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Aerosol emissions from human activities are extensive and changing rapidly over Asia. Model simulations and satellite observations indicate a dipole pattern in aerosol emissions and loading between South Asia and East Asia, two of the most heavily polluted regions of the world. We examine the previously unexplored diverging trends in the existing dipole pattern of aerosols between East and South Asia using the high quality, two-decade long ground-based time series of observations of aerosol properties from the Aerosol Robotic Network (AERONET), from satellites (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)), and from model simulations (Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The data cover the period since 2001 for Kanpur (South Asia) and Beijing (East Asia), two locations taken as being broadly representative of the respective regions. Since 2010 a dipole in aerosol optical depth (AOD) is maintained, but the trend is reversed-the decrease in AOD over Beijing (East Asia) is rapid since 2010, being 17% less in current decade compared to first decade of twenty-first century, while the AOD over South Asia increased by 12% during the same period. Furthermore, we find that the aerosol composition is also changing over time. The single scattering albedo (SSA), a measure of aerosol's absorption capacity and related to aerosol composition, is slightly higher over Beijing than Kanpur, and has increased from 0.91 in 2002 to 0.93 in 2017 over Beijing and from 0.89 to 0.92 during the same period over Kanpur, confirming that aerosols in this region have on an average become more scattering in nature. These changes have led to a notable decrease in aerosol-induced atmospheric heating rate (HR) over both regions between the two decades, decreasing considerably more over East Asia (- 31%) than over South Asia (- 9%). The annual mean HR is lower now, it is still large (>= 0.6 K per day), which has significant climate implications. The seasonal trends in AOD, SSA and HR are more pronounced than their respective annual trends over both regions. The seasonal trends are caused mainly by the increase/decrease in anthropogenic aerosol emissions (sulfate, black carbon and organic carbon) while the natural aerosols (dust and sea salt) did not change significantly over South and East Asia during the last two decades. The MERRA-2 model is able to simulate the observed trends in AODs well but not the magnitude, while it also did not simulate the SSA values or trends well. These robust findings based on observations of key aerosol parameters and previously unrecognized diverging trends over South and East Asia need to be accounted for in current state-of-the-art climate models to ensure accurate quantification of the complex and evolving impact of aerosols on the regional climate over Asia.
Corona and the climate
(2020)
Compound natural hazards likeEl Ninoevents cause high damage to society, which to manage requires reliable risk assessments. Damage modelling is a prerequisite for quantitative risk estimations, yet many procedures still rely on expert knowledge, and empirical studies investigating damage from compound natural hazards hardly exist. A nationwide building survey in Peru after theEl Ninoevent 2017 - which caused intense rainfall, ponding water, flash floods and landslides - enables us to apply data-mining methods for statistical groundwork, using explanatory features generated from remote sensing products and open data. We separate regions of different dominant characteristics through unsupervised clustering, and investigate feature importance rankings for classifying damage via supervised machine learning. Besides the expected effect of precipitation, the classification algorithms select the topographic wetness index as most important feature, especially in low elevation areas. The slope length and steepness factor ranks high for mountains and canyons. Partial dependence plots further hint at amplified vulnerability in rural areas. An example of an empirical damage probability map, developed with a random forest model, is provided to demonstrate the technical feasibility.
We describe a new, original approach to the modelling of the Earth's magnetic field. The overall objective of this study is to reliably render fast variations of the core field and its secular variation. This method combines a sequential modelling approach, a Kalman filter, and a correlation-based modelling step. Sources that most significantly contribute to the field measured at the surface of the Earth are modelled. Their separation is based on strong prior information on their spatial and temporal behaviours. We obtain a time series of model distributions which display behaviours similar to those of recent models based on more classic approaches, particularly at large temporal and spatial scales. Interesting new features and periodicities are visible in our models at smaller time and spatial scales. An important aspect of our method is to yield reliable error bars for all model parameters. These errors, however, are only as reliable as the description of the different sources and the prior information used are realistic. Finally, we used a slightly different version of our method to produce candidate models for the thirteenth edition of the International Geomagnetic Reference Field.
To construct a coherent multi-modal percept, vertebrate brains extract low-level features (such as spatial and temporal frequencies) from incoming sensory signals. However, because frequency processing is lateralized with the right hemisphere favouring low frequencies while the left favours higher frequencies, this introduces asymmetries between the hemispheres. Here, we describe how this lateralization shapes the development of several cognitive domains, ranging from visuo-spatial and numerical cognition to language, social cognition, and even aesthetic appreciation, and leads to the emergence of asymmetries in behaviour. We discuss the neuropsychological and educational implications of these emergent asymmetries and suggest future research approaches.
Carbon nanodots revised
(2020)
Luminescent compounds obtained from the thermal reaction of citric acid and urea have been studied and utilized in different applications in the past few years. The identified reaction products range from carbon nitrides over graphitic carbon to distinct molecular fluorophores. On the other hand, the solid, non-fluorescent reaction product produced at higher temperatures has been found to be a valuable precursor for the CO2-laser-assisted carbonization reaction in carbon laser-patterning. This work addresses the question of structural identification of both, the fluorescent and non-fluorescent reaction products obtained in the thermal reaction of citric acid and urea. The reaction products produced during autoclave-microwave reactions in the melt were thoroughly investigated as a function of the reaction temperature and the reaction products were subsequently separated by a series of solvent extractions and column chromatography. The evolution of a green molecular fluorophore, namely HPPT, was confirmed and a full characterization study on its structure and photophysical properties was conducted. The additional blue fluorescence is attributed to oligomeric ureas, which was confirmed by complementary optical and structural characterization. These two components form strong hydrogen-bond networks which eventually react to form solid, semi-crystalline particles with a size of similar to 7 nm and an elemental composition of 46% C, 22% N, and 29% O. The structural features and properties of all three main components were investigated in a comprehensive characterization study.
Social epigenomics is a new field of research that studies how the social environment shapes the epigenome and how in turn the epigenome modulates behavior. We focus on describing known gene-environment interactions (GEIs) and epigenetic mechanisms in different mammalian social systems. To illustrate how epigenetic mechanisms integrate GEls, we highlight examples where epigenetic mechanisms are associated with social behaviors and with their maintenance through neuroendocrine, locomotor, and metabolic responses. We discuss future research trajectories and open questions for the emerging field of social epigenomics in nonmodel and naturally occurring social systems. Finally, we outline the technological advances that aid the study of epigenetic mechanisms in the establishment of GEIs and vice versa.
The sensitivity of key hydrologic variables and hydropower generation to climate change in the Lake Malawi and Shire River basins is assessed. The study adapts the mesoscale Hydrological Model (mHM) which is applied separately in the Upper Lake Malawi and Shire River basins. A particular Lake Malawi model, which focuses on reservoir routing and lake water balance, has been developed and is interlinked between the two basins. Climate change projections from 20 Coordinated Regional Climate Downscaling Experiment (CORDEX) models for Africa based on two scenarios (RCP4.5 and RCP8.5) for the periods 2021-2050 and 2071-2100 are used. An annual temperature increase of 1 degrees C decreases mean lake level and outflow by 0.3 m and 17%, respectively, signifying the importance of intensified evaporation for Lake Malawi's water budget. Meanwhile, a +5% (-5%) deviation in annual rainfall changes mean lake level by +0.7 m (-0.6 m). The combined effects of temperature increase and rainfall decrease result in significantly lower flows in the Shire River. The hydrological river regime may change from perennial to seasonal with the combination of annual temperature increase and precipitation decrease beyond 1.5 degrees C (3.5 degrees C) and -20% (-15%). The study further projects a reduction in annual hydropower production between 1% (RCP8.5) and 2.5% (RCP4.5) during 2021-2050 and between 5% (RCP4.5) and 24% (RCP8.5) during 2071-2100. The results show that it is of great importance that a further development of hydro energy on the Shire River should take into account the effects of climate change, e.g., longer low flow periods and/or higher discharge fluctuations, and thus uncertainty in the amount of electricity produced.
The occurrence of refugia beyond the arctic treeline and genetic adaptation therein play a crucial role of largely unknown effect size. While refugia have potential for rapidly colonizing the tundra under global warming, the taxa may be maladapted to the new environmental conditions. Understanding the genetic composition and age of refugia is thus crucial for predicting any migration response.
Here, we genotype 194 larch individuals from an similar to 1.8 km(2)area in northcentral Siberia on the southern Taimyr Peninsula by applying an assay of 16 nuclear microsatellite markers. For estimating the age of clonal individuals, we counted tree rings at sections along branches to establish a lateral growth rate that was then combined with geographic distance.
Findings reveal that the predominant reproduction type is clonal (58.76%) by short distance spreading of ramets. One outlier of clones 1 km apart could have been dispersed by reindeer. In clonal groups and within individuals, we find that somatic mutations accumulate with geographic distance. Clonal groups of two or more individuals are observed. Clonal age estimates regularly suggest individuals as old as 2,200 years, which coincides with a major environmental change that forced a treeline retreat in the region.
We conclude that individuals with clonal growth mode were naturally selected as it lowers the likely risk of extinction under a harsh environment. We discuss this legacy from the past that might now be a maladaptation and hinder expansion under currently strongly increasing temperatures.
The Paris Climate Agreement aims to keep temperature rise well below 2 degrees C. This implies mitigation costs as well as avoided climate damages. Here we show that independent of the normative assumptions of inequality aversion and time preferences, the agreement constitutes the economically optimal policy pathway for the century. To this end we consistently incorporate a damage-cost curve reproducing the observed relation between temperature and economic growth into the integrated assessment model DICE. We thus provide an intertemporally optimizing cost-benefit analysis of this century's climate problem. We account for uncertainties regarding the damage curve, climate sensitivity, socioeconomic future, and mitigation costs. The resulting optimal temperature is robust as can be understood from the generic temperature-dependence of the mitigation costs and the level of damages inferred from the observed temperature-growth relationship. Our results show that the politically motivated Paris Climate Agreement also represents the economically favourable pathway, if carried out properly.
Consensify
(2020)
A standard practise in palaeogenome analysis is the conversion of mapped short read data into pseudohaploid sequences, frequently by selecting a single high-quality nucleotide at random from the stack of mapped reads. This controls for biases due to differential sequencing coverage, but it does not control for differential rates and types of sequencing error, which are frequently large and variable in datasets obtained from ancient samples. These errors have the potential to distort phylogenetic and population clustering analyses, and to mislead tests of admixture using D statistics. We introduce Consensify, a method for generating pseudohaploid sequences, which controls for biases resulting from differential sequencing coverage while greatly reducing error rates. The error correction is derived directly from the data itself, without the requirement for additional genomic resources or simplifying assumptions such as contemporaneous sampling. For phylogenetic and population clustering analysis, we find that Consensify is less affected by artefacts than methods based on single read sampling. For D statistics, Consensify is more resistant to false positives and appears to be less affected by biases resulting from different laboratory protocols than other frequently used methods. Although Consensify is developed with palaeogenomic data in mind, it is applicable for any low to medium coverage short read datasets. We predict that Consensify will be a useful tool for future studies of palaeogenomes.
Soil structure, the complex arrangement of soil into aggregates and pore spaces, is a key feature of soils and soil biota. Among them, filamentous saprobic fungi have well-documented effects on soil aggregation. However, it is unclear what properties, or traits, determine the overall positive effect of fungi on soil aggregation. To achieve progress, it would be helpful to systematically investigate a broad suite of fungal species for their trait expression and the relation of these traits to soil aggregation. Here, we apply a trait-based approach to a set of 15 traits measured under standardized conditions on 31 fungal strains including Ascomycota, Basidiomycota, and Mucoromycota, all isolated from the same soil. We find large differences among these fungi in their ability to aggregate soil, including neutral to positive effects, and we document large differences in trait expression among strains. We identify biomass density, i.e., the density with which a mycelium grows (positive effects), leucine aminopeptidase activity (negative effects) and phylogeny as important factors explaining differences in soil aggregate formation (SAF) among fungal strains; importantly, growth rate was not among the important traits. Our results point to a typical suite of traits characterizing fungi that are good soil aggregators, and our findings illustrate the power of employing a trait-based approach to unravel biological mechanisms underpinning soil aggregation. Such an approach could now be extended also to other soil biota groups. In an applied context of restoration and agriculture, such trait information can inform management, for example to prioritize practices that favor the expression of more desirable fungal traits.
Globally, cardiovascular diseases are the leading cause of death in the aging population. While the clinical pathology of the aging heart is thoroughly characterized, underlying molecular mechanisms are still insufficiently clarified. The aim of the present study was to establish an in vitro model system of cardiomyocyte premature senescence, culturing heart muscle cells derived from neonatal C57Bl/6J mice for 21 days. Premature senescence of neonatal cardiac myocytes was induced by prolonged culture time in an oxygen-rich postnatal environment. Age-related changes in cellular function were determined by senescence-associated beta-galactosidase activity, increasing presence of cell cycle regulators, such as p16, p53, and p21, accumulation of protein aggregates, and restricted proteolysis in terms of decreasing (macro-)autophagy. Furthermore, the culture system was functionally characterized for alterations in cell morphology and contractility. An increase in cellular size associated with induced expression of atrial natriuretic peptides demonstrated a stress-induced hypertrophic phenotype in neonatal cardiomyocytes. Using the recently developed analytical software tool Myocyter, we were able to show a spatiotemporal constraint in spontaneous contraction behavior during cultivation. Within the present study, the 21-day culture of neonatal cardiomyocytes was defined as a functional model system of premature cardiac senescence to study age-related changes in cardiomyocyte contractility and autophagy.
Several large-scale cryosphere elements such as the Arctic summer sea ice, the mountain glaciers, the Greenland and West Antarctic Ice Sheet have changed substantially during the last century due to anthropogenic global warming. However, the impacts of their possible future disintegration on global mean temperature (GMT) and climate feedbacks have not yet been comprehensively evaluated. Here, we quantify this response using an Earth system model of intermediate complexity. Overall, we find a median additional global warming of 0.43 degrees C (interquartile range: 0.39-0.46 degrees C) at a CO2 concentration of 400 ppm. Most of this response (55%) is caused by albedo changes, but lapse rate together with water vapour (30%) and cloud feedbacks (15%) also contribute significantly. While a decay of the ice sheets would occur on centennial to millennial time scales, the Arctic might become ice-free during summer within the 21st century. Our findings imply an additional increase of the GMT on intermediate to long time scales. The disintegration of cryosphere elements such as the Arctic summer sea ice, mountain glaciers, Greenland and West Antarctica is associated with temperature and radiative feedbacks. In this work, the authors quantify these feedbacks and find an additional global warming of 0.43 degrees C.
Overnutrition contributes to insulin resistance, obesity and metabolic stress, initiating a loss of functional beta-cells and diabetes development. Whether these damaging effects are amplified in advanced age is barely investigated. Therefore, New Zealand Obese (NZO) mice, a well-established model for the investigation of human obesity-associated type 2 diabetes, were fed a metabolically challenging diet with a high-fat, carbohydrate restricted period followed by a carbohydrate intervention in young as well as advanced age. Interestingly, while young NZO mice developed massive hyperglycemia in response to carbohydrate feeding, leading to beta-cell dysfunction and cell death, aged counterparts compensated the increased insulin demand by persistent beta-cell function and beta-cell mass expansion. Beta-cell loss in young NZO islets was linked to increased expression of thioredoxin-interacting protein (TXNIP), presumably initiating an apoptosis-signaling cascade via caspase-3 activation. In contrast, islets of aged NZOs exhibited a sustained redox balance without changes in TXNIP expression, associated with higher proliferative potential by cell cycle activation. These findings support the relevance of a maintained proliferative potential and redox homeostasis for preserving islet functionality under metabolic stress, with the peculiarity that this adaptive response emerged with advanced age in diabetesprone NZO mice.
Background:
Cyberhate is a growing form of online aggression against a person or a group based on race, ethnicity, nationality, sexual orientation, gender, religion, or disability. The present study aims to examine psychometric properties of the Coping with Cyberhate Questionnaire, the prevalence of coping strategies in Spanish adolescents, differences in coping strategies based in sex, age, and victim status, and the association between coping with cyberhate and adolescents' mental well-being.
Method:
The sample consisted of 1,005 adolescents between 12 and 18 years old (Mage = 14.28 years, SD = 1.63; 51.9% girls) who completed self-report measures on coping strategies, victimization status, and mental well-being.
Results:
The results of confirmatory factor analyses showed a structure for the Coping with Cyberhate Questionnaire composed of six factors, namely Distal advice, Assertiveness, Helplessness/Selfblame, Close support, Technical coping, and Retaliation. It demonstrated acceptable internal consistency. The three most frequently endorsed coping strategies were Technical coping, Close support, and Assertiveness. In addition, lower Helplessness/Self-blame, and higher Close-support, Assertiveness, and Distal advice were significantly related to adolescents' better mental well-being.
Conclusion:
Prevention programs that educate adolescents about how to deal with cyberhate are needed.
Projected changes in compound flood hazard from riverine and coastal floods in northwestern Europe
(2020)
Compound flooding in coastal regions, that is, the simultaneous or successive occurrence of high sea levels and high river flows, is expected to increase in a warmer world. To date, however, there is no robust evidence on projected changes in compound flooding for northwestern Europe. We combine projected storm surges and river floods with probabilistic, localized relative sea-level rise (SLR) scenarios to assess the future compound flood hazard over northwestern coastal Europe in the high (RCP8.5) emission scenario. We use high-resolution, dynamically downscaled regional climate models (RCM) to drive a storm surge model and a hydrological model, and analyze the joint occurrence of high coastal water levels and associated river peaks in a multivariate copula-based approach. The RCM-forced multimodel mean reasonably represents the observed spatial pattern of the dependence strength between annual maxima surge and peak river discharge, although substantial discrepancies exist between observed and simulated dependence strength. All models overestimate the dependence strength, possibly due to limitations in model parameterizations. This bias affects compound flood hazard estimates and requires further investigation. While our results suggest decreasing compound flood hazard over the majority of sites by 2050s (2040-2069) compared to the reference period (1985-2005), an increase in projected compound flood hazard is limited to around 34% of the sites. Further, we show the substantial role of SLR, a driver of compound floods, which has frequently been neglected. Our findings highlight the need to be aware of the limitations of the current generation of Earth system models in simulating coastal compound floods.
The smell of hunger
(2020)
When individuals exchange helpful acts reciprocally, increasing the benefit of the receiver can enhance its propensity to return a favour, as pay-offs are typically correlated in iterated interactions. Therefore, reciprocally cooperating animals should consider the relative benefit for the receiver when deciding to help a conspecific. Norway rats (Rattus norvegicus) exchange food reciprocally and thereby take into account both the cost of helping and the potential benefit to the receiver. By using a variant of the sequential iterated prisoner's dilemma paradigm, we show that rats may determine the need of another individual by olfactory cues alone. In an experimental food-exchange task, test subjects were provided with odour cues from hungry or satiated conspecifics located in a different room. Our results show that wild-type Norway rats provide help to a stooge quicker when they receive odour cues from a hungry rather than from a satiated conspecific. Using chemical analysis by gas chromatography-mass spectrometry (GC-MS), we identify seven volatile organic compounds that differ in their abundance between hungry and satiated rats. Combined, this "smell of hunger" can apparently serve as a reliable cue of need in reciprocal cooperation, which supports the hypothesis of honest signalling.
The Flood Damage Database HOWAS 21 contains object-specific flood damage data resulting from fluvial, pluvial and groundwater flooding. The datasets incorporate various variables of flood hazard, exposure, vulnerability and direct tangible damage at properties from several economic sectors. The main purpose of development of HOWAS 21 was to support forensic flood analysis and the derivation of flood damage models. HOWAS 21 was first developed for Germany and currently almost exclusively contains datasets from Germany. However, its scope has recently been enlarged with the aim to serve as an international flood damage database; e.g. its web application is now available in German and English. This paper presents the recent advancements of HOWAS 21 and highlights exemplary analyses to demonstrate the use of HOWAS 21 flood damage data. The data applications indicate a large potential of the database for fostering a better understanding and estimation of the consequences of flooding.
Hazelnuts are rarely cultivated in Germany, although they are a valuable source for macro- and micronutrients and can thus contribute to a healthy diet. Near the present, 15 varieties were cultivated in Thuringia, Germany, as a pilot study for further research. The aim of our study was to evaluate the micro- and macronutrient composition of representative, randomly mixed samples of the 15 different hazelnut cultivars. Protein, fat, and fiber contents were determined using established methods. Fatty acids, tocopherols, minerals, trace elements, and ultra-trace elements were analyzed using gas chromatography, high-performance liquid chromatography, and inductively coupled plasma triple quadrupole mass-spectrometry, respectively. We found that the different hazelnut varieties contained valuable amounts of fat, protein, dietary fiber, minerals, trace elements, and alpha-tocopherol, however, in different quantities. The variations in nutrient composition were independent of growth conditions, which were identical for all hazelnut varieties. Therefore, each hazelnut cultivar has its specific nutrient profile.
This exploratory study aimed to monitor long-term seasonal developments in measures of anthropometry, body composition, and physical fitness in young judo athletes, and to compute associations between these measures and sporting success. Forty-four young judoka (20 females, 24 males) volunteered to participate. Tests for the assessment of anthropometry (e.g., body height/mass), body-composition (e.g., lean body mass), muscle strength (isometric handgrip strength), vertical jumping (e.g., countermovement-jump (CMJ) height), and dynamic balance (Y-balance test) were conducted at the beginning and end of a 10-month training season. Additionally, sporting success at the end of the season was recorded for each athlete. Analyses revealed significant time x sex interaction effects for lean-body-mass, isometric handgrip strength, and CMJ height (0.7 <= d <= 1.6). Post-hoc analyses showed larger gains for all measures in young males (1.9 <= d <= 6.0) compared with females (d = 2.4) across the season. Additionally, significant increases in body height and mass as well as Y-balance test scores were found from pre-to-post-test (1.2 <= d <= 4.3), irrespective of sex. Further, non-significant small-to-moderate-sized correlations were identified between changes in anthropometry/body composition/physical fitness and sporting success (p > 0.05; -0.34 <= rho <= 0.32). Regression analysis confirmed that no model significantly predicted sporting success. Ten months of judo training and/or growth/maturation contributed to significant changes in anthropometry, body composition, and physical fitness, particularly in young male judo athletes.
Grasslands cover ca. 30% of the global land surface and provide critical ecosystem services. Among them, carbon storage is one of the most important. However, grasslands are increasingly threatened by drought and overgrazing which might negatively affect soil carbon stocks. Despite this threat, there is a dearth of information on how drought and grazing jointly impact soil carbon stocks and CO2 fluxes in dryland grasslands. With the aid of a large field experiment, we studied the combined effects of a 5-year extreme drought and moderate grazing on soil carbon stocks, CO2 fluxes and soil chemical properties. Extreme drought was induced by reducing ambient rainfall by 66% using large rainout shelters. We found CO2 fluxes to strongly respond to the 5-year experimental drought. Extreme drought reduced CO2 emission rates by 32% compared to ambient conditions. CO2 fluxes averaged 5.7 mg m(-2)min(-1) under drought compared to 8.3 mg m(-2) min(-1) under ambient conditions. CO2 fluxes were, however, not influenced by grazing. At the end of the growth period, grazed plots under ambient rainfall had released 16.3 tons of CO2 ha(-1) which was 58% higher than observed on grazed plots subjected to severe drought. Soil carbon stocks were higher under drought conditions due to slower decomposition rates. Drought resulted in increased concentrations of primary macronutrients (N, P, and K), micronutrients (Zn and Mn) and pH in the top 30 cm of the soil relative to ambient conditions. The results also showed that grazing reduced the concentration of N and P in the topsoil compared to the ungrazed plots. This study provided insights on the soil carbon storage, CO2 emission rates and nutrient dynamics in a semi-arid dryland grassland as influenced by both drought and grazing. Our study also revealed that long-term extreme drought may be favorable in terms of preserving the existing soil carbon stocks through reduced CO2 release. This finding is critical for understanding future soil carbon dynamics in dryland grasslands in the face of climate change.
Multi-year index-based insurance for adapting Water Utility Companies to hydrological drought
(2020)
The sustainability of water utility companies is threatened by non-stationary drivers, such as climate and anthropogenic changes. To cope with potential economic losses, instruments such as insurance are useful for planning scenarios and mitigating impacts, but data limitations and risk uncertainties affect premium estimation and, consequently, business sustainability. This research estimated the possible economic impacts of business interruption to the Sao Paulo Water Utility Company derived from hydrological drought and how this could be mitigated with an insurance scheme. Multi-year insurance (MYI) was proposed through a set of "change" drivers: the climate driver, through forcing the water evaluation and planning system (WEAP) hydrological tool; the anthropogenic driver, through water demand projections; and the economic driver, associated with recent water price policies adopted by the utility company during water scarcity periods. In our study case, the evaluated indices showed that MYI contracts that cover only longer droughts, regardless of the magnitude, offer better financial performance than contracts that cover all events (in terms of drought duration). Moreover, through MYI contracts, we demonstrate solvency for the insurance fund in the long term and an annual average actuarially fair premium close to the total expected revenue reduction.
We present a new model of the geomagnetic field spanning the last 20 years and called Kalmag. Deriving from the assimilation of CHAMP and Swarm vector field measurements, it separates the different contributions to the observable field through parameterized prior covariance matrices. To make the inverse problem numerically feasible, it has been sequentialized in time through the combination of a Kalman filter and a smoothing algorithm. The model provides reliable estimates of past, present and future mean fields and associated uncertainties. The version presented here is an update of our IGRF candidates; the amount of assimilated data has been doubled and the considered time window has been extended from [2000.5, 2019.74] to [2000.5, 2020.33].
Arousal is one of the dimensions of core affect and frequently used to describe experienced or observed emotional states. While arousal ratings of facial expressions are collected in many studies it is not well understood how arousal is displayed in or interpreted from facial expressions. In the context of socioemotional disorders such as Autism Spectrum Disorder, this poses the question of a differential use of facial information for arousal perception. In this study, we demonstrate how automated face-tracking tools can be used to extract predictors of arousal judgments. We find moderate to strong correlations among all measures of static information on one hand and all measures of dynamic information on the other. Based on these results, we tested two measures, average distance to the neutral face and average facial movement speed, within and between neurotypical individuals (N = 401) and individuals with autism (N = 19). Distance to the neutral face was predictive of arousal in both groups. Lower mean arousal ratings were found for the autistic group, but no difference in correlation of the measures and arousal ratings could be found between groups. Results were replicated in an high autistic traits group. The findings suggest a qualitatively similar perception of arousal for individuals with and without autism. No correlations between valence ratings and any of the measures could be found, emphasizing the specificity of our tested measures. Distance and speed predictors share variability and thus speed should not be discarded as a predictor of arousal ratings.
Increasing interests in hydrocarbon resources at depths have drawn greater attentions to the deeply-buried carbonate reservoirs in the Tarim Basin in China. In this study, the cyclic dolomite rocks of Upper Cambrian Lower Qiulitag Group from four outcrop sections in northwestern Tarim Basin were selected to investigate and evaluate the petrophysical properties in relation to depositional facies and cyclicity. The Lower Qiulitag Group includes ten lithofacies, which were deposited in intermediate to shallow subtidal, restricted shallow subtidal, intertidal, and supratidal environments on a carbonate ramp system. These lithofacies are vertically stacked into repeated shallowing-upward, meter-scale cycles which are further grouped into six third-order depositional sequences (Sq1 to Sq6). There are variable types of pore spaces in the Lower Qiulitag Group dolomite rocks, including interparticle, intraparticle, and fenestral pores of primary origin, inter crystal, and vuggy pores of late diagenetic modification. The porosity in the dolomites is generally facies-selective as that the microbially-originated thrombolites and stromatolites generally yield a relatively high porosity. In contrast, the high-energy ooidal grainstones generally have very low porosity. In this case, the microbialite-based peritidal cycles and peritidal cycle-dominated highstand (or regressive) successions have relatively high volumes of pore spaces, although highly fluctuating (or vertical inhomogeneous). Accordingly, the grainstone-based subtidal cycles and subtidal cycle-dominated transgressive successions generally yield extremely low porosity. This scenario indicates that porosity development and preservation in the thick dolomite successions are primarily controlled by depositional facies which were influenced by sea-level fluctuations of different orders and later diagenetic overprinting.
The aim of this study was to determine the effect of blanching followed by fermentation of mealworms (Tenebrio molitor) with commercial meat starter cultures on the functional properties of powders produced from the larvae. Full fat and defatted powder samples were prepared from non-fermented and fermented mealworm pastes. Then the crude protein, crude fat, and dry matter contents, pH, bulk density, colour, water and oil binding capacity, foaming capacity and stability, emulsion capacity and stability, protein solubility, quantity of free amino groups, and protein composition of the powders were evaluated. Regardless of the starter culture used, the blanching plus fermentation process reduced the crude and soluble protein contents of the full fat powders and in general impaired their water and oil binding, foaming, and emulsifying properties. Defatting of the powders improved most functional properties studied. The o-phthaldialdehyde assay revealed that the amount of free amino groups was higher in the fermented powders while sodium dodecyl sulfate polyacrylamide gel electrophoresis demonstrated that the soluble proteins of the fermented powders were composed of molecules of lower molecular mass compared to non-fermented powders. As molecular sizes of the soluble proteins decreased, it was clear that the protein structure was also modified by the fermentation process, which in turn led to changes in functional properties. In general, it was concluded that fermentation of mealworms with blanching as a pre-treatment does not contribute to the functional properties studied in this work. Nevertheless, the results confirmed that the properties of non-fermented powders are comparable to other food protein sources.
Background
Anticancer compound 3-bromopyruvate (3-BrPA) suppresses cancer cell growth via targeting glycolytic and mitochondrial metabolism. The malignant peripheral nerve sheath tumor (MPNST), a very aggressive, therapy resistant, and Neurofibromatosis type 1 associated neoplasia, shows a high metabolic activity and affected patients may therefore benefit from 3-BrPA treatment. To elucidate the specific mode of action, we used a controlled cell model overexpressing proteasome activator (PA) 28, subsequently leading to p53 inactivation and oncogenic transformation and therefore reproducing an important pathway in MPNST and overall tumor pathogenesis.
Methods
Viability of MPNST cell lines S462, NSF1, and T265 in response to increasing doses (0-120 mu M) of 3-BrPA was analyzed by CellTiter-Blue (R) assay. Additionally, we investigated viability, reactive oxygen species (ROS) production (dihydroethidium assay), nicotinamide adenine dinucleotide dehydrogenase activity (NADH-TR assay) and lactate production (lactate assay) in mouse B8 fibroblasts overexpressing PA28 in response to 3-BrPA application. For all experiments normal and nutrient deficient conditions were tested. MPNST cell lines were furthermore characterized immunohistochemically for Ki67, p53, bcl2, bcl6, cyclin D1, and p21.
Results
MPNST significantly responded dose dependent to 3-BrPA application, whereby S462 cells were most responsive. Human control cells showed a reduced sensitivity. In PA28 overexpressing cancer cell model 3-BrPA application harmed mitochondrial NADH dehydrogenase activity mildly and significantly failed to inhibit lactate production. PA28 overexpression was associated with a functional glycolysis as well as a partial resistance to stress provoked by nutrient deprivation. 3-BrPA treatment was not associated with an increase of ROS. Starvation sensitized MPNST to treatment.
Conclusions
Aggressive MPNST cells are sensitive to 3-BrPA therapy in-vitro with and without starvation. In a PA28 overexpression cancer cell model leading to p53 inactivation, thereby reflecting a key molecular feature in human NF1 associated MPNST, known functions of 3-BrPA to block mitochondrial activity and glycolysis were reproduced, however oncogenic cells displayed a partial resistance. To conclude, 3-BrPA was sufficient to reduce NF1 associated MPNST viability potentially due inhibition of glycolysis which should lead to the initiation of further studies and promises a potential benefit for NF1 patients.
The reactive oxygen species (ROS) gene network, consisting of both ROS-generating and detoxifying enzymes, adjusts ROS levels in response to various stimuli. We performed a cross-kingdom comparison of ROS gene networks to investigate how they have evolved across all Eukaryotes, including protists, fungi, plants and animals. We included the genomes of 16 extremotolerant Eukaryotes to gain insight into ROS gene evolution in organisms that experience extreme stress conditions. Our analysis focused on ROS genes found in all Eukaryotes (such as catalases, superoxide dismutases, glutathione reductases, peroxidases and glutathione peroxidase/peroxiredoxins) as well as those specific to certain groups, such as ascorbate peroxidases, dehydroascorbate/monodehydroascorbate reductases in plants and other photosynthetic organisms. ROS-producing NADPH oxidases (NOX) were found in most multicellular organisms, although several NOX-like genes were identified in unicellular or filamentous species. However, despite the extreme conditions experienced by extremophile species, we found no evidence for expansion of ROS-related gene families in these species compared to other Eukaryotes. Tardigrades and rotifers do show ROS gene expansions that could be related to their extreme lifestyles, although a high rate of lineage-specific horizontal gene transfer events, coupled with recent tetraploidy in rotifers, could explain this observation. This suggests that the basal Eukaryotic ROS scavenging systems are sufficient to maintain ROS homeostasis even under the most extreme conditions.
Salinization is a well-known problem in agricultural areas worldwide. In the last 20-30 yr, rising salinity in the upper, unconfined aquifer has been observed in the Freepsumer Meer, a grassland near the German North Sea coast. For investigating long-term development of salinity and water balance during 1961-2099, the one-dimensional Soil-Water-Atmosphere-Plant (SWAP) model was set up and calibrated for a soil column in the area. The model setup involves a deep aquifer as the source of salt through upward seepage. In the vertical salt transport equation, dispersion and advection are included. Six different regional outputs of statistical downscaling methods were used as climate scenarios. These comprise different rates of increasing surface temperature and different trends in seasonal rainfall. The simulation results exhibit opposing salinity trends for topsoil and deeper layers. Although projections of some scenarios entail decreasing salinities near the surface, most of them project a rise in subsoil salinity, with the strongest trends of up to +0.9 mg cm(-3) 100 yr(-1) at -65 cm. The results suggest that topsoil salinity trends in the study area are affected by the magnitude of winter rainfall trends, whereas high subsoil salinities correspond to low winter rainfall and high summer temperature. How these projected trends affect the vegetation and thereby future land use will depend on the future management of groundwater levels in the area.
The Fram Strait is an area with a relatively low and irregular distribution of diatom microfossils in surface sediments, and thus microfossil records are scarce, rarely exceed the Holocene, and contain sparse information about past richness and taxonomic composition. These attributes make the Fram Strait an ideal study site to test the utility of sedimentary ancient DNA (sedaDNA) metabarcoding. Amplifying a short, partial rbcL marker from samples of sediment core MSM05/5-712-2 resulted in 95.7% of our sequences being assigned to diatoms across 18 different families, with 38.6% of them being resolved to species and 25.8% to genus level. Independent replicates show a high similarity of PCR products, especially in the oldest samples. Diatom sedaDNA richness is highest in the Late Weichselian and lowest in Mid- and Late Holocene samples. Taxonomic composition is dominated by cold-water and sea-ice-associated diatoms and suggests several reorganisations - after the Last Glacial Maximum, after the Younger Dryas, and after the Early and after the Mid-Holocene. Different sequences assigned to, amongst others, Chaetoceros socialis indicate the detectability of intra-specific diversity using sedaDNA. We detect no clear pattern between our diatom sedaDNA record and the previously published IP25 record of this core, although proportions of pennate diatoms increase with higher IP25 concentrations and proportions of Nitzschia cf. frigida exceeding 2% of the assemblage point towards past sea-ice presence.
We study populations of globally coupled noisy rotators (oscillators with inertia) allowing a nonequilibrium transition from a desynchronized state to a synchronous one (with the nonvanishing order parameter). The newly developed analytical approaches resulted in solutions describing the synchronous state with constant order parameter for weakly inertial rotators, including the case of zero inertia, when the model is reduced to the Kuramoto model of coupled noise oscillators. These approaches provide also analytical criteria distinguishing supercritical and subcritical transitions to the desynchronized state and indicate the universality of such transitions in rotator ensembles. All the obtained analytical results are confirmed by the numerical ones, both by direct simulations of the large ensembles and by solution of the associated Fokker-Planck equation. We also propose generalizations of the developed approaches for setups where different rotators parameters (natural frequencies, masses, noise intensities, strengths and phase shifts in coupling) are dispersed.
In this study, a phosphorus recovery product, struvite palygorskite (S-PAL), obtained from nutrient-rich wastewater by using MgO modified palygorskite was applied for copper remediation in aqueous solution and contaminated soil to achieve waste recycling. The effects of contact time, initial pH, initial Cu(II) concentration and reaction temperature on Cu(II) adsorption in aqueous solution were intensively testified. Pseudo-second-order model was able to properly describe Cu(II) adsorption kinetics by using palygorskite (PAL) and S-PAL, and S-PAL exhibited higher adsorption amount (106.27 mg/g) than PAL (8.46 mg/g) at pH of 4. Cu(II) adsorption on PAL and S-PAL could be well fitted by Freundlich isotherm and Langmuir isotherm, respectively. The calculated thermodynamic parameters indicated that Cu(II) adsorption onto PAL and S-PAL were spontaneous and endothermic. A 28-day soil incubation experiment was conducted to evaluate the effects of PAL and S-PAL with three different rates (1%, 5% and 10% w/w) on Cu immobilization in contaminated soil. In the immobilization test, Cu extracted by 0.01 mol/L CaCl2 after seven days incubation significantly decreased with increasing rate of PAL and S-PAL. BCR sequential extraction results showed the significant decrease of acid soluble Cu and a concomitant increase of the residual fraction of Cu after S-PAL and PAL addition. XRD patterns of soil samples after treatment by PAL and S-PAL showed the formation of Cu0.6Mg1.3Si2O6 and Cu-3.04(PO4)(2)OH0.08 center dot 2H(2)O, which indicated that silanol groups and phosphate exhibited affinity for Cu in the soil.
Polydopamine-based nanoreactors: synthesis and applications in bioscience and energy materials
(2020)
Polydopamine (PDA)-based nanoreactors have shown exceptional promise as multifunctional materials due to their nanoscale dimensions and sub-microliter volumes for reactions of different systems. Biocompatibility, abundance of active sites, and excellent photothermal conversion have facilitated their extensive use in bioscience and energy storage/conversion. This minireview summarizes recent advances in PDA-based nanoreactors, as applied to the abovementioned fields. We first highlight the design and synthesis of functional PDA-based nanoreactors with structural and compositional diversity. Special emphasis in bioscience has been given to drug/protein delivery, photothermal therapy, and antibacterial properties, while for energy-related applications, the focus is on electrochemical energy storage, catalysis, and solar energy harvesting. In addition, perspectives on pressing challenges and future research opportunities regarding PDA-based nanoreactors are discussed.
Cosmic-Ray neutron sensors are widely used to determine soil moisture on the hectare scale. Precise measurements, especially in the case of mobile application, demand for neutron detectors with high counting rates and high signal-to-noise ratios. For a long time Cosmic Ray Neutron Sensing (CRNS) instruments have relied on He-3 as an efficient neutron converter. Its ongoing scarcity demands for technological solutions using alternative converters, which are Li-6 and B-10. Recent developments lead to a modular neutron detector consisting of several B-10-lined proportional counter tubes, which feature high counting rates via its large surface area. The modularity allows for individual shieldings of different segments within the detector featuring the capability of gaining spectral information about the detected neutrons. This opens the possibility for active signal correction, especially useful when applied to mobile measurements, where the influence of constantly changing near-field to the overall signal should be corrected. Furthermore, the signal-to-noise ratio could be increased by combining pulse height and pulse length spectra to discriminate between neutrons and other environmental radiation. This novel detector therefore combines high-selective counting electronics with large-scale instrumentation technology.
Background:
COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking.
Objective:
The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points.
Methods:
We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions.
Results:
Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction.
Conclusions:
We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.
The Victoria microplate between the Eastern and Western Branches of the East African Rift System is one of the largest continental microplates on Earth. In striking contrast to its neighboring plates, Victoria rotates counterclockwise with respect to Nubia. The underlying cause of this distinctive rotation has remained elusive so far. Using 3D numerical models, we investigate the role of pre-existing lithospheric heterogeneities in continental microplate rotation. We find that Victoria's rotation is primarily controlled by the distribution of rheologically stronger zones that transmit the drag of the major plates to the microplate and of the mechanically weaker mobile belts surrounding Victoria that facilitate rotation. Our models reproduce Victoria's GPS-derived counterclockwise rotation as well as key complexities of the regional tectonic stress field. These results reconcile competing ideas on the opening of the rift system by highlighting differences in orientation of the far-field divergence, local extension, and the minimum horizontal stress. One of the largest continental microplates on Earth is situated in the center of the East African Rift System, and oddly, the Victoria microplate rotates counterclockwise with respect to the neighboring African tectonic plate. Here, the authors' modelling results suggest that Victoria microplate rotation is caused by edge-driven lithospheric processes related to the specific geometry of rheologically weak and strong regions.
Microplastics are a global environmental issue contaminating aquatic and terrestrial environments. They have been reported in atmospheric deposition, and indoor and outdoor air, raising concern for public health due to the potential for exposure. Moreover, the atmosphere presents a new vehicle for microplastics to enter the wider environment, yet our knowledge of the quantities, characteristics and pathways of airborne microplastics is sparse. Here we show microplastics in atmospheric deposition in a major population centre, central London. Microplastics were found in all samples, with deposition rates ranging from 575 to 1008 microplastics/m(2)/d. They were found in various shapes, of which fibrous microplastics accounted for the great majority (92%). Across all samples, 15 different petrochemical-based polymers were identified. Bivariate polar plots indicated dependency on wind, with different source areas for fibrous and non-fibrous airborne microplastics. This is the first evidence of airborne microplastics in London and confirms the need to include airborne pathways when consolidating microplastic impacts on the wider environment and human health.
A growing body of experimental syntactic research has revealed substantial variation in the magnitude of island effects, not only across languages but also across different grammatical constructions. Adopting a well-established experimental design, the present study examines island effects in Spanish using a speeded acceptability judgment task. To quantify variation across grammatical constructions, we tested extraction from four different types of structure (subjects, complex noun phrases, adjuncts and interrogative clauses). The results of Bayesian mixed effects modelling showed that the size of island effects varied between constructions, such that there was clear evidence of subject, adjunct and interrogative island effects, but not of complex noun phrase island effects. We also failed to find evidence that island effects were modulated by participants' working memory capacity as measured by an operation span task. To account for our results, we suggest that variability in island effects across constructions may be due to the interaction of syntactic, semantic-pragmatic and processing factors, which may affect island types differentially due to their idiosyncratic properties.
(40)A/Ar-39 step-heating of mica and amphibole megacrysts from hauyne-bearing olivine melilitite scoria/tephra from the Zelezna hurka yielded a 435 +/- 108 ka isotope correlation age for phlogopite and a more imprecise 1.55 Ma total gas age of the kaersutite megacryst. The amphibole megacrysts may constitute the first, and the younger phlogopite megacrysts the later phase of mafic, hydrous melilitic magma crystallization. It cannot be ruled out that the amphibole megacrysts are petrogenetically unrelated to tephra and phlogopite megacrysts and were derived from mantle xenoliths or disaggregated older, deep crustal pegmatites. This is in line both with the rarity of amphibole at Zelezna hurka and with the observed signs of magmatic resorption at the edges of amphibole crystals.
Initiation of subduction following the impingement of a hot buoyant mantle plume is one of the few scenarios that allow breaking the lithosphere and recycling a stagnant lid without requiring any preexisting weak zones. Here, we investigate factors controlling the number and shape of retreating subducting slabs formed by plume-lithosphere interaction. Using 3-D thermomechanical models we show that the deformation regime, which defines formation of single-slab or multi-slab subduction, depends on several parameters such as age of oceanic lithosphere, thickness of the crust and large-scale lithospheric extension rate. Our model results indicate that on present-day Earth multi-slab plume-induced subduction is initiated only if the oceanic lithosphere is relatively young (<30-40 Myr, but >10 Myr), and the crust has a typical thickness of 8 km. In turn, development of single-slab subduction is facilitated by older lithosphere and pre-imposed extensional stresses. In early Earth, plume-lithosphere interaction could have led to formation of either episodic short-lived circular subduction when the oceanic lithosphere was young or to multi-slab subduction when the lithosphere was old.
The Hartousov mofette system is a natural CO2 degassing site in the central Cheb Basin (Eger Rift, Central Europe). In early 2016 a 108 m deep core was obtained from this system to investigate the impact of ascending mantle-derived CO2 on indigenous deep microbial communities and their surrounding life habitat. During drilling, a CO2 blow out occurred at a depth of 78.5 meter below surface (mbs) suggesting a CO2 reservoir associated with a deep low-permeable CO2-saturated saline aquifer at the transition from Early Miocene terrestrial to lacustrine sediments. Past microbial communities were investigated by hopanoids and glycerol dialkyl glycerol tetraethers (GDGTs) reflecting the environmental conditions during the time of deposition rather than showing a signal of the current deep biosphere. The composition and distribution of the deep microbial community potentially stimulated by the upward migration of CO2 starting during Mid Pleistocene time was investigated by intact polar lipids (IPLs), quantitative polymerase chain reaction (qPCR), and deoxyribonucleic acid (DNA) analysis. The deep biosphere is characterized by microorganisms that are linked to the distribution and migration of the ascending CO2-saturated groundwater and the availability of organic matter instead of being linked to single lithological units of the investigated rock profile. Our findings revealed high relative abundances of common soil and water bacteria, in particular the facultative, anaerobic and potential iron-oxidizing Acidovorax and other members of the family Comamonadaceae across the whole recovered core. The results also highlighted the frequent detection of the putative sulfate-oxidizing and CO2-fixating genus Sulfuricurvum at certain depths. A set of new IPLs are suggested to be indicative for microorganisms associated to CO2 accumulation in the mofette system.
The attentional bias to negative information enables humans to quickly identify and to respond appropriately to potentially threatening situations. Because of its adaptive function, the enhanced sensitivity to negative information is expected to represent a universal trait, shared by all humans regardless of their cultural background. However, existing research focuses almost exclusively on humans from Western industrialized societies, who are not representative for the human species. Therefore, we compare humans from two distinct cultural contexts: adolescents and children from Germany, a Western industrialized society, and from the not equal Akhoe Hai parallel to om, semi-nomadic hunter-gatherers in Namibia. We predicted that both groups show an attentional bias toward negative facial expressions as compared to neutral or positive faces. We used eye-tracking to measure their fixation duration on facial expressions depicting different emotions, including negative (fear, anger), positive (happy), and neutral faces. Both Germans and the not equal Akhoe Hai parallel to om gazed longer at fearful faces, but shorter on angry faces, challenging the notion of a general bias toward negative emotions. For happy faces, fixation durations varied between the two groups, suggesting more flexibility in the response to positive emotions. Our findings emphasize the need for placing research on emotion perception into an evolutionary, cross-cultural comparative framework that considers the adaptive significance of specific emotions, rather than differentiating between positive and negative information, and enables systematic comparisons across participants from diverse cultural backgrounds.
User Experience (UX) describes the holistic experience of a user before, during, and after interaction with a platform, product, or service. UX adds value and attraction to their sole functionality and is therefore highly relevant for firms. The increased interest in UX has produced a vast amount of scholarly research since 1983. The research field is, therefore, complex and scattered. Conducting a bibliometric analysis, we aim at structuring the field quantitatively and rather abstractly. We employed citation analyses, co-citation analyses, and content analyses to evaluate productivity and impact of extant research. We suggest that future research should focus more on business and management related topics.
According to established understanding, deep-water formation in the North Atlantic and Southern Ocean keeps the deep ocean cold, counter-acting the downward mixing of heat from the warmer surface waters in the bulk of the world ocean. Therefore, periods of strong Atlantic meridional overturning circulation (AMOC) are expected to coincide with cooling of the deep ocean and warming of the surface waters. It has recently been proposed that this relation may have reversed due to global warming, and that during the past decades a strong AMOC coincides with warming of the deep ocean and relative cooling of the surface, by transporting increasingly warmer waters downward. Here we present multiple lines of evidence, including a statistical evaluation of the observed global mean temperature, ocean heat content, and different AMOC proxies, that lead to the opposite conclusion: even during the current ongoing global temperature rise a strong AMOC warms the surface. The observed weakening of the AMOC has therefore delayed global surface warming rather than enhancing it.
Social Media Abstract:
The overturning circulation in the Atlantic Ocean has weakened in response to global warming, as predicted by climate models. Since it plays an important role in transporting heat, nutrients and carbon, a slowdown will affect global climate processes and the global mean temperature. Scientists have questioned whether this slowdown has worked to cool or warm global surface temperatures. This study analyses the overturning strength and global mean temperature evolution of the past decades and shows that a slowdown acts to reduce the global mean temperature. This is because a slower overturning means less water sinks into the deep ocean in the subpolar North Atlantic. As the surface waters are cold there, the sinking normally cools the deep ocean and thereby indirectly warms the surface, thus less sinking implies less surface warming and has a cooling effect. For the foreseeable future, this means that the slowing of the overturning will likely continue to slightly reduce the effect of the general warming due to increasing greenhouse gas concentrations.
Drainage divide networks
(2020)
Drainage divides are organized into tree-like networks that may record information about drainage divide mobility. However, views diverge about how to best assess divide mobility. Here, we apply a new approach of automatically extracting and ordering drainage divide networks from digital elevation models to results from landscape evolution model experiments. We compared landscapes perturbed by strike-slip faulting and spatiotemporal variations in erodibility to a reference model to assess which topographic metrics (hillslope relief, flow distance, and chi) are diagnostic of divide mobility. Results show that divide segments that are a minimum distance of similar to 5 km from river confluences strive to attain constant values of hillslope relief and flow distance to the nearest stream. Disruptions of such patterns can be related to mobile divides that are lower than stable divides, closer to streams, and often asymmetric in shape. In general, we observe that drainage divides high up in the network, i.e., at great distances from river confluences, are more susceptible to disruptions than divides closer to these confluences and are thus more likely to record disturbance for a longer time period. We found that across-divide differences in hillslope relief proved more useful for assessing divide migration than other tested metrics. However, even stable drainage divide networks exhibit across-divide differences in any of the studied topographic metrics. Finally, we propose a new metric to quantify the connectivity of divide junctions.
Wire Arc Additive Manufacturing (WAAM) features high deposition rates and, thus, allows production of large components that are relevant for aerospace applications. However, a lot of aerospace parts are currently produced by forging or machining alone to ensure fast production and to obtain good mechanical properties; the use of these conventional process routes causes high tooling and material costs. A hybrid approach (a combination of forging and WAAM) allows making production more efficient. In this fashion, further structural or functional features can be built in any direction without using additional tools for every part. By using a combination of forging basic geometries with one tool set and adding the functional features by means of WAAM, the tool costs and material waste can be reduced compared to either completely forged or machined parts. One of the factors influencing the structural integrity of additively manufactured parts are (high) residual stresses, generated during the build process. In this study, the triaxial residual stress profiles in a hybrid WAAM part are reported, as determined by neutron diffraction. The analysis is complemented by microstructural investigations, showing a gradient of microstructure (shape and size of grains) along the part height. The highest residual stresses were found in the transition zone (between WAAM and forged part). The total stress range showed to be lower than expected for WAAM components. This could be explained by the thermal history of the component.
Maytenus disticha (Hook F.), belonging to the Celastraceae family, is an evergreen shrub, native of the central southern mountains of Chile. Previous studies demonstrated that the total extract of M. disticha (MD) has an acetylcholinesterase inhibitory activity along with growth regulatory and insecticidal activities. beta-Dihydroagarofurans sesquiterpenes are the most active components in the plant. However, its activity in cancer has not been analyzed yet. Here, we demonstrate that MD has a cytotoxic activity on breast (MCF-7), lung (PC9), and prostate (C4-2B) human cancer cells with an IC50 (mu g/mL) of 40, 4.7, and 5 mu g/mL, respectively, an increasing Bax/Bcl2 ratio, and inducing a mitochondrial membrane depolarization. The beta-dihydroagarofuran-type sesquiterpene (MD-6), dihydromyricetin (MD-9), and dihydromyricetin-3-O-beta-glucoside (MD-10) were isolated as the major compounds from MD extracts. From these compounds, only MD-6 showed cytotoxic activity on MCF-7, PC9, and C4-2B with an IC50 of 31.02, 17.58, and 42.19 mu M, respectively. Furthermore, the MD-6 increases cell ROS generation, and MD and MD-6 induce a mitochondrial superoxide generation and apoptosis on MCF-7, PC9, and C4-2B, which suggests that the cytotoxic effect of MD is mediated in part by the beta-dihydroagarofuran-type that induces apoptosis by a mitochondrial dysfunction.
It is unclear to what extent teachers can accurately assess the social inclusion of their students with and without SEN. The study aims to shed light on these desiderata. Students (N = 1.644) with SEN (learning, behavior, and language problems) and without SEN and their teachers (N = 79) participated in the study. Sociometric peer nominations, students' self-perceived social inclusion, and teachers' assessments regarding students' social inclusion and self-perceived social inclusion were administered. The results suggest that teachers are moderately accurate in identifying social acceptance and social rejection, while accuracy is low when assessing students' self-perceived social inclusion. That said, rating accuracy varied strongly between teachers, ranging from no agreement to a perfect concordance. Teachers seem to be more accurate in estimating the social acceptance of students with learning problems. The results emphasize the importance of differentiating between various social inclusion criteria (i.e., students' self-report vs. peer nominations) and accounting for inter-individual differences in teachers' rating accuracy.
This paper discusses the fitting of linear state space models to given multivariate time series in the presence of constraints imposed on the four main parameter matrices of these models. Constraints arise partly from the assumption that the models have a block-diagonal structure, with each block corresponding to an ARMA process, that allows the reconstruction of independent source components from linear mixtures, and partly from the need to keep models identifiable. The first stage of parameter fitting is performed by the expectation maximisation (EM) algorithm. Due to the identifiability constraint, a subset of the diagonal elements of the dynamical noise covariance matrix needs to be constrained to fixed values (usually unity). For this kind of constraints, so far, no closed-form update rules were available. We present new update rules for this situation, both for updating the dynamical noise covariance matrix directly and for updating a matrix square-root of this matrix. The practical applicability of the proposed algorithm is demonstrated by a low-dimensional simulation example. The behaviour of the EM algorithm, as observed in this example, illustrates the well-known fact that in practical applications, the EM algorithm should be combined with a different algorithm for numerical optimisation, such as a quasi-Newton algorithm.
CytoSeg 2.0
(2020)
Motivation:
Actin filaments (AFs) are dynamic structures that substantially change their organization over time. The dynamic behavior and the relatively low signal-to-noise ratio during live-cell imaging have rendered the quantification of the actin organization a difficult task.
Results:
We developed an automated image-based framework that extracts AFs from fluorescence microscopy images and represents them as networks, which are automatically analyzed to identify and compare biologically relevant features. Although the source code is freely available, we have now implemented the framework into a graphical user interface that can be installed as a Fiji plugin, thus enabling easy access by the research community.
Background
Generalized weakness and fatigue are underexplored symptoms in emergency medicine. Triage tools often underestimate patients presenting to the emergency department (ED) with these nonspecific symptoms (Nemec et al., 2010). At the same time, physicians' disease severity rating (DSR) on a scale from 0 (not sick at all) to 10 (extremely sick) predicts key outcomes in ED patients (Beglinger et al., 2015; Rohacek et al., 2015). Our goals were (1) to characterize ED patients with weakness and/or fatigue (W|F); to explore (2) to what extent physicians' DSR at triage can predict five key outcomes in ED patients with W|F; (3) how well DSR performs relative to two commonly used benchmark methods, the Emergency Severity Index (ESI) and the Charlson Comorbidity Index (CCI); (4) to what extent DSR provides predictive information beyond ESI, CCI, or their linear combination, i.e., whether ESI and CCI should be used alone or in combination with DSR; and (5) to what extent ESI, CCI, or their linear combination provide predictive information beyond DSR alone, i.e., whether DSR should be used alone or in combination with ESI and / or CCI.
Methods
Prospective observational study between 2013-2015 (analysis in 2018-2020, study team blinded to hypothesis) conducted at a single center. We study an all-comer cohort of 3,960 patients (48% female patients, median age = 51 years, 94% completed 1-year follow-up). We looked at two primary outcomes (acute morbidity (Bingisser et al., 2017; Weigel et al., 2017) and all-cause 1- year mortality) and three secondary outcomes (in-hospital mortality, hospitalization and transfer to ICU). We assessed the predictive power (i.e., resolution, measured as the Area under the ROC Curve, AUC) of the scores and, using logistic regression, their linear combinations.
Findings
Compared to patients without W|F (n = 3,227), patients with W|F (n = 733) showed higher prevalences for all five outcomes, reported more symptoms across both genders, and received higher DSRs (median = 4; interquartile range (IQR) = 3-6 vs. median = 3; IQR = 2-5). DSR predicted all five outcomes well above chance (i.e., AUCs > similar to 0.70), similarly well for both patients with and without W|F, and as good as or better than ESI and CCI in patients with and without W|F (except for 1-year mortality where CCI performs better). For acute morbidity, hospitalization, and transfer to ICU there is clear evidence that adding DSR to ESI and/or CCI improves predictions for both patient groups; for 1-year mortality and in-hospital mortality this holds for most, but not all comparisons. Adding ESI and/or CCI to DSR generally did not improve performance or even decreased it.
Conclusions
The use of physicians' disease severity rating has never been investigated in patients with generalized weakness and fatigue. We show that physicians' prediction of acute morbidity, mortality, hospitalization, and transfer to ICU through their DSR is also accurate in these patients. Across all patients, DSR is less predictive of acute morbidity for female than male patients, however. Future research should investigate how emergency physicians judge their patients' clinical state at triage and how this can be improved and used in simple decision aids.
Classical option pricing schemes assume that the value of a financial asset follows a geometric Brownian motion (GBM). However, a growing body of studies suggest that a simple GBM trajectory is not an adequate representation for asset dynamics, due to irregularities found when comparing its properties with empirical distributions. As a solution, we investigate a generalisation of GBM where the introduction of a memory kernel critically determines the behaviour of the stochastic process. We find the general expressions for the moments, log-moments, and the expectation of the periodic log returns, and then obtain the corresponding probability density functions using the subordination approach. Particularly, we consider subdiffusive GBM (sGBM), tempered sGBM, a mix of GBM and sGBM, and a mix of sGBMs. We utilise the resulting generalised GBM (gGBM) in order to examine the empirical performance of a selected group of kernels in the pricing of European call options. Our results indicate that the performance of a kernel ultimately depends on the maturity of the option and its moneyness.
Real time monitoring of oxygen uptake of hepatocytes in a microreactor using optical microsensors
(2020)
Most in vitro test systems for the assessment of toxicity are based on endpoint measurements and cannot contribute much to the establishment of mechanistic models, which are crucially important for further progress in this field. Hence, in recent years, much effort has been put into the development of methods that generate kinetic data. Real time measurements of the metabolic activity of cells based on the use of oxygen sensitive microsensor beads have been shown to provide access to the mode of action of compounds in hepatocytes. However, for fully exploiting this approach a detailed knowledge of the microenvironment of the cells is required. In this work, we investigate the cellular behaviour of three types of hepatocytes, HepG2 cells, HepG2-3A4 cells and primary mouse hepatocytes, towards their exposure to acetaminophen when the availability of oxygen for the cell is systematically varied. We show that the relative emergence of two modes of action, one NAPQI dependent and the other one transient and NAPQI independent, scale with expression level of CYP3A4. The transient cellular response associated to mitochondrial respiration is used to characterise the influence of the initial oxygen concentration in the wells before exposure to acetaminophen on the cell behaviour. A simple model is presented to describe the behaviour of the cells in this scenario. It demonstrates the level of control over the role of oxygen supply in these experiments. This is crucial for establishing this approach into a reliable and powerful method for the assessment of toxicity.
In a changing world, phytoplankton communities face a large variety of challenges including altered light regimes. These alterations are caused by more pronounced stratification due to rising temperatures, enhanced eutrophication, and browning of lakes. Community responses toward these effects can emerge as alterations in physiology, biomass, biochemical composition, or diversity. In this study, we addressed the combined effects of changes in light and nutrient conditions on community responses. In particular, we investigated how light intensity and variability under two nutrient conditions influence (1) fast responses such as adjustments in photosynthesis, (2) intermediate responses such as pigment adaptation and (3) slow responses such as changes in community biomass and species composition. Therefore, we exposed communities consisting of five phytoplankton species belonging to different taxonomic groups to two constant and two variable light intensity treatments combined with two levels of phosphorus supply. The tested phytoplankton communities exhibited increased fast reactions of photosynthetic processes to light variability and light intensity. The adjustment of their light harvesting mechanisms via community pigment composition was not affected by light intensity, variability, or nutrient supply. However, pigment specific effects of light intensity, light variability, and nutrient supply on the proportion of the respective pigments were detected. Biomass was positively affected by higher light intensity and nutrient concentrations while the direction of the effect of variability was modulated by light intensity. Light variability had a negative impact on biomass at low, but a positive impact at high light intensity. The effects on community composition were species specific. Generally, the proportion of green algae was higher under high light intensity, whereas the cyanobacterium performed better under low light conditions. In addition to that, the diatom and the cryptophyte performed better with high nutrient supply while the green algae as well as the cyanobacterium performed better at low nutrient conditions. This shows that light intensity, light variability, and nutrient supply interactively affect communities. Furthermore, the responses are highly species and pigment specific, thus to clarify the effects of climate change a deeper understanding of the effects of light variability and species interactions within communities is important.
Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM)
(2020)
Simulations of the glacial-interglacial history of the Antarctic Ice Sheet provide insights into dynamic threshold behavior and estimates of the ice sheet's contributions to global sea-level changes for the past, present and future. However, boundary conditions are weakly constrained, in particular at the interface of the ice sheet and the bedrock. Also climatic forcing covering the last glacial cycles is uncertain, as it is based on sparse proxy data. <br /> We use the Parallel Ice Sheet Model (PISM) to investigate the dynamic effects of different choices of input data, e.g., for modern basal heat flux or reconstructions of past changes of sea level and surface temperature. As computational resources are limited, glacial-cycle simulations are performed using a comparably coarse model grid of 16 km and various parameterizations, e.g., for basal sliding, iceberg calving, or for past variations in precipitation and ocean temperatures. In this study we evaluate the model's transient sensitivity to corresponding parameter choices and to different boundary conditions over the last two glacial cycles and provide estimates of involved uncertainties. We also discuss isolated and combined effects of climate and sea-level forcing. Hence, this study serves as a "cookbook" for the growing community of PISM users and paleo-ice sheet modelers in general. <br /> For each of the different model uncertainties with regard to climatic forcing, ice and Earth dynamics, and basal processes, we select one representative model parameter that captures relevant uncertainties and motivates corresponding parameter ranges that bound the observed ice volume at present. The four selected parameters are systematically varied in a parameter ensemble analysis, which is described in a companion paper.
Geochemical processes change the microstructure of rocks and thereby affect their physical behaviour at the macro scale. A micro-computer tomography (micro-CT) scan of a typical reservoir sandstone is used to numerically examine the impact of three spatial alteration patterns on pore morphology, permeability and elastic moduli by correlating precipitation with the local flow velocity magnitude. The results demonstrate that the location of mineral growth strongly affects the permeability decrease with variations by up to four orders in magnitude. Precipitation in regions of high flow velocities is characterised by a predominant clogging of pore throats and a drastic permeability reduction, which can be roughly described by the power law relation with an exponent of 20. A continuous alteration of the pore structure by uniform mineral growth reduces the permeability comparable to the power law with an exponent of four or the Kozeny-Carman relation. Preferential precipitation in regions of low flow velocities predominantly affects smaller throats and pores with a minor impact on the flow regime, where the permeability decrease is considerably below that calculated by the power law with an exponent of two. Despite their complete distinctive impact on hydraulics, the spatial precipitation patterns only slightly affect the increase in elastic rock properties with differences by up to 6.3% between the investigated scenarios. Hence, an adequate characterisation of the spatial precipitation pattern is crucial to quantify changes in hydraulic rock properties, whereas the present study shows that its impact on elastic rock parameters is limited. The calculated relations between porosity and permeability, as well as elastic moduli can be applied for upscaling micro-scale findings to reservoir-scale models to improve their predictive capabilities, what is of paramount importance for a sustainable utilisation of the geological subsurface.
Fractures efficiently affect fluid flow in geological formations, and thereby determine mass and energy transport in reservoirs, which are not least exploited for economic resources. In this context, their response to mechanical and thermal changes, as well as fluid-rock interactions, is of paramount importance. In this study, a two-stage flow-through experiment was conducted on a pure quartz sandstone core of low matrix permeability, containing one single macroscopic tensile fracture. In the first short-term stage, the effects of mechanical and hydraulic aperture on pressure and temperature cycles were investigated. The purpose of the subsequent intermittent-flow long-term (140 days) stage was to constrain the evolution of the geometrical and hydraulic fracture properties resulting from pressure solution. Deionized water was used as the pore fluid, and permeability, as well as the effluent Si concentrations, were systematically measured. Overall, hydraulic aperture was shown to be significantly less affected by pressure, temperature and time, in comparison to mechanical aperture. During the long-term part of the experiment at 140 degrees C, the effluent Si concentrations likely reached a chemical equilibrium state within less than 8 days of stagnant flow, and exceeded the corresponding hydrostatic quartz solubility at this temperature. This implies that the pressure solution was active at the contacting fracture asperities, both at 140 degrees C and after cooling to 33 degrees C. The higher temperature yielded a higher dissolution rate and, consequently, a faster attainment of chemical equilibrium within the contact fluid. X-ray mu CT observations evidenced a noticeable increase in fracture contact area ratio, which, in combination with theoretical considerations, implies a significant decrease in mechanical aperture. In contrast, the sample permeability, and thus the hydraulic fracture aperture, virtually did not vary. In conclusion, pressure solution-induced fracture aperture changes are affected by the degree of time-dependent variations in pore fluid composition. In contrast to the present case of a quasi-closed system with mostly stagnant flow, in an open system with continuous once-through fluid flow, the activity of the pressure solution may be amplified due to the persistent fluid-chemical nonequilibrium state, thus possibly enhancing aperture and fracture permeability changes.
Background:
Several standards have been developed to assess methodological quality of systematic reviews (SR). One widely used tool is the AMSTAR. A recent update -AMSTAR 2 -is a 16 item evaluation tool that enables a detailed assessment of SR that include randomised (RCT) or non-randomised studies (NRS) of healthcare interventions.
Methods:
A cross-sectional study of SR on pharmacological or psychological interventions in major depression in adults was conducted. SR published during 2012-2017 were sampled from MEDLINE, EMBASE and the Cochrane Database of SR. Methodological quality was assessed using AMSTAR 2. Potential predictive factors associated with quality were examined.
Results:
In rating overall confidence in the results of 60 SR four reviews were rated "high", two were "moderate", one was "low" and 53 were "critically low". The mean AMSTAR 2 percentage score was 45.3% (standard deviation 22.6%) in a wide range from 7.1% to 93.8%. Predictors of higher quality were: type of review (higher quality in Cochrane Reviews), SR including only randomized trials and higher journal impact factor.
Limitations:
AMSTAR 2 is not intended to be used for the generation of a percentage score.
Conclusions:
According to AMSTAR 2 the overall methodological quality of SR on the treatment of adult major depression needs improvement. Although there is a high need for summarized information in the field of mental health, this work demonstrates the need to critically assess SR before using their findings. Better adherence to established reporting guidelines for SR is needed.
Relative pollen productivity (RPP) estimates are fractionate values, often in relation to Poaceae, that allow vegetation cover to be estimated from pollen counts with the help of models. RPP estimates are especially used in the scientific community in Europe and China, with a few studies in North America. Here we present a comprehensive compilation of available northern hemispheric RPP studies and their results arising from 51 publications with 60 sites and 131 taxa. This compilation allows scientists to identify data gaps in need of further RPP analyses but can also aid them in finding an RPP set for their study region. We also present a taxonomically harmonised, unified RPP dataset for the Northern Hemisphere and subsets for North America (including Greenland), Europe (including arctic Russia), and China, which we generated from the available studies. The unified dataset gives the mean RPP for 55 harmonised taxa as well as fall speeds, which are necessary to reconstruct vegetation cover from pollen counts and RPP values. Data are openly available at https://doi.org/10.1594/PANGAEA.922661 (Wieczorek and Herzschuh, 2020).
Rodin has it!
(2020)
We report a new discovery on the role of hands in guiding attention, using the classic Stroop effect as our assay. We show that the Stroop effect diminishes, hence selective attention improves, when observers hold their chin, emulating Rodin's famous sculpture, "The Thinker." In two experiments we show that the Rodin posture improves the selectivity of attention as efficiently as holding the hands nearby the visual stimulus (the near-hands effect). Because spatial proximity to the displayed stimulus is neither present nor intended, the presence of the Rodin effect implies that attentional prioritization by the hands is not limited to the space between the hands.
Induced point mutations are important genetic resources for their ability to create hypo- and hypermorphic alleles that are useful for understanding gene functions and breeding. However, such mutant populations have only been developed for a few temperate maize varieties, mainly B73 and W22, yet no tropical maize inbred lines have been mutagenized and made available to the public to date. We developed a novel Ethyl Methanesulfonate (EMS) induced mutation resource in maize comprising 2050 independent M2 mutant families in the elite tropical maize inbred ML10. By phenotypic screening, we showed that this population is of comparable quality with other mutagenized populations in maize. To illustrate the usefulness of this population for gene discovery, we performed rapid mapping-by-sequencing to clone a fasciated-ear mutant and identify a causal promoter deletion in ZmCLE7 (CLE7). Our mapping procedure does not require crossing to an unrelated parent, thus is suitable for mapping subtle traits and ones affected by heterosis. This first EMS population in tropical maize is expected to be very useful for the maize research community. Also, the EMS mutagenesis and rapid mapping-by-sequencing pipeline described here illustrate the power of performing forward genetics in diverse maize germplasms of choice, which can lead to novel gene discovery due to divergent genetic backgrounds.
Floodplains have been degraded in Central Europe for centuries, resulting in less dynamic and less diverse ecosystems than in the past. They provide essential ecosystem services like nutrient retention to improve overall water quality and thus fulfill naturally what EU legislation demands, but this service is impaired by reduced connectivity patterns. Along the second-longest river in Europe, the Danube, restoration measures have been carried out and are planned for the near future in the Austrian Danube Floodplain National Park in accordance with navigation purposes. We investigated nutrient retention capacity in seven currently differently connected side arms and the effects of proposed restoration measures using two complementary modeling approaches. We modeled nutrient retention capacity in two scenarios considering different hydrological conditions, as well as the consequences of planned restoration measures for side arm connectivity. With existing monitoring data on hydrology, nitrate, and total phosphorus concentrations for three side arms, we applied a statistical model and compared these results to a semi-empirical retention model. The latter was originally developed for larger scales, based on transferable causalities of retention processes and set up for this floodplain with publicly available data. Both model outcomes are in a comparable range for NO3-N (77-198 kg ha(-1)yr(-1)) and TP (1.4-5.7 kg ha(-1)yr(-1)) retention and agree in calculating higher retention in floodplains, where reconnection allows more frequent inundation events. However, the differences in the model results are significant for specific aspects especially during high flows, where the semi-empirical model complements the statistical model. On the other hand, the statistical model complements the semi-empirical model when taking into account nutrient retention at times of no connection between the remaining water bodies left in the floodplain. Overall, both models show clearly that nutrient retention in the Danube floodplains can be enhanced by restoring lateral hydrological reconnection and, for all planned measures, a positive effect on the overall water quality of the Danube River is expected. Still, a frequently hydrologically connected stretch of national park is insufficient to improve the water quality of the whole Upper Danube, and more functional floodplains are required.
Three-component molecular brushes with a polyimide backbone and amphiphilic block copolymer side chains with different contents of the "inner" hydrophilic (poly(methacrylic acid)) and "outer" hydrophobic (poly(methyl methacrylate)) blocks were synthesized and characterized by molecular hydrodynamics and optics methods in solutions of chloroform, dimethylformamide, tetrahydrofuran and ethanol. The peculiarity of the studied polymers is the amphiphilic structure of the grafted chains. The molar masses of the molecular brushes were determined by static and dynamic light scattering in chloroform in which polymers form molecularly disperse solutions. Spontaneous self-assembly of macromolecules was detected in dimethylformamide, tetrahydrofuran and ethanol. The aggregates size depended on the thermodynamic quality of the solvent as well as on the macromolecular architectural parameters. In dimethylformamide and tetrahydrofuran, the distribution of hydrodynamic radii of aggregates was bimodal, while in ethanol, it was unimodal. Moreover, in ethanol, an increase in the poly(methyl methacrylate) content caused a decrease in the hydrodynamic radius of aggregates. A significant difference in the nature of the blocks included in the brushes determines the selectivity of the used solvents, since their thermodynamic quality with respect to the blocks is different. The macromolecules of the studied graft copolymers tend to self-organization in selective solvents with formation of a core-shell structure with an insoluble solvophobic core surrounded by the solvophilic shell of side chains.
Field-based sports require athletes to run sub-maximally over significant distances, often while contending with dynamic perturbations to preferred coordination patterns. The ability to adapt movement to maintain performance under such perturbations appears to be trainable through exposure to task variability, which encourages movement variability. The aim of the present study was to investigate the extent to which various wearable resistance loading magnitudes alter coordination and induce movement variability during running. To investigate this, 14 participants (three female and 11 male) performed 10 sub-maximal velocity shuttle runs with either no weight, 1%, 3%, or 5% of body weight attached to the lower limbs. Sagittal plane lower limb joint kinematics from one complete stride cycle in each run were assessed using functional data analysis techniques, both across the participant group and within-individuals. At the group-level, decreases in ankle plantarflexion following toe-off were evident in the 3% and 5% conditions, while increased knee flexion occurred during weight acceptance in the 5% condition compared with unloaded running. At the individual-level, between-run joint angle profiles varied, with six participants exhibiting increased joint angle variability in one or more loading conditions compared with unloaded running. Loading of 5% decreased between-run ankle joint variability among two individuals, likely in accordance with the need to manage increased system load or the novelty of the task. In terms of joint coordination, the most considerable alterations to coordination occurred in the 5% loading condition at the hip-knee joint pair, however, only a minority of participants exhibited this tendency. Coaches should prescribe wearable resistance individually to perturb preferred coordination patterns and encourage movement variability without loading to the extent that movement options become limited.
LiCSBAS
(2020)
For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large amount of associated data is challenging, especially over wide areas. To help address this challenge, we have developed LiCSBAS, an open-source SAR interferometry (InSAR) time series analysis package that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). LiCSBAS utilizes freely available LiCSAR products, and users can save processing time and disk space while obtaining the results of InSAR time series analysis. In the LiCSBAS processing scheme, interferograms with many unwrapping errors are automatically identified by loop closure and removed. Reliable time series and velocities are derived with the aid of masking using several noise indices. The easy implementation of atmospheric corrections to reduce noise is achieved with the Generic Atmospheric Correction Online Service for InSAR (GACOS). Using case studies in southern Tohoku and the Echigo Plain, Japan, we demonstrate that LiCSBAS applied to LiCSAR products can detect both large-scale (>100 km) and localized (similar to km) relative displacements with an accuracy of <1 cm/epoch and similar to 2 mm/yr. We detect displacements with different temporal characteristics, including linear, periodic, and episodic, in Niigata, Ojiya, and Sanjo City, respectively. LiCSBAS and LiCSAR products facilitate greater exploitation of globally available and abundant SAR datasets and enhance their applications for scientific research and societal benefit.
Core stability exercises are regular part of exercise programs for asymptomatic individuals across ages. The purpose of this study was to examine deep abdominal and multifidus muscle thickness in children and adults and to determine reliability of the rehabilitative ultrasound (RUSI) imaging. Transversus abdominis and lumbar multifidus thickness at rest and during core stability exercise were examined in pre-pubertal children (N = 23), adolescents (N = 20), young adults (N = 21) and middle-aged adults (N = 22). Thirty-nine participants were re-tested one week after to establish reliability. Muscle thickness at rest was lower in children and adolescents compared with young and middle-aged adults (p < 0.008). Young adults displayed the highest relative transversus abdominis thickness upon contraction (p < 0.008). Lumbar multfidus contraction thickness was greater in young-adults than middle-aged adults and prepubertal children (p < 0.008), but it was similar between young-adults and adolescents (p > 0.008). Reliability was high for both muscles (ICC3,3 = 0.76 - 0.99). The age-related differences in muscle thickness indicate that core stability exercises may be beneficial for children and middle-aged adults.
The current trends of crop yield improvements are not expected to meet the projected rise in demand. Genomic selection uses molecular markers and machine learning to identify superior genotypes with improved traits, such as growth. Plant growth directly depends on rates of metabolic reactions which transform nutrients into the building blocks of biomass. Here, we predict growth of Arabidopsis thaliana accessions by employing genomic prediction of reaction rates estimated from accession-specific metabolic models. We demonstrate that, comparing to classical genomic selection on the available data sets for 67 accessions, our approach improves the prediction accuracy for growth within and across nitrogen environments by 32.6% and 51.4%, respectively, and from optimal nitrogen to low carbon environment by 50.4%. Therefore, integration of molecular markers into metabolic models offers an approach to predict traits directly related to metabolism, and its usefulness in breeding can be examined by gathering matching datasets in crops. An increase in genomic selection (GS) accuracy can accelerate genetic gain by shortening the breeding cycles. Here, the authors introduce a network-based GS method that uses metabolic models and improves the prediction accuracy of Arabidopsis growth within and across environments.
Flood risk assessments are typically based on scenarios which assume homogeneous return periods of flood peaks throughout the catchment. This assumption is unrealistic for real flood events and may bias risk estimates for specific return periods. We investigate how three assumptions about the spatial dependence affect risk estimates: (i) spatially homogeneous scenarios (complete dependence), (ii) spatially heterogeneous scenarios (modelled dependence) and (iii) spatially heterogeneous but uncorrelated scenarios (complete independence). To this end, the model chain RFM (regional flood model) is applied to the Elbe catchment in Germany, accounting for the spatio-temporal dynamics of all flood generation processes, from the rainfall through catchment and river system processes to damage mechanisms. Different assumptions about the spatial dependence do not influence the expected annual damage (EAD); however, they bias the risk curve, i.e. the cumulative distribution function of damage. The widespread assumption of complete dependence strongly overestimates flood damage of the order of 100% for return periods larger than approximately 200 years. On the other hand, for small and medium floods with return periods smaller than approximately 50 years, damage is underestimated. The overestimation aggravates when risk is estimated for larger areas. This study demonstrates the importance of representing the spatial dependence of flood peaks and damage for risk assessments.
We study properties of magnetohydrodynamic (MHD) eigenmodes by decomposing the data of MHD simulations into linear MHD modes-namely, the Alfven, slow magnetosonic, and fast magnetosonic modes. We drive turbulence with a mixture of solenoidal and compressive driving while varying the Alfven Mach number (M-A), plasma beta, and the sonic Mach number from subsonic to transsonic. We find that the proportion of fast and slow modes in the mode mixture increases with increasing compressive forcing. This proportion of the magnetosonic modes can also become the dominant fraction in the mode mixture. The anisotropy of the modes is analyzed by means of their structure functions. The Alfven-mode anisotropy is consistent with the Goldreich-Sridhar theory. We find a transition from weak to strong Alfvenic turbulence as we go from low to high M-A. The slow-mode properties are similar to the Alfven mode. On the other hand, the isotropic nature of fast modes is verified in the cases where the fast mode is a significant fraction of the mode mixture. The fast-mode behavior does not show any transition in going from low to high M-A. We find indications that there is some interaction between the different modes, and the properties of the dominant mode can affect the properties of the weaker modes. This work identifies the conditions under which magnetosonic modes can be a major fraction of turbulent astrophysical plasmas, including the regime of weak turbulence. Important astrophysical implications for cosmic-ray transport and magnetic reconnection are discussed.
Recent research has linked sphingolipid (SL) metabolism with cystic fibrosis transmembrane conductance regulator (CFTR) activity, affecting bioactive lipid mediator sphingosine-1-phosphate (S1P). We hypothesize that loss of CFTR function in cystic fibrosis (CF) patients influenced plasma S1P levels. Total and unbound plasma S1P levels were measured in 20 lung-transplanted adult CF patients and 20 healthy controls by mass spectrometry and enzyme-linked immunosorbent assay (ELISA). S1P levels were correlated with CFTR genotype, routine laboratory parameters, lung function and pathogen colonization, and clinical symptoms. Compared to controls, CF patients showed lower unbound plasma S1P, whereas total S1P levels did not differ. A positive correlation of total and unbound S1P levels was found in healthy controls, but not in CF patients. Higher unbound S1P levels were measured in Delta F508-homozygous compared to Delta F508-heterozygous CF patients (p = 0.038), accompanied by higher levels of HDL in Delta F508-heterozygous patients. Gastrointestinal symptoms were more common in Delta F508 heterozygotes compared to Delta F508 homozygotes. This is the first clinical study linking plasma S1P levels with CFTR function and clinical presentation in adult CF patients. Given the emerging role of immunonutrition in CF, our study might pave the way for using S1P as a novel biomarker and nutritional target in CF.
Background
The Arabidopsis CONSTITUTIVE EXPRESSER of PATHOGENESIS-RELATED GENES 5 (CPR5) has recently been shown to play a role in gating as part of the nuclear pore complex (NPC). Mutations in CPR5 cause multiple defects, including aberrant trichomes, reduced ploidy levels, reduced growth and enhanced resistance to bacterial and fungal pathogens. The pleiotropic nature of cpr5 mutations implicates that the CPR5 protein affects multiple pathways. However, little is known about the structural features that allow CPR5 to affect the different pathways.
Results
Our in silico studies suggest that in addition to three clusters of putative nuclear localization signals and four or five transmembrane domains, CPR5 contains two putative alternative translation start sites. To test the role of the methionine-encoding nucleotides implicated in those sites, metCPR5 cDNAs, in which the relevant nucleotides were changed to encode glutamine, were fused to the CPR5 native promoter and the constructs transformed to cpr5-2 plants to complement cpr5-compromised phenotypes. The control and metCPR5 constructs were able to complement all cpr5 phenotypes, although the extent of complementation depended on the specific complementing plant lines. Remarkably, plants transformed with metCPR5 constructs showed larger leaves and displayed reduced resistance when challenged to Pseudomonas syringae pv Pst DC3000, as compared to control plants. Thus, the methionine-encoding nucleotides regulate growth and resistance. We propose that structural features of the CPR5 N-terminus are implicated in selective gating of proteins involved in regulating the balance between growth and resistance.
Conclusion
Plants need to carefully balance the amount of resources used for growth and resistance. The Arabidopsis CPR5 protein regulates plant growth and immunity. Here we show that N-terminal features of CPR5 are involved in the regulation of the balance between growth and resistance. These findings may benefit efforts to improve plant yield, while maintaining optimal levels of disease resistance.
The synthesis of new phenanthr[9,10-e][1,3]oxazines was achieved by the direct coupling of 9-phenanthrol with cyclic imines in the modified aza-Friedel-Crafts reaction followed by the ring closure of the resulting bifunctional aminophenanthrols with formaldehyde. Aminophenanthrol-type Mannich bases were synthesised and transformed to phenanthr[9,10-e][1,3]oxazines via [4 + 2] cycloaddition. Detailed NMR structural analyses of the new polyheterocycles as well as conformational studies including Density Functional Theory (DFT) modelling were performed. The relative stability of ortho-quinone methides (o-QMs) was calculated, the geometries obtained were compared with the experimentally determined NMR structures, and thereby, the regioselectivity of the reactions has been assigned.
Underground coal gasification (UCG) is an in situ conversion technique that enables the production of high-calorific synthesis gas from resources that are economically not minable by conventional methods. A broad range of end-use options is available for the synthesis gas, including fuels and chemical feedstock production. Furthermore, UCG also offers a high potential for integration with Carbon Capture and Storage (CCS) to mitigate greenhouse gas emissions. In the present study, a stoichiometric equilibrium model, based on minimization of the Gibbs function has been used to estimate the equilibrium composition of the synthesis gas. Thereto, we further developed and applied a proven thermodynamic equilibrium model to simulate the relevant thermochemical coal conversion processes (pyrolysis and gasification). Our modeling approach has been validated against thermodynamic models, laboratory gasification experiments and UCG field trial data reported in the literature. The synthesis gas compositions have been found to be in good agreement under a wide range of different operating conditions. Consequently, the presented modeling approach enables an efficient quantification of synthesis gas quality resulting from UCG, considering varying coal and oxidizer compositions at deposit-specific pressures and temperatures.
Vast racial inequalities continue to prevail across the United States and are closely linked to economic resources. One particularly prominent argument contends that childhood wealth accounts for black–white (BW) disadvantages in life chances. This article analyzes how much childhood wealth and childhood income mediate BW disadvantages in adult life chances with Panel Study of Income Dynamics and Cross-National Equivalent File data on children from the 1980s and 1990s who were 30+ years old in 2015. Compared with previous research, we exploit longer panel data, more comprehensively assess adult life chances with 18 outcomes, and measure income and wealth more rigorously. We find large BW disadvantages in most outcomes. Childhood wealth and income mediate a substantial share of most BW disadvantages, although there are several significant BW disadvantages even after adjusting for childhood wealth and income. The evidence mostly contradicts the prominent claim that childhood wealth is more important than childhood income. Indeed, the analyses mostly show that childhood income explains more of BW disadvantages and has larger standardized coefficients than childhood wealth. We also show how limitations in prior wealth research explain why our conclusions differ. Replication with the National Longitudinal Survey of Youth and a variety of robustness checks support these conclusions.
Introduction:
The death of a significant person through suicide is a very difficult experience and can have long-term impact on an individual's psychosocial and physical functioning. However, there are only few studies that have examined the effects of interventions in suicide survivors. In the present study, we examine an online-group intervention for people bereaved by suicide using a group-webinar.
Methods:
The intervention was developed based on focus groups with the target group. The cognitive-behavioral 12-module webinar-based group intervention focuses on suicide bereavement-related themes such as feelings of guilt, stigmatization, meaning reconstruction and the relationship to the deceased. Further, the webinar includes testimonial videos and psychoeducation. The suicide survivors are randomized to the intervention or the waiting list in a group-cluster randomized controlled trial. Primary outcomes are suicidality (Beck Scale for Suicide Ideation) and depression (Beck Depression Inventory-II) and secondary outcomes are symptoms of prolonged grief disorder (Inventory of Complicated Grief-German Version ), posttraumatic stress disorder ( Revised Impact of Event Scale ), stigmatization (Stigma of Suicide and Suicide Survivor ) and posttraumatic cognitions (Posttraumatic Cognitions Inventory).
Discussion:
Previous studies of Internet-based interventions for the bereaved were based on writing interventions showing large treatment effects. Little is known about the use of webinars as group interventions. Advantages and challenges of this novel approach of psychological interventions will be discussed.
The world is facing a triple burden of undernourishment, obesity, and environmental impacts from agriculture while nourishing its population. This burden makes sustainable nourishment of the growing population a global challenge. Addressing this challenge requires an understanding of the interplay between diets, health, and associated environmental impacts (e.g., climate change). For this, we identify 11 typical diets that represent dietary habits worldwide for the last five decades. Plant-source foods provide most of all three macronutrients (carbohydrates, protein, and fat) in developing countries. In contrast, animal-source foods provide a majority of protein and fat in developed ones. The identified diets deviate from the recommended healthy diet with either too much (e.g., red meat) or too little (e.g., fruits and vegetables) food and nutrition supply. The total calorie supplies are lower than required for two diets. Sugar consumption is higher than recommended for five diets. Three and five diets consist of larger-than-recommended carbohydrate and fat shares, respectively. Four diets with a large share of animal-source foods exceed the recommended value of red meat. Only two diets consist of at least 400 gm/cap/day of fruits and vegetables while accounting for food waste. Prevalence of undernourishment and underweight dominates in the diets with lower calories. In comparison, a higher prevalence of obesity is observed for diets with higher calories with high shares of sugar, fat, and animal-source foods. However, embodied emissions in the diets do not show a clear relation with calorie supplies and compositions. Two high-calorie diets embody more than 1.5 t CO<mml:semantics>2</mml:semantics>eq/cap/yr, and two low-calorie diets embody around 1 t CO<mml:semantics>2</mml:semantics>eq/cap/yr. Our analysis highlights that sustainable and healthy diets can serve the purposes of both nourishing the population and, at the same time, reducing the environmental impacts of agriculture.
In this work, which is part of a larger research program, a framework called "virtual data fusion" was developed to provide an automated and consistent crack detection method that allows for the cross-comparison of results from large quantities of X-ray computed tomography (CT) data. A partial implementation of this method in a custom program was developed for use in research focused on crack quantification in alkali-silica reaction (ASR)-sensitive concrete aggregates. During the CT image processing, a series of image analyses tailored for detecting specific, individual crack-like characteristics were completed. The results of these analyses were then "fused" in order to identify crack-like objects within the images with much higher accuracy than that yielded by any individual image analysis procedure. The results of this strategy demonstrated the success of the program in effectively identifying crack-like structures and quantifying characteristics, such as surface area and volume. The results demonstrated that the source of aggregate has a very significant impact on the amount of internal cracking, even when the mineralogical characteristics remain very similar. River gravels, for instance, were found to contain significantly higher levels of internal cracking than quarried stone aggregates of the same mineralogical type.
L-(+)-lactic acid from reed
(2020)
Biotechnological production of lactic acid (LA) is based on the so-called first generation feedstocks, meaning sugars derived from food and feed crops such as corn, sugarcane and cassava. The aim of this study was to exploit the potential of a second generation resource: Common reed (Phragmites australis) is a powerfully reproducing sweet grass which grows in wetlands and creates vast monocultural populations. This lignocellulose biomass bears the possibility to be refined to value-added products, without competing with agro industrial land. Besides utilizing reed as a renewable and inexpensive substrate, low-cost nutritional supplementation was analyzed for the fermentation of thermophilicBacilluscoagulans.Various nutritional sources such as baker's and brewer's yeast, lucerne green juice and tryptone were investigated for the replacement of yeast extract. The structure of the lignocellulosic material was tackled by chemical treatment (1% NaOH) and enzymatic hydrolysis (Cellic(R)CTec2).B.coagulansDSM ID 14-300 was employed for the homofermentative conversion of the released hexose and pentose sugars to polymerizable L-(+)-LA of over 99.5% optical purity. The addition of autolyzed baker's yeast led to the best results of fermentation, enabling an LA titer of 28.3 g L(-1)and a yield of 91.6%.
Background: The enzyme-linked immunosorbent assay (ELISA) is an indispensable tool for clinical diagnostics to identify or differentiate diseases such as autoimmune illnesses, but also to monitor their progression or control the efficacy of drugs. One use case of ELISA is to differentiate between different states (e.g. healthy vs. diseased). Another goal is to quantitatively assess the biomarker in question, like autoantibodies. Thus, the ELISA technology is used for the discovery and verification of new autoantibodies, too. Of key interest, however, is the development of immunoassays for the sensitive and specific detection of such biomarkers at early disease stages. Therefore, users have to deal with many parameters, such as buffer systems or antigen-autoantibody interactions, to successfully establish an ELISA. Often, fine-tuning like testing of several blocking substances is performed to yield high signal-to-noise ratios. <br /> Methods: We developed an ELISA to detect IgA and IgG autoantibodies against chitinase-3-like protein 1 (CHI3L1), a newly identified autoantigen in inflammatory bowel disease (IBD), in the serum of control and disease groups (n = 23, respectively). Microwell plates with different surface modifications (PolySorp and MaxiSorp coating) were tested to detect reproducibility problems. <br /> Results: We found a significant impact of the surface properties of the microwell plates. IgA antibody reactivity was significantly lower, since it was in the range of background noise, when measured on MaxiSorp coated plates (p < 0.0001). The IgG antibody reactivity did not differ on the diverse plates, but the plate surface had a significant influence on the test result (p = 0.0005). <br /> Conclusion: With this report, we want to draw readers' attention to the properties of solid phases and their effects on the detection of autoantibodies by ELISA. We want to sensitize the reader to the fact that the choice of the wrong plate can lead to a false negative test result, which in turn has serious consequences for the discovery of autoantibodies.
Background Recent shoulder injury prevention programs have utilized resistance exercises combined with different forms of instability, with the goal of eliciting functional adaptations and thereby reducing the risk of injury. However, it is still unknown how an unstable weight mass (UWM) affects the muscular activity of the shoulder stabilizers. Aim of the study was to assess neuromuscular activity of dynamic shoulder stabilizers under four conditions of stable and UWM during three shoulder exercises. It was hypothesized that a combined condition of weight with UWM would elicit greater activation due to the increased stabilization demand. Methods Sixteen participants (7 m/9 f) were included in this cross-sectional study and prepared with an EMG-setup for the: Mm. upper/lower trapezius (U.TA/L.TA), lateral deltoid (DE), latissimus dorsi (LD), serratus anterior (SA) and pectoralis major (PE). A maximal voluntary isometric contraction test (MVIC; 5 s.) was performed on an isokinetic dynamometer. Next, internal/external rotation (In/Ex), abduction/adduction (Ab/Ad) and diagonal flexion/extension (F/E) exercises (5 reps.) were performed with four custom-made-pipes representing different exercise conditions. First, the empty-pipe (P; 0.5 kg) and then, randomly ordered, water-filled-pipe (PW; 1 kg), weight-pipe (PG; 4.5 kg) and weight + water-filled-pipe (PWG; 4.5 kg), while EMG was recorded. Raw root-mean-square values (RMS) were normalized to MVIC (%MVIC). Differences between conditions for RMS%MVIC, scapular stabilizer (SR: U.TA/L.TA; U.TA/SA) and contraction (CR: concentric/eccentric) ratios were analyzed (paired t-test; p <= 0.05; Bonferroni adjusted alpha = 0.008). Results PWG showed significantly greater muscle activity for all exercises and all muscles except for PE compared to P and PW. Condition PG elicited muscular activity comparable to PWG (p > 0.008) with significantly lower activation of L.TA and SA in the In/Ex rotation. The SR ratio was significantly higher in PWG compared to P and PW. No significant differences were found for the CR ratio in all exercises and for all muscles. Conclusion Higher weight generated greater muscle activation whereas an UWM raised the neuromuscular activity, increasing the stabilization demands. Especially in the In/Ex rotation, an UWM increased the RMS%MVIC and SR ratio. This might improve training effects in shoulder prevention and rehabilitation programs.
The load-depended loss of vertical barbell velocity at the end of the acceleration phase limits the maximum weight that can be lifted. Thus, the purpose of this study was to analyze how increased barbell loads affect the vertical barbell velocity in the sub-phases of the acceleration phase during the snatch. It was hypothesized that the load-dependent velocity loss at the end of the acceleration phase is primarily associated with a velocity loss during the 1st pull. For this purpose, 14 male elite weightlifters lifted seven load-stages from 70-100% of their personal best in the snatch. The load-velocity relationship was calculated using linear regression analysis to determine the velocity loss at 1st pull, transition, and 2nd pull. A group mean data contrast analysis revealed the highest load-dependent velocity loss for the 1st pull (t = 1.85, p = 0.044, g = 0.49 [-0.05, 1.04]) which confirmed our study hypothesis. In contrast to the group mean data, the individual athlete showed a unique response to increased loads during the acceleration sub-phases of the snatch. With the proposed method, individualized training recommendations on exercise selection and loading schemes can be derived to specifically improve the sub-phases of the snatch acceleration phase. Furthermore, the results highlight the importance of single-subject assessment when working with elite athletes in Olympic weightlifting.
Studies show relations between executive function (EF), Theory of Mind (ToM), and conduct-problem (CP) symptoms. However, many studies have involved cross-sectional data, small clinical samples, pre-school children, and/or did not consider potential mediation effects. The present study examined the longitudinal relations between EF, ToM abilities, and CP symptoms in a population-based sample of 1,657 children between 6 and 11 years (T1: M = 8.3 years, T2: M = 9.1 years; 51.9% girls). We assessed EF skills and ToM abilities via computerized tasks at first measurement (T1), CP symptoms were rated via parent questionnaires at T1 and approximately 1 year later (T2). Structural-equation models showed a negative relation between T1 EF and T2 CP symptoms even when controlling for attention-deficit hyperactivity disorder (ADHD) symptoms and other variables. This relation was fully mediated by T1 ToM abilities. The study shows how children's abilities to control their thoughts and behaviors and to understand others' mental states interact in the development of CP symptoms.
In this work, a novel electrochemical molecularly imprinted polymer (MIP) sensor for the detection of the lipopeptide antibiotic Daptomycin (DAP) is presented which integrates gold decorated platinum nanoparticles (Au-Pt NPs) into the nanocomposite film. The sensor was prepared by electropolymerization of o-phenylenediamine (o-PD) in the presence of DAP using cyclic voltammetry. Cyclic voltammetry and differential pulse voltammetry were applied to follow the changes in the MIP-layer related to rebinding and removal of the target DAP by using the redox marker [Fe(CN)(6)](3-/4-). Under optimized operational conditions, the MIP/Au-Pt NPs/ GCE nanosensor exhibits a linear response in the range of 1-20 pM towards DAP. The limit of detection and limit of quantification were determined to be 0.161pM +/- 0.012 and 0.489pM +/- 0.012, respectively. The sensitivity towards the antibiotics Vancomycin and Erythromycin and the amino acids glycine and tryptophan was below 7 percent as compared with DAP. Moreover, the nanosensor was also successfully used for the detection of DAP in deproteinated human serum samples.
The other-race effect (ORE) can be described as difficulties in discriminating between faces of ethnicities other than one's own, and can already be observed at approximately 9 months of age. Recent studies also showed that infants visually explore same-and other-race faces differently. However, it is still unclear whether infants' looking behavior for same- and other-race faces is related to their face discrimination abilities. To investigate this question we conducted a habituation-dishabituation experiment to examine Caucasian 9-month-old infants' gaze behavior, and their discrimination of same- and other-race faces, using eye-tracking measurements. We found that infants looked longer at the eyes of same-race faces over the course of habituation, as compared to other-race faces. After habituation, infants demonstrated a clear other-race effect by successfully discriminating between same-race faces, but not other-race faces. Importantly, the infants' ability to discriminate between same-race faces significantly correlated with their fixation time towards the eyes of same-race faces during habituation. Thus, our findings suggest that for infants old enough to begin exhibiting the ORE, gaze behavior during habituation is related to their ability to differentiate among same-race faces, compared to other-race faces.
Este estudioanalizócómose evoca la oralidad ficcional en la novela Rosario Tijerasa través de la variación lingüística. Para ello, se analizóun corpus de veinteunidades fraseológicas presentes en la novela y su traducción al alemán. En esta novela negra, el autor recurrióa un lenguaje coloquial llamado parlache. Este artículo, por tanto,se pretenderá establecer cómo estas unidades fraseológicas típicas del parlachecontribuyerona la construcción de un diálogo hablado verosímil, además de determinar las divergencias de traducción y profundizar en la descripción de la variación lingüística a través de las unidades fraseológicas.
Interacting particle solutions of Fokker–Planck equations through gradient–log–density estimation
(2020)
Fokker-Planck equations are extensively employed in various scientific fields as they characterise the behaviour of stochastic systems at the level of probability density functions. Although broadly used, they allow for analytical treatment only in limited settings, and often it is inevitable to resort to numerical solutions. Here, we develop a computational approach for simulating the time evolution of Fokker-Planck solutions in terms of a mean field limit of an interacting particle system. The interactions between particles are determined by the gradient of the logarithm of the particle density, approximated here by a novel statistical estimator. The performance of our method shows promising results, with more accurate and less fluctuating statistics compared to direct stochastic simulations of comparable particle number. Taken together, our framework allows for effortless and reliable particle-based simulations of Fokker-Planck equations in low and moderate dimensions. The proposed gradient-log-density estimator is also of independent interest, for example, in the context of optimal control.
The mixture of ammonium nitrate (AN) prills and fuel oil (FO), usually referred to as ANFO, is extensively used in the mining industry as a bulk explosive. One of the major performance predictors of ANFO mixtures is the fuel oil retention, which is itself governed by the complex pore structure of the AN prills. In this study, we present how X-ray computed tomography (XCT), and the associated advanced data processing workflow, can be used to fully characterise the structure and morphology of AN prills. We show that structural parameters such as volume fraction of the different phases and morphological parameters such as specific surface area and shape factor can be reliably extracted from the XCT data, and that there is a good agreement with the measured oil retention values. Importantly, oil retention measurements (qualifying the efficiency of ANFO as explosives) correlate well with the specific surface area determined by XCT. XCT can therefore be employed non-destructively; it can accurately evaluate and characterise porosity in ammonium nitrate prills, and even predict their efficiency.
We search for homovalent alternatives for A, B, and X-ions in ABX(3) type inorganic halide perovskites suitable for tandem solar cell applications. We replace the conventional A-site organic cation CH3NH3, by 3 inorganic cations, Cs, K, and Rb, and the B site consists of metals; Cd, Hg, Ge, Pb, and Sn This work is built on our previous high throughput screening of hybrid perovskite materials (Kar et al 2018 J. Chem. Phys. 149, 214701). By performing a systematic screening study using Density Functional Theory (DFT) methods, we found 11 suitable candidates; 2 Cs-based, 3 K-based and 6 Rb-based that are suitable for tandem solar cell applications.
Groundwater levels are monitored by environmental agencies to support the sustainable use of groundwater resources. For this purpose continuous and spatially comprehensive monitoring in high spatial and temporal resolution is desired. This leads to large datasets that have to be checked for quality and analysed to distinguish local anthropogenic influences from natural variability of the groundwater level dynamics at each well. Both technical problems with the measurements as well as local anthropogenic influences can lead to local anomalies in the hydrographs. We suggest a fast and efficient screening method for the identification of well-specific peculiarities in hydrographs of groundwater head monitoring networks. The only information required is a set of time series of groundwater heads all measured at the same instants of time. For each well of the monitoring network a reference hydrograph is calculated, describing expected "normal" behaviour at the respective well as is typical for the monitored region. The reference hydrograph is calculated by multiple linear regression of the observed hydrograph with the "stable" principal components (PCs) of a principal component analysis of all groundwater head series of the network as predictor variables. The stable PCs are those PCs which were found in a random subsampling procedure to be rather insensitive to the specific selection of the analysed observation wells, i.e. complete series, and to the specific selection of measurement dates. Hence they can be considered to be representative for the monitored region in the respective period. The residuals of the reference hydrograph describe local deviations from the normal behaviour. Peculiarities in the residuals allow the data to be checked for measurement errors and the wells with a possible anthropogenic influence to be identified. The approach was tested with 141 groundwater head time series from the state authority groundwater monitoring network in northeastern Germany covering the period from 1993 to 2013 at an approximately weekly frequency of measurement.
A growing focus is being placed on both individuals and communities to adapt to flooding as part of the Sendai Framework for Disaster Risk Reduction 2015-2030. Adaptation to flooding requires sufficient social capital (linkages between members of society), risk perceptions (understanding of risk), and self-efficacy (self-perceived ability to limit disaster impacts) to be effective. However, there is limited understanding of how social capital, risk perceptions, and self-efficacy interact. We seek to explore how social capital interacts with variables known to increase the likelihood of successful adaptation. To study these linkages we analyze survey data of 1010 respondents across two communities in Thua Tien-Hue Province in central Vietnam, using ordered probit models. We find positive correlations between social capital, risk perceptions, and self-efficacy overall. This is a partly contrary finding to what was found in previous studies linking these concepts in Europe, which may be a result from the difference in risk context. The absence of an overall negative exchange between these factors has positive implications for proactive flood risk adaptation.
Teachers' attitudes toward inclusion are frequently cited as being an important predictor of how successfully a given inclusive school system is implemented. At the same time, beliefs about the nature of teaching and learning are discussed as a possible predictor of attitudes toward inclusion. However, more recent research emphasizes the need of considering implicit processes, such as automatic evaluations, when describing attitudes and beliefs. Previous evidence on the association of attitudes toward inclusion and beliefs about teaching and learning is solely based on explicit reports. Therefore, this study aims to examine the relationship between attitudes toward inclusion, beliefs about teaching and learning, and the subsequent automatic evaluations of pre-service teachers (N = 197). The results revealed differences between pre-service teachers' explicit attitudes/beliefs and their subsequent automatic evaluations. Differences in the relationship between attitudes toward inclusion and beliefs about teaching and learning occur when teachers focus either on explicit measures or automatic evaluations. These differences might be due to different facets of the same attitude object being represented. Relying solely on either explicit measures or automatic evaluations at the exclusion of the other might lead to erroneous assumptions about the relation of attitudes toward inclusion and beliefs about teaching and learning.
Characterisation of gene-regulatory network (GRN) interactions provides a stepping stone to understanding how genes affect cellular phenotypes. Yet, despite advances in profiling technologies, GRN reconstruction from gene expression data remains a pressing problem in systems biology. Here, we devise a supervised learning approach, GRADIS, which utilises support vector machine to reconstruct GRNs based on distance profiles obtained from a graph representation of transcriptomics data. By employing the data fromEscherichia coliandSaccharomyces cerevisiaeas well as synthetic networks from the DREAM4 and five network inference challenges, we demonstrate that our GRADIS approach outperforms the state-of-the-art supervised and unsupervided approaches. This holds when predictions about target genes for individual transcription factors as well as for the entire network are considered. We employ experimentally verified GRNs fromE. coliandS. cerevisiaeto validate the predictions and obtain further insights in the performance of the proposed approach. Our GRADIS approach offers the possibility for usage of other network-based representations of large-scale data, and can be readily extended to help the characterisation of other cellular networks, including protein-protein and protein-metabolite interactions.
STEP.De study
(2020)
Introduction Although exercise therapy has widely been shown to be an efficacious treatment modality for depression, evidence for its effectiveness and cost efficiency is lacking. The Sport/Exercise Therapy for Depression study is a multicentre cluster-randomised effectiveness trial that aims to compare the effectiveness and cost efficiency of exercise therapy and psychotherapy as antidepressant treatment. <br /> Methods and analysis 480 patients (aged 18-65) with an International Classification of Diseases diagnosis associated with depressive symptoms are recruited. Up to 30 clusters (psychotherapists) are randomly assigned to allocate patients to either an exercise or a psychotherapy treatment as usual in a 2: 1 ratio. The primary outcome (depressive symptoms) and the secondary outcomes (work and social adjustment, quality of life) will be assessed at six measurement time points (t0: baseline, t1: 8 weeks after treatment initiation, t2: 16 weeks after treatment initiation, t3/ 4/5: 2, 6, 12 months after treatment). Linear regression analyses will be used for the primary endpoint data analysis. For the secondary endpoints, mixed linear and logistic regression models with fixed and random factors will be added. For the cost efficiency analysis, expenditures in the 12 months before and after the intervention and the outcome difference will be compared between groups in a multilevel model. Recruitment start date was 1 July 2018 and the planned recruitment end date is 31 December 2020. <br /> Ethics and dissemination The study protocol was approved by the ethics committee of the University of Potsdam (No. 17/2018) and the Freie Universitat Berlin (No. 206/2018) and registered in the ISRCTN registry. Informed written consent will be obtained from all participants. The study will be reported in accordance with the Consolidated Standards of Reporting Trials and the Recommendations for Interventional Trials statements. The results will be published in peer-reviewed academic journals and disseminated to the public.
Apple replant disease (ARD) is a specific apple-related form of soil fertility loss due to unidentified causes and is also known as soil fatigue. The effect typically appears in monoculture production sites and leads to production decreases of up to 50%, even though the cultivation practice remains the same. However, an indication of replant disease is challenged by the lack of specification of the particular microbial group responsible for ARD. The objective of this study was to establish an algorithm for estimating growth suppression in orchards irrespective of the unknowns in the complex causal relationship by assessing plant-soil interaction in the orchard several years after planting. Based on a comparison between no-replant and replant soils, the Alternaria group (Ag) was identified as a soil-fungal population responding to replant with abundance. The trunk cross-sectional area (CSA) was found to be a practical and robust parameter representing below-ground and above-ground tree performance. Suppression of tree vigour was therefore calculated by dividing the two inversely related parameters, Q = ln(Ag)/CSA, as a function of soil-fungal proportions and plant responses at the single-tree level. On this basis, five clusters of tree vigour suppression (Q) were defined: (1) no tree vigour suppression/vital (0%), (2) escalating (- 38%), (3) strong (- 53%), (4) very strong (- 62%), and (5) critical (- 74%). By calculating Q at the level of the single tree, trees were clustered according to tree vigour suppression. The weighted frequency of clusters in the field allowed replant impact to be quantified at field level. Applied to a case study on sandy brown, dry diluvial soils in Brandenburg, Germany, the calculated tree vigour suppression was 46% compared to the potential tree vigour on no-replant soil in the same field. It is highly likely that the calculated growth suppression corresponds to ARD-impact This result is relevant for identifying functional changes in soil and for monitoring the economic effects of soil fatigue in apple orchards, particularly where long-period crop rotation or plot exchange are improbable.
There is no consensus on which statistical model estimates school value-added (VA) most accurately. To date, the two most common statistical models used for the calculation of VA scores are two classical methods: linear regression and multilevel models. These models have the advantage of being relatively transparent and thus understandable for most researchers and practitioners. However, these statistical models are bound to certain assumptions (e.g., linearity) that might limit their prediction accuracy. Machine learning methods, which have yielded spectacular results in numerous fields, may be a valuable alternative to these classical models. Although big data is not new in general, it is relatively new in the realm of social sciences and education. New types of data require new data analytical approaches. Such techniques have already evolved in fields with a long tradition in crunching big data (e.g., gene technology). The objective of the present paper is to competently apply these "imported" techniques to education data, more precisely VA scores, and assess when and how they can extend or replace the classical psychometrics toolbox. The different models include linear and non-linear methods and extend classical models with the most commonly used machine learning methods (i.e., random forest, neural networks, support vector machines, and boosting). We used representative data of 3,026 students in 153 schools who took part in the standardized achievement tests of the Luxembourg School Monitoring Program in grades 1 and 3. Multilevel models outperformed classical linear and polynomial regressions, as well as different machine learning models. However, it could be observed that across all schools, school VA scores from different model types correlated highly. Yet, the percentage of disagreements as compared to multilevel models was not trivial and real-life implications for individual schools may still be dramatic depending on the model type used. Implications of these results and possible ethical concerns regarding the use of machine learning methods for decision-making in education are discussed.
Iron-sulfur (Fe-S) clusters are essential protein cofactors. In enzymes, they are present either in the rhombic [2Fe-2S] or the cubic [4Fe-4S] form, where they are involved in catalysis and electron transfer and in the biosynthesis of metal-containing prosthetic groups like the molybdenum cofactor (Moco). Here, we give an overview of the assembly of Fe-S clusters in bacteria and humans and present their connection to the Moco biosynthesis pathway. In all organisms, Fe-S cluster assembly starts with the abstraction of sulfur froml-cysteine and its transfer to a scaffold protein. After formation, Fe-S clusters are transferred to carrier proteins that insert them into recipient apo-proteins. In eukaryotes like humans and plants, Fe-S cluster assembly takes place both in mitochondria and in the cytosol. Both Moco biosynthesis and Fe-S cluster assembly are highly conserved among all kingdoms of life. Moco is a tricyclic pterin compound with molybdenum coordinated through its unique dithiolene group. Moco biosynthesis begins in the mitochondria in a Fe-S cluster dependent step involving radical/S-adenosylmethionine (SAM) chemistry. An intermediate is transferred to the cytosol where the dithiolene group is formed, to which molybdenum is finally added. Further connections between Fe-S cluster assembly and Moco biosynthesis are discussed in detail.
The article describes a systematic investigation of the effects of an aqueous NaOH treatment of 3D printed poly(lactic acid) (PLA) scaffolds for surface activation. The PLA surface undergoes several morphology changes and after an initial surface roughening, the surface becomes smoother again before the material dissolves. Erosion rates and surface morphologies can be controlled by the treatment. At the same time, the bulk mechanical properties of the treated materials remain unaltered. This indicates that NaOH treatment of 3D printed PLA scaffolds is a simple, yet viable strategy for surface activation without compromising the mechanical stability of PLA scaffolds.