Economic crisis and the construction of a neo-liberal regulatory regime in Korea

A consistent theme of the literature on the ontology of the 1997 South Korean crisis is the key role played by regulatory failures and the growing weakness of the state. This paper seeks to briefly highlight both the insights and the limitations of this approach to understanding the crisis. Having done so, we shall set out the argument that the crisis created an opportunity for reformist Korean élites to advance their longstanding, but previously frustrated, project to create a comprehensive unambiguously neo-liberal regulatory regime. This paper will also seek to highlight the implications of our reading of the development of the Korean political economy for broader debates on economic liberalisation, crisis and the future of the developmental state

Global sensitivity analysis of stochastic computer models with joint metamodels

The global sensitivity analysis method used to quantify the influence of uncertain input variables on the variability in numerical model responses has already been applied to deterministic computer codes; deterministic means here that the same set of input variables gives always the same output value. This paper proposes a global sensitivity analysis methodology for stochastic computer codes, for which the result of each code run is itself random. The framework of the joint modeling of the mean and dispersion of heteroscedastic data is used. To deal with the complexity of computer experiment outputs, nonparametric joint models are discussed and a new Gaussian process-based joint model is proposed. The relevance of these models is analyzed based upon two case studies. Results show that the joint modeling approach yields accurate sensitivity index estimatiors even when heteroscedasticity is strong

In the social factory? Immaterial labour, precariousness and cultural work

This article introduces a special section concerned with precariousness and cultural work. Its aim is to bring into dialogue three bodies of ideas -- the work of the autonomous Marxist 'Italian laboratory'; activist writings about precariousness and precarity; and the emerging empirical scholarship concerned with the distinctive features of cultural work, at a moment when artists, designers and (new) media workers have taken centre stage as a supposed 'creative class' of model entrepreneurs. The paper is divided into three sections. It starts by introducing the ideas of the autonomous Marxist tradition, highlighting arguments about the autonomy of labour, informational capitalism and the 'factory without walls', as well as key concepts such as multitude and immaterial labour. The impact of these ideas and of Operaismo politics more generally on the precarity movement is then considered in the second section, discussing some of the issues that have animated debate both within and outside this movement, which has often treated cultural workers as exemplifying the experiences of a new 'precariat'. In the third and final section of the paper we turn to the empirical literature about cultural work, pointing to its main features before bringing it into debate with the ideas already discussed. Several points of overlap and critique are elaborated -- focusing in particular on issues of affect, temporality, subjectivity and solidarity

APOL1 genotype-associated morphologic changes among patients with focal segmental glomerulosclerosis

Background: The G1 and G2 alleles of apolipoprotein L1 (APOL1) are common in the Black population and associated with increased risk of focal segmental glomerulosclerosis (FSGS). The molecular mechanisms linking APOL1 risk variants with FSGS are not clearly understood, and APOL1’s natural absence in laboratory animals makes studying its pathobiology challenging. Methods: In a cohort of 90 Black patients with either FSGS or minimal change disease (MCD) enrolled in the Nephrotic Syndrome Study Network (58% pediatric onset), we used kidney biopsy traits as an intermediate outcome to help illuminate tissue-based consequences of APOL1 risk variants and expression. We tested associations between APOL1 risk alleles or glomerular APOL1 mRNA expression and 83 light- or electron-microscopy traits measuring structural and cellular kidney changes. Results: Under both recessive and dominant models in the FSGS patient subgroup (61%), APOL1 risk variants were significantly correlated (defined as FDR <0.1) with decreased global mesangial hypercellularity, decreased condensation of cytoskeleton, and increased tubular microcysts. No significant correlations were detected in MCD cohort. Independent of risk alleles, glomerular APOL1 expression in FSGS patients was not correlated with morphologic features. Conclusions: While APOL1-associated FSGS is associated with two risk alleles, both one and two risk alleles are associated with cellular/tissue changes in this study of FSGS patients. Our lack of discovery of a large group of tissue differences in FSGS and no significant difference in MCD may be due to the lack of power but also supports investigating whether machine learning methods may more sensitively detect APOL1-associated changes

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections