The impact of technological progress on energy intensity in China (2005-2016): Evidence from a geographically and temporally weighted regression model

This study investigates the impact of Ease of Doing Business on Inward FDI over the period from 2011 to 2015 across the globe. This study measures ease of doing business using starting a business, getting credit, registering property, paying taxes and enforcing contracts. The research used a sample of 177 countries from 190 countries listed in World Bank. Least square regression model via E-views software used to examine causal relationship. The study found that ease of doing business indicators ‘Enforcing Contracts’ was found to have a positive significant impact on Inward FDI. Nevertheless, ‘Getting Credit’ and ‘Registering Property’ were found to have a negative significant impact on Inward FDI. However, ‘Starting a Business’ and ‘Paying Taxes’ have no significant impact on Inward FDI in the studied timeframe of this research. The findings of the study suggested the ease of doing business enables inward FDI through better contract enforcements, getting credit and registering property. The findings of the research will assist international managers and companies to know the importance of ease of doing business when investing in foreign countries through FDI.

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Income Diversification and Bank Efficiency in Vietnam

Journal of Economics and Development ◽

10.33301/jed.2017.19.03.04 ◽

2017 ◽

pp. 52-67

Author(s):

Sang Nguyen Minh

Keyword(s):

Regression Model ◽

Commercial Banks ◽

Banking System ◽

Operational Efficiency ◽

Commercial Banking ◽

Tobit Regression ◽

Income Diversification ◽

Positive Effects ◽

Study Results ◽

The Impact

This study uses the DEA (Data Envelopment Analysis) method to estimate the technical efficiency index of 34 Vietnamese commercial banks in the period 2007-2015, and then it analyzes the impact of income diversification on the operational efficiency of Vietnamese commercial banks through a censored regression model - the Tobit regression model. Research results indicate that income diversification has positive effects on the operational efficiency of Vietnamese commercial banks in the research period. Based on study results, in this research some recommendations forpolicy are given to enhance the operational efficiency of Vietnam’s commercial banking system.

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The Role of Research and Innovation in the Transformation of Agri-Food Systems

Annals ”Valahia” University of Targoviste - Agriculture ◽

10.2478/agr-2018-0019 ◽

2018 ◽

Vol 12 (2) ◽

pp. 60-63

Author(s):

Mariana Sandu ◽

Stefan Mantea

Keyword(s):

Technological Progress ◽

Food Systems ◽

Food System ◽

Agricultural Research ◽

Research And Innovation ◽

And Performance ◽

The Impact ◽

Determinant Factor ◽

Rapid Transformation

Abstract Agri-food systems include branching ramifications, which connect in the upstream the input suppliers with farmers, and downstream farmers, processors, retailers and consumers. In the last decades, at the level of the regions, food systems have undergone rapid transformation as a result of technological progress. The paper analyzes the changes made to the structure, behavior and performance of the agri-food system and the impact on farmers and consumers. Also, the role of agricultural research as a determinant factor of transformation of agri-food system is analyzed. The research objective is to develop technologies that cover the entire food chain (from farm to fork) and meet the specific requirements of consumers (from fork to farm) through scientific solutions in line with the principles of sustainable agriculture and ensuring the safety and food safety of the population.

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Work absence and multimorbidity in Portugal: results from the 1st National Health Examination Survey

European Journal of Public Health ◽

10.1093/eurpub/ckaa166.1390 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

J Matos ◽

C Matias Dias ◽

A Félix

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Chronic Diseases ◽

National Health ◽

Logistic Regression Model ◽

Health Examination ◽

Work Absence ◽

Health Examination Survey ◽

Absence From Work ◽

The Impact

Abstract Background Studies on the impact of patients with multimorbidity in the absence of work indicate that the number and type of chronic diseases may increase absenteeism and that the risk of absence from work is higher in people with two or more chronic diseases. This study analyzed the association between multimorbidity and greater frequency and duration of work absence in the portuguese population between the ages of 25 and 65 during 2015. Methods This is an epidemiological, observational, cross-sectional study with an analytical component that has its source of information from the 1st National Health Examination Survey. The study analyzed univariate, bivariate and multivariate variables under study. A multivariate logistic regression model was constructed. Results The prevalence of absenteeism was 55,1%. Education showed an association with absence of work (p = 0,0157), as well as professional activity (p = 0,0086). It wasn't possible to verify association between the presence of chronic diseases (p = 0,9358) or the presence of multimorbidity (p = 0,4309) with absence of work. The prevalence of multimorbidity was 31,8%. There was association between age (p < 0,0001), education (p < 0,001) and yield (p = 0,0009) and multimorbidity. There is no increase in the number of days of absence from work due to the increase in the number of chronic diseases. In the optimized logistic regression model the only variables that demonstrated association with the variable labor absence were age (p = 0,0391) and education (0,0089). Conclusions The scientific evidence generated will contribute to the current discussion on the need for the health and social security system to develop policies to patients with multimorbidity. Key messages The prevalence of absenteeism and multimorbidity in Portugal was respectively 55,1% and 31,8%. In the optimized model age and education demonstrated association with the variable labor absence.

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Artificial neural network, predictor variables and sensitivity threshold for DNA methylation-based age prediction using blood samples

Scientific Reports ◽

10.1038/s41598-021-81556-2 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Zhonghui Thong ◽

Jolena Ying Ying Tan ◽

Eileen Shuzhen Loo ◽

Yu Wei Phua ◽

Xavier Liang Shun Chan ◽

...

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Regression Model ◽

Sensitivity Threshold ◽

Ann Model ◽

Blood Samples ◽

Ann Models ◽

Artificial Neural ◽

The Impact ◽

Age Prediction

AbstractRegression models are often used to predict age of an individual based on methylation patterns. Artificial neural network (ANN) however was recently shown to be more accurate for age prediction. Additionally, the impact of ethnicity and sex on our previous regression model have not been studied. Furthermore, there is currently no age prediction study investigating the lower limit of input DNA at the bisulfite treatment stage prior to pyrosequencing. Herein, we evaluated both regression and ANN models, and the impact of ethnicity and sex on age prediction for 333 local blood samples using three loci on the pyrosequencing platform. Subsequently, we trained a one locus-based ANN model to reduce the amount of DNA used. We demonstrated that the ANN model has a higher accuracy of age prediction than the regression model. Additionally, we showed that ethnicity did not affect age prediction among local Chinese, Malays and Indians. Although the predicted age of males were marginally overestimated, sex did not impact the accuracy of age prediction. Lastly, we present a one locus, dual CpG model using 25 ng of input DNA that is sufficient for forensic age prediction. In conclusion, the two ANN models validated would be useful for age prediction to provide forensic intelligence leads.

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Primary tumor surgery improves survival in non-metastatic primary urethral carcinoma patients: a large population-based investigation

BMC Cancer ◽

10.1186/s12885-021-08603-z ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jie Wu ◽

Yu-Chen Wang ◽

Wen-Jie Luo ◽

Bo-Dai ◽

Ding-Wei Ye ◽

...

Keyword(s):

Regression Model ◽

Competing Risks ◽

Primary Tumor ◽

Cox Regression ◽

Radical Surgery ◽

Large Population ◽

Local Therapy ◽

Primary Site ◽

Urethral Carcinoma ◽

The Impact

Abstract Background Primary urethral carcinoma (PUC) is a rare genitourinary malignancy with a relatively poor prognosis. The aim of this study was to examine the impact of surgery on survival of patients diagnosed with PUC. Methods A total of 1544 PUC patients diagnosed between 2004 and 2016 were identified based on the SEER database. The Kaplan-Meier estimate and the Fine and Gray competing risks analysis were performed to assess overall survival (OS) and cancer-specific mortality (CSM). The multivariate Cox regression model and competing risks regression model were used to identify independent risk factors of OS and cancer-specific survival (CSS). Results The 5-yr OS was significantly better in patients who received either local therapy (39.8%) or radical surgery (44.7%) compared to patients receiving no surgery of the primary site (21.5%) (p < 0.001). Both local therapy and radical surgery were each independently associated with decreased CSM, with predicted 5-yr cumulative incidence of 45.4 and 43.3%, respectively, compared to 64.7% for patients receiving no surgery of the primary site (p < 0.001). Multivariate analyses demonstrated that primary site surgery was independently associated with better OS (local therapy, p = 0.037; radical surgery, p < 0.001) and decreased CSM (p = 0.003). Similar results were noted regardless of age, sex, T stage, N stage, and AJCC prognostic groups based on subgroup analysis. However, patients with M1 disease who underwent primary site surgery did not exhibit any survival benefit. Conclusion Surgery for the primary tumor conferred a survival advantage in non-metastatic PUC patients.

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