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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.
Land-use intensification is a major driver of biodiversity loss(1,2). Alongside reductions in local species diversity, biotic homogenization at larger spatial scales is of great concern for conservation. Biotic homogenization means a decrease in beta-diversity (the compositional dissimilarity between sites). Most studies have investigated losses in local (alpha)-diversity(1,3) and neglected biodiversity loss at larger spatial scales. Studies addressing beta-diversity have focused on single or a few organism groups (for example, ref. 4), and it is thus unknown whether land-use intensification homogenizes communities at different trophic levels, above-and belowground. Here we show that even moderate increases in local land-use intensity (LUI) cause biotic homogenization across microbial, plant and animal groups, both above- and belowground, and that this is largely independent of changes in alpha-diversity. We analysed a unique grassland biodiversity dataset, with abundances of more than 4,000 species belonging to 12 trophic groups. LUI, and, in particular, high mowing intensity, had consistent effects on beta-diversity across groups, causing a homogenization of soil microbial, fungal pathogen, plant and arthropod communities. These effects were nonlinear and the strongest declines in beta-diversity occurred in the transition from extensively managed to intermediate intensity grassland. LUI tended to reduce local alpha-diversity in aboveground groups, whereas the alpha-diversity increased in belowground groups. Correlations between the alpha-diversity of different groups, particularly between plants and their consumers, became weaker at high LUI. This suggests a loss of specialist species and is further evidence for biotic homogenization. The consistently negative effects of LUI on landscape-scale biodiversity underscore the high value of extensively managed grasslands for conserving multitrophic biodiversity and ecosystem service provision. Indeed, biotic homogenization rather than local diversity loss could prove to be the most substantial consequence of land-use intensification.
Land-use intensification is a key driver of biodiversity change. However, little is known about how it alters relationships between the diversities of different taxonomic groups, which are often correlated due to shared environmental drivers and trophic interactions. Using data from 150 grassland sites, we examined how land-use intensification (increased fertilization, higher livestock densities, and increased mowing frequency) altered correlations between the species richness of 15 plant, invertebrate, and vertebrate taxa. We found that 54% of pairwise correlations between taxonomic groups were significant and positive among all grasslands, while only one was negative. Higher land-use intensity substantially weakened these correlations(35% decrease in rand 43% fewer significant pairwise correlations at high intensity), a pattern which may emerge as a result of biodiversity declines and the breakdown of specialized relationships in these conditions. Nevertheless, some groups (Coleoptera, Heteroptera, Hymenoptera and Orthoptera) were consistently correlated with multidiversity, an aggregate measure of total biodiversity comprised of the standardized diversities of multiple taxa, at both high and lowland-use intensity. The form of intensification was also important; increased fertilization and mowing frequency typically weakened plant-plant and plant-primary consumer correlations, whereas grazing intensification did not. This may reflect decreased habitat heterogeneity under mowing and fertilization and increased habitat heterogeneity under grazing. While these results urge caution in using certain taxonomic groups to monitor impacts of agricultural management on biodiversity, they also suggest that the diversities of some groups are reasonably robust indicators of total biodiversity across a range of conditions.
For the layered transition metal dichalcogenide 1T-TaS2, we establish through a unique experimental approach and density functional theory, how ultrafast charge transfer in 1T-TaS2 takes on isotropic three-dimensional character or anisotropic two-dimensional character, depending on the commensurability of the charge density wave phases of 1T-TaS2. The X-ray spectroscopic core-hole-clock method prepares selectively in-and out-of-plane polarized sulfur 3p orbital occupation with respect to the 1T-TaS2 planes and monitors sub-femtosecond wave packet delocalization. Despite being a prototypical two-dimensional material, isotropic three-dimensional charge transfer is found in the commensurate charge density wave phase (CCDW), indicating strong coupling between layers. In contrast, anisotropic two-dimensional charge transfer occurs for the nearly commensurate phase (NCDW). In direct comparison, theory shows that interlayer interaction in the CCDW phase - not layer stacking variations - causes isotropic three-dimensional charge transfer. This is presumably a general mechanism for phase transitions and tailored properties of dichalcogenides with charge density waves.
We present a setup combining a liquid flatjet sample delivery and a MHz laser system for time-resolved soft X-ray absorption measurements of liquid samples at the high brilliance undulator beamline UE52-SGM at Bessy II yielding unprecedented statistics in this spectral range. We demonstrate that the efficient detection of transient absorption changes in transmission mode enables the identification of photoexcited species in dilute samples. With iron(II)-trisbipyridine in aqueous solution as a benchmark system, we present absorption measurements at various edges in the soft X-ray regime. In combination with the wavelength tunability of the laser system, the set-up opens up opportunities to study the photochemistry of many systems at low concentrations, relevant to materials sciences, chemistry, and biology. (C) 2017 Author(s).
Rodin has it!
(2020)
We report a new discovery on the role of hands in guiding attention, using the classic Stroop effect as our assay. We show that the Stroop effect diminishes, hence selective attention improves, when observers hold their chin, emulating Rodin's famous sculpture, "The Thinker." In two experiments we show that the Rodin posture improves the selectivity of attention as efficiently as holding the hands nearby the visual stimulus (the near-hands effect). Because spatial proximity to the displayed stimulus is neither present nor intended, the presence of the Rodin effect implies that attentional prioritization by the hands is not limited to the space between the hands.
The active global SARS-CoV-2 pandemic caused more than 426 million cases and 5.8 million deaths worldwide. The development of completely new drugs for such a novel disease is a challenging, time intensive process. Despite researchers around the world working on this task, no effective treatments have been developed yet. This emphasizes the importance of drug repurposing, where treatments are found among existing drugs that are meant for different diseases. A common approach to this is based on knowledge graphs, that condense relationships between entities like drugs, diseases and genes. Graph neural networks (GNNs) can then be used for the task at hand by predicting links in such knowledge graphs. Expanding on state-of-the-art GNN research, Doshi et al. recently developed the Dr-COVID model. We further extend their work using additional output interpretation strategies. The best aggregation strategy derives a top-100 ranking of 8,070 candidate drugs, 32 of which are currently being tested in COVID-19-related clinical trials. Moreover, we present an alternative application for the model, the generation of additional candidates based on a given pre-selection of drug candidates using collaborative filtering. In addition, we improved the implementation of the Dr-COVID model by significantly shortening the inference and pre-processing time by exploiting data-parallelism. As drug repurposing is a task that requires high computation and memory resources, we further accelerate the post-processing phase using a new emerging hardware-we propose a new approach to leverage the use of high-capacity Non-Volatile Memory for aggregate drug ranking.
Charge transport layers (CTLs) are key components of diffusion controlled perovskite solar cells, however, they can induce additional non-radiative recombination pathways which limit the open circuit voltage (V-OC) of the cell. In order to realize the full thermodynamic potential of the perovskite absorber, both the electron and hole transport layer (ETL/HTL) need to be as selective as possible. By measuring the photoluminescence yield of perovskite/CTL heterojunctions, we quantify the non-radiative interfacial recombination currents in pin- and nip-type cells including high efficiency devices (21.4%). Our study comprises a wide range of commonly used CTLs, including various hole-transporting polymers, spiro-OMeTAD, metal oxides and fullerenes. We find that all studied CTLs limit the V-OC by inducing an additional non-radiative recombination current that is in most cases substantially larger than the loss in the neat perovskite and that the least-selective interface sets the upper limit for the V-OC of the device. Importantly, the V-OC equals the internal quasi-Fermi level splitting (QFLS) in the absorber layer only in high efficiency cells, while in poor performing devices, the V-OC is substantially lower than the QFLS. Using ultraviolet photoelectron spectroscopy and differential charging capacitance experiments we show that this is due to an energy level mis-alignment at the p-interface. The findings are corroborated by rigorous device simulations which outline important considerations to maximize the V-OC. This work highlights that the challenge to suppress non-radiative recombination losses in perovskite cells on their way to the radiative limit lies in proper energy level alignment and in suppression of defect recombination at the interfaces.
The performance of perovskite solar cells is predominantly limited by non-radiative recombination, either through trap-assisted recombination in the absorber layer or via minority carrier recombination at the perovskite/transport layer interfaces. Here, we use transient and absolute photoluminescence imaging to visualize all non-radiative recombination pathways in planar pintype perovskite solar cells with undoped organic charge transport layers. We find significant quasi-Fermi-level splitting losses (135 meV) in the perovskite bulk, whereas interfacial recombination results in an additional free energy loss of 80 meV at each individual interface, which limits the open-circuit voltage (V-oc) of the complete cell to similar to 1.12 V. Inserting ultrathin interlayers between the perovskite and transport layers leads to a substantial reduction of these interfacial losses at both the p and n contacts. Using this knowledge and approach, we demonstrate reproducible dopant-free 1 cm(2) perovskite solar cells surpassing 20% efficiency (19.83% certified) with stabilized power output, a high V-oc (1.17 V) and record fill factor (>81%).
The immense advances in computer power achieved in the last decades have had a significant impact in Earth science, providing valuable research outputs that allow the simulation of complex natural processes and systems, and generating improved forecasts. The development and implementation of innovative geoscientific software is currently evolving towards a sustainable and efficient development by integrating models of different aspects of the Earth system. This will set the foundation for a future digital twin of the Earth. The codification and update of this software require great effort from research groups and therefore, it needs to be preserved for its reuse by future generations of geoscientists. Here, we report on Geo-Soft-CoRe, a Geoscientific Software & Code Repository, hosted at the archive DIGITAL.CSIC. This is an open source, multidisciplinary and multiscale collection of software and code developed to analyze different aspects of the Earth system, encompassing tools to: 1) analyze climate variability; 2) assess hazards, and 3) characterize the structure and dynamics of the solid Earth. Due to the broad range of applications of these software packages, this collection is useful not only for basic research in Earth science, but also for applied research and educational purposes, reducing the gap between the geosciences and the society. By providing each software and code with a permanent identifier (DOI), we ensure its self-sustainability and accomplish the FAIR (Findable, Accessible, Interoperable and Reusable) principles. Therefore, we aim for a more transparent science, transferring knowledge in an easier way to the geoscience community, and encouraging an integrated use of computational infrastructure.