Correction: Ferreira, P.M., et al. A neural network based intelligent predictive sensor for cloudiness, solar radiation and air temperature. Sensors 2012, 12, 15750–15777

Accurate measurements of global solar radiation and atmospheric temperature, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight and portable sensor was developed, using artificial neural network models as the time-series predictor mechanisms. These have been identified with the aid of a procedure based on the multi-objective genetic algorithm. As cloudiness is the most significant factor affecting the solar radiation reaching a particular location on the Earth surface, it has great impact on the performance of predictive solar radiation models for that location. This work also represents one step towards the improvement of such models by using ground-to-sky hemispherical colour digital images as a means to estimate cloudiness by the fraction of visible sky corresponding to clouds and to clear sky. The implementation of predictive models in the prototype has been validated and the system is able to function reliably, providing measurements and four-hour forecasts of cloudiness, solar radiation and air temperature

Células de linhagem McCoy como um possível modelo contendo receptores CD4+ para estudos da replicação do HIV

Several studies have recently shown the use of recombinant rabies virus as potential vector-viral vaccine for HIV-1. The sequence homology between gp 120 and rabies virus glycoprotein has been reported. The McCoy cell line has therefore been used to show CD4+ or CD4+ like receptors. Samples of HIV-1 were isolated, when plasma of HIV-1 positive patients was inoculated in the McCoy cell line. The virus infection was then studied during successive virus passages. The proteins released in the extra cellular medium were checked for protein activity, by exposure to SDS Electrophoresis and blotting to nitro-cellulose filter, then reacting with sera of HIV positive and negative patients. Successive passages were performed, and showed viral replication, membrane permeabilization, the syncytium formation, and the cellular lysis (cytopathic effect). Flow cytometry analysis shows clear evidence that CD4+ receptors are present in this cell line, which enhances the likelihood of easy isolation and replication of HIV. The results observed allow the use of this cell line as a possible model for isolating HIV, as well as for carrying out studies of the dynamics of viral infection in several situations, including exposure to drugs in pharmacological studies, and possibly studies and analyses of the immune response in vaccine therapies.Recentes estudos demonstraram o uso do vírus raiva como modelo vetor para produzir vacinas expressando as glicoproteínas do vírus HIV-1. A homologia na seqüência entre gp120 do vírus HIV-1 e a glicoproteína G do vírus rábico já foi previamente relatada. Devido a estes fatos a linhagem de célula McCoy utilizada com sucesso para a replicação do vírus rábico foi utilizada para demonstrar a replicação do HIV-1. Amostra de HIV-1 foi isolada de plasma de um paciente soro positivo e inoculada em células de linhagem McCoy e então a infecção viral foi estudada em passagens sucessivas do vírus nesta célula. As proteínas liberadas no meio extra celular foram analisadas quanto a atividade biológica pela técnica de eletroforese em gel de poliacrilamida e imunotransferência em membrana de nitro-celulose reagindo com soros positivos para HIV-1 e soros de pacientes negativos. As passagens sucessivas do HIV-1 em células demonstraram a replicação viral, o aumento da permeabilidade da membrana citoplasmática, a formação de sinsício e lise celular. Análises com citometria de fluxo mostraram com clara evidência a presença de receptores CD4+ o que possivelmente deve ser a causa que possibilita a facilidade do isolamento e replicação do vírus HIV-1 nesta célula. Concluindo os resultados observados permitem utilizar esta linhagem celular como um possível modelo para isolamentos de HIV, bem como realizar estudos da dinâmica de infecção viral em diversas situações inclusive de exposição a drogas em estudos farmacológicos, e talvez estudos e análises da resposta imune em terapias vacinais

Effects of desloratadine on activated sludge: behaviour of EPS and sludge properties

"Available online 8 August 2022"Desloratadine (DESL), a second generation of antihistamines, is an important anti-allergic pharmaceutical used to treat allergic rhinitis, hay fever and urticaria. In this study, the overall performance, extracellular polymeric substances (EPS) production, and sludge properties were assessed in a sequencing batch reactor wastewater treatment process with activated sludge during 139 days, under the presence of DESL (1, 5, and 10mgL-1). DESL at 10mgL-1 impacted biomass activity decreasing the chemical oxygen demand removal (78%) and the ammonium removal (71%). The removal of DESL was of 63%. Tightly bound EPS (TB-EPS) was significantly higher (149.5mg gMLVSS-1) at the end of operation. Peaks attributed to protein-like fluorophores clearly predominated along the experimental phases using three-dimensional excitation-emission matrix (3D-EEM) fluorescence. The peak locations and intensities in the EPS fluorescence revealed the difference in the chemical structures of the EPS caused by DESL exposure. Quantitative image analysis results clearly demonstrated the formation of large aggregates. Principal component analysis (PCA) showed a positive relationship between TB-EPS components, and large aggregates. Moreover, the results allowed to distinguish the different operational phases, emphasizing the effect of DESL on EPS and aggregates.The authors thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/ 04469/2020 unit, and by LABBELS – Associate Laboratory in Biotechnology, Bioengineering and Microelectromechanical Systems, LA/P/ 0029/2020. The authors also acknowledge the financial support to Antonio Melo through the grant number 240-20170220 provided by Instituto Federal de Educação Ciência e Tecnologia de Pernambuco (IFPE). Daniela P. Mesquita and Cristina Quintelas thank FCT for funding through program DL 57/2016 – Norma transitoria.info:eu-repo/semantics/publishedVersio

AVALIAÇÃO DA VULNERABILIDADE NATURAL DO SOLO EM ÁREAS AGRÍCOLAS: SUBSÍDIO À AVALIAÇÃO DO RISCO DE CONTAMINAÇÃO DO LENÇOL FREÁTICO POR AGROQUÍMICOS

Procurou-se mostrar que a vulnerabilidade natural do solo é um parâmetro fundamental nos estudos de avaliação de riscos ambientais, sobretudo em áreas de grande fragilidade, como as áreas de recarga dos aqüíferos sedimentares. Para esse estudo foi adotada uma área típica de recarga direta do Aqüífero Guarani, caracterizada pela microbacia do Córrego do Espraiado, localizada na região de Ribeirão Preto/SP (Brasil). Os procedimentos consistiram na integração dos parâmetros condutividade hidráulica, declividade e profundidade do lençol freático dos principais solos da área objeto de estudo . A condutividade hidráulica foi determinada com a adoção do método da coluna saturada, com valores considerados a partir de estimativa classificada em baixa, média e alta. Nessa estimativa, levou-se em conta a integração dos dados de textura, estrutura, estabilidade de agregados e profundidade do solo, que foram submetidos a tratamento estatístico para validação do método proposto. As correlações foram diretas entre condutividade hidráulica medida e condutividade hidráulica estimada. A declividade da área foi obtida a partir de mapas planialtimétricos, em escala 1:10.000, que permitiram o agrupamento em três classes: baixa, suave e acentuada. Seqüencialmente, foi estabelecida relação matricial entre as classes de condutividade hidráulica e as de declividade, resultando na classificação relativa dos potenciais de infiltração e de escoamento superficial da água para toda a microbacia. Concluiu-se que essas informações combinadas com aquelas relativas à condutividade hidráulica, declividade do terreno e profundidade do solo permitiram, de forma satisfatória, estimar em três classes ( baixa, média e alta) a vulnerabilidade natural dos solos representativos das áreas de recarga do Aqüífero Guarani na região estudada. NATURAL VULNERABILITY OF SOIL IN AGRICULTURAL AREAS: SUBVENTION OF CONTAMINATION RISK ASSESSMENT OF GROUNDWATER BY AGROCHEMICALS Abstract The natural vulnerability of soil is a fundamental parameter in the studies of ambiental risk assessment, mainly in areas of great fragility as recharge areas of sedimentary aquifers. For this study it was adopted one typical area of direct recharge from Guarani aquifer, characterized by Espraiado watershed, localized in Ribeirão Preto region in São Paulo state, Brazil. The procedures consisted in the integration of the parameters hydraulic conductivity, declivity and depth of groundwater from soils of the area in study. The hydraulic conductivity was determined by the method of saturated column, with values considered from a estimation classified in low, medium and high. In this estimation, the integration of texture, structure, aggregate stability and soil depth data, which were submitted to statistical treatment for validation of the proposed method. The area declivity was obtained from planialtimetric maps with scale 1:10000, which allowed grouping in three classes: low, smooth and pronounced. Sequentially, it was established a matricial relation between the classes of hydraulic conductivity and declivity, resulting in the relative classification of infiltration potentials and superficial water flow for all watershed. It was concluded that this information combined to those relative to hydraulic conductivity, soil declivity and depth allowed, in a satisfactory way, to estimate in three classes (low, medium and high), the natural vulnerability of soils representatives of recharge areas of Guarani aquifer in the region studied

Automatic diagnosis of the 12-lead ECG using a deep neural network

The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve clinical practice. Here we present a DNN model trained in a dataset with more than 2 million labeled exams analyzed by the Telehealth Network of Minas Gerais and collected under the scope of the CODE (Clinical Outcomes in Digital Electrocardiology) study. The DNN outperform cardiology resident medical doctors in recognizing 6 types of abnormalities in 12-lead ECG recordings, with F1 scores above 80% and specificity over 99%. These results indicate ECG analysis based on DNNs, previously studied in a single-lead setup, generalizes well to 12-lead exams, taking the technology closer to the standard clinical practice

O impacto da escolaridade sobre a distribuição de renda

Este trabalho investiga o impacto da escolaridade sobre a distribuição de renda do trabalho de Estados/ regiões do Brasil, usando um método semiparamétrico, seguindo DiNardo, Fortin e Lemieux (1996) e informações da PNAD de 1999. Foram construídas densidades contrafactuais, reponderando a distribuição da região/Estado mais pobre (Nordeste/Ceará) pelo perfil de escolaridade da mais rica (Sudeste/São Paulo). Resultados: entre 12% e 36% do diferencial de renda é explicado pelo diferencial de escolaridade; a reponderação pela escolaridade aumentou em cerca de 55% a renda média nos contrafactuais; a renda do contrafactual do Nordeste equivale a 93% da renda média brasileira; quanto mais elevado for o percentil de renda considerado, maior é a contribuição da diferença de escolaridade para a diferença de renda; a dispersão de renda das regiões mais pobres aumenta quando fornecemos a elas o nível de escolaridade das regiões mais ricas, mantendo-se o perfil salarial da região

Tele-electrocardiography and bigdata: the CODE (Clinical Outcomes in Digital Electrocardiography) study

Digital electrocardiographs are now widely available and a large number of digital electrocardiograms (ECGs) have been recorded and stored. The present study describes the development and clinical applications of a large database of such digital ECGs, namely the CODE (Clinical Outcomes in Digital Electrocardiology) study. ECGs obtained by the Telehealth Network of Minas Gerais, Brazil, from 2010 to 17, were organized in a structured database. A hierarchical free-text machine learning algorithm recognized specific ECG diagnoses from cardiologist reports. The Glasgow ECG Analysis Program provided Minnesota Codes and automatic diagnostic statements. The presence of a specific ECG abnormality was considered when both automatic and medical diagnosis were concordant; cases of discordance were decided using heuristisc rules and manual review. The ECG database was linked to the national mortality information system using probabilistic linkage methods. From 2,470,424 ECGs, 1,773,689 patients were identified. After excluding the ECGs with technical problems and patients <16 years-old, 1,558,415 patients were studied. High performance measures were obtained using an end-to-end deep neural network trained to detect 6 types of ECG abnormalities, with F1 scores >80% and specificity >99% in an independent test dataset. We also evaluated the risk of mortality associated with the presence of atrial fibrillation (AF), which showed that AF was a strong predictor of cardiovascular mortality and mortality for all causes, with increased risk in women. In conclusion, a large database that comprises all ECGs performed by a large telehealth network can be useful for further developments in the field of digital electrocardiography, clinical cardiology and cardiovascular epidemiology

Left ventricular systolic dysfunction predicted by artificial intelligence using the electrocardiogram in Chagas disease patients-The SaMi-Trop cohort

BACKGROUND: Left ventricular systolic dysfunction (LVSD) in Chagas disease (ChD) is relatively common and its treatment using low-cost drugs can improve symptoms and reduce mortality. Recently, an artificial intelligence (AI)-enabled ECG algorithm showed excellent accuracy to detect LVSD in a general population, but its accuracy in ChD has not been tested. OBJECTIVE: To analyze the ability of AI to recognize LVSD in patients with ChD, defined as a left ventricular ejection fraction determined by the Echocardiogram ≤ 40%. METHODOLOGY/PRINCIPAL FINDINGS: This is a cross-sectional study of ECG obtained from a large cohort of patients with ChD named São Paulo-Minas Gerais Tropical Medicine Research Center (SaMi-Trop) Study. The digital ECGs of the participants were submitted to the analysis of the trained machine to detect LVSD. The diagnostic performance of the AI-enabled ECG to detect LVSD was tested using an echocardiogram as the gold standard to detect LVSD, defined as an ejection fraction <40%. The model was enriched with NT-proBNP plasma levels, male sex, and QRS ≥ 120ms. Among the 1,304 participants of this study, 67% were women, median age of 60; there were 93 (7.1%) individuals with LVSD. Most patients had major ECG abnormalities (59.5%). The AI algorithm identified LVSD among ChD patients with an odds ratio of 63.3 (95% CI 32.3-128.9), a sensitivity of 73%, a specificity of 83%, an overall accuracy of 83%, and a negative predictive value of 97%; the AUC was 0.839. The model adjusted for the male sex and QRS ≥ 120ms improved the AUC to 0.859. The model adjusted for the male sex and elevated NT-proBNP had a higher accuracy of 0.89 and an AUC of 0.874. CONCLUSION: The AI analysis of the ECG of Chagas disease patients can be transformed into a powerful tool for the recognition of LVSD

Os livros brancos da defesa da República Popular da China 1998-2010

Este estudo é uma análise da evolução das perceções de (in)segurança da República Popular da China (RPC), através da aferição quantitativa e qualitativa de expressões idiomáticas caracterizadoras da evolução do sistema internacional, as quais foram selecionadas e associadas a tais perceções, e que constam das sete edições do Livro Branco da Defesa publicadas pelo Conselho de Estado entre 1998 e 2010. Procura-se através de um enquadramento conceptual e metodológico derivado da análise crítica do discurso baseado nas teorias de Michel Foucault e de Norman Fairclough, bem como do da perceção de ameaças por parte dos Estados no sistema internacional formulado por Robert Jervis, identificar e justificar variações nas perceções de (in)segurança da RPC entre 1998 e 2010, concluindo-se que estas refletem uma visão de natureza essencialmente realista estrutural e Lockeana quanto à evolução do sistema internacional

ReRep: Computational detection of repetitive sequences in genome survey sequences (GSS)

<p>Abstract</p> <p>Background</p> <p>Genome survey sequences (GSS) offer a preliminary global view of a genome since, unlike ESTs, they cover coding as well as non-coding DNA and include repetitive regions of the genome. A more precise estimation of the nature, quantity and variability of repetitive sequences very early in a genome sequencing project is of considerable importance, as such data strongly influence the estimation of genome coverage, library quality and progress in scaffold construction. Also, the elimination of repetitive sequences from the initial assembly process is important to avoid errors and unnecessary complexity. Repetitive sequences are also of interest in a variety of other studies, for instance as molecular markers.</p> <p>Results</p> <p>We designed and implemented a straightforward pipeline called ReRep, which combines bioinformatics tools for identifying repetitive structures in a GSS dataset. In a case study, we first applied the pipeline to a set of 970 GSSs, sequenced in our laboratory from the human pathogen <it>Leishmania braziliensis</it>, the causative agent of leishmaniosis, an important public health problem in Brazil. We also verified the applicability of ReRep to new sequencing technologies using a set of 454-reads of an <it>Escheria coli</it>. The behaviour of several parameters in the algorithm is evaluated and suggestions are made for tuning of the analysis.</p> <p>Conclusion</p> <p>The ReRep approach for identification of repetitive elements in GSS datasets proved to be straightforward and efficient. Several potential repetitive sequences were found in a <it>L. braziliensis </it>GSS dataset generated in our laboratory, and further validated by the analysis of a more complete genomic dataset from the EMBL and Sanger Centre databases. ReRep also identified most of the <it>E. coli </it>K12 repeats prior to assembly in an example dataset obtained by automated sequencing using 454 technology. The parameters controlling the algorithm behaved consistently and may be tuned to the properties of the dataset, in particular to the length of sequencing reads and the genome coverage. ReRep is freely available for academic use at <url>http://bioinfo.pdtis.fiocruz.br/ReRep/</url>.</p