The 2020 Covid-19 pandemic and global value chains

This paper considers the impact of the Covid-19 pandemic on firm strategies and, in particular, the configuration of firms’ global value chains (GVCs) once the pandemic has been brought under control. The merits of alternative location strategies (international diversification vs reshoring) are compared, as are the merits of different governance arrangements (internalization vs externalization) for GVC activities. The possibility of fire-sale foreign direct investment is raised, and the wider geopolitical context is emphasized. The widespread human tragedy is noted, as is the dilemma facing national governments around the world in balancing lives and livelihoods

An experimental study of the intrinsic stability of random forest variable importance measures

BACKGROUND: The stability of Variable Importance Measures (VIMs) based on random forest has recently received increased attention. Despite the extensive attention on traditional stability of data perturbations or parameter variations, few studies include influences coming from the intrinsic randomness in generating VIMs, i.e. bagging, randomization and permutation. To address these influences, in this paper we introduce a new concept of intrinsic stability of VIMs, which is defined as the self-consistence among feature rankings in repeated runs of VIMs without data perturbations and parameter variations. Two widely used VIMs, i.e., Mean Decrease Accuracy (MDA) and Mean Decrease Gini (MDG) are comprehensively investigated. The motivation of this study is two-fold. First, we empirically verify the prevalence of intrinsic stability of VIMs over many real-world datasets to highlight that the instability of VIMs does not originate exclusively from data perturbations or parameter variations, but also stems from the intrinsic randomness of VIMs. Second, through Spearman and Pearson tests we comprehensively investigate how different factors influence the intrinsic stability. RESULTS: The experiments are carried out on 19 benchmark datasets with diverse characteristics, including 10 high-dimensional and small-sample gene expression datasets. Experimental results demonstrate the prevalence of intrinsic stability of VIMs. Spearman and Pearson tests on the correlations between intrinsic stability and different factors show that #feature (number of features) and #sample (size of sample) have a coupling effect on the intrinsic stability. The synthetic indictor, #feature/#sample, shows both negative monotonic correlation and negative linear correlation with the intrinsic stability, while OOB accuracy has monotonic correlations with intrinsic stability. This indicates that high-dimensional, small-sample and high complexity datasets may suffer more from intrinsic instability of VIMs. Furthermore, with respect to parameter settings of random forest, a large number of trees is preferred. No significant correlations can be seen between intrinsic stability and other factors. Finally, the magnitude of intrinsic stability is always smaller than that of traditional stability. CONCLUSION: First, the prevalence of intrinsic stability of VIMs demonstrates that the instability of VIMs not only comes from data perturbations or parameter variations, but also stems from the intrinsic randomness of VIMs. This finding gives a better understanding of VIM stability, and may help reduce the instability of VIMs. Second, by investigating the potential factors of intrinsic stability, users would be more aware of the risks and hence more careful when using VIMs, especially on high-dimensional, small-sample and high complexity datasets

Has the Rajiv Aarogyasri Community Health Insurance Scheme of Andhra Pradesh Addressed the Educational Divide in Accessing Health Care?

Background Equity of access to healthcare remains a major challenge with families continuing to face financial and non-financial barriers to services. Lack of education has been shown to be a key risk factor for 'catastrophic' health expenditure (CHE), in many countries including India. Consequently, ways to address the education divide need to be explored. We aimed to assess whether the innovative state-funded Rajiv Aarogyasri Community Health Insurance Scheme of Andhra Pradesh state launched in 2007, has achieved equity of access to hospital inpatient care among households with varying levels of education. Methods We used the National Sample Survey Organization 2004 survey as our baseline and the same survey design to collect post-intervention data from 8623 households in the state in 2012. Two outcomes, hospitalisation and CHE for inpatient care, were estimated using education as a measure of socio-economic status and transforming levels of education into ridit scores. We derived relative indices of inequality by regressing the outcome measures on education, transformed as a ridit score, using logistic regression models with appropriate weights and accounting for the complex survey design. Findings Between 2004 and 2012, there was a 39% reduction in the likelihood of the most educated person being hospitalised compared to the least educated, with reductions observed in all households as well as those that had used the Aarogyasri. For CHE the inequality disappeared in 2012 in both groups. Sub-group analyses by economic status, social groups and rural-urban residence showed a decrease in relative indices of inequality in most groups. Nevertheless, inequalities in hospitalisation and CHE persisted across most groups. Conclusion During the time of the Aarogyasri scheme implementation inequalities in access to hospital care were substantially reduced but not eliminated across the education divide. Universal access to education and schemes such as Aarogyasri have the synergistic potential to achieve equity of access to healthcare

PolyADP-Ribosylation Is Required for Pronuclear Fusion during Postfertilization in Mice

BACKGROUND: During fertilization, pronuclear envelope breakdown (PNEB) is followed by the mingling of male and female genomes. Dynamic chromatin and protein rearrangements require posttranslational modification (PTM) for the postfertilization development. METHODOLOGY/PRINCIPAL FINDINGS: Inhibition of poly(ADP-ribose) polymerase activity (PARylation) by either PJ-34 or 5-AIQ resulted in developmental arrest of fertilized embryos at the PNEB. PARylation inhibition affects spindle bundle formation and phosphorylation of Erk molecules of metaphase II (MII) unfertilized oocytes. We found a frequent appearance of multiple pronuclei (PN) in the PARylation-inhibited embryos, suggesting defective polymerization of tubulins. Attenuated phosphorylation of lamin A/C by PARylation was detected in the PARylation-inhibited embryos at PNEB. This was associated with sustained localization of heterodomain protein 1 (HP1) at the PN of the one-cell embryos arrested by PARylation inhibition. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that PARylation is required for pronuclear fusion during postfertilization processes. These data further suggest that PARylation regulates protein dynamics essential for the beginning of mouse zygotic development. PARylation and its involving signal-pathways may represent potential targets as contraceptives

Modelling the impact of atherosclerosis on drug release and distribution from coronary stents

Although drug-eluting stents (DES) are now widely used for the treatment of coronary heart disease, there remains considerable scope for the development of enhanced designs which address some of the limitations of existing devices. The drug release profile is a key element governing the overall performance of DES. The use of in vitro, in vivo, ex vivo, in silico and mathematical models has enhanced understanding of the factors which govern drug uptake and distribution from DES. Such work has identified the physical phenomena determining the transport of drug from the stent and through tissue, and has highlighted the importance of stent coatings and drug physical properties to this process. However, there is limited information regarding the precise role that the atherosclerotic lesion has in determining the uptake and distribution of drug. In this review, we start by discussing the various models that have been used in this research area, highlighting the different types of information they can provide. We then go on to describe more recent methods that incorporate the impact of atherosclerotic lesions

Evolution and patterns of global health financing 1995-2014 : development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

Background An adequate amount of prepaid resources for health is important to ensure access to health services and for the pursuit of universal health coverage. Previous studies on global health financing have described the relationship between economic development and health financing. In this study, we further explore global health financing trends and examine how the sources of funds used, types of services purchased, and development assistance for health disbursed change with economic development. We also identify countries that deviate from the trends. Methods We estimated national health spending by type of care and by source, including development assistance for health, based on a diverse set of data including programme reports, budget data, national estimates, and 964 National Health Accounts. These data represent health spending for 184 countries from 1995 through 2014. We converted these data into a common inflation-adjusted and purchasing power-adjusted currency, and used non-linear regression methods to model the relationship between health financing, time, and economic development. Findings Between 1995 and 2014, economic development was positively associated with total health spending and a shift away from a reliance on development assistance and out-of-pocket (OOP) towards government spending. The largest absolute increase in spending was in high-income countries, which increased to purchasing power-adjusted $5221 per capita based on an annual growth rate of 3.0$914 and $267 per capita in 2014, respectively. Spending in low-income countries grew nearly as fast, at 4.6$51 to $120 per capita. In 2014, 59.2$37.6 billion in 2016. Nonetheless, there is a great deal of variation revolving around these averages. 29 countries spend at least 50% more than expected per capita, based on their level of economic development alone, whereas 11 countries spend less than 50% their expected amount. Interpretation Health spending remains disparate, with low-income and lower-middle-income countries increasing spending in absolute terms the least, and relying heavily on OOP spending and development assistance. Moreover, tremendous variation shows that neither time nor economic development guarantee adequate prepaid health resources, which are vital for the pursuit of universal health coverage.Peer reviewe