Citizens and social media in times of natural disaster: Exploring information experience

Introduction. Social media is becoming a vital source of information in disaster or emergency situations. While a growing number of studies have explored the use of social media in natural disasters by emergency staff, military personnel, medial and other professionals, very few studies have investigated the use of social media by members of the public. The purpose of this paper is to explore citizens’ information experiences in social media during times of natural disaster. Method. A qualitative research approach was applied. Data was collected via in-depth interviews. Twenty-five people who used social media during a natural disaster in Australia participated in the study. Analysis. Audio recordings of interviews and interview transcripts provided the empirical material for data analysis. Data was analysed using structural and focussed coding methods. Results. Eight key themes depicting various aspects of participants’ information experience during a natural disaster were uncovered by the study: connected; wellbeing; coping; help; brokerage; journalism; supplementary and characteristics. Conclusion. This study contributes insights into social media’s potential for developing community disaster resilience and promotes discussion about the value of civic participation in social media when such circumstances occur. These findings also contribute to our understanding of information experiences as a new informational research object.

The evolving landscape of natural resource planning and governance in Australia

Australia’s governance of land and natural resources involves multiple polycentric domains of decision-making from global through to local levels. Although certainly complex, these arrangements have not necessarily translated into better decision-making or better environmental outcomes as evidenced by the growing concerns over the health and future of the Great Barrier Reef, (GBR). However within this system, arrangements for natural resource management (NRM) and reef water quality, which both use Australia’s integrated regional NRM model, have showed signs of improving decision-making and environmental outcomes in the GBR. In this paper we describe the latest evolutions in the governance and planning for natural resource use and management in Australia. We begin by reviewing the experience with first generation NRM as published in major audits and evaluations. As our primary interest is the health and future of the GBR, we then consider the impact of changes of second generation planning and governance outcomes in Queensland. We find that first generation plans, although developed under a relatively cohesive governance context, faced substantial problems in target setting, implementation, monitoring and review. Despite this, they were able to progress improvements in water quality in the Great Barrier Reef Regions. Second generation plans, currently being developed, face an even greater risk of failure due to the lack of bilateralism and cross-sectoral cooperation across the NRM governance system. The findings highlight the critical need to re-build and enhance the regional NRM model for NRM planning to have a positive impact on environmental outcomes in the GBR.

Hierarchical clustering of the genetic connectivity matrix reveals the network topology of gene action on brain microstructure: An N=531 twin study

Genetic correlation (rg) analysis determines how much of the correlation between two measures is due to common genetic influences. In an analysis of 4 Tesla diffusion tensor images (DTI) from 531 healthy young adult twins and their siblings, we generalized the concept of genetic correlation to determine common genetic influences on white matter integrity, measured by fractional anisotropy (FA), at all points of the brain, yielding an NxN genetic correlation matrix rg(x,y) between FA values at all pairs of voxels in the brain. With hierarchical clustering, we identified brain regions with relatively homogeneous genetic determinants, to boost the power to identify causal single nucleotide polymorphisms (SNP). We applied genome-wide association (GWA) to assess associations between 529,497 SNPs and FA in clusters defined by hubs of the clustered genetic correlation matrix. We identified a network of genes, with a scale-free topology, that influences white matter integrity over multiple brain regions.

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

Can biophilic urbanism deliver strong economic and social benefits in cities? An economic and policy invetigations into the increased use of natural elements in urban design

Biophilic urbanism, or urban design that reflects humanity’s innate need for nature, stands to make significant contributions to a range of national, state and local government policies related to climate change mitigation and adaptation, by investigating ways in which nature can be integrated into, around and on top of buildings. Potential benefits of such design include reducing the heat island effect, reducing energy consumption for thermal control, enhancing urban biodiversity, improving well being and productivity, improving water cycle management, and assisting in the response to growing needs for densification and revitalisation of cities. This report will give an overview of the concept of biophilia and consider enablers and disablers to its application to urban planning and design. The paper will present findings from stakeholder engagement and a series of detailed case studies, related to a consideration of the economics of the use of biophilic elements (direct and indirect).

Recurrence risk modelling of the genetic susceptibility to ankylosing spondylitis

Objectives - It has long been suspected that susceptibility to ankylosing spondylitis (AS) is influenced by genes lying distant to the major histocompatibility complex. This study compares genetic models of AS to assess the most likely mode of inheritance, using recurrence risk ratios in relatives of affected subjects. Methods - Recurrence risk ratios in different degrees of relatives were determined using published data from studies specifically designed to address the question. The methods of Risch were used to determine the expected recurrence risk ratios in different degrees of relatives, assuming equal first degree relative recurrence risk between models. Goodness of fit was determined by χ2 comparison of the expected number of affected subjects with the observed number, given equal numbers of each type of relative studied. Results - The recurrence risks in different degrees of relatives were: monozygotic (MZ) twins 63% (17/27), first degree relatives 8.2% (441/5390), second degree relatives 1.0% (8/834), and third degree relatives 0.7% (7/997). Parent-child recurrence risk (7.9%, 37/466) was not significantly different from the sibling recurrence risk (8.2%, 404/4924), excluding a significant dominance genetic component to susceptibility. Poor fitting models included single gene, genetic heterogeneity, additive, two locus multiplicative, and one locus and residual polygenes (χ2 > 32 (two degrees of freedom), p < 10-6 for all models). The best fitting model studied was a five locus model with multiplicative interaction between loci (χ2 = 1.4 (two degrees of freedom), p = 0.5). Oligogenic multiplicative models were the best fitting over a range of population prevalences and first degree recurrence risk rates. Conclusions - This study suggests that of the genetic models tested, the most likely model operating in AS is an oligogenic model with predominantly multiplicative interaction between loci.

Land grabs, bio-piracy and the inversion of justice in Colombia

The possibility of commercially exploiting plant, animal and human genetic resources unlocked by biotechnology has given rise to a wide range of cultural, environmental, ethical and economic conflicts. While supporters describe this activity as bioprospecting, critics refer to it as biopiracy. According to this latter view, international legal agreements and treaties have disregarded opposition and legalized the possibility of appropriating genetic resources and their derivative products through the use of patents. The legal framework that permits the appropriation of natural genetic products in Colombia also criminalizes aspects of traditional ways of life and enables a legally approved but socially harmful land-grabbing process. The article describes these processes and impact in terms of the inversion of justice and the erosion of environmental sustainability.

Inference of the genetic architecture underlying BMI and height with the use of 20,240 sibling pairs

Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 x 10(-)(7)) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 x 10(-10)) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average.

Androgenetic alopecia: Identification of four genetic risk loci and evidence for the contribution of WNT signaling to its etiology

The pathogenesis of androgenetic alopecia (AGA, male-pattern baldness) is driven by androgens, and genetic predisposition is the major prerequisite. Candidate gene and genome-wide association studies have reported that single-nucleotide polymorphisms (SNPs) at eight different genomic loci are associated with AGA development. However, a significant fraction of the overall heritable risk still awaits identification. Furthermore, the understanding of the pathophysiology of AGA is incomplete, and each newly associated locus may provide novel insights into contributing biological pathways. The aim of this study was to identify unknown AGA risk loci by replicating SNPs at the 12 genomic loci that showed suggestive association (5 x 10(-8)of European descent to confirm the association with AGA at these loci. Combined analysis of the replication and the meta-analysis data identified four genome-wide significant risk loci for AGA on chromosomes 2q35, 3q25.1, 5q33.3, and 12p12.1. The strongest association signal was obtained for rs7349332 (P=3.55 x 10(-15)) on chr2q35, which is located intronically in WNT10A. Expression studies in human hair follicle tissue suggest that WNT10A has a functional role in AGA etiology. Thus, our study provides genetic evidence supporting an involvement of WNT signaling in AGA development.

Sustainable life cycles of natural-precursor-derived nanocarbons

Sustainable societal and economic development relies on novel nanotechnologies that offer maximum efficiency at minimal environmental cost. Yet, it is very challenging to apply green chemistry approaches across the entire life cycle of nanotech products, from design and nanomaterial synthesis to utilization and disposal. Recently, novel, efficient methods based on nonequilibrium reactive plasma chemistries that minimize the process steps and dramatically reduce the use of expensive and hazardous reagents have been applied to low-cost natural and waste sources to produce value-added nanomaterials with a wide range of applications. This review discusses the distinctive effects of nonequilibrium reactive chemistries and how these effects can aid and advance the integration of sustainable chemistry into each stage of nanotech product life. Examples of the use of enabling plasma-based technologies in sustainable production and degradation of nanotech products are discussed—from selection of precursors derived from natural resources and their conversion into functional building units, to methods for green synthesis of useful naturally degradable carbon-based nanomaterials, to device operation and eventual disintegration into naturally degradable yet potentially reusable byproducts.

A note on sampling chironomids for RNA-based studies of natural populations that retains critical morphological vouchers

The rapid uptake of transcriptomic approaches in freshwater ecology has seen a wealth of data produced concerning the ways in which organisms interact with their environment on a molecular level. Typically, such studies focus either at the community level and so don’t require species identifications, or on laboratory strains of known species identity or natural populations of large, easily identifiable taxa. For chironomids, impediments still exist for applying these technologies to natural populations because they are small-bodied and often require time-consuming secondary sorting of stream material and morphological voucher preparation to confirm species diagnosis. These procedures limit the ability to maintain RNA quantity and quality in such organisms because RNA degrades rapidly and gene expression can be altered rapidly in organisms; thereby limiting the inclusion of such taxa in transcriptomic studies. Here, we demonstrate that these limitations can be overcome and outline an optimised protocol for collecting, sorting and preserving chironomid larvae that enables retention of both morphological vouchers and RNA for subsequent transcriptomics purposes. By ensuring that sorting and voucher preparation are completed within <4 hours after collection and that samples are kept cold at all times, we successfully retained both RNA and morphological vouchers from all specimens. Although not prescriptive in specific methodology, we anticipate that this paper will assist in promoting transcriptomic investigations of the sublethal impact on chironomid gene expression of changes to aquatic environments.

Behaviour of natural zeolites used for the treatment of simulated and actual coal seam gas water

Coal seam gas operations produce significant quantities of associated water which often require demineralization. Ion exchange with natural zeolites has been proposed as a possible approach. The interaction of natural zeolites with solutions of sodium chloride and sodium bicarbonate in addition to coal seam gas water is not clear. Hence, we investigated ion exchange kinetics, equilibrium, and column behaviour of an Australian natural zeolite. Kinetic tests suggested that the pseudo first order equation best simulated the data. Intraparticle diffusion was part of the rate limiting step and more than one diffusion process controlled the overall rate of sodium ion uptake. Using a constant mass of zeolite and variable concentration of either sodium chloride or sodium bicarbonate resulted in a convex isotherm which was fitted by a Langmuir model. However, using a variable mass of zeolite and constant concentration of sodium ions revealed that the exchange of sodium ions with the zeolite surface sites was in fact unfavourable. Sodium ion exchange from bicarbonate solutions (10.3 g Na/kg zeolite) was preferred relative to exchange from sodium chloride solutions (6.4 g Na/kg zeolite). The formation of calcium carbonate species was proposed to explain the observed behaviour. Column studies of coal seam gas water showed that natural zeolite had limited ability to reduce the concentration of sodium ions (loading 2.1 g Na/kg zeolite) with rapid breakthrough observed. It was concluded that natural zeolites may not be suitable for the removal of cations from coal seam gas water without improvement of their physical properties.

Prediction of individual genetic risk to prostate cancer using a polygenic score

BACKGROUND Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. Prostate 75:1467–1474, 2015. © 2015 Wiley Periodicals, Inc.