Refine
Year of publication
Document Type
- Article (31461) (remove)
Language
- English (16059)
- German (13394)
- Portuguese (696)
- French (387)
- Croatian (251)
- Spanish (250)
- Italian (134)
- Turkish (113)
- Multiple languages (36)
- Latin (35)
Has Fulltext
- yes (31461) (remove)
Keywords
- Deutsch (503)
- taxonomy (454)
- Literatur (299)
- new species (198)
- Hofmannsthal, Hugo von (185)
- Rezeption (178)
- Übersetzung (163)
- Filmmusik (155)
- Johann Wolfgang von Goethe (131)
- Vormärz (117)
Institute
- Medizin (5431)
- Physik (2039)
- Biowissenschaften (1155)
- Biochemie und Chemie (1113)
- Extern (1108)
- Frankfurt Institute for Advanced Studies (FIAS) (804)
- Gesellschaftswissenschaften (804)
- Geowissenschaften (593)
- Präsidium (453)
- Informatik (450)
Measurements of charged-particle production in pp, p−Pb, and Pb−Pb collisions in the toward, away, and transverse regions with the ALICE detector are discussed. These regions are defined event-by-event relative to the azimuthal direction of the charged trigger particle, which is the reconstructed particle with the largest transverse momentum (ptrigT) in the range 8<ptrigT<15 GeV/c. The toward and away regions contain the primary and recoil jets, respectively; both regions are accompanied by the underlying event (UE). In contrast, the transverse region perpendicular to the direction of the trigger particle is dominated by the so-called UE dynamics, and includes also contributions from initial- and final-state radiation. The relative transverse activity classifier, RT=NTch/⟨NTch⟩, is used to group events according to their UE activity, where NTch is the charged-particle multiplicity per event in the transverse region and ⟨NTch⟩ is the mean value over the whole analysed sample. The energy dependence of the RT distributions in pp collisions at s√=2.76, 5.02, 7, and 13 TeV is reported, exploring the Koba-Nielsen-Olesen (KNO) scaling properties of the multiplicity distributions. The first measurements of charged-particle pT spectra as a function of RT in the three azimuthal regions in pp, p−Pb, and Pb−Pb collisions at sNN−−−√=5.02 TeV are also reported. Data are compared with predictions obtained from the event generators PYTHIA 8 and EPOS LHC. This set of measurements is expected to contribute to the understanding of the origin of collective-like effects in small collision systems (pp and p−Pb).
Controlling and understanding electron correlations in quantum matter is one of the most challenging tasks in materials engineering. In the past years a plethora of new puzzling correlated states have been found by carefully stacking and twisting two-dimensional van der Waals materials of different kind. Unique to these stacked structures is the emergence of correlated phases not foreseeable from the single layers alone. In Ta-dichalcogenide heterostructures made of a good metallic “1H”- and a Mott insulating “1T”-layer, recent reports have evidenced a cross-breed itinerant and localized nature of the electronic excitations, similar to what is typically found in heavy fermion systems. Here, we put forward a new interpretation based on first-principles calculations which indicates a sizeable charge transfer of electrons (0.4-0.6 e) from 1T to 1H layers at an elevated interlayer distance. We accurately quantify the strength of the interlayer hybridization which allows us to unambiguously determine that the system is much closer to a doped Mott insulator than to a heavy fermion scenario. Ta-based heterolayers provide therefore a new ground for quantum-materials engineering in the regime of heavily doped Mott insulators hybridized with metallic states at a van der Waals distance.
We investigate the applicability of the well-known multilevel Monte Carlo (MLMC) method to the class of density-driven flow problems, in particular the problem of salinisation of coastal aquifers. As a test case, we solve the uncertain Henry saltwater intrusion problem. Unknown porosity, permeability and recharge parameters are modelled by using random fields. The classical deterministic Henry problem is non-linear and time-dependent, and can easily take several hours of computing time. Uncertain settings require the solution of multiple realisations of the deterministic problem, and the total computational cost increases drastically. Instead of computing of hundreds random realisations, typically the mean value and the variance are computed. The standard methods such as the Monte Carlo or surrogate-based methods are a good choice, but they compute all stochastic realisations on the same, often, very fine mesh. They also do not balance the stochastic and discretisation errors. These facts motivated us to apply the MLMC method. We demonstrate that by solving the Henry problem on multi-level spatial and temporal meshes, the MLMC method reduces the overall computational and storage costs. To reduce the computing cost further, parallelization is performed in both physical and stochastic spaces. To solve each deterministic scenario, we run the parallel multigrid solver ug4 in a black-box fashion.
Determining the structure and mechanisms of all individual functional modules of cells at high molecular detail has often been seen as equal to understanding how cells work. Recent technical advances have led to a flush of high-resolution structures of various macromolecular machines, but despite this wealth of detailed information, our understanding of cellular function remains incomplete. Here, we discuss present-day limitations of structural biology and highlight novel technologies that may enable us to analyze molecular functions directly inside cells. We predict that the progression toward structural cell biology will involve a shift toward conceptualizing a 4D virtual reality of cells using digital twins. These will capture cellular segments in a highly enriched molecular detail, include dynamic changes, and facilitate simulations of molecular processes, leading to novel and experimentally testable predictions. Transferring biological questions into algorithms that learn from the existing wealth of data and explore novel solutions may ultimately unveil how cells work.
Highlights
• Currently, China has the most publications, ahead of the USA and European countries.
• Research focuses are strictly separated into ecological and material science topics.
• Russia and Ukraine are among the frontrunners with a clear focus on materials science.
• The focus in PFAS research is shifting toward ecological issues.
• A national imbalance can be observed that leaves the low economies behind.
Abstract
The European Commission's current efforts to launch the largest proposal to restrict per- and polyfluoroalkyl substances (PFAS) in history reflect the dire global plight of PFAS accumulation in the environment and their health impacts. While there are existing studies on PFAS research, there is a lack of comprehensive analysis that both covers the entire research period and provides deep insights into global research patterns, incentives, and barriers based on various parameters. We have been able to demonstrate the increasing interest in PFAS research, although citation numbers are declining prematurely. Policy regulations based on proving and establishing the toxicity of PFASs have stimulated research in developed countries and vice versa, with increasing emphasis on ecological aspects. China, in particular, is investing increasingly in PFAS research, but without defining or implementing regulations - with devastating effects. The separation of industrial and environmental research interests is clear, with little involvement of developing countries, even though their exposure to PFAS is devastating. It, therefore, requires increased globally networked and multidisciplinary approaches to address PFAS contamination challenges.
Highlights
• Seed size mediates seedling recruitment in tropical forests and pastures.
• Large-seeded species recruited better than small-seeded species in the forest.
• Recruitment of large-seeded species in pastures was limited by surface temperature.
• Large-seeded species should be protected against drought in regenerating pastures.
Abstract
Seedling recruitment is a key process of plant regeneration that often depends on plant functional traits, such as seed size. To optimize forest restoration efforts, we need to better understand how seedling recruitment of different seed sizes varies along environmental gradients with strong variation in abiotic and biotic factors. To understand these interacting effects, we conducted a sowing experiment with different-sized seeds in forests and pastures in the tropical mountains of southern Ecuador. We quantified seedling recruitment in relation to temperature, soil moisture and biotic pressures. We sowed seeds of five tree species of varying seed size at three elevations (1000, 2000 and 3000 m a.s.l.) in primary forest and pastures. We tested (1) how habitat type influences the recruitment of seedlings belonging to three small- and two large-seeded species, and (2) how abiotic and biotic factors limit seedling recruitment of species with different seed sizes. We found that seedlings of the two large-seeded species recruited better than seedlings of the three small-seeded species, but only in the forest habitat. Seedling recruitment of large seeds was primarily limited by high surface temperature, which explains lower recruitment of large seeds in pastures compared to forests. Our study shows that seed size can be a key trait mediating variability in seedling recruitment in tropical ecosystems. We conclude that restoration measures should aim to mitigate extreme temperatures in tropical pastures to aid the natural regeneration of large-seeded tree species.
Highlights
• Six Newton methods for solving matrix quadratic equations in linear DSGE models.
• Compared to QZ using 99 different DSGE models including Smets and Wouters (2007).
• Newton methods more accurate than QZ with comparable computation burden.
• Apt for refining solutions from alternative methods or nearby parameterizations.
Abstract
This paper presents and compares Newton-based methods from the applied mathematics literature for solving the matrix quadratic that underlies the recursive solution of linear DSGE models. The methods are compared using nearly 100 different models from the Macroeconomic Model Data Base (MMB) and different parameterizations of the monetary policy rule in the medium-scale New Keynesian model of Smets and Wouters (2007) iteratively. We find that Newton-based methods compare favorably in solving DSGE models, providing higher accuracy as measured by the forward error of the solution at a comparable computation burden. The methods, however, suffer from their inability to guarantee convergence to a particular, e.g. unique stable, solution, but their iterative procedures lend themselves to refining solutions either from different methods or parameterizations.
The hierarchical feature regression (HFR) is a novel graph-based regularized regression estimator, which mobilizes insights from the domains of machine learning and graph theory to estimate robust parameters for a linear regression. The estimator constructs a supervised feature graph that decomposes parameters along its edges, adjusting first for common variation and successively incorporating idiosyncratic patterns into the fitting process. The graph structure has the effect of shrinking parameters towards group targets, where the extent of shrinkage is governed by a hyperparameter, and group compositions as well as shrinkage targets are determined endogenously. The method offers rich resources for the visual exploration of the latent effect structure in the data, and demonstrates good predictive accuracy and versatility when compared to a panel of commonly used regularization techniques across a range of empirical and simulated regression tasks.
Highlights
• High resolution profile of C. pipiens' sugar diet has been obtained using UHPLC-MS.
• Artificial feeding using ornamental plants provides similar sugar profiles as observed in field collected mosquitoes.
• Metabolomic profiling found secondary metabolites and pollutants of anthropogenic use.
Abstract: Culex pipiens (Linnaeus, 1758) mosquitoes search plant sources of sugars to cope with the energetic demand of various physiological processes. The crop as part of the digestive system is devoted to the storage of sugar-based meal obtained from various nectars sources. The profiling of sugars and metabolites in the Culex pipiens’ crop is scarce, and only few studies used Liquid Chromatography – Mass Spectrometry (LC-MS), which provides broad detection for biomonitoring environmental substances and even contaminants in the sugar diet of mosquitoes populations.
Therefore, sugar and metabolite profiling were performed on crops obtained from mosquitoes exposed to plant nectar under laboratory or natural conditions by Ultra High-Performance LC-MS (UHPLC-MS). This method allowed us a precise quantitative and qualitative identification of sugar diet and associated environmental compounds in the crop of the mosquito C. pipiens. Under laboratory condition, mosquitoes were allowed to feed on either glucose solution, commercially-available flowers or field collected flowers. In addition, we collected mosquitoes from the field to compare those crop metabolomes with metabolome patterns occurring after nectar feeding in the lab.
The sugar quantities and quality obtained from the crops of mosquitoes collected in the field were similar to those crops obtained from mosquitoes that fed on commercially-available flowers and from field collected flowers with a limit of detection of 10 μg/L for sucrose, glucose and sucrose. Next to sugar compounds, we identified 2 types of amino acids, 12 natural products, and 9 pesticides.
Next to the diversity of sugar compounds, we could confirm that secondary metabolites and environmental pollutants are typically up taken from floral nectar sources by C. pipiens. The in-depth knowledge on mosquito–plant interactions may inspire the development and further optimization of mosquito trap systems and arboviral surveillance systems.
Korean immigrants have migrated to New Zealand over the past three decades in search of a happier and more balanced life. While they anticipated that their children would be integrated into New Zealand society, they have primarily settled in Korean ethnic enclaves. In this context, younger Korean New Zealanders have been exposed to and influenced by New Zealand’s national and Korean ethnic cultures. This study examined success beliefs and well-being among Korean youth in New Zealand with a Third Culture Kid background (TCK K-NZ) in comparison to Korean youth in Korea (K-Korean) and European New Zealand youth (Pākehā). Results indicated that TCK K-NZ youth endorsed extrinsic success similarly to K-Korean youth, but that valuing extrinsic success predicted lowered well-being only for K-Korean youth. Conversely, valuing intrinsic success predicted higher well-being across the three groups. Results also revealed that TCK K-NZ youth's well-being levels were between those of K-Korean and Pākehā youth, potentially influenced by different structural relations between success beliefs and well-being, as well as their position as “third culture kids” in New Zealand. This study contributes to understanding cultures' roles in formulating success beliefs and the relationship between success beliefs and well-being for Korean New Zealander youth.