16 resultados para Supervised and Unsupervised Classification
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
The Restinga of Marambaia is an emerged sand bar located between the Sepetiba Bay and the South Atlantic Ocean, on the south-east coast of Brazil. The objective of this study was to observe the geomorphologic evolution of the coastal zone of the Restinga of Marambaia using multitemporal satellite images acquired by multisensors from 1975 to 2004. The images were digitally segmented by a region growth algorithm and submitted to an unsupervised classification procedure (ISOSEG) followed by a raster edit based on visual interpretation. The image time-series showed a general trend of decrease in the total sand bar area with values varying from 80.61km(2) in 1975 to 78.15km(2) in 2004. The total area calculation based on the 1975 and 1978 Landsat MSS data was shown to be super-estimated in relation to the Landsat TM, Landsat ETM+, and CBERS-2 CCD data. These differences can also be associated to the relatively poorer spatial resolution of the MSS data, nominally 79m, against the 20m of the CCD data and 30m of the TM and ETM+ data. For the estimates of the width in the central portion of the sand bar the variation was from 158m (1975) to 100m (2004). The formation of a spit in the northern region of the study area was visually observed. The area of the spit was estimated, with values varying from 0.82km(2) (1975) to 0.55km(2) (2004).
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HRSV is one of the most important pathogens causing acute respiratory tract diseases as bronchiolitis and pneumonia among infants. HRSV was isolated from two distinct communities, a public day care center and a public hospital in Sao Jose do Rio Preto - SP, Brazil. We obtained partial sequences from G gene that were used on phylogenetic and selection pressure analysis. HRSV accounted for 29% of respiratory infections in hospitalized children and 7.7% in day care center children. On phylogenetic analysis of 60 HRSV strains, 48 (80%) clustered within or adjacent to the GA1 genotype; GA5, NA1, NA2, BA-IV and SAB1 were also observed. SJRP GA1 strains presented variations among deduced amino acids composition and lost the potential O-glycosilation site at amino acid position 295, nevertheless this resulted in an insertion of two potential O-glycosilation sites at positions 296 and 297. Furthermore, a potential O-glycosilation site insertion, at position 293, was only observed for hospital strains. Using SLAC and MEME methods, only amino acid 274 was identified to be under positive selection. This is the first report on HRSV circulation and genotypes classification derived from a day care center community in Brazil.
Resumo:
BACKGROUND/OBJECTIVES: To assess the performance of a food frequency questionnaire (FFQ) for estimating omega-3, omega-6 and trans fatty acid intake during pregnancy. Moreover, we determined whether the fatty acid composition of mature breast milk represents a valuable biomarker for fatty acid intake during pregnancy. SUBJECTS/METHODS: A prospective study in 41 pregnant women, aged 18-35 years, was conducted. Food intake during pregnancy was evaluated by three 24-h recalls (24 hR), and 2 FFQ. The fatty acid composition of mature breast milk was determined by gas chromatography. The method of triads and joint classification between quartiles of intake were applied. RESULTS: The FFQ was accurate for estimating docosahexanoic (DHA), linoleic and total omega-6 fatty acids according to validity coefficients. Higher agreements (>70%) into the same or adjacent quartiles between the dietary methods were found for alpha-linolenic, total omega-3, linoleic and trans fatty acid intake. High validity coefficients for eicosapentanoic (EPA) and DHA acids of human milk were found (0.61 and 0.73, respectively), and the method was adequate for categorizing the intake of alpha-linolenic, total omega-3 and trans fatty acids compared with FFQ estimates, and for arachidonic acid and trans fatty acids compared with food recall estimates, during pregnancy. CONCLUSIONS: The FFQ was an accurate tool for categorizing alpha-linolenic, total omega-3 and trans fatty acid intake. According to the validity coefficients observed, the FFQ accurately estimated DHA, linoleic and total omega-6 fatty acids and the composition of mature breast milk was shown to be a suitable biomarker for EPA and DHA fatty acid intake during pregnancy.
Resumo:
Purpose: To evaluate the retinal nerve fiber layer measurements with time-domain (TD) and spectral-domain (SD) optical coherence tomography (OCT), and to test the diagnostic ability of both technologies in glaucomatous patients with asymmetric visual hemifield loss. Methods: 36 patients with primary open-angle glaucoma with visual field loss in one hemifield (affected) and absent loss in the other (non-affected), and 36 age-matched healthy controls had the study eye imaged with Stratus-OCT (Carl Zeiss Meditec Inc., Dublin, California, USA) and 3 D OCT-1000 (Topcon, Tokyo, Japan). Peripapillary retinal nerve fiber layer measurements and normative classification were recorded. Total deviation values were averaged in each hemifield (hemifield mean deviation) for each subject. Visual field and retinal nerve fiber layer "asymmetry indexes" were calculated as the ratio between affected versus non-affected hemifields and corresponding hemiretinas. Results: Retinal nerve fiber layer measurements in non-affected hemifields (mean [SD] 87.0 [17.1] mu m and 84.3 [20.2] mu m, for TD and SD-OCT, respectively) were thinner than in controls (119.0 [12.2] mu m and 117.0 [17.7] mu m, P<0.001). The optical coherence tomography normative database classified 42% and 67% of hemiretinas corresponding to non-affected hemifields as abnormal in TD and SD-OCT, respectively (P=0.01). Retinal nerve fiber layer measurements were consistently thicker with TD compared to SD-OCT. Retinal nerve fiber layer thickness asymmetry index was similar in TD (0.76 [0.17]) and SD-OCT (0.79 [0.12]) and significantly greater than the visual field asymmetry index (0.36 [0.20], P<0.001). Conclusions: Normal hemifields of glaucoma patients had thinner retinal nerve fiber layer than healthy eyes, as measured by TD and SD-OCT. Retinal nerve fiber layer measurements were thicker with TD than SD-OCT. SD-OCT detected abnormal retinal nerve fiber layer thickness more often than TD-OCT.
Resumo:
A computational pipeline combining texture analysis and pattern classification algorithms was developed for investigating associations between high-resolution MRI features and histological data. This methodology was tested in the study of dentate gyrus images of sclerotic hippocampi resected from refractory epilepsy patients. Images were acquired using a simple surface coil in a 3.0T MRI scanner. All specimens were subsequently submitted to histological semiquantitative evaluation. The computational pipeline was applied for classifying pixels according to: a) dentate gyrus histological parameters and b) patients' febrile or afebrile initial precipitating insult history. The pipeline results for febrile and afebrile patients achieved 70% classification accuracy, with 78% sensitivity and 80% specificity [area under the reader observer characteristics (ROC) curve: 0.89]. The analysis of the histological data alone was not sufficient to achieve significant power to separate febrile and afebrile groups. Interesting enough, the results from our approach did not show significant correlation with histological parameters (which per se were not enough to classify patient groups). These results showed the potential of adding computational texture analysis together with classification methods for detecting subtle MRI signal differences, a method sufficient to provide good clinical classification. A wide range of applications of this pipeline can also be used in other areas of medical imaging. Magn Reson Med, 2012. (c) 2012 Wiley Periodicals, Inc.
Resumo:
Objective: To evaluate serum concentrations of CA-125 and soluble CD-23 and to correlate them with clinical symptoms, localization and stage of pelvic endometriosis and histological classification of the disease. Methods: Blood samples were collected from 44 women with endometriosis and 58 without endometriosis, during the first three days (1st sample) and during the 7th, 8th and 9th day (2nd sample) of the menstrual cycle. Measurements of CA-125 and soluble CD-23 were performed by ELISA. Mann-Whitney U test was used for age, pain evaluations (visual analog scale) and biomarkers concentrations. Results: Serum levels Of CA-125 were higher in endometriosis patients when compared to the control group during both periods of the menstrual cycle evaluated in the study. This marker was also elevated in women with chronic pelvic pain, deep dyspareunia (2nd sample), dysmenorrhea (both samples) and painful defecation during the menstrual flow (2nd sample). CA-125 concentration was higher in advanced stages of the disease in both samples and also in women with ovarian endometrioma. Concerning CD-23, no statistically significant differences were observed between groups. Conclusion: The concentrations of CA-125 were higher in patients with endometriosis than in patients without the disease. No significantly differences were observed for soluble CD-23 levels between groups.
Resumo:
Objective. The aim of this study was to evaluate the need for antibiotic prescription in third molar surgery. Study design. A double-blind randomized study was carried out with 71 patients from CODONT (Dentistry Center of the Police of Sao Paulo). Amoxicillin, clindamycin, or no medication was administered for 7 days immediately after surgery. The participants evaluated the presence of pain, edema, interincisal distance (ID), presence of infection, Pell and Gregory classification, rescue analgesia, osteotomy, and odontosection. Results. There was no difference (P < .05) between antibiotics and control over the surgery duration, dose, visual analog scale (VAS), ID, and edema, yet significant differences were seen over time for VAS, edema, and ID. Conclusions. Antibiotic prescription should not be indicated in all clinical conditions, yet it is necessary to correctly evaluate factors such as systemic condition of the patient, skill of the operator, and contamination of the surgical environment. (Oral Surg Oral Med Oral Pathol Oral Radiol 2012; 114(suppl 5):S26-S31)
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This study aimed to investigate the relationships between the constructs subjective well-being (SWB), dyadic adjustment (DA) and marital satisfaction (MS). Participants were 106 married Brazilians, of both sexes, with a mean age of 42 (+/- 11) years. Instruments used for the sociodemographic characterization and socioeconomic classification were the Subjective Wellbeing Scale (SWBS), the Dyadic Adjustment Scale (DAS) and the Marital Satisfaction Scale (MSS). Through the analysis of correlations and of stepwise multiple regression, it was verified that all the factors of the dyadic adjustment showed correlation with the marital satisfaction. The satisfaction with life (factor of the SWBS) and dyadic satisfaction (factor of the DAS), were positively and significantly correlated (r = .20; p = .04), which reveals that people who say they are satisfied with life in different domains also do so in relation to the marital experience.
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Abstract Background Banana cultivars are mostly derived from hybridization between wild diploid subspecies of Musa acuminata (A genome) and M. balbisiana (B genome), and they exhibit various levels of ploidy and genomic constitution. The Embrapa ex situ Musa collection contains over 220 accessions, of which only a few have been genetically characterized. Knowledge regarding the genetic relationships and diversity between modern cultivars and wild relatives would assist in conservation and breeding strategies. Our objectives were to determine the genomic constitution based on Internal Transcribed Spacer (ITS) regions polymorphism and the ploidy of all accessions by flow cytometry and to investigate the population structure of the collection using Simple Sequence Repeat (SSR) loci as co-dominant markers based on Structure software, not previously performed in Musa. Results From the 221 accessions analyzed by flow cytometry, the correct ploidy was confirmed or established for 212 (95.9%), whereas digestion of the ITS region confirmed the genomic constitution of 209 (94.6%). Neighbor-joining clustering analysis derived from SSR binary data allowed the detection of two major groups, essentially distinguished by the presence or absence of the B genome, while subgroups were formed according to the genomic composition and commercial classification. The co-dominant nature of SSR was explored to analyze the structure of the population based on a Bayesian approach, detecting 21 subpopulations. Most of the subpopulations were in agreement with the clustering analysis. Conclusions The data generated by flow cytometry, ITS and SSR supported the hypothesis about the occurrence of homeologue recombination between A and B genomes, leading to discrepancies in the number of sets or portions from each parental genome. These phenomenons have been largely disregarded in the evolution of banana, as the “single-step domestication” hypothesis had long predominated. These findings will have an impact in future breeding approaches. Structure analysis enabled the efficient detection of ancestry of recently developed tetraploid hybrids by breeding programs, and for some triploids. However, for the main commercial subgroups, Structure appeared to be less efficient to detect the ancestry in diploid groups, possibly due to sampling restrictions. The possibility of inferring the membership among accessions to correct the effects of genetic structure opens possibilities for its use in marker-assisted selection by association mapping.
Resumo:
Personalized treatments have become a primary goal in translational psychiatric research. They include the identification of neural circuits associated with psychiatric disorders and definition of treatment according to individual characteristics. Many new tools and technologies have been developed but further efforts are required to provide clues on how these scientific advances in psychiatry may be translated into more effective therapeutic approaches. Obstacles to the progress of translational psychiatry also involve numerous scientific, financial, ethical, logistics and regulatory aspects. Also, the goal of DSM-5 to expand “signs and symptoms” classification to incorporate biological measures may help the development of new multifactorial and dimensional models able to better understand the pathophysiology of psychiatric disorders and develop improved treatments. Finally, a better understanding on the significant response variability, cognitive functioning, role of comorbidities and treatment-resistant cases are critical for the development of prevention and intervention strategies that are more effective.
Resumo:
This report aims at giving a general overview on the classification of the maximal subgroups of compact Lie groups (not necessarily connected). In the first part, it is shown that these fall naturally into three types: (1) those of trivial type, which are simply defined as inverse images of maximal subgroups of the corresponding component group under the canonical projection and whose classification constitutes a problem in finite group theory, (2) those of normal type, whose connected one-component is a normal subgroup, and (3) those of normalizer type, which are the normalizers of their own connected one-component. It is also shown how to reduce the classification of maximal subgroups of the last two types to: (2) the classification of the finite maximal Sigma-invariant subgroups of centerfree connected compact simple Lie groups and (3) the classification of the Sigma-primitive subalgebras of compact simple Lie algebras, where Sigma is a subgroup of the corresponding outer automorphism group. In the second part, we explicitly compute the normalizers of the primitive subalgebras of the compact classical Lie algebras (in the corresponding classical groups), thus arriving at the complete classification of all (non-discrete) maximal subgroups of the compact classical Lie groups.
Resumo:
Quality of fresh-cut carambola (Averrhoa carambola L) is related to many chemical and biochemical variables especially those involved with softening and browning, both influenced by storage temperature. To study these effects, a multivariate analysis was used to evaluate slices packaged in vacuum-sealed polyolefin bags, and stored at 2.5 degrees C, 5 degrees C and 10 degrees C, for up to 16 d. The quality of slices at each temperature was correlated with the duration of storage, O(2) and CO(2) concentration in the package, physical chemical constituents, and activity of enzymes involved in softening (PG) and browning (PPO) metabolism. Three quality groups were identified by hierarchical cluster analysis, and the classification of the components within each of these groups was obtained from a principal component analysis (PCA). The characterization of samples by PCA clearly distinguished acceptable and non-acceptable slices. According to PCA, acceptable slices presented higher ascorbic acid content, greater hue angles ((o)h) and final lightness (L-5) in the first principal component (PC1). On the other hand, non-acceptable slices presented higher total pectin content. PPO activity in the PC1. Non-acceptable slices also presented higher soluble pectin content, increased pectin solubilisation and higher CO(2) concentration in the second principal component (PC2) whereas acceptable slices showed lower total sugar content. The hierarchical cluster and PCA analyses were useful for discriminating the quality of slices stored at different temperatures. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
We study orthogonal projections of generic embedded hypersurfaces in 'R POT.4' with boundary to 2-spaces. Therefore, we classify simple map germs from 'R POT.3' to the plane of codimension less than or equal to 4 with the source containing a distinguished plane which is preserved by coordinate changes. We also go into some detail on their geometrical properties in order to recognize the cases of codimension less than or equal to 1.
Resumo:
Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) semi-supervised classification model is proposed. It employs a combined random-greedy walk of particles, with competition and cooperation mechanisms, to propagate class labels to the whole network. Due to the competition mechanism, the proposed model has a local label spreading fashion, i.e., each particle only visits a portion of nodes potentially belonging to it, while it is not allowed to visit those nodes definitely occupied by particles of other classes. In this way, a "divide-and-conquer" effect is naturally embedded in the model. As a result, the proposed model can achieve a good classification rate while exhibiting low computational complexity order in comparison to other network-based semi-supervised algorithms. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.
Resumo:
Semi-supervised learning is a classification paradigm in which just a few labeled instances are available for the training process. To overcome this small amount of initial label information, the information provided by the unlabeled instances is also considered. In this paper, we propose a nature-inspired semi-supervised learning technique based on attraction forces. Instances are represented as points in a k-dimensional space, and the movement of data points is modeled as a dynamical system. As the system runs, data items with the same label cooperate with each other, and data items with different labels compete among them to attract unlabeled points by applying a specific force function. In this way, all unlabeled data items can be classified when the system reaches its stable state. Stability analysis for the proposed dynamical system is performed and some heuristics are proposed for parameter setting. Simulation results show that the proposed technique achieves good classification results on artificial data sets and is comparable to well-known semi-supervised techniques using benchmark data sets.