Significant Influencing Factors Research Articles

Comparative analysis of nonlinear impacts on the built environment within station areas with different metro ridership segments

A plethora of studies have investigated the nonlinear correlation between the built environment and metro ridership. However, the spatiotemporal heterogeneity of this relationship from the perspective of ridership segmentation has received little attention. To address this gap, this study capitalizes on data collected from Wuhan, China. We employ a sophisticated amalgamation of quantile regression models and machine learning methods to construct direct ridership models (DRMs) for different ridership segments (low, medium, and high) and distinct temporal intervals (weekdays and weekends). The primary objective of these models is to scrutinize the salient factors that influence metro ridership within the context of spatiotemporal heterogeneity, including nonlinear relationships and threshold effects of the built environment. The research findings reveal pronounced differences in the significant influencing factors of the built environment on metro ridership across various ridership segments and temporal periods. Additionally, conspicuous spatiotemporal heterogeneity is discerned in the nonlinear relationships and threshold effects between the two. Consequently, considering the spatiotemporal heterogeneity inherent in metro stations, targeted policy optimization measures fostering the sustainable development of transit-oriented development (TOD) strategies are essential.

Association of dietary behavior patterns of middle-aged and older adults with their obesity metabolic phenotype: a cross-sectional study

BackgroundMiddle-aged and elderly individuals are the most susceptible groups for metabolic diseases, with their dietary behaviors being significant influencing factors. Exploring the association between overall dietary behaviors and obesity metabolic phenotypes is crucial for early prevention and control of chronic diseases, precision treatment and personalized interventions.MethodsWe conducted a cross-sectional study of 15,160 middle-aged and older adults between June 2019 and August 2021 to collect information on their body mass index (BMI), biochemical indices and disease history. The population was classified into four categories by the criteria of obesity metabolic phenotypes: metabolically healthy non-obesity (MHNO), metabolically unhealthy non-obesity (MUNO), metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). Scores were calculated based on compliance with healthy eating behavior patterns (appropriate or light dietary taste, moderately soft and hard food, slightly hot food temperature, medium or slow eating speed, daily intake of dietary supplements and eating with others), and the population was categorized into subgroups 0–2 (did not meet and met only 1 or 2), 3–4 (met 3 or 4), 5–6 (met 5 or 6). The relationship between dietary behavior patterns and different obesity metabolic phenotypes in middle-aged and elderly people were analyzed by multi-categorical logistic regression model.ResultsCompared with the 5–6 subgroup, the dietary behavior patterns of 0–2 and 3–4 scores were risk factors for MUNO, MHO and MUO (P < 0.05), and the lower the scores of the dietary behavior patterns, the higher the multiplicity of the occurrence of MUNO, MHO and MUO, especially for females and adults between 45–60 years old. Appropriate or light dietary taste, moderately soft and hard food, and slightly hot food temperature were protective factors for MUNO and MUO (P < 0.05); medium or slow eating speed and daily intake of dietary supplements were protective factors for MUNO, MHO and MUO (P < 0.05).ConclusionDietary behavior patterns in middle-aged and older adults are associated with different obesity metabolic phenotypes, and healthy dietary behaviors may be beneficial for the prevention and control of MUNO, MHO and MUO.

Experimental Investigation and Bayesian Assessment for Permeability Characteristics of Lightweight Ceramsite Concrete.

Ceramsite concrete is one of the most widely used lightweight concretes at present. Although mechanical properties of ceramsite concrete have been extensively discussed, its permeability characteristics are neglected in previous studies. Considering the importance of permeability resistance to concrete, the permeability grade and residual compressive strength after permeability of ceramsite concrete are analyzed in this study. The influence of ceramsite content and size on the permeability grade and residual strength of ceramsite concrete were investigated by the orthogonal experimental method. To further understand the above influence, an improved Bayesian framework for small sample data is also established to analyze the permeability grade and residual strength. Results show that the water-binder ratio and the content of 20-30 mm ceramsite aggregates are the most and least significant influencing factors affecting the permeability characteristics, respectively. The 5-10 mm and 10-20 mm ceramsite aggregates play secondary roles. Increasing 5-10 mm and 10-20 mm ceramsite aggregates is not helpful for improving the permeability resistance of ceramsite concrete. Compared with the orthogonal method, the proposed Bayesian framework is a useful tool for revealing the effects of various factors, which can cut the time cost and provide parameter visualization for the analysis process. Results show that the permeability resistance and residual strength of ceramsite concrete are improved significantly under optimal conditions. The permeability grade and residual strength are increased 200% and 80.3%, respectively. In addition, the residual strength may be more suitable for evaluating the permeability characteristics than the permeability grade.

Nutrition literacy level of medical personnel in tertiary hospitals: evidence from a cross-sectional study

BackgroundNutrition literacy (NL), stemming from health literacy, profoundly influences dietary habits and chronic diseases. Despite their pivotal societal role, scant research exists on NL levels among medical personnel. This study examined NL levels among tertiary hospital medical staff in Bengbu and identified influencing factors.MethodsUsing cluster sampling, all Bengbu tertiary hospitals were selected, with 4–5 departments randomly chosen. A structured questionnaire assessed demographic characteristics, while the NL short-form scale (NL-SF12) evaluated NL. SPSS 26.0 and AMOS conducted statistical analysis, including confirmatory factor analysis and Cronbach’s α for reliability. Chi-square tests and logistic regression analyzed group differences and influencing factors.ResultsThe NL-SF12 demonstrated robust reliability and validity. Of participants, 34.22% were male and 65.78% female; 41.03% were doctors and 42.16% nurses. Overall, 45.68% exhibited high NL. Females showed higher total NL (OR = 1.47, 95% CI: 1.08–1.98), cognition (OR = 1.66, 95% CI: 1.22–2.24), skills (OR = 1.48, 95% CI: 1.09-2.00), and interactive NL (OR = 2.21, 95% CI: 1.53–3.19) than males. Those with a master’s or higher had higher total NL (OR = 2.20, 95% CI: 1.33–3.65) and cognition (OR = 3.23, 95% CI: 1.94–5.37) than those with an associate degree or less. Pharmacists, inspectors, and technicians had higher total NL (OR = 1.55, 95% CI: 1.06–2.26) and functional NL (OR = 1.49, 95% CI: 1.02–2.17). Gender, education level, and career were the influencing factors of nutrition literacy among medical personnel.ConclusionsFemale medical staff and those with a master’s degree or higher showed higher nutrition literacy (NL), particularly in cognition and skills. Pharmacists, inspectors, and other technicians exhibited higher levels of total NL and functional NL. Gender, education level, and career were identified as significant influencing factors of nutrition literacy among medical personnel. Understanding and considering these factors are crucial for developing targeted strategies to enhance nutrition literacy among healthcare professionals. Future efforts to improve nutrition literacy through training and interventions should be tailored to the characteristics of different groups to effectively enhance the capabilities and proficiency of healthcare professionals in nutrition knowledge and practice.

Analyzing the worldwide progression of COVID-19 cases and deaths using nonlinear mixed-effects model.

COVID-19 is an infectious disease that continues to spread worldwide. A precise estimation of the cases and deaths due to COVID-19 would allow for appropriate consideration of healthcare resource allocation, public health response, and vaccination and economic planning, to minimize social damage. In this study, we analyzed the progression of COVID-19 cases and deaths until January 2022 in 156 countries using a nonlinear mixed-effect model based on the SIR framework. Given the major changes in mortality from infection, risk of re-infection and social responses, the analysis was limited to the period before the emergence of the Omicron variant. The impact of infection prevention measures in various countries was assessed, with a specific focus on estimating the effectiveness of lockdowns, where the effect was assumed to change over time. By accounting for excess mortality, our analysis allowed the estimation of unreported cases and deaths, and thus providing a more comprehensive understanding of the impact of pandemic. In the analysis, we identified gross domestic product (GDP), proportion of people aged 65 years or older, latitude of the capital city on transmissibility of infection, and city population and cardiovascular death rate on mortality rate as significant influencing factors. Furthermore, the differences in transmissibility and mortality rates by variants and the effect of vaccination on the mortality rate were assessed. The transmissibility has increased by odds ratios of 1.2 to 1.4 in Beta, Gamma, and Delta variants; mortality rate has increased by odds ratios of 1.7, 2.2, and 1.4 in Beta, Gamma, and Delta variants, respectively; and vaccination decreased the mortality rate by odds ratios of 0.4 and 0.1 in Delta and other variants, respectively.

Factors associated with nursing students' mental health-related stigma: A multisite cross-sectional study

BackgroundMental health-related stigma remains a complex and pervasive issue globally. It not only inhibits individuals from seeking help but also influences the quality of healthcare they receive. Despite extensive research on mental health-related stigma, there is still limited understanding of factors influencing mental health-related stigma among nursing students. ObjectivesThis study aimed to assess the level of mental health-related stigma among Chinese nursing students and investigate possible associated factors. MethodsData were collected from the 2023 Psychology and Behavior Investigation of Chinese Residents (PBICR) survey. A total of 967 nursing students were included in the study. Multivariate stepwise linear regression analysis was conducted to examine the influencing factors of mental health stigma. ResultsThe mean mental health-related stigma score among nursing students was 15.31 ± 5.23 (range = 0–27). Perceived stress (β = 0.14, P = 0.001), self-efficacy (β = 0.22, P < 0.001), academic stage (β = 0.17, P < 0.001), depression (β = 0.15, P < 0.001), and adverse life events (β = 0.06, P = 0.044) were significantly associated with mental health-related stigma among nursing students (R2 = 0.147, adjusted R2 = 0.143, F = 33.214, P < 0.001). ConclusionsNursing students in China exhibit a moderate level of mental health-related stigma, suggesting room for improvement. Perceived stress, self-efficacy, academic stage, depression, and adverse life events emerged as significant influencing factors for mental health-related stigma. These findings provide valuable insights for developing interventions to reduce mental health-related stigma among nursing students, ultimately enhancing their well-being and preparing them for becoming competent healthcare professionals in the future.

Heterogeneity in public health service utilization and its relationship with social integration among older adult migrants in China: a latent class analysis.

The older adult migrant population in China is on the rise, which presents challenges for the national public health service system. However, the heterogeneity of public health service utilization and its relationship with social integration among the older adult migrant population remains unclear. This study aims to explore the heterogeneity the public health service utilization and how it relates to their social integration. A total of 6,178 older adult migrants from the China Migrants Dynamic Survey (CMDS) in 2017 were included in this study. Exploratory factor analysis was used to categorize social integration into four dimensions. Latent class analysis (LCA) was used to identify different sub-groups of public health service utilization. ANOVA and multivariate logistic regression were used to determine the characteristics of different sub-groups. Three potential classes of public health service utilization were identified: low utilization of basic public health services class (N = 3,264,52.756%), medium utilization of basic public health services class (N = 1,743,28.172%), and high utilization of basic public health services class (N = 1,180,19.072%). Gender, education, extent of mobility, and move alone or not, flow time were all predictors of the class of public health service utilization. There were significant differences in social integration across potential categories (p<0.0001). The utilization of public health services of the older adult migrants is affected by many aspects. Social integration deserves attention as a significant influencing factor in the utilization of public health services. The government should pay attention to the characteristics of the older adult migrants and formulate relevant policies in a targeted manner in order to improve the utilization of public health services of the older adult migrants.

Peri-urban dynamics: assessing expansion patterns and influencing factors

BackgroundPeri-urbanization, the expansion of large metropolitan centers into adjacent peri-urban regions, is a growing concern due to land scarcity and escalating housing costs. These zones, a blend of rural and urban features, blur the line between urban and rural areas, creating new landscapes. This study examines historical, present, and potential growth trends in the peri-urban area surrounding Durgapur Municipal Corporation (DMC). Analytical techniques and spatial metrics are used to track development intensity changes over time, including built-up density, Shannon’s entropy, Landscape expansion index, Average Weighted Mean Expansion Index, Annual Built-Up Expansion Rate, Built-Up Expansion Intensity Index, and Built-Up Expansion Difference Index. Landscape indices like Patch Density, Edge Density, Landscape Shape Index, Largest Patch Index, Ratio of Open Space, and Area Weighted Mean Patch Fractal are used to understand fragmentation, connectivity, and spatial relationships. The Logistic Regression Model (LRM) is used to identify influencing factors and CA-Markov modeling for future built-up areas.ResultsBetween 1991 and 2001, built-up area in the region increased significantly, primarily due to urban development near industrial zones, roadways, and mining areas. The growth was primarily concentrated in the western sector and near National Highway-2 (NH-2). Urban sprawl was a continuous trend, with the highest built-up density in the South-South-East (SSE) direction from 1991 to 2011. Additionally, a key determinant of built-up development was the distance to the city core. By 2031, the built-up area is expected to concentrate in the western and southeast regions, reaching 177.90 km2.ConclusionsThis expansion is attributed to urban development near industrial zones, roadways, mining areas, and other infrastructure. The study identifies distance to the city center as a significant influencing factor for built-up development. The results emphasize the need for inclusive urban planning methods prioritizing sustainable development principles and prudent resource management for future growth and efficient management in the DMC’s peri-urban area.

Efficient conversion process and mechanism of bromine in bromine-rich saline wastewater

Bromine resources, widely utilized in basic chemical engineering, are considered non-renewable. A substantial amount of Bromine-Rich Saline Wastewater (BRSW), a hazardous waste, is generated during the smelting process of waste printed circuit boards (WPCBs). The efficient conversion of bromine resources is important in BRSW, which contain high concentrations of bromide ions. This study developed a synergistic treatment method utilizing electrolytic manganese anode sludge (EMAS) achieved efficient conversion of Br− to Br2 in BRSW. Optimal technical parameters are determined through single-factor experiments, and the oxidative acid leaching process was optimized using response surface methodology (RSM). The significant influencing factors for Br− conversion were ranked as acidity > anode mud addition amount > temperature > time, resulting in a bromine conversion efficiency of 96.55%. Kinetic studies of bromine conversion in BRSW during the oxidation-acid leaching process indicated a two-stage process: Stage I being a chemical reaction control model and Stage II being a diffusion control model. The reaction mechanism was elucidated, where H+ initially breaks the Mn-O bond in MnO2, exposing O vacancies and forming Mn4+, leading to a redox reaction between free Br− and Mn4+. This research embodies the concept of synergistic solid waste disposal, achieving cost-effectiveness and streamlined preparation of bromine, and providing technical and theoretical support for bromine resource recovery in BRSW.

Prevalence of Smoking Among School Students in Iraq.

Background Developing communities like Iraq are critical to building a good community environment. Many complex patterns of behaviors like smoking among adolescents have been exacerbated rapidly in the current era which led to changes in the Iraqi community's perspectives and life expectancy. This study aims to find out the prevalence of smoking among secondary school students in Iraq and their perceived contributing factors. Methods A cross-sectional study design was used with a representative sample of Iraqi school students recruited through a multistage cluster randomization from the Nineveh Governorate's intermediate and secondary schools to ensure the representation of the general public strata. A total of 330 students were randomly selected from eight schools distributed all over Mosul city (the center of Nineveh Governorate) and its boundaries semi-rural areas. Data collection utilized a standardized, anonymous questionnaire based on the Global Youth Tobacco Survey (GYTS) administered within classrooms with the researcher's presence. The questionnaire included questions related to sociodemographic characteristics of the students, smoking state, smoking types, frequency of smoking, relative smoking state, opinion on predisposing factors for initiation of smoking, and knowledge about hazards of smoking. Data analysis was done using SPSS version 26 to calculate frequency distribution with further logistic regression analysis was performed to identify statistically significant factors contributing to initiation of smoking among the student participants with p-value estimation of any compares considered significant below 0.05. Results Prevenance of all types of smoking was 24.5% from 330 students with 30% from 246 males and 7%from 84 females has been encountered. Hookah (Shisha) was the most prevalent type of smoking.About a third of the smoker sample reported smoking at least once daily. Peer pressure (OR=3.49, P< 0.001) or family smoking (OR=1.769, P=0.019) emerged as the strongest influence for initiation of smoking, besides stress (OR=2.23, P= 0.04) and personality traits like stammering and jealousy (OR=2.58, P= 0.013), (OR=2.22, P= 0.017, respectively) have also significant odds. Interestingly, media (movie star) influence played a significant role also. (OR=1.492, P= 0.045). Conclusion The prevalence of smoking among the study sample was 24.5 % out of 330 participating students. Significant influencing factors were found that raised the concern and necessitated the development of targeted interventions. Implementing evidence-based strategies, such as comprehensive school-based educational programs and smoke-free indoor air policies, can significantly improve public health outcomes.

A multicenter cross-sectional study in China revealing the intrinsic relationship between medical students’ grade and their perceptions of the learning environment

BackgroundMedical school learning environment (MSLE) has a holistic impact on students’ psychosomatic health, academic achievements, and personal development. Students in different grades perceive MSLE in different ways. Thus, it is essential to investigate the specific role of student’s grade in the perception of MSLE.MethodsUsing the Johns Hopkins Learning Environment Scale (JHLES) as a quantification instrument for the perception level of MSLE, 10,901 medical students in 12 universities in China were categorized into low or high JHLES group according to their questionnaires. We investigated the relationship between student’s grade and JHLES category by univariate analysis employing Pearson Chi-square test and Welch’s ANOVA. Then multivariable logistic regression analysis confirmed the predictive efficacy of student’s grade. A nomogram concerning the prediction of low JHLES score probability in medical students was also constructed.ResultsA significant difference between two JHLES categories among students in different grades was observed (p < 0.001), with the proportion of the high JHLES group dominating in grade 1, 5, and the graduate subgroups (p < 0.001). The mean JHLES score declined especially in the third and fourth graders compared to freshmen (p < 0.001), while the mean score among the fifth graders had a remarkable rebound from the third graders (p < 0.001). Most imperatively, identified by multivariable logistic regression analysis, students in grade 3 (OR = 1.470, 95% CI = 1.265–1.709, p < 0.001) and 4 (OR = 1.578, 95% CI = 1.326–1.878, p < 0.001) perceived more negatively than freshmen. The constructed nomogram provided a promising prediction model for student’s low JHLES score probability, with accuracy, accordance, and discrimination (area under the curve (AUC) = 0.627).ConclusionThe student’s grade was a significant influencing factor in medical students’ perception of MSLE. The perceptions among the third and fourth graders got worse, probably due to the worrying changes in various aspects of MSLE during that period. The relevant and appropriate interventions to improve medical students’ perceptions are urgently needed.

Analysis of Influencing Factors for Choosing Dermatology as a Future Career: A Cross-Sectional Study Among Medical Students at King Abdulaziz University.

Determining the influencing factors of choice of medical specialty is key to a balanced distribution of physicians across specialties. Dermatology, the specialty concerned with treating skin disorders, is known for being among the most wanted; however, studies identifying the factors that attract students to this specialty are lacking. Our study aimed to investigate the influencing factors of the choice of dermatology as a career in clinical-year medical students. We conducted a cross-sectional study with a sample of clinical-year medical students from King Abdulaziz University, Jeddah, Saudi Arabia, between 2020 and 2021. We collected data using an online self-administered questionnaire; we replicated a questionnaire present in prior research. We compared categorical data using the chi-square and Fisher's exact tests. Results: In total, there were 252 participants, with 30 (11.9%) choosing dermatology as a specialty. Over half showed an average grade of more than 4.5 (66.7%), and 83.3% were female. The significant influencing factors of students' choice of dermatology as a career were: the likelihood of dermatologists influencing patients' lives (p=0.000), opportunities to conduct research in dermatology (P=0.000), how Dermatology allows people to have a satisfying family life (P=0.001), and opportunities for part-time work in dermatology (p=0.000). Many factors influenced the choice of a future medical specialty in our sample. Focusing on these factors while guiding students to choose their specialty may enable a promising next generation of physicians.

CBAM VGG16: An efficient driver distraction classification using CBAM embedded VGG16 architecture

Driver monitoring systems (DMS) are crucial in autonomous driving systems (ADS) when users are concerned about driver/vehicle safety. In DMS, the significant influencing factor of driver/vehicle safety is the classification of driver distractions or activities. The driver’s distractions or activities convey meaningful information to the ADS, enhancing the driver/ vehicle safety in real-time vehicle driving. The classification of driver distraction or activity is challenging due to the unpredictable nature of human driving. This paper proposes a convolutional block attention module embedded in Visual Geometry Group (CBAM VGG16) deep learning architecture to improve the classification performance of driver distractions. The proposed CBAM VGG16 architecture is the hybrid network of the CBAM layer with conventional VGG16 network layers. Adding a CBAM layer into a traditional VGG16 architecture enhances the model’s feature extraction capacity and improves the driver distraction classification results. To validate the significant performance of our proposed CBAM VGG16 architecture, we tested our model on the American University in Cairo (AUC) distracted driver dataset version 2 (AUCD2) for cameras 1 and 2 images. Our experiment results show that the proposed CBAM VGG16 architecture achieved 98.65% classification accuracy for camera 1 and 97.85% for camera 2 AUCD2 datasets. The CBAM VGG16 architecture also compared the driver distraction classification performance with DenseNet121, Xception, MoblieNetV2, InceptionV3, and VGG16 architectures based on the proposed model’s accuracy, loss, precision, F1 score, recall, and confusion matrix. The drivers’ distraction classification results indicate that the proposed CBAM VGG16 has 3.7% classification improvements for AUCD2 camera 1 images and 5% for camera 2 images compared to the conventional VGG16 deep learning classification model. We also tested our proposed architecture with different hyperparameter values and estimated the optimal values for best driver distraction classification. The significance of data augmentation techniques for the data diversity performance of the CBAM VGG16 model is also validated in terms of overfitting scenarios. The Grad-CAM visualization of our proposed CBAM VGG16 architecture is also considered in our study, and the results show that VGG16 architecture without CBAM layers is less attentive to the essential parts of the driver distraction images. Furthermore, we tested the effective classification performance of our proposed CBAM VGG16 architecture with the number of model parameters, model size, various input image resolutions, cross-validation, Bayesian search optimization and different CBAM layers. The results indicate that CBAM layers in our proposed architecture enhance the classification performance of conventional VGG16 architecture and outperform the state-of-the-art deep learning architectures.

基于离散元法的油莎豆振动参数标定与试验

In this study, the parameters of tiger nut were calibrated based on discrete element method, and significant influencing factors and optimal levels were selected by Plackett-Burman test, steepest climb test and center compound test, and verified by electromagnetic vibration hopper bench test. The results show that the relative error between the simulated resting angle and the actual resting angle is only 0.381%. The fitting degree of the model is 96.32% and 94.57% respectively, which can provide theoretical basis for the study of the parameters and discrete element simulation of tiger nut.

Impact of COVID-19 on Sleep, Anxiety, and Depression Among Medical Call Center Staff: Insights from a January 2021 Study.

BACKGROUND The COVID-19 outbreak emerged as a dual threat, effecting both the physical and mental well-being of healthcare staff. This study aimed to evaluate sleep quality using the Pittsburgh Sleep Quality Index (PSQI), levels of anxiety and depression using the Hospital Anxiety Depression Scale (HADS), and the significant influencing factors during COVID-19 pandemic in 284 workers in a medical call center in January 2021. MATERIAL AND METHODS Out of 443 pre-hospital care providers, 284 consented to participate. Data collection was done using an introductory information form, the PSQI for sleep quality, and the HADS for anxiety (HADS-A) and depression (HADS-D). Surveys were hosted on an online survey website and distributed via WhatsApp, with completed forms retrieved from the website. RESULTS Male sex (P=0.0001) and extended working hours in current workplace (P=0.017) were associated with higher HADS-A scores. Health problems, increased need for mental support, and poor job satisfaction correlated with lower HADS-D scores (P=0.025, P=0.005, P=0.0001, respectively) and higher PSQI scores (P=0.008, P=0.009, P=0.008, respectively). A moderately significant positive correlation was found between overall sleep quality and HADS-A (P=0.001, r=0.538) and HADS-D scores (P=0.001, r=0.493). CONCLUSIONS The pandemic significantly impacted the mental health and sleep quality of frontline healthcare personnel, necessitating the identification and mitigation of adverse psychosocial factors. Implementing and evaluating psychoeducational programs and establishing multidisciplinary mental health teams can provide for essential support and counseling, promoting the well-being of healthcare staff and ensuring effective emergency care.

Impact of contextual factors on the evaluation outcomes of national virtual simulation experimental teaching projects in biology and medicine

The number of applications for National Virtual Simulation Experimental Teaching Projects (NVSETPs) in China has seen a significant increase. Consequently, the influence of contextual factors and their potential personal connections on the evaluation results, whether for national or non-national NVSETPs, has become a prominent concern. In this study, we employed a modified back-chaining method using logistic regression to examine whether contextual factors in NVSETP applications could explain the evaluation outcomes. Our analysis was based on data available on the open platform of China's Ministry of Education (MOE). We identified several significant influencing factors, including the score on a five-point rating system, the number of clicks on the application page, school quality, school region, and the gender, title, and position of the applicants. Our results shed light on the impact of contextual factors on the evaluation results of NVSETPs in the fields of biology and medicine, using a modified back-chaining method. We conclude that enhancing the transparency of the assessment process and implementing standardized, detailed scoring guidelines for NVSETPs would mitigate the negative influence of contextual factors.

Determination of Teacher Performance in Improving Education Quality in the Pandemic Era

Determining Teacher Performance to Improve the Quality of Education in the Pandemic Era. The problem that is used as the object of research is teacher performance which is seen to have decreased due to the change in the learning system from offline to online. This can cause the quality of education to decline. This research aims to analyze: 1). The Influence of Internal Factors on Teacher Performance. 2). The influence of internal factors on the quality of education. 3). The influence of external factors on teacher performance. 4). The influence of external factors on the quality of education. 5). The influence of teacher performance on the quality of education. 6). The influence of internal factors on the quality of education is mediated by teacher performance. 7). The influence of external factors on the quality of education is mediated by teacher performance. The data collection technique was using a questionnaire given to 85 respondents (teachers) from 3 schools, namely SMA Al Adzkar, SM AI Sinar Cendikia and Sekolah Alam Bintaro. The hypothesis used is Smart PLS ( Partial Least Square ). The research results show that: 1). The statistical value of internal factors on performance is 3.116 with a p value of 0.00 2 and a p value of less than 0.05, so it has a positive effect on teacher performance. 2). The statistical t value of internal factors on the quality of education is 3.277, the p value is 0.001 and the p value is more than 0.05, then positive influence on the quality of education. 3). The statistical t value of external factors on teacher performance is 2.561 with a p value of 0.011 or less than 0.05, so it has a positive effect on teacher performance. 4). The statistical value of external factors on the quality of education is 3.920 with a p value of 0.000 or a p value of more than 0.05, so it has a positive effect on the quality of education. 5). The statistical t value of teacher performance on the quality of education is equal to a p value of 0.022, so teacher performance has a positive effect on the quality of education. 6). The VAF value is 0.598, this shows that teacher performance is a partial mediator in the relationship between internal factors and the quality of education. 7). The VAF value is 0.631, this shows that teacher performance is a partial mediator in the relationship between external factors and the quality of education. The research conclusion is that, 1). There is a positive and significant influence of f actors internal on teacher performance. 2). There is a positive and significant influence of internal factors on the quality of education. 3). There is positive and significant influence external factors on teacher performance. 4) There is a positive and significant influence external factors on the quality of education. 5). There is a positive and significant influence on teacher performance to quality of education. 6) There is a positive and significant influence between internal factors on the quality of education with teacher performance as mediation. 7). There is a positive and significant influence between external factors on the quality of education and teacher performance as mediation.

Impacts of COVID-19 on the Building Construction Industry in Nepal

The COVID-19 epidemic has created unprecedented challenges for global economies, affecting every industry, including the building construction industry in Nepal as well. This research aims to examine the impact of the COVID-19 epidemic on the building construction industry in Nepal. This study examines institutional, psychological, individual, operational, contractual, and financial factors. To achieve the objective, data were collected from 330 Nepalese construction professionals using a structured Likert scale questionnaire and analyzed with Smart PLS version 3 software for partial least squares structural equation modeling. The reliability and validity of both the measurement and structural models were tested and found satisfactory. All six factors were found to be significant at a 5% level of significance. Among all factors, the institutional factor was found as the most significant factor with a t-value of 7.654 and a beta value of 0.679, emphasizing the crucial role of institutional support in Nepal's building construction industry. The psychological factor also emerged as the second most significant influential factor (t value: 6.087, beta value: 0.463), underscoring the profound effect on the mental well-being of professionals in the field. The finding highlights the critical importance of institutional support and the profound influence of psychological factors on the well-being of construction professionals, necessitating targeted interventions to support the industry's recovery and resilience.

성장혼합모형을 적용한 교사-아동 갈등관계 변화 유형화, 영향요인 및 학교적응 차이 검증

Objectives This study aimed to typify the longitudinal changes in teacher-child conflict relationships among elementary school students and to verify the impact of children's personal and parental factors on the classification of latent profiles in the trajectories of changes in teacher-child conflict relationships. Additionally, the study examined differences in school adaptation across types of teacher-child conflict relationships. Methods Utilizing data from the 9th to 13th waves (2nd to 6th grade in elementary school) of the Panel Study on Korean Children(PSKC), the study estimated a change function suitable for the changes in teacher-child conflict relationships and applied it to classify latent classes. A growth mixture model was used to identify the significance of related child, parental factors, and school adaptation. Results First, it was found that a first-order function model was suitable for the longitudinal changes in teacher-child conflict relationships, and three latent profiles (‘Decreasing’, ‘Maintaining’, ‘Increasing’) were identified based on this model. Upon verifying the influencing factors, compared to the ‘Maintaining’ group set as the reference group, externalized difficulties were significant in the ‘Increasing’ group, while parental interest in school life and externalized difficulties had a significant impact in the ‘Decreasing’ group. Furthermore, when the ‘Decreasing’ group was set as the reference group, externalized difficulties emerged as a significant influencing factor in comparison with the ‘Increasing’ group. In addition, there were overall differences in school adaptation among the three classified groups, with the ‘Maintaining’ group showing a higher level of school adaptation than the ‘Decreasing’ group. Conclusions Based on these results, the study discussed possible measures for improving the conflict relationships between teachers and children.

A 10-year mono-center study on patients with burns ≥70% TBSA: prediction model construction and multi-center validation: retrospective cohort.

Burn injuries with ≥70% total body surface area (TBSA) are especially acute and life-threatening, leading to severe complications and terrible prognosis, while a powerful model for prediction of overall survival (OS) is lacked. The objective of this study is to identify prognostic factors for the OS of patients with burn injury ≥70% TBSA, construct and validate a feasible predictive model. Patients diagnosed with burns ≥70% TBSA admitted and treated between 2010 and 2020 in our hospital were included. A cohort of the patients from the Kunshan explosion were assigned as the validation set. The Chi-square test and K-M survival analysis were conducted to identify potential predictors for OS. Then, multi-variate Cox regression analysis was performed to identify the independent factors. Afterwards, we constructed a nomogram to predict OS probability. Finally, the Kunshan cohort was applied as an external validation set. Gender, the percentage of third- and fourth-degree burn as well as organ dysfunction were identified as significant independent factors. A nomogram only based on the factors of the individuals was built and evidenced to have promising predictive accuracy, accordance, and discrimination by both internal and external validation. This study recognized significant influencing factors for the OS of patients with burns ≥70% TBSA. Furthermore, our nomogram proved to be an effective tool for doctors to quickly evaluate patients' outcomes and make appropriate clinical decisions at an early stage of treatment.