What is national wellbeing and what is progress?Why measure these definitions?Why are measures beyond economic performance needed and how will they be used? How do we measure national wellbeing & ...turn the definitions into observable quantities? Where are we now and where to next? These questions are asked and answered in this much needed, timely book. The Wellbeing of Nations provides an accessible and comprehensive overview of the measurement of national well-being, examining whether national wellbeing is more than the sum of the wellbeing of everyone in the country, and identifying and reviewing requirements for new measures. It begins with definitions, describes how to operationalize those definitions, and takes a critical look at the uses to which such measures are to be put. The authors examine initiatives from around the world, using the UK 'measuring national wellbeing programme' as a case study throughout the book, along with case studies drawn from other countries, as well as discussion of the position in some countries not yet drawn into the national wellbeing scene.
The area under the ROC curve (
AUC
) is a very widely used measure of performance for classification and diagnostic rules. It has the appealing property of being objective, requiring no subjective ...input from the user. On the other hand, the
AUC
has disadvantages, some of which are well known. For example, the
AUC
can give potentially misleading results if ROC curves cross. However, the
AUC
also has a much more serious deficiency, and one which appears not to have been previously recognised. This is that it is fundamentally incoherent in terms of misclassification costs: the
AUC
uses different misclassification cost distributions for different classifiers. This means that using the
AUC
is equivalent to using different metrics to evaluate different classification rules. It is equivalent to saying that, using one classifier, misclassifying a class 1 point is
p
times as serious as misclassifying a class 0 point, but, using another classifier, misclassifying a class 1 point is
P
times as serious, where
p
≠
P
. This is nonsensical because the relative severities of different kinds of misclassifications of individual points is a property of the problem, not the classifiers which happen to have been chosen. This property is explored in detail, and a simple valid alternative to the
AUC
is proposed.
The United Kingdom and Scottish governments instigated a societal lockdown in response to the COVID-19 pandemic. Subsequently, many experienced substantial lifestyle changes alongside the stresses of ...potentially catching the virus or experiencing bereavement. Stressful situations and poorer health behaviors (e.g., higher alcohol consumption, unhealthy diet, poorer sleep quality, physical inactivity) are frequently linked to poor mental health. Our objective was to examine changes in health behaviors and their relationship with negative mood during COVID-19 lockdown. We also considered associations between health behaviors and socio-demographic differences and COVID-19-induced changes. 399 participants completed a questionnaire asking about their personal situation and health behaviors during lockdown as well as a negative mood scale. The significance threshold for all analyses was α = 0.05. Poorer diet was linked to more-negative mood, and to changes to working status. Poorer sleep quality was linked with more-negative mood, and with 'shielding' from the virus. Being less physically active was related to more-negative mood and student status, whereas being more physically active was linked to having or suspecting COVID-19 infection within the household. Increased alcohol consumption was linked to living with children, but not to negative mood. Changes to diet, sleep quality, and physical activity related to differences in negative mood during COVID-19 lockdown. This study adds to reports on poor mental health during lockdown and identifies lifestyle restrictions and changes to health behaviors which may, to some extent, be responsible for higher negative mood. Our data suggests that it is advisable to maintain or improve health behaviors during pandemic-associated restrictions.
The F-measure, also known as the F1-score, is widely used to assess the performance of classification algorithms. However, some researchers find it lacking in intuitive interpretation, questioning ...the appropriateness of combining two aspects of performance as conceptually distinct as precision and recall, and also questioning whether the harmonic mean is the best way to combine them. To ease this concern, we describe a simple transformation of the F-measure, which we call
F
∗
(F-star), which has an immediate practical interpretation.
A great many tools have been developed for supervised classification, ranging from early methods such as linear discriminant analysis through to modern developments such as neural networks and ...support vector machines. A large number of comparative studies have been conducted in attempts to establish the relative superiority of these methods. This paper argues that these comparisons often fail to take into account important aspects of real problems, so that the apparent superiority of more sophisticated methods may be something of an illusion. In particular, simple methods typically yield performance almost as good as more sophisticated methods, to the extent that the difference in performance may be swamped by other sources of uncertainty that generally are not considered in the classical supervised classification paradigm.
Summary
Studies examining the effect of social isolation on cognitive function typically involve older adults and/or specialist groups (e.g., expeditions). We considered the effects of ...COVID‐19‐induced social isolation on cognitive function within a representative sample of the general population. We additionally considered how participants ‘shielding’ due to underlying health complications, or living alone, performed. We predicted that performance would be poorest under strictest, most‐isolating conditions. At five timepoints over 13 weeks, participants (N = 342; aged 18–72 years) completed online tasks measuring attention, memory, decision‐making, time‐estimation, and learning. Participants indicated their mood as ‘lockdown’ was eased. Performance typically improved as opportunities for social contact increased. Interactions between participant sub‐groups and timepoint demonstrated that performance was shaped by individuals' social isolation levels. Social isolation is linked to cognitive decline in the absence of ageing covariates. The impact of social isolation on cognitive function should be considered when implementing prolonged pandemic‐related restrictive conditions.
Type 2 diabetes mellitus (T2DM) is a complex disease characterized by the inability of the insulin-producing β cells in the endocrine pancreas to overcome insulin resistance in peripheral tissues. To ...determine if microRNAs are involved in the pathogenesis of human T2DM, we sequenced the small RNAs of human islets from diabetic and nondiabetic organ donors. We identified a cluster of microRNAs in an imprinted locus on human chromosome 14q32 that is highly and specifically expressed in human β cells and dramatically downregulated in islets from T2DM organ donors. The downregulation of this locus strongly correlates with hypermethylation of its promoter. Using HITS-CLIP for the essential RISC-component Argonaute, we identified disease-relevant targets of the chromosome 14q32 microRNAs, such as IAPP and TP53INP1, that cause increased β cell apoptosis upon overexpression in human islets. Our results support a role for microRNAs and their epigenetic control by DNA methylation in the pathogenesis of T2DM.
•An imprinted DLK1-MEG3 miRNA cluster is downregulated in human T2DM islets•The MEG3 promoter is hypermethylated in islets from T2DM organ donors•>700 β cell-specific mRNA targets of these miRNAs were identified by HITS-CLIP•Targets are involved in β cell apoptosis and contribute to T2DM pathogenesis
Genetic variants at the solute carrier family 39 member 8 (SLC39A8) gene locus are associated with the regulation of whole-blood manganese (Mn) and multiple physiological traits. SLC39A8 encodes ...ZIP8, a divalent metal ion transporter best known for zinc transport. Here, we hypothesized that ZIP8 regulates Mn homeostasis and Mn-dependent enzymes to influence metabolism. We generated Slc39a8-inducible global-knockout (ZIP8-iKO) and liver-specific-knockout (ZIP8-LSKO) mice and observed markedly decreased Mn levels in multiple organs and whole blood of both mouse models. By contrast, liver-specific overexpression of human ZIP8 (adeno-associated virus-ZIP8 AAV-ZIP8) resulted in increased tissue and whole blood Mn levels. ZIP8 expression was localized to the hepatocyte canalicular membrane, and bile Mn levels were increased in ZIP8-LSKO and decreased in AAV-ZIP8 mice. ZIP8-LSKO mice also displayed decreased liver and kidney activity of the Mn-dependent enzyme arginase. Both ZIP8-iKO and ZIP8-LSKO mice had defective protein N-glycosylation, and humans homozygous for the minor allele at the lead SLC39A8 variant showed hypogalactosylation, consistent with decreased activity of another Mn-dependent enzyme, β-1,4-galactosyltransferase. In summary, hepatic ZIP8 reclaims Mn from bile and regulates whole-body Mn homeostasis, thereby modulating the activity of Mn-dependent enzymes. This work provides a mechanistic basis for the association of SLC39A8 with whole-blood Mn, potentially linking SLC39A8 variants with other physiological traits.
Speciated aerosol composition data from the rural Interagency Monitoring for Protected Visual Environments (IMPROVE) network and the Environmental Protection Agency's urban/suburban Chemical ...Speciation Network (CSN) were combined to evaluate and contrast the PM2.5 composition and its seasonal patterns at urban and rural locations throughout the United States. We examined the 2005–2008 monthly and annual mean mass concentrations of PM2.5 ammonium sulfate (AS), ammonium nitrate (AN), particulate organic matter (POM), light‐absorbing carbon (LAC), mineral soil, and sea salt from 168 rural and 176 urban sites. Urban and rural AS concentrations and seasonality were similar, and both were substantially higher in the eastern United States. Urban POM and LAC concentrations were higher than rural concentrations and were associated with very different seasonality depending on location. The highest urban and rural POM and LAC concentrations occurred in the southeastern and northwestern United States. Wintertime peaks in AN were common for both urban and rural sites, but urban concentrations were several times higher, and both were highest in California and the Midwest. Fine soil concentrations were highest in the Southwest, and similar regional patterns and seasonality in urban and rural concentrations suggested impacts from long‐range transport. Contributions from sea salt to the PM2.5 budget were non‐negligible only at coastal sites. This analysis revealed spatial and seasonal variability in urban and rural aerosol concentrations on a continental scale and provided insights into their sources, processes, and lifetimes.
Key Points
PM2.5 speciated aerosol concentrations from urban and rural sites are presented
Seasonality of speciated aerosol from urban and rural regions are compared
Insights into sources, processes and lifetimes are provided
PDF
