Maternal decision on obtaining prenatal care: a study in Brazil

Objective: to address the social aspects of pregnancy and the views of pregnant women regarding prenatal assistance in Brazil. Design: this qualitative study was focused on describing the Social Representations of prenatal care held by pregnant women. The discourse of the collective subject (DCS) framework was used to analyse the data collected, within the theoretical background of social representations, as proposed and developed by Serge Moscovici. Participants and setting: 21 pregnant women who were users of the publicly funded Brazilian unified health-care system and resided in the area served by its family health programme in a low- to middle-income neighbourhood on the outskirts of Campo Grande, the capital of the state of Mato Grosso do Sul, in southwestern Brazil. Data were collected by conducting in-depth, face-to-face interviews from January to October 2006. Findings: all participants were married. Formal education of the participants was less than five years in four cases, between five and eight years in six cases, and greater than 11 years in 10 cases. Nine participants had informal jobs and earned up to US$ 200 per month, four paricipants had administrative jobs and earned over US$ 500 per month, and eight participants did not work. No specific racial/ethnic background predominated. Lack of adherence to prenatal care allowed for the identification of two DCS themes: `organisation of prenatal care services` and `lifestyle features`. Key conclusions: the respondents were found to have negative feelings about pregnancy which manifest as many fears, including the fear of harming their children`s health, of being punished during labour, and of being reprimanded by health-care professionals for overlooking their prenatal care, in addition to the insecurity felt towards the infant and self. Implications for practice: the findings reveal that communication between pregnant women and healthcare professionals has been ineffective and that prenatal care has not been effective for the group interviewed-features that are likely to be found among other low- to middle-income groups living elsewhere in Brazil. (C) 2009 Elsevier Ltd. All rights reserved.

Friere`s Dialogic Concept Enables Family Health Program Teams to Incorporate Health Promotion

Objective The study analyzes the possibility of incorporating health promotion measures into the work processes of Family Health Program teams at a primary health care clinic in Brazil. Design and Sample We used the participatory research concept developed in 1968 by Freire. The study sample comprised the end-users of the health care system, together with 3 multidisciplinary teams. A total of 77 health care users and 55 health professionals participated in the study. Measures Culture circles composed of health care professionals, and users from different areas investigated generative topics, encoded/decoded topics, and engaged in critical probing for clarification. Topics affecting quality of life and health were heuristically evaluated. Results Although most topics were related to changing the focus of health care facilities, some were related to subsidizing community-based interventions, improving environmental strategies, individual skills, and public policies. Incorporating the novel health promotion measures and creating an expanded full-treatment clinic are important steps toward that goal. Conclusions Topics that can stimulate dialogue among the members of the culture circles include creating an environment of closer cultural contact, with repercussions for work processes, family health models, and general health models, as well as the inclusion of social aspects in the decision-making processes related to health issues that affect the living conditions of the population.

An approach based on neural networks for estimation and generalization of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behaviour. In this paper, a system based on artificial neural networks is developed to overcome the problems usually found in the conventional mathematical models. More specifically, the developed system uses an artificial neural network that simulates the behaviour of the crossflow filtration process in a robust way. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the neural approach. Simulation results are presented to justify the validity of the proposed approach. (C) 2007 Elsevier B.V. All rights reserved.

Financial distress, financial constraint and investment decision: Evidence from Brazil

This paper analyses the presence of financial constraint in the investment decisions of 367 Brazilian firms from 1997 to 2004, using a Bayesian econometric model with group-varying parameters. The motivation for this paper is the use of clustering techniques to group firms in a totally endogenous form. In order to classify the firms we used a hybrid clustering method, that is, hierarchical and non-hierarchical clustering techniques jointly. To estimate the parameters a Bayesian approach was considered. Prior distributions were assumed for the parameters, classifying the model in random or fixed effects. Ordinate predictive density criterion was used to select the model providing a better prediction. We tested thirty models and the better prediction considers the presence of 2 groups in the sample, assuming the fixed effect model with a Student t distribution with 20 degrees of freedom for the error. The results indicate robustness in the identification of financial constraint when the firms are classified by the clustering techniques. (C) 2010 Elsevier B.V. All rights reserved.

Microbial processes and bacterial populations associated to anaerobic treatment of sulfate-rich wastewater

A pilot-scale (1.2 m(3)) anaerobic sequencing batch biofilm reactor (ASBBR) containing mineral coal for biomass attachment was fed with sulfate-rich wastewater at increasing sulfate concentrations. Ethanol was used as the main organic source. Tested COD/sulfate ratios were of 1.8 and 1.5 for sulfate loading rates of 0.65-1.90 kgSO(4)(2-)/cycle (48 h-cycle) or of 1.0 in the trial with 3.0 gSO(4)(2-) l(-1). Sulfate removal efficiencies observed in all trials were as high as 99%. Molecular inventories indicated a shift on the microbial composition and a decrease on species diversity with the increase of sulfate concentration. Beta-proteobacteria species affiliated with Aminomonas spp. and Thermanaerovibrio spp. predominated at 1.0 gSO(4)(2-) l(-1). At higher sulfate concentrations the predominant bacterial group was Delta-proteobacteria mainly Desulfovibrio spp. and Desulfomicrobium spp. at 2.0 gSO(4)(2-) l(-1), whereas Desulfurella spp. and Coprothermobacter spp. predominated at 3.0 gSO(4)(2-) l(-1). These organisms have been commonly associated with sulfate reduction producing acetate, sulfide and sulfur. Methanogenic archaea(Methanosaeta spp.)was found at 1.0 and 2.0 gSO(4)(2-) l(-1). Additionally, a simplified mathematical model was used to infer on metabolic pathways of the biomass involved in sulfate reduction. (C) 2009 Elsevier Ltd. All rights reserved.

Feasibility of a Sequencing Reactor Operated in Batch and Fed-batch Mode Applied to Nitrification and Denitrification Processes

The objective of this work was to study the operational feasibility of nitrification and denitrification processes in a mechanically stirred sequencing batch reactor (SBR) operated in batch and fed-batch mode. The reactor was equipped with a draft-tube to improve mass transfer and contained dispersed (aerobic) and granulated (anaerobic) biomass. The following reactor variables were adjusted: aeration time during the nitrification step; dissolved oxygen concentration, feed time defining batch and fed-batch phases, concentration of external carbon source used as electron donor during the denitrification stage and volumetric ammonium nitrogen load in the influent. The reactor (5 L volume) was maintained at 30 +/- 1 degrees C and treated either 1.0 or 1.5 L wastewater in 8-h cycles. Ammonium nitrogen concentrations assessed were: 50 (condition 1) and 100 mgN-NH(4)(+).L(-1) (condition 2), resulting in 29 and 67 mgN-NH(4)(+).L-1-d(-1), respectively. A synthetic medium and ethanol were used as external carbon sources (ECS). Total nitrogen removal efficiencies were 94.4 and 95.9% when the reactor was operated under conditions 1 and 2, respectively. Low nitrite (0.2 and 0.3 mgN-NO(2)(-).L(-1), respectively) and nitrate (0.01 and 0.3 mgN-NO(3)(-).L(-1), respectively) concentrations were detected in the effluent and ammonium nitrogen removal efficiencies were 97.6% and 99.6% under conditions 1 and 2, respectively.

Denoising swallowing sound to improve the evaluator`s qualitative analysis

Swallowing dynamics involves the coordination and interaction of several muscles and nerves which allow correct food transport from mouth to stomach without laryngotracheal penetration or aspiration. Clinical swallowing assessment depends on the evaluator`s knowledge of anatomic structures and of neurophysiological processes involved in swallowing. Any alteration in those steps is denominated oropharyngeal dysphagia, which may have many causes, such as neurological or mechanical disorders. Videofluoroscopy of swallowing is presently considered to be the best exam to objectively assess the dynamics of swallowing, but the exam needs to be conducted under certain restrictions, due to patient`s exposure to radiation, which limits periodical repetition for monitoring swallowing therapy. Another method, called cervical auscultation, is a promising new diagnostic tool for the assessment of swallowing disorders. The potential to diagnose dysphagia in a noninvasive manner by assessing the sounds of swallowing is a highly attractive option for the dysphagia clinician. Even so, the captured sound has an amount of noise, which can hamper the evaluator`s decision. In that way, the present paper proposes the use of a filter to improve the quality of audible sound and facilitate the perception of examination. The wavelet denoising approach is used to decompose the noisy signal. The signal to noise ratio was evaluated to demonstrate the quantitative results of the proposed methodology. (C) 2007 Elsevier Ltd. All rights reserved.

Decision making in fuzzy environment and multicriteria power engineering problems

This paper presents results of research into the use of the Bellman-Zadeh approach to decision making in a fuzzy environment for solving multicriteria power engineering problems. The application of the approach conforms to the principle of guaranteed result and provides constructive lines in computationally effective obtaining harmonious solutions on the basis of solving associated maxmin problems. The presented results are universally applicable and are already being used to solve diverse classes of power engineering problems. It is illustrated by considering problems of power and energy shortage allocation, power system operation, optimization of network configuration in distribution systems, and energetically effective voltage control in distribution systems. (c) 2011 Elsevier Ltd. All rights reserved.

A flexible consensus scheme for multicriteria group decision making under linguistic assessments

The present paper proposes a flexible consensus scheme for group decision making, which allows one to obtain a consistent collective opinion, from information provided by each expert in terms of multigranular fuzzy estimates. It is based on a linguistic hierarchical model with multigranular sets of linguistic terms, and the choice of the most suitable set is a prerogative of each expert. From the human viewpoint, using such model is advantageous, since it permits each expert to utilize linguistic terms that reflect more adequately the level of uncertainty intrinsic to his evaluation. From the operational viewpoint, the advantage of using such model lies in the fact that it allows one to express the linguistic information in a unique domain, without losses of information, during the discussion process. The proposed consensus scheme supposes that the moderator can interfere in the discussion process in different ways. The intervention can be a request to any expert to update his opinion or can be the adjustment of the weight of each expert`s opinion. An optimal adjustment can be achieved through the execution of an optimization procedure that searches for the weights that maximize a corresponding soft consensus index. In order to demonstrate the usefulness of the presented consensus scheme, a technique for multicriteria analysis, based on fuzzy preference relation modeling, is utilized for solving a hypothetical enterprise strategy planning problem, generated with the use of the Balanced Scorecard methodology. (C) 2009 Elsevier Inc. All rights reserved.

Multicriteria analysis in decision making under information uncertainty

This paper presents results of research related to multicriteria decision making under information uncertainty. The Bell-man-Zadeh approach to decision making in a fuzzy environment is utilized for analyzing multicriteria optimization models (< X, M > models) under deterministic information. Its application conforms to the principle of guaranteed result and provides constructive lines in obtaining harmonious solutions on the basis of analyzing associated maxmin problems. This circumstance permits one to generalize the classic approach to considering the uncertainty of quantitative information (based on constructing and analyzing payoff matrices reflecting effects which can be obtained for different combinations of solution alternatives and the so-called states of nature) in monocriteria decision making to multicriteria problems. Considering that the uncertainty of information can produce considerable decision uncertainty regions, the resolving capacity of this generalization does not always permit one to obtain unique solutions. Taking this into account, a proposed general scheme of multicriteria decision making under information uncertainty also includes the construction and analysis of the so-called < X, R > models (which contain fuzzy preference relations as criteria of optimality) as a means for the subsequent contraction of the decision uncertainty regions. The paper results are of a universal character and are illustrated by a simple example. (c) 2007 Elsevier Inc. All rights reserved.

Equivalent Carbon Dioxide Capture and Storage Processes in Offshore Petroleum Production Facilities

The present study approaches the economic and technical evaluation of equivalent carbon dioxide (CO(2) eqv.) capture and storage processes, considered in a proposal case compared to a base case. The base case considers an offshore petroleum production facility, with high CO(2) content (4 vol%) in the composition of the produced gas and both CO(2) and natural gas emissions to the atmosphere, called CO(2) eqv. emissions. The results obtained with this study, by using a Hysys process simulator, showed a CO(2) emission reduction of 65% comparing the proposal case in relation to the base case.

Knowledge transfer in product development processes: A case study in small and medium enterprises (SMEs) of the metal-mechanic sector from Sao Paulo, Brazil

This paper reports a research that evaluated the product development methodologies used in Brazilian small and medium-sized metal-mechanic enterprises (SMEs), in a specific region of Sao Paulo. The tool used for collecting the data was a questionnaire, which was developed and applied through interviews conducted by the researchers in 32 companies. The main focus of this paper can be condensed in the synthesis-question ""Is only the company responsible for the development?"" which was analyzed thoroughly. The results obtained from this analysis were evaluated directly (through the respective percentages of answers) and statistically (through the search of an index which demonstrates if two questions are related). The results point to a degree of maturity in SMEs, which allows product development to be conducted in cooperation networks. (C) 2007 Elsevier Ltd. All rights reserved.

Risk-based decision making method for maintenance policy selection of thermal power plant equipment

This study presents a decision-making method for maintenance policy selection of power plants equipment. The method is based on risk analysis concepts. The method first step consists in identifying critical equipment both for power plant operational performance and availability based on risk concepts. The second step involves the proposal of a potential maintenance policy that could be applied to critical equipment in order to increase its availability. The costs associated with each potential maintenance policy must be estimated, including the maintenance costs and the cost of failure that measures the critical equipment failure consequences for the power plant operation. Once the failure probabilities and the costs of failures are estimated, a decision-making procedure is applied to select the best maintenance policy. The decision criterion is to minimize the equipment cost of failure, considering the costs and likelihood of occurrence of failure scenarios. The method is applied to the analysis of a lubrication oil system used in gas turbines journal bearings. The turbine has more than 150 MW nominal output, installed in an open cycle thermoelectric power plant. A design modification with the installation of a redundant oil pump is proposed for lubricating oil system availability improvement. (C) 2009 Elsevier Ltd. All rights reserved.

MODELLING AND CONTROL OF ERSW PROCESSES BY NEURONAL NETWORK

A study on the use of artificial intelligence (AI) techniques for the modelling and subsequent control of an electric resistance spot welding process (ERSW) is presented. The ERSW process is characterized by the coupling of thermal, electrical, mechanical, and metallurgical phenomena. For this reason, early attempts to model it using computational methods established as the methods of finite differences, finite element, and finite volumes, ask for simplifications that lead the model obtained far from reality or very costly in terms of computational costs, to be used in a real-time control system. In this sense, the authors have developed an ERSW controller that uses fuzzy logic to adjust the energy transferred to the weld nugget. The proposed control strategies differ in the speed with which it reaches convergence. Moreover, their application for a quality control of spot weld through artificial neural networks (ANN) is discussed.

Sequential decision making with partially ordered preferences

This paper presents new insights and novel algorithms for strategy selection in sequential decision making with partially ordered preferences; that is, where some strategies may be incomparable with respect to expected utility. We assume that incomparability amongst strategies is caused by indeterminacy/imprecision in probability values. We investigate six criteria for consequentialist strategy selection: Gamma-Maximin, Gamma-Maximax, Gamma-Maximix, Interval Dominance, Maximality and E-admissibility. We focus on the popular decision tree and influence diagram representations. Algorithms resort to linear/multilinear programming; we describe implementation and experiments. (C) 2010 Elsevier B.V. All rights reserved.