The interaction of narcissism, agreeableness and conscientiousness in entrepreneurial mentoring: Implications for learning outcomes.

The personality configuration of mentors and mentees is important in understanding mentoring outcomes. While the best mentors appear to have higher degrees of agreeableness and conscientiousness, entrepreneurs generally score lower on agreeableness and have higher degrees of narcissism, a personality trait that could be detrimental to mentoring. We investigated the interaction of narcissism with two traits from the Big Five Inventory, namely agreeableness and conscientiousness, to see how this interaction influenced learning from the relationship of mentee entrepreneurs. Our findings suggest that mentee narcissism negatively influences learning, and mentor agreeableness mitigates the negative effects on mentee learning. These findings show certain beneficial personality configurations in entrepreneurial mentoring and provide elements to consider in managerial practice when pairing mentors and mentees in this context.

Exploring healthy lifestyle with health locus of control and sociodemographic variables in Türkiye.

In this study, we aimed to explore the effects of Internal/Chance/Powerful Others Health Locus of Control (IHLC/CHLC/PHLC) on the healthy lifestyle and to assess the sensitivity of the healthy lifestyle to sociodemographic variables. To achieve this goal, we collected data by performing online and hand-delivered surveys (n = 950) with individuals aged 18 or older in Türkiye. The results showed that IHLC and PHLC had positive and significant effects on Healthy Lifestyle Index (HLI). However, the results expressed that CHLC had no negative and significant effect on HLI. Our assessment of a healthy lifestyle in terms of health locus of control (HLC) and sociodemographic variables revealed important findings, which may contribute to the development of public health strategies in several ways; for example, they can be used as a framework to conduct public health interventions that promote a healthy lifestyle.

Effect of preoperative autologous platelet-rich plasmapheresis on postoperative bleeding in patients undergoing heart valve surgery.

Background: Cardiovascular surgeries often require deep hypothermic circulatory arrest and cardiopulmonary bypass (CPB), which can disrupt blood clotting and lead to excessive bleeding. Traditional treatments involve transfusing blood and blood products, which can have adverse effects and place significant strain on the global blood supply. Research suggests that autologous platelet-rich plasmapheresis (aPRP) may reduce the need for transfusions by preserving blood components. However, the impact of aPRP on postoperative blood loss and clinical outcomes in cardiovascular surgery remains controversial. This study aimed to examine the effects of aPRP on postoperative blood loss and recovery in patients undergoing heart valve surgery. Methods: A total of 183 patients were divided into either aPRP or control groups. The aPRP group received aPRP before CPB, whereas the control group did not. The primary endpoint was postoperative bleeding between the groups. The secondary endpoints were postoperative bleeding risk factors and clinical outcome assessment. Logistic regression analysis with covariate adjustment was used to calculate these risk factors. Results: A total of 76 patients (41.5%) in the aPRP group and 107 patients (58.5%) in the control group were included in the analysis. No significant difference was found in the occurrence of postoperative bleeding [odds ratio (OR) =0.53, 95% confidence interval (CI): 0.28-1.00, P=0.05], and the aPRP group had fewer complications than the controls (OR =0.28, 95% CI: 0.10-0.68, P=0.009). However, after adjusting for the New York Heart Association (NYHA) classification, diabetes, arrhythmology, mean activated clotting time (ACTmean), CPB, bleeding, thoracotomy, and body mass index (BMI), there was a significant difference in postoperative bleeding (adjusted OR =0.47, 95% CI: 0.22-0.98, P=0.04) and complications (adjusted OR =0.23, 95% CI: 0.07-0.64, P=0.008) between the two groups. Conclusions: Preoperative aPRP can improve postoperative outcomes and reduce complications in patients undergoing heart valve surgery.

Association of olfactory and cognitive function test scores with hippocampal and amygdalar grey matter volume: a cross-sectional study.

Few population-based studies including younger adults have examined the potential of olfactory function tests to capture the degree of atrophy in memory-associated brain regions, which cannot be adequately explained by cognitive function tests screening for cognitive impairment. This population-based study investigated associations between high-resolution olfactory test data with few odours and grey matter volumes (GMVs) of the left and right hippocampi, amygdala, parahippocampi, and olfactory cortex, while accounting for differences in cognitive decline, in 1444 participants (aged 31-91 years). Regression analyses included intracranial volume (ICV)-normalised GMVs of eight memory-related regions as objective variables and age, sex, education duration, smoking history, olfaction test score, and the Montreal Cognitive Assessment-Japanese version (MoCA-J) score as explanatory variables. Significant relationships were found between olfactory test scores and ICV-normalised GMVs of the left and right hippocampi and left amygdala (p = 0.020, 0.024, and 0.028, respectively), adjusting for the MoCA-J score. The olfactory test score was significantly related to the right amygdalar GMV (p = 0.020) in older adults (age ≥ 65 years). These associations remained significant after applying Benjamini-Hochberg multiple testing correction (false discovery rate < 0.1). Therefore, olfactory and cognitive function tests may efficiently capture the degree of atrophy in the hippocampi and amygdala, especially in older adults.

Influence of chemical structures on reduction rates and defluorination of fluoroarenes during catalytic reduction using a rhodium-based catalyst.

Continuous growth in fluoroarene production has led to environmental pollution and health concerns owing to their persistence, which is attributed to the stable C-F bond in their structures. Herein, we investigated fluoroarene decomposition via hydrodefluorination using a rhodium-based catalyst, focusing on the effects of the chemical structure and functional group on the defluorination yield. Most compounds, except (pentafluoroethyl)benzene, exhibited full or partial reduction with pseudo-first-order rate constants in the range of 0.002-0.396 min-1 and defluorination yields of 0%-100%. Fluoroarenes with hydroxyl, methyl, and carboxylate groups were selected to elucidate how hydrocarbon and oxygen-containing functional groups influence the reaction rate and defluorination. Inhibition of the reaction rate and defluorination yield based on functional groups increased in the order of hydroxyl < methyl < carboxylate, which was identical to the order of the electron-withdrawing effect. Fluoroarenes with polyfluoro groups were also assessed; polyfluoro groups demonstrated a different influence on catalyst activity than non-fluorine functional groups because of fluorine atoms in the substituents undergoing defluorination. The reaction kinetics of (difluoromethyl)fluorobenzenes and their intermediates suggested that hydrogenation and defluorination occurred during degradation. Finally, the effects of the type and position of functional groups on the reaction rate and defluorination yield were investigated via multivariable linear regression analysis. Notably, the electron-withdrawing nature of functional groups appeared to have a greater impact on the defluorination yield of fluoroarenes than the calculated C-F bond dissociation energy.

The relationship between general self-efficacy and nursing practice competence for second-year nurses: Empirical quantitative research.

AIM: To examine the relationship between general self-efficacy and nursing practice competence for nurses in the second year of employment. DESIGN: A cross-sectional design was used. DATA SOURCES: The study included 596 nurses in their second year of employment at 75 medical facilities across Japan and used an online questionnaire survey for data collection. RESULTS: The covariance structure analysis showed the path from general self-efficacy (latent variable) to nursing practice competence. Positive correlations were found between all factors on both scales. Multiple regression analysis results showed that the general self-efficacy factors of 'positivity in behavior' and 'confidence in social competence' affect nursing practice competence. CONCLUSION: This study emphasizes the importance of enhancing the general self-efficacy of second-year nurses to improve their nursing practice competence. To achieve this, it suggests developing strategies from the perspective of the factors that comprise general self-efficacy. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: The findings suggest that improving general self-efficacy can enhance nursing practice competence, which could inform the development of interventions to support nurses in improving their competence. The study provides basic data for improving nurses' practice competence. IMPACT: This study is the first to establish a relationship between general self-efficacy and nursing practice competence among second-year nurses. It demonstrates the significance of general self-efficacy in enhancing nursing practice competence, particularly for second-year nurses worldwide who may be struggling with their nursing practice competence and considering leaving the profession. The findings offer practical implications for stakeholders involved in nursing education and training programs, with potential applications in professional development. REPORTING METHOD: This manuscript adheres to the STROBE guidelines for the reporting of cross-sectional studies. PATIENT OR PUBLIC CONTRIBUTION: There was no patient or public contribution.

A Nationwide Nepalese Study to Establish Reference Intervals for Major Biochemical Analytes with Elucidation of Nepalese Features of Reference Values.

Despite immense importance of reference intervals (RIs) for clinical diagnosis, there have been no reliable RIs available for Nepalese. Hence, this nationwide study was organized to establish RIs for 30 common biochemical parameters. This study was conducted following the harmonized protocol provided by IFCC Committee on Reference Interval and Decision Limits (C-RIDL) with recruitment of 617 apparently healthy volunteers (18 - 65 years) by near-equal gender balance from 5 major cities. Fasting blood were collected, serum was separated and measured collectively using Beckman-Coulter/Olympus AU480 chemistry analyzer. The sources of variations of reference values (RVs) were evaluated by multiple regression analysis and nested ANOVA. Latent abnormal values exclusion (LAVE) method was applied to reduce influence of latent diseases. RIs were standardized based on a value-assigned serum panel provided by C-RIDL. By ANOVA, no between-city differences were observed, while sex-related changes were typically noted for urate, creatinine, iron, γ-glutamyl transferase (GGT), immunoglobulin M, and transferrin, but not for high-density lipoprotein cholesterol. Age-related changes were observed for total cholesterol (TC), triglyceride, low-density lipoprotein cholesterol, and C-reactive protein (CRP). RIs were successfully derived all parametrically. The LAVE procedure was effective in lowering upper limits for aspartate aminotransferase, alanine aminotransferase (ALT), and CRP. Compared to other collaborating countries, Nepalese RIs were low for urea, cholesterols, ALT, and high for triglyceride, GGT, CRP, immunoglobulin G, and complements. The RIs for major chemistry analytes were derived and standardized for nationwide use in Nepal. This study distinctly elucidated sources of variation and international features of Nepalese RIs. Supplementary Information: The online version supplementary material available at 10.1007/s12291-023-01123-6.

Factors determining the short-term clinical outcomes of conservative treatment in patients with supraspinatus tear.

INTRODUCTION: To identify factors influencing the better and worse changes in the Western Ontario Rotator Cuff Index of patients undergoing conservative treatment for supraspinatus tendon tear. METHODS: The study included 30 patients with supraspinatus tendon tear who underwent conservative treatment. The average duration of intervention was 35.4 days. The Western Ontario Rotator Cuff Index, shoulder range of motion, isometric muscle strength, supraspinatus tendon thickness, thickness of the supraspinatus, infraspinatus, and teres minor muscles, and acromiohumeral interval were assessed before and after the intervention. In the statistical analyses, change in the Western Ontario Rotator Cuff Index was the dependent variable, and the amount of change in each measurement variable before and after the intervention was the independent variable. RESULTS: The average Western Ontario Rotator Cuff Index improved from 1067 at pre-treatment to 997 at post-treatment, but without a significant difference (p = 0.29). A multiple regression analysis revealed that supraspinatus tendon thickness and muscle strength in shoulder external rotation at 90° scaption had a significant effect on the change in the Western Ontario Rotator Cuff Index (R2 = 0.44, p < 0.01). CONCLUSION: Supraspinatus tendon thickness and muscle strength in shoulder external rotation at 90° scaption were important factors for the Western Ontario Rotator Cuff Index score in the early stages of conservative treatment for patients with supraspinatus tendon tear.

Understanding and alleviating informal caregiver burden through the development and validation of a caregiver strain index-based model in Taiwan.

BACKGROUND: Quantifying the informal caregiver burden is important for understanding the risk factors associated with caregiver overload and for evaluating the effectiveness of services provided in Long-term Care (LTC). OBJECTIVE: This study aimed to develop and validate a Caregiver Strain Index (CSI)-based score for quantifying the informal caregiver burden, while the original dataset did not fully cover evaluation items commonly included in international assessments. Subsequently, we utilized the CSI-based score to pinpoint key caregiver burden risk factors, examine the initial timing of LTC services adoption, and assess the impact of LTC services on reducing caregiver burden. METHODS: The study analyzed over 28,000 LTC cases in Southern Taiwan from August 2019 to December 2022. Through multiple regression analysis, we identified significant risk factors associated with caregiver burden and examined changes in this burden after utilizing various services. Survival analysis was employed to explore the relationship between adopting the first LTC services and varying levels of caregiver burden. RESULTS: We identified 126 significant risk factors for caregiver burden. The most critical factors included caregiving for other disabled family members or children under the age of three (ß = 0.74, p < 0.001), the employment status of the caregiver (ß = 0.30-0.53, p < 0.001), the frailty of the care recipient (ß = 0.28-0.31, p < 0.001), and the behavioral symptoms of dementia in care recipients (ß = 0.28-2.60, p < 0.05). Generally, caregivers facing higher burdens sought LTC services earlier, and providing home care services alleviated the caregiver's burden. CONCLUSION: This comprehensive study suggests policy refinements to recognize high-risk caregivers better early and provide timely support to improve the overall well-being of both informal caregivers and care recipients.

Effects of temperature and moisture fluctuations for suitable use of raw-crushed wind-turbine blade in concrete.

Raw-crushed wind-turbine blade (RCWTB), a waste from the recycling of wind-turbine blades, is used as a raw material in concrete in this research. It contains not only fiberglass-composite fibers that bridge the cementitious matrix but also polyurethane and balsa-wood particles. Therefore, concrete containing RCWTB can be notably affected by moisture and temperature fluctuations and by exposure to high temperatures. In this research, the performance of five concrete mixes with 0.0%, 1.5%, 3.0%, 4.5%, and 6.0% RCWTB, respectively, is studied under moist/dry, alternating-sign-temperature-shock, and high-temperature-shock tests. Two damage mechanisms of RCWTB within concrete were found through these tests: on the one hand, micro-cracking of the cementitious matrix, which was verified by microscopic analyses and was dependent on concrete porosity; on the other, damage and degradation of the RCWTB components, as the polyurethane melted, and the balsa-wood particles burned. Both phenomena led to larger remaining-strain levels and reduced concrete compressive strength by up to 25% under temperature and humidity variations, although the bridging effect of the fiberglass-composite fibers was effective when adding RCWTB amounts higher than 3.0%. The compressive-strength loss after the high-temperature-shock test increased with the RCWTB content, reaching maximum values of 8% after an exposure time of 7 days. Statistical analyses revealed that effect of the RCA amount in the concrete was conditioned by the exposure times in all the tests. The accurate definition of those times is therefore key to set an RCWTB content in concrete that ensures its suitable behavior under the environmental conditions analyzed.

A clinical risk score enables early prediction of dissatisfaction 1 year after total knee arthroplasty.

PURPOSE: Dissatisfaction after total knee arthroplasty (TKA) is a prevalent and clinically relevant problem that affects approximately 10%-20% of patients. The aim of this study is to identify factors associated with dissatisfaction 1 year after TKA. METHODS: A total of 236 patients undergoing TKA were included in this prospective cohort study. Demographic data, preoperative clinical parameters (e.g., axial alignment, osteoarthritis severity) and patient-reported outcome measures (PROMs) were collected preoperatively, at 1 month and 1 year after TKA, encompassing the Knee Society Score (KSS) and Knee injury and Osteoarthritis Outcome Score (KOOS). The primary outcome was dissatisfaction 1 year after TKA, defined as ≤20 points on the KSS satisfaction scale. A risk score based on multiple regression and area under the curve (AUC) analyses was calculated to predict dissatisfaction. RESULTS: One year after TKA, 16% of the patients were dissatisfied. Dissatisfied patients were significantly younger (p = 0.023) and had a higher body mass index (BMI) (p = 0.007). No differences were observed in preoperative objective (p = 0.903) and functional KSS (p = 0.346), pain (p = 0.306), osteoarthritis severity (p = 0.358), axial knee alignment (p = 0.984) or psychological distress (p = 0.138). The likelihood of dissatisfaction at 1 year was 3.0, 4.0, 7.4, 4.3 and 2.8 times higher amongst patients aged <63.5 years, with a BMI > 30.1 kg/m2, a KOOSPain < 50%, a KSSFunction < 42 points and a KSSExpectation < 9 points (all at 1 month), respectively. Using these variables, a risk score with a maximum of 7 points was developed, demonstrating a high predictive value for dissatisfaction (AUC: 0.792 [95% confidence interval: 0.700-0.884], p < 0.001). CONCLUSION: Dissatisfaction 1 year after TKA can be predicted by a weighted risk score that includes patient age, BMI, pain, subjective functionality and unmet expectation 1 month postoperatively. Using the risk score, early detection of dissatisfaction has the potential to enable targeted interventions and improve patients' quality of life. LEVEL OF EVIDENCE: Level II, Prognostic study.

Estimation of instantaneous peak flows in Canadian rivers: an evaluation of conventional, nonlinear regression, and machine learning methods.

Instantaneous peak flows (IPFs) are often required to derive design values for sizing various hydraulic structures, such as culverts, bridges, and small dams/levees, in addition to informing several water resources management-related activities. Compared to mean daily flows (MDFs), which represent averaged flows over a period of 24 h, information on IPFs is often missing or unavailable in instrumental records. In this study, conventional methods for estimating IPFs from MDFs are evaluated and new methods based on the nonlinear regression framework and machine learning architectures are proposed and evaluated using streamflow records from all Canadian hydrometric stations with natural and regulated flow regimes. Based on a robust model selection criterion, it was found that multiple methods are suitable for estimating IPFs from MDFs, which precludes the idea of a single universal method. The performance of machine learning-based methods was also found reasonable compared to conventional and regression-based methods. To build on the strengths of individual methods, the fusion modeling concept from the machine learning area was invoked to synthesize outputs of multiple methods. The study findings are expected to be useful to the climate change adaptation community, which currently heavily relies on MDFs simulated by hydrologic models.

Reappraisal of serum retinol-binding protein as a surrogate marker for retinol and discovery of a novel retinol estimation formula.

BACKGROUND & AIMS: Serum retinol (ROH) is commonly used for population level assessment of vitamin A status. High-performance liquid chromatography (HPLC) is considered most accurate method for measuring ROH. However, with the technical difficulty of using HPLC for routine assays, serum retinol-binding protein (RBP) measured by immunological assays is expected to be a surrogate marker for ROH, with reports of a close correlation between serum RBP and ROH. Nevertheless, RBP is not commonly tested to assess vitamin A status with concerns over RBP alterations under various physiopathological conditions. Thus, we reappraised the extent to which RBP could be used as a surrogate marker in representative disorders that alter serum RBP levels. As a related marker, diagnostic utility of transthyretin (TTR) was also evaluated. METHODS: To evaluate the reliability of ROH and RBP assays, specimen stability was assessed in terms of (1) storage at 25, 4, -20, and -80 °C for 1-28 days, (2) five-cycle freeze-thawing, and (3) fluorescent light exposure for 1-14 days. Sources of variation (sex, age, body mass index [BMI], and drinking habits) and reference intervals for ROH, RBP, and TTR were determined in 617 well-defined healthy individuals. To investigate the influence of disorders that affect serum RBP, patients with five diagnostic groups were enrolled: 26 with chronic kidney disease (CKD); 13 with various malignancies in advanced stages (AdM), 12 with acute bacterial infections (ABI), 6 with liver cirrhosis (LC), and 26 with simple obesity (BMI ≥ 27 kg/m2). RESULTS: The stability of RBP and ROH in serum was confirmed under all conditions. In healthy individuals, serum ROH, RBP, and TTR were appreciably high in males with a slight increase in proportion to age and BMI. The major-axis regression line between RBP (x) and ROH (y) in healthy individuals was y = x, with a correlation coefficient of 0.986. In the LC, AdM, and ABI groups, similar strong correlations were observed; however, the regression lines were shifted slightly rightward from the healthy group line, indicating a positive bias in estimating ROH. Interestingly, the same analyses between TTR and ROH revealed similar strong linear relationships in all groups; however, the regression line of each group showed a leftward (opposite) shift from the healthy group line. Based on these observations, we developed a novel regression model composed of RBP and TTR, which gave much improved accuracy in estimating ROH, even under these pathological conditions. CONCLUSIONS: The perfect RBP-ROH correlation in healthy individuals indicates the utility of RPB as a surrogate marker for ROH. Nevertheless, under RBP-altered conditions, a slight overestimation of ROH is inevitable. However, when the TTR was tested together, the bias can be corrected almost perfectly using the novel ROH estimation formula comprising RBP and TTR.

High-Resolution Estimates of N2O Emissions from Inland Waters and Wetlands in China.

Inland waters (rivers, lakes, and reservoirs) and wetlands (marshes and coastal wetlands) represent large and continuous sources of nitrous oxide (N2O) emissions, in view of adequate biomass and anaerobic conditions. Considerable uncertainties remain in quantifying spatially explicit N2O emissions from aquatic systems, attributable to the limitations of models and a lack of comprehensive data sets. Herein, we conducted a synthesis of 1659 observations of N2O emission rates to determine the major environmental drivers across five aquatic systems. A framework for spatially explicit estimates of N2O emissions in China was established, employing a data-driven approach that upscaled from site-specific N2O fluxes to robust multiple-regression models. Results revealed the effectiveness of models incorporating soil organic carbon and water content for marshes and coastal wetlands, as well as water nitrate concentration and dissolved organic carbon for lakes, rivers, and reservoirs for predicting emissions. Total national N2O emissions from inland waters and wetlands were 1.02 × 105 t N2O yr-1, with contributions from marshes (36.33%), rivers (27.77%), lakes (25.27%), reservoirs (6.47%), and coastal wetlands (4.16%). Spatially, larger emissions occurred in the Songliao River Basin and Continental River Basin, primarily due to their substantial terrestrial biomass. This study offers a vital national inventory of N2O emissions from inland waters and wetlands in China, providing paradigms for the inventorying work in other countries and insights to formulate effective mitigation strategies for climate change.

Escalation on Kihon Checklist Scores Preceding the Certification of Long-Term Care Need in the Older Population in Japan. A 9-Year Retrospective Study.

Objectives: The Kihon Checklist (KCL) is valuable for predicting long-term care (LTC) certification. However, the precise association between KCL scores and the temporal dynamics of LTC need certification remains unclear. This study clarified the characteristic trajectory of KCL scores in individuals certified for LTC need. Methods: The KCL scores spanning from 2011 to 2019 were obtained from 5630 older individuals, including those certified for LTC need in November 2020, in Iiyama City, Nagano, Japan. We analyzed the KCL score trajectories using a linear mixed model, both before and after propensity score matching. Results: Throughout the 9-year observation period, the KCL scores consistently remained higher in the certified group compared to the non-certified group. Notably, a significant score increase occurred within the 3 years preceding LTC certification. Discussion: Our findings highlight the effectiveness of continuous surveillance using the KCL in identifying individuals likely to require LTC within a few years.

Country-based modelling of COVID-19 case fatality rate: A multiple regression analysis.

BACKGROUND: The spread of the severe acute respiratory syndrome coronavirus 2 outbreak worldwide has caused concern regarding the mortality rate caused by the infection. The determinants of mortality on a global scale cannot be fully understood due to lack of information. AIM: To identify key factors that may explain the variability in case lethality across countries. METHODS: We identified 21 Potential risk factors for coronavirus disease 2019 (COVID-19) case fatality rate for all the countries with available data. We examined univariate relationships of each variable with case fatality rate (CFR), and all independent variables to identify candidate variables for our final multiple model. Multiple regression analysis technique was used to assess the strength of relationship. RESULTS: The mean of COVID-19 mortality was 1.52 ± 1.72%. There was a statistically significant inverse correlation between health expenditure, and number of computed tomography scanners per 1 million with CFR, and significant direct correlation was found between literacy, and air pollution with CFR. This final model can predict approximately 97% of the changes in CFR. CONCLUSION: The current study recommends some new predictors explaining affect mortality rate. Thus, it could help decision-makers develop health policies to fight COVID-19.

Predicting neural activity of whole body cast shadow through object cast shadow in dynamic environments.

Shadows, as all other objects that surround us, are incorporated into the body and extend the body mediating perceptual information. The current study investigates the hypothesis according to which the perception of object shadows would predict the perception of body shadows. 38 participants (19 males and 19 females) aged 23 years on average were immersed into a virtual reality environment and instructed to perceive and indicate the coincidence or non coincidence between the movement of a ball shadow with regard to ball movement on the one hand, and between their body shadow and their body position in space on the other. Their brain activity was recording via a 32-channel EEG system, in which beta (13.5-30 Hz) oscillations were analyzed. A series of Multiple Regression Analysis (MRA) revealed that the beta dynamic oscillations patterns of the bilateral occipito-parieto-frontal pathway associated with the perception of ball shadow appeared to be a significant predictor of the increase in beta oscillations across frontal areas related to the body shadow perception and the decrease in beta oscillations across frontal areas connected to the decision making of the body shadow. Taken together, the findings suggest that inferential thinking ability relative to body shadow would be reliably predicted from object shadows and that the bilateral beta oscillatory modulations would be indicative of the formation of predictive neural frontal assemblies, which encode and infer body shadow neural representation, that is, a substitution of the physical body.

A Confidence Interval for the Difference Between Standardized Regression Coefficients.

Researchers are often interested in comparing predictors, a practice commonly done via informal comparisons of standardized regression slopes. However, formal interval-based approaches offer advantages over informal comparison. Specifically, this article examines a delta-method-based confidence interval for the difference between two standardized regression coefficients, building upon previous work on confidence intervals for single coefficients. Using Monte Carlo simulation studies, the proposed approach is evaluated at finite sample sizes with respect to coverage rate, interval width, Type I error rate, and statistical power under a variety of conditions, and is shown to outperform an alternative approach that uses the standard covariance matrix found in regression textbooks. Additional simulations evaluate current software implementations, small sample performance, and multiple comparison procedures for simultaneously testing multiple differences of interest. Guidance on sample size planning for narrow confidence intervals, an R function to conduct the proposed method, and two empirical demonstrations are provided. The goal is to offer researchers a different tool in their toolbox for when comparisons among standardized coefficients are desired, as a supplement to, rather than a replacement for, other potentially useful analyses.

Leveraging Statistical Theory In Sports Competitions: An Analysis Of Probabilistic Models And Multiple Regression Within The Framework Of Big Data

CBA is a sports event that allows fans to enjoy themselves and players to give full play, and traditional Chinese cultural values have a profound influence on it. This paper takes the 100 sets of historical rating data of the fourteen teams in CBA league as the basic basis, firstly, we simply deal with the 100 sets of historical rating data and use Excel function formula to find out the mean, extreme deviation and variance of each team, then we carry out SAS normal test, and we find that except for the very few data with large deviation, the historical rating data satisfy the normal distribution. Through the outlier algorithm to screen the values, compare the confidence intervals as well as carry out hypothesis testing, to objectively and scientifically explore the probability of each team winning the championship in the CBA league. Compare the probability of winning the championship of these fourteen teams and predict the top four teams in the CBA league to ensure that the prediction results are as reasonable as possible. With the help of hierarchical analysis to qualitatively analyze the level of each team, and then through cluster analysis to compare these data, and combined with the trend of the development of the world's basketball movement, the use of multiple regression and SPSS to analyze the level of the team's factors, in-depth thinking about the league, a more reasonable to give a more scientific to improve the probability of the team's winning the championship, and to promote better development of the basketball movement. (AU)