A Hierarchical Archimedean Copula (HAC) model for climatic variables: an application to Kenyan data by Kevin Otieno, Linda Chaba, Linda Chaba, Evans Omondi, Evans Omondi, Collins Odhiambo, Collins Odhiambo, Bernard Omolo, Bernard Omolo

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Intelligent system for modelling climate variability by P. G. Asalkhanov, N. V. Bendik, Ya. M. Ivanyo

“…The article describes the main functions of the presented intelligent system, which expand the possibility of assessing the variability of climate characteristics by combining quantitative and qualitative information in the form of historical and archival evidence. …”
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In-cell structure and variability of pyrenoid Rubisco by Nadav Elad, Zhen Hou, Maud Dumoux, Alireza Ramezani, Juan R. Perilla, Peijun Zhang

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Analysis of effects of meteorological variables on dengue incidence in Bangladesh using VAR and Granger causality approach by Md. Jamal Hossain, Nazia Sultana, Anwesha Das, Fariea Nazim Jui, Md. Kamrul Islam, Md. Mijanoor Rahman, Mohammad Mafizur Rahman

“…BackgroundDengue fever is a serious public health issue in Bangladesh, where its incidence rises with the monsoon. Meteorological variables are believed to be responsible factors among others. …”
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Heart rate variability in university students engaged in competitive sports at the beginning of a training season by P. N. Chainikov, V. G. Cherkasova, S. V. Muraviev, А. М. Kulesh

“…Objective: to study heart rate variability in university students engaged in competitive sports at the beginning of a training season. …”
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Visit-to-visit glucose variability is associated with echocardiographic variables in people with type 2 diabetes: epidemiological and mendelian randomization approaches by Cheng-Chieh Lin, Chia-Ing Li, Chiu-Shong Liu, Chih-Hsueh Lin, Shing-Yu Yang, Tsai-Chung Li

“…The echocardiographic variables included those for cardiac structural, cardiac systolic, and diastolic function. …”
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Characterizing the effects of age, puberty, and sex on variability in resting-state functional connectivity in late childhood and early adolescence by Kelly A. Duffy, Andrea Wiglesworth, Donovan J. Roediger, Ellery Island, Bryon A. Mueller, Monica Luciana, Bonnie Klimes-Dougan, Kathryn R. Cullen, Mark B. Fiecas

“…We found decreased variability in global efficiency across the age range, and increased variability within the frontolimbic network driven primarily by those assigned female at birth (AFAB). …”
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The distribution of Coronal Plane Alignment of the Knee (CPAK) phenotypes in the Malaysian population and their correlation with demographic variables by Wai Kit Wong, Azliana Abu Bakar Sajak, Hwa Sen Chua

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Comparison of the efficiency of zero and first order minimization methods in neural networks by E. A. Gubareva, S. I. Khashin, E. S. Shemyakova

“…Numerous experiments show that the analytical calculation time of an N variable function’s gradient is approximately N/5 times longer than the calculation time of the function itself. …”
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Hydrophobic nanostructured bioaerogel filters for efficient particulate matter removal by Wafa Mustafa Saleh, Esam Bashir Yahya, Mardiana Idayu Ahmad, Abdul Khalil H. P. S.

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Long-Term Teleconnections Between Global Circulation Patterns and Interannual Variability of Surface Air Temperature over Kingdom of Saudi Arabia by Abdullkarim K. Almaashi, Hosny M. Hasanean, Abdulhaleem H. Labban

“…The empirical orthogonal function (EOF) method is employed for analyzing SAT due to its effectiveness in extracting dominant patterns of variability during the winter (DJF) and summer (JJA) seasons. …”
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An Analytical Approximation of the Stress Function for Conical Flywheels by Miguel Garcia, Onofre Orozco-López, Jesús Uribe-Chavira, Andrés Blanco-Ortega

“…The current paper addresses the lack of explicit analytical solutions for stress evaluations in variable-thickness flywheels by proposing an approximate formulation for conical profiles, where thickness varies linearly along the radius. …”
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Modular quantum signal processing in many variables by Zane M. Rossi, Jack L. Ceroni, Isaac L. Chuang

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Resolving structural variability in network models and the brain. by Florian Klimm, Danielle S Bassett, Jean M Carlson, Peter J Mucha

“…We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. …”
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Robust Group Identification and Variable Selection in Regression by Ali Alkenani, Tahir R. Dikheel

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Effects of Mental Fatigue on Gait Performance and Variability by Ali Zardosht, Jessie Daw, Lee T Atkins, C Roger James, Hyung Suk Yang

“…OBJECTIVES Mental fatigue has been shown to negatively impact physical performance, including motor skills and neuromuscular function. This study aimed to investigate the effects of mental fatigue on gait performance and variability in healthy young male adults. …”
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Speckle-Tracking Echocardiography in Dogs: Evaluating Imaging Parameters and Methodological Variability in Global Longitudinal Strain Assessment by Jonas E. Mogensen, Maiken B. T. Bach, Pernille G. Bay, Tuğba Varlik, Jakob L. Willesen, Caroline H. Gleerup, Jørgen Koch

“…Two-dimensional speckle-tracking echocardiography (2D-STE) is an advanced imaging technique that offers quantitative insights into myocardial function by analyzing the motion of speckles created during ultrasound–tissue interactions. …”
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Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson’s Disease Mobility Assessments by Rana M. Khalil, Lisa M. Shulman, Ann L. Gruber-Baldini, Sunita Shakya, Jeffrey M. Hausdorff, Rainer von Coelln, Michael P. Cummings

“…Although the total duration remains relatively consistent between trials (intraclass correlation coefficient (ICC) = 0.62 to 0.95), greater variability is seen in subtask duration and sensor-derived measures, reflected in machine learning performance and statistical differences. …”
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Improving Scheduling Efficiency: A Mathematical Approach to Multi-Operation Optimization in MSMEs by Reyner Pérez-Campdesuñer, Alexander Sánchez-Rodríguez, Margarita De Miguel-Guzmán, Gelmar García-Vidal, Rodobaldo Martínez-Vivar

“…The results show that prioritizing the objective function leads to a balanced optimization of all indicators, improving operational efficiency and reducing flow time. …”
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Morpho-functional groups as an efficient tool for monitoring and management of the Billings reservoir (São Paulo, Brazil) by Ana Carolina Peixoto Chamizo, Cacilda Thais Janson Mercante, Munique de Almeida Bispo Moraes, Clóvis Ferreira do Carmo, Matheus Barbosa Herbst de Oliveira, João Alexandre Saviolo Osti

“…Three canonical correspondence analyses were calculated aiming to examine the effect of environmental variables on the phytoplankton structure from each classification method (descriptor species, classes, and MBFGs), identifying the influence of environmental variables (independent variables) on the abundance patterns of the phytoplankton community (dependent variables). …”
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