Software Application That Evaluates the Diagnostic Accuracy of Nursing Students

PURPOSE: Apply the educational software Fuzzy Kitten with undergraduate Brazilian nursing students. METHODS: This software, based on fuzzy logic, generates performance scores that evaluate the ability to identify defining characteristics/risk factors present in clinical cases, relate them with nursing diagnoses, and determine the diagnoses freely or using a decision support model. FINDINGS: There were differences in student performance compared to the year of the course. The time to perform the activity did not present a significant relation to the performance. The students' scores in the diagnoses indicated by the model was superior (p = .01). CONCLUSIONS: The software was able to evaluate the diagnostic accuracy of students. IMPLICATIONS: The software enables an objective evaluation of diagnostic accuracy.

Hybrid Water Demand Forecasting Model Associating Artificial Neural Network with Fourier Series

This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.

Linear matrix inequality-based robust model predictive control for time-delayed systems

This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.

Relationship among social support, treatment adherence and metabolic control of diabetes mellitus patients

This cross-sectional and quantitative study aimed to analyze the relationship among social support, adherence to non-pharmacological (diet and physical exercise) and pharmacological treatments (insulin and/or oral anti-diabetic medication) and clinical and metabolic control of 162 type 2 diabetes mellitus patients. Data were collected through instruments validated for Brazil. Social support was directly correlated with treatment adherence. Adherence to non-pharmacological treatment was inversely correlated with body mass index, and medication adherence was inversely correlated with diastolic blood pressure. There were no associations between social support and clinical and metabolic control variables. Findings indicate that social support can be useful to achieve treatment adherence. Studies with other designs should be developed to broaden the analysis of relations between social support and other variables.

Closed-loop stable model predictive control of integrating systems with dead time

Model predictive control (MPC) applications in the process industry usually deal with process systems that show time delays (dead times) between the system inputs and outputs. Also, in many industrial applications of MPC, integrating outputs resulting from liquid level control or recycle streams need to be considered as controlled outputs. Conventional MPC packages can be applied to time-delay systems but stability of the closed loop system will depend on the tuning parameters of the controller and cannot be guaranteed even in the nominal case. In this work, a state space model based on the analytical step response model is extended to the case of integrating time systems with time delays. This model is applied to the development of two versions of a nominally stable MPC, which is designed to the practical scenario in which one has targets for some of the inputs and/or outputs that may be unreachable and zone control (or interval tracking) for the remaining outputs. The controller is tested through simulation of a multivariable industrial reactor system. (C) 2012 Elsevier Ltd. All rights reserved.

A Novel Method of Evaluating Ureteropelvic Junction Obstruction: Dynamic Near Infrared Fluorescence Imaging Compared to Standard Modalities to Assess Urinary Obstruction in a Swine Model

Purpose: Dynamic near infrared fluorescence imaging of the urinary tract provides a promising way to diagnose ureteropelvic junction obstruction. Initial studies demonstrated the ability to visualize urine flow and peristalsis in great detail. We analyzed the efficacy of near infrared imaging in evaluating ureteropelvic junction obstruction, renal involvement and the anatomical detail provided compared to conventional imaging modalities. Materials and Methods: Ten swine underwent partial or complete unilateral ureteral obstruction. Groups were survived for the short or the long term. Imaging was performed with mercaptoacetyltriglycine diuretic renogram, magnetic resonance urogram, excretory urogram, ultrasound and near infrared imaging. Scoring systems for ureteropelvic junction obstruction were developed for magnetic resonance urogram and near infrared imaging. Physicians and medical students graded ureteropelvic junction obstruction based on magnetic resonance urogram and near infrared imaging results. Results: Markers of vascular and urinary dynamics were quantitatively consistent among control renal units. The same markers were abnormal in obstructed renal units with significantly different times of renal phase peak, start of pelvic phase and start of renal uptake. Such parameters were consistent with those obtained with mercaptoacetyltriglycine diuretic renography. Near infrared imaging provided live imaging of urinary flow, which was helpful in identifying the area of obstruction for surgical planning. Physicians and medical students categorized the degree of obstruction appropriately for fluorescence imaging and magnetic resonance urogram. Conclusions: Near infrared imaging offers a feasible way to obtain live, dynamic images of urine flow and ureteral peristalsis. Qualitative and quantitative parameters were comparable to those of conventional imaging. Findings support fluorescence imaging as an accurate, easy to use method of diagnosing ureteropelvic junction obstruction.

Low fatness, reduced fat intake and adequate plasmatic concentrations of LDL-cholesterol are associated with high bone mineral density in women: a cross-sectional study with control group

Background: Several parameters are associated with high bone mineral density (BMD), such as overweight, black background, intense physical activity (PA), greater calcium intake and some medications. The objectives are to evaluate the prevalence and the main aspects associated with high BMD in healthy women. Methods: After reviewing the database of approximately 21,500 BMD scans performed in the metropolitan area of Sao Paulo, Brazil, from June 2005 to October 2010, high BMD (over 1400 g/cm(2) at lumbar spine and/or above 1200 g/cm2 at femoral neck) was found in 421 exams. Exclusion criteria were age below 30 or above 60 years, black ethnicity, pregnant or obese women, disease and/or medications known to interfere with bone metabolism. A total of 40 women with high BMD were included and matched with 40 healthy women with normal BMD, paired to weight, age, skin color and menopausal status. Medical history, food intake and PA were assessed through validated questionnaires. Body composition was evaluated through a GE-Lunar DPX MD + bone densitometer. Radiography of the thoracic and lumbar spine was carried out to exclude degenerative alterations or fractures. Biochemical parameters included both lipid and hormonal profiles, along with mineral and bone metabolism. Statistical analysis included parametric and nonparametric tests and linear regression models. P < 0.05 was considered significant. Results: The mean age was 50.9 (8.3) years. There was no significant difference between groups in relation to PA, smoking, intake of calcium and vitamin D, as well as laboratory tests, except serum C-telopeptide of type I collagen (s-CTX), which was lower in the high BMD group (p = 0.04). In the final model of multivariate regression, a lower fat intake and body fatness as well a better profile of LDL-cholesterol predicted almost 35% of high BMD in women. (adjusted R2 = 0.347; p < 0.001). In addition, greater amounts of lean mass and higher IGF-1 serum concentrations played a protective role, regardless age and weight. Conclusion: Our results demonstrate the potential deleterious effect of lipid metabolism-related components, including fat intake and body fatness and worse lipid profile, on bone mass and metabolism in healthy women.

Reference model for implementing an MRP system in a highly diverse component and seasonal lean production environment

Companies are currently choosing to integrate logics and systems to achieve better solutions. These combinations also include companies striving to join the logic of material requirement planning (MRP) system with the systems of lean production. The purpose of this article was to design an MRP as part of the implementation of an enterprise resource planning (ERP) in a company that produces agricultural implements, which has used the lean production system since 1998. This proposal is based on the innovation theory, theory networks, lean production systems, ERP systems and the hybrid production systems, which use both components and MRP systems, as concepts of lean production systems. The analytical approach of innovation networks enables verification of the links and relationships among the companies and departments of the same corporation. The analysis begins with the MRP implementation project carried out in a Brazilian metallurgical company and follows through the operationalisation of the MRP project, until its production stabilisation. The main point is that the MRP system should help the company's operations with regard to its effective agility to respond in time to demand fluctuations, facilitating the creation process and controlling the branch offices in other countries that use components produced in the matrix, hence ensuring more accurate estimates of stockpiles. Consequently, it presents the enterprise knowledge development organisational modelling methodology in order to represent further models (goals, actors and resources, business rules, business process and concepts) that should be included in this MRP implementation process for the new configuration of the production system.

Factors associated with maternal intrapartum transfers from a freestanding birth centre in Sao Paulo, Brazil: A case control study

Objectives: to identify factors associated with maternal intrapartum transfer from a freestanding birth centre to hospital. Design: case-control study with retrospective data collection. Participants and settings: cases included all 111 women transferred from a freestanding birth centre in Sao Paulo to the referral hospital, from March 2002 to December 2009. The controls were 456 women who gave birth in the birth centre during the same period who were not transferred, randomly selected with four controls for each case. Methods: data were obtained from maternal records. Factors associated with maternal intrapartum transfers were initially analysed using a chi(2) test of association. Variables with p < 0.20 were then included in multivariate analyses. A multiple logistic regression model was built using stepwise forward selection; variables which reached statistical significance at p < 0.05 were considered to be independently associated with maternal transfer. Findings: during the study data collection period, 111(4%) of 2,736 women admitted to the centre were transferred intrapartum. Variables identified as independently associated factors for intrapartum transfer included nulliparity (OR 5.1, 95% CI 2.7-9.8), maternal age >= 35 years (OR 5.4, 95% CI 2.1-13.4), not having a partner (OR 2.8, 95% CI 1.5-5.3), cervical dilation <= 3 cm on admission to the birth centre (OR 1.9, 95% CI 1.1-3.2) and between 5 and 12 antenatal appointments at the birth centre (OR 3.8, 95% CI 1.9-7.5). In contrast, a low correlation between fundal height and pregnancy gestation (OR 0.3, 95% CI 0.2-0.6) appeared to be protective against transfer. Conclusions and implications for practice: identifying factors associated with maternal intrapartum transfer could support decision making by women considering options for place of birth, and support the content of appropriate information about criteria for admission to a birth centre. Findings add to the evidence base to support identification of women in early labour who may experience later complications and could support timely implementation of appropriate interventions associated with reducing transfer rates. (C) 2012 Elsevier Ltd. All rights reserved.

Biogeographic and diversification patterns of Neotropical Troidini butterflies (Papilionidae) support a museum model of diversity dynamics for Amazonia

Background: The temporal and geographical diversification of Neotropical insects remains poorly understood because of the complex changes in geological and climatic conditions that occurred during the Cenozoic. To better understand extant patterns in Neotropical biodiversity, we investigated the evolutionary history of three Neotropical swallowtail Troidini genera (Papilionidae). First, DNA-based species delimitation analyses were conducted to assess species boundaries within Neotropical Troidini using an enlarged fragment of the standard barcode gene. Molecularly delineated species were then used to infer a time-calibrated species-level phylogeny based on a three-gene dataset and Bayesian dating analyses. The corresponding chronogram was used to explore their temporal and geographical diversification through distinct likelihood-based methods. Results: The phylogeny for Neotropical Troidini was well resolved and strongly supported. Molecular dating and biogeographic analyses indicate that the extant lineages of Neotropical Troidini have a late Eocene (33-42 Ma) origin in North America. Two independent lineages (Battus and Euryades + Parides) reached South America via the GAARlandia temporary connection, and later became extinct in North America. They only began substantive diversification during the early Miocene in Amazonia. Macroevolutionary analysis supports the "museum model" of diversification, rather than Pleistocene refugia, as the best explanation for the diversification of these lineages. Conclusions: This study demonstrates that: (i) current Neotropical biodiversity may have originated ex situ; (ii) the GAARlandia bridge was important in facilitating invasions of South America; (iii) colonization of Amazonia initiated the crown diversification of these swallowtails; and (iv) Amazonia is not only a species-rich region but also acted as a sanctuary for the dynamics of this diversity. In particular, Amazonia probably allowed the persistence of old lineages and contributed to the steady accumulation of diversity over time with constant net diversification rates, a result that contrasts with previous studies on other South American butterflies.

A Robust Structural PGN Model for Control of Cell-Cycle Progression Stabilized by Negative Feedbacks

The cell division cycle comprises a sequence of phenomena controlled by a stable and robust genetic network. We applied a probabilistic genetic network (PGN) to construct a hypothetical model with a dynamical behavior displaying the degree of robustness typical of the biological cell cycle. The structure of our PGN model was inspired in well-established biological facts such as the existence of integrator subsystems, negative and positive feedback loops, and redundant signaling pathways. Our model represents genes interactions as stochastic processes and presents strong robustness in the presence of moderate noise and parameters fluctuations. A recently published deterministic yeast cell-cycle model does not perform as well as our PGN model, even upon moderate noise conditions. In addition, self stimulatory mechanisms can give our PGN model the possibility of having a pacemaker activity similar to the observed in the oscillatory embryonic cell cycle.

Numerical analysis of control surface effects on AUV

Computational fluid dynamics, CFD, is becoming an essential tool in the prediction of the hydrodynamic efforts and flow characteristics of underwater vehicles for manoeuvring studies. However, when applied to the manoeuvrability of autonomous underwater vehicles, AUVs, most studies have focused on the de- termination of static coefficients without considering the effects of the vehicle control surface deflection. This paper analyses the hydrodynamic efforts generated on an AUV considering the combined effects of the control surface deflection and the angle of attack using CFD software based on the Reynolds-averaged Navier–Stokes formulations. The CFD simulations are also independently conducted for the AUV bare hull and control surface to better identify their individual and interference efforts and to validate the simulations by comparing the experimental results obtained in a towing tank. Several simulations of the bare hull case were conducted to select the k –ω SST turbulent model with the viscosity approach that best predicts its hydrodynamic efforts. Mesh sensitivity analyses were conducted for all simulations. For the flow around the control surfaces, the CFD results were analysed according to two different methodologies, standard and nonlinear. The nonlinear regression methodology provides better results than the standard methodology does for predicting the stall at the control surface. The flow simulations have shown that the occurrence of the control surface stall depends on a linear relationship between the angle of attack and the control surface deflection. This type of information can be used in designing the vehicle’s autopilot system.