Spatio-Temporal Impact of Global Migration on Carbon Transfers Based on Complex Network and Stepwise Regression Analysis

Considering the advancement of economic globalization, the reasons for migration together with the lifestyles of migrants will change the use of energy, environment of origin and destination. This study therefore explores the patterns of global trade-induced carbon emission transfers using “center-of-gravity” and complex network analysis. We further investigate the determinants of carbon transfers by integrating the impact of population migration through the STIRPAT framework for 64 countries over the period 2005–2015 using the stepwise regression approach. Our results unveil that higher levels of migration flow induce higher carbon flow. Specifically, every 1% increase in migration, triggers carbon transfers to increase within the range of 0.118%−0.124%. The rising impact of migration cannot be ignored, even though the coefficients were not so high. Besides, for both male and female migrants, their impact on carbon transfers generated by the intermediate products were higher than those generated by the final products. However, the influence is more obvious in male migrants. With the aim of dividing the sample of countries into three income groups, the results generally show that the impacts of migration vary across levels of income. Therefore, the environmental pressure caused by immigration should be considered by destination countries in the formulating of migration policies. On the other hand, origin countries should take some responsibility for carbon emissions according to their development characteristics.

Relationship between Inherent Cooking Rate and Warner-Bratzler Shear Force of Pork Chops Cooked to Two Degrees of Doneness

The objective was to test inherent cooking rate differences on tenderness values of boneless pork chops when exogenous factors known to influence cooking rate were controlled. Temperature and elapsed time were monitored during cooking for all chops. Cooking rate was calculated as the change in °C per minute of cooking time. Warner-Bratzler shear force (WBSF) was measured on chops cooked to either 63 °C or 71 °C. Slopes of regression lines and coefficients of determination between cooking rate and tenderness values for both degrees of doneness (DoD) were calculated. Shear force values decreased as cooking rate increased regardless of DoD (p ≤ 0.05), however changes in tenderness due to increased cooking rate were limited (β1 = −0.201 for 63 °C; β1 = −0.217 for 71 °C). Cooking rate only explained 3.2% and 5.4% of variability in WBSF of chops cooked to 63 °C and 71 °C, respectively. Cooking loss explained the most variability in WBSF regardless of DoD (partial R2 = 0.09–0.12). When all factors were considered, a stepwise regression model explained 20% of WBSF variability of chops cooked to 63 °C and was moderately predictive of WBSF (model R2 = 0.34) for chops cooked to 71 °C. Overall, cooking rate had minimal effect on pork chop tenderness.

Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan

One of the most important traits that plant breeders aim to improve is grain yield which is a highly quantitative trait controlled by various agro-morphological traits. Twelve morphological traits such as Germination Percentage, Days to Spike Emergence, Plant Height, Spike Length, Awn Length, Tillers/Plant, Leaf Angle, Seeds/Spike, Plant Thickness, 1000-Grain Weight, Harvest Index and Days to Maturity have been considered as independent factors. Correlation, regression, and principal component analysis (PCA) are used to identify the different durum wheat traits, which significantly contribute to the yield. The necessary assumptions required for applying regression modeling have been tested and all the assumptions are satisfied by the observed data. The outliers are detected in the observations of fixed traits and Grain Yield. Some observations are detected as outliers but the outlying observations did not show any influence on the regression fit. For selecting a parsimonious regression model for durum wheat, best subset regression, and stepwise regression techniques have been applied. The best subset regression analysis revealed that Germination Percentage, Tillers/Plant, and Seeds/Spike have a marked increasing effect whereas Plant thickness has a negative effect on durum wheat yield. While stepwise regression analysis identified that the traits, Germination Percentage, Tillers/Plant, and Seeds/Spike significantly contribute to increasing the durum wheat yield. The simple correlation coefficient specified the significant positive correlation of Grain Yield with Germination Percentage, Number of Tillers/Plant, Seeds/Spike, and Harvest Index. These results of correlation analysis directed the importance of morphological characters and their significant positive impact on Grain Yield. The results of PCA showed that most variation (70%) among data set can be explained by the first five components. It also identified that Seeds/Spike; 1000-Grain Weight and Harvest Index have a higher influence in contributing to the durum wheat yield. Based on the results it is recommended that these important parameters might be considered and focused in future durum wheat breeding programs to develop high yield varieties.

A Statistical Analysis for the Accessibility of Electronic Data Delivery System of the Central Bank of the Turkish Republic

The study aims to reveal the most effective factors on the accessibility statistics of the Electronic Data Delivery System (EDDS) of The Central Bank of The Turkish Republic. Besides, another aim is to reveal the effect of the exchange rate on the access statistics of EDDS exchange rate data. For this purpose, a stepwise regression model was used to find the most effective factors on accessibility statistics. According to the results of stepwise regression analysis, it was revealed that 9 out of 26 variables significantly affected the EDDS access statistics. Engle-Granger cointegration test was chosen as the method to examine the relationship between exchange rate and EDDS access statistics. It has been revealed that there is a long-run equilibrium relationship between the EURO/TRY exchange rate and the access statistics of EDDS exchange rate data.

China’s Consumers Have Different Purchase Motivations for International Enterprises and Chinese Enterprises

Many Chinese consumers believe the service attitude of salespeople is very important for consumers to buy a product. However, compare with many local China enterprises, many international enterprises do not seem to realise it. Which generals the question: are consumers’ motivations for purchasing from these two types of enterprises different? The paper describes using an international shopping mall (A) and a Chinese shopping mall (B) as examples. The researchers randomly distributed a questionnaire survey to 110 consumers and analysis questionnaire result via the stepwise regression model. The researchers found consumers purchase goods from international enterprises (A) because of gender, and consumers buy goods from Chinese enterprise (B) as their age and the service attitude of salespeople. This paper confirms that the service attitude of salespeople may not the advantage of international enterprises, but the drawback of the research does not consider consumers to have different purchase motives for different enterprises. In the conclusion, the researchers posit that future research should examine whether consumers’ purchase motivations affect international companies to make profit in the Chinese market

Development of Mathematical Functions to Predict Deflection of Radial and Bias Tractor Tires on Rigid Surface

The objective of this study was to develop mathematical functions to predict deflection for radial and bias tires. In order to develop the models, the data were obtained from the tire manufacturing companies and organized in Excel first and then transferred to Minitab® for stepwise regression analysis. The variables considered in the study were inflation pressure, load and tire width and overall diameter. Tire width (w) and overall diameter (d) was considered in a multiplication form. The tire deflection models in two different form (linear and non-linear) were developed for both, radial and bias tires. The model selection was achieved by three different criteria and % differences between the measured and predicted data. Based on the results of applying model selection criteria, the models for radial and bias tire in non-linear form were found to be adequate for predicting the tire deflection. The results from the stepwise analysis indicated that the load on tire was the predominant variable in the models and made the highest contribution to the prediction functions. The developed models were verified against to published literature data and found a good agreement.

Motivasi Belajar Mahasiswa: Peran Dukungan Sosial Melalui Mediator Religiositas

Students’ motivation to learn has many important influences on university students. Motivation can increase learning involvement, learning autonomy, social presence and enrolment, critical thinking skills, writing skills, problem-solving skills, and learning achievement. This study aims to determine the effect of social support on student learning motivation through the mediator of religiosity. The research subjects were 202 students (male and female) at an Islamic university. The measuring instruments used are the Islamic Religiosity Scale from Nashori, the Multidimensional Scale of Perceived Social Support from Zimet, Dahlem, Zimet, and Farley, and the Learning Motivation Scale from Utami, Nashori, and Rachmawati. The data were analyzed using stepwise regression. The results showed that social support and religiosity influenced learning motivation. So, social support influenced learning motivation with religiosity as a full mediator.

Classification of Parkinson’s disease with freezing of gait based on 360° turning analysis using 36 kinematic features

Background Freezing of gait (FOG) is a sensitive problem, which is caused by motor control deficits and requires greater attention during postural transitions such as turning in people with Parkinson’s disease (PD). However, the turning characteristics have not yet been extensively investigated to distinguish between people with PD with and without FOG (freezers and non-freezers) based on full-body kinematic analysis during the turning task. The objectives of this study were to identify the machine learning model that best classifies people with PD and freezers and reveal the associations between clinical characteristics and turning features based on feature selection through stepwise regression. Methods The study recruited 77 people with PD (31 freezers and 46 non-freezers) and 34 age-matched older adults. The 360° turning task was performed at the preferred speed for the inner step of the more affected limb. All experiments on the people with PD were performed in the “Off” state of medication. The full-body kinematic features during the turning task were extracted using the three-dimensional motion capture system. These features were selected via stepwise regression. Results In feature selection through stepwise regression, five and six features were identified to distinguish between people with PD and controls and between freezers and non-freezers (PD and FOG classification problem), respectively. The machine learning model accuracies revealed that the random forest (RF) model had 98.1% accuracy when using all turning features and 98.0% accuracy when using the five features selected for PD classification. In addition, RF and logistic regression showed accuracies of 79.4% when using all turning features and 72.9% when using the six selected features for FOG classification. Conclusion We suggest that our study leads to understanding of the turning characteristics of people with PD and freezers during the 360° turning task for the inner step of the more affected limb and may help improve the objective classification and clinical assessment by disease progression using turning features.