Defect-unbinding transitions and inherent structures in two dimensions

We present a large-scale (36000-particle) computational study of the "inherent structures" (IS) associated with equilibrium, two-dimensional, one-component Lennard-Jones systems. Our results provide strong support both for the inherent-structures theory of classical fluids, and for the KTHNY theory of two-stage melting in two dimensions. This support comes from the observation of three qualitatively distinct "phases" of inherent structures: a crystal, a "hexatic glass", and a "liquid glass". We also directly observe, in the IS, analogs of the two defect-unbinding transitions (respectively, of dislocations, and disclinations) believed to mediate the two equilibrium phase transitions. Each transition shows up in the inherent structures---although the free disclinations in the "liquid glass" are embedded in a percolating network of grain boundaries. The bond-orientational correlation functions of the inherent structures show the same progressive loss of order as do the three equilibrium phases: long-range to quasi-long-range to short-range.Comment: RevTeX, 8 pages, 15 figure

Mainstreaming domestic and gender-based violence into sociology and the criminology of violence

Sociological and criminological views of domestic and gender-based violencegenerally either dismiss it as not worthy of consideration, or focus on specificgroups of offenders and victims (male youth gangs, partner violence victims). Inthis paper, we take a holistic approach to violence, extending the definition fromthat commonly in use to encompass domestic violence and sexual violence. Weoperationalize that definition by using data from the latest sweep of the CrimeSurvey for England and Wales. By so doing, we identify that violence is currentlyunder-measured and ubiquitous; that it is gendered, and that other forms of violence (family violence, acquaintance violence against women) are equally ofconcern. We argue that violence studies are an important form of activity forsociologists

Assessing the Effectiveness of Tradable Landuse Rights for Biodiversity Conservation: An Application to Canada's Boreal Mixedwood Forest

Ecological reserve networks are an important strategy for conserving biodiversity. One approach to selecting reserves is to use optimization algorithms that maximize an ecological objective function subject to a total reserve area constraint. Under this approach, economic factors such as potential land values and tenure arrangements are often ignored. Tradable landuse rights are proposed as an alternative economic mechanism for selecting reserves. Under this approach economic considerations determine the spatial distribution of development and reserves are allocated to sites with the lowest development value, minimizing the cost of the reserve network. The configuration of the reserve network as well as the biodiversity outcome is determined as a residual. However cost savings can be used to increase the total amount of area in reserve and improve biodiversity outcomes. The appropriateness of this approach for regional planning is discussed in light of key uncertainties associated with biodiversity protection. A comparison of biodiversity outcomes and costs under ecological versus economic approaches is undertaken for the Boreal Forest Natural Region of Alberta, Canada. We find a significant increase in total area protected and an increase in species representation under the TLR approach

The gas-phase formation mechanism of iodic acid as an atmospheric aerosol source

Iodine is a reactive trace element in atmospheric chemistry that destroys ozone and nucleates particles. Iodine emissions have tripled since 1950 and are projected to keep increasing with rising O-3 surface concentrations. Although iodic acid (HIO3) is widespread and forms particles more efficiently than sulfuric acid, its gas-phase formation mechanism remains unresolved. Here, in CLOUD atmospheric simulation chamber experiments that generate iodine radicals at atmospherically relevant rates, we show that iodooxy hypoiodite, IOIO, is efficiently converted into HIO3 via reactions (R1) IOIO + O-3 -> IOIO4 and (R2) IOIO4 + H2O -> HIO3 + HOI + O-(1)(2). The laboratory-derived reaction rate coefficients are corroborated by theory and shown to explain field observations of daytime HIO3 in the remote lower free troposphere. The mechanism provides a missing link between iodine sources and particle formation. Because particulate iodate is readily reduced, recycling iodine back into the gas phase, our results suggest a catalytic role of iodine in aerosol formation.Peer reviewe

Storylines: an alternative approach to representing uncertainty in physical aspects of climate change

As climate change research becomes increasingly applied, the need for actionable information is growing rapidly. A key aspect of this requirement is the representation of uncertainties. The conventional approach to representing uncertainty in physical aspects of climate change is probabilistic, based on ensembles of climate model simulations. In the face of deep uncertainties, the known limitations of this approach are becoming increasingly apparent. An alternative is thus emerging which may be called a ‘storyline’ approach. We define a storyline as a physically self-consistent unfolding of past events, or of plausible future events or pathways. No a priori probability of the storyline is assessed; emphasis is placed instead on understanding the driving factors involved, and the plausibility of those factors. We introduce a typology of four reasons for using storylines to represent uncertainty in physical aspects of climate change: (i) improving risk awareness by framing risk in an event-oriented rather than a probabilistic manner, which corresponds more directly to how people perceive and respond to risk; (ii) strengthening decision-making by allowing one to work backward from a particular vulnerability or decision point, combining climate change information with other relevant factors to address compound risk and develop appropriate stress tests; (iii) providing a physical basis for partitioning uncertainty, thereby allowing the use of more credible regional models in a conditioned manner and (iv) exploring the boundaries of plausibility, thereby guarding against false precision and surprise. Storylines also offer a powerful way of linking physical with human aspects of climate change

A Candidate Gene Association Study Identifies DAPL1 as a Female-Specific Susceptibility Locus for Age-Related Macular Degeneration (AMD)

Age-related macular degeneration (AMD) is the leading cause of blindness among white caucasians over the age of 50 years with a prevalence rate expected to increase markedly with an anticipated increase in the life span of the world population. To further expand our knowledge of the genetic architecture of the disease, we pursued a candidate gene approach assessing 25 genes and a total of 109 variants. Of these, synonymous single nucleotide polymorphism (SNP) rs17810398 located in death-associated protein-like 1 (DAPL1) was found to be associated with AMD in a joint analysis of 3,229 cases and 2,835 controls from five studies [combined PADJ = 1.15 × 10−6, OR 1.332 (1.187–1.496)]. This association was characterized by a highly significant sex difference (Pdiff = 0.0032) in that it was clearly confined to females with genome-wide significance [PADJ = 2.62 × 10−8, OR 1.541 (1.324–1.796); males: PADJ = 0.382, OR 1.084 (0.905–1.298)]. By targeted resequencing of risk and non-risk associated haplotypes in the DAPL1 locus, we identified additional potentially functional risk variants, namely a common 897-bp deletion and a SNP predicted to affect a putative binding site of an exonic splicing enhancer. We show that the risk haplotype correlates with a reduced retinal transcript level of two, less frequent, non-canonical DAPL1 isoforms. DAPL1 plays a role in epithelial differentiation and may be involved in apoptotic processes thereby suggesting a possible novel pathway in AMD pathogenesis

A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.

This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.3448Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.We thank all participants of all the studies included for enabling this research by their participation in these studies. Computer resources for this project have been provided by the high-performance computing centers of the University of Michigan and the University of Regensburg. Group-specific acknowledgments can be found in the Supplementary Note. The Center for Inherited Diseases Research (CIDR) Program contract number is HHSN268201200008I. This and the main consortium work were predominantly funded by 1X01HG006934-01 to G.R.A. and R01 EY022310 to J.L.H

Brain-Age Prediction: Systematic Evaluation of Site Effects, and Sample Age Range and Size

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain‐age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain‐age has highlighted the need for robust and publicly available brain‐age models pre‐trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain‐age model. Here we expand this work to develop, empirically validate, and disseminate a pre‐trained brain‐age model to cover most of the human lifespan. To achieve this, we selected the best‐performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain‐age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5–90 years; 53.59% female). The pre‐trained models were tested for cross‐dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8–80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9–25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age‐bins (5–40 and 40–90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain‐age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open‐science, web‐based platform for individualized neuroimaging metrics

Brain-Age Prediction: Systematic Evaluation of Site Effects, and Sample Age Range and Size

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain‐age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain‐age has highlighted the need for robust and publicly available brain‐age models pre‐trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain‐age model. Here we expand this work to develop, empirically validate, and disseminate a pre‐trained brain‐age model to cover most of the human lifespan. To achieve this, we selected the best‐performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain‐age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5–90 years; 53.59% female). The pre‐trained models were tested for cross‐dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8–80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9–25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age‐bins (5–40 and 40–90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain‐age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open‐science, web‐based platform for individualized neuroimaging metrics

Role of iodine oxoacids in atmospheric aerosol nucleation

Iodic acid (HIO₃) is known to form aerosol particles in coastal marine regions, but predicted nucleation and growth rates are lacking. Using the CERN CLOUD (Cosmics Leaving Outdoor Droplets) chamber, we find that the nucleation rates of HIO₃ particles are rapid, even exceeding sulfuric acid–ammonia rates under similar conditions. We also find that ion-induced nucleation involves IO₃⁻ and the sequential addition of HIO₃ and that it proceeds at the kinetic limit below +10°C. In contrast, neutral nucleation involves the repeated sequential addition of iodous acid (HIO₂) followed by HIO₃, showing that HIO₂ plays a key stabilizing role. Freshly formed particles are composed almost entirely of HIO₃, which drives rapid particle growth at the kinetic limit. Our measurements indicate that iodine oxoacid particle formation can compete with sulfuric acid in pristine regions of the atmosphere