First-principles calculation of the thermoelectric figure of merit for [2,2]paracyclophane-based single-molecule junctions

Here we present a theoretical study of the thermoelectric transport through {[}2,2{]}para\-cyclo\-phane-based single-molecule junctions. Combining electronic and vibrational structures, obtained from density functional theory (DFT), with nonequilibrium Green's function techniques, allows us to treat both electronic and phononic transport properties at a first-principles level. For the electronic part, we include an approximate self-energy correction, based on the DFT+$\Sigma$ approach. This enables us to make a reliable prediction of all linear response transport coefficients entering the thermoelectric figure of merit $ZT$. Paracyclophane derivatives offer a great flexibility in tuning their chemical properties by attaching different functional groups. We show that, for the specific molecule, the functional groups mainly influence the thermopower, allowing to tune its sign and absolute value. We predict that the functionalization of the bare paracyclophane leads to a largely enhanced electronic contribution $Z_{\mathrm{el}}T$ to the figure of merit. Nevertheless, the high phononic contribution to the thermal conductance strongly suppresses $ZT$. Our work demonstrates the importance to include the phonon thermal conductance for any realistic estimate of the $ZT$ for off-resonant molecular transport junctions. In addition, it shows the possibility of a chemical tuning of the thermoelectric properties for a series of available molecules, leading to equally performing hole- and electron-conducting junctions based on the same molecular framework.Comment: 8 pages, 7 figure

Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field Campaign

The High-Latitude Measurement of Snowfall (HiLaMS) campaign explored variability in snowfall properties and processes at meteorologically distinct field sites located in Haukeliseter, Norway, and Kiruna, Sweden, during the winters of 2016/17 and 2017/18, respectively. Campaign activities were founded upon the sensitivities of a low-cost, core instrumentation suite consisting of Micro Rain Radar, Precipitation Imaging Package, and Multi-Angle Snow Camera. These instruments are highly portable to remote field sites and, considered together, provide a unique and complementary set of snowfall observations including snowflake habit, particle size distributions, fall speeds, surface snowfall accumulations, and vertical profiles of radar moments and snow water content. These snow-specific parameters, used in combination with existing observations from the field sites such as snow gauge accumulations and ambient weather conditions, allow for advanced studies of snowfall processes. HiLaMS observations were used to 1) successfully develop a combined radar and in situ microphysical property retrieval scheme to estimate both surface snowfall accumulation and the vertical profile of snow water content, 2) identify the predominant snowfall regimes at Haukeliseter and Kiruna and characterize associated macrophysical and microphysical properties, snowfall production, and meteorological conditions, and 3) identify biases in the HARMONIE-AROME numerical weather prediction model for forecasts of snowfall accumulations and vertical profiles of snow water content for the distinct snowfall regimes observed at the mountainous Haukeliseter site. HiLaMS activities and results suggest value in the deployment of this enhanced snow observing instrumentation suite to new and diverse high-latitude locations that may be underrepresented in climate and weather process studies.Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field CampaignpublishedVersio

R2D2 TPC: first Xenon results

Radial time projection chambers (TPC), already employed in the search for rare phenomena such as light Dark Matter candidate, could provide a new detection approach for the search of neutrinoless double beta decay ($\beta\beta0\nu$). The assessment of the performances of such a detector for $\beta\beta0\nu$ search is indeed the goal of the Rare Decays with Radial Detector (R2D2) R\&D. Promising results operating a spherical TPC with argon up to 1~bar have been published in 2021. Supplementary measurements were recently taken extending the gas pressure range up to 3~bar. In addition, a comparison between two detector geometries, namely spherical (SPC for spherical proportional counter) and cylindrical (CPC for cylindrical proportional counter), was performed. Using a relatively simple gas purification system the CPC detector was also operated with xenon at 1~bar: an energy resolution of 1.4\% full-width at half-maximum was achieved for drift distances up to 17~cm. Much lower resolution was observed with the SPC. These results are presented in this article.Comment: 16 pages 14 figure

Clinical Outcomes With a Repositionable Self-Expanding Transcatheter Aortic Valve Prosthesis: The International FORWARD Study

Background Clinical outcomes in large patient populations from real-world clinical practice with a next-generation self-expanding transcatheter aortic valve are lacking. Objectives This study sought to document the clinical and device performance outcomes of transcatheter aortic valve replacement (TAVR) with a next-generation, self-expanding transcatheter heart valve (THV) system in patients with severe symptomatic aortic stenosis (AS) in routine clinical practice. Methods The FORWARD (CoreValve Evolut R FORWARD) study is a prospective, single-arm, multinational, multicenter, observational study. An independent clinical events committee adjudicated safety endpoints based on Valve Academic Research Consortium-2 definitions. An independent echocardiographic core laboratory evaluated all echocardiograms. From January 2016 to December 2016, TAVR with the next-generation self-expanding THV was attempted in 1,038 patients with symptomatic, severe AS at 53 centers on 4 continents. Results Mean age was 81.8 ± 6.2 years, 64.9% were women, the mean Society of Thoracic Surgeons Predicted Risk of Mortality was 5.5 ± 4.5%, and 33.9% of patients were deemed frail. The repositioning feature of the THV was applied in 25.8% of patients. A single valve was implanted in the proper anatomic location in 98.9% of patients. The mean aortic valve gradient was 8.5 ± 5.6 mm Hg, and moderate or severe aortic regurgitation was 1.9% at discharge. All-cause mortality was 1.9%, and disabling stroke occurred in 1.8% at 30 days. The expected-to-observed early surgical mortality ratio was 0.35. A pacemaker was implanted in 17.5% of patients. Conclusions TAVR using the next-generation THV is clinically safe and effective for treating older patients with severe AS at increased operative risk. (CoreValve Evolut R FORWARD Study [FORWARD]; NCT02592369

Nucleo-cytoplasmic transport of proteins and RNA in plants

Merkle T. Nucleo-cytoplasmic transport of proteins and RNA in plants. Plant Cell Reports. 2011;30(2):153-176.Transport of macromolecules between the nucleus and the cytoplasm is an essential necessity in eukaryotic cells, since the nuclear envelope separates transcription from translation. In the past few years, an increasing number of components of the plant nuclear transport machinery have been characterised. This progress, although far from being completed, confirmed that the general characteristics of nuclear transport are conserved between plants and other organisms. However, plant-specific components were also identified. Interestingly, several mutants in genes encoding components of the plant nuclear transport machinery were investigated, revealing differential sensitivity of plant-specific pathways to impaired nuclear transport. These findings attracted attention towards plant-specific cargoes that are transported over the nuclear envelope, unravelling connections between nuclear transport and components of signalling and developmental pathways. The current state of research in plants is summarised in comparison to yeast and vertebrate systems, and special emphasis is given to plant nuclear transport mutants

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

Swarm Learning for decentralized and confidential clinical machine learning

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine

Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease

The DUNE far detector vertical drift technology. Technical design report

DUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals