Homogeneity testing for skewed and cross-correlated data in regional flood frequency analysis

In regional frequency analysis the homogeneity of a group of multiple stations is an essential pre-assumption. A standard procedure in hydrology to evaluate this condition is the test based on the homogeneity measure of Hosking and Wallis, which applies L-moments. Disadvantages of it are the lack of power when analysing highly skewed data and the implicit assumption of spatial independence. To face these issues we generalize this procedure in two ways. Copulas are utilised to model intersite dependence and trimmed L-moments as a more robust alternative to ordinary L-moments. The results of simulation studies are presented to discuss the influence of different copula models and different trimming parameters. It turns out that the usage of asymmetrically trimmed L-moments improves the heterogeneity detection in skewed data, while maintaining a reasonable error rate. Simple copula models are sufficient to incorporate the dependence structure of the data in the procedure. Additionally, a more robust behaviour against extreme events at single stations is achieved with the use of trimmed L-moments. Strong intersite dependence and skewed data reveal the need of a modified procedure in a case study with data from Saxony, Germany

Global irrigation water demand: Variability and uncertainties arising from agricultural and climate data sets

Agricultural water use accounts for around 70% of the total water that is withdrawn from surface water and groundwater. We use a new, gridded, global-scale water balance model to estimate interannual variability in global irrigation water demand arising from climate data sets and uncertainties arising from agricultural and climate data sets. We used contemporary maps of irrigation and crop distribution, and so do not account for variability or trends in irrigation area or cropping. We used two different global maps of irrigation and two different reconstructions of daily weather 1963–2002. Simulated global irrigation water demand varied by ∼30%, depending on irrigation map or weather data. The combined effect of irrigation map and weather data generated a global irrigation water use range of 2200 to 3800 km3 a−1. Weather driven variability in global irrigation was generally less than ±300 km3 a−1, globally (\u3c∼10%), but could be as large as ±70% at the national scale

The significance of local water resources captured in small reservoirs for crop production – A global-scale analysis

Rainwater harvesting, broadly defined as the collection and storage of surface runoff, has a long history in supplying water for agricultural purposes. Despite its significance, rainwater harvesting in small reservoirs has previously been overlooked in large-scale assessments of agricultural water supply and demand. We used a macroscale hydrological model, observed climate data and other physical datasets to explore the potential role of small, localized rainwater harvesting systems in supplying water for irrigated areas. We first estimated the potential contribution of local water harvesting to supply currently irrigated areas. We then explored the potential of supplemental irrigation applied to all cropland areas to increase crop evapotranspiration (or green water flow), using locally stored surface runoff in small reservoirs for different scenarios of installed reservoir capacity. The estimated increase in green water flow varied between 623 and 1122 km3 a1 . We assessed the implications of this increase in green water flows for cereal production by assuming a constant crop water productivity in areas where current levels of crop yield are below global averages. Globally, the supplemental irrigation of existing cropland areas could increase cereal production by 35% for a medium variant of reservoir capacity, with large potential increases in Africa and Asia. As small reservoirs can significantly impact the hydrological regime of river basins, we also assessed the impacts of small reservoirs on downstream river flow and quantified evaporation losses from small reservoirs

Denaturation transition of stretched DNA

We generalize the Poland-Scheraga model to consider DNA denaturation in the presence of an external stretching force. We demonstrate the existence of a force-induced DNA denaturation transition and obtain the temperature-force phase diagram. The transition is determined by the loop exponent $c$ for which we find the new value $c=4\nu-1/2$ such that the transition is second order with $c=1.85<2$ in $d=3$. We show that a finite stretching force $F$ destabilizes DNA, corresponding to a lower melting temperature $T(F)$, in agreement with single-molecule DNA stretching experiments.Comment: 5 pages, 3 figure

Sun stanshe

Розглянута структура фотоелектричної станції середньої потужності з можливістю передачі енергії в промислову мережу. Запропоновані рішення для спрощення схемотехніки перетворювальної частини сонячної станції, спрямовані на зниження її собівартості. Проведено експериментальні дослідження особливостей функціонування сонячної станції. Розглянуто можливі аварійні режими роботи сонячної станції та надано рекомендації щодо їх усунення. Проведено аналіз експериментальних досліджень і на їх основі запропоновано шляхи підвищення ККД станції.The structure of a small-scale photovoltaic station, which can be used on single structures, is considered. At the same time, it is desirable to have a backup the battery on accumulators for reliable power supply and to be connected to the industrial network. Thus, the structure of the photovoltaic station, which has the ability to accumulate energy in the battery on accumulators and transfer the remnants to the industrial network, using it as a reservoir of infinite capacity, is proposed. The influence on the production of electricity from the photovoltaic station is shown due to the unevenness of the illumination of the surface of the solar panels

The empirical replicability of task-based fMRI as a function of sample size

Replicating results (i.e. obtaining consistent results using a new independent dataset) is an essential part of good science. As replicability has consequences for theories derived from empirical studies, it is of utmost importance to better understand the underlying mechanisms influencing it. A popular tool for non-invasive neuroimaging studies is functional magnetic resonance imaging (fMRI). While the effect of underpowered studies is well documented, the empirical assessment of the interplay between sample size and replicability of results for task-based fMRI studies remains limited. In this work, we extend existing work on this assessment in two ways. Firstly, we use a large database of 1400 subjects performing four types of tasks from the IMAGEN project to subsample a series of independent samples of increasing size. Secondly, replicability is evaluated using a multi-dimensional framework consisting of 3 different measures: (un)conditional test-retest reliability, coherence and stability. We demonstrate not only a positive effect of sample size, but also a trade-off between spatial resolution and replicability. When replicability is assessed voxelwise or when observing small areas of activation, a larger sample size than typically used in fMRI is required to replicate results. On the other hand, when focussing on clusters of voxels, we observe a higher replicability. In addition, we observe variability in the size of clusters of activation between experimental paradigms or contrasts of parameter estimates within these

Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence

Background Autistic traits are commonly viewed as dimensional in nature, and as continuously distributed in the general population. In this respect, the identification of predictive values of markers such as subtle autism-related alterations in brain morphology for parameter values of autistic traits could increase our understanding of this dimensional occasion. However, currently, very little is known about how these traits correspond to alterations in brain morphology in typically developing individuals, particularly during a time period where changes due to brain development processes do not provide a bias. Therefore, in the present study, we analyzed brain volume, cortical thickness (CT) and surface area (SA) in a cohort of 14-15-year-old adolescents (N = 285, female: N = 162) and tested their predictive value for autistic traits, assessed with the social responsiveness scale (SRS) two years later at the age of 16-17 years, using a regression-based approach. We found that autistic traits were significantly predicted by volumetric changes in the amygdala (r = 0.181), cerebellum (r = 0.128) and hippocampus (r = -0.181, r = -0.203), both in boys and girls. Moreover, the CT of the superior frontal region was negatively correlated (r = -0.144) with SRS scores. Furthermore, we observed a significant association between the SRS total score and smaller left putamen volume, specifically in boys (r = -0.217), but not in girls. Our findings suggest that neural correlates of autistic traits also seem to lie on a continuum in the general population, are determined by limbic-striatal neuroanatomical brain areas, and are partly dependent on sex. As we imaged adolescents from a large population-based cohort within a small age range, these data may help to increase the understanding of autistic-like occasions in otherwise typically developing individuals

Interplay of early negative life events, development of orbitofrontal cortical thickness and depression in young adulthood

Background Early negative life events (NLE) have long-lasting influences on neurodevelopment and psychopathology. Reduced orbitofrontal cortex (OFC) thickness was frequently associated with NLE and depressive symptoms. OFC thinning might mediate the effect of NLE on depressive symptoms, although few longitudinal studies exist. Using a complete longitudinal design with four time points, we examined whether NLE during childhood and early adolescence predict depressive symptoms in young adulthood through accelerated OFC thinning across adolescence. Methods We acquired structural MRI from 321 participants at two sites across four time points from ages 14 to 22. We measured NLE with the Life Events Questionnaire at the first time point and depressive symptoms with the Center for Epidemiologic Studies Depression Scale at the fourth time point. Modeling latent growth curves, we tested whether OFC thinning mediates the effect of NLE on depressive symptoms. Results A higher burden of NLE, a thicker OFC at the age of 14, and an accelerated OFC thinning across adolescence predicted young adults' depressive symptoms. We did not identify an effect of NLE on OFC thickness nor OFC thickness mediating effects of NLE on depressive symptoms. Conclusions Using a complete longitudinal design with four waves, we show that NLE in childhood and early adolescence predict depressive symptoms in the long term. Results indicate that an accelerated OFC thinning may precede depressive symptoms. Assessment of early additionally to acute NLEs and neurodevelopment may be warranted in clinical settings to identify risk factors for depression

Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence

Background: Autistic traits are commonly viewed as dimensional in nature, and as continuously distributed in the general population. In this respect, the identification of predictive values of markers such as subtle autism-related alterations in brain morphology for parameter values of autistic traits could increase our understanding of this dimensional occasion. However, currently, very little is known about how these traits correspond to alterations in brain morphology in typically developing individuals, particularly during a time period where changes due to brain development processes do not provide a bias. Therefore, in the present study, we analyzed brain volume, cortical thickness (CT) and surface area (SA) in a cohort of 14–15-year-old adolescents (N = 285, female: N = 162) and tested their predictive value for autistic traits, assessed with the social responsiveness scale (SRS) two years later at the age of 16–17 years, using a regression-based approach. We found that autistic traits were significantly predicted by volumetric changes in the amygdala (r = 0.181), cerebellum (r = 0.128) and hippocampus (r = −0.181, r = −0.203), both in boys and girls. Moreover, the CT of the superior frontal region was negatively correlated (r = −0.144) with SRS scores. Furthermore, we observed a significant association between the SRS total score and smaller left putamen volume, specifically in boys (r = −0.217), but not in girls. Our findings suggest that neural correlates of autistic traits also seem to lie on a continuum in the general population, are determined by limbic–striatal neuroanatomical brain areas, and are partly dependent on sex. As we imaged adolescents from a large population-based cohort within a small age range, these data may help to increase the understanding of autistic-like occasions in otherwise typically developing individuals

The relationship between negative life events and cortical structural connectivity in adolescents

Adolescence is a crucial period for physical and psychological development. The impact of negative life events represents a risk factor for the onset of neuropsychiatric disorders. This study aims to investigate the relationship between negative life events and structural brain connectivity, considering both graph theory and connectivity strength. A group (n = 487) of adolescents from the IMAGEN Consortium was divided into Low and High Stress groups. Brain networks were extracted at an individual level, based on morphological similarity between grey matter regions with regions defined using an atlas-based region of interest (ROI) approach. Between-group comparisons were performed with global and local graph theory measures in a range of sparsity levels. The analysis was also performed in a larger sample of adolescents (n = 976) to examine linear correlations between stress level and network measures. Connectivity strength differences were investigated with network-based statistics. Negative life events were not found to be a factor influencing global network measures at any sparsity level. At local network level, between-group differences were found in centrality measures of the left somato-motor network (a decrease of betweenness centrality was seen at sparsity 5%), of the bilateral central visual and the left dorsal attention network (increase of degree at sparsity 10% at sparsity 30% respectively). Network-based statistics analysis showed an increase in connectivity strength in the High stress group in edges connecting the dorsal attention, limbic and salience networks. This study suggests negative life events alone do not alter structural connectivity globally, but they are associated to connectivity properties in areas involved in emotion and attention.</p