Reflectance spectroscopy of indoor settled dust in Tel Aviv, Israel: comparison between the spring and the summer seasons

International audienceThe influence of mineral and anthropogenic dust components on the VIS-NIR-SWIR spectral reflectance of artificial laboratory dust mixtures was evaluated and used in combination with Partial Least Squares (PLS) regression to construct a model that correlates the dust content with its reflectance. Small amounts of dust (0.018?0.33 mg/cm2) were collected using glass traps placed in different indoor environments in Tel Aviv, Israel during the spring and summer of 2005. The constructed model was applied to reflectance spectroscopy measurements derived from the field dust samples to assess their mineral content. Additionally, field samples were examined using Principal Component Analysis (PCA) to identify the most representative spectral pattern for each season. Across the visible range of spectra two main spectral shapes were observed, convex and concave, though spectra exhibiting hybrid shapes were also seen. Spectra derived from spring season dust samples were characterized mostly by a convex shape, which indicates a high mineral content. In contrast, the spectra generated from summer samples were characterized generally by a concave shape, which indicates a high organic matter content. In addition to this seasonal variation in spectral patterns, spectral differences were observed associated with the dwelling position in the city. Samples collected in the city center showed higher organic content, whereas samples taken from locations at the city margins, near the sea and next to open areas, exhibited higher mineral content. We conclude that mineral components originating in the outdoor environment influence indoor dust loads, even when considering relatively small amounts of indoor settled dust. The sensitive spectral-based method developed here has potentially many applications for environmental researchers and policy makers concerned with dust pollution

Stability of Relativistic Matter with Magnetic Fields for Nuclear Charges up to the Critical Value

We give a proof of stability of relativistic matter with magnetic fields all the way up to the critical value of the nuclear charge $Z\alpha=2/\pi$.Comment: LaTeX2e, 12 page

Compressible flow structures interaction with a two-dimensional ejector: a cold-flow study

An experimental study has been conducted to examine the interaction of compressible flow structures such as shocks and vortices with a two-dimensional ejector geometry using a shock-tube facility. Three diaphragm pressure ratios ofP4 =P1 = 4, 8, and 12 have been employed, whereP4 is the driver gas pressure andP1 is the pressure within the driven compartment of the shock tube. These lead to incident shock Mach numbers of Ms = 1:34, 1.54, and 1.66, respectively. The length of the driver section of the shock tube was 700 mm. Air was used for both the driver and driven gases. High-speed shadowgraphy was employed to visualize the induced flowfield. Pressure measurements were taken at different locations along the test section to study theflow quantitatively. The induced flow is unsteady and dependent on the degree of compressibility of the initial shock wave generated by the rupture of the diaphragm

Mineral content analysis of atmospheric dust using hyperspectralinformation from space

The Bodélé depression of northern Chad is considered one of the world\u27s largest sources of atmospheric mineral dust. Mineral composition of such transported dust is essential to our understanding of climate forcing, mineralogy of dust sources, aerosol optical properties, and mineral deposition to Amazon forests. In this study we examine hyperspectral information acquired over the Bodélé by EO‐1 Hyperion satellite during a dust storm event and during a calm clean day. We show that, for the suspended dust, the absorption signature can be decoupled from scattering, allowing detection of key minerals. Our results, based on the visible and shortwave infrared hyperspectral data, demonstrate that the Bodélé surface area is composed of iron‐oxides, clays (kaosmectite) and sulfate groups (gypsum). Atmospheric dust spectra downwind of Bodélé reveal striking differences in absorption signatures across shortwave infrared from those of the underlying surface

Acid sensing by the Drosophila olfactory system.

The odour of acids has a distinct quality that is perceived as sharp, pungent and often irritating. How acidity is sensed and translated into an appropriate behavioural response is poorly understood. Here we describe a functionally segregated population of olfactory sensory neurons in the fruitfly, Drosophila melanogaster, that are highly selective for acidity. These olfactory sensory neurons express IR64a, a member of the recently identified ionotropic receptor (IR) family of putative olfactory receptors. In vivo calcium imaging showed that IR64a+ neurons projecting to the DC4 glomerulus in the antennal lobe are specifically activated by acids. Flies in which the function of IR64a+ neurons or the IR64a gene is disrupted had defects in acid-evoked physiological and behavioural responses, but their responses to non-acidic odorants remained unaffected. Furthermore, artificial stimulation of IR64a+ neurons elicited avoidance responses. Taken together, these results identify cellular and molecular substrates for acid detection in the Drosophila olfactory system and support a labelled-line mode of acidity coding at the periphery

C-axis lattice dynamics in Bi-based cuprate superconductors

We present results of a systematic study of the c axis lattice dynamics in single layer Bi2Sr2CuO6 (Bi2201), bilayer Bi2Sr2CaCu2O8 (Bi2212) and trilayer Bi2Sr2Ca2Cu3O10 (Bi2223) cuprate superconductors. Our study is based on both experimental data obtained by spectral ellipsometry on single crystals and theoretical calculations. The calculations are carried out within the framework of a classical shell model, which includes long-range Coulomb interactions and short-range interactions of the Buckingham form in a system of polarizable ions. Using the same set of the shell model parameters for Bi2201, Bi2212 and Bi2223, we calculate the frequencies of the Brillouin-zone center phonon modes of A2u symmetry and suggest the phonon mode eigenvector patterns. We achieve good agreement between the calculated A2u eigenfrequencies and the experimental values of the c axis TO phonon frequencies which allows us to make a reliable phonon mode assignment for all three Bi-based cuprate superconductors. We also present the results of our shell model calculations for the Gamma-point A1g symmetry modes in Bi2201, Bi2212 and Bi2223 and suggest an assignment that is based on the published experimental Raman spectra. The superconductivity-induced phonon anomalies recently observed in the c axis infrared and resonant Raman scattering spectra in trilayer Bi2223 are consistently explained with the suggested assignment.Comment: 29 pages, 13 figure

A global spectral library to characterize the world's soil

Soil provides ecosystem services, supports human health and habitation, stores carbon and regulates emissions of greenhouse gases. Unprecedented pressures on soil from degradation and urbanization are threatening agro-ecological balances and food security. It is important that we learn more about soil to sustainably manage and preserve it for future generations. To this end, we developed and analyzed a global soil visible-near infrared (vis-NIR) spectral library. It is currently the largest and most diverse database of its kind. We show that the information encoded in the spectra can describe soil composition and be associated to land cover and its global geographic distribution, which acts as a surrogate for global climate variability. We also show the usefulness of the global spectra for predicting soil attributes such as soil organic and inorganic carbon, clay, silt, sand and iron contents, cation exchange capacity, and pH. Using wavelets to treat the spectra, which were recorded in different laboratories using different spectrometers and methods, helped to improve the spectroscopic modelling. We found that modelling a diverse set of spectra with a machine learning algorithm can find the local relationships in the data to produce accurate predictions of soil properties. The spectroscopic models that we derived are parsimonious and robust, and using them we derived a harmonized global soil attribute dataset, which might serve to facilitate research on soil at the global scale. This spectroscopic approach should help to deal with the shortage of data on soil to better understand it and to meet the growing demand for information to assess and monitor soil at scales ranging from regional to global. New contributions to the library are encouraged so that this work and our collaboration might progress to develop a dynamic and easily updatable database with better global coverage. We hope that this work will reinvigorate our community's discussion towards larger, more coordinated collaborations. We also hope that use of the database will deepen our understanding of soil so that we might sustainably manage it and extend the research outcomes of the soil, earth and environmental sciences towards applications that we have not yet dreamed of

Inadequacy of Existing Clinical Prediction Models for Predicting Mortality after Transcatheter Aortic Valve Implantation

Background: The performance of emerging transcatheter aortic valve implantation (TAVI) clinical prediction models (CPMs) in national TAVI cohorts distinct from those where they have been derived is unknown. This study aimed to investigate the performance of the German Aortic Valve, FRANCE-2, OBSERVANT and American College of Cardiology (ACC) TAVI CPMs compared with the performance of historic cardiac CPMs such as the EuroSCORE and STS-PROM, in a large national TAVI registry. Methods: The calibration and discrimination of each CPM were analyzed in 6676 patients from the UK TAVI registry, as a whole cohort and across several subgroups. Strata included gender, diabetes status, access route, and valve type. Furthermore, the amount of agreement in risk classification between each of the considered CPMs was analyzed at an individual patient level. Results: The observed 30-day mortality rate was 5.4%. In the whole cohort, the majority of CPMs over-estimated the risk of 30-day mortality, although the mean ACC score (5.2%) approximately matched the observed mortality rate. The areas under ROC curve were between 0.57 for OBSERVANT and 0.64 for ACC. Risk classification agreement was low across all models, with Fleiss's kappa values between 0.17 and 0.50. Conclusions: Although the FRANCE-2 and ACC models outperformed all other CPMs, the performance of current TAVI-CPMs was low when applied to an independent cohort of TAVI patients. Hence, TAVI specific CPMs need to be derived outside populations previously used for model derivation, either by adapting existing CPMs or developing new risk scores in large national registries