940 resultados para Schooling in low SES areas


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The Carr-Purcell pulse sequence, with low refocusing flip angle, produces echoes midway between refocusing pulses that decay to a minimum value dependent on T*(2). When the refocusing flip angle was pi/2 (CP90) and tau > T*(2), the signal after the minimum value, increased to reach a steady-state free precession regime (SSFP), composed of a free induction decay signal after each pulse and an echo, before the next pulse. When tau < T*(2), the signal increased from the minimum value to the steady-state regime with a time constant (T*) = 2T(1)T(2)/(T-1 + T-2). identical to the time constant observed in the SSFP sequence, known as the continuous wave free precession (CWFP). The steady-state amplitude obtained with M-cp90 = M0T2/(T-1+T-2) was identical to CWFP. Therefore, this sequence was named CP-CWFP because it is a Carr-Purcell sequence that produces results similar to the CWFP. However, CP-CWFP is a better sequence for measuring the longitudinal and transverse relaxation times in single scan, when the sample exhibits T-1 similar to T-2. Therefore, this sequence can be a useful method in time domain NMR and can be widely used in the agriculture, food and petrochemical industries because those samples tend to have similar relaxation times in low magnetic fields. (C) 2011 Elsevier Inc. All rights reserved.

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Abstract Background The development of protective immunity against malaria is slow and to be maintained, it requires exposure to multiple antigenic variants of malaria parasites and age-associated maturation of the immune system. Evidence that the protective immunity is associated with different classes and subclasses of antibodies reveals the importance of considering the quality of the response. In this study, we have evaluated the humoral immune response against Plasmodium falciparum blood stages of individuals naturally exposed to malaria who live in endemic areas of Brazil in order to assess the prevalence of different specific isotypes and their association with different malaria clinical expressions. Methods Different isotypes against P. falciparum blood stages, IgG, IgG1, IgG2, IgG3, IgG4, IgM, IgE and IgA, were determined by ELISA. The results were based on the analysis of different clinical expressions of malaria (complicated, uncomplicated and asymptomatic) and factors related to prior malaria exposure such as age and the number of previous clinical malaria attacks. The occurrence of the H131 polymorphism of the FcγIIA receptor was also investigated in part of the studied population. Results The highest levels of IgG, IgG1, IgG2 and IgG3 antibodies were observed in individuals with asymptomatic and uncomplicated malaria, while highest levels of IgG4, IgE and IgM antibodies were predominant among individuals with complicated malaria. Individuals reporting more than five previous clinical malaria attacks presented a predominance of IgG1, IgG2 and IgG3 antibodies, while IgM, IgA and IgE antibodies predominated among individuals reporting five or less previous clinical malaria attacks. Among individuals with uncomplicated and asymptomatic malaria, there was a predominance of high-avidity IgG, IgG1, IgG2 antibodies and low-avidity IgG3 antibodies. The H131 polymorphism was found in 44.4% of the individuals, and the highest IgG2 levels were observed among asymptomatic individuals with this allele, suggesting the protective role of IgG2 in this population. Conclusion Together, the results suggest a differential regulation in the anti-P. falciparum antibody pattern in different clinical expressions of malaria and showed that even in unstable transmission areas, protective immunity against malaria can be observed, when the appropriated antibodies are produced.

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Abstract Background In areas with limited structure in place for microscopy diagnosis, rapid diagnostic tests (RDT) have been demonstrated to be effective. Method The cost-effectiveness of the Optimal® and thick smear microscopy was estimated and compared. Data were collected on remote areas of 12 municipalities in the Brazilian Amazon. Data sources included the National Malaria Control Programme of the Ministry of Health, the National Healthcare System reimbursement table, hospitalization records, primary data collected from the municipalities, and scientific literature. The perspective was that of the Brazilian public health system, the analytical horizon was from the start of fever until the diagnostic results provided to patient and the temporal reference was that of year 2006. The results were expressed in costs per adequately diagnosed cases in 2006 U.S. dollars. Sensitivity analysis was performed considering key model parameters. Results In the case base scenario, considering 92% and 95% sensitivity for thick smear microscopy to Plasmodium falciparum and Plasmodium vivax, respectively, and 100% specificity for both species, thick smear microscopy is more costly and more effective, with an incremental cost estimated at US$549.9 per adequately diagnosed case. In sensitivity analysis, when sensitivity and specificity of microscopy for P. vivax were 0.90 and 0.98, respectively, and when its sensitivity for P. falciparum was 0.83, the RDT was more cost-effective than microscopy. Conclusion Microscopy is more cost-effective than OptiMal® in these remote areas if high accuracy of microscopy is maintained in the field. Decision regarding use of rapid tests for diagnosis of malaria in these areas depends on current microscopy accuracy in the field.

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The aim of this study was to identify future distribution areas and propose actions to preserve passion fruit pollination service under a scenario of future climate change. We used four species of Xylocopa bees that are important for passion fruit pollination in Brazilian Tropical Savannas. We also used the known forage plant species (33 species) that are associated with this same area, since passion fruit flowers provide only nectar for bees and only during their blossoming period. We used species distribution modeling to predict the potential areas of occurrence for each bee and plant based on the current day distribution and a future climate scenario (moderate projections of climate change to 2050). We used a geographic information system to classify the models and to analyze the future areas for both groups of species. The current day distribution map showed that Xylocopa and plant species occurred primarily in the southern and central-eastern areas of the Brazilian Tropical Savannas. In the north, Xylocopa species only occurred in a small area between the states of Maranhão and Piauí while forage plant species were only observed in the northern part of the Tocantins State. However, both future scenarios (bees and plants) showed a shift in distribution, with occurrence predominantly detected in the northern areas of Brazilian Tropical Savannas. Possible conservation areas and the use of appropriate agricultural practices were suggested to ensure the maintenance of the bee/plant focal species.

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OBJECTIVE: To analyze cause-specific mortality rates according to the relative income hypothesis. METHODS: All 96 administrative areas of the city of São Paulo, southeastern Brazil, were divided into two groups based on the Gini coefficient of income inequality: high (>0.25) and low (<0.25). The propensity score matching method was applied to control for confounders associated with socioeconomic differences among areas. RESULTS: The difference between high and low income inequality areas was statistically significant for homicide (8.57 per 10,000; 95%CI: 2.60;14.53); ischemic heart disease (5.47 per 10,000 [95%CI 0.76;10.17]); HIV/AIDS (3.58 per 10,000 [95%CI 0.58;6.57]); and respiratory diseases (3.56 per 10,000 [95%CI 0.18;6.94]). The ten most common causes of death accounted for 72.30% of the mortality difference. Infant mortality also had significantly higher age-adjusted rates in high inequality areas (2.80 per 10,000 [95%CI 0.86;4.74]), as well as among males (27.37 per 10,000 [95%CI 6.19;48.55]) and females (15.07 per 10,000 [95%CI 3.65;26.48]). CONCLUSIONS: The study results support the relative income hypothesis. After propensity score matching cause-specific mortality rates was higher in more unequal areas. Studies on income inequality in smaller areas should take proper accounting of heterogeneity of social and demographic characteristics.

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Toxocariasis is a worldwide public-health problem that poses major risks to children who may accidentally ingest embryonated eggs of Toxocara. The objectives of this study were to investigate the occurrence of anti-Toxocara spp. antibodies in children and adolescents and the variables that may be involved, as well as environmental contamination by Toxocara spp. eggs, in urban recreation areas of north central mesoregion, Paraná State, Brazil. From June 2005 to March 2007. a total of 376 blood samples were collected by the Public Health Service from children and adolescents one to 12 years old, of both genders. Samples were analyzed by the indirect ELISA method for detection of anti-Toxocara antibodies. Serum samples were previously absorbed with Ascaris suum antigens, and considered positive with a reagent reactivity index ≥1. Soil samples from all of the public squares and schools located in the four evaluated municipalities that had sand surfaces (n = 19) or lawns (n = 15) were analyzed. Of the 376 serum samples, 194 (51.6%) were positive. The seroprevalence rate was substantially higher among children aging one to five years (p = 0.001) and six to eight years (p = 0.022). The clinical signs and symptoms investigated did not show a statistical difference between seropositive and seronegative individuals (p > 0.05). In 76.5% of the investigated recreation places, eggs of Toxocara were detected in at least one of the five collected samples. Recreation areas from public schools were 2.8 times more contaminated than from public squares. It is important to institute educational programs to inform families and educators, as well as to improve sanitary control of animals and cleaning of the areas intended for recreation in order to prevent toxocariasis.

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The abandonment of less productive fields and agro-forest activities has occured in the last decades, interesting large mountain areas in all mediterranean basin. Until the fifties, agricultural practices dealt mainly with soil surface and surface runoff control systems. However, the apparent sustainability of soil use results often in contrast with historical documents, witnessing heavy hydrogeological instability, in naturally fragile areas. The research focused on the dynamics and effects of post-coltural land abandonment in a critical mountain area of the Reno River. The Reno River rappresents a typical Tuscan-Emilian Apennines Watershed where soil erosion occurs under very different conditions depending on interactions between land use, climate, geomorphology and lithology. Landslides are largely rappresented, due to the diffusion of clay hill slopes. Recent researches suggest that climatic variability will increase as a consequence of global climate change, resulting in greater frequency and intensity of extreme weather events, which could increase rates of erosion, landslides reactivations and diffusion of calanchive basins. As far as hill slopes are concerned, instability is today basically due to intrinsic factors, as the Apennine range is a rather young formation, in geological terms, and is mainly formed by sedimentary rocks with high occurrence of clays. Therefore landslides and rockfalls are very frequent, while surface soil erosion is generally low and anyway concentrated in the low Apennine, where intensive farming is still economically worth. The study, supported by GIS use, analyses the main fisical characteristics of the area and the historical changes of land use, and focalizes the dynamics of spontaneous reafforestation. Futhermore, the research studies the results of soil bioengineering and surface water control solutions for the restablishment of landslides occured in the last period. Infact soil bioengineering has been recently used in different situations in order to consolidate slopes and hillsides and prevent erosion; when applied, it gave good results, both in terms of engineering efficiency and vegetational development, expecially if combined with a good hydraulic control, thus proving to be an actual alternative to other techniques with heavier environmental impacts. Research into the specific site features and the use of proper plant species is vital to the success of bioengineering works.

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In this work we aim to propose a new approach for preliminary epidemiological studies on Standardized Mortality Ratios (SMR) collected in many spatial regions. A preliminary study on SMRs aims to formulate hypotheses to be investigated via individual epidemiological studies that avoid bias carried on by aggregated analyses. Starting from collecting disease counts and calculating expected disease counts by means of reference population disease rates, in each area an SMR is derived as the MLE under the Poisson assumption on each observation. Such estimators have high standard errors in small areas, i.e. where the expected count is low either because of the low population underlying the area or the rarity of the disease under study. Disease mapping models and other techniques for screening disease rates among the map aiming to detect anomalies and possible high-risk areas have been proposed in literature according to the classic and the Bayesian paradigm. Our proposal is approaching this issue by a decision-oriented method, which focus on multiple testing control, without however leaving the preliminary study perspective that an analysis on SMR indicators is asked to. We implement the control of the FDR, a quantity largely used to address multiple comparisons problems in the eld of microarray data analysis but which is not usually employed in disease mapping. Controlling the FDR means providing an estimate of the FDR for a set of rejected null hypotheses. The small areas issue arises diculties in applying traditional methods for FDR estimation, that are usually based only on the p-values knowledge (Benjamini and Hochberg, 1995; Storey, 2003). Tests evaluated by a traditional p-value provide weak power in small areas, where the expected number of disease cases is small. Moreover tests cannot be assumed as independent when spatial correlation between SMRs is expected, neither they are identical distributed when population underlying the map is heterogeneous. The Bayesian paradigm oers a way to overcome the inappropriateness of p-values based methods. Another peculiarity of the present work is to propose a hierarchical full Bayesian model for FDR estimation in testing many null hypothesis of absence of risk.We will use concepts of Bayesian models for disease mapping, referring in particular to the Besag York and Mollié model (1991) often used in practice for its exible prior assumption on the risks distribution across regions. The borrowing of strength between prior and likelihood typical of a hierarchical Bayesian model takes the advantage of evaluating a singular test (i.e. a test in a singular area) by means of all observations in the map under study, rather than just by means of the singular observation. This allows to improve the power test in small areas and addressing more appropriately the spatial correlation issue that suggests that relative risks are closer in spatially contiguous regions. The proposed model aims to estimate the FDR by means of the MCMC estimated posterior probabilities b i's of the null hypothesis (absence of risk) for each area. An estimate of the expected FDR conditional on data (\FDR) can be calculated in any set of b i's relative to areas declared at high-risk (where thenull hypothesis is rejected) by averaging the b i's themselves. The\FDR can be used to provide an easy decision rule for selecting high-risk areas, i.e. selecting as many as possible areas such that the\FDR is non-lower than a prexed value; we call them\FDR based decision (or selection) rules. The sensitivity and specicity of such rule depend on the accuracy of the FDR estimate, the over-estimation of FDR causing a loss of power and the under-estimation of FDR producing a loss of specicity. Moreover, our model has the interesting feature of still being able to provide an estimate of relative risk values as in the Besag York and Mollié model (1991). A simulation study to evaluate the model performance in FDR estimation accuracy, sensitivity and specificity of the decision rule, and goodness of estimation of relative risks, was set up. We chose a real map from which we generated several spatial scenarios whose counts of disease vary according to the spatial correlation degree, the size areas, the number of areas where the null hypothesis is true and the risk level in the latter areas. In summarizing simulation results we will always consider the FDR estimation in sets constituted by all b i's selected lower than a threshold t. We will show graphs of the\FDR and the true FDR (known by simulation) plotted against a threshold t to assess the FDR estimation. Varying the threshold we can learn which FDR values can be accurately estimated by the practitioner willing to apply the model (by the closeness between\FDR and true FDR). By plotting the calculated sensitivity and specicity (both known by simulation) vs the\FDR we can check the sensitivity and specicity of the corresponding\FDR based decision rules. For investigating the over-smoothing level of relative risk estimates we will compare box-plots of such estimates in high-risk areas (known by simulation), obtained by both our model and the classic Besag York Mollié model. All the summary tools are worked out for all simulated scenarios (in total 54 scenarios). Results show that FDR is well estimated (in the worst case we get an overestimation, hence a conservative FDR control) in small areas, low risk levels and spatially correlated risks scenarios, that are our primary aims. In such scenarios we have good estimates of the FDR for all values less or equal than 0.10. The sensitivity of\FDR based decision rules is generally low but specicity is high. In such scenario the use of\FDR = 0:05 or\FDR = 0:10 based selection rule can be suggested. In cases where the number of true alternative hypotheses (number of true high-risk areas) is small, also FDR = 0:15 values are well estimated, and \FDR = 0:15 based decision rules gains power maintaining an high specicity. On the other hand, in non-small areas and non-small risk level scenarios the FDR is under-estimated unless for very small values of it (much lower than 0.05); this resulting in a loss of specicity of a\FDR = 0:05 based decision rule. In such scenario\FDR = 0:05 or, even worse,\FDR = 0:1 based decision rules cannot be suggested because the true FDR is actually much higher. As regards the relative risk estimation, our model achieves almost the same results of the classic Besag York Molliè model. For this reason, our model is interesting for its ability to perform both the estimation of relative risk values and the FDR control, except for non-small areas and large risk level scenarios. A case of study is nally presented to show how the method can be used in epidemiology.

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The production, segregation and migration of melt and aqueous fluids (henceforth called liquid) plays an important role for the transport of mass and energy within the mantle and the crust of the Earth. Many properties of large-scale liquid migration processes such as the permeability of a rock matrix or the initial segregation of newly formed liquid from the host-rock depends on the grain-scale distribution and behaviour of liquid. Although the general mechanisms of liquid distribution at the grain-scale are well understood, the influence of possibly important modifying processes such as static recrystallization, deformation, and chemical disequilibrium on the liquid distribution is not well constrained. For this thesis analogue experiments were used that allowed to investigate the interplay of these different mechanisms in-situ. In high-temperature environments where melts are produced, the grain-scale distribution in “equilibrium” is fully determined by the liquid fraction and the ratio between the solid-solid and the solid-liquid surface energy. The latter is commonly expressed as the dihedral or wetting angle between two grains and the liquid phase (Chapter 2). The interplay of this “equilibrium” liquid distribution with ongoing surface energy driven recrystallization is investigated in Chapter 4 and 5 with experiments using norcamphor plus ethanol liquid. Ethanol in contact with norcamphor forms a wetting angle of about 25°, which is similar to reported angles of rock-forming minerals in contact with silicate melt. The experiments in Chapter 4 show that previously reported disequilibrium features such as trapped liquid lenses, fully-wetted grain boundaries, and large liquid pockets can be explained by the interplay of the liquid with ongoing recrystallization. Closer inspection of dihedral angles in Chapter 5 reveals that the wetting angles are themselves modified by grain coarsening. Ongoing recrystallization constantly moves liquid-filled triple junctions, thereby altering the wetting angles dynamically as a function of the triple junction velocity. A polycrystalline aggregate will therefore always display a range of equilibrium and dynamic wetting angles at raised temperature, rather than a single wetting angle as previously thought. For the deformation experiments partially molten KNO3–LiNO3 experiments were used in addition to norcamphor–ethanol experiments (Chapter 6). Three deformation regimes were observed. At a high bulk liquid fraction >10 vol.% the aggregate deformed by compaction and granular flow. At a “moderate” liquid fraction, the aggregate deformed mainly by grain boundary sliding (GBS) that was localized into conjugate shear zones. At a low liquid fraction, the grains of the aggregate formed a supporting framework that deformed internally by crystal plastic deformation or diffusion creep. Liquid segregation was most efficient during framework deformation, while GBS lead to slow liquid segregation or even liquid dispersion in the deforming areas.

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The present work, then, is concerned with the forgotten elements of the Lebanese economy, agriculture and rural development. It investigates the main problematic which arose from these forgotten components, in particular the structure of the agricultural sector, production technology, income distribution, poverty, food security, territorial development and local livelihood strategies. It will do so using quantitative Computable General Equilibrium (CGE) modeling and a qualitative phenomenological case study analysis, both embedded in a critical review of the historical development of the political economy of Lebanon, and a structural analysis of its economy. The research shows that under-development in Lebanese rural areas is not due to lack of resources, but rather is the consequence of political choices. It further suggests that agriculture – in both its mainstream conventional and its innovative locally initiated forms of production – still represents important potential for inducing economic growth and development. In order to do so, Lebanon has to take full advantage of its human and territorial capital, by developing a rural development strategy based on two parallel sets of actions: one directed toward the support of local rural development initiatives, and the other directed toward intensive form of production. In addition to its economic returns, such a strategy would promote social and political stability.