Past warming trend constrains future warming in CMIP6 models

Future global warming estimates have been similar across past assessments, but several climate models of the latest Sixth Coupled Model Intercomparison Project (CMIP6) simulate much stronger warming, apparently inconsistent with past assessments. Here, we show that projected future warming is correlated with the simulated warming trend during recent decades across CMIP5 and CMIP6 models, enabling us to constrain future warming based on consistency with the observed warming. These findings carry important policy-relevant implications: The observationally constrained CMIP6 median warming in high emissions and ambitious mitigation scenarios is over 16 and 14% lower by 2050 compared to the raw CMIP6 median, respectively, and over 14 and 8% lower by 2090, relative to 1995–2014. Observationally constrained CMIP6 warming is consistent with previous assessments based on CMIP5 models, and in an ambitious mitigation scenario, the likely range is consistent with reaching the Paris Agreement target

Extended polarized semiclassical model for quantum-dot cavity QED and its application to single-photon sources

We present a simple extension of the semi-classical model for a two-level system in a cavity, in order to incorporate multiple polarized transitions, such as those appearing in neutral and charged quantum dots (QDs), and two nondegenerate linearly polarized cavity modes. We verify the model by exact quantum master equation calculations, and experimentally using a neutral QD in a polarization non-degenerate micro-cavity, in both cases we observe excellent agreement. Finally, the usefulness of this approach is demonstrated by optimizing a single-photon source based on polarization postselection, where we find an increase in the brightness for optimal polarization conditions as predicted by the model.Comment: 8 pages, for simple code see https://doi.org/10.5281/zenodo.347666

Effects of urban, atmosphericallyderived organic C on soil: A review

Urban areas generate about 77%, worldwide, of the carbon (C) based compounds that are annually released to the atmosphere, whether in the form of gases (e.g., 71% of CO2, 60% of CO) or fine aromatic C solids (70%), all of which may pose environmental risks, from biological cell to global levels (e.g., air quality, scattering light). Those C-rich atmospheric particles, referred to as “particulate matter and black carbon” (PM-BC), as opposed to aquatic origin “particulate organic carbon” (POC), are present as finer than 2.5 µm and produced during incomplete combustion processes such as in vehicle emissions, domestic heating and biomass burning. However, while the post combustion C gases remain for a while in the aerial environment, PM-BC undergoes a relatively brief cycle of emission-dispersion-transformation-deposition. Globally, these account for about 47 Tg C y-1 from wet deposition of PM-BC, and 400 Tg C y-1 from deposition of dissolved organic carbon (DOC) in rainfall, which generally disturbs the global C cycle, and specifically those of urban centers and surrounding areas, permanently shifting the C budget of the soil, and altering its chemistry, which is important because the soil is considered, by far, as the main C sink in terrestrial ecosystems. However, once the deposited C begins interacting with soil components, its negative effects are not necessarily measurable in the soil environment. On the contrary, soils in which PM-BC is deposited may produce a negative bioenergy that subsequently shifts the biogeochemical C reactions towards those materials that are composed of more stable organic molecules, thereby increasing the recalcitrant C pool, and likely contributing to other soil organic C (SOC) stabilization mechanisms that increase C sequestration in soil. In addition, PM-BC plays an important role as a strong sorbent for common urban pollutants (e.g., trace elements and persistent organic pollutants). Therefore, the focus of this review is to synthesize the previously published reports of the effects of PM-BC on the physico-chemical mechanisms of long term C storage in soils

SODAR Core: a Django-based framework for scientific data management and analysis web apps

Modern life science is generating large data sets at a unprecedented speed. A major source of data are so-called omics (e.g., genomics, metabolomics, or proteomics) experiments. Consequently, management and analysis of scientific data has become a major challenge. Further, the heterogeneity of projects makes "one size fits all" data analysis systems infeasible and calls for specialized data analysis platforms. The authors are actively developing applications for the FAIR (findable, accessible, interoperable, and reuseable) data management of omics data and their analysis. In order to prevent duplication of work, we have extracted the commonly useful components into SODAR Core, a Python framework on top of Django. It is used in our actively developed applications and also proved useful in internal web app prototypes. Examples for using SODAR Core in the development of scientific data management web apps is Digestiflow and the Filesfolders module shipping with SODAR Core. An example for using SODAR Core in the development of scientific data analysis web apps is VarFis

RNA based approaches to profile oncogenic pathways from low quantity samples to drive precision oncology strategies

Precision treatment of cancer requires knowledge on active tumor driving signal transduction pathways to select the optimal effective targeted treatment. Currently only a subset of patients derive clinical benefit from mutation based targeted treatment, due to intrinsic and acquired drug resistance mechanisms. Phenotypic assays to identify the tumor driving pathway based on protein analysis are difficult to multiplex on routine pathology samples. In contrast, the transcriptome contains information on signaling pathway activity and can complement genomic analyses. Here we present the validation and clinical application of a new knowledge-based mRNA-based diagnostic assay platform (OncoSignal) for measuring activity of relevant signaling pathways simultaneously and quantitatively with high resolution in tissue samples and circulating tumor cells, specifically with very small specimen quantities. The approach uses mRNA levels of a pathway\u27s direct target genes, selected based on literature for multiple proof points, and used as evidence that a pathway is functionally activated. Using these validated target genes, a Bayesian network model has been built and calibrated on mRNA measurements of samples with known pathway status, which is used next to calculate a pathway activity score on individual test samples. Translation to RT-qPCR assays enables broad clinical diagnostic applications, including small analytes. A large number of cancer samples have been analyzed across a variety of cancer histologies and benchmarked across normal controls. Assays have been used to characterize cell types in the cancer cell microenvironment, including immune cells in which activated and immunotolerant states can be distinguished. Results support the expectation that the assays provide information on cancer driving signaling pathways which is difficult to derive from next generation DNA sequencing analysis. Current clinical oncology applications have been complementary to genomic mutation analysis to improve precision medicine: (1) prediction of response and resistance to various therapies, especially targeted therapy and immunotherapy; (2) assessment and monitoring of therapy efficacy; (3) prediction of invasive cancer cell behavior and prognosis; (4) measurement of circulating tumor cells. Preclinical oncology applications lie in a better understanding of cancer behavior across cancer types, and in development of a pathophysiology-based cancer classification for development of novel therapies and precision medicine

VarFish - Collaborative and comprehensive variant analysis for diagnosis and research

VarFish is a user-friendly web application for the quality control, filtering, prioritization, analysis, and user-based annotation of panel and exome variant data for rare disease genetics. It is capable of processing variant call files with single or multiple samples. The variants are automatically annotated with population frequencies, molecular impact, and presence in databases such as ClinVar. Further, it provides support for pathogenicity scores including CADD, MutationTaster, and phenotypic similarity scores. Users can filter variants based on these annotations and presumed inheritance pattern and sort the results by these scores. Filtered variants are listed with their annotations and many useful link-outs to genome browsers, other gene/variant data portals, and external tools for variant assessment. VarFish allows user to create their own annotations including support for variant assessment following ACMG-AMP guidelines. In close collaboration with medical practitioners, VarFish was designed for variant analysis and prioritization in diagnostic and research settings as described in the software’s extensive manual. The user interface has been optimized for supporting these protocols. Users can install VarFish on their own in-house servers where it provides additional lab notebook features for collaborative analysis and allows re-analysis of cases, e.g., after update of genotype or phenotype databases

Femtosecond multimodal imaging with a laser-driven X-ray source

Laser-plasma accelerators are compact linear accelerators based on the interaction of high-power lasers with plasma to form accelerating structures up to 1000 times smaller than standard radiofrequency cavities, and they come with an embedded X-ray source, namely betatron source, with unique properties: small source size and femtosecond pulse duration. A still unexplored possibility to exploit the betatron source comes from combining it with imaging methods able to encode multiple information like transmission and phase into a single-shot acquisition approach. In this work, we combine edge illumination-beam tracking (EI-BT) with a betatron X-ray source and present the demonstration of multimodal imaging (transmission, refraction, and scattering) with a compact light source down to the femtosecond timescale. The advantage of EI-BT is that it allows multimodal X-ray imaging technique, granting access to transmission, refraction and scattering signals from standard low-coherence laboratory X-ray sources in a single shot

Wave vector dependence of the dynamics in supercooled metallic liquids

We present a detailed investigation of the wave vector dependence of collective atomic motion in Au49Cu26.9Si16.3Ag5.5Pd2.3 and Pd42.5Cu27Ni9.5P21 supercooled liquids close to the glass transition temperature. Using x-ray photon correlation spectroscopy in a precedent uncovered spatial range of only few interatomic distances, we show that the microscopic structural relaxation process follows in phase the structure with a marked slowing down at the main average inter-particle distance. This behavior is accompanied by dramatic changes in the shape of the intermediate scattering functions which suggest the presence of large dynamical heterogeneities at length-scales corresponding to few particle diameters. A ballistic-like mechanism of particle motion seems to govern the structural relaxation of the two systems in the highly viscous phase, likely associated to hopping of caged particles in agreement with theoretical studies

Polarization of photospheric lines from turbulent dynamo simulations

We employ the magnetic and velocity fields from turbulent dynamo simulations to synthesize the polarization of a typical photospheric line. The synthetic Stokes profiles have properties in common with those observed in the quiet Sun. The simulated magnetograms present a level of signal similar to that of the Inter-Network regions. Asymmetric Stokes V profiles with two, three and more lobes appear in a natural way. The intensity profiles are broadened by the magnetic fields in fair agreement with observational limits. Furthermore, the Hanle depolarization signals of the Sr I 4607 A line turn out to be within the solar values. Differences between synthetic and observed polarized spectra can also be found. There is a shortage of Stokes V asymmetries, that we attribute to a deficit of structuring in the magnetic and velocity fields from the simulations as compared to the Sun This deficit may reflect the fact that the Reynolds numbers of the numerical data are still far from solar values. We consider the possibility that intense and tangled magnetic fields, like those in the simulations, exist in the Sun. This scenario has several important consequences. For example, less than 10% of the existing unsigned magnetic flux would be detected in present magnetograms. The existing flux would exceed by far that carried by active regions during the maximum of the solar cycle. Detecting these magnetic fields would involve improving the angular resolution, the techniques to interpret the polarization signals, and to a less extent, the polarimetric sensitivity.Comment: Accepted for publication in ApJ. 20 pag. 11 fig

Advanced structural analysis of a laser additive manufactured Zr-based bulk metallic glass along the build height

Additive manufacturing of bulk metallic glasses (BMGs) has opened this material class to an exciting new range of potential applications, as bulk-scale, net-shaped amorphous components can be fabricated in a single step. However, there exists a critical need to understand the structural details of additive manufactured BMGs and how the glassy structure is linked to the mechanical properties. Here, we present a study of structure and property variations along the build height for a laser powder bed fusion (LPBF) processed Zr-based BMG with composition Zr59.3Cu28.8Nb1.5Al10.4 commercially termed AMZ4, using hardness testing, calorimetry, positron annihilation spectroscopy, synchrotron X-ray diffraction, and transmission electron microscopy. A lower hardness, more rejuvenated glassy structure was found at the bottom of the build compared to the middle region of the build, with the structure and properties of the top region between the two. Such differences could not be attributed to variability in chemical composition or crystallisation; rather, the softer bottom region was found to have a larger medium range order cluster size, attributed to heat dissipation into the build plate during processing, which gave faster cooling rates and less reheating compared to the steady-state middle of the build. However, at the top of the build less reheating occurs compared to the middle, leading to a somewhat softer and less relaxed state