Spintronic properties of one-dimensional electron gas in graphene armchair ribbons

We have investigated, using effective mass approach (EMA), magnetic properties of a one-dimensional electron gas in graphene armchair ribbons when the electrons of occupy only the lowest conduction subband. We find that magnetic properties of the one-dimensional electron gas may depend sensitively on the width of the ribbon. For ribbon widths $L_x=3Ma_0$, a critical point separates ferromagnetic and paramagnetic states while for $L_x=(3M+1)a_0$ paramagnetic state is stable ($M$ is an integer and $a_{0}$ is the length of the unit cell). These width-dependent properties are a consequence of eigenstates that have a subtle width-dependent mixture of $\mathbf{K}$ and $\mathbf{K'}$ states, and can be understood by examining the wavefunction overlap that appears in the expression for the many-body exchange self-energy. Ferromagnetic and paramagnetic states may be used for spintronic purposes.Comment: 5 pages, 6 figure

Risk Management: A Practical Design Tool For Space Systems and Technology Development

Over the past two decades, risk management and risk analysis have emerged throughout the business community in the United States (US) as prominent planning and development strategies used to mitigate risk of failure and ensure a high return on investment (ROI) for business endeavors (financial and otherwise). They are generic tools that can be applied to any business regardless of the sector (i.e., government, university, private) and have been used by the Federal government in the form of institutional practices aimed at maximizing the probability of success in business activities. One US Federal agency that incorporates risk management and analysis techniques into business and/or engineering activities is the National Aeronautics and Space Administration (NASA). The present work is a discussion on mission, spacecraft and instrument design (as well as technology development) and the role of risk management, analysis and mitigation as a fundamental tool in the design process

Antibody responses to the merozoite surface protein-1 complex in cerebral malaria patients in India

<p>Abstract</p> <p>Background</p> <p><it>Plasmodium falciparum </it>infection causes cerebral malaria (CM) in a subset of patients with anti-malarial treatment protecting only about 70% to 80% of patients. Why a subset of malaria patients develops CM complications, including neurological sequelae or death, is still not well understood. It is believed that host immune factors may modulate CM outcomes and there is substantial evidence that cellular immune factors, such as cytokines, play an important role in this process. In this study, the potential relationship between the antibody responses to the merozoite surface protein (MSP)-1 complex (which consists of four fragments namely: MSP-1₈₃, MSP-1₃₀, MSP-1₃₈and MSP-1₄₂), MSP-6₃₆and MSP-7₂₂and CM was investigated.</p> <p>Methods</p> <p>Peripheral blood antibody responses to recombinant antigens of the two major allelic forms of MSP-1 complex, MSP-6₃₆and MSP-7₂₂were compared between healthy subjects, mild malaria patients (MM) and CM patients residing in a malaria endemic region of central India. Total IgG and IgG subclass antibody responses were determined using ELISA method.</p> <p>Results</p> <p>The prevalence and levels of IgG and its subclasses in the plasma varied for each antigen. In general, the prevalence of total IgG, IgG1 and IgG3 was higher in the MM patients and lower in CM patients compared to healthy controls. Significantly lower levels of total IgG antibodies to the MSP-1_f38, IgG1 levels to MSP-1_d83, MSP-1₁₉and MSP-6₃₆and IgG3 levels to MSP-1_f42and MSP-7₂₂were observed in CM patients as compared to MM patients.</p> <p>Conclusion</p> <p>These results suggest that there may be some dysregulation in the generation of antibody responses to some MSP antigens in CM patients and it is worth investigating further whether perturbations of antibody responses in CM patients contribute to pathogenesis.</p

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk outcome pairs, and new data on risk exposure levels and risk outcome associations. Methods: We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings: In 2017,34.1 million (95% uncertainty interval [UI] 33.3-35.0) deaths and 121 billion (144-1.28) DALYs were attributable to GBD risk factors. Globally, 61.0% (59.6-62.4) of deaths and 48.3% (46.3-50.2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10.4 million (9.39-11.5) deaths and 218 million (198-237) DALYs, followed by smoking (7.10 million [6.83-7.37] deaths and 182 million [173-193] DALYs), high fasting plasma glucose (6.53 million [5.23-8.23] deaths and 171 million [144-201] DALYs), high body-mass index (BMI; 4.72 million [2.99-6.70] deaths and 148 million [98.6-202] DALYs), and short gestation for birthweight (1.43 million [1.36-1.51] deaths and 139 million [131-147] DALYs). In total, risk-attributable DALYs declined by 4.9% (3.3-6.5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23.5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18.6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Mapping the Birch and Grass Pollen Seasons in the UK Using Satellite Sensor Time-series

Grass and birch pollen are two major causes of seasonal allergic rhinitis (hay fever) in the UK and parts of Europe affecting around 15-20% of the population. Current prediction of these allergens in the UK is based on (i) measurements of pollen concentrations at a limited number of monitoring stations across the country and (ii) general information about the phenological status of the vegetation. Thus, the current prediction methodology provides information at a coarse spatial resolution only. Most station-based approaches take into account only local observations of flowering, while only a small number of approaches take into account remote observations of land surface phenology. The systematic gathering of detailed information about vegetation status nationwide would therefore be of great potential utility. In particular, there exists an opportunity to use remote sensing to estimate phenological variables that are related to the flowering phenophase and, thus, pollen release. In turn, these estimates can be used to predict pollen release at a fine spatial resolution. In this study, time-series of MERIS Terrestrial Chlorophyll Index (MTCI) data were used to predict two key phenological variables: the start of season and peak of season. A technique was then developed to estimate the flowering phenophase of birch and grass from the MTCI time-series. For birch, the timing of flowering was defined as the time after the start of the growing season when the MTCI value reached 25% of the maximum. Similarly, for grass this was defined as the time when the MTCI value reached 75% of the maximum. The predicted pollen release dates were validated with data from nine pollen monitoring stations in the UK. For both birch and grass, we obtained large positive correlations between the MTCI-derived start of pollen season and the start of the pollen season defined using station data, with a slightly larger correlation observed for birch than for grass. The technique was applied to produce detailed maps for the flowering of birch and grass across the UK for each of the years from 2003 to 2010. The results demonstrate that the remote sensing-based maps of onset flowering of birch and grass for the UK together with the pollen forecast from the Meteorology Office and National Pollen and Aerobiology Research Unit (NPARU) can potentially provide more accurate information to pollen allergy sufferers in the UK