998 resultados para RNA quality


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A presente dissertação apresenta o estudo de previsão do diagrama de carga de subestações da Rede Elétrica Nacional (REN) utilizando redes neuronais, com o intuito de verificar a viabilidade do método utilizado, em estudos futuros. Atualmente, a energia elétrica é um bem essencial e desempenha um papel fundamental, tanto a nível económico do país, como a nível de conforto e satisfação individual. Com o desenvolvimento do setor elétrico e o aumento dos produtores torna-se importante a realização da previsão de diagramas de carga, contribuindo para a eficiência das empresas. Esta dissertação tem como objetivo a utilização do modelo das redes neuronais artificiais (RNA) para criar uma rede capaz de realizar a previsão de diagramas de carga, com a finalidade de oferecer a possibilidade de redução de custos e gastos, e a melhoria de qualidade e fiabilidade. Ao longo do trabalho são utilizados dados da carga (em MW), obtidos da REN, da subestação da Prelada e dados como a temperatura, humidade, vento e luminosidade, entre outros. Os dados foram devidamente tratados com a ajuda do software Excel. Com o software MATLAB são realizados treinos com redes neuronais, através da ferramenta Neural Network Fitting Tool, com o objetivo de obter uma rede que forneça os melhores resultados e posteriormente utiliza-la na previsão de novos dados. No processo de previsão, utilizando dados reais das subestações da Prelada e Ermesinde referentes a Março de 2015, comprova-se que com a utilização de RNA é possível obter dados de previsão credíveis, apesar de não ser uma previsão exata. Deste modo, no que diz respeito à previsão de diagramas de carga, as RNA são um bom método a utilizar, uma vez que fornecem, à parte interessada, uma boa previsão do consumo e comportamento das cargas elétricas. Com a finalização deste estudo os resultados obtidos são no mínimo satisfatórios. Consegue-se alcançar através das RNA resultados próximos aos valores que eram esperados, embora não exatamente iguais devido à existência de uma margem de erro na aprendizagem da rede neuronal.

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INTRODUCTION: Prolonged survival of patients under HAART has resulted in new demands for assisted reproductive technologies. HIV serodiscordant couples wish to make use of assisted reproduction techniques in order to avoid viral transmission to the partner or to the newborn. It is therefore essential to test the effectiveness of techniques aimed at reducing HIV and HCV loads in infected semen using molecular biology tests. METHODS: After seminal analysis, semen samples from 20 coinfected patients were submitted to cell fractioning and isolation of motile spermatozoa by density gradient centrifugation and swim-up. HIV and HCV RNA detection tests were performed with RNA obtained from sperm, seminal plasma and total semen. RESULTS: In pre-washing semen, HIV RNA was detected in 100% of total semen samples, whereas HCV RNA was concomitantly amplified in only one specimen. Neither HIV nor HCV were detected either in the swim-up or in the post-washing semen fractions. CONCLUSIONS: Reduction of HIV and/or HCV shedding in semen by density gradient centrifugation followed by swim-up is an efficient method. These findings lead us to believe that, although semen is rarely found to contain HCV, semen processing is highly beneficial for HIV/HCV coinfected individuals.

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Trypanosoma rangeli is non pathogenic for humans but of important medical and epidemiological interest because it shares vertebrate hosts, insect vectors, reservoirs and geographic areas with T. cruzi, the etiological agent of Chagas disease. Therefore, in this work, we set up two PCR reactions, TcH2AF/R and TrFR2, to distinguish T. cruzi from T. rangeli in mixed infections of vectors based on amplification of the histone H2A/SIRE and the small nucleolar RNA Cl1 genes, respectively. Both PCRs were able to appropriately detect all T. cruzi or T. rangeli experimentally infected-triatomines, as well as the S35/S36 PCR which amplifies the variable region of minicircle kDNA of T. cruzi. In mixed infections, whereas T. cruzi DNA was amplified in 100% of samples with TcH2AF/R and S35/S36 PCRs, T. rangeli was detected in 71% with TrF/R2 and in 6% with S35/S36. In a group of Rhodnius colombiensis collected from Coyaima (Colombia), T. cruzi was identified in 100% with both PCRs and T. rangeli in 14% with TrF/R2 and 10% with S35/S36 PCR. These results show that TcH2AF/R and TrF/R2 PCRs which are capable of recognizing all T. cruzi and T. rangeli strains and lineages could be useful for diagnosis as well as for epidemiological field studies of T. cruzi and T. rangeli vector infections.

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Presented at INForum - Simpósio de Informática (INFORUM 2015). 7 to 8, Sep, 2015. Covilhã, Portugal.

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An "in-house" RT-PCR method was developed that allows the simultaneous detection of the RNA of the Hepatitis C Virus (HCV) and an artificial RNA employed as an external control. Samples were analyzed in pools of 6-12 donations, each donation included in two pools, one horizontal and one vertical, permitting the immediate identification of a reactive donation, obviating the need for pool dismembering. The whole process took 6-8 hours per day and results were issued in parallel to serology. The method was shown to detect all six HCV genotypes and a sensitivity of 500 IU/mL was achieved (95% hit rate). Until July 2005, 139,678 donations were tested and 315 (0.23%) were found reactive for HCV-RNA. Except for five false-positives, all 310 presented the corresponding antibody as well, so the yield of NAT-only donations was zero, presenting a specificity of 99.83%. Detection of a window period donation, in the population studied, will probably demand testing of a larger number of donations. International experience is showing a rate of 1:200,000 - 1:500,000 of isolated HCV-RNA reactive donations.

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Both managers and scholars have convictions about the organizational approaches that best support organizational performance of the respective organizations and its Quality Management Systems. After a literature review of ISO 9001 Quality Management Systems (including the changes introduced by the 2015 edition), Organizational Culture theories are addressed and input from a CEO´s focus group was gathered. The importance of organizational culture for the success of Quality Management Systems and the achievement of the organizational desired results is highlighted. The article advances a proposal to analyze ISO 9001 International Standard through the lens of organizational culture theories identifying a stronger open systems approach (influence of the environment, dynamic perspective, need for survival) of the 2015 ISO 9001 edition when compared with the 2008 one. This provides additional knowledge both to scholars and practitioners for a better understanding of the culture issues that can maximize ISO 9001 Quality Management Systems 2015 edition contributions to organizational enduring success.

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This research focuses on the influence of company sector and size on the level of utilization of Basic and Advanced Quality Tools. The paper starts with a literature review and then presents the methodology used for the survey. Based on the responses from 202 managers of Portuguese ISO 9001:2008 Quality Management System certified organizations, statistical tests were performed. Results show, with 95% confidence level, that industry and services have a similar proportion of use of Basic and Advanced Quality Tools. Concerning size, bigger companies show a higher trend to use Advanced Quality Tools than smaller ones. For Basic Quality Tools, there was no statistical significant difference at a 95% confidence level for different company sizes. The three basic Quality tools with higher utilization were Check sheets, Flow charts and Histograms (for Services) or Control Charts/ (for Industry), however 22% of the surveyed organizations reported not using Basic Quality Tools, which highlights a major improvement opportunity for these companies. Additional studies addressing motivations, benefits and barriers for Quality Tools application should be undertaken for further validation and understanding of these results.

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Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

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The Internet of Things (IoT) has emerged as a paradigm over the last few years as a result of the tight integration of the computing and the physical world. The requirement of remote sensing makes low-power wireless sensor networks one of the key enabling technologies of IoT. These networks encompass several challenges, especially in communication and networking, due to their inherent constraints of low-power features, deployment in harsh and lossy environments, and limited computing and storage resources. The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) [1] was proposed by the IETF ROLL (Routing Over Low-power Lossy links) working group and is currently adopted as an IETF standard in the RFC 6550 since March 2012. Although RPL greatly satisfied the requirements of low-power and lossy sensor networks, several issues remain open for improvement and specification, in particular with respect to Quality of Service (QoS) guarantees and support for mobility. In this paper, we focus mainly on the RPL routing protocol. We propose some enhancements to the standard specification in order to provide QoS guarantees for static as well as mobile LLNs. For this purpose, we propose OF-FL (Objective Function based on Fuzzy Logic), a new objective function that overcomes the limitations of the standardized objective functions that were designed for RPL by considering important link and node metrics, namely end-to-end delay, number of hops, ETX (Expected transmission count) and LQL (Link Quality Level). In addition, we present the design of Co-RPL, an extension to RPL based on the corona mechanism that supports mobility in order to overcome the problem of slow reactivity to frequent topology changes and thus providing a better quality of service mainly in dynamic networks application. Performance evaluation results show that both OF-FL and Co-RPL allow a great improvement when compared to the standard specification, mainly in terms of packet loss ratio and average network latency. 2015 Elsevier B.V. Al

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Because of the scientific evidence showing that arsenic (As), cadmium (Cd), and nickel (Ni) are human genotoxic carcinogens, the European Union (EU) recently set target values for metal concentration in ambient air (As: 6 ng/m3, Cd: 5 ng/m3, Ni: 20 ng/m3). The aim of our study was to determine the concentration levels of these trace elements in Porto Metropolitan Area (PMA) in order to assess whether compliance was occurring with these new EU air quality standards. Fine (PM2.5) and inhalable (PM10) air particles were collected from October 2011 to July 2012 at two different (urban and suburban) locations in PMA. Samples were analyzed for trace elements content by inductively coupled plasma–mass spectrometry (ICP-MS). The study focused on determination of differences in trace elements concentration between the two sites, and between PM2.5 and PM10, in order to gather information regarding emission sources. Except for chromium (Cr), the concentration of all trace elements was higher at the urban site. However, results for As, Cd, Ni, and lead (Pb) were well below the EU limit/target values (As: 1.49 ± 0.71 ng/m3; Cd: 1.67 ± 0.92 ng/m3; Ni: 3.43 ± 3.23 ng/m3; Pb: 17.1 ± 10.1 ng/m3) in the worst-case scenario. Arsenic, Cd, Ni, Pb, antimony (Sb), selenium (Se), vanadium (V), and zinc (Zn) were predominantly associated to PM2.5, indicating that anthropogenic sources such as industry and road traffic are the main source of these elements. High enrichment factors (EF > 100) were obtained for As, Cd, Pb, Sb, Se, and Zn, further confirming their anthropogenic origin.

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In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

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In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

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Despite all efforts to store and reduce its consumption, water is becoming less inexhaustible and its quality is falling faster. Considering that water is essential to animal life, it is necessary to adopt measures to ensure its sanitary conditions in order to be fit for consumption. The aim of this study was to analyze the microbiological quality of drinking rainwater used by rural communities of Tuparetama, a small town located in Northeast Brazil. The study covered seven rural communities, totaling 66 households. In each household two samples were collected, one from a tank and the other from a clay pot located inside the home, resulting in 132 samples (tank plus clay pot). Approximately 90% of samples were below the standard recommended by the current legislation, being considered unfit for human consumption. Part of this high microbiological contamination of drinking rainwater could be related to the lack of sanitary education and of an adequate sewerage sanitation system.

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The question of whether HIV-1 RNA in cerebrospinal fluid (CSF) is derived from viral replication in the central nervous system or simply reflects the transit of infected lymphocytes from the blood compartment has long been a matter of debate. Some studies found no correlation between CSF and plasma viral load, whereas others did. The lack of a correlation between the two compartments suggests that the presence of HIV-1 RNA is not simply due to the passive passage of the virus from blood to CSF but rather due to intrathecal replication. To evaluate the correlation between plasma and CSF HIV-1 RNA levels and to identify situations in which there is no correlation between the two compartments, seventy patients were prospectively studied. The association between CSF and plasma viral load was evaluated in the total population and in subgroups of patients with similar characteristics. A correlation between the CSF and plasma compartments was observed for patients undergoing highly active antiretroviral therapy (HAART), those with a CD4 T lymphocyte count lower than 200 cells/mm³, and those with increased CSF protein content. On the other hand, no correlation was observed for patients without adequate virological control, who had a CD4 count higher than 200 cells/mm³ and who did not use HAART. The correlation between the two compartments observed in some patients suggests that CSF HIV-1 RNA levels may reflect plasma levels in these subjects. In contrast, the lack of a correlation between the two compartments in patients who were not on HAART and who had normal CSF proteins and a poor virological control possibly indicates compartmentalization of the virus in CSF and, consequently, plasma-independent intrathecal viral replication.