929 resultados para Rainfall, Mosquito Density, Polynomial Distributed Lag Model, Ross River Virus
Resumo:
Our previous studies have shown that two distinct genotypes of Sindbis (SIN) virus occur in Australia. One of these, the Oriental/Australian type, circulates throughout most of the Australian continent, whereas the recently identified south-west (SW) genetic type appears to be restricted to a distinct geographic region located in the temperate south-west of Australia. We have now determined the complete nucleotide and translated amino acid sequences of a SW isolate of SIN virus (SW6562) and performed comparative analyses with other SIN viruses at the genomic level. The genome of SW6562 is 11,569 nucleotides in length, excluding the cap nucleotide and poly (A) tail. Overall this virus differs from the prototype SIN virus (strain AR339) by 23% in nucleotide sequence and 12.5% in amino acid sequence. Partial sequences of four regions of the genome of four SW isolates were determined and compared with the corresponding sequences from a number of SIN isolates from different regions of the World. These regions are the non-structural protein (nsP3), the E2 gene, the capsid gene, and the repeated sequence elements (RSE) of the 3'UTR. These comparisons revealed that the SW SIN viruses were more closely related to South African and European strains than to other Australian isolates of SIN virus. Thus the SW genotype of SIN virus may have been introduced into this region of Australia by viremic humans or migratory birds and subsequently evolved independently in the region. The sequence data also revealed that the SW genotype contains a unique deletion in the RSE of the 3'UTR region of the genome. Previous studies have shown that deletions in this region of the SIN genome can have significant effects on virus replication in mosquito and avian cells, which may explain the restricted distribution of this genotype of SIN virus.
Resumo:
After the 1st appearance of Japanese encephalitis virus (JE) on mainland Australia in 1998, a study was undertaken to investigate whether JE had become established in enzootic transmission cycles on western Cape York Peninsula. Adult mosquitoes were collected during the late wet season from Kowanyama and Pormpuraaw in April 1999, and Pormpuraaw and Barr's Yard in April 2000. Despite processing 269,270 mosquitoes for virus isolation, no isolates of JE were obtained. However, other flaviviruses comprising Murray Valley encephalitis virus, Kunjin virus, Alfuy virus, and Kokobera virus (KOK) were isolated. Isolates of the alphaviruses Ross River virus, Barmah Forest virus (BF), and Sindbis virus (SIN) also were obtained. The majority (88%) of isolates were from members of the Culex sitiens subgroup. Single isolates of KOK, BF and SIN were obtained from Ochlerotatus vigilax, Oc. normanensis, and Anopheles bancroftii, respectively. The isolations of flaviviruses during the late wet season indicate that conditions were suitable for flavivirus activity in the area. No evidence was found to suggest that JE has become established in enzootic transmission cycles on western Cape York, although study sites and field trips were limited.
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An important cytokine role in dengue fever pathogenesis has been described. These molecules can be associated with haemorrhagic manifestations, coagulation disorders, hypotension and shock, all symptoms implicated in vascular permeability and disease worsening conditions. Several immunological diseases have been treated by cytokine modulation and dexamethasone is utilized clinically to treat pathologies with inflammatory and autoimmune ethiologies. We established an in vitro model with human monocytes infected by dengue virus-2 for evaluating immunomodulatory and antiviral activities of potential pharmaceutical products. Flow cytometry analysis demonstrated significant dengue antigen detection in target cells two days after infection. TNF-alpha, IFN-alpha, IL-6 and IL-10 are produced by in vitro infected monocytes and are significantly detected in cell culture supernatants by multiplex microbead immunoassay. Dexamethasone action was tested for the first time for its modulation in dengue infection, presenting optimistic results in both decreasing cell infection rates and inhibiting TNF-alpha, IFN-alpha and IL-10 production. This model is proposed for novel drug trials yet to be applyed for dengue fever.
Resumo:
Dengue fever is a noncontagious infectious disease caused by dengue virus (DENV). DENV belongs to the family Flaviviridae, genus Flavivirus, and is classified into four antigenically distinct serotypes: DENV-1, DENV-2, DENV-3, and DENV-4. The number of nations and people affected has increased steadily and today is considered the most widely spread arbovirus (arthropod-borne viral disease) in the world. The absence of an appropriate animal model for studying the disease has hindered the understanding of dengue pathogenesis. In our study, we have found that immunocompetent C57BL/6 mice infected intraperitoneally with DENV-1 presented some signs of dengue disease such as thrombocytopenia, spleen hemorrhage, liver damage, and increase in production of IFN gamma and TNF alpha cytokines. Moreover, the animals became viremic and the virus was detected in several organs by real-time RT-PCR. Thus, this animal model could be used to study mechanism of dengue virus infection, to test antiviral drugs, as well as to evaluate candidate vaccines.
Resumo:
Members of the Culex sitiens subgroup are important vectors of arboviruses, including Japanese encephalitis virus, Murray Valley encephalitis virus and Ross River virus. Of the eight described species, Cx. annulirostris Skuse, Cx. sitiens Wiedemann, and Cx. palpalis Taylor appear to be the most abundant and widespread throughout northern Australia and Papua New Guinea (PNG). Recent investigations using allozymes have shown this subgroup to contain cryptic species that possess overlapping adult morphology. We report the development of a polymerase chain reaction-restriction fragment-length polymorphism (PCR-RFLP) procedure that reliably separates these three species. This procedure utilizes the sequence variation in the ribosomal DNA ITS1 and demonstrates species-specific PCR-RFLP profiles from both colony and field collected material. Assessment of the consistency of this procedure was undertaken on mosquitoes sampled from a wide geographic area including Australia, PNG, and the Solomon Islands. Overlapping adult morphology was observed for Cx. annulirostris and Cx. palpalis in both northern Queensland and PNG and for all three species at one site in northwest Queensland.
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The structures of Sindbis virus and Ross River virus complexed with Fab fragments from monoclonal antibodies have been determined from cryoelectron micrographs. Both antibodies chosen for this study bind to regions of the virions that have been implicated in cell-receptor recognition and recognize epitopes on the E2 glycoprotein. The two structures show that the Fab fragments bind to the outermost tip of the trimeric envelope spike protein. Hence, the same region of both the Sindbis virus and Ross River virus envelope spike is composed of E2 and is involved in recognition of the cellular receptor.
Resumo:
Intensification of agricultural production without a sound management and regulations can lead to severe environmental problems, as in Western Santa Catarina State, Brazil, where intensive swine production has caused large accumulations of manure and consequently water pollution. Natural resource scientists are asked by decision-makers for advice on management and regulatory decisions. Distributed environmental models are useful tools, since they can be used to explore consequences of various management practices. However, in many areas of the world, quantitative data for model calibration and validation are lacking. The data-intensive distributed environmental model AgNPS was applied in a data-poor environment, the upper catchment (2,520 ha) of the Ariranhazinho River, near the city of Seara, in Santa Catarina State. Steps included data preparation, cell size selection, sensitivity analysis, model calibration and application to different management scenarios. The model was calibrated based on a best guess for model parameters and on a pragmatic sensitivity analysis. The parameters were adjusted to match model outputs (runoff volume, peak runoff rate and sediment concentration) closely with the sparse observed data. A modelling grid cell resolution of 150 m adduced appropriate and computer-fit results. The rainfall runoff response of the AgNPS model was calibrated using three separate rainfall ranges (< 25, 25-60, > 60 mm). Predicted sediment concentrations were consistently six to ten times higher than observed, probably due to sediment trapping along vegetated channel banks. Predicted N and P concentrations in stream water ranged from just below to well above regulatory norms. Expert knowledge of the area, in addition to experience reported in the literature, was able to compensate in part for limited calibration data. Several scenarios (actual, recommended and excessive manure applications, and point source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions.
Resumo:
The distributed-tubes model of hepatic elimination is extended to include intermixing between sinusoids, resulting in the formulation of a new, interconnected-tubes model. The new model is analysed for the simple case of two interconnected tubes, where an exact solution is obtained. For the case of many strongly-interconnected tubes, it is shown that a zeroth-order approximation leads to the convection-dispersion model. As a consequence the dispersion number is expressed, for the first time, in terms of its main physiological determinants: heterogeneity of flow and density of interconnections between sinusoids. The analysis of multiple indicator dilution data from a perfused liver preparation using the simplest version of the model yields the estimate 10.3 for the average number of interconnections. The problem of boundary conditions for the dispersion model is considered from the viewpoint that the dispersion-convection equation is a zeroth-order approximation to the equations for the interconnected-tubes model. (C) 1997 Academic Press Limited.
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Global hydrological models (GHMs) model the land surface hydrologic dynamics of continental-scale river basins. Here we describe one such GHM, the Macro-scale - Probability-Distributed Moisture model.09 (Mac-PDM.09). The model has undergone a number of revisions since it was last applied in the hydrological literature. This paper serves to provide a detailed description of the latest version of the model. The main revisions include the following: (1) the ability for the model to be run for n repetitions, which provides more robust estimates of extreme hydrological behaviour, (2) the ability of the model to use a gridded field of coefficient of variation (CV) of daily rainfall for the stochastic disaggregation of monthly precipitation to daily precipitation, and (3) the model can now be forced with daily input climate data as well as monthly input climate data. We demonstrate the effects that each of these three revisions has on simulated runoff relative to before the revisions were applied. Importantly, we show that when Mac-PDM.09 is forced with monthly input data, it results in a negative runoff bias relative to when daily forcings are applied, for regions of the globe where the day-to-day variability in relative humidity is high. The runoff bias can be up to - 80% for a small selection of catchments but the absolute magnitude of the bias may be small. As such, we recommend future applications of Mac-PDM.09 that use monthly climate forcings acknowledge the bias as a limitation of the model. The performance of Mac-PDM.09 is evaluated by validating simulated runoff against observed runoff for 50 catchments. We also present a sensitivity analysis that demonstrates that simulated runoff is considerably more sensitive to method of PE calculation than to perturbations in soil moisture and field capacity parameters.
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Many climate models have problems simulating Indian summer monsoon rainfall and its variability, resulting in considerable uncertainty in future projections. Problems may relate to many factors, such as local effects of the formulation of physical parametrisation schemes, while common model biases that develop elsewhere within the climate system may also be important. Here we examine the extent and impact of cold sea surface temperature (SST) biases developing in the northern Arabian Sea in the CMIP5 multi-model ensemble, where such SST biases are shown to be common. Such biases have previously been shown to reduce monsoon rainfall in the Met Office Unified Model (MetUM) by weakening moisture fluxes incident upon India. The Arabian Sea SST biases in CMIP5 models consistently develop in winter, via strengthening of the winter monsoon circulation, and persist into spring and summer. A clear relationship exists between Arabian Sea cold SST bias and weak monsoon rainfall in CMIP5 models, similar to effects in the MetUM. Part of this effect may also relate to other factors, such as forcing of the early monsoon by spring-time excessive equatorial precipitation. Atmosphere-only future time-slice experiments show that Arabian Sea cold SST biases have potential to weaken future monsoon rainfall increases by limiting moisture flux acceleration through non-linearity of the Clausius-Clapeyron relationship. Analysis of CMIP5 model future scenario simulations suggests that, while such effects are likely small compared to other sources of uncertainty, models with large Arabian Sea cold SST biases suppress the range of potential outcomes for changes to future early monsoon rainfall.
Resumo:
In this paper ensembles of forecasts (of up to six hours) are studied from a convection-permitting model with a representation of model error due to unresolved processes. The ensemble prediction system (EPS) used is an experimental convection-permitting version of the UK Met Office’s 24- member Global and Regional Ensemble Prediction System (MOGREPS). The method of representing model error variability, which perturbs parameters within the model’s parameterisation schemes, has been modified and we investigate the impact of applying this scheme in different ways. These are: a control ensemble where all ensemble members have the same parameter values; an ensemble where the parameters are different between members, but fixed in time; and ensembles where the parameters are updated randomly every 30 or 60 min. The choice of parameters and their ranges of variability have been determined from expert opinion and parameter sensitivity tests. A case of frontal rain over the southern UK has been chosen, which has a multi-banded rainfall structure. The consequences of including model error variability in the case studied are mixed and are summarised as follows. The multiple banding, evident in the radar, is not captured for any single member. However, the single band is positioned in some members where a secondary band is present in the radar. This is found for all ensembles studied. Adding model error variability with fixed parameters in time does increase the ensemble spread for near-surface variables like wind and temperature, but can actually decrease the spread of the rainfall. Perturbing the parameters periodically throughout the forecast does not further increase the spread and exhibits “jumpiness” in the spread at times when the parameters are perturbed. Adding model error variability gives an improvement in forecast skill after the first 2–3 h of the forecast for near-surface temperature and relative humidity. For precipitation skill scores, adding model error variability has the effect of improving the skill in the first 1–2 h of the forecast, but then of reducing the skill after that. Complementary experiments were performed where the only difference between members was the set of parameter values (i.e. no initial condition variability). The resulting spread was found to be significantly less than the spread from initial condition variability alone.
Resumo:
The reliable evaluation of the flood forecasting is a crucial problem for assessing flood risk and consequent damages. Different hydrological models (distributed, semi-distributed or lumped) have been proposed in order to deal with this issue. The choice of the proper model structure has been investigated by many authors and it is one of the main sources of uncertainty for a correct evaluation of the outflow hydrograph. In addition, the recent increasing of data availability makes possible to update hydrological models as response of real-time observations. For these reasons, the aim of this work it is to evaluate the effect of different structure of a semi-distributed hydrological model in the assimilation of distributed uncertain discharge observations. The study was applied to the Bacchiglione catchment, located in Italy. The first methodological step was to divide the basin in different sub-basins according to topographic characteristics. Secondly, two different structures of the semi-distributed hydrological model were implemented in order to estimate the outflow hydrograph. Then, synthetic observations of uncertain value of discharge were generated, as a function of the observed and simulated value of flow at the basin outlet, and assimilated in the semi-distributed models using a Kalman Filter. Finally, different spatial patterns of sensors location were assumed to update the model state as response of the uncertain discharge observations. The results of this work pointed out that, overall, the assimilation of uncertain observations can improve the hydrologic model performance. In particular, it was found that the model structure is an important factor, of difficult characterization, since can induce different forecasts in terms of outflow discharge. This study is partly supported by the FP7 EU Project WeSenseIt.
Resumo:
The frequency spectrums are inefficiently utilized and cognitive radio has been proposed for full utilization of these spectrums. The central idea of cognitive radio is to allow the secondary user to use the spectrum concurrently with the primary user with the compulsion of minimum interference. However, designing a model with minimum interference is a challenging task. In this paper, a transmission model based on cyclic generalized polynomial codes discussed in [2] and [15], is proposed for the improvement in utilization of spectrum. The proposed model assures a non interference data transmission of the primary and secondary users. Furthermore, analytical results are presented to show that the proposed model utilizes spectrum more efficiently as compared to traditional models.
Resumo:
We use an automatic weather station and surface mass balance dataset spanning four melt seasons collected on Hurd Peninsula Glaciers, South Shetland Islands, to investigate the point surface energy balance, to determine the absolute and relative contribution of the various energy fluxes acting on the glacier surface and to estimate the sensitivity of melt to ambient temperature changes. Long-wave incoming radiation is the main energy source for melt, while short-wave radiation is the most important flux controlling the variation of both seasonal and daily mean surface energy balance. Short-wave and long-wave radiation fluxes do, in general, balance each other, resulting in a high correspondence between daily mean net radiation flux and available melt energy flux. We calibrate a distributed melt model driven by air temperature and an expression for the incoming short-wave radiation. The model is calibrated with the data from one of the melt seasons and validated with the data of the three remaining seasons. The model results deviate at most 140 mm w.e. from the corresponding observations using the glaciological method. The model is very sensitive to changes in ambient temperature: a 0.5 ◦ C increase results in 56 % higher melt rates.