Formal and informal sectors: is there any wage differential?

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The main objective of this paper is to investigate if a wage difference exists between formal and informal sectors in the case of the Turkish labour market using a sample of wageworkers. To this end, we use data for 2004 and 2009 and a novel definition of the informal sector. On the methodological front, we adopt three alternative decomposition techniques, namely, the Oaxaca-Ransom (1994) decomposition in the context of mean regression, the Machado and Mata (2005) decomposition in the quantile regression framework and the non-parametric decomposition method proposed by Nopo (2008). The results reveal the existence of a wage gap between the two sectors. We found education and experience to be key determinants of earnings. The findings of this paper have implications for policies, which might be directed towards developing approaches with a focus on education and experience

Data mining experiments on the Angiotensin II-Antagonist in Paroxysmal Atrial Fibrillation (ANTIPAF-AFNET 2) trial: ‘Exposing the invisible’

Aims: The aims of this study include (i) pursuing data-mining experiments on the Angiotensin II-Antagonist in Paroxysmal Atrial Fibrillation (ANTIPAF-AFNET 2) trial dataset containing atrial fibrillation (AF) burden scores of patients with many clinical parameters and (ii) revealing possible correlations between the estimated risk factors of AF and other clinical findings or measurements provided in the dataset. Methods: Ranking Instances by Maximizing the Area under a Receiver Operating Characteristics (ROC) Curve (RIMARC) is used to determine the predictive weights (Pw) of baseline variables on the primary endpoint. Chi-square automatic interaction detector algorithm is performed for comparing the results of RIMARC. The primary endpoint of the ANTIPAF-AFNET 2 trial was the percentage of days with documented episodes of paroxysmal AF or with suspected persistent AF. Results: By means of the RIMARC analysis algorithm, baseline SF-12 mental component score (Pw = 0.3597), age (Pw = 0.2865), blood urea nitrogen (BUN) (Pw = 0.2719), systolic blood pressure (Pw = 0.2240), and creatinine level (Pw = 0.1570) of the patients were found to be predictors of AF burden. Atrial fibrillation burden increases as baseline SF-12 mental component score gets lower; systolic blood pressure, BUN and creatinine levels become higher; and the patient gets older. The AF burden increased significantly at age >76. Conclusions: With the ANTIPAF-AFNET 2 dataset, the present data-mining analyses suggest that a baseline SF-12 mental component score, age, systolic blood pressure, BUN, and creatinine level of the patients are predictors of AF burden. Additional studies are necessary to understand the distinct kidney-specific pathophysiological pathways that contribute to AF burden. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016

The harm of anticoagulation in patients with low-risk by CHADS2 and reclassified as high-risk by CHA2DS2VASc: inferences from TRAF cohort.

OBJECTIVE: There is a gap in the knowledge concerning oral anticoagulation (OAC) in atrial fibrillation (AF) patients with a non-high risk of stroke. CHA2DS2VASc and CHADS2 scores generated imprecise risk estimates for low risk patients. We aimed to assess OAC in patients with low risk by CHADS2 and reclassified as high-risk by CHA2DS2VASc. PATIENTS AND METHODS: In this study, retrospective nationwide population-based study, data were obtained from the Turkish claims and utilization management system. Patients with non-valvular AF (n=451,113) between 2007 and 2012 sub-divided into those with a CHA2DS2VASc≥1 and CHADS2=0 (n=41,273) who were off-warfarin (n=29,448) and on-warfarin (n=11,825). Stroke and systemic embolism, major bleeding, all-cause mortality, net clinical benefit (NCB) and ultimate NCB (UNCB) were assessed. RESULTS: Of the total cohort (mean age 66.1 ± 14.1 years, 56.1% female), CHA2DS2VASc improved the net reclassification index of observed 5-year composite thromboembolic endpoint by 6.9% (p<0.05). CHA2DS2VASc reclassified 9.7% low risk patients as high risk. Among reclassified-high-risk category (patients with a CHA2DS2VASc score of ≥1 and CHADS2 score of 0), major bleeding for that prescribed warfarin was 3% and higher than the rate of thromboembolism among those off-warfarin. NCB (-0.035) and UNCB (-0.021) were negative. Death and hospitalization at 1 year were significantly higher for on-warfarin group. CONCLUSIONS: Clinical outcomes, net clinical benefit indices are negative; rates of death and hospitalization were significantly higher for OAC in reclassified category. This emphasizes the importance of greater attention to balancing the risks and benefits of OAC in patients with low risk by CHADS2 and reclassified as high-risk by CHA2DS2VASc

Predictors of sinus rhythm after electrical cardioversion of atrial fibrillation: Results from a data mining project on the Flec-SL trial data set

Aims: Data mining is the computational process to obtain information from a data set and transform it for further use. Herein, through data mining with supportive statistical analyses, we identified and consolidated variables of the Flecainide Short-Long (Flec-SL—AFNET 3) trial dataset that are associated with the primary outcome of the trial, recurrence of persistent atrial fibrillation (AF) or death. Methods and results: The ‘Ranking Instances by Maximizing the Area under the ROC Curve’ (RIMARC) algorithm was applied to build a classifier that can predict the primary outcome by using variables in the Flec-SL dataset. The primary outcome was time to persistent AF or death. The RIMARC algorithm calculated the predictive weights of each variable in the Flec-SL dataset for the primary outcome. Among the initial 21 parameters, 6 variables were identified by the RIMARC algorithm. In univariate Cox regression analysis of these variables, increased heart rate during AF and successful pharmacological conversion (PC) to sinus rhythm (SR) were found to be significant predictors. Multivariate Cox regression analysis revealed successful PC as the single relevant predictor of SR maintenance. The primary outcome risk was 3.14 times (95% CI:1.7–5.81) lower in those who had successful PC to SR than those who needed electrical cardioversion. Conclusions: Pharmacological conversion of persistent AF with flecainide without the need for electrical cardioversion is a powerful and independent predictor of maintenance of SR. A strategy of flecainide pretreatment for 48 h prior to planned electrical cardioversion may be a useful planning of a strategy of long-term rhythm control

Consequences of Covid-19 on the Social Isolation of the Chinese Economy: Accounting for the Role of Reduction in Carbon Emissions

The main contribution of the present study to the energy literature is linked to the interaction between economic growth and pollution emission amidst globalization. Unlike other studies, this research explores the effect of economic and social isolation as a dimension of globalization. This allows underpinning the effects on the Chinese economic development of the isolation phenomenon as a consequence of coronavirus (COVID-19). To this end, annual time frequency data is used to achieve the hypothesized claims. The study resolutions include (i) The existence of a long-run equilibrium bond between the outlined variables (ii) The long-run estimates suggest that the Chinese economy over the investigated period, is inelastic to pollutant–driven economic growth as reported by the dynamic ordinary least squares, fully modified ordinary least squares and canonical regressions with a magnitude of 0.09%. (iii) The Chinese isolation is less responsive to its economic growth while the country political willpower is elastic as demonstrated by current government commitment to dampen the effect of the COVID-19 pandemic. This is marked by the aggressive response on the government officials resolute by flattening the exponential impact of the pandemic. Based on these robust results some far-reaching policy implication(s) are underlined in the concluding remark section

Application of the RIMARC algorithm to a large data set of action potentials and clinical parameters for risk prediction of atrial fibrillation

Ex vivo recorded action potentials (APs) in human right atrial tissue from patients in sinus rhythm (SR) or atrial fibrillation (AF) display a characteristic spike-and-dome or triangular shape, respectively, but variability is huge within each rhythm group. The aim of our study was to apply the machine-learning algorithm ranking instances by maximizing the area under the ROC curve (RIMARC) to a large data set of 480 APs combined with retrospectively collected general clinical parameters and to test whether the rules learned by the RIMARC algorithm can be used for accurately classifying the preoperative rhythm status. APs were included from 221 SR and 158 AF patients. During a learning phase, the RIMARC algorithm established a ranking order of 62 features by predictive value for SR or AF. The model was then challenged with an additional test set of features from 28 patients in whom rhythm status was blinded. The accuracy of the risk prediction for AF by the model was very good (0.93) when all features were used. Without the seven AP features, accuracy still reached 0.71. In conclusion, we have shown that training the machine-learning algorithm RIMARC with an experimental and clinical data set allows predicting a classification in a test data set with high accuracy. In a clinical setting, this approach may prove useful for finding hypothesis-generating associations between different parameters. © 2014, International Federation for Medical and Biological Engineering

The tourism and economic growth enigma: Examining an ambiguous relationship through multiple prisms

This paper revisits the ambiguous relationship between tourism and economic growth, providing a comprehensive study of destinations across the globe which takes into account the key dynamics that influence tourism and economic performance. We focus on 113 countries over the period 1995-2014, clustered, for the first time, around six criteria that reflect their economic, political and tourism dimensions. A Panel Vector Autoregressive model is employed which, in contrast to previous studies, allows the data to reveal any tourism-economy interdependencies across these clusters, without imposing a priori the direction of causality. Overall, the economic-driven tourism growth hypothesis seems to prevail in countries which are developing, non-democratic, highly bureaucratic and have low tourism specialization. Conversely, bidirectional relationships are established for economies which are stronger, democratic and with higher levels of government effectiveness. Thus, depending on the economic, political and tourism status of a destination, different policy implications apply

Tourism and Economic Globalization: An Emerging Research Agenda

Globalization characterizes the economic, social, political, and cultural spheres of the modern world. Tourism has long been claimed as a crucial force shaping globalization, while in turn the developments of the tourism sector are under the influences of growing interdependence across the world. As globalization proceeds, destination countries have become more and more susceptible to local and global events. By linking the existing literature coherently, this study explores a number of themes on economic globalization in tourism. It attempts to identify the forces underpinning globalization and assess the implications on both the supply side and the demand side of the tourism sector. In view of a lack of quantitative evidence, future directions for empirical research have been suggested to investigate the interdependence of tourism demand, the convergence of tourism productivity, and the impact of global events

Antimicrobial activity against oral pathogens and immunomodulatory effects and toxicity of geopropolis produced by the stingless bee Melipona fasciculata Smith

<p>Abstract</p> <p>Background</p> <p>Native bees of the tribe Meliponini produce a distinct kind of propolis called geopropolis. Although many pharmacological activities of propolis have already been demonstrated, little is known about geopropolis, particularly regarding its antimicrobial activity against oral pathogens. The present study aimed at investigating the antimicrobial activity of <it>M. fasciculata </it>geopropolis against oral pathogens, its effects on <it>S. mutans </it>biofilms, and the chemical contents of the extracts. A gel prepared with a geopropolis extract was also analyzed for its activity on <it>S. mutans </it>and its immunotoxicological potential.</p> <p>Methods</p> <p>Antimicrobial activities of three hydroalcoholic extracts (HAEs) of geopropolis, and hexane and chloroform fractions of one extract, were evaluated using the agar diffusion method and the broth dilution technique. Ethanol (70%, v/v) and chlorhexidine (0.12%, w/w) were used as negative and positive controls, respectively. Total phenol and flavonoid concentrations were assayed by spectrophotometry. Immunotoxicity was evaluated in mice by topical application in the oral cavity followed by quantification of biochemical and immunological parameters, and macro-microscopic analysis of animal organs.</p> <p>Results</p> <p>Two extracts, HAE-2 and HAE-3, showed inhibition zones ranging from 9 to 13 mm in diameter for <it>S. mutans </it>and <it>C. albicans</it>, but presented no activity against <it>L</it>. <it>acidophilus</it>. The MBCs for HAE-2 and HAE-3 against <it>S. mutans </it>were 6.25 mg/mL and 12.5 mg/mL, respectively. HAE-2 was fractionated, and its chloroform fraction had an MBC of 14.57 mg/mL. HAE-2 also exhibited bactericidal effects on <it>S. mutans </it>biofilms after 3 h of treatment. Significant differences (p < 0.05) in total phenol and flavonoid concentrations were observed among the samples. Signs toxic effects were not observed after application of the geopropolis-based gel, but an increase in the production of IL-4 and IL-10, anti-inflammatory cytokines, was detected.</p> <p>Conclusions</p> <p>In summary, geopropolis produced by <it>M. fasciculata </it>can exert antimicrobial action against <it>S. mutans </it>and <it>C. albicans</it>, with significant inhibitory activity against <it>S. mutans </it>biofilms. The extract with the highest flavonoid concentration, HAE-2, presented the highest antimicrobial activity. In addition, a geopropolis-based gel is not toxic in an animal model and displays anti-inflammatory effect.</p