Methods Of Analyses Research Articles

Making decisions on the basis of data science in managing social and economic systems

Aim. To identify the prospects and possible areas of data science use in the decision-making process in the management of social and economic systems.Objectives. To analyze existing approaches and promising directions of data science use; to analyze methods that allow to obtain real-time data for decision-making, to identify gaps and shortcomings; to briefly formulate conclusions relevant for practitioners and policy makers in the process of decision-making based on data science.Methodology. The authors analyzed the scientific literature, applied methods of logical analysis and interpretation of data.Results. In the course of the research, it was found that data science makes a significant contribution to the global transformation of society, allowing solving urgent problems of socioeconomic development. Methods that facilitate the acquisition of real-time data increase the effectiveness of decisions in the management of social and economic systems. These methods were analyzed, their advantages and disadvantages were identified, and examples of their use were presented. The key data requirements were defined: confidentiality, ethics, and security. A range of new questions for future research in the context of the topic under consideration was proposed.Conclusions. The results obtained contribute to the theoretical development of new approaches to the application of data science, as well as the practical use of best practices in cases of decision-making in the management of social and economic systems. These results can form the basis for the design and implementation of solutions by policy makers and practitioners.

ANALISIS KUALITAS PELAYANAN SISTEM X-RAY PADA PT PELINDO CABANG BENOA

This study aims to assess the service quality of the X-ray system at Benoa Port and provide recommendations for improving service quality at Benoa Port. The analysis methods used are the Service Quality (Servqual) method to identify gaps between the perceptions and expectations of passengers regarding service quality at Benoa Port and the Importance Performance Analysis (IPA) method to determine service improvement priorities. The sample of this study consisted of 96 cruise passengers in 2024. The result of the research using the servqual method indicate that there are gaps in all dimensions. The highest gap is in the tangible dimension with -0,49 and the lowest gap is in the assurance dimension with a gap of -0,24. Overall the average perception score is 3,80 and the average expectation score is 4,19, resulting in a gap of -0,39 and an average Q score of 0,91 indicating that the service quality provided almost meets the passengers expectations but is not yet perfect. The analysis result using Importance Performance Analysis (IPA) methode show a conformity rate (TKi) between importance and performance of 93,65%, indicating that the quality of the X-ray service system at Benoa Port meets the passengers expectations but still requires improvements. Based on the Cartesian Diagram, there are 5 attributes located in quadrant I, which means that improvements are necessary, consisting of the dimensions of tangibles, responsiveness, and empathy

Did Covid-19 Pandemic Raised Tax Incomes in Bad Economic Situations?

The fact that COVID-19 pandemic affected economic situation is known widely, but many companies actually can use ratios for measuring financial situation. If we look deeper, financial ratios can give actual fact about the financial performance periodically. The aim of this research is to find out whether liquidity ratios, Solvability ratios, activity ratios, profitability ratios, and tax ratios have an effect on financial performance. This research was conducted on companies listed on the Indonesia Stock Exchange in 2019 - 2023 with a sample of 117 companies for five years. Thus, the number of samples used in this research was 585. The independent variables in this research were liquidity ratios, Solvability ratios, activity ratios, profitability ratios, and tax ratios, while the dependent variable was financial performance. The data analysis method uses the difference test analyze method with SPSS version 26 software. The results of different tests for liquidity ratios show that there is no significant difference between the years before the COVID-19 pandemic, during the COVID-19 pandemic and after the COVID-19 pandemic. The results of different tests for the Solvability ratios, activity ratios, profitability ratios, and tax ratios showed that there was no significant difference between the years before the COVID-19 pandemic, during the COVID-19 pandemic and after the COVID-19 pandemic.

PENGARUH E-COMMERCE, LITERASI KEUANGAN, DAN LITERASI DIGITAL TERHADAP PERILAKU KONSUMTIF MAHASISWA

This study aims to examine whether there is an influence of e-commerece, financial literacy, digital literacy on consumtive behaviour. The population in this study were active accounting students of Muhamadiyah University The number of samples in this study were 77 respondents. The sampling technique uses simple random sampling method. The research method used is quantitative with primary data sources. The methode of data analysis uses multiple linear regression analysis with SPSS version 27. The results of this study provide evidence that partially the e-commerce variable has a positive effect on consumptive behavior, while the financial literacy and digital literacy variables have a negative effect on consumptive behavior. Simultaneously e-commerce variables, financial literacy and digital literacy have a significant effect on consumptive behavior

Testosterone with Silymarin Improves Diabetes-obesity Comorbidity Complications by Modulating Inflammatory Responses and CYP7A1/ACC Gene Expressions in Rats.

The co-morbidity of DMOB has become increasingly problematic among the world's population because of a high-calorie diet and sedentary lifestyle. DMOB is associated with lower testosterone (TN) levels, the male sex hormone. The phytochemical compound silymarin (SN) exerts antidiabetic activity by modifying β-cells and anti-obesity activity by inhibiting adipogenesis by methylxanthine. The goal of this study was to find out how well testosterone (TN) with silymarin (SN) protects against oxidative stress and inflammation in the liver of the experimental rats with type 2 diabetes (T2D) and obesity (DMOB). The present study evaluates the efficacy of TN and SN combination (TNSN) on the levels of the potential parameters, such as body mass, serum marker enzymes, fasting glucose levels, HbA1c levels, lipid profile, enzymatic and non-enzymatic antioxidants, proinflammatory cytokines, gene expression pathways, and histopathology in a DMOB comorbidity rat model. Male Sprague-Dawley (SD) rats were fed a high-fat diet (HFD) for 20 weeks with an administration of a single dose of streptozotocin (STZ) i.p. injection (30 mg/kg) on the 9th week of the study. The procedure was to develop the DMOB co-morbidity model in the experimental animals. Co-treatment of TN and SN administration were followed throughout the experiment. Rats were sacrificed after overnight fasting to collect serum and liver tissue samples. Samples were analyzed using a clinical chemistry automated analyzer, spectrophotometry, and quantitative real-time PCR (qPCR) methods and protocols. Analyses of body mass changes, serum marker enzymes, fasting glucose levels, HbA1c levels, lipid profiles, enzymatic and non-enzymatic antioxidants, TNF-α, IL-6, adiponectin, CYP7A1, ACC expression pathways, and histopathology showed significant abnormal levels (P ≤ 0.05) in the pathological group. These were efficiently treated to normal by the administration of TNSN. These results concluded that TNSN exerted protective efficacy against the liver abnormalities in the co-morbidity of the DMOB rat model.

Characterization of pressure-dependent nonlinear bending behavior of yarns and its application in modeling the compression of 2D woven fabrics

This paper investigates the pressure-dependent nonlinear bending behavior of yarns, which is essential for the application of the virtual fiber modeling (VFM) method in the mechanical analyses of fabrics. An experimental method, along with a theoretical model based on classical beam theory, is presented to characterize the varying bending stiffness of yarns under different pressures. A tailored beam user element is then developed, incorporating the nonlinear bending behavior and combined with a truss element to create a physics-based virtual fiber formulation. Utilizing this formulation, the original kinematic VFM method is extended for modeling the mechanical response of 2D woven fabrics under compression. The predicted results of the proposed model closely match the reported experiment, demonstrating the significance of introducing the nonlinear bending behavior of yarns. This method can be a valuable tool for the fabric compression process and generating realistic mesoscale geometries for textile composites.

An alignment- and reference-free strategy using k-mer present pattern for population genomic analyses

ABSTRACT Pangenomes are replacing single reference genomes to capture all variants within a species or clade, but their analysis predominantly leverages graph-based methods that require multiple high-quality genomes and computationally intensive multiple-genome alignments. K-mer decomposition is an alternative to graph-based pangenomes. However, how to directly use k-mers for the population genetic analyses is unknown. Here, we developed a novel strategy that uses the variants of k-mer count in the genome for population analyses. To test the effectivity of this method, we compared it directly to the SNP-based method on the analysis of population structure and genetic diversity of 267 Saccharomyces cerevisiae strains within two simulated datasets and a real sequence dataset. The population structure identified with k-mers recapitulates that obtained using SNPs, indicating the effectiveness of k-mer-based approach, and higher genetic diversity within real dataset supported k-mers contained more genetic variants. Based on k-mer frequency, we found not only SNP but also some insertion/deletion and horizontal gene transfer (HGT) fragments related to the adaptive evolution of S. cerevisiae. Our study creates a framework for the alignment- and reference-free (ARF) method in population genetic analyses, which will be more pronounced in the species with no complete genome or highly diverged species.

The association between hematologic traits and aneurysm-related subarachnoid hemorrhage: a two-sample mendelian randomization study.

Several hematologic traits have been suggested to potentially contribute to the formation and rupture of intracranial aneurysms (IA). The purpose of this study is to explore the causal association between hematologic traits and the risk of IA. To explore the causal association between hematologic traits and the risk of IA, we employed two-sample Mendelian randomization (MR) analysis. Two independent summary-level GWAS data were used for preliminary and replicated MR analyses. The inverse variance weighted (IVW) method was employed as the primary method in the MR analyses. The stabilities of the results were further confirmed by a meta-analysis. In the preliminary MR analysis, hematocrit, hemoglobin concentration (p = 0.0047), basophil count (p = 0.0219) had a suggestive inverse causal relationship with the risk of aneurysm-associated subarachnoid hemorrhage (aSAH). The monocyte percentage of white cells (p = 0.00956) was suggestively positively causally correlated with the risk of aSAH. In the replicated MR analysis, only the monocyte percentage of white cells (p = 0.00297) remained consistent with the MR results in the preliminary analysis. The hematocrit, hemoglobin concentration, and basophil count no longer showed significant causal relationship (p > 0.05). Meta-analysis results further confirmed that only the MR result of monocyte percentage of white cells reached significance in the random effect model and fixed effect model. None of the 25 hematologic traits was causally associated with the risk of unruptured intracranial aneurysms (uIA). This study revealed a suggestive positive association between the monocyte percentage of white cells and the risk of aSAH. This finding contributes to a better understanding that monocytes/macrophages could participate in the risk of aSAH.

Towards optimal use of the explicit [formula omitted]-Bathe time integration method for linear and nonlinear dynamics

In an earlier publication, we proposed a new explicit time integration scheme, the β1/β2-Bathe method, which is simple in its formulation and showed remarkable accuracy in the solution of problems [1]. A particular strength of the method is that it can directly be used as a first-order or second-order scheme by a change of the values of β1 and β2. While good results are obtained with reasonable values of β1 and β2, for excellent accuracy better values of the parameters need to be chosen. We propose in this paper values of β1 and β2 for the first-order scheme, best used in wave propagation analyses, and separate values for the second-order scheme, best used in analyses of structural vibrations. In each case, one set of values of (β1,β2) is given and to possibly improve the results only one of the parameters needs to be changed, that is, β1 for wave propagations and β2 for structural vibrations, making the scheme a one-parameter method. Another strength of the procedure is that physical damping can directly be included in the solution, the effect of which on the stability and accuracy of the solutions we analyze in the paper. The use of the solution scheme in nonlinear analysis is, as we show in the paper, a simple extension from linear analysis. Finally, we give various solutions using the explicit β1/β2-Bathe method in linear and nonlinear analyses to illustrate the performance of the method with the given recommendations for its use.

Case weighted power priors for hybrid control analyses with time-to-event data.

We develop a method for hybrid analyses that uses external controls to augment internal control arms in randomized controlled trials (RCTs) where the degree of borrowing is determined based on similarity between RCT and external control patients to account for systematic differences (e.g., unmeasured confounders). The method represents a novel extension of the power prior where discounting weights are computed separately for each external control based on compatibility with the randomized control data. The discounting weights are determined using the predictive distribution for the external controls derived via the posterior distribution for time-to-event parameters estimated from the RCT. This method is applied using a proportional hazards regression model with piecewise constant baseline hazard. A simulation study and a real-data example are presented based on a completed trial in non-small cell lung cancer. It is shown that the case weighted power prior provides robust inference under various forms of incompatibility between the external controls and RCT population.

Covariance Matrix Estimation for High-Throughput Biomedical Data with Interconnected Communities

Estimating a covariance matrix is central to high-dimensional data analysis. Empirical analyses of high-dimensional biomedical data, including genomics, proteomics, microbiome, and neuroimaging, among others, consistently reveal strong modularity in the dependence patterns. In these analyses, intercorrelated high-dimensional biomedical features often form communities or modules that can be interconnected with others. While the interconnected community structure has been extensively studied in biomedical research (e.g., gene co-expression networks), its potential to assist in the estimation of covariance matrices remains largely unexplored. To address this gap, we propose a procedure that leverages the commonly observed interconnected community structure in high-dimensional biomedical data to estimate large covariance and precision matrices. We derive the uniformly minimum variance unbiased estimators for covariance and precision matrices in closed forms and provide theoretical results on their asymptotic properties. Our proposed method enhances the accuracy of covariance- and precision-matrix estimation and demonstrates superior performance compared to the competing methods in both simulations and real data analyses.

Exergetic Analyses of Detonation Engine Cogeneration Plants

Efficiency improvements are very important in all research and technology. Detonation engines are high technology devices. In the last decades they attracted attention by many researchers. However, detonation engines for cogeneration are not researched efficiently. This article is about the detonation engines cogeneration cycles which analysed by using 1. and 2. law of thermodynamics and exergy analyses methods by the authors. The exergetic performance analyses, their advantage and disadvantages of the ZND-HRSG detonation engine cogeneration cycles were obtained. The exergetic performance analyses were done for various excess air rates to obtain the variations of the combustion exit pressures and temperatures, exergy efficiencies, electric heat rates, SFC and other parameters of their performance. Also, an optimization analysis was done for the ZND-HRSG by searching the optimum values for different excess air rates. The results showed that, the ZND-HRSG cycle have the optimum values of the performance at 1.6-1.8 of the excess air rates.

Application of EEM fluorescence spectroscopy for characterizing organic DBP precursors in different water sources: a review

Abstract Disinfection by-products (DBPs), generated from the reaction of disinfectants with DBP precursors, have been found to pose unintentional risks to human health. Considering that the concentration and speciation of DBPs formed during disinfection will be affected by the content and composition of dissolved organic matter (DOM), widespread concern about the characteristics of DBP precursors in water sources have been prompted. Three-dimensional excitation–emission matrix (EEM) can quickly and efficiently determine the properties and composition of DOM in water, and thus is generally used to investigate the origin of DBP precursors in water sources. This study overviews the fluorescent properties of different DBP precursors, summarizes the application of different EEM interpretation methods in DBP precursors and analyses the key factors affecting the correlation between the fluorescent components and DBP precursors (e.g., natural organic matter, algal organic matter, effluent organic matter and organic matter derived from other sources). A series of factors, including composition of fluorophores, bromide concentration, spatio-temporal characteristics and disinfectant types, could impact the correlation between DBP formation potential and fluorescent components. As for future research needs, it is of significance to select suitable fluorescence analysis methods and investigate the combination of EEM with other characterization technologies based on different situations.

Leucine rich repeat LGI family member 3: Integrative analyses support its prognostic association with pancreatic adenocarcinoma.

Leucine rich repeat LGI family member 3 (LGI3) is a member of the LGI protein family. Previous studies of our group have reported that LGI3 is expressed in adipose tissue, skin and brain, and serves as a multifunctional cytokine. LGI3 may also be involved in cytokine networks in various cancers. This study aimed to analyze differentially expressed genes in pancreatic adenocarcinoma (PAC) tissues and PAC cohort data in order to evaluate the prognostic role of LGI3. The expression microarray and the PAC cohort data were analyzed by bioinformatic methods for differential expression, protein-protein interactions, functional enrichment and pathway analyses, gene co-expression network analysis, and prognostic association analysis. Results showed that LGI3 expression was significantly reduced in PAC tissues. Nineteen upregulated genes and 31 downregulated genes in PAC tissues were identified as LGI3-regulated genes. Protein-protein interaction network analysis demonstrated that 92% (46/50) of the LGI3-regulated genes that were altered in PACs belonged to a protein-protein interaction network cluster. Functional enrichment and gene co-expression network analyses demonstrated that these genes in the network cluster were associated with various processes including inflammatory and immune responses, metabolic processes, cell differentiation, and angiogenesis. PAC cohort analyses revealed that low expression levels of LGI3 were significantly associated with poor PAC prognosis. Analysis of favorable or unfavorable prognostic gene products in PAC showed that 93 LGI3-regulated genes were differentially associated with PAC prognosis. LGI3 expression was correlated with the tumor-infiltration levels of various immune cells. Taken together, these results suggested that LGI3 may be a potential prognostic marker of PAC.

How authors select covariates in the multivariate analysis of cancer studies in 10 oncology journals in Korea: a descriptive study

Purpose: Cancer is the leading cause of death in Korea, leading many investigators to focus on cancer research. We present the current practice of variable selection methods for multivariate analyses in cancer studies recently published in major oncology journals in Korea.Methods: We included observational studies investigating associations between exposures and outcomes using multivariate analysis from 10 major oncology journals published in 2021 in KoreaMed, a Korean electronic database. Two reviewers independently and in duplicate performed the reference screening and data extraction. For each study included in this review, we collected important aspects of the variable selection methods in multivariate models, including the study characteristics, analytic methods, and covariate selection methods. The descriptive statistics of the data are presented.Results: In total, 107 studies were included. None used prespecified covariate selection methods, and half of the studies did not provide enough information to classify covariate selection methods. Among the studies reporting selection methods, almost all studies only used data-driven methods, despite having study questions related to causality. The most commonly used method for variable selection was significance in the univariate model, with the outcome as the dependent variable.Conclusion: Half of the included studies did not provide sufficient information to assess the variable selection method, and most used a limited data-driven method. We believe that the reporting of covariate selection methods requires improvement, and our results can be used to educate researchers, editors, and reviewers to increase the transparency and adequacy of covariate selection for multivariable analyses in observational studies.

A controlled randomized trial with a 12-week follow-up investigating the effects of medium-frequency neuromuscular electrical stimulation on pain, VMO thickness, and functionality in patients with knee osteoarthritis

BackgroundOne of the major contributors to disability in Knee osteoarthritis (KOA) patients is weakness in the Quadriceps Femoris muscle. Neuromuscular electrical stimulation (NMES) has been used in rehabilitation for patients suffering from muscle weakness. Thus, the purpose of the study was to assess the effectiveness of NMES and exercise therapy, for improving pain, muscle weakness and function among patients with KOA.MethodsA randomized controlled trial was conducted with 75 female patients diagnosed with KOA. Participants were divided into three intervention groups: NMES-only, exercise therapy (Exs) alone, and a combination of NMES and exercise (NMES + Exs). All patients underwent 12 supervised treatment sessions, three times a week. Outcome measures included pain intensity measured by visual analog scale (VAS), knee flexion range of motion (FROM), thigh muscle girth (TG), thickness of the Vastus Medialis Oblique (VMO), timed up and go test (TUG), six-minute walk test (6MWT), and WOMAC scores. Statistical analyses (ANOVA and Kruskal–Wallis) methods were done to compare the amounts at the baseline, immediately after treatment and after 12 weeks.ResultsThe NMES group exhibited a significant reduction in pain at the 12-week follow-up compared to the other groups(p = 0.022). The NMES + Exs group showed better outcomes in terms of FROM, TG, and VMO thickness post-intervention (p < 0.0001, p < 0.004, p = 0.003, respectively) and at the 12-week follow-up (p < 0.0001, p < 0.0001, p < 0.0001, respectively). Additionally, NMES was superior in improving TUG and 6MWT post-intervention (p < 0.0001, p = 0.038, respectively) and during the follow-up assessments (p < 0.0001, p = 0.029, respectively). The NMES + Exs group achieved better WOMAC stiffness scores at both post-intervention and follow-up evaluations (p < 0.0001, p < 0.0001, respectively). Furthermore, at the 12-week follow-up, NMES + Exs group outperformed the others in WOMAC pain and function subscales (p = 0.003, p = 0.017, respectively), while the NMES group demonstrated better WOMAC total scores compared to the other groups (p = 0.007).ConclusionThe combination of NMES and exercise seems to be an efficient approach for managing KOA, as it enhances knee flexion range and TG, increases VMO thickness, and improves WOMAC scores. On the other hand, NMES alone was found to be effective in improving the physical function of KOA patients.Trial registrationIRCT20101228005486N7 (06–02-2020).

Skeletal Muscle Evaluation in Patients With Acromegaly.

Patients with acromegaly are characterized by chronic exposure to high growth hormone (GH) and insulin-like growth factor-1 levels, known for their anabolic effect on skeletal muscle. Therefore, an increased skeletal muscle mass could be hypothesized in these individuals. Herein, we have performed a systematic revision of published evidence regarding skeletal muscle mass, quality, and performance in patients with acromegaly. A systematic review of the literature in the PubMed database up to September 1, 2023, was conducted with the following query: acromegaly AND ("muscle mass" OR "skeletal muscle"). We excluded studies that did not compare different disease states or used nonradiological methods for the skeletal muscle analyses, except for bioelectrical impedance analysis. Fifteen studies met the inclusion criteria. A total of 360 patients were evaluated for skeletal muscle mass, 122 for muscle fatty atrophy, and 192 for muscle performance. No clear evidence of increased skeletal muscle mass in patients with active disease compared to control or healthy individuals emerged. As for skeletal muscle quality, we observed a trend toward higher fatty infiltration among patients with acromegaly compared to healthy participants. Likewise, patients with active disease showed consistently worse physical performance compared to control or healthy individuals. Skeletal muscle in acromegaly has lower quality and performance compared to that of healthy individuals. The small number of published studies and multiple confounding factors (eg, use of different radiological techniques) contributed to mixed results, especially regarding skeletal muscle mass. Well-designed prospective studies are needed to investigate skeletal muscle mass in patients with acromegaly.

The role of lifestyle factors, biological sex, and racial identity for (visually induced) motion sickness susceptibility: Insights from an online survey

Motion sickness (MS) and visually induced motion sickness (VIMS) are common side-effects when travelling or when using visual devices, respectively. A variety of individual factors may determine one’s susceptibility to MS/VIMS. Here, the role of lifestyle factors including video-game usage, physical activity, diet, and substance use on self-reported susceptibility to MS/VIMS was investigated. Additionally, the roles of biological sex and racial identity on the overall prevalence of MS/VIMS were analyzed. A total of 711 responses to an online survey were collected from adults between the ages of 17–49 years. Methods of analyses included correlations, comparison tests, and multiple regressions. The results showed that, overall, VIMS is a prevalent issue for most participants, with approximately 24 % of users reporting nausea at least sometimes when using visual displays. Although some lifestyle factors (video game usage, assorted dietary elements) were identified as potentially relevant for MS/VIMS susceptibility, these factors only explained a minimal amount of the variance in MS/VIMS susceptibility. Significant sex differences were found, with female participants reporting higher susceptibility for MS/VIMS than male participants. Additionally, East Asians participants reported higher MS susceptibility. Our findings do not suggest that lifestyle factors are prominent predictors for the susceptibility of VIMS and MS.

Healthcare and health protection institutions in the context of preserving the health capital of the elderly: Evidence from Russian regions

Subject. This article discusses the issues of State policy in the field of healthcare, the problems of increasing life expectancy, and the development of a network of medical institutions in the regions of Russia. Objectives. The article aims to analyze some quantitative and qualitative characteristics of the current system of medical care in Russia. Methods. For the study, we used the methods of statistical and correlation analyses. Results. The article finds that the inequality of the elderly in health is due to regional differences in the efficiency of the functioning of medical institutions. Conclusions. Significant differences in the availability of medical care across the constituent entities of the Russian Federation hinder the successful implementation of projects aimed at solving the country's demographic problems.

Parameters of sustainability of Russian regions: State and vectors of development in relation to the least stable group

Subject. This article considers the region as a dynamic system. Objectives. The article aims to group the regions of Russia according to the level of stability and determine the prospects for the economic development of these groups from the systems theory point of view. Methods. For the study, we used the methods of logical, cluster, comparative, correlation and regression analyses. Results. The article divides the regions of Russia into six groups (virtual clusters) depending on the level of socio-ecological-economic stability. A reduction in the average life expectancy of the population should be considered as a general indicator characterizing the low level of stability. Conclusions. A decrease in the number of students in universities, a decrease in the level of employment, as well as environmental problems pose a threat in the strategic perspective for the regions of Russia characterized by a low level of sustainability.