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Results on the production of 4He and Image 1 nuclei in Pb–Pb collisions at √sNN=2.76TeV in the rapidity range |y|<1, using the ALICE detector, are presented in this paper. The rapidity densities corresponding to 0–10% central events are found to be dN/dyHe4=(0.8±0.4(stat)±0.3(syst))×10−6 and Image 2, respectively. This is in agreement with the statistical thermal model expectation assuming the same chemical freeze-out temperature (Tchem=156MeV) as for light hadrons. The measured ratio of Image 3 is 1.4±0.8(stat)±0.5(syst).
Transverse momentum (pT ) spectra of charged particles at mid-pseudorapidity in Xe–Xe collisions at √sNN=5.44TeV measured with the ALICE apparatus at the Large Hadron Collider are reported. The kinematic range 0.15<pT<50GeV/c and |η|<0.8 is covered. Results are presented in nine classes of collision centrality in the 0–80% range. For comparison, a pp reference at the collision energy of √s=5.44 TeV is obtained by interpolating between existing pp measurements at √s=5.02 and 7 TeV. The nuclear modification factors in central Xe–Xe collisions and Pb–Pb collisions at a similar center-of-mass energy of √sNN=5.02 TeV, and in addition at 2.76 TeV, at analogous ranges of charged particle multiplicity density 〈dNch/dη〉 show a remarkable similarity at pT>10 GeV/c. The centrality dependence of the ratio of the average transverse momentum 〈pT〉 in Xe–Xe collisions over Pb–Pb collision at √s=5.02 TeV is compared to hydrodynamical model calculations.
The ALICE Collaboration reports the measurement of semi-inclusive distributions of charged-particle jets recoiling from a high-transverse momentum trigger hadron in p–Pb collisions at √sNN=5.02 TeV. Jets are reconstructed from charged-particle tracks using the anti-kT algorithm with resolution parameter R=0.2 and 0.4. A data-driven statistical approach is used to correct the uncorrelated background jet yield. Recoil jet distributions are reported for jet transverse momentum 15<pT,jetch<50GeV/c and are compared in various intervals of p–Pb event activity, based on charged-particle multiplicity and zero-degree neutral energy in the forward (Pb-going) direction. The semi-inclusive observable is self-normalized and such comparisons do not require the interpretation of p–Pb event activity in terms of collision geometry, in contrast to inclusive jet observables. These measurements provide new constraints on the magnitude of jet quenching in small systems at the LHC. In p–Pb collisions with high event activity, the average medium-induced out-of-cone energy transport for jets with R=0.4 and 15<pT,jetch<50GeV/c is measured to be less than 0.4 GeV/c at 90% confidence, which is over an order of magnitude smaller than a similar measurement for central Pb–Pb collisions at √sNN=2.76TeV. Comparison is made to theoretical calculations of jet quenching in small systems, and to inclusive jet measurements in p–Pb collisions selected by event activity at the LHC and in d–Au collisions at RHIC.
We present a measurement of azimuthal correlations between inclusive J/ψ and charged hadrons in p–Pb collisions recorded with the ALICE detector at the CERN LHC. The J/ψ are reconstructed at forward (p-going, 2.03<y<3.53) and backward (Pb-going, −4.46<y<−2.96) rapidity via their μ+μ− decay channel, while the charged hadrons are reconstructed at mid-rapidity (|η|<1.8). The correlations are expressed in terms of associated charged-hadron yields per J/ψ trigger. A rapidity gap of at least 1.5 units is required between the trigger J/ψ and the associated charged hadrons. Possible correlations due to collective effects are assessed by subtracting the associated per-trigger yields in the low-multiplicity collisions from those in the high-multiplicity collisions. After the subtraction, we observe a strong indication of remaining symmetric structures at Δφ≈0 and Δφ≈π, similar to those previously found in two-particle correlations at middle and forward rapidity. The corresponding second-order Fourier coefficient (v2) in the transverse momentum interval between 3 and 6 GeV/c is found to be positive with a significance of about 5σ. The obtained results are similar to the J/ψ v2 coefficients measured in Pb–Pb collisions at sNN=5.02 TeV, suggesting a common mechanism at the origin of the J/ψ v2.
The procedure for the energy calibration of the high granularity electromagnetic calorimeter PHOS of the ALICE experiment is presented. The methods used to perform the relative gain calibration, to evaluate the geometrical alignment and the corresponding correction of the absolute energy scale, to obtain the nonlinearity correction coefficients and finally, to calculate the time-dependent calibration corrections, are discussed and illustrated by the PHOS performance in proton-proton (pp) collisions at √s=13 TeV. After applying all corrections, the achieved mass resolutions for π0 and η mesons for pT > 1.7 GeV/c are σmπ0 = 4.56 ± 0.03 MeV/c2 and σmη = 15.3 ± 1.0 MeV/c2, respectively.
We present a method that enables the identification and analysis of conformational Markovian transition states from atomistic or coarse-grained molecular dynamics (MD) trajectories. Our algorithm is presented by using both analytical models and examples from MD simulations of the benchmark system helix-forming peptide Ala5, and of larger, biomedically important systems: the 15-lipoxygenase-2 enzyme (15-LOX-2), the epidermal growth factor receptor (EGFR) protein, and the Mga2 fungal transcription factor. The analysis of 15-LOX-2 uses data generated exclusively from biased umbrella sampling simulations carried out at the hybrid ab initio density functional theory (DFT) quantum mechanics/molecular mechanics (QM/MM) level of theory. In all cases, our method automatically identifies the corresponding transition states and metastable conformations in a variationally optimal way, with the input of a set of relevant coordinates, by accurately reproducing the intrinsic slowest relaxation rate of each system. Our approach offers a general yet easy-to-implement analysis method that provides unique insight into the molecular mechanism and the rare but crucial (i.e., rate-limiting) transition states occurring along conformational transition paths in complex dynamical systems such as molecular trajectories.
Floodplains play an important role in the terrestrial water cycle and are very important for biodiversity. Therefore, an improved representation of the dynamics of floodplain water flows and storage in global hydrological and land surface models is required. To support model validation, we combined monthly time series of satellite-derived inundation areas (Papa et al., 2010) with data on irrigated rice areas (Portmann et al., 2010). In this way, we obtained global-scale time series of naturally inundated areas (NIA), with monthly values of inundation extent during 1993–2004 and a spatial resolution of 0.5°. For most grid cells (0.5°×0.5°), the mean annual maximum of NIA agrees well with the static open water extent of the Global Lakes and Wetlands database (GLWD) (Lehner and Döll, 2004), but in 16% of the cells NIA is larger than GLWD. In some regions, like Northwestern Europe, NIA clearly overestimates inundated areas, probably because of confounding very wet soils with inundated areas. In other areas, such as South Asia, it is likely that NIA can help to enhance GLWD. NIA data will be very useful for developing and validating a floodplain modeling algorithm for the global hydrological model WGHM. For example, we found that monthly NIAs correlate with observed river discharges.
Floodplains and other wetlands depend on seasonal river flooding and play an important role in the terrestrial water cycle. They influence evapotranspiration, water storage and river discharge dynamics, and they are the habitat of a large number of animals and plants. Thus, to assess the Earth’s system and its changes, a robust understanding of the dynamics of floodplain wetlands including inundated areas, water storages, and water flows is required.
This PhD thesis aims at improving the modeling of large floodplains and wetlands within the global-scale hydrological model WaterGAP, in order to better estimate water flows and water storage variations in different storage compartments. Within the scope of this thesis, I have developed a new approach to simulate dynamic floodplain inundation on a global-scale. This approach introduces an algorithm into WaterGAP, which has a spatial resolution of 0.5 degree (longitude and latitude) globally. The new approach uses subgrid-scale topography, based on high-resolution digital elevation models, to describe the floodplain elevation profile within each grid cell by applying a hypsographic curve. The approach comprises the modeling of a two-way river-floodplain interaction, the separate downstream water transport within the river and the floodplain – both with temporally and spatially different variable flow velocities – and the floodplain-groundwater interactions. The WaterGAP version that includes the floodplain algorithm, WaterGAP 2.2b_fpl, estimates floodplain and river water storage, inundated area and water table elevation, and also simulates backwater effects.
WaterGAP 2.2b_fpl was applied to model river discharge, river flow velocity, water storages, water heights and surface water extent on a global-scale. Model results were comprehensively validated against ground observations and remote sensing data. Overall, the modeled and observed data are in agreement. In comparison to the former version WaterGAP 2.2b, the model performance has improved significantly. The improvements are most remarkable in the Amazon River basin. However, the seasonal variation of surface water extent and total water storage anomalies are still too low in many regions on the globe when compared to observations. A detailed analysis of the simulated results suggests that in the Amazon River basin the introduction of backwater effects is important for realistically simulating water storages and surface water extent. Future efforts should focus on the simulation of water levels in order to better model the flow routing according to water slope. To further improve the model performance in specific regions, I recommend that the globally constant model parameters that affect inundation initiation, river-floodplain interaction, DEM correction for vegetation, and backwater amount at basin or subbasin-scale be adjusted.
Global investment in biomedical research has grown significantly over the last decades, reaching approximately a quarter of a trillion US dollars in 2010. However, not all of this investment is distributed evenly by gender. It follows, arguably, that scarce research resources may not be optimally invested (by either not supporting the best science or by failing to investigate topics that benefit women and men equitably). Women across the world tend to be significantly underrepresented in research both as researchers and research participants, receive less research funding, and appear less frequently than men as authors on research publications. There is also some evidence that women are relatively disadvantaged as the beneficiaries of research, in terms of its health, societal and economic impacts. Historical gender biases may have created a path dependency that means that the research system and the impacts of research are biased towards male researchers and male beneficiaries, making it inherently difficult (though not impossible) to eliminate gender bias. In this commentary, we – a group of scholars and practitioners from Africa, America, Asia and Europe – argue that gender-sensitive research impact assessment could become a force for good in moving science policy and practice towards gender equity. Research impact assessment is the multidisciplinary field of scientific inquiry that examines the research process to maximise scientific, societal and economic returns on investment in research. It encompasses many theoretical and methodological approaches that can be used to investigate gender bias and recommend actions for change to maximise research impact. We offer a set of recommendations to research funders, research institutions and research evaluators who conduct impact assessment on how to include and strengthen analysis of gender equity in research impact assessment and issue a global call for action.
When assessing global water resources with hydrological models, it is essential to know about methodological uncertainties. The values of simulated water balance components may vary due to different spatial and temporal aggregations, reference periods, and applied climate forcings, as well as due to the consideration of human water use, or the lack thereof. We analyzed these variations over the period 1901–2010 by forcing the global hydrological model WaterGAP 2.2 (ISIMIP2a) with five state-of-the-art climate data sets, including a homogenized version of the concatenated WFD/WFDEI data set. Absolute values and temporal variations of global water balance components are strongly affected by the uncertainty in the climate forcing, and no temporal trends of the global water balance components are detected for the four homogeneous climate forcings considered (except for human water abstractions). The calibration of WaterGAP against observed long-term average river discharge Q significantly reduces the impact of climate forcing uncertainty on estimated Q and renewable water resources. For the homogeneous forcings, Q of the calibrated and non-calibrated regions of the globe varies by 1.6 and 18.5 %, respectively, for 1971–2000. On the continental scale, most differences for long-term average precipitation P and Q estimates occur in Africa and, due to snow undercatch of rain gauges, also in the data-rich continents Europe and North America. Variations of Q at the grid-cell scale are large, except in a few grid cells upstream and downstream of calibration stations, with an average variation of 37 and 74 % among the four homogeneous forcings in calibrated and non-calibrated regions, respectively. Considering only the forcings GSWP3 and WFDEI_hom, i.e., excluding the forcing without undercatch correction (PGFv2.1) and the one with a much lower shortwave downward radiation SWD than the others (WFD), Q variations are reduced to 16 and 31 % in calibrated and non-calibrated regions, respectively. These simulation results support the need for extended Q measurements and data sharing for better constraining global water balance assessments. Over the 20th century, the human footprint on natural water resources has become larger. For 11–18% of the global land area, the change of Q between 1941–1970 and 1971–2000 was driven more strongly by change of human water use including dam construction than by change in precipitation, while this was true for only 9–13 % of the land area from 1911–1940 to 1941–1970.
When assessing global water resources with hydrological models, it is essential to know the methodological uncertainties in the water resources estimates. The study presented here quantifies effects of the uncertainty in the spatial and temporal patterns of meteorological variables on water balance components at the global, continental and grid cell scale by forcing the global hydrological model WaterGAP 2.2 (ISI-MIP 2.1) with five state-of-the-art climate forcing input data-sets. While global precipitation over land during 1971–2000 varies between 103 500 and 111 000 km3 yr−1, global river discharge varies between 39 200 and 42 200 km3 yr−1. Temporal trends of global wa- ter balance components are strongly affected by the uncertainty in the climate forcing (except human water abstractions), and there is a need for temporal homogenization of climate forcings (in particular WFD/WFDEI). On about 10–20 % of the global land area, change of river discharge between two consecutive 30 year periods was driven more strongly by changes of human water use including dam construction than by changes in precipitation. This number increases towards the end of the 20th century due to intensified human water use and dam construction. The calibration approach of WaterGAP against observed long-term average river discharge reduces the impact of climate forcing uncertainty on estimated river discharge significantly. Different homgeneous climate forcings lead to a variation of Q of only 1.6 % for the 54 % of global land area that are constrained by discharge observations, while estimated renewable water resources in the remaining uncalibrated regions vary by 18.5 %. Uncertainties are especially high in Southeast Asia where Global Runoff Data Centre (GRDC) data availability is very sparse. By sharing already available discharge data, or installing new streamflow gauging stations in such regions, water balance uncertainties could be reduced which would lead to an improved assessment of the world’s water resources.
The assessment of water balance components using global hydrological models is subject to climate forcing uncertainty as well as to an increasing intensity of human water use within the 20th century. The uncertainty of five state-of-the-art climate forcings and the resulting range of cell runoff that is simulated by the global hydrological model WaterGAP is presented. On the global land surface, about 62 % of precipitation evapotranspires, whereas 38 % discharges into oceans and inland sinks. During 1971–2000, evapotranspiration due to human water use amounted to almost 1 % of precipitation, while this anthropogenic water flow increased by a factor of approximately 5 between 1901 and 2010. Deviation of estimated global discharge from the ensemble mean due to climate forcing uncertainty is approximately 4 %. Precipitation uncertainty is the most important reason for the uncertainty of discharge and evapotranspiration, followed by shortwave downward radiation. At continental levels, deviations of water balance components due to uncertain climate forcing are higher, with the highest discharge deviations occurring for river discharge in Africa (−6 to 11 % from the ensemble mean). Uncertain climate forcings also affect the estimation of irrigation water use and thus the estimated human impact of river discharge. The uncertainty range of global irrigation water consumption amounts to approximately 50 % of the global sum of water consumption in the other water use sector.
The COVID-19 pandemic has caused strains on health systems worldwide disrupting routine hospital services for all non-COVID patients. Within this retrospective study, we analyzed inpatient hospital admissions across 18 German university hospitals during the 2020 lockdown period compared to 2018. Patients admitted to hospital between January 1 and May 31, 2020 and the corresponding periods in 2018 and 2019 were included in this study. Data derived from electronic health records were collected and analyzed using the data integration center infrastructure implemented in the university hospitals that are part of the four consortia funded by the German Medical Informatics Initiative. Admissions were grouped and counted by ICD 10 chapters and specific reasons for treatment at each site. Pooled aggregated data were centrally analyzed with descriptive statistics to compare absolute and relative differences between time periods of different years. The results illustrate how care process adoptions depended on the COVID-19 epidemiological situation and the criticality of the disease. Overall inpatient hospital admissions decreased by 35% in weeks 1 to 4 and by 30.3% in weeks 5 to 8 after the lockdown announcement compared to 2018. Even hospital admissions for critical care conditions such as malignant cancer treatments were reduced. We also noted a high reduction of emergency admissions such as myocardial infarction (38.7%), whereas the reduction in stroke admissions was smaller (19.6%). In contrast, we observed a considerable reduction in admissions for non-critical clinical situations, such as hysterectomies for benign tumors (78.8%) and hip replacements due to arthrosis (82.4%). In summary, our study shows that the university hospital admission rates in Germany were substantially reduced following the national COVID-19 lockdown. These included critical care or emergency conditions in which deferral is expected to impair clinical outcomes. Future studies are needed to delineate how appropriate medical care of critically ill patients can be maintained during a pandemic.
The Coulomb Dissociation (CD) cross sections of the stable isotopes 92,94,100Mo and of the unstable isotope 93Mo were measured at the LAND/R3B setup at GSI Helmholtzzentrum für Schwerionenforschung in Darmstadt, Germany. Experimental data on these isotopes may help to explain the problem of the underproduction of 92,94Mo and 96,98Ru in the models of p-process nucleosynthesis. The CD cross sections obtained for the stable Mo isotopes are in good agreement with experiments performed with real photons, thus validating the method of Coulomb Dissociation. The result for the reaction 93Mo(γ,n) is especially important since the corresponding cross section has not been measured before. A preliminary integral Coulomb Dissociation cross section of the 94Mo(γ,n) reaction is presented. Further analysis will complete the experimental database for the (γ,n) production chain of the p-isotopes of molybdenum.