Search

The mechanism of fermionic pairing is the key to understanding various phenomena such as high-temperature superconductivity and the pseudogap phase in cuprate materials. We study the pair correlations in the attractive Hubbard model using ultracold fermions in a two-dimensional optical lattice. By combining the fluctuation-dissipation theorem and the compressibility equation of state, we extract the interacting pair-correlation functions and deduce a characteristic length scale of pairs as a function of interaction and density filling. At sufficiently low filling and weak onsite interaction, we observe that the pair correlations extend over a few lattice sites even at temperatures above the superfluid transition temperature.

We measure entropy and short-range correlations of ultracold fermionic atoms in an optical lattice for a range of interaction strengths, temperatures, and fillings. In particular, we extract the mutual information between a single lattice site and the rest of the system from a comparison between the reduced density matrix of a single lattice site and the thermodynamic entropy. Moreover, we determine the single-particle density matrix between nearest neighbors from thermodynamic observables and show that even in a strongly interacting Mott insulator fermions are significantly delocalized over short distances in the lattice.

Whole-body electromyostimulation has proven to be a highly effective alternative to conventional resistance-type exercise training. However, due to adverse effects in the past, very extensive contraindications have been put in place for the commercial, non-medical WB-EMS market. Considering recent positive innovations e.g., federal regulation, mandatory trainer education, revised guidelines, and new scientific studies on WB-EMS application, we believe that a careful revision of the very restrictive contraindications on WB-EMS is needed. This applies all the more because many cohorts with limited options for conventional exercise have so far been excluded. During a first meeting of an evidence-based consensus process, stakeholders from various backgrounds (e.g., research, education, application) set the priorities for revising the contraindications. We decided to focus on four categories of absolute contraindications: “Arteriosclerosis, arterial circulation disorders”, “Diabetes mellitus” (DM), “Tumor and cancer” (TC), “Neurologic diseases, neuronal disorders, epilepsy”. Based on scientific studies, quality criteria, safety aspects and benefit/risk assessment of the category, DM and TC were moved to the relative contraindication catalogue, while arteriosclerosis/arterial circulation disorders and neurologic diseases/neuronal disorders/epilepsy were still considered as absolute contraindications. While missing evidence suggests maintaining the status of neurologic diseases/neuronal disorders as an absolute contraindication, the risk/benefit-ratio does not support the application of WB-EMS in people with arteriosclerosis/arterial circulation diseases. Despite these very cautious modifications, countries with less restrictive structures for non-medical WB-EMS should consider our approach critically before implementing the present revisions. Considering further the largely increased amount of WB-EMS trials we advice regular updates of the present contraindication list.

A new global dataset of annually averaged ultrafine particle (UFP) concentrations at the Earth's surface for the years 2015–2017 has been developed through numerical simulations using the ECHAM/MESSy Atmospheric Chemistry model (EMAC). We present total and size-resolved concentrations along with their interannual variability. Size distributions of emitted particles from the contributing source sectors have been derived based on literature reports. The model results of UFP concentrations are evaluated using particle size distribution and particle number concentration measurements from available datasets and the literature. While we obtain reasonable agreement between the model results and observations (logarithmic-scale correlation of r=0.76 for non-remote, polluted regions), the highest values of observed, street-level UFP concentrations are systematically underestimated, whereas in rural environments close to urban areas the model generally overestimates observed UFP concentrations. As the relatively coarse global model does not resolve concentration gradients in urban centres and industrial UFP hotspots, high-resolution data of anthropogenic emissions are used to account for such differences in each model grid box, obtaining UFP concentrations with unprecedented 0.1∘×0.1∘ horizontal resolution at the Earth's surface. This observation-guided downscaling further improves the agreement with observations, leading to an increase in the logarithmic-scale correlation between observed and simulated UFP concentrations to r=0.84 in polluted environments (and 0.95 in all regions), a decrease in the root mean squared logarithmic error (from 0.57 to 0.43), and removal of discrepancies associated with air quality and population density gradients within the model grid boxes. The model results are made publicly available for studies on public health and other impacts of atmospheric UFPs, as well as for intercomparison with other regional and global models and datasets.

Above-ground cosmic-ray neutron sensing (CRNS) allows for the non-invasive estimation of the field-scale soil moisture content in the upper decimetres of the soil. However, large parts of the deeper vadose zone remain outside of its observational window. Retrieving soil moisture information from these deeper layers requires extrapolation, modelling or other methods, all of which come with methodological challenges. Against this background, we investigate CRNS for downhole soil moisture measurements in deeper layers of the vadose zone. To render calibration with in situ soil moisture measurements unnecessary, we rescaled neutron intensities observed below the terrain surface with intensities measured above a waterbody. An experimental set-up with a CRNS sensor deployed at different depths of up to 10 m below the surface in a groundwater observation well combined with particle transport simulations revealed the response of downhole thermal neutron intensities to changes in the soil moisture content at the depth of the downhole neutron detector as well as in the layers above it. The simulation results suggest that the sensitive measurement radius of several decimetres, which depends on soil moisture and soil bulk density, exceeds that of a standard active neutron probe (which is only about 30 cm). We derived transfer functions to estimate downhole neutron signals from soil moisture information, and we describe approaches for using these transfer functions in an inverse way to derive soil moisture from the observed neutron signals. The in situ neutron and soil moisture observations confirm the applicability of these functions and prove the concept of passive downhole soil moisture estimation, even at larger depths, using cosmic-ray neutron sensing.

Cosmic-ray neutron sensing (CRNS) allows for the estimation of root-zone soil water content (SWC) at the scale of several hectares. In this paper, we present the data recorded by a dense CRNS network operated from 2019 to 2022 at an agricultural research site in Marquardt, Germany – the first multi-year CRNS cluster. Consisting, at its core, of eight permanently installed CRNS sensors, the cluster was supplemented by a wealth of complementary measurements: data from seven additional temporary CRNS sensors, partly co-located with the permanent ones; 27 SWC profiles (mostly permanent); two groundwater observation wells; meteorological records; and Global Navigation Satellite System reflectometry (GNSS-R). Complementary to these continuous measurements, numerous campaign-based activities provided data by mobile CRNS roving, hyperspectral imagery via UASs, intensive manual sampling of soil properties (SWC, bulk density, organic matter, texture, soil hydraulic properties), and observations of biomass and snow (cover, depth, and density). The unique temporal coverage of 3 years entails a broad spectrum of hydro-meteorological conditions, including exceptional drought periods and extreme rainfall but also episodes of snow coverage, as well as a dedicated irrigation experiment. Apart from serving to advance CRNS-related retrieval methods, this data set is expected to be useful for various disciplines, for example, soil and groundwater hydrology, agriculture, or remote sensing. Hence, we show exemplary features of the data set in order to highlight the potential for such subsequent studies. The data are available at doi.org/10.23728/b2share.551095325d74431881185fba1eb09c95 (Heistermann et al., 2022b).

This paper presents a new theoretical approach to estimate the contribution of distant areas to the measurement signal of cosmic-ray neutron detectors for snow and soil moisture monitoring. The algorithm is based on the local neutron production and the transport mechanism, given by the neutron–moisture relationship and the radial intensity function, respectively. The purely analytical approach has been validated with physics-based neutron transport simulations for heterogeneous soil moisture patterns, exemplary landscape features, and remote fields at a distance. We found that the method provides good approximations of simulated signal contributions in patchy soils with typical deviations of less than 1 %. Moreover, implications of this concept have been investigated for the neutron–moisture relationship, where the signal contribution of an area has the potential to explain deviating shapes of this curve that are often reported in the literature. Finally, the method has been used to develop a new practical footprint definition to express whether or not a distant area's soil moisture change is actually detectable in terms of measurement precision. The presented concepts answer long-lasting questions about the influence of distant landscape structures in the integral footprint of the sensor without the need for computationally expensive simulations. The new insights are highly relevant to support signal interpretation, data harmonization, and sensor calibration and will be particularly useful for sensors positioned in complex terrain or on agriculturally managed sites.

The understanding of neutron transport by Monte Carlo simulations led to major advancements towards precise interpretation of measurements. URANOS (Ultra Rapid Neutron-Only Simulation) is a free software package which has been developed in the last few years in cooperation with particle physics and environmental sciences, specifically for the purposes of cosmic-ray neutron sensing (CRNS). Its versatile user interface and input/output scheme tailored for CRNS applications offers hydrologists straightforward access to model individual scenarios and to directly perform advanced neutron transport calculations. The geometry can be modeled layer-wise, whereas in each layer a voxel geometry is extruded using a two-dimensional map from pixel images representing predefined materials and allowing for the construction of objects on the basis of pixel graphics without a three-dimensional editor. It furthermore features predefined cosmic-ray neutron spectra and detector configurations and also allows for a replication of important site characteristics of study areas – from a small pond to the catchment scale. The simulation thereby gives precise answers to questions like from which location do neutrons originate? How do they propagate to the sensor? What is the neutron's response to certain environmental changes? In recent years, URANOS has been successfully employed by a number of studies, for example, to calculate the cosmic-ray neutron footprint, signals in complex geometries like mobile applications on roads, urban environments and snow patterns.

Accurate soil moisture (SM) monitoring is key in irrigation as it can greatly improve water use efficiency. Recently, cosmic-ray neutron sensors (CRNSs) have been recognized as a promising tool in SM monitoring due to their large footprint of several hectares. CRNSs also have great potential for irrigation applications, but few studies have investigated whether irrigation monitoring with CRNSs is feasible, especially for irrigated fields with a size smaller than the CRNS footprint. Therefore, the aim of this study is to use Monte Carlo simulations to investigate the feasibility of monitoring irrigation with CRNSs. This was achieved by simulating irrigation scenarios with different field dimensions (from 0.5 to 8 ha) and SM variations between 0.05 and 0.50 cm3 cm−3. Moreover, the energy-dependent response functions of eight moderators with different high-density polyethylene (HDPE) thickness or additional gadolinium thermal shielding were investigated. It was found that a considerable part of the neutrons that contribute to the CRNS footprint can originate outside an irrigated field, which is a challenge for irrigation monitoring with CRNSs. The use of thin HDPE moderators (e.g. 5 mm) generally resulted in a smaller footprint and thus stronger contributions from the irrigated area. However, a thicker 25 mm HDPE moderator with gadolinium shielding improved SM monitoring in irrigated fields due to a higher sensitivity of neutron counts with changing SM. This moderator and shielding set-up provided the highest chance of detecting irrigation events, especially when the initial SM was relatively low. However, variations in SM outside a 0.5 or 1 ha irrigated field (e.g. due to irrigation of neighbouring fields) can affect the count rate more than SM variations due to irrigation. This suggests the importance of retrieving SM data from the surrounding of a target field to obtain more meaningful information for supporting irrigation management, especially for small irrigated fields.

The branching ratio of the structure dependent (SD) radiative K+→e+νeγ decay relative to that of the K+→e+νe(γ) decay including the internal bremsstrahlung (IB) process (Ke2(γ)) has been measured in the J-PARC E36 experiment using plastic scintillator/lead sandwich detectors, in contrast to the previous E36 measurement, which used a CsI(Tl) calorimeter. In the analysis, the effect of IB was also taken into account in the SD radiative decay as Ke2γ(γ)SD. By combining the new data with the previous E36 result after revision for the IB correction for Ke2γ(γ)SD, a new value Br(Ke2γ(γ)SD)/Br(Ke2(γ))=1.20±0.07 has been determined. This is consistent with a recent lattice QCD calculation, but larger than the expectation of Chiral Perturbation Theory (ChPT) at order O(p4) and the previous KLOE value. Using the method to relate form factor and branching ratio described in the KLOE paper, the present result is also consistent with the form factor prediction based on a gauged nonlocal chiral quark model, but larger than that from ChPT at order O(p6).

Aerosols influence the Earth's energy balance directly by modifying the radiation transfer and indirectly by altering the cloud microphysics. Anthropogenic aerosol emissions dropped considerably when the global COVID-19 pandemic resulted in severe restraints on mobility, production, and public life in spring 2020. We assess the effects of these reduced emissions on direct and indirect aerosol radiative forcing over Europe, excluding contributions from contrails. We simulate the atmospheric composition with the ECHAM5/MESSy Atmospheric Chemistry (EMAC) model in a baseline (business-as-usual) and a reduced emission scenario. The model results are compared to aircraft observations from the BLUESKY aircraft campaign performed in May–June 2020 over Europe. The model agrees well with most of the observations, except for sulfur dioxide, particulate sulfate, and nitrate in the upper troposphere, likely due to a biased representation of stratospheric aerosol chemistry and missing information about volcanic eruptions. The comparison with a baseline scenario shows that the largest relative differences for tracers and aerosols are found in the upper troposphere, around the aircraft cruise altitude, due to the reduced aircraft emissions, while the largest absolute changes are present at the surface. We also find an increase in all-sky shortwave radiation of 0.21 ± 0.05 W m−2 at the surface in Europe for May 2020, solely attributable to the direct aerosol effect, which is dominated by decreased aerosol scattering of sunlight, followed by reduced aerosol absorption caused by lower concentrations of inorganic and black carbon aerosols in the troposphere. A further increase in shortwave radiation from aerosol indirect effects was found to be much smaller than its variability. Impacts on ice crystal concentrations, cloud droplet number concentrations, and effective crystal radii are found to be negligible.

To address current challenges related to climate change, novel concepts, such as engine-based polygeneration under fuel-rich conditions, have recently been developed. In this context, understanding and validation of the associated chemical kinetics are a key factor for prediction and optimizations. In this work, the combined effect of ozone and DME as additives on the partial oxidation of natural gas mixtures is investigated in a plug-flow reactor at a pressure of 4 bar and at temperatures ranging from 373 to 973 K. Double-imaging photoelectron photoion coincidence (i2PEPICO) spectroscopy measurements are presented to study the conversion of the reactants and the formation of main products, and to identify important intermediates responsible for the low temperature chemistry phenomena and ignition characteristics of the natural gas/dimethyl ether/ozone mixture. Among the activation effect of ozone, the temperature-variant ozone dissociation at elevated pressures up to 20 bar is studied for the first time, revealing the start of ozone decomposition at 423 K in the investigated pressure range. In addition, the ozone decomposition is shown to be slightly pressure-dependent in the pressure range between 1 and 20 bar with lower ozone conversions at higher pressures. The experimental results are compared with model predictions using literature reaction mechanisms for validation and further analysis. The ozone decomposition initiates fuel conversion and the formation of oxygenates and hydroperoxides at very low temperatures, i.e., 423 K, resulting in an overall three-stage oxidation process at ∼450 K (1. stage), ∼550 K (2. stage), and ∼750 K (3. stage). Also, the overall fuel conversion is enhanced in the intermediate temperature range (between 550 K and 750 K) by up to 40%-points. The hydroperoxides, among other species, are clearly identified by mass-selected threshold photoelectron spectra from the literature. Excellent agreement between experiments and simulations is found, while deviations are observed for some oxygenates at very low temperatures showing the need for further model improvements.

An updated and expanded representation of organics in the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry) has been evaluated. First, the comprehensive Mainz Organic Mechanism (MOM) in the submodel MECCA (Module Efficiently Calculating the Chemistry of the Atmosphere) was activated with explicit degradation of organic species up to five carbon atoms and a simplified mechanism for larger molecules. Second, the ORACLE submodel (version 1.0) now considers condensation on aerosols for all organics in the mechanism. Parameterizations for aerosol yields are used only for the lumped species that are not included in the explicit mechanism. The simultaneous usage of MOM and ORACLE allows an efficient estimation of not only the chemical degradation of the simulated volatile organic compounds but also the contribution of organics to the growth and fate of (organic) aerosol, with the complexity of the mechanism largely increased compared to EMAC simulations with more simplified chemistry. The model evaluation presented here reveals that the OH concentration is reproduced well globally, whereas significant biases for observed oxygenated organics are present. We also investigate the general properties of the aerosols and their composition, showing that the more sophisticated and process-oriented secondary aerosol formation does not degrade the good agreement of previous model configurations with observations at the surface, allowing further research in the field of gas–aerosol interactions.

Abstract Background Early support for children with developmental disabilities is crucial but frequently unavailable in low-resource settings. We conducted a mixed-methods evaluation to assess the feasibility, acceptability, and impact of a programme of early detection and intervention for young children with developmental disabilities in Western Uganda. Methods Early child development training for healthcare workers (HCWs) was implemented in three rural districts, and attendance was tracked. HCW knowledge and confidence were assessed pre-/post-intervention, and referral numbers tracked to evaluate impact. Facilitators were trained and mentored to deliver a participatory, group, early intervention programme (EIP) for young children with developmental disabilities and their families. Facilitators were tracked as they were identified, trained, and delivered the intervention, and attendance of families was tracked. Pre−/post-intervention assessments evaluated changes in family quality of life (PedsQL 2.0, Family Impact Module), and child nutritional outcomes. Focus group discussions with stakeholders also assessed feasibility, acceptability and impact. Results Overall, 93 HCWs from 45 healthcare facilities received training. In the pre−/post-evaluation, median knowledge and confidence scores increased significantly (from 4.0 to 7.0 and from 2.7 to 4.7, respectively (p

Cosmic-ray neutron sensing (CRNS) is a non-invasive tool for measuring hydrogen pools such as soil moisture, snow or vegetation. The intrinsic integration over a radial hectare-scale footprint is a clear advantage for averaging out small-scale heterogeneity, but on the other hand the data may become hard to interpret in complex terrain with patchy land use. This study presents a directional shielding approach to prevent neutrons from certain angles from being counted while counting neutrons entering the detector from other angles and explores its potential to gain a sharper horizontal view on the surrounding soil moisture distribution. Using the Monte Carlo code URANOS (Ultra Rapid Neutron-Only Simulation), we modelled the effect of additional polyethylene shields on the horizontal field of view and assessed its impact on the epithermal count rate, propagated uncertainties and aggregation time. The results demonstrate that directional CRNS measurements are strongly dominated by isotropic neutron transport, which dilutes the signal of the targeted direction especially from the far field. For typical count rates of customary CRNS stations, directional shielding of half-spaces could not lead to acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates should be feasible.

Cosmic-ray neutron sensing (CRNS) allows for non-invasive soil moisture estimations at the field scale. The derivation of soil moisture generally relies on secondary cosmic-ray neutrons in the epithermal to fast energy ranges. Most approaches and processing techniques for observed neutron intensities are based on the assumption of homogeneous site conditions or of soil moisture patterns with correlation lengths shorter than the measurement footprint of the neutron detector. However, in view of the non-linear relationship between neutron intensities and soil moisture, it is questionable whether these assumptions are applicable. In this study, we investigated how a non-uniform soil moisture distribution within the footprint impacts the CRNS soil moisture estimation and how the combined use of epithermal and thermal neutrons can be advantageous in this case. Thermal neutrons have lower energies and a substantially smaller measurement footprint around the sensor than epithermal neutrons. Analyses using the URANOS (Ultra RApid Neutron-Only Simulation) Monte Carlo simulations to investigate the measurement footprint dynamics at a study site in northeastern Germany revealed that the thermal footprint mainly covers mineral soils in the near-field to the sensor while the epithermal footprint also covers large areas with organic soils. We found that either combining the observed thermal and epithermal neutron intensities by a rescaling method developed in this study or adjusting all parameters of the transfer function leads to an improved calibration against the reference soil moisture measurements in the near-field compared to the standard approach and using epithermal neutrons alone. We also found that the relationship between thermal and epithermal neutrons provided an indicator for footprint heterogeneity. We, therefore, suggest that the combined use of thermal and epithermal neutrons offers the potential of a spatial disaggregation of the measurement footprint in terms of near- and far-field soil moisture dynamics.

The global polarization of Λ hyperons along the total orbital angular momentum of a relativistic heavy-ion collision is presented based on the high statistics data samples collected in Au+Au collisions at sNN=2.4 GeV and Ag+Ag at 2.55 GeV with the High-Acceptance Di-Electron Spectrometer (HADES) at GSI, Darmstadt. This is the first measurement below the strangeness production threshold in nucleon-nucleon collisions. Results are reported as a function of the collision centrality as well as a function of the hyperon's transverse momentum (pT) and rapidity (yCM) for the range of centrality 0–40%. We observe a strong centrality dependence of the polarization with an increasing signal towards peripheral collisions. For mid-central (20 – 40%) collisions the polarization magnitudes are 〈PΛ〉(%)=6.8±1.3(stat.)±2.1(syst.) for Au+Au and 〈PΛ〉(%)=6.2±0.4(stat.)±0.6(syst.) for Ag+Ag, which are the largest values observed so far. This observation thus provides a continuation of the increasing trend previously observed by STAR and contrasts expectations from recent theoretical calculations predicting a maximum in the region of collision energies about 3 GeV. The observed polarization is of a similar magnitude as predicted by 3D-fluid-dynamics and the UrQMD plus thermal vorticity model and significantly above results from the AMPT model.

Current state-of-the-art regional numerical weather prediction (NWP) models employ kilometer-scale horizontal grid resolutions, thereby simulating convection within the grey zone. Increasing resolution leads to resolving the 3D motion field and has been shown to improve the representation of clouds and precipitation. Using a hectometer-scale model in forecasting mode on a large domain therefore offers a chance to study processes that require the simulation of the 3D motion field at small horizontal scales, such as deep summertime moist convection, a notorious problem in NWP. We use the ICOsahedral Nonhydrostatic weather and climate model in large-eddy simulation mode (ICON-LEM) to simulate deep moist convection and distinguish between scattered, large-scale dynamically forced, and frontal convection. We use different ground- and satellite-based observational data sets, which supply information on ice water content and path, ice cloud cover, and cloud-top height on a similar scale as the simulations, in order to evaluate and constrain our model simulations. We find that the timing and geometric extent of the convectively generated cloud shield agree well with observations, while the lifetime of the convective anvil was, at least in one case, significantly overestimated. Given the large uncertainties of individual ice water path observations, we use a suite of observations in order to better constrain the simulations. ICON-LEM simulates a cloud ice water path that lies between the different observational data sets, but simulations appear to be biased towards a large frozen water path (all frozen hydrometeors). Modifications of parameters within the microphysical scheme have little effect on the bias in the frozen water path and the longevity of the anvil. In particular, one of our convective days appeared to be very sensitive to the initial and boundary conditions, which had a large impact on the convective triggering but little impact on the high frozen water path and long anvil lifetime bias. Based on this limited set of sensitivity experiments, the evolution of locally forced convection appears to depend more on the uncertainty of the large-scale dynamical state based on data assimilation than of microphysical parameters. Overall, we judge ICON-LEM simulations of deep moist convection to be very close to observations regarding the timing, geometrical structure, and cloud ice water path of the convective anvil, but other frozen hydrometeors, in particular graupel, are likely overestimated. Therefore, ICON-LEM supplies important information for weather forecasting and forms a good basis for parameterization development based on physical processes or machine learning.

The structure dependent radiative K+→e+νγ (Ke2γSD+) decay was investigated with stopped positive kaons. The e+ momentum spectra containing 574±30 Ke2γSD+ events with a K+→μ+ν (Kμ2) background of 28±19 events were measured with and without a photon in coincidence and analyzed with Monte Carlo simulations for acceptance and detector response to extract the ratio of the branching ratio of the Ke2γSD+ decay and the K+→e+ν decay including the internal bremsstrahlung process (Ke2(γ)). A value of Br(Ke2γSD+)/Br(Ke2(γ))=1.12±0.07stat±0.04syst was obtained. This indicates a partial branching ratio, Br(Ke2γSD+,pe>200MeV/c,Eγ>10MeV)/Br(Kμ2)=(1.85±0.11stat±0.07syst)×10−5, which is 25% (∼2.5σ) higher than the previous experimental result.

Monitoring soil moisture is still a challenge: it varies strongly in space and time and at various scales while conventional sensors typically suffer from small spatial support. With a sensor footprint up to several hectares, cosmic-ray neutron sensing (CRNS) is a modern technology to address that challenge. So far, the CRNS method has typically been applied with single sensors or in sparse national-scale networks. This study presents, for the first time, a dense network of 24 CRNS stations that covered, from May to July 2019, an area of just 1 km2: the pre-Alpine Rott headwater catchment in Southern Germany, which is characterized by strong soil moisture gradients in a heterogeneous landscape with forests and grasslands. With substantially overlapping sensor footprints, this network was designed to study root-zone soil moisture dynamics at the catchment scale. The observations of the dense CRNS network were complemented by extensive measurements that allow users to study soil moisture variability at various spatial scales: roving (mobile) CRNS units, remotely sensed thermal images from unmanned areal systems (UASs), permanent and temporary wireless sensor networks, profile probes, and comprehensive manual soil sampling. Since neutron counts are also affected by hydrogen pools other than soil moisture, vegetation biomass was monitored in forest and grassland patches, as well as meteorological variables; discharge and groundwater tables were recorded to support hydrological modeling experiments. As a result, we provide a unique and comprehensive data set to several research communities: to those who investigate the retrieval of soil moisture from cosmic-ray neutron sensing, to those who study the variability of soil moisture at different spatiotemporal scales, and to those who intend to better understand the role of root-zone soil moisture dynamics in the context of catchment and groundwater hydrology, as well as land–atmosphere exchange processes. The data set is available through the EUDAT Collaborative Data Infrastructure and is split into two subsets: https://doi.org/10.23728/b2share.282675586fb94f44ab2fd09da0856883 (Fersch et al., 2020a) and https://doi.org/10.23728/b2share.bd89f066c26a4507ad654e994153358b (Fersch et al., 2020b).

Abstract Background Improved, multimodal treatment strategies have been shown to increase cure rates in cancer patients. Those who survive cancer as a child, adolescent or young adult (CAYA), are at a higher risk for therapy-, or disease-related, late or long-term effects. The CARE for CAYA-Program has been developed to comprehensively assess any potential future problems, to offer need-based preventative interventions and thus to improve long-term outcomes in this particularly vulnerable population. Methods The trial is designed as an adaptive trial with an annual comprehensive assessment followed by needs stratified, modular interventions, currently including physical activity, nutrition and psycho-oncology, all aimed at improving the lifestyle and/or the psychosocial situation of the patients. Patients, aged 15–39 years old, with a prior cancer diagnosis, who have completed tumour therapy and are in follow-up care, and who are tumour free, will be included. At baseline (and subsequently on an annual basis) the current medical and psychosocial situation and lifestyle of the participants will be assessed using a survey compiled of various validated questionnaires (e.g. EORTC QLQ C30, NCCN distress thermometer, PHQ-4, BSA, nutrition protocol) and objective parameters (e.g. BMI, WHR, co-morbidities like hyperlipidaemia, hypertension, diabetes), followed by basic care (psychological and lifestyle consultation). Depending on their needs, CAYAs will be allocated to preventative interventions in the above-mentioned modules over a 12-month period. After 1 year, the assessment will be repeated, and further interventions may be applied as needed. During the initial trial phase, the efficacy of this approach will be compared to standard care (waiting list with intervention in the following year) in a randomized study. During this phase, 530 CAYAs will be included and 320 eligible CAYAs who are willing to participate in the interventions will be randomly allocated to an intervention. Overall, 1500 CAYAs will be included and assessed. The programme is financed by the innovation fund of the German Federal Joint Committee and will be conducted at 14 German sites. Recruitment began in January 2018. Discussion CAYAs are at high risk for long-term sequelae. Providing structured interventions to improve lifestyle and psychological situation may counteract against these risk factors. The programme serves to establish uniform regular comprehensive assessments and need-based interventions to improve long-term outcome in CAYA survivors. Trial registration Registered at the German Clinical Trial Register (ID: DRKS00012504, registration date: 19th January 2018).

In this letter we report the first multi-differential measurement of correlated pion-proton pairs from 2 billion Au+Au collisions at sNN=2.42 GeV collected with HADES. In this energy regime the population of Δ(1232) resonances plays an important role in the way energy is distributed between intrinsic excitation energy and kinetic energy of the hadrons in the fireball. The triple differential d3N/dMπ±pdpTdy distributions of correlated π±p pairs have been determined by subtracting the πp combinatorial background using an iterative method. The invariant-mass distributions in the Δ(1232) mass region show strong deviations from a Breit-Wigner function with vacuum width and mass. The yield of correlated pion-proton pairs exhibits a complex isospin, rapidity and transverse-momentum dependence. In the invariant mass range 1.1

Repeated, grid-based forest soil inventories such as the National Forest Soil Inventory of Germany (NFSI) aim, among other things, at detecting changes in soil properties and plant nutrition. In these types of inventories, the only information on soil phosphorus (P) is commonly the total P content. However, total P content in mineral soils of forests is usually not a meaningful variable with respect to predicting the availability of P to trees. Here we tested a modified sequential P extraction according to Hedley (1982) to determine the distribution of different plant-available P fractions in soil samples (at depths of 0–5 and 10–30 cm) from 146 NFSI sites, encompassing a wide variety of soil conditions. In addition, we analyzed relationships between these P fractions and common soil properties such as pH, texture, and soil organic carbon content (SOC). The total P content among our samples ranged from approximately 60 to 2800 mg kg−1. The labile, moderately labile, and stable P fractions contributed to 27 %, 51 %, and 22 % of the total P content, respectively, at a depth of 0–5 cm. At a depth of 10–30 cm, the labile P fractions decreased to 15 %, whereas the stable P fractions increased to 30 %. These changes with depth were accompanied by a decrease in the organic P fractions. High P contents were related to high pH values. While the labile Hedley P pool increased with decreasing pH in absolute and relative terms, the stable Hedley P pool decreased in absolute and relative terms. Increasing SOC in soils led to significant increases in all Hedley P pools and in total P. In sandy soils, the P content across all fractions was lower than in other soil texture types. Multiple linear regression models indicated that Hedley P pools and P fractions were moderately well related to soil properties (with r2 values that were mostly above 0.5), and that the sand content of soils had the strongest influence. Foliar P contents in Pinus sylvestris were reasonably well explained by the labile and moderately labile P pool (r2 = 0.67) but not so for Picea abies and Fagus sylvatica. Foliar P contents in all three species could not be related to specific Hedley P pools. Our study indicates that soil properties such as pH, SOC content, and soil texture may be used to predict certain soil Hedley P pools with different plant availability on the basis of large soil inventories. However, the foliar P contents of tree species cannot be sufficiently well predicted by the soil variables considered here.

Abstract ICON‐A is the new icosahedral nonhydrostatic (ICON) atmospheric general circulation model in a configuration using the Max Planck Institute physics package, which originates from the ECHAM6 general circulation model, and has been adapted to account for the changed dynamical core framework. The coupling scheme between dynamics and physics employs a sequential updating by dynamics and physics, and a fixed sequence of the physical processes similar to ECHAM6. To allow a meaningful initial comparison between ICON‐A and the established ECHAM6‐LR model, a setup with similar, low resolution in terms of number of grid points and levels is chosen. The ICON‐A model is tuned on the base of the Atmospheric Model Intercomparison Project (AMIP) experiment aiming primarily at a well balanced top‐of atmosphere energy budget to make the model suitable for coupled climate and Earth system modeling. The tuning addresses first the moisture and cloud distribution to achieve the top‐of‐atmosphere energy balance, followed by the tuning of the parameterized dynamic drag aiming at reduced wind errors in the troposphere. The resulting version of ICON‐A has overall biases, which are comparable to those of ECHAM6. Problematic specific biases remain in the vertical distribution of clouds and in the stratospheric circulation, where the winter vortices are too weak. Biases in precipitable water and tropospheric temperature are, however, reduced compared to the ECHAM6. ICON‐A will serve as the basis of further development and as the atmosphere component to the coupled model, ICON‐Earth system model (ESM).