L-arginine Supplementation in Endurance Athletes: A Systematic Review of Recovery Mechanisms and Performance Enhancement by Łukasz Karoń, Anna Ewa Zygmunt, Karolina Karoń, Wojciech Grabowski, Grzegorz Drapała, Emilia Pedrycz, Daria Pedrycz

“…Recognized for its multifaceted roles in cardiovascular, immune, and metabolic functions, L-arginine serves as a precursor to biologically active molecules, including nitric oxide (NO), creatine, and polyamines, which are integral to muscle function and recovery. …”
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The association between age and long-term quality of life after curative treatment for prostate cancer: a cross-sectional study by Reidun Sletten, Ola Berger Christiansen, Line Merethe Oldervoll, Lennart Åstrøm, Håvard Kjesbu Skjellegrind, Jūratė Šaltytė Benth, Øyvind Kirkevold, Sverre Bergh, Bjørn Henning Grønberg, Siri Rostoft, Asta Bye, Paul Jarle Mork, Marit Slaaen

“…We found no statistically significant independent association between age at treatment and global QoL, PF or side effects, except for sexual function (regression coefficient [RC] −0.77; p < 0.001) and hormonal/vitality (RC 0.30; p = 0.006) function. …”
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Comparative Genomics of Rhamnolipid Synthesis and Monoaromatic Hydrocarbon Tolerance Genes in Environmental Pseudomonas aeruginosa strains [version 2; peer review: 2 approved] by Sandro B. Martel-Torres, Camila Castillo-Vilcahuaman, ROGER A. PALOMINO HUARCAYA, Susana M. Gutiérrez Moreno, Fernando A. Merino Rafael

“…The BTEX (benzene, toluene, ethylbenzene, and xylene) are toxic hydrocarbons requiring efficient microbial degradation for bioremediation. …”
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Association between metabolic parameters and erection in erectile dysfunction patients with hyperuricemia by Guo-Wei Du, Pei-Ning Niu, Zhao-Xu Yang, Xing-Hao Zhang, Jin-Chen He, Tao Liu, Yan Xu, Jian-Huai Chen, Yun Chen

“…Fasting plasma glucose (β = −0.628, P < 0.001), uric acid (β = −0.552, P < 0.001), triglycerides (β = −0.088, P = 0.047), low-density lipoprotein cholesterol (β = −0.164, P = 0.027), glycated hemoglobin (HbA1c; β = −0.562, P = 0.012), and smoking history (β = −0.074, P = 0.037) exhibited significant negative impacts on erectile function. The coefficient of determination (R²) for the model was 0.239, and the adjusted R² was 0.230, indicating overall statistical significance (F-statistic = 26.52, P < 0.001). …”
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Reconfiguration of dynamic brain networks in heart failure with preserved ejection fraction: Linking neurovascular coupling and cardiac dysfunction by Xiulin Liang, Qinghua Zhang, Chuanlong Zhang, Jingjing Liu, Pengcheng Sang, Qing Mao, Lei Wang

“…Results: (1) Static network topology properties exhibited significantly decreased local network efficiency among patients with HFpEF. The connectivity strength and information processing efficiency were diminished in the left parahippocampal gyrus, left cingulate gyrus, and right insular gyrus brain regions, and improved in the left thalamus, right fusiform gyrus, and right precuneus regions. (2) Dynamic network topology properties of patients with HFpEF showed decreased variability in critical nodes and brain subregions (e.g., the superior frontal gyrus, left amygdala, and left fusiform gyrus) and compensatory increases in the variability of specific regions (e.g., right insular gyrus, right postcentral gyrus, and right temporal gyrus). (3) In HFpEF, the static and dynamic functional brain network topology properties of the fusiform gyrus, cingulate gyrus, superior temporal gyrus, precuneus, parahippocampal gyrus, insular gyrus, and amygdala regions were significantly correlated with cardiac structural and functional indices, such as LVDd, LVMI, and E/e′ ratio. …”
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Analisis Penerimaan Learning Management System Institut Teknologi Garut Menggunakan Technology Acceptance Model by Asri Mulyani, Dede Kurniadi, Mita Hidayani Putri

“…It is hoped that the results of this research can be used as a reference for developers to continue to optimize the functionality of the Learning Management System so that it can be used optimally. …”
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Stability analysis of the inner dump with inclined base considering anti-slip pillar by Li MA, Xinyu JIN, Qifeng ZHANG, Kaisheng JIANG, Mengbo LI, Yan HU

“…Taking the angle of inclination of the basement stratum and the discharge height of the soil disposal site as the variables for research, it was obtained that the angle of inclination of the basement stratum α or the height of the soil disposal H and the slope stability coefficient Fs were negatively correlated with the inverse proportionality function, the angle of inclination of the basement stratum had a greater influence on the slope stability, and the height of the discharge height of the soil disposal site had a second greater influence on the stability of the slope. …”
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Model Evaluasi Usability Menggunakan Confirmatory Factor Analysis pada KRS Online by Endah Ratna Arumi, Pristi Sukmasetya, Agus Setiawan

“…Abstract Nowadays, the development of computer software systems is not just a functional analysis. At this time, the software interface has begun to become a focus in software development. …”
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rcprd: An R package to simplify the extraction and processing of Clinical Practice Research Datalink (CPRD) data, and create analysis-ready datasets. by Alexander Pate, Rosa Parisi, Evangelos Kontopantelis, Matthew Sperrin

“…Functions are available to extract common variable types (e.g., history of a condition, or time until an event occurs, relative to an index date), and more general functions for database queries, allowing users to define their own variables for extraction. …”
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Intelligent hybrid method to predict generated power of solar PV system by Prashant Singh, Navneet Kumar Singh, Asheesh Kumar Singh

“…The input solar PV power data are broken down into intrinsic mode functions (IMFs) using EMD technique is fed into the PSO-ANFIS, along with important meteorological variables. …”
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Forecasting Wind Power Generation Using Artificial Neural Network: “Pawan Danawi”—A Case Study from Sri Lanka by Amila T. Peiris, Jeevani Jayasinghe, Upaka Rathnayake

“…This paper develops artificial neural network (ANN) models to forecast wind power generation in “Pawan Danawi”, a functioning wind farm in Sri Lanka. Wind speed, wind direction, and ambient temperature of the area were used as the independent variable matrices of the developed ANN models, while the generated wind power was used as the dependent variable. …”
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Spatial pattern of Trees in the Riparian Forests (Case Study: Wildlife Refuge of Karkhe) by Shaieste Gholami

“…This result showed that there was the small-scale variability and important proportion of unexplained variance. …”
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An assessment of the likely impact of strain-related phenotypic plasticity on hominin fossil species identification by M. Collard, S.J. Lycett

“…We divided the measurements into three groups: measurements of features subject to high masticatory strain, measurements of features subject to low-to-moderate masticatory strain, and measurements of features that do not remodel and therefore are not prone to strain-related phenotypic plasticity. Next, we used the coefficient of variation and ANOVA to investigate whether masticatory strain is a cause of variability. …”
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Supplier Selection and Order Allocation in A Pharmaceutical Wholesaler by Ryan Hikmah Fadilla, Cucuk Nur Rosyidi, Wakhid Ahmad Jauhari

“…As part of the system modeling, a sensitivity analysis was performed to explore the effects of specific parameters on the objective function and decision variables, assessing variations in inventory costs, shortage costs, and demand. …”
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Calculation and Forecast of Glacial Feeding in River Basins by V. G. Konovalov

“…Index δ for the upper reaches of the Rhone River turned out to be not only a representative characteristic of changes in the vegetation period and annual runoff of the river, but also an efficient argument for the super-long-range prediction of these variables for 2025–2054 years.…”
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Bivariate Epanechnikov-exponential distribution: statistical properties, reliability measures, and applications to computer science data by H. M. Barakat, M. A. Alawady, I. A. Husseiny, M. Nagy, A. H. Mansi, M. O. Mohamed

“…The statistical properties of the EP-EX-FGM model are examined, including product moments, coefficient of correlation between the internal variables, moment generating function, conditional distribution, concomitants of order statistics (OSs), mean residual life function, and vitality function. …”
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Optimization of medium components for the production of exopolysaccharide by Lycoperdon pyriforme Schaeff.: Pers. using response surface methodology by MA Xiaokui, JIANG Hua, LI Junzhi, CHEN Yong, HE Xiaojing

“….: Pers. is one of medicinal macro-fungi, which has become an attractive topic as a functional food and as a source for the development of drugs and nutraceuticals. …”
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Modeling biogeochemical processes in the Azov Sea using statistically processed data on river flow by A. I. Sukhinov, Y. V. Belova, A. V. Nikitina, A. M. Atayan

“…In the course of statistical analysis of the series of long-term observations over river flows, the values of the following indicators were found: skewness coefficient, degree of kurtosis, variance and standard deviation, coefficient of variation, autocorrelation coefficient, Neumann ratio, and Anderson criterion.Results. …”
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Explaining the COVID19 mortality growth rate: an empirical analysis of Israeli cities by Yuval Arbel, Yifat Arbel, Amichai Kerner, Miryam Kerner, Miryam Kerner

“…These include population size, median age, a socio-economic ranking at a city level, a date variable and a dummy variable that equals 1 for post-vaccination and 0 for pre-vaccination era.MethodRegression analysis, where each variable is converted to the standard normal distribution function. …”
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Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost by Ji XU, Zicheng XIN, Mo LAN, Wenhui LIN, Bo ZHANG, Qing LIU

“…The MM–BO–XGBoost model demonstrates excellent training efficiency and prediction performance.Conclusion The analysis of the mechanism of the VD furnace refining process and Pearson correlation analysis are conducted, and the input variables for the prediction model of VD furnace endpoint liquid steel temperature are identified. …”
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