999 resultados para Radiation Sensitivity


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BACKGROUND: Bruchid beetles, Callosobruchus species, are serious pests of economically important grain legumes; their activity in stores is often controlled by use of synthetic insecticides. Esterases are known to be involved in insecticide resistance in insects. However, there is dearth of information on esterase activity in the genus Callosobruchus. In this study we investigated the effect of species, geographical strain and food type on the variation of acetylcholinesterase (AChE) activity and its inhibition by malaoxon (malathion metabolite) using an in vitro spectrophotometric method. RESULT: AChE activity varied significantly among species and strains and also among legume type used for rearing them. Generally irrespective of species, strain or food type, the higher the AChE activity of a population, the higher its inhibition by malaoxon. C. chinensis had the highest AChE activity of the species studied and in the presence of malaoxon it had the lowest remaining AChE activity, while C. rhodesianus retained the highest activity. CONCLUSION: A firsthand knowledge of AChE activity in regional Callosobruchus in line with the prevailing food types should be of utmost importance to grain legume breeders, researchers on plant materials for bruchid control and pesticide manufacturer/applicators for a robust integrated management of these bruchids.

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[1] Remotely sensed, multiannual data sets of shortwave radiative surface fluxes are now available for assimilation into land surface schemes (LSSs) of climate and/or numerical weather prediction models. The RAMI4PILPS suite of virtual experiments assesses the accuracy and consistency of the radiative transfer formulations that provide the magnitudes of absorbed, reflected, and transmitted shortwave radiative fluxes in LSSs. RAMI4PILPS evaluates models under perfectly controlled experimental conditions in order to eliminate uncertainties arising from an incomplete or erroneous knowledge of the structural, spectral and illumination related canopy characteristics typical for model comparison with in situ observations. More specifically, the shortwave radiation is separated into a visible and near-infrared spectral region, and the quality of the simulated radiative fluxes is evaluated by direct comparison with a 3-D Monte Carlo reference model identified during the third phase of the Radiation transfer Model Intercomparison (RAMI) exercise. The RAMI4PILPS setup thus allows to focus in particular on the numerical accuracy of shortwave radiative transfer formulations and to pinpoint to areas where future model improvements should concentrate. The impact of increasing degrees of structural and spectral subgrid variability on the simulated fluxes is documented and the relevance of any thus emerging biases with respect to gross primary production estimates and shortwave radiative forcings due to snow and fire events are investigated.

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Various studies investigating the future impacts of integrating high levels of renewable energy make use of historical meteorological (met) station data to produce estimates of future generation. Hourly means of 10m horizontal wind are extrapolated to a standard turbine hub height using the wind profile power or log law and used to simulate the hypothetical power output of a turbine at that location; repeating this procedure using many viable locations can produce a picture of future electricity generation. However, the estimate of hub height wind speed is dependent on the choice of the wind shear exponent a or the roughness length z0, and requires a number of simplifying assumptions. This paper investigates the sensitivity of this estimation on generation output using a case study of a met station in West Freugh, Scotland. The results show that the choice of wind shear exponent is a particularly sensitive parameter which can lead to significant variation of estimated hub height wind speed and hence estimated future generation potential of a region.

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The results of an integrated geoarchaeological and palaeoecological pilot study of a prehistoric agricultural terrace and nearby mire basin are presented. They reveal two stages of terrace construction for the cultivation of Zea mays during the Middle Horizon (615–695 AD) and late, Late Intermediate Period (1200–1400 AD). These stages were strongly associated with evidence for vegetation succession, destabilisation and erosion of the surrounding landscape, and changes in mire surface wetness. The reasons for agricultural terrace abandonment and/or reconstruction are uncertain, with only circumstantial evidence for climatically induced agricultural change.

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Background: Autism spectrum conditions have a strong genetic component. Atypical sensory sensitivities are one of the core but neglected features of autism spectrum conditions. GABRB3 is a well-characterised candidate gene for autism spectrum conditions. In mice, heterozygous Gabrb3 deletion is associated with increased tactile sensitivity. However, no study has examined if tactile sensitivity is associated with GABRB3 genetic variation in humans. To test this, we conducted two pilot genetic association studies in the general population, analysing two phenotypic measures of tactile sensitivity (a parent-report and a behavioural measure) for association with 43 SNPs in GABRB3. Findings: Across both tactile sensitivity measures, three SNPs (rs11636966, rs8023959 and rs2162241) were nominally associated with both phenotypes, providing a measure of internal validation. Parent-report scores were nominally associated with six SNPs (P <0.05). Behaviourally measured tactile sensitivity was nominally associated with 10 SNPs (three after Bonferroni correction). Conclusions: This is the first human study to show an association between GABRB3 variation and tactile sensitivity. This provides support for the evidence from animal models implicating the role of GABRB3 variation in the atypical sensory sensitivity in autism spectrum conditions. Future research is underway to directly test this association in cases of autism spectrum conditions.

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Solar-pointing Fourier transform infrared (FTIR) spectroscopy offers the capability to measure both the fine scale and broadband spectral structure of atmospheric transmission simultaneously across wide spectral regions. It is therefore suited to the study of both water vapour monomer and continuum absorption behaviours. However, in order to properly address this issue, it is necessary to radiatively calibrate the FTIR instrument response. A solar-pointing high-resolution FTIR spectrometer was deployed as part of the ‘Continuum Absorption by Visible and Infrared radiation and its Atmospheric Relevance’ (CAVIAR) consortium project. This paper describes the radiative calibration process using an ultra-high-temperature blackbody and the consideration of the related influence factors. The result is a radiatively calibrated measurement of the solar irradiation at the ground across the IR region from 2000 to 10 000 cm−1 with an uncertainty of between 3.3 and 5.9 per cent. This measurement is shown to be in good general agreement with a radiative-transfer model. The results from the CAVIAR field measurements are being used in ongoing studies of atmospheric absorbers, in particular the water vapour continuum.

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A frequently used diagram summarizing the annual- and global-mean energy budget of the earth and atmosphere indicates that the irradiance reaching the top of the atmosphere from the surface, through the midinfrared atmospheric window, is 40 W m−2; this can be compared to the total outgoing longwave radiation (OLR) of about 235 W m−2. The value of 40 W m−2 was estimated in an ad hoc manner. A more detailed calculation of this component, termed here the surface transmitted irradiance (STI), is presented, using a line-by-line radiation code and 3D climatologies of temperature, humidity, cloudiness, etc. No assumption is made as to the wavelengths at which radiation from the surface can reach the top of the atmosphere. The role of the water vapor continuum is highlighted. In clear skies, if the continuum is excluded, the global- and annual-mean STI is calculated to be about 100 W m−2 with a broad maximum throughout the tropics and subtropics. When the continuum is included, the clear-sky STI is reduced to 66 W m−2, with a distinctly different geographic distribution, with a minimum in the tropics and local peaks over subtropical deserts. The inclusion of clouds reduces the STI to about 22 W m−2. The actual value is likely somewhat smaller due to processes neglected here, and an STI value of 20 W m−2 (with an estimated uncertainty of about ±20%) is suggested to be much more realistic than the previous estimate of 40 W m−2. This indicates that less than one-tenth of the OLR originates directly from the surface.

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Data assimilation refers to the problem of finding trajectories of a prescribed dynamical model in such a way that the output of the model (usually some function of the model states) follows a given time series of observations. Typically though, these two requirements cannot both be met at the same time–tracking the observations is not possible without the trajectory deviating from the proposed model equations, while adherence to the model requires deviations from the observations. Thus, data assimilation faces a trade-off. In this contribution, the sensitivity of the data assimilation with respect to perturbations in the observations is identified as the parameter which controls the trade-off. A relation between the sensitivity and the out-of-sample error is established, which allows the latter to be calculated under operational conditions. A minimum out-of-sample error is proposed as a criterion to set an appropriate sensitivity and to settle the discussed trade-off. Two approaches to data assimilation are considered, namely variational data assimilation and Newtonian nudging, also known as synchronization. Numerical examples demonstrate the feasibility of the approach.

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Near-isogenic lines (NILs) of winter wheat varying for alleles for reduced height (Rht), gibberellin (GA) response and photoperiod insensitivity (Ppd-D1a) in cv. Mercia background (rht (tall), Rht-B1b, Rht-D1b, Rht-B1c, Rht8c+Ppd-D1a, Rht-D1c, Rht12) and cv. Maris Widgeon (rht (tall), Rht-D1b, Rht-B1c) backgrounds were compared to investigate main effects and interactions with tillage (plough-based, minimum-, and zero-tillage) over two years. Both minimum- and zero- tillage were associated with reduced grain yields allied to reduced harvest index, biomass accumulation, interception of photosynthetically active radiation (PAR), and plant populations. Grain yields were optimized at mature crop heights of around 740mm because this provided the best compromise between harvest index which declined with height, and above ground biomass which increased with height. Improving biomass with height was due to improvements in both PAR interception and radiation-use efficiency. Optimum height for grain yield was unaffected by tillage system or GA-sensitivity. After accounting for effects of height, GA insensitivity was associated with increased grain yields due to increased grains per spike, which was more than enough to compensate for poorer plant establishment and lower mean grain weights compared to the GA-sensitive lines. Although better establishment was possible with GA-sensitive lines, there was no evidence that this effect interacted with tillage method. We find, therefore, little evidence to question the current adoption of wheats with reduced sensitivity to GA in the UK, even as tillage intensity lessens.

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The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Net- work (AERONET) routinely monitor clouds using zenith ra- diances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a liquid-water-absorbing wavelength (i.e., 1640 nm) with a non-water-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g m−2 and horizontal resolution of 201 m, the retrieval method underestimates the mean effective radius by 0.8μm, with a root-mean-squared error of 1.7 μm and a relative deviation of 13%. For actual observations with a liquid water path less than 450 g m−2 at the ARM Oklahoma site during 2007– 2008, our 1.5-min-averaged retrievals are generally larger by around 1 μm than those from combined ground-based cloud radar and microwave radiometer at a 5-min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 μm and the relative deviation of 22 % are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11 % with satellite observations and have a negative bias of 1 μm. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.

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We diagnose forcing and climate feedbacks in benchmark sensitivity experiments with the new Met Office Hadley Centre Earth system climate model HadGEM2-ES. To identify the impact of newly-included biogeophysical and chemical processes, results are compared to a parallel set of experiments performed with these processes switched off, and different couplings with the biogeochemistry. In abrupt carbon dioxide quadrupling experiments we find that the inclusion of these processes does not alter the global climate sensitivity of the model. However, when the change in carbon dioxide is uncoupled from the vegetation, or when the model is forced with a non-carbon dioxide forcing – an increase in solar constant – new feedbacks emerge that make the climate system less sensitive to external perturbations. We identify a strong negative dust-vegetation feedback on climate change that is small in standard carbon dioxide sensitivity experiments due to the physiological/fertilization effects of carbon dioxide on plants in this model.

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Interest in the impacts of climate change is ever increasing. This is particularly true of the water sector where understanding potential changes in the occurrence of both floods and droughts is important for strategic planning. Climate variability has been shown to have a significant impact on UK climate and accounting for this in future climate cahgne projections is essential to fully anticipate potential future impacts. In this paper a new resampling methodology is developed which includes the variability of both baseline and future precipitation. The resampling methodology is applied to 13 CMIP3 climate models for the 2080s, resulting in an ensemble of monthly precipitation change factors. The change factors are applied to the Eden catchment in eastern Scotland with analysis undertaken for the sensitivity of future river flows to the changes in precipitation. Climate variability is shown to influence the magnitude and direction of change of both precipitation and in turn river flow, which are not apparent without the use of the resampling methodology. The transformation of precipitation changes to river flow changes display a degree of non-linearity due to the catchment's role in buffering the response. The resampling methodology developed in this paper provides a new technique for creating climate change scenarios which incorporate the important issue of climate variability.

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The evaluation of the quality and usefulness of climate modeling systems is dependent upon an assessment of both the limited predictability of the climate system and the uncertainties stemming from model formulation. In this study a methodology is presented that is suited to assess the performance of a regional climate model (RCM), based on its ability to represent the natural interannual variability on monthly and seasonal timescales. The methodology involves carrying out multiyear ensemble simulations (to assess the predictability bounds within which the model can be evaluated against observations) and multiyear sensitivity experiments using different model formulations (to assess the model uncertainty). As an example application, experiments driven by assimilated lateral boundary conditions and sea surface temperatures from the ECMWF Reanalysis Project (ERA-15, 1979–1993) were conducted. While the ensemble experiment demonstrates that the predictability of the regional climate varies strongly between different seasons and regions, being weakest during the summer and over continental regions, important sensitivities of the modeling system to parameterization choices are uncovered. In particular, compensating mechanisms related to the long-term representation of the water cycle are revealed, in which summer dry and hot conditions at the surface, resulting from insufficient evaporation, can persist despite insufficient net solar radiation (a result of unrealistic cloud-radiative feedbacks).

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Genetic background may interact with habitual dietary fat composition, and affect development of the metabolic syndrome (MetS). The phosphoenolpyruvate carboxykinase gene (PCK1) plays a significant role regulating glucose metabolism, and fatty acids are key metabolic regulators, which interact with transcription factors and influence glucose metabolism. We explored genetic variability at the PCK1 gene locus in relation to degree of insulin resistance and plasma fatty acid levels in MetS subjects. Moreover, we analyzed the PCK1 gene expression in the adipose tissue of a subgroup of MetS subjects according to the PCK1 genetic variants.