942 resultados para The Indian Scenario
Resumo:
OBJECTIVE: To compare insulin sensitivity (Si) from a frequently sampled intravenous glucose tolerance test (FSIGT) and subsequent minimal model analyses with surrogate measures of insulin sensitivity and resistance and to compare features of the metabolic syndrome between Caucasians and Indian Asians living in the UK. SUBJECTS: In all, 27 healthy male volunteers (14 UK Caucasians and 13 UK Indian Asians), with a mean age of 51.2 +/- 1.5 y, BMI of 25.8 +/- 0.6 kg/m(2) and Si of 2.85 +/- 0.37. MEASUREMENTS: Si was determined from an FSIGT with subsequent minimal model analysis. The concentrations of insulin, glucose and nonesterified fatty acids (NEFA) were analysed in fasting plasma and used to calculate surrogate measure of insulin sensitivity (quantitative insulin sensitivity check index (QUICKI), revised QUICKI) and resistance (homeostasis for insulin resistance (HOMA IR), fasting insulin resistance index (FIRI), Bennetts index, fasting insulin, insulin-to-glucose ratio). Plasma concentrations of triacylglycerol (TAG), total cholesterol, high density cholesterol, (HDL-C) and low density cholesterol, (LDL-C) were also measured in the fasted state. Anthropometric measurements were conducted to determine body-fat distribution. RESULTS: Correlation analysis identified the strongest relationship between Si and the revised QUICKI (r = 0.67; P = 0.000). Significant associations were also observed between Si and QUICKI (r = 0.51; P = 0.007), HOMA IR (r = -0.50; P = 0.009), FIRI and fasting insulin. The Indian Asian group had lower HDL-C (P = 0.001), a higher waist-hip ratio (P = 0.01) and were significantly less insulin sensitive (Si) than the Caucasian group (P = 0.02). CONCLUSION: The revised QUICKI demonstrated a statistically strong relationship with the minimal model. However, it was unable to differentiate between insulin-sensitive and -resistant groups in this study. Future larger studies in population groups with varying degrees of insulin sensitivity are recommended to investigate the general applicability of the revised QUICKI surrogate technique.
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The possibilities and need for adaptation and mitigation depends on uncertain future developments with respect to socio-economic factors and the climate system. Scenarios are used to explore the impacts of different strategies under uncertainty. In this chapter, some scenarios are presented that are used in the ADAM project for this purpose. One scenario explores developments with no mitigation, and thus with high temperature increase and high reliance on adaptation (leading to 4oC increase by 2100 compared to pre-industrial levels). A second scenario explores an ambitious mitigation strategy (leading to 2oC increase by 2100 compared to pre-industrial levels). In the latter scenario, stringent mitigation strategies effectively reduces the risks of climate change, but based on uncertainties in the climate system a temperature increase of 3oC or more cannot be excluded. The analysis shows that, in many cases, adaptation and mitigation are not trade-offs but supplements. For example, the number of people exposed to increased water resource stress due to climate change can be substantially reduced in the mitigation scenario, but even then adaptation will be required for the remaining large numbers of people exposed to increased stress. Another example is sea level rise, for which adaptation is more cost-effective than mitigation, but mitigation can help reduce damages and the cost of adaptation. For agriculture, finally, only the scenario based on a combination of adaptation and mitigation is able to avoid serious climate change impacts.
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The relationship between tropical convection, surface fluxes, and sea surface temperature (SST) on intraseasonal timescales has been examined as part of an investigation of the possibility that the intraseasonal oscillation is a coupled atmosphere–ocean phenomenon. The unique feature of this study is that 15 yr of data and the whole region from the Indian Ocean to the Pacific Ocean have been analyzed using lag-correlation analysis and compositing techniques. A coherent relationship between convection, surface fluxes, and SST has been found on intraseasonal timescales in the Indian Ocean, Maritime Continent, and west Pacific regions of the Tropics. Prior to the maximum in convection, there are positive shortwave and latent heat flux anomalies into the surface, followed by warm SST anomalies about 10 days before the convective maximum. Coincident with the convective maximum, there is a minimum in the shortwave flux, followed by a cooling due to increased evaporation associated with enhanced westerly wind stress, leading to negative SST anomalies about 10 days after the convection. The relationships are robust from year to year, including both phases of the El Niño–Southern Oscillation (ENSO) although the eastward extent of the region over which the relationship holds varies with the phase of ENSO, consistent with the variations in the eastward extent of the warm pool and westerly winds. The spatial scale of the anomalies is about 60° longitude, consistent with the scale of the intraseasonal oscillation. The spatial and temporal characteristics of the surface flux and SST perturbations are consistent with the surface flux variations forcing the ocean, and the magnitudes of the anomalies are consistent with mixed-layer depths appropriate to the Indian Ocean and west Pacific
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Subantarctic mode water (SAMW) has been shown to be a good indicator of anthropogenic climate change in coupled climate models. SAMW in a coupled climate model and the response of modeled SAMW to increasing CO2 are examined in detail. How SAMW adjusts from climatological values toward a new equilibrium in the coupled model, with different climatological temperature and salinity properties, is shown. The combined formation rate of SAMW and Antarctic intermediate water is calculated as approximately 18 Sv (Sv ≡ 106 m3 s−1) in the Indian sector of the Southern Ocean, slightly lower than climatological values would suggest. When forced with increasing CO2, SAMW is produced at a similar rate but at lower densities. This result suggests that the rate of heat uptake in this part of the ocean will be unchanged by anthropogenic forcing. The important signal in the response of SAMW is the shift to colder and fresher values on isopycnals that is believed to be related to changes in thermodynamic surface forcing. It is shown that, given uniform forcing, SAMW is expected to enhance the signal relative to other water masses. Independent increases in surface heating or freshwater forcing can produce changes similar to those observed, but the two different types of forcing are distinguishable using separate forcing experiments, hodographs, and passive anomaly tracers. The changes in SAMW forced by increasing CO2 are dominated by surface heating, but changes to freshwater fluxes are also important.
Cannabis sativa and the endogenous cannabinoid system: therapeutic potential for appetite regulation
Resumo:
The herb Cannabis sativa (C. sativa) has been used in China and on the Indian subcontinent for thousands of years as a medicine. However, since it was brought to the UK and then the rest of the western world in the late 19th century, its use has been a source of controversy. Indeed, its psychotropic side effects are well reported but only relatively recently has scientific endeavour begun to find valuable uses for either the whole plant or its individual components. Here, we discuss evidence describing the endocannabinoid system, its endogenous and exogenous ligands and their varied effects on feeding cycles and meal patterns. Furthermore we also critically consider the mounting evidence which suggests non‐tetrahydrocannabinol phytocannabinoids play a vital role in C. sativa‐induced feeding pattern changes. Indeed, given the wide range of phytocannabinoids present in C. sativa and their equally wide range of intra‐, inter‐ and extra‐cellular mechanisms of action, we demonstrate that non‐Δ9tetrahydrocannabinol phytocannabinoids retain an important and, as yet, untapped clinical potential.
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This paper assesses the implications of climate policy for exposure to water resources stresses. It compares a Reference scenario which leads to an increase in global mean temperature of 4oC by the end of the 21st century with a Mitigation scenario which stabilises greenhouse gas concentrations at around 450ppm CO2e and leads to a 2oC increase in 2100. Associated changes in river runoff are simulated using a global hydrological model, for four spatial patterns of change in temperature and rainfall. There is a considerable difference in hydrological change between these four patterns, but the percentages of change avoided at the global scale are relatively robust. By the 2050s, the Mitigation scenario typically avoids between 16 and 30% of the change in runoff under the Reference scenario, and by 2100 it avoids between 43 and 65%. Two different measures of exposure to water resources stress are calculated, based on resources per capita and the ratio of withdrawals to resources. Using the first measure, the Mitigation scenario avoids 8-17% of the impact in 2050 and 20-31% in 2100; with the second measure, the avoided impacts are 5-21% and 15-47% respectively. However, at the same time, the Mitigation scenario also reduces the positive impacts of climate change on water scarcity in other areas. The absolute numbers and locations of people affected by climate change and climate policy vary considerably between the four climate model patterns.
Resumo:
Scenarios are used to explore the consequences of different adaptation and mitigation strategies under uncertainty. In this paper, two scenarios are used to explore developments with (1) no mitigation leading to an increase of global mean temperature of 4 °C by 2100 and (2) an ambitious mitigation strategy leading to 2 °C increase by 2100. For the second scenario, uncertainties in the climate system imply that a global mean temperature increase of 3 °C or more cannot be ruled out. Our analysis shows that, in many cases, adaptation and mitigation are not trade-offs but supplements. For example, the number of people exposed to increased water resource stress due to climate change can be substantially reduced in the mitigation scenario, but adaptation will still be required for the remaining large numbers of people exposed to increased stress. Another example is sea level rise, for which, from a global and purely monetary perspective, adaptation (up to 2100) seems more effective than mitigation. From the perspective of poorer and small island countries, however, stringent mitigation is necessary to keep risks at manageable levels. For agriculture, only a scenario based on a combination of adaptation and mitigation is able to avoid serious climate change impacts.
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Laboratory experiments to determine the preferred orientation of free-falling hexagonal prisms were performed at Reynolds numbers appropriate to falling ice crystals in the atmosphere. Hexagonal plates orient with their c axis vertical for aspect ratios < 0.9, whilst hexagonal columns fall with their c axis horizontal. A secondary alignment is also observed: regular hexagonal columns fall preferentially with two prism facets aligned vertically and not horizontally – the latter scenario was previously assumed to be responsible for the rare Parry arc. However, if the column is made scalene in its cross-section, it can orient such that a pair of prism facets is horizontal. This finding indicates that the development of scalene crystals may be key to the production of certain ice-crystal optical phenomena
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In this paper, we propose a scenario framework that could provide a scenario “thread” through the different climate research communities (climate change – vulnerability, impact, and adaptation (VIA) and mitigation) in order to provide assessment of mitigation and adaptation strategies and other VIA challenges. The scenario framework is organised around a matrix with two main axes: radiative forcing levels and socio-economic conditions. The radiative forcing levels (and the associated climate signal) are described by the new Representative Concentration Pathways. The second axis, socio-economic developments, comprises elements that affect the capacity for mitigation and adaptation, as well as the exposure to climate impacts. The proposed scenarios derived from this framework are limited in number, allow for comparison across various mitigation and adaptation levels, address a range of vulnerability characteristics, provide information across climate forcing and vulnerability states and span a full century time scale. Assessments based on the proposed scenario framework would strengthen cooperation between integrated-assessment modelers, climate modelers and vulnerability, impact and adaptation researchers, and most importantly, facilitate the development of more consistent and comparable research within and across communities.
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This study investigates the impacts of the transition of El Niño decaying phases on the western North Pacific anticyclone (WNPAC) anomalies in the subsequent summer with a coupled GCM. The modeling results suggest that the El Niños with short decaying phases lead to significant WNPAC anomalies in the following summer, which are contributed to mainly by the El Niños followed by La Niñas, in comparison with those not followed by La Niñas. In contrast, the long decaying cases are associated with the disappearance of WNPAC anomalies in the summer. These differences in the WNP circulation anomalies can be explained by the different configurations of simultaneous SSTs in the Indian Ocean and in the central and eastern tropical Pacific: positive SSTs in the former region and negative ones in the latter region constructively induce significant WNPAC anomalies for the short decaying cases, while the roles of positive SSTs in both regions for the long decaying cases work destructively and lead to weak WNP circulation anomalies. Further analysis indicates that the different lengths of El Niño decaying phases are predicted by the strength of Indian Ocean SSTs in the mature winter. The warmer wintertime Indian Ocean SSTs favor the anomalous easterly wind over the western and central equatorial Pacific in the subsequent summer, leading to a short decaying of El Niño. Thus, the strength of wintertime Indian Ocean SSTs is one of the important factors that affect the length of El Niño decaying phase and resultant WNPAC anomalies in the following summer.
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The Kalpana Very High Resolution Radiometer (VHRR) water vapour (WV) channel is very similar to the WV channel of the Meteosat Visible and Infrared Radiation Imager (MVIRI) on Meteosat-7, and both satellites observe the Indian subcontinent. Thus it is possible to compare the performance of VHRR and MVIRI in numerical weather prediction (NWP) models. In order to do so, the impact of Kalpana- and Meteosat-7-measured WV radiances was evaluated using analyses and forecasts of moisture, temperature, geopotential and winds, using the European Centre for Medium-range Weather Forecasts (ECMWF) NWP model. Compared with experiments using Meteosat-7, the experiments using Kalpana WV radiances show a similar fit to all observations and produce very similar forecasts.
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This paper investigates the regional characteristics of Indian manufacturing industry. Its aim is to assess whether geography plays any major role in determining the performance or characteristics of Indian manufacturing firms, and in order to do this, it presents the results of cross-section regressions estimated on the basis of a balanced sample of 1607 firms across the 30 Indian states. The results suggest that firm performance and characteristics are related to many of the expected industrial organization variables. However, there is also evidence of significant region–state influences on both the performance and characteristics of Indian manufacturing industry. As such, the results demonstrate that analyses which focus solely on standard non-spatial industrial organization variables will fail to explain much of the cross-sectional variation in firm performance and characteristics. In particular, while there are no systematic simple centre–periphery variations in the Indian regional economic system, there is evidence to suggest that industrial spatial concentration, regional specialization, and regional market size play a key role in determining the performance and characteristics of Indian manufacturing industry.
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AOGCMs of the two latest phases (CMIP3 and CMIP5) of the Coupled Model Intercomparison Project, like earlier AOGCMs, predict large regional variations in future sea level change. The model-mean pattern of change in CMIP3 and CMIP5 is very similar, and its most prominent feature is a zonal dipole in the Southern Ocean: sea level rise is larger than the global mean north of 50°S and smaller than the global mean south of 50°S in most models. The individual models show widely varying patterns, although the inter-model spread in local sea level change is smaller in CMIP5 than in CMIP3. Here we investigate whether changes in windstress can explain the different patterns of projected sea level change, especially the Southern Ocean feature, using two AOGCMs forced by the changes in windstress from the CMIP3 and CMIP5 AOGCMs. We show that the strengthening and poleward shift of westerly windstress accounts for the most of the large spread among models in magnitude of this feature. In the Indian, North Pacific and Arctic Oceans, the windstress change is influential, but does not completely account for the projected sea level change.
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In this article, we make two important contributions to the literature on clusters. First, we provide a broader theory of cluster connectivity that has hitherto focused on organization-based pipelines and MNE subsidiaries, by including linkages in the form of personal relationships. Second, we use the lens of social network theory to derive a number of testable propositions. We propose that global linkages with decentralized network structures have the highest potential for local spillovers. In the emerging economy context, our theory implies that clusters linked to the global economy by decentralized pipelines have potential for in-depth catch-up, focused in industry and technology scope. In contrast, clusters linked through decentralized personal relationships have potential for in-breadth catch-up over a range of related industries and technologies. We illustrate our theoretical propositions by contrasting two emerging economy case studies: Bollywood, the Indian filmed entertainment cluster in Mumbai and the Indian software cluster in Bangalore.
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We present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statistical-dynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971–2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6–35 % for 2011–2040, of 20–30 % for 2041–2070, and of 40–55 % for 2071–2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses.