39 resultados para spatial trend analysis
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Biological control of Diatraea saccharalis is regarded as one of the best examples of successful classical biological control in Brazil. Since the introduction of the exotic parasitoid Cotesia flavipes, the decrease of D. saccharalis infestation in sugarcane fields has been attributed to the effectiveness of this agent. Recently, the native tachinid fly parasitoids (Lydella minense and Paratheresia claripalpis) have also been implicated in the success. Here, we investigated the spatial and temporal population interactions between C. flavipes and the tachinid flies, and provide a critical analysis of the biological control practice, focusing on the undesirable effects of introductions of exotic natural enemies. To investigate these questions, a large data set comprising information from two sugarcane mills located in the state of São Paulo, Brazil (Barra and Sao Joao Mills), was analysed. Analysis of the correlation between C. flavipes and tachinid fly population densities through time revealed that such populations were inversely correlated in the Sao Joao Mill and not correlated in the Barra Mill. Logistic regressions were computed to investigate the proportion of sites occupied by the parasitoid species at both mills as a function of time. An increasing trend in the proportion of sites occupied by C. flavipes was observed, with a concomitant decrease of the sites occupied by tachinid flies. This effect was more intense in the Sao Joao Mill. Thus, there is a convincing possibility that constant releases of C. flavipes decreased the tachinid fly populations, resulting in an undesirable effect of biological control practice.
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Spatial analysis and fuzzy classification techniques were used to estimate the spatial distributions of heavy metals in soil. The work was applied to soils in a coastal region that is characterized by intense urban occupation and large numbers of different industries. Concentrations of heavy metals were determined using geostatistical techniques and classes of risk were defined using fuzzy classification. The resulting prediction mappings identify the locations of high concentrations of Pb, Zn, Ni, and Cu in topsoils of the study area. The maps show that areas of high pollution of Ni and Cu are located at the northeast, where there is a predominance of industrial and agricultural activities; Pb and Zn also occur in high concentrations in the northeast, but the maps also show significant concentrations of Pb and Zn in other areas, mainly in the central and southeastern parts, where there are urban leisure activities and trade centers. Maps were also prepared showing levels of pollution risk. These maps show that (1) Cu presents a large pollution risk in the north-northwest, midwest, and southeast sectors, (2) Pb represents a moderate risk in most areas, (3) Zn generally exhibits low risk, and (4) Ni represents either low risk or no risk in the studied area. This study shows that combining geostatistics with fuzzy theory can provide results that offer insight into risk assessment for environmental pollution.
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The objective of the present study, developed in a mountainous region in Brazil where many landslides occur, is to present a method for detecting landslide scars that couples image processing techniques with spatial analysis tools. An IKONOS image was initially segmented, and then classified through a Batthacharrya classifier, with an acceptance limit of 99%, resulting in 216 polygons identified with a spectral response similar to landslide scars. After making use of some spatial analysis tools that took into account a susceptibility map, a map of local drainage channels and highways, and the maximum expected size of scars in the study area, some features misinterpreted as scars were excluded. The 43 resulting features were then compared with visually interpreted landslide scars and field observations. The proposed method can be reproduced and enhanced by adding filtering criteria and was able to find new scars on the image, with a final error rate of 2.3%.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Design tools have existed for decades for standard step-index fibers, with analytical expressions for cutoff conditions as a function of core size, refractive indexes, and wavelength. We present analytical expressions for cutoff conditions for fibers with a ring-shaped propagation region. We validate our analytical expressions against numerical solutions, as well as via asymptotic analysis yielding the existing solutions for standard step-index fiber. We demonstrate the utility of our solutions for optimizing fibers supporting specific eigenmode behaviors of interest for spatial division multiplexing. In particular, we address large mode separation for orbital angular momentum modes and fibers supporting only modes with a single intensity ring.
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Background There are limited studies on the prevalence and risk factors associated with hepatitis C virus (HCV) infection. Objective Identify the prevalence and risk factors for HCV infection in university employees of the state of São Paulo, Brazil. Methods Digital serological tests for anti-HCV have been performed in 3153 volunteers. For the application of digital testing was necessary to withdraw a drop of blood through a needlestick. The positive cases were performed for genotyping and RNA. Chi-square and Fisher’s exact test were used, with P-value <0.05 indicating statistical significance. Univariate and multivariate logistic regression were also used. Results Prevalence of anti-HCV was 0.7%. The risk factors associated with HCV infection were: age >40 years, blood transfusion, injectable drugs, inhalable drugs (InDU), injectable Gluconergam®, glass syringes, tattoos, hemodialysis and sexual promiscuity. Age (P=0.01, OR 5.6, CI 1.4 to 22.8), InDU (P<0.0001, OR=96.8, CI 24.1 to 388.2), Gluconergam® (P=0.0009, OR=44.4, CI 4.7 to 412.7) and hemodialysis (P=0.0004, OR=90.1, CI 7.5 – 407.1) were independent predictors. Spatial analysis of the prevalence with socioeconomic indices, Gross Domestic Product and Human Development Index by the geoprocessing technique showed no positive correlation. Conclusions The prevalence of HCV infection was 0.7%. The independent risk factors for HCV infection were age, InDU, Gluconergan® and hemodialysis. There was no spatial correlation of HCV prevalence with local economic factors.