of determination (R2) values ranging from 0.89 to 0.93 when validated against rain gauge measurements. …”
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ROLE OF FINANCIAL INSTRUMENTS IN ENSURING LIQUIDITY AND STABILITY OF THE CURRENCY MARKET OF UKRAINE IN THE CONDITIONS OF MILITARY CONFLICT by Oleksandr Zhurba

“…The research aims to identify the influence of the instruments of the National Bank of Ukraine (NBU) on the liquidity of the currency market of Ukraine within the context of long-term military conflict. The methods of regression analysis, correlation analysis, and analysis of variance were used in the study to determine the leading factors that influence the liquidity of the currency market in Ukraine in the conditions of military conflict. …”
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Substantial Impact of School Closure on the Transmission Dynamics during the Pandemic Flu H1N1-2009 in Oita, Japan. by Shoko Kawano, Masayuki Kakehashi

“…<h4>Results</h4>The model with a 3-day delay from transmission to reporting yielded the best fit using R2 (the coefficient of determination). This result suggests that the recommended period of school closure is more than 4 days. …”
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Communicative health literacy with physicians in healthcare services– results of a Hungarian nationwide survey by Frederico Epalanga Albano Israel, Ferenc Vincze, Róza Ádány, Éva Bíró

“…Our aims are to check the measurement properties of the Hungarian version of this COMM-HL questionnaire, to describe the COMM-HL of the Hungarian adult population and to investigate its determinants. Methods A total of 1205 adults completed the telephone interview in 2020 as part of the European Health Literacy Population Survey 2019–2021. …”
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Sequence‐Dependent Repolarization Is Modulated by Endogenous Action Potential Duration Gradients Rather Than Electrical Coupling in Ventricular Myocardium by Grace A. Blair, Madeline Depman, William P. Adams, Rowan O. Maisonneuve, Gregory S. Hoeker, Seth H. Weinberg, Steve Poelzing

“…SD of APD and the AT–APD slope and coefficient of determination were quantified as metrics of APD heterogeneity. …”
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Landslide susceptibility assessment based on machine learning and encoder coupling by ZHANG Mengmeng, LI Shaoda, WANG Xiao, LI Xinyue, DAI Keren

“…Twelve influencing factors were selected to construct the landslide susceptibility evaluation index system， the coefficient of determination （CF） was used to quantify the evaluation index， and noise-reducing auto-encoders （DAEs） and convolutional auto-encoders （CAE） were added to the best-performing model by comparing the logistic regression （LR） and the support vector machine（SVM） models.ResultsThe results showed that compared with the CF-LR model， the CF-SVM model， the precision （P）， F-measure， Kappa coefficient， overall accuracy （OA）， and AUC of the CF-SVM model increased by 31.9%， 1.1%， 17.1%， 8.5%， and 8.6%， respectively， After adding the DAE encoder， the recall （R）， F-measure， Kappa coefficient， and overall accuracy （OA） of the CF-SVM-DAE model increased by 8.1%， 5.8%， 8.1%， and 4%， respectively， compared to the CF-SVM model After adding CAE encoders， the recall （R）， F-measure， Kappa coefficient， and overall accuracy （OA） of the CF-SVM-CAE model increased by 0.4%， 0.2%， 0.2%， and 0.1%， respectively， compared to the CF-SVM model.ConclusionsThe CF-SVM model has higher prediction accuracy among the selected machine learning methods. …”
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Relationship between assertiveness and reporting of job errors among nurses by Leili Borimnejad, Marjan Mardani Hmouleh, Naeimeh Seyed Fatemi, Mehrdad Mostaghaci

“…Methods: This descriptive and cross sectional study was performed on 153 nurses from Fatemeh Zahra hospital of Najafabad through census sampling. …”
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Accurate estimation of permeability reduction resulted from low salinity water flooding in clay-rich sandstones by Xiaojuan Zhang, Muntadher Abed Hussein, Tarak Vora, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Farzona Alimova, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Ahmad Khalid

“…The results show that random forest and ensemble learning algorithms delivered the highest predictive accuracy, evidenced by the most substantial coefficient of determination (R2) and minimal error metrics. …”
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Evaluating the reliability and validity of the geriatric assessment of disability scale in older adults undergoing hemodialysis by Jia Wanning, He Wenwen, Yang Liu, Lu Haitao, Wang Haifeng, Dong Wan

“…Split-half reliability, as measured by the Spearman–Brown coefficient, was 0.940 for the overall scale, with corresponding coefficients of 0.943, 0.891, and 0.947 for personal life, family life, and social activity functions, respectively. …”
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The Main Factors and Trends of Urbanization in Kazakhstan: Analysis and Recommendations by N. K. Nurlanova, A. Tleuberdinova, N. Saparbek

“…Specific methods were applied to calculate the coefficients of urbanization intensity. …”
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Processing of orthogonal frequency-compensated signals transmitted via communication channels with fading by V. P. Tuzlukov

“…Thus, the classical methods for determining the generating function of moments can be directly used to determine the exact mathematical representation of the probability of error receiving signals for various types of modulation and diversity of signals.…”
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Snow albedo and its parameterization for natural systems and climate modeling by D. V. Turkov, E. D. Drozdov, A. A. Lomakin

“…When compared with the old scheme for parameterizing the albedo of snow cover in the LSM SPONSOR model, based on the dependence of the albedo only on the age of the snow, the new scheme showed a significant increase in the quality of albedo calculations: the correlation coefficients between the observed data and the calculation results are 0.78–0.83, which gives determination coefficients of 0.61–0.69. …”
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Nurses\' Performance and Related Factors in End-of-Life Care in the Intensive Care Unit: A Cross-sectional Study by Maryam Tabrizi, Masoomeh Adib, Tahereh Khaleghdoost Mohamadi, Saman Maroufizadeh

“…Based on the regression model, the total performance score of nurses regarding end-of-life care in nurses with master's education was significantly 22.28 units lower than nurses with bachelor's education (b= -22.28و 95% CI; -38.62 to -5.96, P=0.008). The coefficient of determination (R2) was 0.05, which indicates that 5.0% of the variations in the total performance score of nurses regarding end-of-life care are explained by their personal and occupational characteristics. …”
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Exploring personal, community, and societal conditions associated with South Korean new graduate nurses’ organizational socialization: a cross-sectional survey study by Jihye Song, Jeongsuk Lee, Youmin Cho, Ahyoung Jeon, Moonhee Gang

“…The results of the multiple regression analysis indicated that grit (coefficient = 0.24, p <.001), confusion in professional nursing values (coefficient = -0.18, p <.001), social support (coefficient = 0.09, p =.01), perceived social awareness of nurses (coefficient = 0.06, p =.03), and gender (female) (coefficient = -0.19, p =.002), were significantly associated with new graduate nurses’ organizational socialization, accounting for 49% of the variance. …”
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Use of Information Technology on Students' Physical Activity by Anisa Lutfiyani, Tri Anggoro, Rahmawan Santoso, Febri Wijaya

“…The coefficient of determination shows that r2 = (0.113)2 = 0.176, meaning 17.6%. …”
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ATHEROSCLEROSIS PREDICTION SYSTEM BASED ON THE IDENTIFICATION OF THE MOST SIGNIFICANT RISK FACTORS IN WORKERS OF THE MAIN PROFESSIONS OF THE COAL INDUSTRY IN THE SOUTH OF KUZBASS by Егор Сергеевич Филимонов, Ольга Юрьевна Коротенко

“…Based on work experience in harmful working conditions, impaired external respiratory function, smoking, burdened family history, obesity, increased ratio of waist circumference to hip circumference, fasting hyperglycemia, increased glycated hemoglobin, hypercholesterolemia, increased low-density lipoprotein cholesterol, triglycerides and atherogenicity coefficient, as well as a decrease in high-density lipoprotein cholesterol prognostic coefficients were calculated, by the sum of which it was possible to determine the probability of developing arterial hypertension and atherosclerosis in coal industry workers. …”
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Evaluating the performance of Random Forest, Decision Tree, Support Vector Regression and Gradient Boosting for streamflow prediction by Osahon Idemudia, Jacob Odeh Ehiorobo, Christopher Osadolor Izinyon, Idowu Ilaboya

“…From the machine learning results, random forest algorithm outperformed other methods in predicting streamflow, with a mean square error of 0.02 and a coefficient of determination of 0.98. …”
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Evaluating the performance of Random Forest, Decision Tree, Support Vector Regression and Gradient Boosting for streamflow prediction by Osahon Idemudia, Jacob Odeh Ehiorobo, Christopher Osadolor Izinyon, Idowu Ilaboya

“…From the machine learning results, random forest algorithm outperformed other methods in predicting streamflow, with a mean square error of 0.02 and a coefficient of determination of 0.98. …”
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