Rigid-foldable parabolic deployable reflector concept based on the origami flasher pattern

This paper presents a novel deployable reflector concept based on the origami flasher pattern. The proposed folding architecture achieves rigid foldability for flasher patterns applied to doubly curved surfaces, allowing parabolic reflectors to be divided into a number of rigid panels for efficient stowage. Such an architecture provides an intermediate solution between current rigid-surface and flexible-surface reflectors, offering both surface precision and stowage compactness. The proposed patterns have a positive-finite degree of mobility, and so reliable and deterministic deployment is realized through suitable actuation. A Bayesian optimization approach is used in conjunction with kinematics and collision models in order to find optimal stowage patterns that accommodate finite thickness panels and supporting structures. For the generated optimal patterns, panel split line geometries are designed analytically to eliminate gaps while avoiding collision at panel edges during folding

Fixation dynamics of beneficial alleles in prokaryotic polyploid chromosomes and plasmids

Theoretical population genetics has been mostly developed for sexually reproducing diploid and for monoploid (haploid) organisms, focusing on eukaryotes. The evolution of bacteria and archaea is often studied by models for the allele dynamics in monoploid populations. However, many prokaryotic organisms harbor multicopy replicons—chromosomes and plasmids—and theory for the allele dynamics in populations of polyploid prokaryotes remains lacking. Here, we present a population genetics model for replicons with multiple copies in the cell. Using this model, we characterize the fixation process of a dominant beneficial mutation at 2 levels: the phenotype and the genotype. Our results show that depending on the mode of replication and segregation, the fixation of the mutant phenotype may precede genotypic fixation by many generations; we term this time interval the heterozygosity window. We furthermore derive concise analytical expressions for the occurrence and length of the heterozygosity window, showing that it emerges if the copy number is high and selection strong. Within the heterozygosity window, the population is phenotypically adapted, while both alleles persist in the population. Replicon ploidy thus allows for the maintenance of genetic variation following phenotypic adaptation and consequently for reversibility in adaptation to fluctuating environmental conditions

The tropopause inversion layer in models and analyses

Recent high-resolution radiosonde climatologies have revealed a tropopause inversion layer (TIL) in the extratropics: temperature strongly increases just above a sharp local cold point tropopause. Here, it is asked to what extent a TIL exists in current general circulation models (GCMs) and meteorological analyses. Only a weak hint of a TIL exists in NCEP/NCAR reanalysis data. In contrast, the Canadian Middle Atmosphere Model (CMAM), a comprehensive GCM, exhibits a TIL of realistic strength. However, in data assimilation mode CMAM exhibits a much weaker TIL, especially in the Southern Hemisphere where only coarse satellite data are available. The discrepancy between the analyses and the GCM is thus hypothesized to be mainly due to data assimilation acting to smooth the observed strong curvature in temperature around the tropopause. This is confirmed in the reanalysis where the stratification around the tropopause exhibits a strong discontinuity at the start of the satellite era

Potential for using simulated altitude as a means of prehabilitation:a physiology study

The current pandemic of surgical complications necessitates urgent and pragmatic innovation to reduce postoperative morbidity and mortality, which are associated with poor pre-operative fitness and anaemia. Exercise prehabilitation is a compelling strategy, but it has proven difficult to establish that it improves outcomes either in isolation or as part of a multimodal approach. Simulated altitude exposure improves performance in athletes and offers a novel potential means of improving cardiorespiratory and metabolic fitness and alleviating anaemia within the prehabilitation window. We aimed to provide an initial physiological foundation for ‘altitude prehabilitation’ by determining the physiological effects of one week of simulated altitude (FIO2 15%, equivalent to approximately 2438 m (8000 ft)) in older sedentary volunteers. The study used a randomised, double-blind, sham-controlled crossover design. Eight participants spent counterbalanced normoxic and hypoxic weeks in a residential hypoxia facility and underwent repeated cardiopulmonary exercise tests. Mean (SD) age of participants was 64 (7) y and they were unfit, with mean (SD) baseline anaerobic threshold 12 (2) ml.kg-1.min-1 and mean (SD) peak V̇O2 15 (3) ml.kg-1.min-1. Hypoxia was mild (mean (SD) SpO2 93 (2) %, p &lt; 0.001) and well-tolerated. Despite some indication of greater peak exercise capacity following hypoxia, overall there was no effect of simulated altitude on anaerobic threshold or peak V̇O2. However, hypoxia induced a substantial increase in mean (SD) haemoglobin of 1.5 (2.7) g.dl-1 (13% increase, p = 0.028). This study has established the concept and feasibility of ‘altitude prehabilitation’ and demonstrated specific potential for improving haematological fitness. Physiologically, there is value in exploring a possible role for simulated altitude in pre-operative optimisation.</p

Universal eigenvector statistics in a quantum scattering ensemble

We calculate eigenvector statistics in an ensemble of non-Hermitian matrices describing open quantum systems [F. Haake et al., Z. Phys. B 88, 359 (1992)] in the limit of large matrix size. We show that ensemble-averaged eigenvector correlations corresponding to eigenvalues in the center of the support of the density of states in the complex plane are described by an expression recently derived for Ginibre's ensemble of random non-Hermitian matrices.Comment: 4 pages, 5 figure

Ocean variability and its influence on the detectability of greenhouse warming signals

Recent investigations have considered whether it is possible to achieve early detection of greenhouse-gas-induced climate change by observing changes in ocean variables. In this study we use model data to assess some of the uncertainties involved in estimating when we could expect to detect ocean greenhouse warming signals. We distinguish between detection periods and detection times. As defined here, detection period is the length of a climate time series required in order to detect, at some prescribed significance level, a given linear trend in the presence of the natural climate variability. Detection period is defined in model years and is independent of reference time and the real time evolution of the signal. Detection time is computed for an actual time-evolving signal from a greenhouse warming experiment and depends on the experiment's start date. Two sources of uncertainty are considered: those associated with the level of natural variability or noise, and those associated with the time-evolving signals. We analyze the ocean signal and noise for spatially averaged ocean circulation indices such as heat and fresh water fluxes, rate of deep water formation, salinity, temperature, transport of mass, and ice volume. The signals for these quantities are taken from recent time-dependent greenhouse warming experiments performed by the Max Planck Institute for Meteorology in Hamburg with a coupled ocean-atmosphere general circulation model. The time-dependent greenhouse gas increase in these experiments was specified in accordance with scenario A of the Intergovernmental Panel on Climate Change. The natural variability noise is derived from a 300-year control run performed with the same coupled atmosphere-ocean model and from two long (>3000 years) stochastic forcing experiments in which an uncoupled ocean model was forced by white noise surface flux variations. In the first experiment the stochastic forcing was restricted to the fresh water fluxes, while in the second experiment the ocean model was additionally forced by variations in wind stress and heat fluxes. The mean states and ocean variability are very different in the three natural variability integrations. A suite of greenhouse warming simulations with identical forcing but different initial conditions reveals that the signal estimated from these experiments may evolve in noticeably different ways for some ocean variables. The combined signal and noise uncertainties translate into large uncertainties in estimates of detection time. Nevertheless, we find that ocean variables that are highly sensitive indicators of surface conditions, such as convective overturning in the North Atlantic, have shorter signal detection times (35?65 years) than deep-ocean indicators (≥100 years). We investigate also whether the use of a multivariate detection vector increases the probability of early detection. We find that this can yield detection times of 35?60 years (relative to a 1985 reference date) if signal and noise are projected onto a common ?fingerprint? which describes the expected signal direction. Optimization of the signal-to-noise ratio by (spatial) rotation of the fingerprint in the direction of low-noise components of the stochastic forcing experiments noticeably reduces the detection time (to 10?45 years). However, rotation in space alone does not guarantee an improvement of the signal-to-noise ratio for a time-dependent signal. This requires an ?optimal fingerprint? strategy in which the detection pattern (fingerprint) is rotated in both space and time

Incidence and sociodemographic characteristics of eczema diagnosis in children: a cohort study

Letter to the Editor

Identification of external influences on temperatures in California

We use eight different observational datasets to estimate California-average temperature trends over 1950-1999. Observed results are compared to trends from a suite of control simulations of natural internal climate variability. Observed increases in annual-mean surface temperature are distinguishable from climate noise in some but not all observational datasets. The most robust results are large positive trends in mean and maximum daily temperatures in late winter/early spring, as well as increases in minimum daily temperatures from January to September. These trends are inconsistent with model-based estimates of natural internal climate variability, and thus require one or more external forcing agents to be explained. Our results suggest that the warming of Californian winters over the second half of the twentieth century is associated with human-induced changes in large-scale atmospheric circulation. We also hypothesize that the lack of a detectable increase in summertime maximum temperature arises from a cooling associated with large-scale irrigation. This cooling may have, until now, counteracted the warming induced by increasing greenhouse gases and urbanization effects