Mobile Application as a Learning Aid for Nurses and Nursing Students to Identify and Care for Stroke Patients: Pretest and Posttest Results.

Cerebrovascular accident is a serious public health problem and requires the attention of professionals who can detect, diagnose, and provide care in a timely fashion. A quantitative quasi-experimental study was conducted using a mobile app called mSmartAVC for clinical evaluation of nursing care at the bedside. The study aimed at measuring the knowledge of nurses and nursing students in the detection and care of cerebrovascular accident. In this study, a total of 115 nurses from health services in the South of Brazil and 35 nursing students of a community university participated. The stages focused on development, modeling of clinical cases, problem-based learning, pretest (before) app use, and posttest (after) use of the app. The results of the pretest and posttest corrections showed a substantial statistical difference (P < .001), indicating a significant knowledge gain after the use of the app, particularly in terms of the detection scales and interpretation of the imaging tests. The mSmartAVC app used at the bedside supported decision-making for detection and nursing care. It was possible to confirm that the use of mobile apps plays an essential role as a learning tool for nurses and nursing students.

Dynamic model for biospeckle.

This paper reports the development of a simple dynamic microscopic model to describe the main features of the phenomenon known as dynamic speckle, or biospeckle. Biospeckle is an interference pattern formed when a biological surface is illuminated with coherent light. The dynamic characteristics of biospeckle have been investigated as possible tools for assessing the quality of biological products. Our model, despite its simplicity, was able to reproduce qualitatively the main features of biospeckle. We were able to correlate variations in a microscopic parameter associated with movement of the particles comprising the organic surface with changes in a macroscopic parameter that measures the change rate of a dynamic interference pattern. We showed that this correlation occurs only within a limited range of parameter microscope values. We also showed how our model was able to describe nonuniform surfaces composed of more than one type of particles.

Ajuste de modelos de platô de resposta via regressão isotônica / Response plateau models fitting via isotonic regression

Dentro do contexto nutricional, a suplementação de microminerais em rações para aves frequentemente é feita em quantidades superiores às exigidas na tentativa de assegurar o bom desempenho dos animais. Os experimentos do tipo dose resposta são muito comuns na determinação de níveis ótimos dos nutrientes na ração e contemplam a utilização de modelos de regressão para atingir tal objetivo. Porém, na análise de regressão usual, geralmente, não se usa uma informação a priori sobre uma possível relação de ordem na variável resposta. A regressão isotônica é um método de estimação por mínimos quadrados que gera estimativas que satisfazem a mesma ordenação dos dados. Na teoria da regressão isotônica, essa informação é utilizada de forma essencial e espera-se que a eficiência do ajuste seja aumentada quando se faz uso dela. Diante do exposto, o presente trabalho tem como objetivo utilizar uma metodologia de regressão isotônica, como uma forma alternativa para analisar dados de deposição de zinco (Zn) na tíbia de aves machos da linhagem Hubbard. No estudo, foram considerados os modelos de platô de resposta polinomial quadrático e não linear exponencial. Além desses modelos, também foi proposto o ajuste de um modelo logarítmico para os dados e a eficiência da metodologia foi avaliada por meio de um estudo de simulação Monte Carlo, considerando diferentes cenários para os valores paramétricos. A isotonização dos dados propiciou uma melhora em todos os avaliadores de qualidade de ajuste considerados no trabalho. Dentre os modelos utilizados, o logarítmico apresentou estimativas dos parâmetros mais coerentes com os valores relatados na literatura, para os dados de deposição de Zn na tíbia de aves machos.

Within the nutritional context, the supplementation of microminerals in bird food is often made in quantities exceeding those required in the attempt to ensure the proper performance of the animals. The experiments of type dosage x response are very common in the determination of levels of nutrients in optimal food balance and include the use of regression models to achieve this objective. Nevertheless, the regression analysis routine, generally, uses a priori information about a possible relationship between the response variable. The isotonic regression is a method of estimation by least squares that generates estimates which preserves data ordering. In the theory of isotonic regression this information is essential and it is expected to increase fitting efficiency. The objective of this work was to use an isotonic regression methodology, as an alternative way of analyzing data of Zn deposition in tibia of male birds of Hubbard lineage. We considered the models of plateau response of polynomial quadratic and linear exponential forms. In addition to these models, we also proposed the fitting of a logarithmic model to the data and the efficiency of the methodology was evaluated by Monte Carlo simulations, considering different scenarios for the parametric values. The isotonization of the data yielded an improvement in all the fitting quality parameters evaluated. Among the models used, the logarithmic presented estimates of the parameters more consistent with the values reported in literature.