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Fitorremediação por plantas do genêro Brassica a partir do uso de fitorreguladores
(Universidade Federal de São Carlos, 2021-05-13) Silva, Mayra Dhaiane Cabral; Baron, Daniel; https://lattes.cnpq.br/2054014705484176; https://lattes.cnpq.br/3084126825868267
Contamination of the soil by heavy metals has become a global environmental problem aggravated by increased anthropic activities. The accumulation of heavy metals in cultivation environments becomes increasingly frequent and worrying, as these are highly toxic in the soil-plant-atmosphere system. The decontamination of heavy metals from the soil can be carried out through phytoremediation, a promising strategy to 'clean' the soil, through the use of vegetables. For the applicability of phytoremediation, the choice of the 'ideal plant' should take into account the plant species that has rapid growth, high biomass accumulation, and deep roots in its plant tissue. Plant species belonging to the botanical family Brassicaceae, specifically belonging to the botanical genus Brassica, are described in the literature with phytoremediator potential for tolerating excess heavy metals, from the increase in enzymatic activity, total amino acids, production of osmoprotectants, metal quelatization. Although the literature indicates that 'brassicas' can accumulate and tolerate excess metals in their aerial part, plant growth and development may suffer reductions and adverse effects. Although, the adoption of sustainable methodologies to circumvent phytotoxicity, for example, the use of phytoregulators, becomes a potential candidate to stimulate the absorption of pollutants and their tolerance. One of the phytoregulators, widely studied, are brassinosteroids (BRs), which can relieve oxidative stress and increase the antioxidant defense system of plants under stress. Based on the hypothesis about the effect of the phytoregulator 24-Epibrassinolide (EBL) on the primary metabolism of vegetables belonging to the botanical genus Brassica, the objective of this work was to compile published information on the phytoremediator potential of heavy metals by 'brássicas', adopting applied methodology with the critical reading of recent publications, performing the screening of abstracts. The exogenous application of EBL will prevent damage to the metabolism of phytoremediation brássic species of heavy metals. However, studies are needed to elucidate gene editing in the improvement of the phytoremediator potential. Given the restrictive measures imposed by the COVID-19 pandemic, which suspended face-to-face activities on the Lagoa do Sino campus and on other University campuses, the present course conclusion paper is written in the form of a bibliographic review article for future submission in a scientific journal with high impact factor.
Análise da influência do uso de telas no cultivo de uvas da espécie “Benitaka” (Vitis vinífera) no município de Capão Bonito – SP
(Universidade Federal de São Carlos, 2021-05-13) Bernardo, Taynara Aparecida; Yamamoto, Robson Ryu; https://lattes.cnpq.br/2781829944725891; Gazzola, Jonathan; https://lattes.cnpq.br/0159433721761670; https://lattes.cnpq.br/7680213213000531
The objective of this study was to evaluate the influence of microclimatic changes, through the use of different shading screens colors on the vegetative and productive response under the climatic conditions of the city of Capão Bonito - SP. Benitaka vineyards (Vitis vinifera) of the area in full sun (without coverage) and covered with shading screens in red, black and aluminized colors were used. The analysis was separated in two moments: microclimate analysis and plant analysis. For the analysis of the microclimate effect, the multiparameter equipment was used to take measurements of light, air temperature and relative humidity, where the sensors were positioned above the usable vine and below the metalic structure during the period from 12h to 13h. For the plant analysis, the leaves of the vines and the quality of the fruit were analyzed. For the leaf analysis, the software ImageJ® was used to obtain data on leaf length and leaf area. In order to analyze the fruit harvested four bunches of grapes in the different treatments according to their maturity, these were weighed using a digital scale in order to obtain the weight of clusters, using a ruler and a plate with a white background took the measurements of width and height of the clusters. For the analysis of the sugar content used a reflatometer, selected from the bunches of grapes three berries from different locations being, top, middle and bottom, being macerated to obtain the liquid that determines the content of soluble solids. It was analyzed that the screens showed significant interference in modifying the microclimate under the screens and in the productivity of the crop. In relation to the microclimate, the luminousity variable showed better results under the control screen compared to the shading screens, and in comparison between the screens, the red colored screen showed better results. The air temperature showed higher values under the red fabric compared to the control and other fabrics, showing that it can be used in periods of mild air temperature, preventing frost loss. Another factor, relative humidity, knowing that mildew is the main fungal disease of the grapevine and its propagation occurs in environments with high relative humidity and air temperature, it was observed that the red cloth showed lower values compared to the other screens. The production and quality of the grapevine were measured by the variables soluble solids content (brix), bunch weight (g), production per plant (g), number of bunches, height and width of bunches, where the red shade cloth stood out in relation to sugar content and production per plant; the black shade cloth in the weight and height of the bunch, the aluminized screen in relation to the width of the bunch and the open air screen in the number of bunches.
Gerenciamento da qualidade da energia elétrica em smart grids baseado em técnicas de soft computing
(Universidade Federal de São Carlos, 2021-05-13) Moraes, Anderson Luis de; Fernandes, Ricardo Augusto Souza; https://lattes.cnpq.br/0880243208789454; https://lattes.cnpq.br/3469531495595424
The increasing use of nonlinear loads (mainly those based on power electronics), the integration of renewable sources (such as wind and photovoltaic), atmospheric discharges, starting of motors and driving large load blocks generate disturbances that affect the Power Quality, i.e., the energy delivered to consumers. In the Smart Grids context, the distribution utilities seek ways to monitor the Power Quality, so that disturbances can be detected by smart meters and the resulting data should be compressed to ensure an efficient exchange of data packets. In this sense, it is expected that, after unpacking the data, the signals will be recovered with few information losses and can be classified to assist in the utilities’ decision making. Therefore, this work proposes a framework based on the edge and cloud computing technologies, where the processes of detection/segmentation, compression and classification of power quality disturbances will be properly performed. To analyze the performance of this framework, a synthetic database with 15 disturbance classes (simple and combined) was generated. Thus, detection of disturbances was performed by a Decision Tree capable of identifying 94.71% of the disturbance windows. Next, the disturbances detected were submitted to a treatment stage in order to guarantee a more efficient segmentation of the signals. The resulting windows of disturbances were then compressed using a Wavelet Transform, considering filters from the Daubechies family, in which it was possible to reduce the data packets to a compression rate greater than 3.6. Through data unpacking, a low information loss was observed. Finally, there was a transformation of the temporal signals in Recurrence Plots, Gramian Angular Summation Field and Gramian Angular Difference Field in order to identify the voltage signal patterns through a set of Convolutional Neural Networks. In this context, the proposed approach allows to obtain an average accuracy above 94%. Thus, the results of this research will contribute to advance the state-of-the-art in Power Quality automatic signal processing.
Influência da obesidade sobre as morfologias de onda da pressão intracraniana e cerebral: um estudo prospectivo
(Universidade Federal de São Carlos, 2021-05-13) Marine, Diego Adorna; Duarte, Ana Cláudia Garcia de Oliveira; https://lattes.cnpq.br/1996950253264696; https://lattes.cnpq.br/2675179641148838
Introduction: Obesity is a low-grade inflammatory disease, which can lead to the development of other pathologies, such as diabetes mellitus, dyslipidemias and arterial hypertension (AH). Compare the relationship between blood pressure (BP) and intracranial pressure (ICP), given by the cerebral perfusion pressure, AH can cause an increase in ICP. The increase in ICP is related to stroke, migraines, ocular hypertension, among other pathologies. Thus, the aim of this study was to analyze the behavior of the ICP wave morphology in the face of obesity, to analyze the non-invasive form and to prospect for information about AH, ICP, inflammatory and metabolic aspects, and cerebral morphology in Wistar rats. Materials and methods: Two parallel studies were carried out, with a 24-week treatment of a high-fat diet, to induce obesity, after a previous adaptation of 60 days, with a standard diet. In study 1, 16 rats were divided into the Obese (OB, n = 9) and Non-Obese (NOB, n = 7) groups. All animals were adopted every 4 weeks, being: Fat percentage (% g), Body mass (BM), Fat free mass (FFM), Bone mineral content (BMC), BP, Heart rate (HR) and ICP. In study 2, 61 animals were divided into the groups, high-fat diet (HFD) and chow diet (CD) and subdivided by weeks in which they were sacrificed, over the 24 weeks (W0, W8, W16, W24). Group OB and W-HFD were fed with HFD and NOB and W-CD with CD. The evaluations of the non-invasive variables were carried out in study 2 every 8 weeks, and part of the animals being sacrificed. Also extracted were: brain weight, brain lipid content, number of cells in the primary motor area (M1), the thickness of the gray matter in this area, in addition to blood glucose, lipid profile, and inflammatory profile. Euthanasia took place every 8 weeks in study 2, and in study 1 at the end of 24 weeks. Results: Study 1 statistical difference in the area under the ICP curve, between OB and NOB, with a reduction in the NOB group, remaining below OB during treatment. In study 2, there was no difference between the groups, only was a probability of an increase in the W24-HFD group. Regarding BP, no statistical difference was found in both studies. However, HR was statistically different in study 1, being higher in OB, and the probability of increase in study 2. BM,%fat, FFM, and BMC were higher in the OB and W24-HFD groups, compared to the control. There is no difference in brain lipid content or relative brain weight at the end of treatment. There was a probability of a decrease in brain weight in the HFD groups, and also a decrease in the total number of M1 cells, in addition to an increase in the thickness of the gray matter of this same area in the HFD group. Discovery of decreased brain-derived neurotrophic factor (BDNF), and increased leptin at the end of treatment in the W24-HFD group. Conclusion: The HFD developed obesity in rats, but did not promote dyslipidemia or chronic inflammation. The increase in blood glucose in the OB group demonstrates possible insulin resistance. Variations in ICP are due to the better cerebral compliance of the NOB group. An increased likelihood of leptin, gray matter thickness, loss of cell number and reduction of circulating BDNF levels may indicate loss of neural plasticity, glial cells, and increased fluid in the brain parenchyma. This scenario may be the beginning of a greater damage to the brain, potentially leading to an increase in the PIC.
Método Zero-Variance para Monte Carlo Hamiltoniano aplicado a modelos GARCH univariados e multivariados
(Universidade Federal de São Carlos, 2021-05-13) Paixão, Rafael Soares; Ehlers, Ricardo Sandes; https://lattes.cnpq.br/4020997206928882; https://lattes.cnpq.br/6477788005623690
This PhD work develops, compares and applies Monte Carlo Markov Chains (MCMC) methods for parameter estimation in univariate and multivariate GJR-GARCH models. Specifically, the following problems are addressed: (i) conception of a purely bayesian estimation approach; (ii) development of a bayesian method for higher computational efficiency in parameter estimation; and (iii) flexible selection of residual probability distributions for GJR-GARCH models. As a result from the investigations of the aforementioned problems, this work presents four contributions. The first corresponds to a bayesian inference approach for univariate and multivariate GJR-GARCH models. The second consists of studying three residual probability distributions, one of which having been inovatively employed for multivariate cases. The third combines two techniques, namely the Hamiltonian Monte Carlo (HMC) algorithm and the Zero-Variance method, to allow parameter estimation in GJR-GARCH models with higher estimator efficiency, as well as higher computational performance. Finally, the fourth presents results from simulation studies and an application over real-world data, in the context of worldwide stock market indexes, show that the proposed contributions solve the addressed problems effective and efficiently, advancing the state of the art of univariate and multivariate GARCH models.