SWIRP (Submm-Wave and Long Wave InfraRed Polarimeter); Development and Characterization of a Sub-Mm Polarimeter for Ice Cloud Investigations

A major source of uncertainty in climate models is the presence, shape and distribution of ice particles in the uppermost layers of the clouds. The effects of this component are poorly constrained, turning ice particles into an almost-free variable in many climate models.NASA-GSFC is developing a new instrument aimed at measuring the size and shape of ice particles. The instrument consists of two sub-mm polarimeters (at 220 and 670 GHz) coupled with a long-wave infrared polarimeter at 10 micron. Each polarimeter has identical V-pol and H-pol channels; the axes of polarization are defined geometrically by the orientation of the waveguide elements, and the purity has been measured in the lab. The instrument is configured as a conical scanner, suitable for deployment as a payload on a small satellite or on a high-altitude sub-orbital platform. From a 400 km orbit, the instrument has a 3dB spatial resolution of 20 (10) km at 220 (670) GHz and a swath of 600 km over 180 degrees of view.The BAPTA (Bearing And Power Transfer Assembly) carries heritage from the SSMIS design, now in its 22nd year of on-orbit operation, but with a much reduced SWaP (Size Weight and Power) footprint, suitable for a small satellite.The main components of the instrument have been fabricated and are undergoing final testing prior to their integration as a single unit. The sub-mm channels have dedicated secondary reflectors which illuminate a shared primary reflector. The receiving units are placed behind the focal point of the optical arrangement, so that all beams equally illuminate the primary reflector and are almost co-located on the ground (within a single 220 GHz footprint). Primary and secondary beam patterns have been measured and verified to match the as-designed expectations. A Zytex (TM) window is deployed to protect the secondary reflectors and the feed horns from debris and other contaminants, and to reduce the heat load from the active (hot) IR calibration unit. The insertion loss of Zytex has been measured and is accounted in the calibration equation of the sub-mm channels.The radiometric performance of the sub-mm receivers has been characterized in the lab and under operational conditions of temperature and pressure.This paper discusses the design constraints on the sub-mm components, details of the scientific goals and their flowdown, and describes the characterization of the polarimeters. Options to optimize the layout and distribution of the masses within the assembly, with the goal of making the instrument even more compact and fully-compatible with cubesat-class satellites will be presented

Depolarization metric spaces for biological tissues classification

Classification of tissues is an important problem in biomedicine. An efficient tissue classification protocol allows, for instance, the guided-recognition of structures through treated images or discriminating between healthy and unhealthy regions (e.g., early detection of cancer). In this framework, we study the potential of some polarimetric metrics, the so-called depolarization spaces, for the classification of biological tissues. The analysis is performed using 120 biological ex vivo samples of three different tissues types. Based on these data collection, we provide for the first time a comparison between these depolarization spaces, as well as with most commonly used depolarization metrics, in terms of biological samples discrimination. The results illustrate the way to determine the set of depolarization metrics which optimizes tissue classification efficiencies. In that sense, the results show the interest of the method which is general, and which can be applied to study multiple types of biological samples, including of course human tissues. The latter can be useful for instance, to improve and to boost applications related to optical biopsy.Agència de Gestió d'Ajuts Universitaris i de Recerca, Grant/Award Number: 2017-SGR-001500; Ministerio de Economía y Competitividad, Grant/Award Numbers: Fondos FEDER, RTI2018-097107-B-C3

Measurements and Modeling of Near-Surface Radio Propagation in Glacial Ice and Implications for Neutrino Experiments

We present measurements of radio transmission in the $\sim$100 MHz range through a $\sim100$ m deep region below the surface of the ice at Summit Station, Greenland, called the firn. In the firn, the index of refraction changes due to the transition from snow at the surface to glacial ice below, affecting the propagation of radio signals in that region. We compare our observations to a finite-difference time-domain (FDTD) electromagnetic wave simulation, which supports the existence of three classes of propagation: a bulk propagation ray-bending mode that leads to so-called "shadowed" regions for certain geometries of transmission, a surface-wave mode induced by the ice/air interface, and an arbitrary-depth horizontal propagation mode that requires perturbations from a smooth density gradient. In the non-shadowed region, our measurements are consistent with the bulk propagation ray-bending mode both in timing and in amplitude. We also observe signals in the shadowed region, in conflict with a bulk-propagation-only ray-bending model, but consistent with FDTD simulations using a variety of firn models for Summit Station. The amplitude and timing of our measurements in all geometries are consistent with the predictions from FDTD simulations. In the shadowed region, the amplitude of the observed signals is consistent with a best-fit coupling fraction value of $2.4$% (0.06% in power) or less to a surface or horizontal propagation mode from the bulk propagation mode. The relative amplitude of observable signals in the two regions is important for experiments that aim to detect radio emission from astrophysical high-energy neutrinos interacting in glacial ice, which rely on a radio propagation model to inform simulations and perform event reconstruction.Comment: 14 pages, 13 figures, version accepted to PR

Land cover classification using multi-temporal MERIS vegetation indices

The spectral, spatial, and temporal resolutions of Envisat's Medium Resolution Imaging Spectrometer (MERIS) data are attractive for regional- to global-scale land cover mapping. Moreover, two novel and operational vegetation indices derived from MERIS data have considerable potential as discriminating variables in land cover classification. Here, the potential of these two vegetation indices (the MERIS global vegetation index (MGVI), MERIS terrestrial chlorophyll index (MTCI)) was evaluated for mapping eleven broad land cover classes in Wisconsin. Data acquired in the high and low chlorophyll seasons were used to increase inter-class separability. The two vegetation indices provided a higher degree of inter-class separability than data acquired in many of the individual MERIS spectral wavebands. The most accurate landcover map (73.2%) was derived from a classification of vegetation index-derived data with a support vector machine (SVM), and was more accurate than the corresponding map derived from a classification using the data acquired in the original spectral wavebands

ExoPlanet Optics: conceptual design processes for stealth telescopes

In this paper we examine several contrast-degrading static signature sources present in current terrestrial exoplanet Lyot Coronagraph/Telescope optical systems. These are: - Unnecessary optical surfaces, which increase cost, absorption, scatter, wavefront control and alignment issues. A suggested solution is to make every effort to investigate innovative solutions to reduce the number of optical surfaces during the early design phase. Consider free-form optics. - Diffraction from secondary support systems and classical hexagon segmented apertures, which masks the low IWA terrestrial exoplanets. A suggested mitigation is to investigate curved secondary support systems and a pinwheel architecture for the deployable primary aperture. - Polarization Fresnel and form birefringence aberrations, which distort the system PSF, introduce absorption, scatter and wavefront control issues. Mitigation is to reduce all ray-angles of incidence to a minimum, investigate zero-loss polarization compensation wavefront technology, and investigate metal thin film deposition processes required to minimize form birefringence in large-area high-reflectivity coatings. - Small-angle specular or resolved angle scattered light, which places a narrow halo of incoherent light around the base of the PSF. There is no requirement on mirror smooth-surface scatter. Investigate the physical source of the small angle scatter and develop mirror polishing and thin film deposition processes to minimize scatter

Tamoxifen for prevention of breast cancer: extended long-term follow-up of the IBIS-I breast cancer prevention trial

© Cuzick et al. Open Access article distributed under the terms of CC BY.http://dx.doi.org/10.1016/S1470-2045(14)71171-

Bayesian Classification and Regression Trees for Predicting Incidence of Cryptosporidiosis

Background Classification and regression tree (CART) models are tree-based exploratory data analysis methods which have been shown to be very useful in identifying and estimating complex hierarchical relationships in ecological and medical contexts. In this paper, a Bayesian CART model is described and applied to the problem of modelling the cryptosporidiosis infection in Queensland, Australia. Methodology/Principal Findings We compared the results of a Bayesian CART model with those obtained using a Bayesian spatial conditional autoregressive (CAR) model. Overall, the analyses indicated that the nature and magnitude of the effect estimates were similar for the two methods in this study, but the CART model more easily accommodated higher order interaction effects. Conclusions/Significance A Bayesian CART model for identification and estimation of the spatial distribution of disease risk is useful in monitoring and assessment of infectious diseases prevention and control

Mapping Drug Physico-Chemical Features to Pathway Activity Reveals Molecular Networks Linked to Toxicity Outcome

The identification of predictive biomarkers is at the core of modern toxicology. So far, a number of approaches have been proposed. These rely on statistical inference of toxicity response from either compound features (i.e., QSAR), in vitro cell based assays or molecular profiling of target tissues (i.e., expression profiling). Although these approaches have already shown the potential of predictive toxicology, we still do not have a systematic approach to model the interaction between chemical features, molecular networks and toxicity outcome. Here, we describe a computational strategy designed to address this important need. Its application to a model of renal tubular degeneration has revealed a link between physico-chemical features and signalling components controlling cell communication pathways, which in turn are differentially modulated in response to toxic chemicals. Overall, our findings are consistent with the existence of a general toxicity mechanism operating in synergy with more specific single-target based mode of actions (MOAs) and provide a general framework for the development of an integrative approach to predictive toxicology