Selénio e a importância para o organismo humano

O selénio (Se) é um micronutriente essencial para o crescimento, desenvolvimento e normal metabolismo dos animais, incluindo o ser humano. É parte integrante de um conjunto de proteínas, as selenoproteínas, com ação antioxidante (protegendo as membranas celulares contra danos dos radicais livres), envolvidas no metabolismo das hormonas da tiróide, na regulação do crescimento e viabilidade celular, nas funções do sistema imune e na reprodução. É introduzido na dieta alimentar (principalmente nas formas de selenometionina e selenocisteína) através das plantas, e de produtos que delas derivam, que assimilam os compostos de selénio presentes no solo. Uma vez que a quantidade de selénio existente nos solos é muito variável, o teor nos alimentos vai depender da sua origem geográfica e, por consequência, a ingestão de selénio varia entre regiões e países. Baixos níveis de selénio estão associados a um declínio na função imune e problemas cognitivos. A deficiência de Se pode também ocasionar problemas musculares e cardiomiopatia. Concentrações reduzidas foram observadas em indíviduos com crises epiléticas e também em casos de pré-eclampsia. A deficiência de selénio pode também desenvolver-se durante a nutrição parenteral. Atualmente, a Dose Diária Recomendada (DDR) é de 55 μg/dia para homens e mulheres adultos e saudáveis. No entanto, existem evidências clínicas de que a ingestão em doses superiores (200-300 μg/dia) pode ter um papel benéfico na prevenção de alguns tipos de cancro e doenças cardiovasculares, na melhoria da resposta imunológica, como neuroprotetor e na fertilidade. O Se desempenha um papel importante na fertilidade masculina, sendo necessário na biossíntese da testosterona e na formação e normal desenvolvimento dos espermatozóides. Em mulheres grávidas o Se, ajuda a prevenir complicações antes e durante o parto e promove o normal desenvolvimento do feto. Como antioxidante o selénio vai combater os danos provocados pelos radicais livres, impedindo que estes exerçam o seu papel prejudicial no organismo. Sendo o sistema imunológico muito suscetível aos danos provocados pelo stress oxidativo, o Se vai exercer efeitos benéficos combatendo os danos por ele causados. Relativamente à capacidade viral, não é possível saber com exatidão qual a quantidade de Se necessária ou concentração ideal no plasma para evitar a ocorrência e desenvolvimento de infeções virais. No entanto, sabe-se que tem um efeito benéfico em pacientes HIV positivos e em indivíduos infetados com o vírus da hepatite (B ou C) contra a progressão para o neoplasia de fígado. Em teoria, a nível cardiovascular, este elemento pode exercer um efeito protetor, embora alguns estudos epidemiológicos não tenham mostrado uma associação clara entre o risco cardiovascular e os níveis selénio. A nível cerebral o Se vai atuar como neuroprotetor, prevenindo o aparecimento de patologias como demência e doença de Alzheimer. Apesar destes indicadores, a maioria dos países europeus, incluindo Portugal, regista uma deficiente ingestão de selénio por parte da população. A suplementação poderá constituir uma opção para garantir os níveis nutricionais recomendados e/ou ser utilizada com o objetivo de prevenir algumas doenças e o envelhecimento. No entanto o selénio pode também ser tóxico se ingerido em excesso, estando a dose máxima admissível fixada em 400 μg/dia. A intoxicação por selénio é chamada selenose e os sintomas comuns incluem: hálito a alho, distúrbios gastrointestinais, perda de cabelo, descamação das unhas, danos neurológicos e fadiga. Assim, atualmente acredita-se que enquanto indivíduos com baixo nível de Se podem obter benefícios da suplementação, esta pode ser prejudicial aqueles com valores normais ou elevados.

Occupational lead neurotoxicity: A behavioural and electrophysiological evaluation. study design and year one results.

To evaluate the effects of chronic lead exposure on the nervous system in adults, a set of neurobehavioural and electrophysiological tests was administered to 99 lead exposed foundry employees and 61 unexposed workers. Current and past blood lead concentrations were used to estimate the degree of lead absorption; all previous blood lead concentrations had been less than or equal to 90 micrograms/100 ml. Characteristic signs (such as wrist extensor weakness) or symptoms (such as colic) of lead poisoning were not seen. Sensory conduction in the sural nerve was not affected. By contrast, various neurobehavioural functions deteriorated with increasing lead burden. Workers with blood lead concentrations between 40 and 60 micrograms/100 ml showed impaired performance on tests of verbal concept formation, visual/motor performance, memory, and mood. Thus impairment in central nervous system function in lead exposed adults occurred in the absence of peripheral nervous system derangement and increased in severity with increasing lead dose.

Survey of the potential environmental and health impacts in the immediate aftermath of the coal ash spill in Kingston, Tennessee.

An investigation of the potential environmental and health impacts in the immediate aftermath of one of the largest coal ash spills in U.S. history at the Tennessee Valley Authority (TVA) Kingston coal-burning power plant has revealed three major findings. First the surface release of coal ash with high levels of toxic elements (As = 75 mg/kg; Hg = 150 microg/kg) and radioactivity (226Ra + 228Ra = 8 pCi/g) to the environment has the potential to generate resuspended ambient fine particles (< 10 microm) containing these toxics into the atmosphere that may pose a health risk to local communities. Second, leaching of contaminants from the coal ash caused contamination of surface waters in areas of restricted water exchange, but only trace levels were found in the downstream Emory and Clinch Rivers due to river dilution. Third, the accumulation of Hg- and As-rich coal ash in river sediments has the potential to have an impact on the ecological system in the downstream rivers by fish poisoning and methylmercury formation in anaerobic river sediments.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Design of Scheduling Algorithms Using Game Theoretic Ideas

Scheduling a set of jobs over a collection of machines to optimize a certain quality-of-service measure is one of the most important research topics in both computer science theory and practice. In this thesis, we design algorithms that optimize {\em flow-time} (or delay) of jobs for scheduling problems that arise in a wide range of applications. We consider the classical model of unrelated machine scheduling and resolve several long standing open problems; we introduce new models that capture the novel algorithmic challenges in scheduling jobs in data centers or large clusters; we study the effect of selfish behavior in distributed and decentralized environments; we design algorithms that strive to balance the energy consumption and performance.

The technically interesting aspect of our work is the surprising connections we establish between approximation and online algorithms, economics, game theory, and queuing theory. It is the interplay of ideas from these different areas that lies at the heart of most of the algorithms presented in this thesis.

The main contributions of the thesis can be placed in one of the following categories.

1. Classical Unrelated Machine Scheduling: We give the first polygorithmic approximation algorithms for minimizing the average flow-time and minimizing the maximum flow-time in the offline setting. In the online and non-clairvoyant setting, we design the first non-clairvoyant algorithm for minimizing the weighted flow-time in the resource augmentation model. Our work introduces iterated rounding technique for the offline flow-time optimization, and gives the first framework to analyze non-clairvoyant algorithms for unrelated machines.

2. Polytope Scheduling Problem: To capture the multidimensional nature of the scheduling problems that arise in practice, we introduce Polytope Scheduling Problem (\psp). The \psp problem generalizes almost all classical scheduling models, and also captures hitherto unstudied scheduling problems such as routing multi-commodity flows, routing multicast (video-on-demand) trees, and multi-dimensional resource allocation. We design several competitive algorithms for the \psp problem and its variants for the objectives of minimizing the flow-time and completion time. Our work establishes many interesting connections between scheduling and market equilibrium concepts, fairness and non-clairvoyant scheduling, and queuing theoretic notion of stability and resource augmentation analysis.

3. Energy Efficient Scheduling: We give the first non-clairvoyant algorithm for minimizing the total flow-time + energy in the online and resource augmentation model for the most general setting of unrelated machines.

4. Selfish Scheduling: We study the effect of selfish behavior in scheduling and routing problems. We define a fairness index for scheduling policies called {\em bounded stretch}, and show that for the objective of minimizing the average (weighted) completion time, policies with small stretch lead to equilibrium outcomes with small price of anarchy. Our work gives the first linear/ convex programming duality based framework to bound the price of anarchy for general equilibrium concepts such as coarse correlated equilibrium.

Profitability and the poor: corporate strategies, innovation and sustainability

Based on empirical evidence, the article looks at the implications of private sector participation (PSP) for the delivery of water supply and sanitation to the urban and peri-urban poor in developing countries, with particular reference to Africa and Latin America. More precisely, the article addresses the impact produced by multinational companies’ (MNCs) strategies, in light of the pursuit of profitability, on the extension of connections to the pipeline network. It does so by questioning the assumptions that greater private sector efficiency and innovation, together with contract design, will enable the sustainable extension of service coverage to low income dwellers. The strategies of the major water MNCs are considered both in relation to the global expansion of their operations and the adjustment of local strategies to commercial considerations. The latter might result in identifying proWtable markets, modifying contractual provisions, attempting to reduce costs and increase income, reducing risks and exiting from non-performing contracts. The evidence reviewed allows for re-assessing the relative roles of the public and private sectors in extending and delivering water services to the poor. First, the most far reaching innovative approaches to extending connections are more likely to come from communities, public authorities and political activity than from MNCs. Secondly, whenever MNCs are liable to exit from non-profitable contracts, the public sector has no other option than to deal with external risks aVecting continuity of provision. Finally, market limitations affecting MNCs’ ability to serve marginal populations and access cheap capital do not apply to well-organised, politically led public sector undertakings

Review of climate change impacts on marine fisheries in the UK and Ireland

1.Commercial fishing is an important socio-economic activity in coastal regions of the UK and Ireland. Ocean–atmospheric changes caused by greenhouse gas emissions are likely to affect future fish and shellfish production, and lead to increasing challenges in ensuring long-term sustainable fisheries management. 2.The paper reviews existing knowledge and understanding of the exposure of marine ecosystems to ocean-atmospheric changes, the consequences of these changes for marine fisheries in the UK and Ireland, and the adaptability of the UK and Irish fisheries sector. 3.Ocean warming is resulting in shifts in the distribution of exploited species and is affecting the productivity of fish stocks and underlying marine ecosystems. In addition, some studies suggest that ocean acidification may have large potential impacts on fisheries resources, in particular shell-forming invertebrates. 4.These changes may lead to loss of productivity, but also the opening of new fishing opportunities, depending on the interactions between climate impacts, fishing grounds and fleet types. They will also affect fishing regulations, the price of fish products and operating costs, which in turn will affect the economic performance of the UK and Irish fleets. 5.Key knowledge gaps exist in our understanding of the implications of climate and ocean chemistry changes for marine fisheries in the UK and Ireland, particularly on the social and economic responses of the fishing sectors to climate change. However, these gaps should not delay climate change mitigation and adaptation policy actions, particularly those measures that clearly have other ‘co-benefits’.

Projected impacts of climate change on marine fish and fisheries

This paper reviews current literature on the projected effects of climate change on marine fish and shellfish, their fisheries, and fishery-dependent communities throughout the northern hemisphere. The review addresses the following issues: (i) expected impacts on ecosystem productivity and habitat quantity and quality; (ii) impacts of changes in production and habitat on marine fish and shellfish species including effects on the community species composition, spatial distributions, interactions, and vital rates of fish and shellfish; (iii) impacts on fisheries and their associatedcommunities; (iv) implications for food security and associated changes; and (v) uncertainty andmodelling skill assessment. Climate change will impact fish and shellfish, their fisheries, and fishery-dependent communities through a complex suite of linked processes. Integrated interdisciplinary research teams are forming in many regions to project these complex responses. National and international marine research organizations serve a key role in the coordination and integration of research to accelerate the production of projections of the effects of climate change on marine ecosystems and to move towards a future where relative impacts by region could be compared on a hemispheric or global level. Eight research foci were identified that will improve the projections of climate impacts on fish, fisheries, and fishery-dependent communities.

Modelling a light-driven phytoplankton succession

We used a numerical model to investigate if and to what extent cellular photoprotective capacity accounts for succession and vertical distribution of marine phytoplankton species/groups. A model describing xanthophyll photoprotective activity in phytoplankton has been implemented in the European Regional Sea Ecosystem Model and applied at the station L4 in the Western English Channel. Primary producers were subdivided into three phytoplankton functional types defined in terms of their capacity to acclimate to different light-specific environments: low light (LL-type), high light (HL-type) and variable light (VL-type) adapted species. The LL-type is assumed to have low cellular level of xanthophyll-cycling pigments (PX) relative to the modelled photosynthetically active pigments (chlorophyll and fucoxanthin (FUCO) = PSP). The HL-type has high PX content relative to PSP while VL-type presents an intermediate PX to PSP ratio. Furthermore, the VL-type is capable of reversibly converting FUCO to PX and synthesizing new PX under high-light stress. In order to reproduce phytoplankton community succession with each of the three groups being dominant in different periods of the year, we had also to assume reduced grazing pressure on HL-adapted species. Model simulations realistically reproduce the observed seasonal patterns of pigments and nutrients highlighting the reasonability of the underpinning assumptions. Our model suggests that pigment-mediated photophysiology plays a primary role in determining the evolution of marine phytoplankton communities in the winter-spring period corresponding to the shoaling of the mixed layer and the increase of light intensity. Grazing selectivity however contributes to the phytoplankton community composition in summer.