907 resultados para P-scale
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Prostate cancer is a serious public health problem accounting for up to 30% of clinical tumors in men. The diagnosis of this disease is made with clinical, laboratorial and radiological exams, which may indicate the need for transrectal biopsy. Prostate biopsies are discerningly evaluated by pathologists in an attempt to determine the most appropriate conduct. This paper presents a set of techniques for identifying and quantifying regions of interest in prostatic images. Analyses were performed using multi-scale lacunarity and distinct classification methods: decision tree, support vector machine and polynomial classifier. The performance evaluation measures were based on area under the receiver operating characteristic curve (AUC). The most appropriate region for distinguishing the different tissues (normal, hyperplastic and neoplasic) was defined: the corresponding lacunarity values and a rule's model were obtained considering combinations commonly explored by specialists in clinical practice. The best discriminative values (AUC) were 0.906, 0.891 and 0.859 between neoplasic versus normal, neoplasic versus hyperplastic and hyperplastic versus normal groups, respectively. The proposed protocol offers the advantage of making the findings comprehensible to pathologists. (C) 2014 Elsevier Ltd. All rights reserved.
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The first search at the LHC for the extinction of QCD jet production is presented, using data collected with the CMS detector corresponding to an integrated luminosity of 10.7 fb-1 of proton-proton collisions at a center-of-mass energy of 8 TeV. The extinction model studied in this analysis is motivated by the search for signatures of strong gravity at the TeV scale (terascale gravity) and assumes the existence of string couplings in the strong-coupling limit. In this limit, the string model predicts the suppression of all high-transverse-momentum standard model processes, including jet production, beyond a certain energy scale. To test this prediction, the measured transverse-momentum spectrum is compared to the theoretical prediction of the standard model. No significant deficit of events is found at high transverse momentum. A 95% confidence level lower limit of 3.3 TeV is set on the extinction mass scale.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The best irrigation management depends on accurate estimation of reference evapotranspiration (ET0) and then selection of the appropriate crop coefficient for each phenological stage. However, the evaluation of water productivity on a large scale can be done by using actual evapotranspiration (ETa), determined by coupling agrometeorological and remote sensing data. This paper describes methodologies used for estimating ETa for 20 centerpivots using three different approaches: the traditional FAO crop coefficient (K-c) method and two remote sensing algorithms, one called SEBAL and other named TEIXEIRA. The methods were applied to one Landsat 5 Thematic Mapper image acquired in July 2010 over the Northwest portion of the Sao Paulo State, Brazil. The corn, bean and sugar cane crops are grown under center pivot sprinkler irrigation. ET0 was calculated by the Penman-Monteith method with data from one automated weather station close to the study site. The results showed that for the crops at effective full cover, SEBAL and TEIXEIRA's methods agreed well comparing with the traditional method. However, both remote sensing methods overestimated ETa according to the degree of exposed soil, with the TEIXEIRA method presenting closer ETa values with those resulted from the traditional FAO K-c method. This study showed that remote sensing algorithms can be useful tools for monitoring and establishing realistic K-c values to further determine ETa on a large scale. However, several images during the growing seasons must be used to establish the necessary adjustments to the traditional FAO crop coefficient method.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The head is the most important and specialized region in the body because it contains a range of specialized organs and, because it has interconnections between specialized organs, there is a great overlap of images. Thus, computed tomography (CT) helps in diagnosing diseases in this region, such as oral conditions, as they provide millimetric slices or cuts and demonstrate the relationship between the various anatomical structures involved, in volume and depth. Within dentistry, CT helps in the identification of pathological processes such as infection, tumors, visualization of embedded teeth and bone bed. This study aimed to assess the density of the mandibular alveolar bone at a determined point to later predict how periodontal disease is involved in bone resorption. For this, we performed a blind retrospective study (n = 124) of the CT scan files of dog skulls at FMVZ-UNESP in order to determine the density of the jaw bone using a Hounsfield scale, in the region of the dental apex of the cranial root of the first molar tooth in dogs. The results obtained were evaluated using mean and standard deviation (27.28 +/- 9.53 HU) in order to predict the normal density of the mandibular alveolar bone in the studied region. Thus, this data analysis allows a more concise evaluation of bone resorption of mandibular alveolar bone and, therefore, provides an adequate surgical planning in cases of osteosynthesis given mainly by the presence of installed periodontal disease.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Aim: To estimate the reliability and validity of the Dental Anxiety Scale (DAS) and identify the prevalence and the effect of the socio-demographic characteristics of dental anxiety, in a sample of 212 adults. Methods: The psychometric sensitivity of the scale was assessed. A confirmatory factor analysis was performed, and the convergent validity and internal consistency were determined. The prevalence of anxiety was estimated, and the effect of socio-demographic variables on anxiety was assessed using structural equation modelling. Results: The participants’ mean age was 33.5 (SD = 15.6) years, and 62.3% were female. There was an adequate factorial adjustment of the scale in this sample. The convergent validity and internal consistency were adequate in the one-factor model. Regarding two-factor model, there was a high correlation (r) among the factors, which jeopardized the discriminant validity. A total of 47.6% of the participants (IC95% = 40.9 - 54.4) presented low levels of anxiety, 32.5% (IC95% = 26.2 - 38.9) moderate levels, and 12.3% (IC95% = 7.8 - 16.7) exacerbated levels. There was a non-significant effect of gender, age and education on the anxiety levels of this sample. Conclusion: We concluded that the one-factor model presented better psychometric qualities, that anxiety was highly prevalent and there was no significant effect of the demographic variables on anxiety, in this sample
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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)