Statistical Linear Regression Research Articles

Satisfação de discentes no Ensino Superior: uma análise a partir do curso de Agronomia do Instituto Federal Goiano

Este estudo tem como objetivo avaliar a satisfação percebida pelos alunos do curso de agronomia de dois campis do Instituto Federal Goiano em relação ao curso de Agronomia. A identifica­ção dos principais componentes da Satisfação Geral dos estudantes foi feita com base em estudos ante­riores. Os dados foram coletados por aplicação de questionários a 149 estudantes do curso de do curso de agronomia e analisados através das técnicas estatísticas Análise de Cluster Hierárquica e Regressão Linear Múltipla, para estabelecer de forma não paramétrica, uma vez que os construtos não apresentaram distribuição normal, quais dos construtos estudados representam a satisfação geral dos estudantes. Os resultados apon­taram que o Envolvimento do Professor e Interação entre o Professor e o Estudante, são os construtos determinantes para a satisfação geral do estudante, demonstrando nesse estudo que o papel do professor se mostra de grande importância na sensação de satisfação por parte do aluno do curso de agronomia.

Consumption of Beverages Containing Low-Calorie Sweeteners, Diet, and Cardiometabolic Health in Youth With Type 2 Diabetes

BackgroundLow-calorie sweetened beverages (LCSBs) are commonly used as a lower-calorie alternative to sugar-sweetened beverages (SSBs) by individuals with type 2 diabetes. However, little is known about how intake of LCSBs is related to dietary intake and cardiometabolic health, particularly among youth. ObjectiveTo test the hypothesis that having higher baseline LCSB intake and increasing LCSB intake over 2 years of follow-up are associated with poorer dietary intake and higher cardiometabolic risk factors among youth enrolled in the Treatment Option for Type 2 Diabetes in Adolescents and Youth (TODAY) study. DesignSecondary, exploratory, analysis of baseline and longitudinal data from the TODAY study, which was a randomized, multisite trial conducted from 2004 to 2012, to compare effects of 3 interventions (metformin alone, metformin + rosiglitazone, and metformin + intensive lifestyle intervention) on glycemic control in youth with type 2 diabetes. Participants/settingThe study included 476 children and adolescents (10-17 years, mean body mass index 34.9 ± 7.8 kg/m2), who were participants in the multicenter (n = 15) TODAY study. Main outcome measuresDiet was assessed using a food frequency questionnaire. Differences in energy intake, macronutrients, food group intakes, and cardiometabolic biomarkers were evaluated in 3 groups of LCSB consumers at baseline (low [1-4 servings/wk], medium [5-11 servings/wk], and high [≥12 servings/wk]), each compared with nonconsumers, and between 4 groups of change in LCSB intake (nonconsumption at start of study and nonconsumption after 2 years, increase in consumption after 2 years, decrease in consumption after 2 years, and high consumption at start of study and high consumption after 2 years). Statistical analyses performedMultivariable linear regression was performed at baseline and longitudinally over 2 years of follow-up. ResultsEnergy (kilocalories), fiber, carbohydrate, total fat, saturated fat, and protein intake (grams) were higher among high LCSB consumers compared with nonconsumers at baseline. No associations were observed between LCSB consumption and cardiometabolic risk factors at baseline. Change in LCSB intake between baseline and follow-up was not associated with change in energy intake or cardiometabolic risk factors. Participants who decreased LCSB consumption reported greater increases in sugar intake (18.4 ± 4.8 g) compared with those who increased LCSB consumption (5.7 ± 4.9 g) or remained high LCSB consumers (5.9 ± 7.4 g), but this trend was not statistically significant after a correction for multiple testing. ConclusionsLCSB consumption was associated with higher energy intake in youth with type 2 diabetes, with the highest energy intakes reported in high LCSB consumers. Those who reduced LCSB consumption tended to report greater increases in sugar intake during follow-up, but further studies are needed to better understand this trend.

DAMPAK DANA DESA TERHADAP PEMBANGUNAN DESA DAN PEMBERDAYAAN MASYARAKAT DESA (STUDI KASUS PADA DESA CIBITUNG KECAMATAN SAGARANTEN KABUPATEN SUKABUMI)

The priority of village funds is used to finance the implementation of village programs and activities in the field of village development and village community empowerment. The development and empowerment of village communities can be carried out well if the management of village funds is carried out in a transparent, accountable, orderly and disciplined budget as well as the participation of various parties. The purpose of this study was to determine the effect of village funds on village development and village community empowerment (Case Study in Cibitung Village, Sagaranten District, Sukabumi). The research method used in this research is the mix method. The object of this research is the people of Cibitung Village, Sagaranten Sukabumi District, the sampling technique in this study was determined by quota sampling of 110 respondents. For statistical analysis simple linear regression analysis is used, the coefficient of determination and to test the hypothesis the t test is used. Based on the results of research and data analysis that has been done, the test results are obtained that the management and distribution of village funds on target can have an impact on the progress of village development and empowerment of rural communities so as to encourage the development of community independence and increase the welfare of village communities.

A mixed methods approach to exploring the moderating factors of implementation fidelity of the integrated chronic disease management model in South Africa

BackgroundChronic care models like the Integrated Chronic Disease Management (ICDM) model strive to improve the efficiency and quality of care for patients with chronic diseases. However, there is a dearth of studies assessing the moderating factors of fidelity during the implementation of the ICDM model. The aim of this study is to assess moderating factors of implementation fidelity of the ICDM model.MethodsThis was a cross-sectional mixed method study conducted in two health districts in South Africa. The process evaluation and implementation fidelity frameworks were used to guide the assessment of moderating factors influencing implementation fidelity of the ICDM model. We interviewed 30 purposively selected healthcare workers from four facilities (15 from each of the two facilities with lower and higher levels of implementation fidelity of the ICDM model). Data on facility characteristics were collected by observation and interviews. Linear regression and descriptive statistics were used to analyse quantitative data while qualitative data were analysed thematically.ResultsThe median age of participants was 36.5 (IQR: 30.8–45.5) years, and they had been in their roles for a median of 4.0 (IQR: 1.0–7.3) years. The moderating factors of implementation fidelity of the ICDM model were the existence of facilitation strategies (training and clinical mentorship); intervention complexity (healthcare worker, time and space integration); and participant responsiveness (observing operational efficiencies, compliance of patients and staff attitudes). One feature of the ICDM model that seemingly compromised fidelity was the inclusion of tuberculosis patients in the same stream (waiting areas, consultation rooms) as other patients with non-communicable diseases and those with HIV/AIDS with no clear infection control guidelines. Participants also suggested that poor adherence to any one component of the ICDM model affected the implementation of the other components. Contextual factors that affected fidelity included supply chain management, infrastructure, adequate staff, and balanced patient caseloads.ConclusionThere are multiple (context, participant responsiveness, intervention complexity and facilitation strategies) interrelated moderating factors influencing implementation fidelity of the ICDM model. Augmenting facilitation strategies (training and clinical mentorship) could further improve the degree of fidelity during the implementation of the ICDM model.

Investigation of the Environmental and Socio-Economic Characteristics of Counties with a High Asthma Burden to Focus Asthma Action in Utah

Rising adult asthma prevalence (AAP) rates and asthma emergency room (AER) visits constitute a large burden on public health in Utah (UT), a high-altitude state in the Great Basin Desert, USA. This warrants an investigation of the characteristics of the counties with the highest asthma burden within UT to improve allocation of health resources and for planning. The relations between several predictor environmental, health behavior and socio-economic variables and two health outcome variables, AAP and AER visits, were investigated for UT’s 29 counties. Non-parametric statistical comparison tests, correlation and linear regression analysis were used to determine the factors significantly associated with AER visits and AAP. Regression kriging with Utah small area data (USAD) as well as socio-economic and pollution data enabled local Moran’s I cluster analysis and the investigation of moving correlations between health outcomes and risk factors. Results showed the importance of desert/mining dust and socio-economic status as AAP and AER visits were greatest in the south of the state, highlighting a marked north–south divide in terms of these factors within the state. USAD investigations also showed marked differences in pollution and socio-economic status associated with AAP within the most populous northern counties. Policies and interventions need to address socio-economic inequalities within counties and between the north and south of the state. Fine (PM2.5) and coarse (PM10) particulate matter monitors should be installed in towns in central and southern UT to monitor air quality as these are sparse, but in the summer, air quality can be worse here. Further research into spatiotemporal variation in air quality within UT is needed to inform public health interventions such as expanding clean fuel programs and targeted land-use policies. Efforts are also needed to examine barriers to routine asthma care.

High-sensitivity cardiac troponin I in women with a history of early-onset preeclampsia.

Preeclampsia is associated with an elevated risk of cardiovascular disease later in life. Women with a history of preeclampsia are at risk of developing hypertension as well as ischemic heart disease. Identification of women at the highest risk is important to initiate preventive strategies. We investigated whether high-sensitivity cardiac troponin I (hs-cTnI) levels are associated with a history of early-onset preeclampsia, and with hypertension in these high-risk women. Approximately 9-10 years after pregnancy, hs-cTnI levels were measured for 339 women of the Preeclampsia Risk Evaluation in FEMales cohort, consisting of 177 women with a history of early-onset preeclampsia and 162 women with a previous uncomplicated index pregnancy. Associations were analyzed using several statistical tests and linear regression analysis. The median hs-cTnI levels (IQR) were 2.50 ng/l (2.30) in women with a history of early-onset preeclampsia and 2.35 ng/l (2.50) in women without a history of preeclampsia, P = 0.53. Among women with a history of early-onset preeclampsia, the hs-cTnI levels were higher in women who were hypertensive compared with their normotensive counterparts (medians 2.60 versus 2.30; P = 0.03). In addition, blood pressure levels increased with increasing hs-cTnI levels. We did not find a difference in hs-cTnI levels between women with and without a history of early-onset preeclampsia. Nonetheless, hs-cTnI levels were statistically significantly higher in current hypertensive women with a history of preeclampsia compared with their normotensive counterparts. Therefore, hs-cTnI levels might improve risk prediction for women at the highest risk of cardiovascular disease.

Improving Critical Thinking Skill of Junior High School Students through Science Process Skills Based Learning

This study aimed to investigate impact the science process skill-based learning on critical thinking skills of Junior High School students. Subjects were eighth grade students of Rengel Junior High School 1 that were selected by purposive random sampling. Measurement data by means of science process skills test and critical thinking skill test was analyzed by using inferential statistical one-tailed t-test and linear regression. The results showed that implementation of science process skill-based learning was effective to improve the critical thinking skill of Junior High School student

Wave characteristics in the nearshore waters of Sanmen bay

The wave characteristics in the bay of central coast of Zhejiang are studied based on the AWAC-measured data for 1 year off Sanmen at 7.5 m water depth. The observed wave parameters are analyzed by statistical analysis and linear regression analysis, and moreover the variations of wave parameters and wave spectra in Sanmen Bay under the influence of typhoon are discussed. The results show that: The dominant wave direction and the strong wave direction are both E due to the topography of Sanmen Bay, while the one-tenth wave height (H1/10) is mainly under 0.8 m with a typical Rayleigh distribution of wave height. Due to the influence of typhoon Talim, the maximum wave height (Hmax) of 2.71 m was observed on 14 September 2017. The wave spectra estimated during typhoon Talim are mainly double-peaked, and the sea waves are mixed waves consisting of swells and wind-seas, when the low frequency swells about 0.08 Hz are in a dominant position and the high frequency wind-seas about 0.3 Hz are relatively weak. This study will be important as reference in the design of offshore structures as well as for disaster prevention and mitigation.

Ultrasound-Guided Percutaneous Irrigation of Rotator Cuff Calcific Tendinopathy (US-PICT): Patient Experience.

Purpose To assess patients' experience of ultrasound-guided percutaneous irrigation of rotator cuff calcific tendinopathy (US-PICT). Methods Ninety-one patients (58 females; mean age: 50.5 ± 8.3 years) treated by US-PICT (local anesthesia, single-needle lavage, and intrabursal steroid injection) answered to a list of questions regarding their experience of the procedure before treatment, immediately after treatment, and three months later. The Borg CR10 scale was used to evaluate perceived pain, discomfort during anesthetic injection, and anxiety. The Wilcoxon, Spearman's rho, linear regression, and chi-square statistics were used. Results 81/91 patients complained mild discomfort during the injection of anesthetics (2, 1-2). Pain scores during US-PICT were very low (0, 0-1), with 70% patients having not experienced pain. After treatment, we found a significant reduction of pain (before: 8, 7-8; 3-month: 3, 1-6; p < .001) and anxiety (before: 5, 2-7; during treatment: 2, 1-7; p = 0.010), with high overall satisfaction (immediately after: 10, 9-10; 3-month: 9, 7-10) and confidence in the possibility of recovery (immediately after: 9, 8-10; 3-month: 10, 8-10), respectively. Treatments performed before US-PICT were not statistically associated with pain relief (p = 0.389) and clinical improvement (p = 0.937). We found a correlation between satisfaction immediately postprocedure and confidence in the possibility of recovery (p = 0.002) and between satisfaction three months after treatment and clinical improvement (p < 0.001) and patients' reminds about the description of the procedure (p = 0.005) and of the potential complications (p = 0.035). Conclusions US-PICT is a mildly painful, comfortable, and well-tolerated procedure, regardless of any previous treatments. Patients' satisfaction is correlated with clinical benefit and full explanation of the procedure and its complications.

Vehicle related injury patterns during the COVID-19 pandemic: What has changed?

BackgroundFollowing the emergence of the COVID-19 pandemic, normal daily life in the United States (US) has changed dramatically. As the US population shifts to practice social distancing, there are undoubtedly changes in the pattern of traumatic injuries presenting to Emergency Departments across the US. This analysis aims to analyze previously undocumented trends on how the COVID-19 pandemic has changed the pattern of vehicle related injuries in selected US states. MethodsA retrospective analysis was performed utilizing public vehicle collision data gathered from the Department of Transportation of Florida, New York, and Massachusetts from October 1, 2019 to March 31, 2020 regarding 158,341 motor vehicle collisions. Descriptive statistical analysis and linear regression was performed to investigate the counts and trends of motor vehicle collisions and injuries during the study period in order to determine what effect, if any, COVID-19 has had on the incidence and pattern of these events. ResultsIn Florida, New York, and Massachusetts, there was a general downward trend of vehicle collisions and vehicle related injuries over this time period, with statistically significant association between number of total vehicle collisions vs. date (p < 0.001), as well as number of vehicle related injuries vs. date (p < 0.001). ConclusionIncidence of vehicle collisions and vehicle related injuries have significantly decreased during the COVID-19 pandemic. The creation of improved public transport modalities and use of virtual/remote replacements for social activities could serve as long-term solutions to reduce vehicle collisions and vehicle related injuries.

EFFECTS OF DESCRIPTIVE NORMS, PERCEIVED ECONOMIC VIABILITY AND BEHAVIOURAL INTENTION ON LIVESTOCK AGRIPRENEURSHIP AMONG AGRICULTURAL COLLEGE STUDENTS IN NIGER STATE, NIGERIA

Agripreneurship is a means of eradicating poverty among Nigerian youths. The study examined the effects of descriptive norms, perceived economic viability and behavioural intention on livestock agripreneurship among agricultural college students in Niger State, Nigeria. Multi-stage sampling technique was used to select 432 respondents across three agricultural colleges in Niger State, Nigeria. Data were analyzed using descriptive and inferential statistics (linear regression) at P≤0.05. Results showed that the respondents were male (63.2%), not married (87.5%), were of good standing in their class performance with a cumulative grade point average of ≥2.5 (59.7%) and below 26 years old (84.7%) with a mean age of approximately 23 years. The most descriptive norm of livestock agripreneurship by respondents was the popularity of poultry production (x̅ = 3.85). The most perceived economic viability of livestock agripreneurship by respondents was the gainful employment in fish production business (x̅ =3.97). The most behavioural intention of respondents in livestock agripreneurship was to make a career out of poultry production (x̅ =3.81). Linear regression revealed that descriptive norms (β0.203) and perceived economic viability (β = 0.247) were significant factors that influenced the respondents’ behavioural intention. The study concluded that descriptive norms and perceived economic viability are major determinants of the behavioural intention of agricultural college students in livestock agripreneurship in the study area. It was recommended that agripreneurship norms, its economic viability and the behavioural intention towards it could be enhanced through the youth engagement programmes, better enabling environment, agripreneurship awareness and promotions.

Diaphragm pacing improves respiratory mechanics in acute cervical spinal cord injury.

Cervical spinal cord injury (CSCI) is devastating with ventilator-associated pneumonia being a main driver of morbidity and mortality. Laparoscopic diaphragm pacing implantation (DPS) has been used for earlier liberation from mechanical ventilation. We hypothesized that DPS would improve respiratory mechanics and facilitate liberation. We performed a retrospective review of acute CSCI patients between January 2005 and May 2017. Routine demographics were collected. Patients underwent propensity score matching based on age, Injury Severity Score, ventilator days, hospital length of stay, and need for tracheostomy. Patients with complete respiratory mechanics data were analyzed and compared. Those who did not have DPS (NO DPS) had spontaneous tidal volume (Vt) recorded at time of intensive care unit admission, at day 7, and at day 14, and patients who had DPS had spontaneous Vt recorded before and after DPS. Time to ventilator liberation and changes in size of spontaneous Vt for patients while on the ventilator were analyzed. Bivariate and multivariate logistic and linear regression statistics were performed using STATA v10. Between July 2011 and May 2017, 37 patients that had DPS were matched to 34 who did not (NO DPS). Following DPS, there was a statistically significant increase in spontaneous Vt compared with NO DPS (+88 mL vs. -13 mL; 95% confidence interval, 46-131 mL vs. -78 to 51 mL, respectively; p = 0.004). Median time to liberation after DPS was significantly shorter (10 days vs. 29 days; 95% CI, 6.5-13.6 days vs. 23.1-35.3 days; p < 0.001). Liberation prior to hospital discharge was not different between the two groups. The DPS placement was found to be associated with a statistically significant decrease in days to liberation and an increase in spontaneous Vt in multivariate linear regression models. The DPS implantation in acute CSCI patients produces significant improvements in spontaneous Vt and reduces time to liberation from mechanical ventilation. Prospective comparative studies are needed to define the clinical benefits and potential cost savings of DPS implantation. Therapeutic IV.

Analyzing the aggressive behavior of domestic violence perpetrators

The study was conducted by analyzing the aggressive behavior of domestic violence perpetrators which can be seen through how much the contribution of aggressive behavior between sub-variables. This research method uses a quantitative approach with descriptive methods. The subjects in this study were perpetrators who lived in the city of Padang and were taken using purposive sampling techniques, amounting to 82 people. Data is collected through the Aggressive Behavior Inventory Instrument for Domestic Violence developed from Buss theory about aspects of aggressive behavior that contains 4 sub, including physical aggression (4 items), verbal aggression (7 items), anger (3 items) and hostility (2 items). The instrument uses a Likert scale model that has five alternative answers with interval data and analyzed with descriptive statistical techniques and simple linear regression analysis. The research findings show that on average the figure of aggressive domestic violence perpetrators is in the moderate category by 71% and aggressive behavior in terms of verbal aggression contributes to physical aggression of 10.3% while aggressive behavior itself contributes to verbal aggression by 65.8%. With the results of this study become input for therapists/counselors sone of them is through family counseling with an experimental approach that prioritizes now and here experience.

Chlorophyll estimation in soybean leaves infield with smartphone digital imaging and machine learning

Soybean (Glycine max (L.) Merrill) leaf chlorophyll content is indicative of the plant growth and health issues. However, chlorophyll measurement using the standard chemical procedure is laborious, while the sensor-based electronic options, such as soil plant analysis development (SPAD) meter tend to be highly expensive and made only spot measurements. Therefore, a simpler and less expensive infield method of chlorophyll measurement in soybeans using smartphone camera with image processing and machine learning models was developed. Soybean leaf images (720 images) and SPAD readings were collected from different cultivars (4), with replications (3) and sampling dates (2) from experimental plots. Of the several color vegetation indices (CVIs) tested, the dark green color index (DGCI) had the best correlation with SPAD meter readings (r=0.90), which was further improved by color calibration (r=0.93). The results of the random coefficients model showed that both cultivars and sampling dates had no significant effect (0.06≤P≤0.96), hence data were combined for the analysis. The simpler statistical linear regression (SLR) and polynomial regression (PR), multiple linear regression as well as the advanced machine learning models (support vector machine (SVM), random forest (RF)) tested with color scheme inputs (RGB, DGCI, range pixel count (RPC) of DGCI, and ‘Both’ (RPC + RGB)) produced the best chlorophyll prediction with DGCI, RPC, and ‘Both’ inputs (0.87<R2<0.89; 2.90≤RMSE≤3.41 SPAD units). Overall, these models were not significantly different, but the SVM model found to be the best (R2=0.89 and RMSE=2.90SPAD units). The simpler SLR and PR models with DGCI input (R2≥0.87 and RMSE≤3.1 SPAD units) performed as good as the advanced SVM and RF models. The SVM model had the potential of predicting the chlorophyll directly with the raw RGB input (R2=0.86 and RMSE=3.20SPAD units) without the need of using the standard calibration board. The developed methodology of image processing with machine learning modeling and conversion relationship of measuring infield soybean leaf chlorophyll is efficient, inexpensive, not requiring the standard calibration board, and can be easily extended to other large-scale aerial imaging platforms and field crops.

Effect of organizational climate upon the job performance of instructors’ physical education

Propose: The current study was conducted to examine the effect of organizational climate on the Job Performance of Instructors’ Physical Education. Material: A quantitative method was employed for this purpose; a survey research design was used. There was 169 Instructors’ Physical Education preferred through stratified sampling technique. A structured questionnaire was administered to collect the data. The data was analyzed using inferential statistics (linear and multiple regression). Results: The results of the study indicated that organizational climate affect job satisfaction significantly. All the dimensions of organizational climate contribute to increasing the Instructors’ Physical Education performance. Conclusion: The current study concluded that Instructors’ Physical Education not only feel comfortable in a healthy organizational climate but also increase their level of performance. The study also depicted that effective communication structure, reward system, teamwork, career development, and effective planning and decision making strategies are the valuable ingredients to enhance the performance of Instructors’ Physical Education. Recommendation: Keeping in view the results of the current study, it is recommended that head of the institution may focus or promote supportive culture in their respective educational institutions to enhance the performance of instructors’ physical education.

Pediatric Scoliosis Surgery-A Comprehensive Analysis of Treatment-Specific Variables and Trends in Latvia.

Background and Objectives: There are currently no data available regarding pediatric scoliosis surgery in Latvia. The aim of this article is to present treatment specific variables, investigate their interrelation, and identify predictors for the length of stay after surgical pediatric scoliosis correction. Materials and Methods: This retrospective study included all surgical pediatric scoliosis corrections in Latvia for the years 2012 to 2016. Analyzed parameters were chosen to portray the patients’ demographics, pathology, as well as treatment specific variables. Descriptive, inferential, and linear regression statistics were calculated. Results: A total of 69 cases, 74% female and 26% male, were identified. The diagnostic subgroups consisted of 62% idiopathic (IDI) and 38% non-idiopathic (non-IDI) scoliosis cases. Non-IDI cases had significantly increased operation time, hospital stay, Cobb angle before surgery, and instrumented levels, while IDI cases showed significantly higher Cobb angle percentage correction. For all operated cases, the operation time and the hospital stay decreased significantly over the investigated time period. Early post-operative complications (PCs) occurred in 15.9% of the cases and were associated with increased hospital stay, instrumented levels, and Cobb angle before surgery. The linear regression analysis revealed that operation time and the presence of PCs were significant predictors for the length of the hospital stay. Conclusions: This is the first study to provide comprehensive insight into pediatric scoliosis surgery since its establishment in Latvia. Our regression model offers clinically applicable predictors and further underlines the significance of the operation length on the hospital stay. These results build the foundation for international comparison and facilitate improvement in the field.

Development of a Probabilistic Seismic Performance Assessment Model of Slope Using Machine Learning Methods

The objective of this study is to propose a model that can predict the seismic performance of slope relatively accurately and efficiently by using machine learning methods. Probabilistic seismic fragility analyses of the slope had been carried out in other studies, and a closed-form equation for slope seismic performance was proposed through a multiple linear regression analysis. However, the traditional statistical linear regression analysis showed a limit that could not accurately represent such nonlinear slope seismic performances. To overcome this limit, in this study, we used three machine learning methods (i.e., support vector machine (SVM), artificial neural network (ANN), Gaussian process regression (GPR)) to generate prediction models of the slope seismic performance. The models obtained through the machine learning methods basically showed better performance compared to the models of the traditional statistical methods. The results of the SVM showed no significant performance difference compared with the results of the nonlinear regression analysis method, but the results based on the ANN and GPR showed a remarkable improvement in the prediction performance over the other models. Furthermore, this study confirmed that the GPR-based model predicted relatively accurate seismic performance values compared with the model through the ANN.

Child Labor in Agricultural Sector Hyderabad Sindh, Pakistan

Child labor is one of the major National and International issue. It has strongly affected the child’s social, psychological and physical growth the child labor does not only influence on social, psychological, and physical growth but it also affects the child education and allowing the child further into dark era of his life. This research study addresses the causes and consequences of child labor in agricultural sector of Hyderabad vicinity in Pakistan. The aim of this study is to highlight hidden factors related to child labor and providing the possibilities to policy makers and stockholders to mitigate this curse from the childhood in the agriculture sector of Hyderabad city of Pakistan. Researchers have applied “The theory related to concept of poverty” declares the child labor in terms of poverty. A sample of 260 respondents was taken from the targeted population, mainly focusses on close-ended questionnaire. Further, the raw data is analysed through (SPSS) software, and other techniques used for analysing the statistical data Non-parametric tests, ANOVA, reliability, Linear Regression and correlation Chi-Square test based on the collected raw data from individuals.

Variability in sound power levels: Implications for static and dynamic traffic models

Classically, one mean vehicle representative of each category is used by both static and dynamic traffic noise prediction models. The spectrum associated with this mean vehicle is determined from a linear statistical regression analysis based on measurement campaigns on a track or in situ. However, the variability of individual vehicle emissions can influence predictions and hinder comparison between static and dynamic models. In order to estimate the induced bias, statistical analysis of the distributions of sound power levels emitted by the individual passage of vehicles during 82 measurement campaigns was carried out. The results show that 92% of the residual regression distributions are Gaussian and that standard deviations can reach 3.6 dBA. The value of the proposed correction term for this case study could reach 1.4 dBA for light vehicles and 1.2 dBA for heavy vehicles. This analysis also shows that the variability in sound power levels and thus the corresponding corrections are higher at the lowest speeds that correspond to urban driving conditions.

Analyzing the Effect of Need for Achievement and Locus of Control on Student Entrepreneurial Intentions

This study aimed to analyze the student entrepreneurial intentions model based on their psychological characteristics. More specifically, this study sought to explain whether the Need for Achievement (N-Ach) and Locus of Control (LoC) of students had an effect on Entrepreneurial Intentions (EI). An inferential research design with a cross-sectional study was adopted to collect the data. Students from faculty of teacher training and education, one public university in Jambi, were involved as the sample of the study. 63.14% of male students were selected by using a simple random sampling strategy, dominated by 81.78% of respondents aged less than 20 years. Data were collected through questionnaires and were analyzed by using the statistical correlation software and linear regression models to ensure the relationship between psychological characteristics and EI. The results indicated that there was a positive effect on psychological characteristics and EI on Student Entrepreneurial Intentions. N-Ach and LoC positively affected EI, both partially and jointly. Due to the limited instrument used in this study, only a self-reported questionnaire, which carried an opportunity for the response bias, and involved male students from a faculty in one public university in Jambi. Therefore, this model needs a further development through the incorporation of behavioral characteristics by involving larger samples allowing us understand on whether behavioral theories and traits are conflicting or complementary.