A holographic model for the fractional quantum Hall effect

Experimental data for fractional quantum Hall systems can to a large extent be explained by assuming the existence of a modular symmetry group commuting with the renormalization group flow and hence mapping different phases of two-dimensional electron gases into each other. Based on this insight, we construct a phenomenological holographic model which captures many features of the fractional quantum Hall effect. Using an SL(2,Z)-invariant Einstein-Maxwell-axio-dilaton theory capturing the important modular transformation properties of quantum Hall physics, we find dyonic diatonic black hole solutions which are gapped and have a Hall conductivity equal to the filling fraction, as expected for quantum Hall states. We also provide several technical results on the general behavior of the gauge field fluctuations around these dyonic dilatonic black hole solutions: We specify a sufficient criterion for IR normalizability of the fluctuations, demonstrate the preservation of the gap under the SL(2,Z) action, and prove that the singularity of the fluctuation problem in the presence of a magnetic field is an accessory singularity. We finish with a preliminary investigation of the possible IR scaling solutions of our model and some speculations on how they could be important for the observed universality of quantum Hall transitions.Comment: 86 pages, 16 figures; v.2 references added, typos fixed, improved discussion of ref. [39]; v.3 more references added and typos fixed, several statements clarified, v.4 version accepted for publication in JHE

Reaction Time and Mortality from the Major Causes of Death:The NHANES-III Study

Studies examining the relation of information processing speed, as measured by reaction time, with mortality are scarce. We explored these associations in a representative sample of the US population

Overweight, obesity, and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120 813 adults from 16 cohort studies from the USA and Europe

BACKGROUND: Although overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight. METHODS: We pooled individual-participant data for BMI and incident cardiometabolic multimorbidity from 16 prospective cohort studies from the USA and Europe. Participants included in the analyses were 35 years or older and had data available for BMI at baseline and for type 2 diabetes, coronary heart disease, and stroke at baseline and follow-up. We excluded participants with a diagnosis of diabetes, coronary heart disease, or stroke at or before study baseline. According to WHO recommendations, we classified BMI into categories of healthy (20·0-24·9 kg/m(2)), overweight (25·0-29·9 kg/m(2)), class I (mild) obesity (30·0-34·9 kg/m(2)), and class II and III (severe) obesity (≥35·0 kg/m(2)). We used an inclusive definition of underweight (<20 kg/m(2)) to achieve sufficient case numbers for analysis. The main outcome was cardiometabolic multimorbidity (ie, developing at least two from: type 2 diabetes, coronary heart disease, and stroke). Incident cardiometabolic multimorbidity was ascertained via resurvey or linkage to electronic medical records (including hospital admissions and death). We analysed data from each cohort separately using logistic regression and then pooled cohort-specific estimates using random-effects meta-analysis. FINDINGS: Participants were 120  813 adults (mean age 51·4 years, range 35-103; 71 445 women) who did not have diabetes, coronary heart disease, or stroke at study baseline (1973-2012). During a mean follow-up of 10·7 years (1995-2014), we identified 1627 cases of multimorbidity. After adjustment for sociodemographic and lifestyle factors, compared with individuals with a healthy weight, the risk of developing cardiometabolic multimorbidity in overweight individuals was twice as high (odds ratio [OR] 2·0, 95% CI 1·7-2·4; p<0·0001), almost five times higher for individuals with class I obesity (4·5, 3·5-5·8; p<0·0001), and almost 15 times higher for individuals with classes II and III obesity combined (14·5, 10·1-21·0; p<0·0001). This association was noted in men and women, young and old, and white and non-white participants, and was not dependent on the method of exposure assessment or outcome ascertainment. In analyses of different combinations of cardiometabolic conditions, odds ratios associated with classes II and III obesity were 2·2 (95% CI 1·9-2·6) for vascular disease only (coronary heart disease or stroke), 12·0 (8·1-17·9) for vascular disease followed by diabetes, 18·6 (16·6-20·9) for diabetes only, and 29·8 (21·7-40·8) for diabetes followed by vascular disease. INTERPRETATION: The risk of cardiometabolic multimorbidity increases as BMI increases; from double in overweight people to more than ten times in severely obese people compared with individuals with a healthy BMI. Our findings highlight the need for clinicians to actively screen for diabetes in overweight and obese patients with vascular disease, and pay increased attention to prevention of vascular disease in obese individuals with diabetes. FUNDING: NordForsk, Medical Research Council, Cancer Research UK, Finnish Work Environment Fund, and Academy of Finland

Job strain and risk of obesity: systematic review and meta-analysis of cohort studies

Job strain, the most widely used indicator of work stress, is a risk factor for obesity-related disorders such as cardiovascular disease and type 2 diabetes. However, the extent to which job strain is related to the development of obesity itself has not been systematically evaluated. We carried out a systematic review (PubMed and Embase until May 2014) and meta-analysis of cohort studies to address this issue. Eight studies that fulfilled inclusion criteria showed no overall association between job strain and the risk of weight gain (pooled odds ratio for job strain compared with no job strain 1.04, 95% confidence interval (CI) 0.99-1.09, NTotal=18 240) or becoming obese (1.00, 95% CI 0.89-1.13, NTotal=42 222). In addition, a reduction in job strain over time was not associated with lower obesity risk (1.13, 95% CI 0.90-1.41, NTotal=6507). These longitudinal findings do not support the hypothesis that job strain is an important risk factor for obesity or a promising target for obesity prevention.International Journal of Obesity advance online publication, 30 June 2015; doi:10.1038/ijo.2015.103

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

Individual tree and stand-level carbon and nutrient contents across one rotation of loblolly pine plantations on a reclaimed surface mine

While reclaimed loblolly pine (Pinus taeda L.) plantations in east Texas, USA have demonstrated similar aboveground productivity levels relative to unmined forests, there is interest in assessing carbon (C) and nutrients in aboveground components of reclaimed trees. Numerous studies have previously documented aboveground biomass, C, and nutrient contents in loblolly pine plantations; however, similar data have not been collected on mined lands. We investigated C, N, P, K, Ca, and Mg aboveground contents for first-rotation loblolly pine growing on reclaimed mined lands in the Gulf Coastal Plain over a 32-year chronosequence and correlated elemental rates to stand age, stem growth, and similar data for unmined lands. At the individual tree level, we evaluated elemental contents in aboveground biomass components using tree size, age, and site index as predictor variables. At the stand-level, we then scaled individual tree C and nutrients and fit a model to determine the sensitivity of aboveground elemental contents to stand age and site index. Our data suggest that aboveground C and nutrients in loblolly pine on mined lands exceed or follow similar trends to data for unmined pine plantations derived from the literature. Diameter and height were the best predictors of individual tree stem C and nutrient contents (R ≥ 0.9473 and 0.9280, respectively) followed by stand age (R ≥ 0.8660). Foliage produced weaker relationships across all predictor variables compared to stem, though still significant (P ≤ 0.05). The model for estimating stand-level C and nutrients using stand age provided a good fit, indicating that contents aggrade over time predictably. Results of this study show successful modelling of reclaimed loblolly pine aboveground C and nutrients, and suggest elemental cycling is comparable to unmined lands, thus providing applicability of our model to related systems

Head Circumference of Infants Born to Mothers with Different Educational Levels; The Generation R Study

Objective: Head circumference (HC) reflect growth and development of the brain in early childhood. It is unknown whether socioeconomic differences in HC are present in early childhood. Therefore, we investigated the association between socioeconomic position (SEP) and HC in early childhood, and potential underlying factors. Methods: The study focused on Dutch children born between April 2002 and January 2006 who participated in The Generation R Study, a population-based prospective cohort study in Rotterdam, the Netherlands. Maternal educational level was used as indicator of SEP. HC measures were concentrated around 1, 3, 6 and 11 months. Associations and explanatory factors were investigated using linear regression analysis, adjusted for potential mediators. Results: The study included 3383 children. At 1, 3 and 6 months of age, children of mothers with a low education had a smaller HC than those with a high education (difference at 1 month: -0.42 SD; 95% CI: -0.54,-0.30; at 3 months: -0.27 SD; 95% CI -0.40,-0.15; and at 6 months: -0.13 SD; 95% CI -0.24,-0.02). Child's length and weight could only partially explain the smaller HC at 1 and 3 months of age. At 6 months, birth weight, gestational age and parental height explained the HC differences. At 11 months, no HC differences were found. Conclusion: Educational inequalities in HC in the first 6 months of life can be mainly explained by pregnancy-related factors, such as birth weight and gestational age. These findings further support public health policies to prevent negative birth outcomes in lower socioeconomic groups

Cognitive function during early abstinence from opioid dependence: a comparison to age, gender, and verbal intelligence matched controls

BACKGROUND: Individuals with opioid dependence have cognitive deficits during abuse period in attention, working memory, episodic memory, and executive function. After protracted abstinence consistent cognitive deficit has been found only in executive function. However, few studies have explored cognitive function during first weeks of abstinence. The purpose of this study was to study cognitive function of individuals with opioid dependence during early abstinence. It was hypothesized that cognitive deficits are pronounced immediately after peak withdrawal symptoms have passed and then partially recover. METHODS: Fifteen patients with opioid dependence and fifteen controls matched for, age, gender, and verbal intelligence were tested with a cognitive test battery When patients performed worse than controls correlations between cognitive performance and days of withdrawal, duration of opioid abuse, duration of any substance abuse, or opioid withdrawal symptom inventory score (Short Opiate Withdrawal Scale) were analyzed. RESULTS: Early abstinent opioid dependent patients performed statistically significantly worse than controls in tests measuring complex working memory, executive function, and fluid intelligence. Their complex working memory and fluid intelligence performances correlated statistically significantly with days of withdrawal. CONCLUSION: The results indicate a rather general neurocognitive deficit in higher order cognition. It is suggested that cognitive deficit during early abstinence from opioid dependence is related to withdrawal induced neural dysregulation in the prefrontal cortex and is partly transient

A Macroecological Analysis of SERA Derived Forest Heights and Implications for Forest Volume Remote Sensing

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H100, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H100 and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 102–106 plants/hectare and heights 6–49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H100

As cold as a fish? Relationships between the Dark Triad personality traits and affective experience during the day: A day reconstruction study

The Dark Triad of personality is a cluster of three socially aversive personality traits: Machiavellianism, narcissism and psychopathy. These traits are associated with a selfish, aggressive and exploitative interpersonal strategy. The objective of the current study was to establish relationships between the Dark Triad traits (and their dimensions) and momentary affect. Machiavellianism, grandiose narcissism, vulnerable narcissism and the dimensions of the Triarchic model of psychopathy (namely, boldness, meanness and disinhibition) were examined. We used the Day Reconstruction Method, which is based on reconstructing affective states experienced during the previous day. The final sample consisted of 270 university students providing affective ratings of 3047 diary episodes. Analyses using multilevel modelling showed that only boldness had a positive association with positive affective states and affect balance, and a negative association with negative affective states. Grandiose narcissism and its sub-dimensions had no relationship with momentary affect. The other dark traits were related to negative momentary affect and/or inversely related to positive momentary affect and affect balance. As a whole, our results empirically demonstrated distinctiveness of the Dark Triad traits in their relationship to everyday affective states. These findings are not congruent with the notion that people with the Dark Triad traits, who have a dispositional tendency to manipulate and exploit others, are generally cold and invulnerable to negative feelings. The associations between the Dark Triad and momentary affect were discussed in the contexts of evolutionary and positive psychology, in relation to the role and adaptive value of positive and negative emotions experienced by individuals higher in Machiavellianism, narcissism and psychopathy