Navegando por Palavras-chave "PCA"

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    Avaliação de uma nova metodologia para segmentação de imagens micro-FTIR utilizando PCA e k-means
    (Universidade Federal de São Paulo, 2021-02-25) Augusto, Bruno do Amarante [UNIFESP]; Pereira, Thiago Martini [UNIFESP]; http://lattes.cnpq.br/3291751276972553
    Os exames de imagens são procedimentos essenciais para a saúde. Por meio deles, de acordo com a interação do elemento biológico com a onda eletromagnética incidente, é possível obter diagnósticos mais rápidos, precisos e seguros. No diagnóstico do câncer, os exames de espectroscopia em infravermelho ajudam a diferenciar os tecidos saudáveis dos tecidos patológicos, identificando também a natureza do tumor e a sua gravidade. No entanto, a quantidade de dados gerados por esses procedimentos é alta e, portanto, leva tempo e exige uma alta capacidade de processamento computacional. Um dos caminhos para otimizar essa análise é melhorar a etapa de pré-processamento, filtrando as informações importantes e eliminando os dados repetitivos e não relevantes. Assim, o trabalho proposto tem como objetivo otimizar a etapa de pré-processamento de imagens micro-FTIR no contexto do diagnóstico de câncer, avaliando o ganho computacional do processo de clusterização k-means por meio da Análise de Componentes Principais (PCA).
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    Green Coffea arabica L. seed oil influences the stability and protective effects of topical formulations
    (Elsevier B.V., 2015-01-01) Wagemaker, Tais A. L.; Silva, Silas A. M. [UNIFESP]; Leonardi, Gislaine R. [UNIFESP]; Maia Campos, Patricia M. B. G.; Universidade de São Paulo (USP); Universidade Federal de São Paulo (UNIFESP)
    Green Coffea arabica L. seed oil (GCO) has been used as an active ingredient in many skin care products, due to its properties as an emollient, improver of skin hydration and absorbent of UVB radiation. However, to obtain a stable, effective and pleasant formulation containing variable amounts of GCO it is necessary to know specific chemical characteristics of the combined ingredients. Thus, this study evaluated rheological behavior, presence of liquid crystals (LCs) and skin protective effects of GCO-containing formulations aiming to correlate these parameters with GCO concentrations by using a principal component analysis (PCA). Formulations containing GCO or not (0-15%) were submitted to physical stability assays by determinations of rheological behavior after 90 days storage, detection of LCs by polarized light microscopy and in vitro determination of the sun protection factor (SPF). in vivo protective effects in mice were evaluated with biophysical techniques and histological analysis. Data were correlated using PCA. Despite the low SPF values, GCO addition to formulations resulted in significant and proportional increases of these values. It is concluded that formulation stability and skin protective properties are influenced by GCO but desirable effects are only possible when GCO is present in high concentrations. (C) 2014 Elsevier B.V. All rights reserved.
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    PCA statistical method for classification of sensors
    (Universidade Federal de São Paulo, 2022-11-25) Paula, Jessica Fernandes de [UNIFESP]; Antonelli, Eduardo [UNIFESP]; http://lattes.cnpq.br/8535325155568005; http://lattes.cnpq.br/9339565565705439
    A large number of the global population suffers from infectious diseases, so studies in the health area aimed at identifying these diseases are of great importance. Some diseases have a long immunological window, where antibodies take a long time to be identified. Rapid detection tests are essential for disease control and eradication. A possible identification and classification method uses the statistical analysis performed by the Principal Component Analysis (PCA), through which we can reduce the number of variables and identify the presence of these antibodies. This work aims to classify immunosensors according to the antibody detected, analyzing their responses in relation to impedance and frequency using the PCA statistical method. The study was based on data collected from two immunosensors, HCV sensor and HIV sensor (Hepatitis C virus and Human Immunodeficiency Virus), analyzing their response as a function of frequency. For the PCA statistical method, an interactive laboratory was adopted with Jupyter Notebook, Python, using libraries known as Pandas, Plotly, NumPyand Scikit-learn. This study analyzed several data and variables from the dataset of both sensors to build models with the PCA statistical method, it was possible to separate and classify the HIV and HCV sensors at specific frequencies. The PCA analysis results for the selected datasets showed a relevant classification using PC1 and PC2, with a variance of the original data above 90%.
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    Perfil químico dos óleos voláteis de indivíduos jovens de Nectandra megapotamica (Spreng.) Mez (Lauraceae) sob déficit hídrico 2018
    (Universidade Federal de São Paulo, 2018-11-23) Santos, Valdilene Maria dos [UNIFESP]; Lago, João Henrique Ghilardi [UNIFESP]; Universidade Federal de São Paulo (UNIFESP)
    In this work the chemical composition of the volatile oils of the leaves of young individuals of Nectandra megapotamica under normal conditions of cultivation and under water deficit was carried out under three conditions: plants irrigated every two days (group I), every seven (group II) and every 15 days (group III). The study was conducted during 60 days in greenhouse, with biweekly collections, being repeated in three distinct periods, covering the four seasons of 2017 (summer/autumm, autumn/winter and spring). The qualitative and quantitative analysis of the constituents present in the volatile oils was performed using gas chromatography with flame ionization detector (GC/FID) and gas chromatography coupled to mass spectrometry (GC/ MS). 25 Compounds were identified, four monoterpenes (Δ 3 -carene, o-cymene, d-limonene and bornila acetate), eighteen sesquiterpenes (δ-elemene, α-copaene, βelemene, Z-α-bergamotene, β-caryophyllene, α-humulene, alloaromadendrene , germacrene D, δ-selinene, β-bisabolene, α-bisabolene, α-elemol, E-nerolidol, espatulenol, globulol, rosifoliol, alismol and α-bisabolol), as well as two diterpenes (caurene and E-phytol) and one phenylpropanoid (E-asarone). The summer/autumm and fall-winter experiments responded more strongly to the water deficits imposed, especially autumn-winter, in which the lowest water potential (-1.0 MPa) was observed. The contents of the constituents of the volatile oils of N. megapotamica underwent quantitative/qualitative variation throughout the experiment, being the most intense observed for the summer/autumm and fall-winter. The reductions in the relative proportions of the constituents were more evident for the oxygenated sesquiterpenes, especially for the plants with greater water restriction (group III). In addition, a systematic study was carried out throughout the year 2017, covering the summer/fall, autumn/winter and spring seasons, where relative variations of the constituents present in N. megapotamica volatile oils were observed. water deficiency treatments imposed. In order to understand which constituents had similarities and / or differences among them as a result of the treatments, principal component analyzes (PCA) were performed. It was possible to establish some relationships such as, in the summer/autumm experiment the α-bisabolol oxygen sesquiterpene was related to samples with higher water availability, whereas germacrene D was more relevant in samples with low water availability. Physiological analyzes (water potential, relative water content and growth rate) were also carried out to verify if the plants were responding to the treatments. In view of the obtained results, it can be suggested that the controlled conditions can be an alternative to select substances with biological activity of interest and commercially aggregated value, thus allowing the choice of Keywords: PCA, GC-FID, GC-MS, Water deficit, N. megapotamica, volatile oils, chemical composition. a better period to obtain them.