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Gamma-ray line signatures can be expected in the very-high-energy (E-gamma > 100 GeV) domain due to self-annihilation or decay of dark matter (DM) particles in space. Such a signal would be readily distinguishable from astrophysical gamma-ray sources that in most cases produce continuous spectra that span over several orders of magnitude in energy. Using data collected with the H. E. S. S. gamma-ray instrument, upper limits on linelike emission are obtained in the energy range between similar to 500 GeV and similar to 25 TeV for the central part of the Milky Way halo and for extragalactic observations, complementing recent limits obtained with the Fermi-LAT instrument at lower energies. No statistically significant signal could be found. For monochromatic gamma-ray line emission, flux limits of (2 x 10(-7)-2 x 10(-5)) m(-2)s(-1)sr(-1) and (1 x 10(-8)- 2 x 10(-6)) m(-2)s(-1)sr(-1) are obtained for the central part of the Milky Way halo and extragalactic observations, respectively. For a DM particle mass of 1 TeV, limits on the velocity- averaged DM annihilation cross section <sigma upsilon >(chi chi ->gamma gamma) reach similar to 10(-27)cm(3)s(-1), based on the Einasto parametrization of the Galactic DM halo density profile. DOI: 10.1103/PhysRevLett.110.041301
Re-observations with the HESS telescope array of the very high-energy (VHE) source HESS J1018-589A that is coincident with the Fermi-LAT gamma-ray binary 1FGL J1018.6-5856 have resulted in a source detection significance of more than 9 sigma and the detection of variability (chi(2)/nu of 238.3/155) in the emitted gamma-ray flux. This variability confirms the association of HESS J1018-589A with the high-energy gamma-ray binary detected Fermi-LAT and also confirms the point-like source as a new VHE binary system. The spectrum of HESS J1018-589A is best fit with a power-law function with photon index Gamma = 2.20 +/- 0.14(stat) +/- 0.2(sys). Emission is detected up to similar to 20 TeV. The mean differential flux level is (2.9 +/- 0.4) x 10(-13) TeV-1 cm(-2) s(-1) at 1 TeV, equivalent to similar to 1% of the flux from the Crab Nebula at the same energy. Variability is clearly detected the night-by-night light curve. When folded on the orbital period of 16.58 days, the rebinned light curve peaks in phase with the observed X-ray high-energy phaseograms. The fit of the HESS phaseogram to a constant flux provides evidence of periodicity at the level of N-sigma > 3 sigma. The of the VHE phaseogram and measured spectrum suggest a low-inclination, low-eccentricity system with a modest impact from VHE gamma-ray due to pair production (tau less than or similar to 1 at 300 GeV).
Galactic cosmic rays reach energies of at least a few petaelectronvolts (of the order of 1015 electronvolts). This implies that our Galaxy contains petaelectronvolt accelerators (‘PeVatrons’), but all proposed models of Galactic cosmic-ray accelerators encounter difficulties at exactly these energies. Dozens of Galactic accelerators capable of accelerating particles to energies of tens of teraelectronvolts (of the order of 1013 electronvolts) were inferred from recent γ-ray observations3. However, none of the currently known accelerators—not even the handful of shell-type supernova remnants commonly believed to supply most Galactic cosmic rays—has shown the characteristic tracers of petaelectronvolt particles, namely, power-law spectra of γ-rays extending without a cut-off or a spectral break to tens of teraelectronvolts4. Here we report deep γ-ray observations with arcminute angular resolution of the region surrounding the Galactic Centre, which show the expected tracer of the presence of petaelectronvolt protons within the central 10 parsecs of the Galaxy. We propose that the supermassive black hole Sagittarius A* is linked to this PeVatron. Sagittarius A* went through active phases in the past, as demonstrated by X-ray outbursts5and an outflow from the Galactic Centre6. Although its current rate of particle acceleration is not sufficient to provide a substantial contribution to Galactic cosmic rays, Sagittarius A* could have plausibly been more active over the last 106–107 years, and therefore should be considered as a viable alternative to supernova remnants as a source of petaelectronvolt Galactic cosmic rays.
The inner region of the Milky Way halo harbors a large amount of dark matter (DM). Given its proximity, it is one of the most promising targets to look for DM. We report on a search for the annihilations of DM particles using gamma-ray observations towards the inner 300 pc of the Milky Way, with the H.E.S.S. array of ground-based Cherenkov telescopes. The analysis is based on a 2D maximum likelihood method using Galactic Center (GC) data accumulated by H.E.S.S. over the last 10 years (2004-2014), and does not show any significant gamma-ray signal above background. Assuming Einasto and Navarro-Frenk-White DM density profiles at the GC, we derive upper limits on the annihilation cross section <sigma nu >. These constraints are the strongest obtained so far in the TeV DM mass range and improve upon previous limits by a factor 5. For the Einasto profile, the constraints reach <sigma nu > values of 6 x 10(-26) cm(3) s(-1) in the W+W- channel for a DM particle mass of 1.5 TeV, and 2 x 10(-26) cm(3) s(-1) in the tau(+)tau(-) channel for a 1 TeV mass. For the first time, ground-based gamma-ray observations have reached sufficient sensitivity to probe <sigma nu > values expected from the thermal relic density for TeV DM particles.
The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia
(2019)
The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.
Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.
Birth weight within the normal range is associated with a variety of adult-onset diseases, but the mechanisms behind these associations are poorly understood(1). Previous genome-wide association studies of birth weight identified a variant in the ADCY5 gene associated both with birth weight and type 2 diabetes and a second variant, near CCNL1, with no obvious link to adult traits(2). In an expanded genome-wide association metaanalysis and follow-up study of birth weight (of up to 69,308 individuals of European descent from 43 studies), we have now extended the number of loci associated at genome-wide significance to 7, accounting for a similar proportion of variance as maternal smoking. Five of the loci are known to be associated with other phenotypes: ADCY5 and CDKAL1 with type 2 diabetes, ADRB1 with adult blood pressure and HMGA2 and LCORL with adult height. Our findings highlight genetic links between fetal growth and postnatal growth and metabolism.
During aging, intracranial volume remains unchanged and represents maximally attained brain size, while various interacting biological phenomena lead to brain volume loss. Consequently, intracranial volume and brain volume in late life reflect different genetic influences. Our genome-wide association study (GWAS) in 8,175 community-dwelling elderly persons did not reveal any associations at genome-wide significance (P < 5 x 10(-8)) for brain volume. In contrast, intracranial volume was significantly associated with two loci: rs4273712 (P = 3.4 x 10(-11)), a known height-associated locus on chromosome 6q22, and rs9915547 (P = 1.5 x 10(-12)), localized to the inversion on chromosome 17q21. We replicated the associations of these loci with intracranial volume in a separate sample of 1,752 elderly persons (P = 1.1 x 10(-3) for 6q22 and 1.2 x 10(-3) for 17q21). Furthermore, we also found suggestive associations of the 17q21 locus with head circumference in 10,768 children (mean age of 14.5 months). Our data identify two loci associated with head size, with the inversion at 17q21 also likely to be involved in attaining maximal brain size.
The purpose of this study was to investigate whether neural adaptations following functional multiple-joint leg press training can induce neural adaptations to the plantar flexor muscles in a single-joint contraction task. Subjects were randomised to a maximal strength training (MST) (n = 10) or a control group (n = 9). MST consisted of 24 sessions (8 weeks) of 4 x 4 repetitions of horizontal leg press using maximal intended velocity in the concentric phase with the movement ending in a plantar flexion. Neural adaptations in the soleus and gastrocnemius medialis (GM) were assessed by surface electromyographic activity and V-waves during maximum voluntary isometric contraction (MVIC), and also by H- reflexes in the soleus during rest and 20% MVIC. One repetition maximum leg press increased by 44 +/- A 14% (mean +/- A SD; P < 0.01). Plantar flexion MVIC increased by 20 +/- A 14% (P < 0.01), accompanied by 13 +/- A 19% (P < 0.05) increase in soleus, but not GM surface electromyography. Soleus V/M-SUP increased by 53 +/- A 66% and in GM by 59 +/- A 64% (P < 0.05). Normalised soleus H-reflexes remained unchanged by training. No changes occurred in the control group. These results suggest that leg press MST can induce neural adaptations in a single-joint plantar flexion MVIC task.
Multiple sclerosis (MS) patients suffer from impaired muscle activation and lower limb strength. Strength training enhances muscle activation and muscle strength, but neural adaptations to strength training remain unexplored in MS patients. The hypothesis was that maximal strength training (MST) using high loads and few repetitions would improve central neural drive and thus strength capacity of MS patients. 14 MS patients staying at a national MS rehabilitation center were randomly assigned to a MST group or a control group (CG). Both groups received "today's treatment". In addition, the MST group trained 4 x 4 repetitions of unilateral dynamic leg press and plantar flexion 5 days a week for 3 weeks. Neural adaptations of the soleus muscle were assessed by surface electromyography (EMG) activity, and by superimposed H-reflexes and V-waves obtained during maximum voluntary isometric plantar flexor contractions (MVCs). H-reflexes and V-waves were normalized by the M-wave (H (SUP)/M (SUP), V/M (SUP), respectively). In the MST group, MVC increased by 20 +/- A 9% (P < 0.05). Soleus EMG activity and V/M (SUP) ratio increased by 40 and 55%, respectively, in the MST group compared to the CG (P a parts per thousand currency sign 0.05). The H (SUP)/M (SUP) ratio remained unchanged. No change was apparent in the CG. MST group subjects were able to complete all training sessions. No adverse effects were reported. This randomized study provides evidence that MST is effective of augmenting the magnitude of efferent motor output of spinal motor neurons in MS patients, alleviating some neuromuscular symptoms linked to the disease.
Serving many at once: How a database approach can create unity in dynamical ecosystem modelling
(2014)
Simulation modelling in ecology is a field that is becoming increasingly compartmentalized. Here we propose a Database Approach To Modelling (DATM) to create unity in dynamical ecosystem modelling with differential equations. In this approach the storage of ecological knowledge is independent of the language and platform in which the model will be run. To create an instance of the model, the information in the database is translated and augmented with the language and platform specifics. This process is automated so that a new instance can be created each time the database is updated. We describe the approach using the simple Lotka-Volterra model and the complex ecosystem model for shallow lakes PCLake, which we automatically implement in the frameworks OSIRIS, GRIND for MATLAB, ACSL, R, DUFLOW and DELWAQ. A clear advantage of working in a database is the overview it provides. The simplicity of the approach only adds to its elegance. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-SA license (http://creativecommons.org/licenses/by-nc-sa/3.0/).
Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective
(2015)
Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5-10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary.
Water quality modelling deals with multidisciplinary questions ranging from fundamental to applied. Addressing this broad range of questions requires multiple analysis techniques and therefore multiple frameworks. Through the recently developed database approach to modelling (DATM), it has become possible to run a model in multiple software frameworks without much overhead. Here we apply DATM to the ecosystem model for ditches PCDitch and its twin model for shallow lakes PCLake. Using DATM, we run these models in six frameworks (ACSL, DELWAQ, DUFLOW, GRIND for MATLAB, OSIRIS and R), and report on the possible model analyses with tools provided by each framework. We conclude that the dynamic link between frameworks and models resulting from DATM has the following main advantages: it allows one to use the framework one is familiar with for most model analyses and eases switching between frameworks for complementary model analyses, including the switch between a 0-D and 1-D to 3-D setting. Moreover, the strength of each framework - including runtime performance - can now be easily exploited. We envision that a community-based further development of the concept can contribute to the future development of water quality modelling, not only by addressing multidisciplinary questions but also by facilitating the exchange of models and process formulations within the community of water quality modellers.
Aus dem Inhalt:
- 10 Jahre Responsibility to Protect: Ein Sieg für die Menschenrechte? – Eine politik- und rechtswissenschaftliche Analyse
- Neue Regeln zur Abwesenheit des Angeklagten vor dem IStGH:
Menschenrechtliche Anforderungen an In-absentia-Verfahren
- EGMR: S.A.S. ./. Frankreich – Urteilsbesprechung zum Burkaverbot
Context. Galactic globular clusters (GCs) are now known to host multiple populations displaying particular abundance variations. The different populations within a GC can be well distinguished following their position in the pseudo two-colors diagrams, also referred to as "chromosome maps". These maps are constructed using optical and near-UV photometry available from the Hubble Space Telescope (HST) UV survey of GCs. However, the chemical tagging of the various populations in the chromosome maps is hampered by the fact that HST photometry and elemental abundances are both only available for a limited number of stars. Aims. The spectra collected as part of the MUSE survey of globular clusters provide a spectroscopic counterpart to the HST photometric catalogs covering the central regions of GCs. In this paper, we use the MUSE spectra of 1115 red giant branch (RGB) stars in NGC 2808 to characterize the abundance variations seen in the multiple populations of this cluster. Methods. We used the chromosome map of NGC 2808 to divide the RGB stars into their respective populations. We then combined the spectra of all stars belonging to a given population, resulting in one high signal-to-noise ratio spectrum representative of each population. Results. Variations in the spectral lines of O, Na, Mg, and Al are clearly detected among four of the populations. In order to quantify these variations, we measured equivalent width differences and created synthetic populations spectra that were used to determine abundance variations with respect to the primordial population of the cluster. Our results are in good agreement with the values expected from previous studies based on high-resolution spectroscopy. We do not see any significant variations in the spectral lines of Ca, K, and Ba. We also do not detect abundance variations among the stars belonging to the primordial population of NGC 2808. Conclusions. We demonstrate that in spite of their low resolution, the MUSE spectra can be used to investigate abundance variations in the context of multiple populations.
During the Ring Grazing orbits near the end of Cassini mission, the spacecraft crossed the equatorial plane near the orbit of Janus/Epimetheus (similar to 2.5 Rs). This region is populated with dust particles that can be detected by the Radio and Plasma Wave Science (RPWS) instrument via an electric field antenna signal. Analysis of the voltage waveforms recorded on the RPWS antennas provides estimations of the density and size distribution of the dust particles. Measured RPWS profiles, fitted with Lorentzian functions, are shown to be mostly consistent with the Cosmic Dust Analyzer, the dedicated dust instrument on board Cassini. The thickness of the dusty ring varies between 600 and 1,000 km. The peak location shifts north and south within 100 km of the ring plane, likely a function of the precession phase of Janus orbit.
Recent global warming is acting across marine, freshwater, and terrestrial ecosystems to favor species adapted to warmer conditions and/or reduce the abundance of cold-adapted organisms (i.e., "thermophilization" of communities). Lack of community responses to increased temperature, however, has also been reported for several taxa and regions, suggesting that "climatic lags" may be frequent. Here we show that microclimatic effects brought about by forest canopy closure can buffer biotic responses to macroclimate warming, thus explaining an apparent climatic lag. Using data from 1,409 vegetation plots in European and North American temperate forests, each surveyed at least twice over an interval of 12-67 y, we document significant thermophilization of ground-layer plant communities. These changes reflect concurrent declines in species adapted to cooler conditions and increases in species adapted to warmer conditions. However, thermophilization, particularly the increase of warm-adapted species, is attenuated in forests whose canopies have become denser, probably reflecting cooler growing-season ground temperatures via increased shading. As standing stocks of trees have increased in many temperate forests in recent decades, local microclimatic effects may commonly be moderating the impacts of macroclimate warming on forest understories. Conversely, increases in harvesting woody biomass-e.g., for bioenergy-may open forest canopies and accelerate thermophilization of temperate forest biodiversity.
Micro-RNAs are cellular components regulating gene expression at the post-transcription level. In the present study, artificial micro-RNAs were used to decrease the transcript level of two genes, AtExpA8 (encoding an expansin) and AHL25 (encoding an AT-hook motif nuclear localized protein) in Arabidopsis thaliana. The backbone of the Arabidopsis endogenous MIR319a micro-RNA was used in a site-directed mutagenesis approach for the generation of artificial micro-RNAs targeting two genes. The recombinant cassettes were expressed under the control of the CaMV 35S promoter in individual A. thaliana plants. Transgenic lines of the third generation were tested by isolating total RNA and by subsequent cDNA synthesis using oligo-dT18 primers and mRNAs as templates. The expression of the two target genes was checked through quantitative realtime polymerase chain reaction to confirm reduced transcript levels for AtExpA8 and AHL25. Downregulation of AtExpA8 resulted in the formation of short hypocotyls compared with those of the wild-type control in response to low pH and high salt concentration. This technology could be used to prevent the expression of exogenous and invading genes posing a threat to the normal cellular physiology of the host plant.
X-ray absorption spectroscopy at the L-edge of 3d transition metals provides unique information on the local metal charge and spin states by directly probing 3d-derived molecular orbitals through 2p-3d transitions. However, this soft x-ray technique has been rarely used at synchrotron facilities for mechanistic studies of metalloenzymes due to the difficulties of x-ray-induced sample damage and strong background signals from light elements that can dominate the low metal signal. Here, we combine femtosecond soft x-ray pulses from a free-electron laser with a novel x-ray fluorescence-yield spectrometer to overcome these difficulties. We present L-edge absorption spectra of inorganic high-valent Mn complexes (Mn similar to 6-15 mmol/l) with no visible effects of radiation damage. We also present the first L-edge absorption spectra of the oxygen evolving complex (Mn4CaO5) in Photosystem II (Mn < 1 mmol/l) at room temperature, measured under similar conditions. Our approach opens new ways to study metalloenzymes under functional conditions. (C) 2017 Author(s).
While the Intergovernmental Panel on Climate Change (IPCC) physical science reports usually assess a handful of future scenarios, the Working Group III contribution on climate mitigation to the IPCC's Sixth Assessment Report (AR6 WGIII) assesses hundreds to thousands of future emissions scenarios. A key task in WGIII is to assess the global mean temperature outcomes of these scenarios in a consistent manner, given the challenge that the emissions scenarios from different integrated assessment models (IAMs) come with different sectoral and gas-to-gas coverage and cannot all be assessed consistently by complex Earth system models. In this work, we describe the “climate-assessment” workflow and its methods, including infilling of missing emissions and emissions harmonisation as applied to 1202 mitigation scenarios in AR6 WGIII. We evaluate the global mean temperature projections and effective radiative forcing (ERF) characteristics of climate emulators FaIRv1.6.2 and MAGICCv7.5.3 and use the CICERO simple climate model (CICERO-SCM) for sensitivity analysis. We discuss the implied overshoot severity of the mitigation pathways using overshoot degree years and look at emissions and temperature characteristics of scenarios compatible with one possible interpretation of the Paris Agreement. We find that the lowest class of emissions scenarios that limit global warming to “1.5 ∘C (with a probability of greater than 50 %) with no or limited overshoot” includes 97 scenarios for MAGICCv7.5.3 and 203 for FaIRv1.6.2. For the MAGICCv7.5.3 results, “limited overshoot” typically implies exceedance of median temperature projections of up to about 0.1 ∘C for up to a few decades before returning to below 1.5 ∘C by or before the year 2100. For more than half of the scenarios in this category that comply with three criteria for being “Paris-compatible”, including net-zero or net-negative greenhouse gas (GHG) emissions, median temperatures decline by about 0.3–0.4 ∘C after peaking at 1.5–1.6 ∘C in 2035–2055. We compare the methods applied in AR6 with the methods used for SR1.5 and discuss their implications. This article also introduces a “climate-assessment” Python package which allows for fully reproducing the IPCC AR6 WGIII temperature assessment. This work provides a community tool for assessing the temperature outcomes of emissions pathways and provides a basis for further work such as extending the workflow to include downscaling of climate characteristics to a regional level and calculating impacts.
We introduce azobenzene-functionalized polyelectrolyte multilayers as efficient, inexpensive optoacoustic transducers for hyper-sound strain waves in the GHz range. By picosecond transient reflectivity measurements we study the creation of nanoscale strain waves, their reflection from interfaces, damping by scattering from nanoparticles and propagation in soft and hard adjacent materials like polymer layers, quartz and mica. The amplitude of the generated strain epsilon similar to 5 x 10(-4) is calibrated by ultrafast X-ray diffraction.
Monolithic perovskite silicon tandem solar cells can overcome the theoretical efficiency limit of silicon solar cells. This requires an optimum bandgap, high quantum efficiency, and high stability of the perovskite. Herein, a silicon heterojunction bottom cell is combined with a perovskite top cell, with an optimum bandgap of 1.68 eV in planar p-i-n tandem configuration. A methylammonium-free FA(0.75)Cs(0.25)Pb(I0.8Br0.2)(3) perovskite with high Cs content is investigated for improved stability. A 10% molarity increase to 1.1 m of the perovskite precursor solution results in approximate to 75 nm thicker absorber layers and 0.7 mA cm(-2) higher short-circuit current density. With the optimized absorber, tandem devices reach a high fill factor of 80% and up to 25.1% certified efficiency. The unencapsulated tandem device shows an efficiency improvement of 2.3% (absolute) over 5 months, showing the robustness of the absorber against degradation. Moreover, a photoluminescence quantum yield analysis reveals that with adapted charge transport materials and surface passivation, along with improved antireflection measures, the high bandgap perovskite absorber has the potential for 30% tandem efficiency in the near future.
Monolithic perovskite silicon tandem solar cells can overcome the theoretical efficiency limit of silicon solar cells. This requires an optimum bandgap, high quantum efficiency, and high stability of the perovskite. Herein, a silicon heterojunction bottom cell is combined with a perovskite top cell, with an optimum bandgap of 1.68 eV in planar p-i-n tandem configuration. A methylammonium-free FA(0.75)Cs(0.25)Pb(I0.8Br0.2)(3) perovskite with high Cs content is investigated for improved stability. A 10% molarity increase to 1.1 m of the perovskite precursor solution results in approximate to 75 nm thicker absorber layers and 0.7 mA cm(-2) higher short-circuit current density. With the optimized absorber, tandem devices reach a high fill factor of 80% and up to 25.1% certified efficiency. The unencapsulated tandem device shows an efficiency improvement of 2.3% (absolute) over 5 months, showing the robustness of the absorber against degradation. Moreover, a photoluminescence quantum yield analysis reveals that with adapted charge transport materials and surface passivation, along with improved antireflection measures, the high bandgap perovskite absorber has the potential for 30% tandem efficiency in the near future.
Objective: Hypertension before and during early pregnancy has been associated with an increased risk of gestational diabetes mellitus (GDM) in retrospective analyses. We aimed to investigate the prospective blood pressure trackings in a population-based cohort of pregnant women, who were stratified according to their metabolic status in early third trimester. Methods: We recorded blood pressure longitudinally during pregnancy in 1230 women from the Odense Child Cohort, Denmark. Fasting glucose and insulin were measured at gestational weeks 28-30. Metabolic status was evaluated according to the WHO 2013 threshold for GDM (GDM-WHO: fasting plasma glucose >= 5.1 mmol/l), insulin and homeostatic model assessment of insulin resistance (HOMA-IR). Relationships between metabolic status in third trimester and blood pressure trajectories were evaluated with adjusted linear mixed models. Trajectory was defined as blood pressure records in pregnancy per 4 weeks interval. Results: Prevalence of GDM-WHO was 40% (498/1230). GDM-WHO was associated with 1.46 (0.22-2.70) mmHg higher SBP and 1.04 (0.07-2.01) mmHg higher DBP trajectories in the overall cohort. The associations were driven by differences in the overweight group, with 3.14 (1.05-5.25) mmHg higher SBP and 1.94 (0.42-3.47) mmHg higher DBP per 4 weeks in women with GDM-WHO compared with women without GDM-WHO. GDM-WHO was not associated with blood pressure in women with normal weight. Blood pressure trajectories were elevated across quartiles of insulin resistance. Conclusion: GDM-WHO is associated with higher blood pressure in pregnancy, and there appears to be a stronger effect in overweight women.
The role that climate and environmental history may have played in influencing human evolution has been the focus of considerable interest and controversy among paleoanthropologists for decades. Prior attempts to understand the environmental history side of this equation have centered around the study of outcrop sediments and fossils adjacent to where fossil hominins (ancestors or close relatives of modern humans) are found, or from the study of deep sea drill cores. However, outcrop sediments are often highly weathered and thus are unsuitable for some types of paleoclimatic records, and deep sea core records come from long distances away from the actual fossil and stone tool remains. The Hominin Sites and Paleolakes Drilling Project (HSPDP) was developed to address these issues. The project has focused its efforts on the eastern African Rift Valley, where much of the evidence for early hominins has been recovered. We have collected about 2 km of sediment drill core from six basins in Kenya and Ethiopia, in lake deposits immediately adjacent to important fossil hominin and archaeological sites. Collectively these cores cover in time many of the key transitions and critical intervals in human evolutionary history over the last 4 Ma, such as the earliest stone tools, the origin of our own genus Homo, and the earliest anatomically modern Homo sapiens. Here we document the initial field, physical property, and core description results of the 2012-2014 HSPDP coring campaign.
The great auk was once abundant and distributed across the North Atlantic. It is now extinct, having been heavily exploited for its eggs, meat, and feathers. We investigated the impact of human hunting on its demise by integrating genetic data, GPS-based ocean current data, and analyses of population viability. We sequenced complete mitochondrial genomes of 41 individuals from across the species' geographic range and reconstructed population structure and population dynamics throughout the Holocene. Taken together, our data do not provide any evidence that great auks were at risk of extinction prior to the onset of intensive human hunting in the early 16th century. In addition, our population viability analyses reveal that even if the great auk had not been under threat by environmental change, human hunting alone could have been sufficient to cause its extinction. Our results emphasise the vulnerability of even abundant and widespread species to intense and localised exploitation.
Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P< 5 x 10(-8). In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.
Management intensity modifies soil properties, e.g., organic carbon (C-org) concentrations and soil pH with potential feedbacks on plant diversity. These changes might influence microbial P concentrations (P-mic) in soil representing an important component of the Pcycle. Our objectives were to elucidate whether abiotic and biotic variables controlling P-mic concentrations in soil are the same for forests and grasslands, and to assess the effect of region and management on P-mic concentrations in forest and grassland soils as mediated by the controlling variables. In three regions of Germany, Schwabische Alb, Hanich-Dun, and Schorfheide-Chorin, we studied forest and grassland plots (each n=150) differing in plant diversity and land-use intensity. In contrast to controls of microbial biomass carbon (C-mic), P-mic was strongly influenced by soil pH, which in turn affected phosphorus (P) availability and thus microbial Puptake in forest and grassland soils. Furthermore, P-mic concentrations in forest and grassland soils increased with increasing plant diversity. Using structural equation models, we could show that soil C-org is the profound driver of plant diversity effects on P-mic in grasslands. For both forest and grassland, we found regional differences in P-mic attributable to differing environmental conditions (pH, soil moisture). Forest management and tree species showed no effect on P-mic due to a lack of effects on controlling variables (e.g., C-org). We also did not find management effects in grassland soils which might be caused by either compensation of differently directed effects across sites or by legacy effects of former fertilization constraining the relevance of actual practices. We conclude that variables controlling P-mic or C-mic in soil differ in part and that regional differences in controlling variables are more important for P-mic in soil than those induced by management.
In the last decade, there has been an increasing interest in compensating thermally induced errors to improve the manufacturing accuracy of modular tool systems. These modular tool systems are interfaces between spindle and workpiece and consist of several complicatedly formed parts. Their thermal behavior is dominated by nonlinearities, delay and hysteresis effects even in tools with simpler geometry and it is difficult to describe it theoretically. Due to the dominant nonlinear nature of this behavior the so far used linear regression between the temperatures and the displacements is insufficient. Therefore, in this study we test the hypothesis whether we can reliably predict such thermal displacements via nonlinear temperature-displacement regression functions. These functions are estimated firstly from learning measurements using the alternating conditional expectation (ACE) algorithm and then tested on independent data sets. First, we analyze data that were generated by a finite element spindle model. We find that our approach is a powerful tool to describe the relation between temperatures and displacements for simulated data. Next, we analyze the temperature-displacement relationship in a silent real experimental setup, where the tool system is thermally forced. Again, the ACE-algorithm is powerful to estimate the deformation with high precision. The corresponding errors obtained by using the nonlinear regression approach are 10-fold lower in comparison to multiple linear regression analysis. Finally, we investigate the thermal behavior of a modular tool system in a working milling machine and get again promising results. The thermally inducedaccuracy using this nonlinear regression analysis. Therefore, this approach seems to be very useful for the development of new modular tool systems. errors can be estimated with 1-2 micrometer
In the last decade, there has been an increasing interest in compensating thermally induced errors to improve the manufacturing accuracy of modular tool systems. These modular tool systems are interfaces between spindle and workpiece and consist of several complicatedly formed parts. Their thermal behavior is dominated by nonlinearities, delay and hysteresis effects even in tools with simpler geometry and it is difficult to describe it theoretically. Due to the dominant nonlinear nature of this behavior the so far used linear regression between the temperatures and the displacements is insufficient. Therefore, in this study we test the hypothesis whether we can reliably predict such thermal displacements via nonlinear temperature-displacement regression functions. These functions are estimated firstly from learning measurements using the alternating conditional expectation (ACE) algorithm and then tested on independent data sets. First, we analyze data that were generated by a finite element spindle model. We find that our approach is a powerful tool to describe the relation between temperatures and displacements for simulated data. Next, we analyze the temperature-displacement relationship in a silent real experimental setup, where the tool system is thermally forced. Again, the ACE-algorithm is powerful to estimate the deformation with high precision. The corresponding errors obtained by using the nonlinear regression approach are 10-fold lower in comparison to multiple linear regression analysis. Finally, we investigate the thermal behavior of a modular tool system in a working milling machine and get again promising results. The thermally induced errors can be estimated with 1-2${mu m}$ accuracy using this nonlinear regression analysis. Therefore, this approach seems to be very useful for the development of new modular tool systems.
Plain Language Summary Cassini flew through the gap between Saturn and its rings for 22 times before plunging into the atmosphere of Saturn, ending its 20-year mission. The radio and plasma waves instrument on board Cassini helped quantify the dust hazard in this previously unexplored region. The measured density of large dust particles was much lower than expected, allowing high-value science observations during the subsequent Grand Finale orbits.
We compiled global occurrence data sets of 13 congeneric sexual and apomictic species pairs, and used principal components analysis (PCA) and kernel smoothers to compare changes in climatic niche optima, breadths and unfilling/expansion between native and alien ranges. Niche change metrics were compared between sexual and apomictic species. All 26 species showed changes in niche optima and/or breadth and 14 species significantly expanded their climatic niches. However, we found no effect of the reproductive system on niche dynamics. Instead, species with narrower native niches showed higher rates of niche expansion in the alien ranges. Our results suggest that niche shifts are frequent in plant invasions but evolutionary potential may not be of major importance for such shifts. Niche dynamics rather appear to be driven by changes of the realized niche without adaptive change of the fundamental climatic niche.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
Amonchquite dyke, in the vicinity of Loch Roag, Lewis, Outer Hebrides has an unusually enriched chemistry, and contains a unique assemblage of megacrysts and xenoliths from the lithosphere of the Hebridean craton. A Ar-40/Ar-39 plateau age of 45.2 +/- 0.2 Ma (2 sigma) of a phlogopite megacryst from the dyke overlaps an earlier reported K-Ar age, and confirms that the British Palaeogene Igneous Province extended into the Eocene. Similar late low-volume melts were erupted in the Eocene and Oligocene in West and East Greenland, suggesting that such late-stage magmatic rejuvenescence is a widespread feature across the North Atlantic Igneous Province.
We used single-molecule FRET in combination with other biophysical methods and molecular simulations to investigate the effect of temperature on the dimensions of unfolded proteins. With singlemolecule FRET, this question can be addressed even under nearnative conditions, where most molecules are folded, allowing us to probe a wide range of denaturant concentrations and temperatures. We find a compaction of the unfolded state of a small cold shock protein with increasing temperature in both the presence and the absence of denaturant, with good agreement between the results from single-molecule FRET and dynamic light scattering. Although dissociation of denaturant from the polypeptide chain with increasing temperature accounts for part of the compaction, the results indicate an important role for additional temperaturedependent interactions within the unfolded chain. The observation of a collapse of a similar extent in the extremely hydrophilic, intrinsically disordered protein prothymosin suggests that the hydrophobic effect is not the sole source of the underlying interactions. Circular dichroism spectroscopy and replica exchange molecular dynamics simulations in explicit water show changes in secondary structure content with increasing temperature and suggest a contribution of intramolecular hydrogen bonding to unfolded state collapse.
Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother–child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 Â 10 À8 . In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.
X-ray free electron lasers (XFELs) enable unprecedented new ways to study the electronic structure and dynamics of transition metal systems. L-edge absorption spectroscopy is a powerful technique for such studies and the feasibility of this method at XFELs for solutions and solids has been demonstrated. However, the required x-ray bandwidth is an order of magnitude narrower than that of self-amplified spontaneous emission (SASE), and additional monochromatization is needed. Here we compare L-edge x-ray absorption spectroscopy (XAS) of a prototypical transition metal system based on monochromatizing the SASE radiation of the linac coherent light source (LCLS) with a new technique based on self-seeding of LCLS. We demonstrate how L-edge XAS can be performed using the self-seeding scheme without the need of an additional beam line monochromator. We show how the spectral shape and pulse energy depend on the undulator setup and how this affects the x-ray spectroscopy measurements. (C) 2016 Optical Society of America
L-edge spectroscopy of 3d transition metals provides important electronic structure information and has been used in many fields. However, the use of this method for studying dilute aqueous systems, such as metalloenzymes, has not been prevalent because of severe radiation damage and the lack of suitable detection systems. Here we present spectra from a dilute Mn aqueous solution using a high-transmission zone-plate spectrometer at the Linac Coherent Light Source (LCLS). The spectrometer has been optimized for discriminating the Mn L-edge signal from the overwhelming 0 K-edge background that arises from water and protein itself, and the ultrashort LCLS X-ray pulses can outrun X-ray induced damage. We show that the deviations of the partial-fluorescence yield-detected spectra from the true absorption can be well modeled using the state-dependence of the fluorescence yield, and discuss implications for the application of our concept to biological samples.
Thermally driven chemistry as well as materials’ functionality are determined by the potential energy surface of a systems electronic ground state. This makes the potential energy surface a central and powerful concept in physics, chemistry and materials science. However, direct experimental access to the potential energy surface locally around atomic centers and to its long-range structure are lacking. Here we demonstrate how sub-natural linewidth resonant inelastic soft x-ray scattering at vibrational resolution is utilized to determine ground state potential energy surfaces locally and detect long-range changes of the potentials that are driven by local modifications. We show how the general concept is applicable not only to small isolated molecules such as O2 but also to strongly interacting systems such as the hydrogen bond network in liquid water. The weak perturbation to the potential energy surface through hydrogen bonding is observed as a trend towards softening of the ground state potential around the coordinating atom. The instrumental developments in high resolution resonant inelastic soft x-ray scattering are currently accelerating and will enable broad application of the presented approach. With this multidimensional potential energy surfaces that characterize collective phenomena such as (bio)molecular function or high-temperature superconductivity will become accessible in near future.
The thermal behavior of poly(methoxydiethylenglycol acrylate) (PMDEGA) is studied in thin hydrogel films on solid supports and is compared with the behavior in aqueous solution. The PMDEGA hydrogel film thickness is varied from 2 to 422 nm. Initially, these films are homogenous, as measured with optical microscopy, atomic force microscopy, X-ray reflectivity, and grazing-incidence small-angle X-ray scattering (GISAXS). However, they tend to de-wet when stored under ambient conditions. Along the surface normal, no long-ranged correlations between substrate and film surface are detected with GISAXS, due to the high mobility of the polymer at room temperature. The swelling of the hydrogel films as a function of the water vapor pressure and the temperature are probed for saturated water vapor pressures between 2,380 and 3,170 Pa. While the swelling capability is found to increase with water vapor pressure, swelling in dependence on the temperature revealed a collapse phase transition of a lower critical solution temperature type. The transition temperature decreases from 40.6 A degrees C to 36.6 A degrees C with increasing film thickness, but is independent of the thickness for very thin films below a thickness of 40 nm. The observed transition temperature range compares well with the cloud points observed in dilute (0.1 wt.%) and semi-dilute (5 wt.%) solution which decrease from 45 A degrees C to 39 A degrees C with increasing concentration.
A 2-fold thermoresponsive diblock copolymer PSPP430-b-PNIPAM(200) consisting of a zwitterionic polysulfobetaine (PSPP) block and a nonionic poly(N-isopropylacrylamide) (PNIPAM) block is prepared by successive RAFT polymerizations. In aqueous solution, the corresponding homopolymers PSPP and PNIPAM feature both upper and lower critical solution temperature (UCST and LCST) behavior, respectively. The diblock copolymer exhibits thermally induced "schizophrenic" aggregation behavior in aqueous solutions. Moreover, the ion sensitivity of the, cloud point of the zwitterionic PSPP block to both the ionic strength and the nature of the salt offers the possibility to create switchable systems which respond sensitively to changes of the temperature and of the electrolyte type and concentration. The diblock copolymer solutions in D2O are investigated by means of turbidimetry and small-angle neutron scattering (SANS) with respect to the phase behavior and the self-assembled structures in dependence on temperature and electrolyte content. Marked, differences of the aggregation below the UCST-type and above the LCST-type transition are observed. The addition of a small amount of NaBr (0.004 M) does not affect the overall behavior, and only the UCST-type transition and aggregate structures are slightly altered, reflecting the well-known ion sensitivity of the zwitterionic PSPP block.
Pak choi (Brassica rapa subsp. chinensis) is rich in secondary metabolites and contains numerous antioxidants, including flavonoids; hydroxycinnamic acids; carotenoids; chlorophylls; and glucosinolates, which can be hydrolyzed to epithionitriles, nitriles, or isothiocyanates. Here, we investigate the effect of reduced exposure to ultraviolet B (UVB) and UV (UVA and UVB) light at four different developmental stages of pak choi. We found that both the plant morphology and secondary metabolite profiles were affected by reduced exposure to UVB and UV, depending on the plant’s developmental stage. In detail, mature 15- and 30-leaf plants had higher concentrations of flavonoids, hydroxycinnamic acids, carotenoids, and chlorophylls, whereas sprouts contained high concentrations of glucosinolates and their hydrolysis products. Dry weights and leaf areas increased as a result of reduced UVB and low UV. For the flavonoids and hydroxycinnamic acids in 30-leaf plants, less complex compounds were favored, for example, sinapic acid acylated kaempferol triglycoside instead of the corresponding tetraglycoside. Moreover, also in 30-leaf plants, zeaxanthin, a carotenoid linked to protection during photosynthesis, was increased under low UV conditions. Interestingly, most glucosinolates were not affected by reduced UVB and low UV conditions. However, this study underlines the importance of 4-(methylsulfinyl)butyl glucosinolate in response to UVA and UVB exposure. Further, reduced UVB and low UV conditions resulted in higher concentrations of glucosinolate-derived nitriles. In conclusion, exposure to low doses of UVB and UV from the early to late developmental stages did not result in overall lower concentrations of plant secondary metabolites.
Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe
(2020)
Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that similar to 75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least onethird of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.