Quantum fluctuations of D5dD_{5d} polarons on C60C_{60} molecules

The dynamic Jahn-Teller splitting of the six equivalent $D_{5d}$ polarons due to quantum fluctuations is studied in the framework of the Bogoliubov-de Gennes formalism. The tunneling induced level splittings are determined to be $^2 T_{1u} \bigoplus ^2 T_{2u}$ and $^1 A_g \bigoplus ^1 H_g$ for $C_{60}^{1-}$ and $C_{60}^{2-}$, respectively, which should give rise to observable effects in experiments.Comment: REVTEX 3.0, 13 pages, to be published in Phys. Rev.

Thermodynamically stable noncomposite vortices in mesoscopic two-gap superconductors

In mesoscopic two-gap superconductors with sizes of the order of the coherence length noncomposite vortices are found to be thermodynamically stable in a large domain of the $T - H$ phase diagram. In these phases the vortex cores of one condensate are spatially separated from the other condensate ones, and their respective distributions can adopt distinct symmetries. The appearance of these vortex phases is caused by a non-negligible effect of the boundary of the sample on the superconducting order parameter and represents therefore a genuine mesoscopic effect. For low values of interband Josephson coupling vortex patterns with $L_1 \neq L_2$ can arise in addition to the phases with $L_1 =L_2$, where $L_1$ and $L_2$ are total vorticities in the two condensates. The calculations show that noncomposite vortices could be observed in thin mesoscopic samples of MgB$_{2}$.Comment: 5 pages, 3 figures, to be published in Europhysics Letter

Radiative transfer as a Bayesian linear regression problem

Electromagnetic radiation plays a crucial role in various physical and chemical processes. Hence, almost all astrophysical simulations require some form of radiative transfer model. Despite many innovations in radiative transfer algorithms and their implementation, realistic radiative transfer models remain very computationally expensive, such that one often has to resort to approximate descriptions. The complexity of these models makes it difficult to assess the validity of any approximation and to quantify uncertainties on the model results. This impedes scientific rigour, in particular, when comparing models to observations, or when using their results as input for other models. We present a probabilistic numerical approach to address these issues by treating radiative transfer as a Bayesian linear regression problem. This allows us to model uncertainties on the input and output of the model with the variances of the associated probability distributions. Furthermore, this approach naturally allows us to create reduced-order radiative transfer models with a quantifiable accuracy. These are approximate solutions to exact radiative transfer models, in contrast to the exact solutions to approximate models that are often used. As a first demonstration, we derive a probabilistic version of the method of characteristics, a commonly-used technique to solve radiative transfer problems

Theory of Spontaneous Polarization of Endohedral Fullerenes

A pseudo-Jahn-Teller model describing central atom distortions is proposed for endohedral fullerenes of the form A@C$_{60}$ where A is either a rare gas or a metal atom. A critical (dimensionless) coupling $g_c$ is found, below which the symmetric configuration is stable and above which inversion symmetry is broken. Vibronic parameters are given for selected endohedral fullerenes.Comment: 4 pages, REVTEX, 1 Postscript figure. [Phys. Rev. Lett. (in press)

PCovR2:A flexible principal covariates regression approach to parsimoniously handle multiple criterion variables

Principal covariates regression (PCovR) allows one to deal with the interpretational and technical problems associated with running ordinary regression using many predictor variables. In PCovR, the predictor variables are reduced to a limited number of components, and simultaneously, criterion variables are regressed on these components. By means of a weighting parameter, users can flexibly choose how much they want to emphasize reconstruction and prediction. However, when datasets contain many criterion variables, PCovR users face new interpretational problems, because many regression weights will be obtained and because some criteria might be unrelated to the predictors. We therefore propose PCovR2, which extends PCovR by also reducing the criteria to a few components. These criterion components are predicted based on the predictor components. The PCovR2 weighting parameter can again be flexibly used to focus on the reconstruction of the predictors and criteria, or on filtering out relevant predictor components and predictable criterion components. We compare PCovR2 to two other approaches, based on partial least squares (PLS) and principal components regression (PCR), that also reduce the criteria and are therefore called PLS2 and PCR2. By means of a simulated example, we show that PCovR2 outperforms PLS2 and PCR2 when one aims to recover all relevant predictor components and predictable criterion components. Moreover, we conduct a simulation study to evaluate how well PCovR2, PLS2 and PCR2 succeed in finding (1) all underlying components and (2) the subset of relevant predictor and predictable criterion components. Finally, we illustrate the use of PCovR2 by means of empirical data

Blockwise simple component analysis via rotation, constraints or penalties, with an application to product × attribute × panelist data

Sensory profiling data consisting of judgements on a number of products with respect to a number of attributes by a number of panelists can be summarized in various ways. Besides finding components describing the main product features, there is an interest in individual panelist behavior. Earlier methods identify this by means of separate PCAs, Procrustes analyses, or three-way component methods, but these give only global comparisons of panelists. In the present paper, methods that can distinguish panelist behavior related to separate attributes, are described. These methods model the data in such a way that blocks of loadings pertaining to the attributes are either small or large. At the same time, one can zoom in on the loadings for panelists within each block of loadings associated with an attribute to inspect differences in panelist behavior. Two types of methods have been proposed for this earlier (rotation to simple blocks and penalizing blocks of loadings), and a third one is proposed in the present paper (constraining blocks of loadings to zero). The new approach is compared here to the other two methods. It is found that the rotation and constraints approaches work about equally well and better than the penalty approach. However, the rotation approach offers richer panelist behavior information, as is illustrated by the analysis of empirical data. It is also shown how, in this example, the reliability of idiosyncratic panelist behavior indicators can be evaluated.status: publishe

Vegetation reflectance spectroscopy for biomonitoring of heavy metal pollution in urban soils

Heavy metals in urban soils may impose a threat to public health and may negatively affect urban tree viability. Vegetation spectroscopy techniques applied to bio-indicators bring new opportunities to characterize heavy metal contamination, without being constrained by laborious soil sampling and lab-based sample processing. Here we used Tilia tomentosa trees, sampled across three European cities, as bio-indicators i) to investigate the impacts of elevated concentrations of cadmium (Cd) and lead (Pb) on leaf mass per area (LMA), total chlorophyll content (Chl), chlorophyll a to b ratio (Chla:Chlb) and the maximal PSII photochemical efficiency (Fv/Fm); and ii) to evaluate the feasibility of detecting Cd and Pb contamination using leaf reflectance spectra. For the latter, we used a partial-least-squares discriminant analysis (PLS-DA) to train spectral-based models for the classification of Cd and/or Pb contamination. We show that elevated soil Pb concentrations induced a significant decrease in the LMA and Chla:Chlb, with no decrease in Chl. We did not observe pronounced reductions of Fv/Fm due to Cd and Pb contamination. Elevated Cd and Pb concentrations induced contrasting spectral changes in the red-edge (690–740 nm) region, which might be associated with the proportional changes in leaf pigments. PLS-DA models allowed for the classifications of Cd and Pb contamination, with a classification accuracy of 86% (Kappa = 0.48) and 83% (Kappa = 0.66), respectively. PLS-DA models also allowed for the detection of a collective elevation of soil Cd and Pb, with an accuracy of 66% (Kappa = 0.49). This study demonstrates the potential of using reflectance spectroscopy for biomonitoring of heavy metal contamination in urban soils.info:eu-repo/semantics/acceptedVersio

Impact of the COVID-19 pandemic on Swiss pregnant and breastfeeding women - a cross-sectional study covering the first pandemic wave.

Information on the impact of the COVID-19 pandemic on pregnancy and breastfeeding experiences, as well as on perinatal mental health in Switzerland is limited. In Switzerland, there are few national studies and little information. Using an anonymous online survey accessible after the first wave of the outbreak in Switzerland, we have investigated how this pandemic affected pregnant and breastfeeding women. Among women who completed the survey, 69.0% (1050/1518) indicated the first wave of the pandemic affected their personal habits, 61.0% (689/1131) were affected in their work and 40.0% (632/1573) reported impaired relations with healthcare services (different denominators correspond to the number of participants who answered the question). 36.8% (110/299) of women reported an impact of the pandemic on their current pregnancy experience or breastfeeding experience (8.2%, 46/555). Overall, 11.6% (170/1467) of participants who completed the validated screening tests for mental health symptoms (Edinburgh Postnatal Depression Scale, Generalized Anxiety Disorder 7, Perceived Stress Scale) presented a score compatible with symptoms of major depression, severe anxiety or high perceived stress, which is higher than in the pre-pandemic period according to literature. Risk factors independently associated with impaired mental health were being hospitalized, having symptoms of COVID-19, living with a person with COVID-19 symptoms, having comorbidities, having experienced reduced healthcare services, having restricted usual activities and being a housewife. Protective factors independently associated were a high level of education and living with a partner. Our findings suggest that the COVID-19 pandemic might have significantly affected the well-being and mental health of pregnant and breastfeeding women, directly in the case of exposure, and indirectly as a result of the potential modifications in their life habits and in healthcare facilities

Atmospheric drivers of storage water use in Scots pine

International audienceIn this study we determined the microclimatic drivers of storage water use in Scots pine (Pinus sylvestris L.) growing in a temperate climate. The storage water use was modeled using the ANAFORE model, integrating a dynamic water flow and ? storage model with a process-based transpiration model. The model was calibrated and validated with sap flow measurements for the growing season of 2000 (26 May?18 October). Because there was no severe soil drought during the study period, we were able to study atmospheric effects. Incoming radiation was the main driver of storage water use. The general trends of sap flow and storage water use are similar, and follow more or less the pattern of incoming radiation. Nevertheless, considerable differences in the day-to-day pattern of sap flow and storage water use were observed, mainly driven by vapour pressure deficit (VPD). During dry atmospheric conditions (high VPD) storage water use was reduced. This reduction was disproportionally higher than the reduction in measured sap flow. Our results suggest that the trees did not rely more on storage water during periods of atmospheric drought, without severe soil drought. A third important factor was the tree water deficit. When storage compartments were depleted beyond a threshold, storage water use was limited due to the low water potential in the storage compartments. The maximum relative contribution of storage water to daily transpiration was also constrained by an increasing tree water deficit