Prevalence of health promotion programs in primary health care units in Brazil

OBJECTIVE Assessment of prevalence of health promotion programs in primary health care units within Brazil’s health system. METHODS We conducted a cross-sectional descriptive study based on telephone interviews with managers of primary care units. Of a total 42,486 primary health care units listed in the Brazilian Unified Health System directory, 1,600 were randomly selected. Care units from all five Brazilian macroregions were selected proportionally to the number of units in each region. We examined whether any of the following five different types of health promotion programs was available: physical activity; smoking cessation; cessation of alcohol and illicit drug use; healthy eating; and healthy environment. Information was collected on the kinds of activities offered and the status of implementation of the Family Health Strategy at the units. RESULTS Most units (62.0%) reported having in place three health promotion programs or more and only 3.0% reported having none. Healthy environment (77.0%) and healthy eating (72.0%) programs were the most widely available; smoking and alcohol use cessation were reported in 54.0% and 42.0% of the units. Physical activity programs were offered in less than 40.0% of the units and their availability varied greatly nationwide, from 51.0% in the Southeast to as low as 21.0% in the North. The Family Health Strategy was implemented in most units (61.0%); however, they did not offer more health promotion programs than others did. CONCLUSIONS Our study showed that most primary care units have in place health promotion programs. Public policies are needed to strengthen primary care services and improve training of health providers to meet the goals of the agenda for health promotion in Brazil.

Methods and challenges for the health impact assessment of vaccination programs in Latin America

ABSTRACT OBJECTIVE To describe methods and challenges faced in the health impact assessment of vaccination programs, focusing on the pneumococcal conjugate and rotavirus vaccines in Latin America and the Caribbean. METHODS For this narrative review, we searched for the terms "rotavirus", "pneumococcal", "conjugate vaccine", "vaccination", "program", and "impact" in the databases Medline and LILACS. The search was extended to the grey literature in Google Scholar. No limits were defined for publication year. Original articles on the health impact assessment of pneumococcal and rotavirus vaccination programs in Latin America and the Caribbean in English, Spanish or Portuguese were included. RESULTS We identified 207 articles. After removing duplicates and assessing eligibility, we reviewed 33 studies, 25 focusing on rotavirus and eight on pneumococcal vaccination programs. The most frequent studies were ecological, with time series analysis or comparing pre- and post-vaccination periods. The main data sources were: health information systems; population-, sentinel- or laboratory-based surveillance systems; statistics reports; and medical records from one or few health care services. Few studies used primary data. Hospitalization and death were the main outcomes assessed. CONCLUSIONS Over the last years, a significant number of health impact assessments of pneumococcal and rotavirus vaccination programs have been conducted in Latin America and the Caribbean. These studies were carried out few years after the programs were implemented, meet the basic methodological requirements and suggest positive health impact. Future assessments should consider methodological issues and challenges arisen in these first studies conducted in the region.

A debugging engine for parallel and distributed programs

Dissertação apresentada para a obtenção do Grau de Doutor em Informática pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia.

Digital-domain self-calibration technique for video-rate pipeline A/D converters using Gaussian white noise

Electronics Letters Vol.38, nº 19

New simple digital self-calibration technique for pipeline ADCs using the internal thermal noise

IEEE International Symposium on Circuits and Systems, pp. 232 – 235, Seattle, EUA

An example-based generator of XSLT programs

XSLT is a powerful and widely used language for transforming XML documents. However, its power and complexity can be overwhelming for novice or infrequent users, many of whom simply give up on using this language. On the other hand, many XSLT programs of practical use are simple enough to be automatically inferred from examples of source and target documents. An inferred XSLT program is seldom adequate for production usage but can be used as a skeleton of the final program, or at least as scaffolding in the process of coding it. It should be noted that the authors do not claim that XSLT programs, in general, can be inferred from examples. The aim of Vishnu—the XSLT generator engine described in this chapter—is to produce XSLT programs for processing documents similar to the given examples and with enough readability to be easily understood by a programmer not familiar with the language. The architecture of Vishnu is composed by a graphical editor and a programming engine. In this chapter, the authors focus on the editor as a GWT Web application where the programmer loads and edits document examples and pairs their content using graphical primitives. The programming engine receives the data collected by the editor and produces an XSLT program.

Low-power 6-bit 1-GS/s two-channel pipeline ADC with open-loop amplification using amplifiers with local-feedback

IEEE International Symposium on Circuits and Systems, pp. 2258 – 2261, Seattle, EUA

Design and testing of a radiation hardened 13-bit 80 MS/s pipeline ADC implemented in a 90nm standard CMOS process

Second International Workshop on Analog and Mixed Signal Integrated Circuits for Space Applications (AMICSA 2008), Sintra, Portugal, Setembro de 2008

Efficient digital self-calibration of video-rate pipeline ADCs using white gaussian noise

Proceedings of IEEE, ISCAS 2003, Vol.I, pp. 877-880

Environmental indicator frameworks to design and assess environmental monitoring programs

Impact Assessment and Project Appraisal, vol. 22, n.1, March 2004, p. 47–62

Decision Support Concerning Demand Response Programs Design and Use – A Conceptual Framework and Simulation Tool

Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.

Optimizing memory transactions for large-scale programs

Even though Software Transactional Memory (STM) is one of the most promising approaches to simplify concurrent programming, current STM implementations incur significant overheads that render them impractical for many real-sized programs. The key insight of this work is that we do not need to use the same costly barriers for all the memory managed by a real-sized application, if only a small fraction of the memory is under contention lightweight barriers may be used in this case. In this work, we propose a new solution based on an approach of adaptive object metadata (AOM) to promote the use of a fast path to access objects that are not under contention. We show that this approach is able to make the performance of an STM competitive with the best fine-grained lock-based approaches in some of the more challenging benchmarks. (C) 2015 Elsevier Inc. All rights reserved.

Static detection of anomalies in transactional memory programs

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

Consumers Performance Evaluation of the Participation in Demand Response Programs Using Baseline Methods

Demand response has gain increasing importance in the context of competitive electricity markets environment. The use of demand resources is also advantageous in the context of smart grid operation. In addition to the need of new business models for integrating demand response, adequate methods are necessary for an accurate determination of the consumers’ performance evaluation after the participation in a demand response event. The present paper makes a comparison between some of the existing baseline methods related to the consumers’ performance evaluation, comparing the results obtained with these methods and also with a method proposed by the authors of the paper. A case study demonstrates the application of the referred methods to real consumption data belonging to a consumer connected to a distribution network.

Incentive-based demand response programs designed by asset-light retailers for day-ahead market

Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand.