Capacitive impedance measurement : dual-frequency approach.

The most widely used technique for measuring capacitive impedances (or complex electrical permittivity) is to apply a frequency signal to the sensor and measure the amplitude and phase of the output signal. The technique, although efficient, involves high-speed circuits for phase measurement, especially when the medium under test has high conductivity. This paper presents a sensor to measure complex electrical permittivity based on an alternative approach to amplitude and phase measurement: The application of two distinct frequencies using a current-to-voltage converter circuit based in a transimpedance amplifier, and an 8-bit microcontroller. Since there is no need for phase measurement and the applied frequency is lower compared to the standard method, the circuit presents less complexity and cost than the traditional technique. The main advance presented in this work is the use of mathematical modeling of the frequency response of the circuit to make it possible for measuring the dielectric constant using a lower frequency than the higher cut-off frequency of the system, even when the medium under test has high conductivity (tested up to 1220 ?S/cm). The proposed system caused a maximum error of 0.6% for the measurement of electrical conductivity and 2% for the relative dielectric constant, considering measurement ranges from 0 to 1220 ?S/cm and from 1 to 80, respectively

Problem-based learning in engineering teaching.

A partir do estudo de uma disciplina regular do curso de gradua??o de Engenharia Agr?cola e Ambiental, relacionando as perspectivas do professor e dos estudantes e considerando a carga hor?ria e do conte?do abordado, foi proposta uma sistem?tica de trabalho em sala de aula, de curso presencial, para introdu??o do m?todo de ensino conhecido como ?Problem-Based Learning? (PBL) no ensino de Engenharia. Os resultados demonstraram viabilidade na proposi??o de uso do PBL de forma parcial e aplicado para disciplinas que preveem uma carga hor?ria pr?tica, como foi o caso da que foi estudada, a ?Termodin?mica?. O artigo apresenta, ainda, uma metodologia para organiza??o dos grupos de estudantes em sala de aula, para dinamizar o processo de aprendizagem e troca de conhecimentos pelo PBL

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

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

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

The 1-wireTM technology applied to real time control of grain aeration systems

Neste trabalho, desenvolveu-se um sistema de controle inteligente, em tempo real, para aeração de grãos armazenados, utilizando-se a tecnologia 1-wireTM da Dallas Semiconductor. No lugar dos termopares convencionais, utilizaram-se sensores de temperatura DS1820. Esta tecnologia, proposta pela Dallas Semiconductor, permite uma transferência bidirecional de dados ao mesmo tempo em que alimenta dispositivos remotos por meio da própria linha de dados. Cada um destes dispositivos pode ser endereçado, pois possui um código de endereçamento individual e único. Trata-se de um sistema com um mestre e múltiplos escravos ligados por meio de um único condutor, com saída em dreno aberto, alimentado por uma fonte de 5 V CC, através de um resistor de polarização. Para testar o sistema de controle proposto, construiu-se um silo protótipo e desenvolveu-se um programa computacional que realiza a aquisição de dados de temperatura em tempo real, faz os cálculos necessários e, baseado nas condições psicrométricas do ar e da massa de grãos, juntamente com a estratégia de manejo utilizada, gerencia o sistema de controle.In this work, a real time intelligent control system for stored grain aeration systems was developed, employing the 1- wireTM technology developed by Dallas Semiconductor. The standard thermocouples, commonly used in aeration systems, were replaced by DS1820 digital temperature sensors. This technology allows for a half duplex data transfer and each device connected to the system can be addressed, because each one contains a unique individual identification code. The 1-wireTM system is an open drain master-slave system connected by a single conductor and powered by a 5 V DC, through a pull up resistor, at the master. For testing the control system, a grain bin prototype was built and a software was developed to perform real time temperature data acquisition. The program makes the necessary calculations and, based on psychrometric conditions of the air and of the grain mass, and the aeration strategy used, monitors the control system.Fundação de Amparo a Pesquisa do Estado de Minas Gerai