Similar ultrafast dynamics of several dissimilar Dirac and Weyl semimetals

Recent years have seen the rapid discovery of solids whose low-energy electrons have a massless, linear dispersion, such as Weyl, line-node, and Dirac semimetals. The remarkable optical properties predicted in these materials show their versatile potential for optoelectronic uses. However, little is known of their response in the picoseconds after absorbing a photon. Here we measure the ultrafast dynamics of four materials that share non-trivial band structure topology but that differ chemically, structurally, and in their low-energy band structures: ZrSiS, which hosts a Dirac line node and Dirac points; TaAs and NbP, which are Weyl semimetals; and Sr$_{1-y}$Mn$_{1-z}$Sb$_2$, in which Dirac fermions coexist with broken time-reversal symmetry. After photoexcitation by a short pulse, all four relax in two stages, first sub-picosecond, and then few-picosecond. Their rapid relaxation suggests that these and related materials may be suited for optical switches and fast infrared detectors. The complex change of refractive index shows that photoexcited carrier populations persist for a few picoseconds

The Association of Multiple Gene Variants with Ageing Skeletal Muscle Phenotypes in Elderly Women

There is a scarcity of studies that have investigated the role of multiple single nucleotide polymorphisms (SNPs) on a range of muscle phenotypes in an elderly population. The present study investigated the possible association of 24 SNPs with skeletal muscle phenotypes in 307 elderly Caucasian women (aged 60–91 years, 66.3 ± 11.3 kg). Skeletal muscle phenotypes included biceps brachii thickness, vastus lateralis cross-sectional areas, maximal hand grip strength, isometric knee extension and elbow flexion torque. Genotyping for 24 SNPs, chosen on their skeletal muscle structural or functional links, was conducted on DNA extracted from blood or saliva. Of the 24 SNPs, 10 were associated with at least one skeletal muscle phenotype. HIF1A rs11549465 was associated with three skeletal muscle phenotypes and PTK2 rs7460 and ACVR1B rs10783485 were each associated with two phenotypes. PTK2 rs7843014, COL1A1 rs1800012, CNTF rs1800169, NOS3 rs1799983, MSTN rs1805086, TRHR rs7832552 and FTO rs9939609 were each associated with one. Elderly women possessing favourable genotypes were 3.6–13.2% stronger and had 4.6–14.7% larger muscle than those with less favourable genotypes. These associations, together with future work involving a broader range of SNPs, may help identify individuals at particular risk of an age-associated loss of independence.</jats:p

Critical current density: Measurements vs. reality

Different experimental techniques are employed to evaluate the critical current density (Jc), namely transport current measurements and two different magnetisation measurements forming quasi-equilibrium and dynamic critical states. Our technique-dependent results for superconducting YBa 2Cu3O7 (YBCO) film and MgB2 bulk samples show an extremely high sensitivity of Jc and associated interpretations, such as irreversibility fields and Kramer plots, which lose meaning without a universal approach. We propose such approach for YBCO films based on their unique pinning features. This approach allows us to accurately recalculate the magnetic-field-dependent Jc obtained by any technique into the Jc behaviour, which would have been measured by any other method without performing the corresponding experiments. We also discovered low-frequency-dependent phenomena, governing flux dynamics, but contradicting the considered ones in the literature. The understanding of these phenomena, relevant to applications with moving superconductors, can clarify their dramatic impact on the electric-field criterion through flux diffusivity and corresponding measurements. © Copyright EPLA, 2013

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

Time-varying wing-twist improves aerodynamic efficiency of forward flight in butterflies

PMC3547021Insect wings can undergo significant chordwise (camber) as well as spanwise (twist) deformation during flapping flight but the effect of these deformations is not well understood. The shape and size of butterfly wings leads to particularly large wing deformations, making them an ideal test case for investigation of these effects. Here we use computational models derived from experiments on free-flying butterflies to understand the effect of time-varying twist and camber on the aerodynamic performance of these insects. High-speed videogrammetry is used to capture the wing kinematics, including deformation, of a Painted Lady butterfly (Vanessa cardui) in untethered, forward flight. These experimental results are then analyzed computationally using a high-fidelity, three-dimensional, unsteady Navier-Stokes flow solver. For comparison to this case, a set of non-deforming, flat-plate wing (FPW) models of wing motion are synthesized and subjected to the same analysis along with a wing model that matches the time-varying wing-twist observed for the butterfly, but has no deformation in camber. The simulations show that the observed butterfly wing (OBW) outperforms all the flat-plate wings in terms of usable force production as well as the ratio of lift to power by at least 29% and 46%, respectively. This increase in efficiency of lift production is at least three-fold greater than reported for other insects. Interestingly, we also find that the twist-only-wing (TOW) model recovers much of the performance of the OBW, demonstrating that wing-twist, and not camber is key to forward flight in these insects. The implications of this on the design of flapping wing micro-aerial vehicles are discussed.JH Libraries Open Access Fun

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Polygenic Models Partially Predict Muscle Size and Strength but Not Low Muscle Mass in Older Women

BACKGROUND Heritability explains 45-82% of muscle mass and strength variation, yet polygenic models for muscle phenotypes in older women are scarce. Therefore, the objective of the present study was to (1) assess if total genotype predisposition score (GPS) for a set of polymorphisms differed between older women with low and high muscle mass, and (2) utilise a data-driven GPS (GPS) to predict the variance in muscle size and strength-related phenotypes. METHODS In three-hundred 60- to 91-year-old Caucasian women (70.7 ± 5.7 years), skeletal muscle mass, biceps brachii thickness, vastus lateralis anatomical cross-sectional area (VL), hand grip strength (HGS), and elbow flexion (MVC) and knee extension (MVC) maximum voluntary contraction were measured. Participants were classified as having low muscle mass if the skeletal muscle index (SMI) &lt; 6.76 kg/m or relative skeletal muscle mass (%SMM) &lt; 22.1%. Genotyping was completed for 24 single-nucleotide polymorphisms (SNPs). GPS was calculated from 23 SNPs and compared between the low and high muscle mass groups. A GPS was performed to identify the association of SNPs with other skeletal muscle phenotypes. RESULTS There was no significant difference in GPS between low and high muscle mass groups, irrespective of classification based on SMI or %SMM. The GPS model, using 23 selected SNPs, revealed that 13 SNPs were associated with at least one skeletal muscle phenotype: rs11549465 was associated with four phenotypes and, in descending number of phenotype associations, rs4341 with three; rs7460 and rs2070802 with two; and rs17421511, rs10783485, rs1800169, rs1801131, rs1537516, rs7832552, rs1805086, rs1800012, and rs9939609 with one phenotype. The GPS with age included as a predictor variable explained 1.7% variance of biceps brachii thickness, 12.5% of VL, 19.0% of HGS, 8.2% of MVC, and 9.6% of MVC. CONCLUSIONS In older women, GPS did not differ between low and high muscle mass groups. However, GPS was associated with muscle size and strength phenotypes. Further advancement of polygenic models to understand skeletal muscle function during ageing might become useful in targeting interventions towards older adults most likely to lose physical independence