Factors influencing Intensive Care Units nurses in end-of-life decisions

OBJECTIVETo identify the factors that influence the Intensive Care Unit nurse in the decision-making process in end-of-life situations.METHODEthnographic case study, which used the theoretical framework of medical anthropology. Data were collected through semi-structured interviews with 10 nurses.RESULTSThe inductive thematic analysis enabled us to identify four themes:The cultural context of the Intensive Care Unit: decision-making in situations of end-of-life; Beliefs and subjectivity of care in end-of-life situations; Professional experience and context characteristics of end-of-life care situations; and Humanization practices in end-of-life situations: the patient and family centered care.CONCLUSIONProfessional maturity, the ability to transmit information and the ability to negotiate are directly related to the inclusion of nurses in the decision-making process.

Dysfunctional psychological responses among Intensive Care Unit nurses: a systematic review of the literature

AbstractOBJECTIVETo systematically review evidence on dysfunctional psychological responses of Intensive Care Units nurses (ICUNs), with focus on anxiety and depressive symptoms and related factors.METHODA literature search was performed in CINAHL, PubMed and Scopus databases, from 1999 to present, along with a critical appraisal and synthesis of all relevant data. The following key words, separately and in combination, were used: "mental status" "depressive symptoms" "anxiety" "ICU nurses" "PTSD" "burnout" "compassion fatigue" "psychological distress".RESULTSThirteen quantitative studies in English and Greek were included. The results suggested increased psychological burden in ICUNs compared to other nursing specialties, as well as to the general population.CONCLUSIONSStudies investigating psychological responses of ICUNs are limited, internationally. Future longitudinal and intervention studies will contribute to a better understanding of the phenomenon.

Copper, zinc and manganese in soils of two watersheds in Santa Catarina with intensive use of pig slurry

Systematic pig slurry application to crop soils may lead to the accumulation of heavy metals in regions with intensive pig raising. The aim of this study was to evaluate the accumulation of Cu, Zn and Mn in soils under systematic pig slurry application. For this purpose, soil samples were collected from two of the most representative watersheds of Santa Catarina where the predominant activity is pig raising. In each watershed, 12 properties were chosen to evaluate the different systems of pig husbandry (complete cycle (CC), farrowing (FaU) and finishing units (FiU)). Based on information of the producers, soil samples were collected in areas with and without systematic manure application. To determine the total Cu, Zn and Mn content in soils and manure, a methodology proposed by the Environmental Protection Agency of the United States (USEPA), method nº 3050B, was used. For the available heavy metal content, Cu and Zn was extracted with HCl 0.1 mol L-1 and Mn with KCl 1 mol L-1. Data were subjected to multivariate analysis, using the canonical discriminant analysis to identify the metals that best differentiate the soils studied within each swine housing system. Successive pig slurry applications cause an increase in Cu, Zn and Mn availability in the soil and this indicates the need for monitoring of the metal concentrations over time. The critical values of Cu in the soil can be reached and exceeded more rapidly than Zn. The results showed that the soil type may be one of the attribute underlying the determination of public policies in pig raising and waste management because soils such as Inceptisols were shown to be more prone to possible contamination since they may more rapidly reach total critical Cu levels.

Three-dimensional interpolation of soil data: fertility and pedomorphological features in southern Brazil

The graphical representation of spatial soil properties in a digital environment is complex because it requires a conversion of data collected in a discrete form onto a continuous surface. The objective of this study was to apply three-dimension techniques of interpolation and visualization on soil texture and fertility properties and establish relationships with pedogenetic factors and processes in a slope area. The GRASS Geographic Information System was used to generate three-dimensional models and ParaView software to visualize soil volumes. Samples of the A, AB, BA, and B horizons were collected in a regular 122-point grid in an area of 13 ha, in Pinhais, PR, in southern Brazil. Geoprocessing and graphic computing techniques were effective in identifying and delimiting soil volumes of distinct ranges of fertility properties confined within the soil matrix. Both three-dimensional interpolation and the visualization tool facilitated interpretation in a continuous space (volumes) of the cause-effect relationships between soil texture and fertility properties and pedological factors and processes, such as higher clay contents following the drainage lines of the area. The flattest part with more weathered soils (Oxisols) had the highest pH values and lower Al3+ concentrations. These techniques of data interpolation and visualization have great potential for use in diverse areas of soil science, such as identification of soil volumes occurring side-by-side but that exhibit different physical, chemical, and mineralogical conditions for plant root growth, and monitoring of plumes of organic and inorganic pollutants in soils and sediments, among other applications. The methodological details for interpolation and a three-dimensional view of soil data are presented here.

Estimation of field capacity from ring infiltrometer-drainage data

Field capacity (FC) is a parameter widely used in applied soil science. However, its in situ method of determination may be difficult to apply, generally because of the need of large supplies of water at the test sites. Ottoni Filho et al. (2014) proposed a standardized procedure for field determination of FC and showed that such in situ FC can be estimated by a linear pedotransfer function (PTF) based on volumetric soil water content at the matric potential of -6 kPa [θ(6)] for the same soils used in the present study. The objective of this study was to use soil moisture data below a double ring infiltrometer measured 48 h after the end of the infiltration test in order to develop PTFs for standard in situ FC. We found that such ring FC data were an average of 0.03 m³ m- 3 greater than standard FC values. The linear PTF that was developed for the ring FC data based only on θ(6) was nearly as accurate as the equivalent PTF reported by Ottoni Filho et al. (2014), which was developed for the standard FC data. The root mean squared residues of FC determined from both PTFs were about 0.02 m³ m- 3. The proposed method has the advantage of estimating the soil in situ FC using the water applied in the infiltration test.

Modeling growth and yield of loblolly pinestands under intensive management

Abstract:The objective of this work was to develop and validate a prognosis system for volume yield and basal area of intensively managed loblolly pine (Pinus taeda) stands, using stand and diameter class models compatible in basal area estimates. The data used in the study were obtained from plantations located in northern Uruguay. For model validation without data loss, a three-phase validation scheme was applied: first, the equations were fitted without the validation database; then, model validation was carried out; and, finally, the database was regrouped to recalibrate the parameter values. After the validation and final parameterization of the models, a simulation of the first commercial thinning was carried out. The developed prognosis system was precise and accurate in estimating basal area production per hectare or per diameter classes. There was compatibility in basal area estimates between diameter class and whole stand models, with a mean difference of -0.01 m2ha-1. The validation scheme applied is logic and consistent, since information on the accuracy and precision of the models is obtained without the loss of any information in the estimation of the models' parameters.

Application of differential scanning calorimetry in hair samples as a possible tool in Forensic Science

The Differential Scanning Calorimetry (DSC) was used to study the thermal behavior of hair samples and to verify the possibility of identifying an individual based on DSC curves from a data bank. Hair samples of students and officials from Instituto de Química de Araraquara, UNESP were obtained to build up a data bank. Thus to sought an individual, under incognito participant of this data bank, was identified using DSC curves.

The Brazilian investment in science and technology

An analysis of Brazilian federal expenditures in science and technology is presented is this study. The 1990-1999 data were compiled from records provided by two federal agencies (MCT and CNPq) responsible for managing most of the national budget related to these activities. The results indicate that the federal investments in Brazilian science and technology stagnated during the last decade (US$ 2.32 billion in 1990, US$ 2.39 billion in 1996, and US$ 2.36 billion in 1999). In contrast, a great increase in private investments in research was acknowledged both by industry and by the government during the same period, from US$ 2.12 to US$ 4.64 billion. However, this investment did not result in an increase in invention patents granted to residents (492 in 1990 and only 232 in 1997) or in a reduction of patent costs. Despite this unfavorable scenario, the number of graduate programs in the country has increased two-fold in the last decade and the contribution of Brazilians to the database of the Institute for Scientific Information has increased 4.7-fold from 1990 (2,725 scientific publications) to 2000 (12,686 scientific publications). Unstable federal resources for science, together with the poor returns of private resources in terms of developing new technologies, may jeopardize the future of Brazilian technological development.

Vancomycin-resistant enterococcus outbreak in a pediatric intensive care unit: report of successful interventions for control and prevention

The objective of this study is to retrospectively report the results of interventions for controlling a vancomycin-resistant enterococcus (VRE) outbreak in a tertiary-care pediatric intensive care unit (PICU) of a University Hospital. After identification of the outbreak, interventions were made at the following levels: patient care, microbiological surveillance, and medical and nursing staff training. Data were collected from computer-based databases and from the electronic prescription system. Vancomycin use progressively increased after March 2008, peaking in August 2009. Five cases of VRE infection were identified, with 3 deaths. After the interventions, we noted a significant reduction in vancomycin prescription and use (75% reduction), and the last case of VRE infection was identified 4 months later. The survivors remained colonized until hospital discharge. After interventions there was a transient increase in PICU length-of-stay and mortality. Since then, the use of vancomycin has remained relatively constant and strict, no other cases of VRE infection or colonization have been identified and length-of-stay and mortality returned to baseline. In conclusion, we showed that a bundle intervention aiming at a strict control of vancomycin use and full compliance with the Hospital Infection Control Practices Advisory Committee guidelines, along with contact precautions and hand-hygiene promotion, can be effective in reducing vancomycin use and the emergence and spread of vancomycin-resistant bacteria in a tertiary-care PICU.

Sensory evaluation of "dulce de leche" with coffee and whey using different affective data analysis methods

This study sought to evaluate the acceptance of "dulce de leche" with coffee and whey. The results were analyzed through response surface, ANOVA, test of averages, histograms, and preference map correlating the global impression data with results of physical, physiochemical and sensory analysis. The response surface methodology, by itself, was not enough to find the best formulation. For ANOVA, test of averages, and preference map it was observed that the consumers' favorite "dulce de leche" were those of formulation 1 (10% whey and 1% coffee) and 2 (30% whey and 1% coffee), followed by formulation 9 (20% whey and 1.25% coffee). The acceptance of samples 1 and 2 was influenced by the higher acceptability in relation to the flavor and for presenting higher pH, L*, and b* values. It was observed that samples 1 and 2 presented higher purchase approval score and higher percentages of responses for the 'ideal' category in terms of sweetness and coffee flavor. It was found that consumers preferred the samples with low concentrations of coffee independent of the concentration of whey thus enabling the use of whey and coffee in the manufacture of dulce de leche, obtaining a new product.

Artificial neural networks (ANN): prediction of sensory measurements from instrumental data

The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.