Radiosterilization of historical documents: the potential effects of gamma irradiation on paper and printing inks

The controlled exposition to gamma radiation is a physical process which can be used for the preservation and recovery of historical documents. Depending on the intrinsic characteristics of the material to be treated, it is necessary to research and stablish, from time to time, the optimum dose rate and total dose, the conditions to eliminate or reduce the biological threat, the equipment and its logistics, the economic aspects and any other impact caused by radiation on the material to be treated. The references indicate that through research it is possible to consolidate the knowledge about gamma radiation emitted from 60Co in order to completely remove or at least greatly reduce infestation by insects or biodeterioration microorganisms. On this work we have used a MDS Nordion self-contained 60Co research irradiator, model Gamacell Excel 220, at Postgraduate Institute of Engineering and Research Alberto Luiz Coimbra, in Rio de Janeiro Federal University. The analysis of the samples submitted to controlled thermal dry aging and to gamma radiation made possible to verify the differences between treated and untreated samples. The results of the chromatic measures indicate that, with the optimum total dose, the gamma radiation treatment does not significantly alter the properties of paper or printing inks. This way, it is possible to conclude that even though the gamma irradiation of historical documents is a complex procedure which demands a detailed study in order to assure its safe application, it is environmentally safer than the use of chemical pesticides

Desenvolvimento dos conversores de potência para o sistema de alimentação de uma microrrede isolada baseada em energias renováveis

Dissertação de mestrado em Engenharia Eletrónica e de ComputadoresA energia elétrica tem um papel extremamente importante no desenvolvimento de uma região, bem como na melhoria da qualidade de vida do ser humano. É assim fundamental eletrificar regiões isoladas e com elevadas taxas de subdesenvolvimento. A eletrificação da grande maioria destas regiões isoladas, passa pela produção local de energia recorrendo a fontes de energia renovável, quer por razões logísticas quer ambientais. Nesta dissertação são apresentados e descritos, os sistemas de eletrónica de potência que permitem implementar uma microrrede isolada com produção a partir de fontes renováveis e capacidade de armazenamento local de energia. O foco principal deste trabalho é o desenvolvimento e validação do sistema responsável pela implementação de uma microrrede isolada monofásica com tensão alternada sinusoidal de 230 V/50 Hz. O desenvolvimento do sistema responsável pela produção e armazenamento de energia encontra-se descrito numa dissertação com o tema complementar, realizada pelo colega de laboratório João Silva. Para a realização da presente dissertação foi necessário o estudo, dimensionamento e implementação do conversor CC-CA de três estágios. Este conversor pode ser dividido num conversor CC-CC em ponte completa isolado de alta frequência do tipo buck e num conversor CC-CA em ponte completa. Para ambos os conversores foi desenvolvido um controlador digital, sendo utilizado um controlador Proporcional Integral no conversor CC-CC e um controlador Preditivo no conversor CC-CA monofásico. Depois de desenvolvido o protótipo do sistema de alimentação da mirorrede isolada, foram realizados alguns ensaios laboratoriais de modo a validar a solução apresentada. Os ensaios realizados, permitiram analisar o comportamento do sistema para três tipos de carga diferentes: carga linear puramente resistiva; carga linear predominantemente indutiva; e carga não linear do tipo retificador com filtro capacitivo. Por último, foram ainda realizados alguns ensaios ao sistema desenvolvido na presente dissertação, interligado com o sistema complementar desenvolvido pelo colega João Silva. Perante os resultados obtidos, foi possível comprovar o conceito e validar o funcionamento do sistema de alimentação da microrrede isolada.Electric power plays an essential role in the development of an isolated rural region, as well as in improving the overall human well-being. Therefore, the electrification of isolated and underdeveloped zones is a matter of extreme importance. Due to either logistic or environmental reasons, in most of these isolated regions, the required electrification involves the local energy production through renewable energy sources. In this dissertation, the power electronics system that allows the implementation of an islanded microgrid with local production and storage of energy is presented and described in detail. The main focus of this work is the development and validation of the power electronics system to implement a single-phase islanded microgrid with 230 V/50 Hz sinusoidal voltage. The electronic system responsible for energy production and storage is being developed within the dissertation work of the classmate João Silva. In order to complete this dissertation, it was required to study, sizing and implement a three-stage DC-AC converter. This converter is composed of a high-frequency isolated buck type full-bridge DC-DC converter and of a single-phase full-bridge DC-AC converter. A digital controller was developed for both converters, namely a Proportional Integral in the case of the DC-DC converter and a Predictive Deadbeat in the case of the DC-AC converter. After the development of the islanded microgrid power system prototype, some laboratorial tests were carried out to analyze the response of the presented solution. The elaborated tests allowed the analysis of the converters toward three different loads: a purely resistive linear load; a predominantly inductive linear load; and a rectifier with capacitive filter nonlinear load. Finally, a few tests were done on the system developed in the presented dissertation combined with the complementary system developed by João Silva. Concerning the final results, it was possible to prove the concept and to validate the operation of the islanded microgrid power system

Flow measurements in hydrotransport units using gamma scattering and cross-correlation techniques

The proposal of this research was to develop a methodology using gamma radiation and cross-correlation techniques to measure the speed of ore pellets in a hydrotansport duct. An experimental unit was designed and built to be used in a two-phase flows transport simulation It was used to measure the velocity of the solid pellets. The flowmeter system consists in two independent systems, each one composed by a NaI (1x1”) scintillators detector- 241Am gamma source, installed outside the tube, both systems were located in the same vertical plane and separated by 18.0 cm. As pellets, were produced a variety of specimens with different compositions in order to verify the methodology. Using this flowmeter was possible to calculate the solid phase velocity

Volume fraction calculation in multiphase system such as oil-water-gas using neutron

Multi-phase flows are common in diverse industrial sectors and the attainment of the volume fraction of each element that composes the flow system presents difficulties for the engineering process, therefore, to determine them is very important. In this work is presented methodology for determination of volume fractions in annular three-phase flow systems, such as oil-water-gas, based on the use of nuclear techniques and artificial intelligence. Using the principle of the fast-neutron transmission/scattering, come from an isotopic 241Am-Be source, and two point detectors, is gotten measured that they are influenced by the variations of the volumec fractions of each phase present in the flow. An artificial neural network is trained to correlate such measures with the respective volume fractions. In order to get the data for training of the artificial neural network without necessity to carry through experiments, MCNP-X code is used, that simulates computational of the neutrons transport. The methodology is sufficiently advantageous, therefore, allows to develop a measurement system capable to determine the fractions of the phases (oil-water-gas), with proper requirements of each petroliferous installation and with national technology contributing, possibly, with reduction of costs and increase of productivity

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