54 resultados para radiation variability
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Organochlorine compounds (OC) are known to induce vitamin A (retinoids) deficiency in mammals, which may be associated with impairment of immunocompetence, reproduction and growth. This makes retinoids a potentially useful biomarker of organochlorine impact on marine mammals. However, use of retinoids as a biomarker requires knowledge about its intrapopulation patterns of variation in natural conditions, information which is not currently available. We investigated these patterns in a cetacean population living in an unpolluted environment. 100 harbour porpoises Phocoena phocoena from West Greenland were sampled during the 1995 hunting season. Sex, age, morphometrics, nutritive condition, and retinol (following saponification) and OC levels in blubber were determined for each individual. OC levels found were extremely low and therefore considered unlikely to affect the population adversely: mean blubber concentrations, expressed on an extractable basis, were 2.04 (SD = 1.1) ppm for PCBs and 2.76 (SD = 1.66) ppm for tDDT. The mean blubber retinol concentration for the overall population was 59.66 (SD = 45.26) mu g g(-1). Taking into account the high contribution of blubber to body mass, blubber constitutes a significant body site for retinoid deposition in harbour porpoises. Retinol concentrations did not differ significantly between geographical regions or sexes, but they did correlate significantly (p <0.001) with age. Body condition, measured by determining the lipid content of the blubber, did not have a significant effect on retinol levels but the individuals examined were considered to be in an overall good nutritive condition. It is concluded that measurement of retinol concentrations in blubber samples is feasible and has a potential for use as a biomarker of organochlorine exposure in cetaceans. However, in order to do so, biological information, particularly age, is critical for the correct assessment of physiological impact
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Postprint (published version)
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Although the efficacy of methadone maintenance treatment (MMT) in opioid dependence disorder has been well established, the influence of methadone pharmacokinetics in dose requirement and clinical outcome remains controversial. The aim of this study is to analyze methadone dosage in responder and nonresponder patients considering pharmacogenetic and pharmacokinetic factors that may contribute to dosage adequacy. Opioid dependence patients (meeting Diagnostic and Statistical Manual of Mental Disorders, [4th Edition] criteria) from a MMT community program were recruited. Patients were clinically assessed and blood samples were obtained to determine plasma concentrations of (R,S)-, (R) and (S)- methadone and to study allelic variants of genes encoding CYP3A5, CYP2D6, CYP2B6, CYP2C9, CYP2C19, and P-glycoprotein. Responders and nonresponders were defined by illicit opioid consumption detected in random urinalysis. The final sample consisted in 105 opioid dependent patients of Caucasian origin. Responder patients received higher doses of methadone and have been included into treatment for a longer period. No differences were found in terms of genotype frequencies between groups. Only CYP2D6 metabolizing phenotype differences were found in outcome status, methadone dose requirements, and plasma concentrations, being higher in the ultrarapid metabolizers. No other differences were found between phenotype and responder status, methadone dose requirements, neither in methadone plasma concentrations. Pharmacokinetic factors could explain some but not all differences in MMT outcome and methadone dose requirements.
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The first objective of this study is to furnish new evidence concerning the aggregate profitability of the accumulation of human capital. In addition to the traditional measure of the return to human capital, combining the information on its shadow price with the social cost of providing education allows us to confirm the profitability of human capital investments as a tool for promoting economic growth. The possibility of obtaining estimations of these effects for each Spanish region enables us to empirically evaluate the amount of heterogeneity across economies in the effects of human capital. As a second objective, we provide evidence on the indirect effect of human capital in making private capital investment more attractive. Among the main explanations for this process, we observe that higher worker skill levels enable higher returns to be extracted from investment in physical capital.
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Observational and theoretical studies point to microquasars (MQs) as possible counterparts of a significant fraction of the unidentified gamma-ray sources detected so far. At present, a proper scenario to explain the emission beyond soft X-rays from these objects is not known, nor what the precise connection is between the radio and the high-energy radiation. We develop a new model where the MQ jet is dynamically dominated by cold protons and radiatively dominated by relativistic leptons. The matter content and power of the jet are both related with the accretion process. The magnetic field is assumed to be close to equipartition, although it is attached to and dominated by the jet matter. For the relativistic particles in the jet, their maximum energy depends on both the acceleration efficiency and the energy losses. The model takes into account the interaction of the relativistic jet particles with the magnetic field and all the photon and matter fields. Such interaction produces significant amounts of radiation from radio to very high energies through synchrotron, relativistic Bremsstrahlung, and inverse Compton (IC) processes. Variability of the emission produced by changes in the accretion process (e.g. via orbital eccentricity) is also expected. The effects of the gamma-ray absorption by the external photon fields on the gamma-ray spectrum have been taken into account, revealing clear spectral features that might be observed. This model is consistent to the accretion scenario, energy conservation laws, and current observational knowledge, and can provide deeper physical information of the source when tested against multiwavelength data.
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As a result of the growing interest in studying employee well-being as a complex process that portrays high levels of within-individual variability and evolves over time, this present study considers the experience of flow in the workplace from a nonlinear dynamical systems approach. Our goal is to offer new ways to move the study of employee well-being beyond linear approaches. With nonlinear dynamical systems theory as the backdrop, we conducted a longitudinal study using the experience sampling method and qualitative semi-structured interviews for data collection; 6981 registers of data were collected from a sample of 60 employees. The obtained time series were analyzed using various techniques derived from the nonlinear dynamical systems theory (i.e., recurrence analysis and surrogate data) and multiple correspondence analyses. The results revealed the following: 1) flow in the workplace presents a high degree of within-individual variability; this variability is characterized as chaotic for most of the cases (75%); 2) high levels of flow are associated with chaos; and 3) different dimensions of the flow experience (e.g., merging of action and awareness) as well as individual (e.g., age) and job characteristics (e.g., job tenure) are associated with the emergence of different dynamic patterns (chaotic, linear and random).
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The paper presents the variability of major floods in Switzerland for the period 1800-2008 from a summer index (INU). The index is constructed from the damage caused by flooding, with the aim of establishing the possible influence of the solar and climate variability on the major floods. The coincidence of flood-rich periods with those observed in other regions of different climate and fluvial regimes suggests that climate forcings and changes in the general circulation of the atmosphere are those who govern the appearance of these high-frequency temporal clusters.
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Identification of clouds from satellite images is now a routine task. Observation of clouds from the ground, however, is still needed to acquire a complete description of cloud conditions. Among the standard meteorologicalvariables, solar radiation is the most affected by cloud cover. In this note, a method for using global and diffuse solar radiation data to classify sky conditions into several classes is suggested. A classical maximum-likelihood method is applied for clustering data. The method is applied to a series of four years of solar radiation data and human cloud observations at a site in Catalonia, Spain. With these data, the accuracy of the solar radiation method as compared with human observations is 45% when nine classes of sky conditions are to be distinguished, and it grows significantly to almost 60% when samples are classified in only five different classes. Most errors are explained by limitations in the database; therefore, further work is under way with a more suitable database
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We model the wavelength-dependent absorption of atmospheric gases by assuming constant mass absorption coefficients in finite-width spectral bands. Such a semigray atmosphere is analytically solved by a discrete ordinate method. The general solution is analyzed for a water vapor saturated atmosphere that also contains a carbon dioxide-like absorbing gas in the infrared. A multiple stable equilibrium with a relative upper limit in the outgoing long-wave radiation is found. Differing from previous radiative–convective models, we find that the amount of carbon dioxide strongly modifies the value of this relative upper limit. This result is also obtained in a gray (i.e., equal absorption of radiation at all infrared wavelengths) water vapor saturated atmosphere. The destabilizing effect of carbon dioxide implies that massive carbon dioxide atmospheres are more likely to reach a runaway greenhouse state than thin carbon dioxide ones