Multiple Regression Research Articles

Compression-based inference of network motif sets.

Physical and functional constraints on biological networks lead to complex topological patterns across multiple scales in their organization. A particular type of higher-order network feature that has received considerable interest is network motifs, defined as statistically regular subgraphs. These may implement fundamental logical and computational circuits and are referred to as "building blocks of complex networks". Their well-defined structures and small sizes also enable the testing of their functions in synthetic and natural biological experiments. Here, we develop a framework for motif mining based on lossless network compression using subgraph contractions. This provides an alternative definition of motif significance which allows us to compare different motifs and select the collectively most significant set of motifs as well as other prominent network features in terms of their combined compression of the network. Our approach inherently accounts for multiple testing and correlations between subgraphs and does not rely on a priori specification of an appropriate null model. It thus overcomes common problems in hypothesis testing-based motif analysis and guarantees robust statistical inference. We validate our methodology on numerical data and then apply it on synaptic-resolution biological neural networks, as a medium for comparative connectomics, by evaluating their respective compressibility and characterize their inferred circuit motifs.

Comparison of interfacial injected energy between simulated lightning return stroke experiment and common Joule heat & Arc heat model application

A previous study has shown that the thermal damage of the Joule thermal arc heat transfer model is lighter than that of a natural lightning strike. Therefore, this paper focuses on the return stroke current and proposes an improved experimental method of simulated return damage without using arc-inducing wire. Combining the data with the inversion model of injected energy, the energy transfer characteristics of the samples are characterized. Furthermore, a data dimensionality reduction method based on multiple correlation coefficients is used to discuss the impact of the current peak/rise rate/wave tail time on the injected energy discrepancy. The results indicate a positive correlation between the current peak and current rise rate with the injected energy discrepancy. When the tail time exceeds 15 microseconds, the injected energy discrepancy decreases as the tail time increases. The thermal source characteristics of energy transfer during the return stroke process are determined. During the initial phase of the return stroke current, interfacial energy transfer includes contributions from ion enthalpy flux, Joule heating, and electronic enthalpy flux. When the tail time exceeds 15 microseconds, the contribution of ion enthalpy flux to the injected energy diminishes with increasing tail time.

Bibliometric Analysis on of the Impact of Screening to Minimize Maternal Mental Health on Neonatal Outcomes: A Systematic Review.

(1) Background: Prenatal depression, maternal anxiety, puerperal psychosis, and suicidal thoughts affect child welfare and development and maternal health and mortality. Women in low-income countries suffer maternal mental health issues in 25% of cases during pregnancy and 20% of cases thereafter. However, MMH screening, diagnosis, and reporting are lacking. The primary goals of the present study are twofold, as follows: firstly, to evaluate the importance of screening maternal mental health to alleviate perinatal depression and maternal anxiety, and, secondly, to analyze research patterns and propose novel approaches and procedures to bridge the current research gap and aid practitioners in enhancing the quality of care offered to women exhibiting symptoms of perinatal depression. (2) Methods: We conducted a bibliometric analysis to analyze the research topic, using the bibliometric tools Biblioshiny and VOSviewer, as well as the R statistical programming language. To accomplish our goal, we obtained a total of 243 documents from the Scopus and PubMed databases and conducted an analysis utilizing network, co-occurrence, and multiple correlation approaches. (3) Results: Most of the publications in the field were published between the years 2021 and 2024. The results of this study highlight the significance of shifting from conventional screening methods to digital ones for healthcare professionals to effectively manage the symptoms of maternal mental health associated with postpartum depression. Furthermore, the results of the present study suggest that digital screening can prevent maternal physical morbidity, contribute to psychosocial functioning, and enhance infant physical and cognitive health. (4) Conclusions: The research indicates that it is crucial to adopt and include a computerized screening practice to efficiently and immediately detect and clarify the signs of prenatal to neonatal depression. The introduction of digital screening has led to a decrease in scoring errors, an improvement in screening effectiveness, a decrease in administration times, the creation of clinical and patient reports, and the initiation of referrals for anxiety and depression therapy.

Relationships between self-efficacy beliefs and personal factors in final-year medical students

BackgroundMedical students entering postgraduate training often feel ill-prepared for clinical practice. This has implications for physician well-being and the quality of patient care. Self-efficacy represents an important contributing factor in the transition process. Identifying student characteristics associated with self-efficacy is important in order to design possible interventions to enhance self-efficacy. Therefore, we assessed the relationship between final-year medical students’ general self-efficacy with their personality traits, need for cognitive closure, and medical knowledge in order to identify factors contributing to the assessment and improvement of self-efficacy.MethodsSelf-assessed data regarding general self-efficacy was collected from 188 final-year medical students who participated in a first day of residency simulation between March and September 2023. We also assessed several personal factors including the HEXACO Personality Inventory Revised (HEXACO-PI-R), a short scale to measure Need for Cognitive Closure (16-NCCS), and students’ medical exam grades (M2). We ran multiple correlation and multiple linear regression analyses across all variables. We then added a second analysis each with general self-efficacy and HEXACO domains Emotionality and Extraversion on facet level, which both showed significant associations with self-efficacy in the respective first analysis.ResultsAcross all variables, self-efficacy correlated significantly negatively with Emotionality and positively with Extraversion. Both domains also significantly predicted self-efficacy accordingly in the regression model. On a facet analysis, Sentimentality (Emotionality) and Sociability (Extraversion) did not correlate significantly with self-efficacy. In the regression model only the facets Sociability (Extraversion) and Fearfulness (Emotionality) significantly predicted lower self-efficacy. Furthermore, self-efficacy correlated significantly and negatively with the Need for Cognitive Closure (NCC). Additionally, significant positive and negative correlations of the NCC with both Emotionality and Extraversion, respectively, as well as a significant positive correlation for exam grades (M2) and Extraversion were found.ConclusionsSelf-efficacy contributes to medial students’ preparedness for clinical practice and can be predicted by several personal factors. Students should learn and reflect about these factors and need to be supported in increasing their self-efficacy and its self-assessment towards their transition to postgraduate training. Construction of a specific instrument for self-efficacy assessment utilizing the insight provided by the findings is proposed as a next step.

The mediating of perceived organizational support between ethical leadership and employee engagement at information and communication technology telecommunication in Palestine

This paper recognizes the gaps in previous studies and provides insight into the significance of leadership guided by ethical principles in influencing employee engagement through the mediating role of perceived organizational support (POS). Thus, this paper aims to examine the impact of ethical leadership on employee engagement and to determine whether perceived organizational support (POS) mediates the relationships between both constructs. This study used a quantitative research method and collected data from 328 employees in the Information and Communication Technology telecommunications sector in Palestine. The hypotheses underwent examination through the application of partial least squares structural equation modeling (PLS-SEM). The findings show that 328 people responded to the current study's questionnaire. Ethical leadership the dependent variable was strongly impacted by perceived organizational support (EL POS) at the significant level of 0.01 (β = .697, µ =.0.669, SD=0.035, t=20.104, P=0.000 and f^2= 78% respectively. All of the study's variables had some effect on the dependent variable and employee engagement. Similarly, the remaining hypotheses are verified. When the R-squared adjusted values of the independent variables for the variance of employee engagement were more than 53 percent, the R-squared multiple correlations (R2) for the dependent variables indicated that the model appropriately matched the data.

Association between micronutrient intake and cognitive performance of school-aged children attending selected private schools in Lagos State

Background: It has been reported that the academic performance of school-aged children has been on the decline in recent years. Feeding pattern determines micronutrient consumption and plays an important role in cognitive performance. Objectives: This research assessed the micronutrient consumption, feeding pattern, and cognitive performance of school-aged children in selected private schools in Lagos State. Methods: The socio-demographic characteristics of the parents and children, knowledge of parents on micronutrients, feeding pattern of the children, and identifying micronutrient-rich food among consumed foods were obtained using a semi-structured questionnaire. The micronutrient intake was assessed using twenty-four-hour dietary recall and the cognitive performance of the respondents was evaluated with structured questions from Slosson’s intelligence test revised third edition after which the micronutrient consumption was correlated against overall cognitive performance using Pearson’s multiple correlation range test. Results: The results indicated that the feeding pattern of the children showed that 51.3% were fed three times a day, 47.3% took snacks at least once a day and more than half (52.0%) took fruits and vegetables once a day. The micronutrient-rich foods among consumed foods were identified and they include efo and egusi, ewedu, okro, apple, orange, and milk, among others. There was a negative correlation (p<0.05) between micronutrient consumption and cognitive performance among the students studied. Conclusion: This study concludes that an increase in micronutrient consumption alone does not increase cognitive performance.

A Crucible of IoT Applications and Services and the Gambia Revenue Generation

The study investigated the relationship between Internet of Things (IoT) applications and services and The Gambia revenue generation, tax evasion and tax compliance respectively. It identified the challenges impeding the adoption and implementation of IoT applications and services in the revenue generation processes by the Gambia Revenue Authority (GRA). Both primary and secondary data were used in the study. Questionnaire and interview were used to generate the primary data. The study population (2188) comprised senior and mid-tier management personnel from the Ministry of Finance and Economic Affairs (MoFEA), staff members of The Gambia Revenue Authority, and the corporate taxpayers. The sampling approach used in this study was multistage. Personnel from the MoFEA and GRA were purposively selected, while corporate taxpayers were randomly selected. Their populations were then divided into various strata to ensure fair representation. Respondents were randomly picked from each stratum. To ensure an appropriate sample size, 327 individuals were selected. Data obtained were analysed using multiple regression, correlation coefficient, and simple regression analysis. Qualitative analyses were done on the interview responses. The study revealed that connectivity, networking, and data collection improve revenue generation, while increased IoT adoption and higher data utilisation and infrastructure investment reduce tax evasion and boost tax compliance. However, implementation of the IoT has encountered challenges in the form of technological barriers, financial constraints, and skill gaps. In view of these, investment must be made in enhancing connectivity and networking infrastructure, training staff in data analytics and cyber-security to optimise IoT data usage and boost IoT adoption through inducements and awareness programs. The study concluded that IOT applications and services are in the right direction to revolutionise The Gambia revenue generation.

REXPACO ASDI: joint unmixing and deconvolution of the circumstellar environment by angular and spectral differential imaging

ABSTRACT Angular and spectral differential imaging is an observational technique of choice to investigate the immediate vicinity of stars. By leveraging the relative angular motion and spectral scaling between on-axis and off-axis sources, post-processing techniques can separate residual star light from light emitted by surrounding objects such as circumstellar discs or point-like objects. This paper introduces a new algorithm that jointly unmixes these components and deconvolves disc images. The proposed algorithm is based on a statistical model of the residual star light, accounting for its spatial and spectral correlations. These correlations are crucial yet remain inadequately modelled by existing reconstruction algorithms. We employ dedicated shrinkage techniques to estimate the large number of parameters of our correlation model in a data-driven fashion. We show that the resulting separable model of the spatial and spectral covariances captures very accurately the star light, enabling its efficient suppression. We apply our method to data sets from the Very Large Telescope/Spectro-Polarimetry High-contrast Exoplanet REsearch instrument and compare its performance with standard algorithms (median subtraction, PCA, PACO). We demonstrate that considering the multiple correlations within the data significantly improves reconstruction quality, resulting in better preservation of both disc morphology and photometry. With its unique joint spectral modelling, the proposed algorithm can reconstruct discs with circular symmetry (e.g. rings, spirals) at intensities one million times fainter than the star, without needing additional reference data sets free from off-axis objects.

The Influence Of Work Environment And Motivation On Employee Spirit At Pt Perkebunan Nusantara IV, Gunung Meliau Palm Oil Mill Work Unit

This study aims to identify and analyze the influence of the Work Environment and Motivation on the Work Spirit of employees at PT Perkebunan Nusantara IV, Gunung Meliau Palm Oil Mill Work Unit. The population in this study consists of 125 individuals, using a saturated sampling technique. Data collection techniques in this study include interviews and questionnaires. The analytical tools used in this research are instrument tests, classical assumption tests, multiple linear regression analysis, correlation coefficients, determination coefficients, F-tests, and T-tests. The results of the study show that the work environment and motivation affect work spirit both simultaneously and partially. Therefore, to enhance work spirit, both the work environment and motivation must be well managed

Mortality and comorbidities in a Nationwide cohort of HIV-infected adults: comparison to a matched non-HIV adults' cohort, France, 2006-18.

Human immunodeficiency virus (HIV) remains a significant cause of morbidity and mortality worldwide. The aim of this study was to describe the mortality rate and associated comorbidities in a nationwide population-based cohort of persons living with HIV (PLWHIV) and to compare it with mortality in an age and gender-matched cohort of non-HIV individuals in France. Using data from the French national health data system, we identified and included 173712 PLWHIV (66.5% men) and 173712 non-HIV participants (66.5% men) matched for age and gender. PLHIV were identified based on ICD-10 HIV diagnoses, HIV-specific laboratory tests, and/or prescriptions for antiretroviral therapy specific to HIV. Hazard ratios (HRs) of mortality were assessed using multiple Cox regression models. During the 13 years of follow-up (2006-18), we observed 20018 deaths among PLWHIV compared with 6262 deaths among non-HIV participants (11.52% vs. 3.60%, P < 0.001). The over-mortality of PLWHIV was expressed by univariable HR = 2.135 (2.072-2.199), which remained significant after adjustment for region, Complementary Universal Health Insurance and AME, with multivariable HR = 2.182 (2.118-2.248). The results remained significant after adjusting for comorbidities, including infectious diseases [HR = 1.587 (1.538-1.638)]. Notably, PLWHIV were more importantly associated with mortality in women [HR = 2.966 (2.767-3.180)], compared in men [HR = 1.961 (1.898-2.027)]. Although the life expectancy of PLWHIV has globally increased, the causes of death should be prioritized in prevention policies and care management. Gender-specific policies should be highlighted, as we observed a higher impact of HIV mortality in women.

Obesity classification predicts early complications and mortality after acetabular fracture.

Obesity remains a global epidemic. The effect of obesity on the risk of complications after acetabular fracture is unknown. Here, we evaluate the effect of BMI on early complications and mortality after acetabular fracture. We hypothesize that the risk of inpatient complications and mortality will be greater in patients with high BMI when compared to those with normal BMI. Adult patients with acetabular fracture were identified via the Trauma Quality Improvement Program data from 2015 to 2019. The primary outcome was overall complication rate with reference to normal-weight patients (BMI = 25-30kg/m2). The secondary outcome was rates of death. The association of obesity class on the primary and secondary outcomes was assessed using Bonferroni-corrected multiple logistic regression models considering patient, injury, and treatment covariates. A total of 99,721 patients with acetabular fracture were identified. Class I obesity (BMI = 30-35kg/m2) was associated with 1.2 greater adjusted relative risk (aRR; 95% confidence interval (CI) 1.1-1.3) of any adverse event, without significant increases in adjusted risk of death. Class II obesity (BMI = 35-40kg/m2) was associated with aRR = 1.2 (95% CI 1.1-1.3) of any adverse event and aRR = 1.5 (95% CI 1.2-2.0) of death. Class III obesity (BMI ≥ 40kg/m2) was associated with aRR = 1.3 (95% CI 1.2-1.4) of any adverse event and aRR = 2.3 (95% CI 1.8-2.9) of death. Obesity is associated greater risk of adverse events and death following acetabular fracture. Obesity severity classification scales with these risks.

Strong positive direct impact of soil moisture on the growth of central asian grasslands

As the issue of global climate change becomes increasingly prominent, the grassland ecosystems in Central Asia are facing severe challenges posed by the impacts of climate change. However, the dominant factors, impact pathways, and cumulative and time-lagged effects of climate factors on various grassland indices remain to be explored. This study selected data from 1988 to 2019, including Fractional Vegetation Cover (FVC), Leaf Area Index (LAI), Net Primary Productivity (NPP), and Vegetation Optical Depth (VOD), to characterize grassland coverage, greenness, biomass accumulation, and water content features. Utilizing multiple linear regression, path analysis, and correlation analysis, this study investigated the dominant effects, direct impacts, indirect influences, and cumulative and time-lagged effects of climate factors on various grassland indices from spatial and climatic zone perspectives. The research findings indicate that over time, the grassland FVC and NPP exhibited increasing trends, while the LAI and VOD showed decreasing trends. Grassland indices are primarily influenced by precipitation and soil moisture (SM). The direct impact of SM on grassland indices was higher than precipitation. Vapour pressure deficit (VPD) has a direct negative impact on grassland indices. Grassland indices are subject to positive indirect effects from precipitation via SM and negative indirect effects from VPD via SM. Precipitation and SM mainly exhibited no cumulative and time-lagged effects on the impact of grassland VOD. VPD primarily demonstrated cumulative and time-lagged effects on grassland indices. The research findings offer valuable insights for conserving grassland ecosystems in Central Asia, as well as for shaping socioeconomic strategies and formulating climate policies.

Multi-timescale inconsistency evaluation and data-driven state of health prediction for circulating water-cooled series battery pack

Inter-cell inconsistency significantly challenges battery pack lifetime, performance, and safety. Current research is deficient in evaluation across multiple time scales and correlation analysis with the state of health (SOH) of batteries. In this paper, we innovatively propose a multi-timescale evaluation method using the correlation coefficient to quantify the inconsistency during long-term aging while employing the coefficient of variation to accurately capture short-term inconsistency fluctuations within a single cycle. We extracted 29 health factors from cyclic data to accurately predict SOH and proposed an improved sparrow search algorithm combined with a support vector regression (ISSA-SVR) model. The model optimizes the sparrow position update strategy by introducing a chicken flock optimization algorithm and incorporating a stochastic function mechanism. This improvement effectively reduces the error and uncertainty in the traditional search process. The experiments are carried out on a 1P36 circulating water-cooled series battery pack, verified by rigorous aging tests. The results show that the correlation coefficient is excellent in assessing long-term inconsistency. In contrast, the coefficient of variation accurately maps the subtle differences in short-term variations and is highly correlated with changes in battery capacity. The ISSA-SVR model demonstrates significantly improved accuracy and robustness in SOH prediction compared to other methods.

Multiple Heterogeneous Networks Representation With Latent Space for Synthetic Lethality Prediction.

Computational synthetic lethality (SL) method has become a promising strategy to identify SL gene pairs for targeted cancer therapy and cancer medicine development. Feature representation for integrating various biological networks is crutial to improve the identification performance. However, previous feature representation, such as matrix factorization and graph neural network, projects gene features onto latent variables by keeping a specific geometric metric. There is a lack of models of gene representational latent space with considerating multiple dimentionalities correlation and preserving latent geometric structures in both sample and feature spaces. Therefore, we propose a novel method to model gene Latent Space using matrix Tri-Factorization (LSTF) to obtain gene representation with embedding variables resulting from the potential interpretation of synthetic lethality. Meanwhile, manifold subspace regularization is applied to the tri-factorization to capture the geometrical manifold structure in the latent space with gene PPI functional and GO semantic embeddings. Then, SL gene pairs are identified by the reconstruction of the associations with gene representations in the latent space. The experimental results illustrate that LSTF is superior to other state-of-the-art methods. Case study demonstrate the effectiveness of the predicted SL associations.

Effect of lithium concentration on the network connectivity of nuclear waste glasses

Structure of borosilicate glasses with varying Li2O contents were investigated using Magic Angle Spinning (MAS) Nuclear Magnetic Resonance (NMR), employing 6Li, 11B, 23Na, 27Al and 29Si nuclei. 11B MAS NMR revealed that increasing Li2O contents result in formation of [BO4]− sites at the expense of BO3. 11B{6Li} and 27Al{6Li} dipolar heteronuclear multiple quantum correlation (D-HMQC) NMR revealed Li as a charge compensator for anionic tetrahedral sites with increased Li. 11B{6Li} J-coupling mediated HMQC NMR suggested the possible association of Li with non-bridging oxygens on Q2 and Q3 sites, indicating its dual role in the glass network. 29Si and 23Na MAS NMR spectra showed depolymerisation of the silicate network and shortening of Na-O bond lengths with increased Li. NMR results are supported by Raman spectroscopy and thermal analysis that indicate depolymerisation of the silicate network and a reduction in glass transition temperature at higher Li content.

Effects on Sleep Bruxism Activity of Three Different Oral Appliances: One Year Longitudinal Cohort Study.

Different oral appliances (OAs) have been proposed to control sleep bruxism (SB) detrimental effects on the stomatognathic system. The aim of the study was to evaluate the effect of different OAs on SB activity and masticatory muscle activity (sMMA) measured by EMG. This longitudinal cohort study was conducted on 51 patients (21 M, 30 F, mean age 26,5 ± 3,5) suffering from SB diagnosed with a validated portable EMG-ECG holter and wearing different OAs: occlusal splints, functional appliance with metallic bites and clear aligners followed after 1 week, 1 month, 3 months, 6 months and 12 months from delivery. A control group of 16 non-treated SB patients (6 M, 10 F mean age 27,1 ± 1,4) was used as a reference. A multiple regression analysis was performed to estimate the differences between groups. The level of significance was set as P value <0,05. Occlusal splint reduced sleep bruxism index after 1 week, 3, 6 and 12 months from delivery while functional appliance only after 12 months. Occlusal splints reduced general phasic contractions only in the first week and sleep bruxism-related phasic contractions at 1 week, 3 and 6 months after delivery with no significant reductions after 12 months. Patients wearing clear aligners showed a reduction in general tonic contractions after 6 and 12 months. Resin and metal bites can reduce sleep bruxism index, while resin bites can reduce sleep bruxism-related phasic contractions. Clear aligners do not influence sleep bruxism index but can reduce tonic contractions.

Joint probabilistic modeling approach for harmonic and three-phase unbalanced disturbance sources

Harmonics and three-phase imbalance are two common disturbances in power systems that interact with and affect each other, leading to more complex impacts on power system performance. To comprehensively and accurately analyze the distribution and interaction mechanisms of harmonics and three-phase imbalance, this study investigated the joint emission level of harmonic and three-phase unbalanced disturbance sources (H-TU-DS). This paper proposes a joint probabilistic emission level modeling approach. The power, harmonic, and three-phase unbalanced data of H-TU-DS are multidimensional, and the feature dataset is filtered by calculating multiple correlation coefficients to achieve dimensionality reduction without losing data information. Considering the different operating characteristics of the H-TU-DS, an improved fuzzy C-means (FCM) algorithm is applied to classify operating conditions, enabling a comprehensive and accurate analysis of the joint emission level. Based on the nonparametric kernel density function, joint probability modeling of H-TU-DS is performed using an adaptive bandwidth improvement method, effectively enhancing the accuracy of the modeling process. Finally, the effectiveness and accuracy of the proposed methods for feature dataset filtering, operating condition classification, and joint probability modeling are demonstrated through comparisons with both simulated and actual data. The proposed model facilitates the prediction and assessment of the impact of H-TU-DS on power quality after grid connection, enabling the effective prevention of power-quality problems through advanced treatment.

UNLOCKING THE RELATIONSHIP BETWEEN ORGANIZATIONAL CITIZENSHIP BEHAVIOR AND EMPLOYEE PERFORMANCE IN THE SPORTS INDUSTRY: A HOLISTIC INVESTIGATION

In the course of the research, a total of 173 employees were questioned through the application of a random selection process. Surveys were utilized in order to accomplish the goal of gathering information for the specific study. For the purpose of determining the level of internal consistency that the instruments possessed, the researchers made use of the Cronbach alpha coefficient test. In order to accomplish the goals of this study, descriptive statistics were utilized. These data included percentages, frequencies, standard deviations, and averages. Additionally, inferential statistical approaches such as multiple regressions and correlation were utilized within the scope of the study. The outcomes of the research indicated that the degree of courtesy and politeness exhibited by workers had a positive and significant impact on the level of work performance they achieved. The results of the research indicate that there is a significant connection between higher levels of corporate citizenship and increased levels of productivity in the workplace. The findings of the survey indicate that employees working in the sport industry should be prepared to take on additional responsibilities, should be willing to provide assistance to new employees, should have a positive attitude, and should be able to accept workplace inconveniences. This is necessary in order to keep up with the advancements that have occurred in their own field and to improve the overall performance of the company. It is important for employees to have a conversation with their coworkers before taking any activities that could potentially have an impact on their fellow employees. They should also make every effort to avoid clashes with their teammates, as this is an extra factor that should be taken into consideration. It is of utmost significance that they refrain from making public their grievances and refrain from criticizing their coworkers. This is a matter of great importance. For the purpose of determining the precise nature and extent to which demographic determinants influence organizational citizenship behavior (OCB) components in connection to business outcomes, it is required to do additional study

Analysis of Consumer Purchase Satisfaction According to Network Marketing Selection Attributes of Inner Beauty Products

Purpose: Korean society is increasingly interested in expressing a beautifully maintained appearance rather than simply pursuing beauty. In addition, the development and sales of beauty products related to this are increasing as people are demanding to think about their inner health as well as their outer appearance. Therefore, this study focused on inner beauty products sold through network marketing and objectively examined how consumers evaluate their purchase satisfaction according to their choice attributes.&#x0D; Method: Participants in the study were participants who had purchased inner beauty products through network marketing, and 212 response sheets were used for the final analysis. Multiple regression analysis was conducted to verify the influence of network marketing selection attributes of inner beauty products on consumer purchase satisfaction, and the significance level according to statistical test was determined at p&lt;.05.&#x0D; Results: Multiple regression analysis was conducted to examine the multidimensional influence of the factors of the choice attributes of the study participants on the sub-factors of the purchase satisfaction variables. The results of the study showed that the choice attributes that have a significant impact on consumer purchase satisfaction are internal choice attributes and ecological choice attributes, except for external choice attributes.&#x0D; Conclusion: Consumption choice attributes of modern people show various consumption behaviors depending on individual characteristics and perceived value. In this study, we examined how consumer purchase satisfaction is manifested according to the choice attributes of consumers participating in network marketing. Based on these results, it is expected that network marketing operators can use it as an objective data on the selection attributes and purchase satisfaction evaluation of inner beauty products so that they can have an independent attitude as business owners.

The Impact of Career Orientation of Beauty Salon Workers on Transfer Motivation: Focused on the Moderating Effect of Organizational Support

Purpose: In this study the impact of beauty shop workers’ Career Orientation on Transfer Motivation was analyzed with organization support as a moderating effect.&#x0D; Method: This study looked at previous studies on each variable based on domestic and foreign research papers and books, and analyzed a total of 310 valid questionnaires using beauty shop workers as the population. Statistical processing was performed using the statistical analysis package SPSS v.23. Frequency analysis was conducted to determine the demographic characteristics of the study subjects, and Cronbach's evaluation of internal consistency was conducted to determine the reliability of the questions on Career Orientation, Transfer Motivation, and organizational support. Reliability analysis was conducted using the Alpha coefficient. The comprehensive influence relationship forming the causal relationship between the variables presented in the research model was conducted through multiple regression analysis and controlled regression analysis.&#x0D; Results: The above analysis results are summarized as follows.&#x0D; First, the impact of Career Orientation on Transfer Motivation is that among the Career Orientation factors, Organizational Orientation (Organizational Orientation) and Professional Orientation (Professional Orientation) are It was found to have a positive (+) direction on Transfer Motivation. In other words, as Organizational Orientation and Professional Orientation among Career Orientation factors increase, Transfer Motivation also increases.&#x0D; Second, among Career Orientation factors, it was verified that Professional Orientation has the greatest influence on Transfer Motivation.&#x0D; Third, organizational support was found to moderate the effect of Career Orientation on Transfer Motivation.&#x0D; Among the Career Orientation factors, organizational support was adjusted to have a lower impact on Transfer Motivation the higher the Organizational Orientation, and the higher the Professional Orientation, the higher the Transfer Motivation. It was verified that the effect on (transition motivation) was adjusted to increase.&#x0D; Conclusion: This study provides basic data to improve the capabilities of employees through the organization's continuous support for organizational members and to facilitate human resource management so that they can directly contribute to organizational performance. As a result, the turnover rate of beauty shop workers can be reduced and individual capabilities can be strengthened. I hope that it can be put to good use.