The place and practices of wellbeing in local governance

The concept of well-being has become prominent within national policy goals in the UK since the end of the 1990s. However, the concept of well-being remains ill defined, an instability that is increasingly understood as problematic to policy making. We engage with this terminological instability through an exploration of how the concept of well-being is practised discursively in local governance and critically examine the place of the concept in local policy making. In contrast to the current enthusiasm to define and measure well-being, we argue that the conceptual instability has inherent value for local governance. The concept of well-being is practised through a number of potentially conflicting discourses, but it is exactly this conceptual instability that enables a local negotiation and combination of alternative policy frameworks for local place-shaping strategies. As such, well-being not only is an overarching goal of governance but also contributes to the dynamics of the policy process

Self-assembly of quantum dots: effect of neighbor islands on the wetting in coherent Stranski-Krastanov growth

The wetting of the homogeneously strained wetting layer by dislocation-free three-dimensional islands belonging to an array has been studied. The array has been simulated as a chain of islands in 1+1 dimensions. It is found that the wetting depends on the density of the array, the size distribution and the shape of the neighbor islands. Implications for the self-assembly of quantum dots grown in the coherent Stranski-Krastanov mode are discussed.Comment: 4 pages, 6 figures, accepted version, minor change

Correlation between centrality metrics and their application to the opinion model

In recent decades, a number of centrality metrics describing network properties of nodes have been proposed to rank the importance of nodes. In order to understand the correlations between centrality metrics and to approximate a high-complexity centrality metric by a strongly correlated low-complexity metric, we first study the correlation between centrality metrics in terms of their Pearson correlation coefficient and their similarity in ranking of nodes. In addition to considering the widely used centrality metrics, we introduce a new centrality measure, the degree mass. The m order degree mass of a node is the sum of the weighted degree of the node and its neighbors no further than m hops away. We find that the B_{n}, the closeness, and the components of x_{1} are strongly correlated with the degree, the 1st-order degree mass and the 2nd-order degree mass, respectively, in both network models and real-world networks. We then theoretically prove that the Pearson correlation coefficient between x_{1} and the 2nd-order degree mass is larger than that between x_{1} and a lower order degree mass. Finally, we investigate the effect of the inflexible antagonists selected based on different centrality metrics in helping one opinion to compete with another in the inflexible antagonists opinion model. Interestingly, we find that selecting the inflexible antagonists based on the leverage, the B_{n}, or the degree is more effective in opinion-competition than using other centrality metrics in all types of networks. This observation is supported by our previous observations, i.e., that there is a strong linear correlation between the degree and the B_{n}, as well as a high centrality similarity between the leverage and the degree.Comment: 20 page

Weather, disease, and wheat breeding effects on Kansas wheat varietal yields, 1985 to 2011.

Wheat (Triticum aestivum L.) yields in Kansas have increased due to wheat breeding and improved agronomic practices, but are subject to climate and disease challenges. The objective of this research is to quantify the impact of weather, disease, and genetic improvement on wheat yields of varieties grown in 11 locations in Kansas from 1985 to 2011. Wheat variety yield data from Kansas performance tests were matched with comprehensive location-specific disease and weather data, including seasonal precipitation, monthly air temperature, air temperature and solar radiation around anthesis, and vapor pressure deficit (VPD). The results show that wheat breeding programs increased yield by 34 kg ha⁻¹ yr⁻¹. From 1985 through 2011, wheat breeding increased average wheat yields by 917 kg ha⁻¹, or 27% of total yield. Weather was found to have a large impact on wheat yields. Simulations demonstrated that a 1°C increase in projected mean temperature was associated with a decrease in wheat yields of 715 kg ha⁻¹, or 21%. Weather, diseases, and genetics all had significant impacts on wheat yields in 11 locations in Kansas during 1985 to 2011

Genome-wide association meta-analysis identifies 48 risk variants and highlights the role of the stria vascularis in hearing loss

Hearing loss is one of the top contributors to years lived with disability and is a risk factor for dementia. Molecular evidence on the cellular origins of hearing loss in humans is growing. Here, we performed a genome-wide association meta-analysis of clinically diagnosed and self-reported hearing impairment on 723,266 individuals and identified 48 significant loci, 10 of which are novel. A large proportion of associations comprised missense variants, half of which lie within known familial hearing loss loci. We used single-cell RNA-sequencing data from mouse cochlea and brain and mapped common-variant genomic results to spindle, root, and basal cells from the stria vascularis, a structure in the cochlea necessary for normal hearing. Our findings indicate the importance of the stria vascularis in the mechanism of hearing impairment, providing future paths for developing targets for therapeutic intervention in hearing loss

Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes

Type 2 diabetes (T2D) is a very common disease in humans. Here we conduct a meta-analysis of genome-wide association studies (GWAS) with ~16 million genetic variants in 62,892 T2D cases and 596,424 controls of European ancestry. We identify 139 common and 4 rare variants associated with T2D, 42 of which (39 common and 3 rare variants) are independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2765) with the GWAS results identifies 33 putative functional genes for T2D, 3 of which were targeted by approved drugs. A further integration of DNA methylation (n = 1980) and epigenomic annotation data highlight 3 genes (CAMK1D, TP53INP1, and ATP5G1) with plausible regulatory mechanisms, whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. Our study uncovers additional loci, proposes putative genetic regulatory mechanisms for T2D, and provides evidence of purifying selection for T2D-associated variants

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to similar to 370,000 women, we identify 389 independent signals (P <5 x 10(-8)) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain similar to 7.4% of the population variance in age at menarche, corresponding to similar to 25% of the estimated heritability. We implicate similar to 250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility