Transmissão de áudio através de TDM

Na actualidade, pretende-se que as tecnologias apresentem, entre outras características, uma maior eficiência, autonomia e rapidez. Desta forma, este projecto insere-se no âmbito destas exigências e tem como objectivo o desenvolvimento de um sistema capaz de transferir, através de um único cabo, o sinal áudio proveniente de diferentes microfones e voltar a redistribui-lo pelo mesmo número de canais no destino, usando a técnica Time Division Multiplexing (TDM). A vantagem deste projecto é que em vez de ter, por exemplo, quatro cabos para transferir sinal áudio de quatro microfones tem apenas um cabo ou até nenhum, caso utilize, por exemplo, Bluetooth ou Wi-Fi. Para validar a solução, em primeiro lugar, foi definida arquitectura geral do projecto, que é composta quatro microfones, dois módulos, - o módulo transmissor e o módulo receptor – e quatro colunas. Em segundo lugar, definiu-se que para a transmissão de dados entre os dois módulos se iria usar a comunicação série assíncrona. Em terceiro, foram realizados testes num ambiente controlado e, para tal, foram utilizados dois geradores de sinais, em vez dos quatro microfones. Os testes realizados foram bem-sucedidos e consistiram em injectar, no módulo transmissor, dois sinais com uma dada frequência e obter os mesmos sinais à saída do módulo receptor. No caso do teste em ambiente real, acrescentou-se aos dois geradores de sinais dois Motion Picture Experts Group 1 Audio Layer-3 (MP3). Acrescentou-se, também, um botão para seleccionar o número de entradas activas (número de microfones e de geradores de sinais activos) e dois conjuntos de colunas. Os testes tiveram um resultado muito positivo, porque foi possível ouvir nas colunas as músicas/sons que estavam a ser reproduzidas nos MP3, para além de se conseguir visualizar, à saída do módulo receptor, os mesmos sinais que se estavam a inserir no módulo transmissor. Além disso, conseguiu-se, usando o botão, seleccionar o número de entradas activas pretendidas.Nowadays, the aim is that technologies offer, among other characteristics, a bigger efficiency, autonomy and quickness. In this way, this project fits these demands and has, as objective, the development of a system which is able to transfer through only one cable the audio signal originating from different microphones and redistribute it by the same number of cables at the final destination, using Time Division Multiplexing (TDM). An advantage of this project is that, instead of having four cables to transfer the áudio signal of four microphones, it has only one or even none, if it uses, for example, Bluetooth or Wi-Fi. To validate the solution, the first thing to do was to define the general architecture of the project, which is formed by four microphones, two modules, - the transmitter and the receiver - and four speakers. Secondly, it was defined that to transmit data between the two modules we would use asynchronous module series communication. Thirdly, some tests were carried out in a controlled environment and, for that, two signal generators were used instead of four microphones. The tests were successful and consisted of injecting two signals with a certain frequency into the transmitter module and obtain the same signals at the exit of the receiver module. In the case of the test in real environment, two Motion Picture Experts Group 1 Audio Layer-3 (MP3) were added to the two signals generator. We also added a button to select the number of active entries (number of microphones and active signals generator) and two sets of speakers. The tests had a very positive result as it was possible to hear the songs/ sounds that were being played in the MP3. Besides that, it was also possible to see, at the exit of the receiver module, the same signals that were being inserted in the transmitter module. Moreover, it was possible to select the desired number of entries, using the button

a multicenter study

(1) Background: The Commercial Kit SIRE Nitratase® PlastLabor, is a drug susceptibility test kit used to detect Mycobacterium tuberculosis resistance to first-line TB treatment drugs. The present study aimed at evaluating its performance in a multicenter study. (2) Methods: To determine its accuracy, the proportion methods in Lowenstein Jensen medium or the BACTECTMMGITTM960 system was used as a gold standard. (3) Results: The study revealed that the respective accuracies of the kit with 190 M. tuberculosis clinical isolates, using the proportion methods in Lowenstein Jensen medium or BACTECTMMGITTM960 system as a gold standard, were 93.9% and 94.6%, 96.9% and 94.6%, 98.0% and 97.8%, and 98.0% and 98.9%, for streptomycin, isoniazid, rifampicin, and ethambutol, respectively. (4) Conclusion: Thus, the kit can rapidly screen resistance to streptomycin, isoniazid, rifampicin, and ethambutol. Additionally, it does not require sophisticated equipment; hence, it can be easily used in the laboratories of low and middle income countries.publishersversionpublishe

Bad Choices Make Good Stories: The Impaired Decision-Making Process and Skin Conductance Response in Subjects With Smartphone Addiction

Introduction: Smartphone Addiction (SA) has caused negative consequences and functional impairments in college students, such as reduction of academic performance and impairment in sleep quality. Studies have shown that individuals with chemical and behavioral dependencies have a bias in decision-making process, which leads to short-term advantageous choices even if they cause long-term harm. This bias in decision-making process is accompanied by a change in somatic markers and is associated with the development and maintenance of addictive behavior. The decision-making process and the measurement of physiological parameters have not yet been analyzed in SA. The neuropsychological and physiological characterization of the SA can contribute to its approach with the other dependency syndromes and to its recognition as a disease.Objective: we aimed to evaluate the decision-making process under risk and under ambiguity in individuals with SA and to measure the physiological parameters that accompany this process.Method: We compared the performance in the Iowa Gambling Task (IGT), Game of Dice Task (GDT) and skin conductance response (SCR) between 50 individuals with SA and 50 controls.Results: Smartphone dependents presented a profile of impairment in decision-making under ambiguity, without impairment in decision-making under risk. They demonstrated lower SCR before disadvantageous choices, higher SCR after rewards and lower SCR after punishments during decision-making, which suggests difficulty in recognizing disadvantageous alternatives, high sensitivity to rewards, and low sensitivity to punishments.Conclusion: The impairment in the decision-making process in smartphone dependents is similar to that found in other chemical and behavioral addictions, such as alcohol addiction, gambling disorders and pathological buy. The impairment in decision under ambiguity with preservation of decision under risk may reflect dysfunction of implicit emotional processes without dysfunction of explicit cognitive process. This profile can contribute to the recognition of SA as a behavioral dependence and to guide specific preventive and therapeutic strategies

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Rhinitis associated with asthma is distinct from rhinitis alone: TARIA‐MeDALL hypothesis

Asthma, rhinitis, and atopic dermatitis (AD) are interrelated clinical phenotypes that partly overlap in the human interactome. The concept of “one-airway-one-disease,” coined over 20 years ago, is a simplistic approach of the links between upper- and lower-airway allergic diseases. With new data, it is time to reassess the concept. This article reviews (i) the clinical observations that led to Allergic Rhinitis and its Impact on Asthma (ARIA), (ii) new insights into polysensitization and multimorbidity, (iii) advances in mHealth for novel phenotype definitions, (iv) confirmation in canonical epidemiologic studies, (v) genomic findings, (vi) treatment approaches, and (vii) novel concepts on the onset of rhinitis and multimorbidity. One recent concept, bringing together upper- and lower-airway allergic diseases with skin, gut, and neuropsychiatric multimorbidities, is the “Epithelial Barrier Hypothesis.” This review determined that the “one-airway-one-disease” concept does not always hold true and that several phenotypes of disease can be defined. These phenotypes include an extreme “allergic” (asthma) phenotype combining asthma, rhinitis, and conjunctivitis.info:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

ARIA 2019: Um percurso assistencial integrado para a rinite alérgica em Portugal

International audienceThe Allergic Rhinitis and Its Impact on Asthma (ARIA) initiative started more than 20 years ago and has developed and disseminated evidence-based guidelines and projects in the field of allergic rhinitis. This initiative is currently focused on providing patient-centred guidelines that contribute to an integrated care pathway between the various levels of care and take advantage of digital solutions, and the introduction of integrated care pathways in clinical practice has been recommended. In this article we describe the adaptation for Portugal of the ARIA Integrated Care Pathways document. After a brief review of the epidemiology and impact of allergic rhinitis in Portugal and the activities carried out in Portugal within the ARIA initiative, we describe the broad knowledge base used for the development of recommendations for the pharmacological treatment of allergic rhinitis, and these recommendations are based on the GRADE methodology, real world evidence acquired by mobile technology (mHealth) and resulting from allergenic exposure chamber studies. What follows is a summary of integrated care pathways for allergen immunotherapy produced in 2019. Allergen immunotherapy is considered an example of precision medicine where the use of mHealth technologies will improve stratification for patient selection and response monitoring. These recommendations were considered as best practices of integrated patient-centred care supported by digital systems from Directorate General for Health and Food Safety of the European Union (DG Santé) and represent the ARIA Phase 4 Change Management strategy. Copyrigh

Detection of drug resistant Mycobacterium Tuberculosis strains using kit SIRE Nitratase®: a multicenter study

This research was funded by MINAS GERAIS STATE RESEARCH SUPPORT FOUNDATION (FAPEMIG), grants numbers 65/10 and CDS-APQ-03266-13, and by NATIONAL COUNCIL FOR SCIENTIFIC AND TECHNOLOGICAL DEVELOPMENT (CNPQ) grants numbers 310174/2014-7 and 446796/2014-0.Federal University of Minas Gerais. Faculty of Medicine. Mycobacteria Research Laboratory. Belo Horizonte, MG, Brazil.Federal University of Minas Gerais. Faculty of Medicine. Mycobacteria Research Laboratory. Belo Horizonte, MG, Brazil.Federal University of Minas Gerais. Faculty of Medicine. Mycobacteria Research Laboratory. Belo Horizonte, MG, Brazil.Federal University of Minas Gerais. Faculty of Medicine. Mycobacteria Research Laboratory. Belo Horizonte, MG, Brazil.Federal University of Minas Gerais. Faculty of Pharmacy. Department of Social Pharmacy. Belo Horizonte, MG, Brazil.Federal University of Minas Gerais. Veterinary School. Department of Preventive Veterinary Medicine. Belo Horizonte, MG, Brazil.Federal University of Rio Grande. Faculty of Medicine. Laboratory of Mycobacteria. Rio Grande, RS, Brazil.Federal University of Rio Grande. Faculty of Medicine. Laboratory of Mycobacteria. Rio Grande, RS, Brazil.Federal University of Rio Grande. Faculty of Medicine. Laboratory of Mycobacteria. Rio Grande, RS, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Tropical Medicine Foundation Dr. Heitor Vieira Dourado. Manaus, AM, Brazil.Tropical Medicine Foundation Dr. Heitor Vieira Dourado. Manaus, AM, Brazil.Federal University of Rio de Janeiro. Institute of Chest Diseases. Clementino Fraga Filho University Hospital. Rio de Janeiro, RJ, Brazil.Federal University of Rio de Janeiro. Institute of Chest Diseases. Clementino Fraga Filho University Hospital. Rio de Janeiro, RJ, Brazil.Federal University of Grande Dourados. Faculty of Health Sciences. Dourados, MS, Brazil / Oswaldo Cruz Foundation. Campo Grande, Mato Grosso do Sul, MS, Brazil.Adolfo Lutz Institute. Bacteriology Center. Tuberculosis and Mycobacteriosis Center. São Paulo, SP, Brazil.Adolfo Lutz Institute. Bacteriology Center. Tuberculosis and Mycobacteriosis Center. São Paulo, SP, Brazil.Adolfo Lutz Institute. Bacteriology Center. Tuberculosis and Mycobacteriosis Center. São Paulo, SP, Brazil.State Secretariat of Health of Rio Grande do Sul. State Center for Health Surveillance. Center for Scientific and Technological Development. Porto Alegre, RS, Brazil.State Secretariat of Health of Rio Grande do Sul. State Center for Health Surveillance. Center for Scientific and Technological Development. Porto Alegre, RS, Brazil.Oswaldo Cruz Foundation. National Institute of Infectology Evandro Chagas. Laboratory of Bacteriology and Bioassays of Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Sergio Arouca National Public Health School. Professor Hélio Fraga Reference Center. Rio de Janeiro, RJ, Brazil.Sergio Arouca National Public Health School. Professor Hélio Fraga Reference Center. Rio de Janeiro, RJ, Brazil.Nova University of Lisbon. Institute of Hygiene and Tropical Medicine. Medical Microbiology Unit, Global Health and Tropical Medicine. Lisboa, Portugal.Nova University of Lisbon. Institute of Hygiene and Tropical Medicine. Medical Microbiology Unit, Global Health and Tropical Medicine. Lisboa, Portugal.Federal University of Rio de Janeiro. Faculty of Medicine. Tuberculosis Research Center. Rio de Janeiro, RJ, Brazil.Background: The Commercial Kit SIRE Nitratase® PlastLabor, is a drug susceptibility test kit used to detect Mycobacterium tuberculosis resistance to first-line TB treatment drugs. The present study aimed at evaluating its performance in a multicenter study. (2) Methods: To determine its accuracy, the proportion methods in Lowenstein Jensen medium or the BACTECTMMGITTM960 system was used as a gold standard. (3) Results: The study revealed that the respective accuracies of the kit with 190 M. tuberculosis clinical isolates, using the proportion methods in Lowenstein Jensen medium or BACTECTMMGITTM960 system as a gold standard, were 93.9% and 94.6%, 96.9% and 94.6%, 98.0% and 97.8%, and 98.0% and 98.9%, for streptomycin, isoniazid, rifampicin, and ethambutol, respectively. (4) Conclusion: Thus, the kit can rapidly screen resistance to streptomycin, isoniazid, rifampicin, and ethambutol. Additionally, it does not require sophisticated equipment; hence, it can be easily used in the laboratories of low and middle income countries