A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection

This paper presents three methods for automatic detection of dust devils tracks in images of Mars. The methods are mainly based on Mathematical Morphology and results of their performance are analyzed and compared. A dataset of 21 images from the surface of Mars representative of the diversity of those track features were considered for developing, testing and evaluating our methods, confronting their outputs with ground truth images made manually. Methods 1 and 3, based on closing top-hat and path closing top-hat, respectively, showed similar mean accuracies around 90% but the time of processing was much greater for method 1 than for method 3. Method 2, based on radial closing, was the fastest but showed worse mean accuracy. Thus, this was the tiebreak factor. © 2011 Springer-Verlag.

Survey methods, based on periodically repeated interviews, aimed at determining demographic rates

Includes bibliography

Aplicação da competência em informação no contexto escolar: uma experiência no Colégio Militar de Campo Grande - MS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo da ocorrência de tetraciclinas e estrógenos em água superficial, subterrânea e esgoto tratado na cidade de Campo Grande (MS)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Pesticidas mais empregados na cultura de soja no município de Dourados (MS): determinação em água para consumo humano

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Assessing melatonin and its oxidative metabolites amounts in biological fluid and culture medium by liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Product-portfolio management: A framework based on Methods, Organization, and Strategy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Analysis of criteria for metabolic syndrome in a population-based study of Japanese-Brazilians

Objective: Criteria for metabolic syndrome (MS) differ particularly regarding the definition of central obesity and consequently, there could be differences in the assessment of cardiovascular risk. We estimated the prevalence of metabolic syndrome, compared the agreement of the World Health Organization (WHO) criteria with the standard and a modified National Cholesterol Education Program (NCEP) criterion and investigated whether additional factors were associated with the diagnosis of the syndrome in a Japanese descendant population.Methods: In this cross-sectional, population-based survey, 1166 Japanese-Brazilians (533 men, 633 women) aged 57.4 +/- 12.4 years with mean body mass index (BMI) and waist of 25.2 +/- 4.0 kg/m(2) and 84.5 +/- 10.6 cm, respectively, were included. McNemar and kappa statistics were used to assess the concordance between WHO criteria with the standard and a modified NCEP criteria (waist of 90 and 80 cm, for men and women, respectively). in logistic regression analysis, a number of metabolic variables and albumin-to-creatinine ratio were included to test independent associations with metabolic syndrome defined by the modified NCEP criteria.Results: According to WHO, 55.4% (95% Cl 52.5-58.2%) of the subjects had MS and to NCEP 47.4% (95% Cl 44.6-50.0%). WHO criterion detected 48.3% of central obese subjects while NCEP only 14.0%. Kappa statistics showed a good strength of agreement (k = 0.67, p < 0.01) between WHO and NCEP standard definitions of MS. Using the modified NCEP criterion for Asians, more subjects with metabolic syndrome were identified (58%) and agreement with WHO was improved (k = 0.72, p < 0.001). However, similar Framingham risk scores were attributed to the subsets of subjects classified by any of the three criteria. Areas under the receiver operating characteristic curves, obtained for the modified waist values to diagnose metabolic syndrome according to WHO, were > 0.80 and corresponded, respectively, to sensitivity and specificity of 63 and 83% for men and 77 and 72% for women. In final logistic regression model, age, male sex, BMI and homeostasis model assessment-insulin resistance but not with albumin-to-creatinine ratio (ACR) were independently associated with the syndrome.Conclusions: High prevalence of MS, independent of the criterion considered, was found in this Japanese-Brazilian population. The replacement of waist cutoff by those proposed by WHO for Asians lead to this diagnosis in a higher number of subjects with elevated cardiovascular risk. Our data did not support that ACR should be included in the classical definition of MS in Japanese descendants as previously suggested by WHO.

Metalloproteomic profile determination of muscle samples from nile Tilapia (Oreochromis niloticus) using AAS and ESI-MS/MS after 2D-PAGE separation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Influence of CAD-CAM diamond bur deterioration on surface roughness and maximum failure load of Y-TZP-based restorations

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Spatial methods for plot-based sampling of wildlife populations

Classical sampling methods can be used to estimate the mean of a finite or infinite population. Block kriging also estimates the mean, but of an infinite population in a continuous spatial domain. In this paper, I consider a finite population version of block kriging (FPBK) for plot-based sampling. The data are assumed to come from a spatial stochastic process. Minimizing mean-squared-prediction errors yields best linear unbiased predictions that are a finite population version of block kriging. FPBK has versions comparable to simple random sampling and stratified sampling, and includes the general linear model. This method has been tested for several years for moose surveys in Alaska, and an example is given where results are compared to stratified random sampling. In general, assuming a spatial model gives three main advantages over classical sampling: (1) FPBK is usually more precise than simple or stratified random sampling, (2) FPBK allows small area estimation, and (3) FPBK allows nonrandom sampling designs.

Numerical analysis of different methods to calculate residual stresses in thin films based on instrumented indentation data

In this work, different methods to estimate the value of thin film residual stresses using instrumented indentation data were analyzed. This study considered procedures proposed in the literature, as well as a modification on one of these methods and a new approach based on the effect of residual stress on the value of hardness calculated via the Oliver and Pharr method. The analysis of these methods was centered on an axisymmetric two-dimensional finite element model, which was developed to simulate instrumented indentation testing of thin ceramic films deposited onto hard steel substrates. Simulations were conducted varying the level of film residual stress, film strain hardening exponent, film yield strength, and film Poisson's ratio. Different ratios of maximum penetration depth h(max) over film thickness t were also considered, including h/t = 0.04, for which the contribution of the substrate in the mechanical response of the system is not significant. Residual stresses were then calculated following the procedures mentioned above and compared with the values used as input in the numerical simulations. In general, results indicate the difference that each method provides with respect to the input values depends on the conditions studied. The method by Suresh and Giannakopoulos consistently overestimated the values when stresses were compressive. The method provided by Wang et al. has shown less dependence on h/t than the others.

Nonculture-based identification of bacteria in milk by protein fingerprinting

Traditional methods for bacterial identification include Gram staining, culturing, and biochemical assays for phenotypic characterization of the causative organism. These methods can be time-consuming because they require in vitro cultivation of the microorganisms. Recently, however, it has become possible to obtain chemical profiles for lipids, peptides, and proteins that are present in an intact organism, particularly now that new developments have been made for the efficient ionization of biomolecules. MS has therefore become the state-of-the-art technology for microorganism identification in microbiological clinical diagnosis. Here, we introduce an innovative sample preparation method for nonculture-based identification of bacteria in milk. The technique detects characteristic profiles of intact proteins (mostly ribosomal) with the recently introduced MALDI SepsityperTM Kit followed by MALDI-MS. In combination with a dedicated bioinformatics software tool for databank matching, the method allows for almost real-time and reliable genus and species identification. We demonstrate the sensitivity of this protocol by experimentally contaminating pasteurized and homogenized whole milk samples with bacterial loads of 10(3)-10(8) colony-forming units (cfu) of laboratory strains of Escherichia coli, Enterococcus faecalis, and Staphylococcus aureus. For milk samples contaminated with a lower bacterial load (104 cfu mL-1), bacterial identification could be performed after initial incubation at 37 degrees C for 4 h. The sensitivity of the method may be influenced by the bacterial species and count, and therefore, it must be optimized for the specific application. The proposed use of protein markers for nonculture-based bacterial identification allows for high-throughput detection of pathogens present in milk samples. This method could therefore be useful in the veterinary practice and in the dairy industry, such as for the diagnosis of subclinical mastitis and for the sanitary monitoring of raw and processed milk products.

Evaluation of reference-based two-color methods for measurement of gene expression ratios using spotted cDNA microarrays

Abstract Background Spotted cDNA microarrays generally employ co-hybridization of fluorescently-labeled RNA targets to produce gene expression ratios for subsequent analysis. Direct comparison of two RNA samples in the same microarray provides the highest level of accuracy; however, due to the number of combinatorial pair-wise comparisons, the direct method is impractical for studies including large number of individual samples (e.g., tumor classification studies). For such studies, indirect comparisons using a common reference standard have been the preferred method. Here we evaluated the precision and accuracy of reconstructed ratios from three indirect methods relative to ratios obtained from direct hybridizations, herein considered as the gold-standard. Results We performed hybridizations using a fixed amount of Cy3-labeled reference oligonucleotide (RefOligo) against distinct Cy5-labeled targets from prostate, breast and kidney tumor samples. Reconstructed ratios between all tissue pairs were derived from ratios between each tissue sample and RefOligo. Reconstructed ratios were compared to (i) ratios obtained in parallel from direct pair-wise hybridizations of tissue samples, and to (ii) reconstructed ratios derived from hybridization of each tissue against a reference RNA pool (RefPool). To evaluate the effect of the external references, reconstructed ratios were also calculated directly from intensity values of single-channel (One-Color) measurements derived from tissue sample data collected in the RefOligo experiments. We show that the average coefficient of variation of ratios between intra- and inter-slide replicates derived from RefOligo, RefPool and One-Color were similar and 2 to 4-fold higher than ratios obtained in direct hybridizations. Correlation coefficients calculated for all three tissue comparisons were also similar. In addition, the performance of all indirect methods in terms of their robustness to identify genes deemed as differentially expressed based on direct hybridizations, as well as false-positive and false-negative rates, were found to be comparable. Conclusion RefOligo produces ratios as precise and accurate as ratios reconstructed from a RNA pool, thus representing a reliable alternative in reference-based hybridization experiments. In addition, One-Color measurements alone can reconstruct expression ratios without loss in precision or accuracy. We conclude that both methods are adequate options in large-scale projects where the amount of a common reference RNA pool is usually restrictive.

Towards a precise test for malaria diagnosis in the Brazilian Amazon: comparison among field microscopy, a rapid diagnostic test, nested PCR, and a computational expert system based on artificial neural networks

Abstract Background Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. Methods The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. Results Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). Conclusions An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.