A Comparison of Temperatures Inside Protective Headgear With Indicators of Physiological Strain and Core Temperatures During Exercise in a Hot Environment

Introduction: Non-invasive temperature monitoring with a sensor mounted inside protective headgear such as a football or military helmet or a construction hardhat may be an effective method of detecting temperatures that are indicative of increased risk of heat illness. Hothead Technologies has developed a system for providing temperature information to medical personnel responsible for the health of the individual. Purpose: The purposes of this study were to establish the relationship between in-hardhat temperature (Tih) readings, markers of physiological strain and perceptual responses, and to determine the differences between the in-helmet temperature readings and core temperature (Tc) as measured by rectal (Tre) and esophageal (Tes) probes. Methods: Thirty males (age, 24.57 ± 4.32 years; height 180.51 ±7.06 cm; body mass, 81.06 ±9.35 kg; percent body fat, 13.76 ±5.11; VO2max, 46.84 ± 7.10 mL/Kg/min) completed two experimental trials separated by a minimum of one week: a continuous submaximal exercise (CSE) condition and a series of high intensity 30-second sprints (HIE) with a one-minute rest period between each sprint. Exercise in both conditions was carried out in a 36o C environment with a relative humidity of 40% while wearing a standard construction hardhat with a sensor mounted in the forehead area of the head strap, and continued until one of the following two criteria was met: the subject voluntarily terminated the session, or the subject’s Tc reached 39.5oC. Temperatures, heart rate, cardiorespiratory, and perceptual responses were monitored throughout, and balance error scoring system (BESS) and mental function tests were conducted before and after exercise. A physiological strain index (PSI) was calculated from Tc and HR. Results: CV- Calculated from final temp. Conclusion: The general agreement between the Tih and other temperature measures along with the consistency as indicated by the low coefficient of variation in the recordings of the Tih sensors at the point of termination suggest that this device may have application as a warning system for impending heat-related problems

Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms: validation against collocated MODIS and CALIOP data

The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO₂) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols, i.e., contamination, within the instrument's field of view. Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) X_(CO₂) retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 µm O₂ A band, neglecting scattering by clouds and aerosols, which introduce photon path-length differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO₂ and H₂O column abundances using observations taken at 1.61 µm (weak CO₂ band) and 2.06 µm (strong CO₂ band), while neglecting atmospheric scattering. The CO₂ and H₂O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which are sensitive to different features in the spectra, provides the basis for cloud screening of the OCO-2 data set. To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning of algorithmic threshold parameters that allows for processing of  ≃ 20–25 % of all OCO-2 soundings, agreement between the OCO-2 and MODIS cloud screening methods is found to be  ≃ 85 % over four 16-day orbit repeat cycles in both the winter (December) and spring (April–May) for OCO-2 nadir-land, glint-land and glint-water observations. No major, systematic, spatial or temporal dependencies were found, although slight differences in the seasonal data sets do exist and validation is more problematic with increasing solar zenith angle and when surfaces are covered in snow and ice and have complex topography. To further analyze the performance of the cloud screening algorithms, an initial comparison of OCO-2 observations was made to collocated measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). These comparisons highlight the strength of the OCO-2 cloud screening algorithms in identifying high, thin clouds but suggest some difficulty in identifying some clouds near the surface, even when the optical thicknesses are greater than 1

A Systematic Retrieval Analysis of Secondary Eclipse Spectra. I. A Comparison of Atmospheric Retrieval Techniques

Exoplanet atmosphere spectroscopy enables us to improve our understanding of exoplanets just as remote sensing in our own solar system has increased our understanding of the solar system bodies. The challenge is to quantitatively determine the range of temperatures and molecular abundances allowed by the data, which is often difficult given the low information content of most exoplanet spectra that commonly leads to degeneracies in the interpretation. A variety of spectral retrieval approaches have been applied to exoplanet spectra, but no previous investigations have sought to compare these approaches. We compare three different retrieval methods: optimal estimation, differential evolution Markov chain Monte Carlo, and bootstrap Monte Carlo on a synthetic water-dominated hot Jupiter. We discuss expectations of uncertainties in abundances and temperatures given current and potential future observations. In general, we find that the three approaches agree for high spectral resolution, high signal-to-noise data expected to come from potential future spaceborne missions, but disagree for low-resolution, low signal-to-noise spectra representative of current observations. We also compare the results from a parameterized temperature profile versus a full classical Level-by-Level approach and discriminate in which situations each of these approaches is applicable. Furthermore, we discuss the implications of our models for the inferred C-to-O ratios of exoplanetary atmospheres. Specifically, we show that in the observational limit of a few photometric points, the retrieved C/O is biased toward values near solar and near one simply due to the assumption of uninformative priors

Gerschenkron revisited: The new corporate Russia

© 2015, Journal of Economic Issues / Association for Evolutionary Economics. Our analysis is based on firm-specific data compiled from the Russian Trading System stock exchange and SKRIN (CKP-H in Russian) database. We seek to identify the factors behind Russias dramatically improved corporate sector performance from the beginning of the 2000s to December 2007. We argue that improved long-term corporate performance was a consequence of several policy initiatives associated with the state-dominated banking sector, which enabled statesubsidized investment funds to be channeled from a structurally reengineered energy sector to targeted investment projects located in other industries. We claim that Russias industrial strategy closely conforms to Alexander Gerschenkrons catch-up theory

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy