Proposta educacional on-line sobre úlcera por pressão para alunos e profissionais de enfermagem

OBJETIVOS: Desenvolver uma proposta educacional on-line sobre o tema úlcera por pressão para alunos e profissionais de enfermagem. MÉTODOS: Pesquisa aplicada, de produção tecnológica, composta pelas etapas de concepção/ planejamento e desenvolvimento, caracterizadas por um conjunto de procedimentos, documentação, digitalização de informações e de imagens. Foram utilizados recursos computacionais didáticos interativos como: o Cybertutor e o Homem Virtual. RESULTADOS: Desenvolvimento de uma proposta educacional virtual sobre úlcera por pressão (UP) dividida em módulos de aprendizagem, contendo lista de discussão, estudos de casos e recursos didáticos, tais como fotos e o Homem Virtual. CONCLUSÕES: Utilizou-se de novas tecnologias educacionais, com a finalidade de promover o aprendizado sobre UP a estudantes de graduação de enfermagem e possibilitar a educação continuada de enfermeiros, uma vez que as UP representam um desafio aos profissionais da saúde e aos serviços de saúde.

On-line identification of minor flavones from sugarcane juice by LC/UV/MS and post-column derivatization

This work describes the on-line characterization of minor flavones from sugarcane (Saccharum officinarum) juice by high-performance liquid chromatography coupled to diode array UV detection and mass spectrometry (LC/UV/MS) using atmospheric pressure chemical ionization-collision-induced dissociation (APCI-CID-MS/MS) and post-column derivatization using UV shift reagents. HPLC-UV analysis with shift reagents provided information about the substitution pattern in the flavonoid skeleton and, combined with MS data, these techniques allowed for the on-line identification of five "garapa" flavones: luteolin-8-C-glucosyl-7-O-glucuronide; tricin-7-O-neohesperoside-4'-O-rhamnoside; tricin-7-O-methylglucuronate-4'-O-rhamnoside; tricin-7-O-methylglucuronide; swertisin, while four other compounds were partially identified as glycosylflavones. Only swertisin (7-O-methylapigenin-6-C-glucoside) was reported previously in sugarcane molasses.

Exploitation of a single interface flow system for on-line aqueous biphasic extraction

The exploitation of aqueous biphasic extraction is proposed for the first time in flow analysis This extraction strategy stands out for being environmentally attractive since it is based in the utilization of two immiscible phases that are intrinsically aqueous The organic solvents of the traditional liquid-liquid extractions ale no longer used, being replaced by non-toxic, non-flammable and non-volatile ones. A single interface flow analysis (SIFA) system was implemented to carry out the extraction process due to its favourable operational characteristics that include the high automation level and simplicity of operation, the establishment of a dynamic interface where the mass transfer occurred between the two immiscible aqueous phases, and the versatile control over the extraction process namely the extraction time The application selected to demonstrate the feasibility of SIFA to perform this aqueous biphasic extraction was the pre-concentration of lead. After extraction, lead reacted with 8-hydroxyquinoline-5-sulfonic acid and the resulting product was determined by a fluorimetric detector included in the flow manifold. Therefore, the SIFA single interface was used both as extraction (enrichment) and reaction interface. (C) 2010 Elsevier B.V All rights reserved.

Effect of bandwidth knowledge of results on the learning of a grip force control task

An experiment was conducted to investigate the persistence of the effect of ""bandwidth knowledge of results (KR)"" manipulated during the learning phase of performing a manual force-control task. The experiment consisted of two phases, an acquisition phase with the goal of maintaining 60% maximum force in 30 trials, and a second phase with the objective of maintaining 40% of maximum force in 20 further trials. There were four bandwidths of KR: when performance error exceeded 5, 10, or 15% of the target, and a control group (0% bandwidth). Analysis showed that 5, 10, and 15% bandwidth led to better performance than 0% bandwidth KR at the beginning of the second phase and persisted during the extended trials.

On-line fault diagnostic system for proton exchange membrane fuel cells

In this paper, a supervisor system, able to diagnose different types of faults during the operation of a proton exchange membrane fuel cell is introduced. The diagnosis is developed by applying Bayesian networks, which qualify and quantify the cause-effect relationship among the variables of the process. The fault diagnosis is based on the on-line monitoring of variables easy to measure in the machine such as voltage, electric current, and temperature. The equipment is a fuel cell system which can operate even when a fault occurs. The fault effects are based on experiments on the fault tolerant fuel cell, which are reproduced in a fuel cell model. A database of fault records is constructed from the fuel cell model, improving the generation time and avoiding permanent damage to the equipment. (C) 2007 Elsevier B.V. All rights reserved.

Diagnostic errors and repetitive sequential classifications in on-line process control by attributes

The procedure of on-line process control by attributes, known as Taguchi`s on-line process control, consists of inspecting the mth item (a single item) at every m produced items and deciding, at each inspection, whether the fraction of conforming items was reduced or not. If the inspected item is nonconforming, the production is stopped for adjustment. As the inspection system can be subject to diagnosis errors, one develops a probabilistic model that classifies repeatedly the examined item until a conforming or b non-conforming classification is observed. The first event that occurs (a conforming classifications or b non-conforming classifications) determines the final classification of the examined item. Proprieties of an ergodic Markov chain were used to get the expression of average cost of the system of control, which can be optimized by three parameters: the sampling interval of the inspections (m); the number of repeated conforming classifications (a); and the number of repeated non-conforming classifications (b). The optimum design is compared with two alternative approaches: the first one consists of a simple preventive policy. The production system is adjusted at every n produced items (no inspection is performed). The second classifies the examined item repeatedly r (fixed) times and considers it conforming if most classification results are conforming. Results indicate that the current proposal performs better than the procedure that fixes the number of repeated classifications and classifies the examined item as conforming if most classifications were conforming. On the other hand, the preventive policy can be averagely the most economical alternative rather than those ones that require inspection depending on the degree of errors and costs. A numerical example illustrates the proposed procedure. (C) 2009 Elsevier B. V. All rights reserved.

Cross-situational learning of object-word mapping using Neural Modeling Fields

The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or Virtual agents have brought that issue to a central place in more applied research fields, such as computational linguistics and neural networks, as well. An attractive approach to learning an object-word mapping is the so-called cross-situational learning. This learning scenario is based on the intuitive notion that a learner can determine the meaning of a word by finding something in common across all observed uses of that word. Here we show how the deterministic Neural Modeling Fields (NMF) categorization mechanism can be used by the learner as an efficient algorithm to infer the correct object-word mapping. To achieve that we first reduce the original on-line learning problem to a batch learning problem where the inputs to the NMF mechanism are all possible object-word associations that Could be inferred from the cross-situational learning scenario. Since many of those associations are incorrect, they are considered as clutter or noise and discarded automatically by a clutter detector model included in our NMF implementation. With these two key ingredients - batch learning and clutter detection - the NMF mechanism was capable to infer perfectly the correct object-word mapping. (C) 2009 Elsevier Ltd. All rights reserved.

On-line mass spectrometry of the electro-oxidation of methanol in acidic media on tungsten carbide

The electro-oxidation of methanol at supported tungsten carbide (WC) nanoparticles in sulfuric acid solution was studied using cyclic voltammetry, potentiostatic measurements, and differential electrochemical mass spectroscopy (DEMS). The catalyst was prepared by a sonochemical method and characterized by X-ray diffraction. Over the WC catalyst, the oxidation of methanol (1 M in a sulfuric acid electrolyte) begins at a potential below 0.5 V/RHE during the anodic sweep. During potentiostatic measurements, a maximum current of 0.8 mA mg(-1) was obtained at 0.4 V. Measurements of DEMS showed that the methanol oxidation reaction over tungsten carbide produces CO2 (m/z=44); no methylformate (m/z=60) was detected. These results are discussed in the context of the continued search for alternative materials for the anode catalyst of direct methanol fuel cells.

E-Learning Used in a Training Course on Atraumatic Restorative Treatment (ART) for Brazilian Dentists

The purpose of this study was to assess the benefits of using e-learning resources in a dental training course on Atraumatic Restorative Treatment (ART). This e-course was given in a DVD format, which presented the ART technique and philosophy. The participants were twenty-four dentists from the Brazilian public health system. Prior to receiving the DVD, the dentists answered a questionnaire regarding their personal data, previous knowledge about ART, and general interest in training courses. The dentists also participated in an assessment process consisting of a test applied before and after the course. A single researcher corrected the tests, and intraexaminer reproducibility was calculated (kappa=0.89). Paired t-tests were carried out to compare the means between the assessments, showing a significant improvement in the performance of the subjects on the test taken after the course (p<0.05). A linear regression model was used with the difference between the means as the outcome. A greater improvement on the test results was observed among female dentists (p=0.034), dentists working for a shorter period of time in the public health system (p=0.042), and dentists who used the ART technique only for urgent and/or temporary treatment (p=0.010). In conclusion, e-learning has the potential of improving the knowledge that dentists working in the public health system have about ART, especially those with less clinical experience and less knowledge about the subject.

Modulation of Mediotemporal and Ventrostriatal Function in Humans by Delta 9-Tetrahydrocannabinol A Neural Basis for the Effects of Cannabis sativa on Learning and Psychosis

Context: Cannabis sativa use can impair verbal learning, provoke acute psychosis, and increase the risk of schizophrenia. It is unclear where C sativa acts in the human brain to modulate verbal learning and to induce psychotic symptoms. Objectives: To investigate the effects of 2 main psychoactive constituents of C sativa, Delta 9-tetrahydrocannabinol (Delta 9-THC) and cannabidiol, on regional brain function during verbal paired associate learning. Design: Subjects were studied on 3 separate occasions using a block design functional magnetic resonance imaging paradigm while performing a verbal paired associate learning task. Each imaging session was preceded by the ingestion of Delta 9-THC (10 mg), cannabidiol (600 mg), or placebo in a double-blind, randomized, placebo-controlled, repeated-measures, within-subject design. Setting: University research center. Participants: Fifteen healthy, native English-speaking, right-handed men of white race/ethnicity who had used C sativa 15 times or less and had minimal exposure to other illicit drugs in their lifetime. Main Outcome Measures: Regional brain activation ( blood oxygen level-dependent response), performance in a verbal learning task, and objective and subjective ratings of psychotic symptoms, anxiety, intoxication, and sedation. Results: Delta 9-Tetrahydrocannabinol increased psychotic symptoms and levels of anxiety, intoxication, and sedation, whereas no significant effect was noted on these parameters following administration of cannabidiol. Performance in the verbal learning task was not significantly modulated by either drug. Administration of Delta 9-THC augmented activation in the parahippocampal gyrus during blocks 2 and 3 such that the normal linear decrement in activation across repeated encoding blocks was no longer evident. Delta 9-Tetrahydrocannabinol also attenuated the normal time-dependent change in ventrostriatal activation during retrieval of word pairs, which was directly correlated with concurrently induced psychotic symptoms. In contrast, administration of cannabidiol had no such effect. Conclusion: The modulation of mediotemporal and ventrostriatal function by Delta 9-THC may underlie the effects of C sativa on verbal learning and psychotic symptoms, respectively.

The impact of spatial data redundancy on SOLAP query performance

Geographic Data Warehouses (GDW) are one of the main technologies used in decision-making processes and spatial analysis, and the literature proposes several conceptual and logical data models for GDW. However, little effort has been focused on studying how spatial data redundancy affects SOLAP (Spatial On-Line Analytical Processing) query performance over GDW. In this paper, we investigate this issue. Firstly, we compare redundant and non-redundant GDW schemas and conclude that redundancy is related to high performance losses. We also analyze the issue of indexing, aiming at improving SOLAP query performance on a redundant GDW. Comparisons of the SB-index approach, the star-join aided by R-tree and the star-join aided by GiST indicate that the SB-index significantly improves the elapsed time in query processing from 25% up to 99% with regard to SOLAP queries defined over the spatial predicates of intersection, enclosure and containment and applied to roll-up and drill-down operations. We also investigate the impact of the increase in data volume on the performance. The increase did not impair the performance of the SB-index, which highly improved the elapsed time in query processing. Performance tests also show that the SB-index is far more compact than the star-join, requiring only a small fraction of at most 0.20% of the volume. Moreover, we propose a specific enhancement of the SB-index to deal with spatial data redundancy. This enhancement improved performance from 80 to 91% for redundant GDW schemas.

The development of an immobilized enzyme reactor containing glyceraldehyde-3-phosphate dehydrogenase from Trypanosoma cruzi: the effect of species' specific differences on the immobilization

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) plays an important role in the life cycle of the Trypanosoma cruzi, and an immobilized enzyme reactor (IMER) has been developed for use in the on-line screening for GAPDH inhibitors. An IMER containing human GAPDH has been previously reported; however, these conditions produced a T. cruzi GAPDH-IMER with poor activity and stability. The factors affecting the stability of the human and T. cruzi GAPDHs in the immobilization process and the influence of pH and buffer type on the stability and activity of the IMERs have been investigated. The resulting T. cruzi GAPDH-IMER was coupled to an analytical octyl column, which was used to achieve chromatographic separation of NAD+ from NADH. The production of NADH stimulated by D-glyceraldehyde-3-phosphate was used to investigate the activity and kinetic parameters of the immobilized T. cruzi GAPDH. The Michaelis-Menten constant (K-m) values determined for D-glyceraldehyde-3-phosphate and NAD(+) were K-m = 0.5 +/- 0.05 mM and 0.648 +/- 0.08 mM, respectively, which were consistent with the values obtained using the non-immobilized enzyme.

The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) - Part 1: Model description and evaluation

We introduce the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS). CATT-BRAMS is an on-line transport model fully consistent with the simulated atmospheric dynamics. Emission sources from biomass burning and urban-industrial-vehicular activities for trace gases and from biomass burning aerosol particles are obtained from several published datasets and remote sensing information. The tracer and aerosol mass concentration prognostics include the effects of sub-grid scale turbulence in the planetary boundary layer, convective transport by shallow and deep moist convection, wet and dry deposition, and plume rise associated with vegetation fires in addition to the grid scale transport. The radiation parameterization takes into account the interaction between the simulated biomass burning aerosol particles and short and long wave radiation. The atmospheric model BRAMS is based on the Regional Atmospheric Modeling System (RAMS), with several improvements associated with cumulus convection representation, soil moisture initialization and surface scheme tuned for the tropics, among others. In this paper the CATT-BRAMS model is used to simulate carbon monoxide and particulate material (PM(2.5)) surface fluxes and atmospheric transport during the 2002 LBA field campaigns, conducted during the transition from the dry to wet season in the southwest Amazon Basin. Model evaluation is addressed with comparisons between model results and near surface, radiosondes and airborne measurements performed during the field campaign, as well as remote sensing derived products. We show the matching of emissions strengths to observed carbon monoxide in the LBA campaign. A relatively good comparison to the MOPITT data, in spite of the fact that MOPITT a priori assumptions imply several difficulties, is also obtained.

An algorithmic Friedman-Pippenger theorem on tree embeddings and applications

An (n, d)-expander is a graph G = (V, E) such that for every X subset of V with vertical bar X vertical bar <= 2n - 2 we have vertical bar Gamma(G)(X) vertical bar >= (d + 1) vertical bar X vertical bar. A tree T is small if it has at most n vertices and has maximum degree at most d. Friedman and Pippenger (1987) proved that any ( n; d)- expander contains every small tree. However, their elegant proof does not seem to yield an efficient algorithm for obtaining the tree. In this paper, we give an alternative result that does admit a polynomial time algorithm for finding the immersion of any small tree in subgraphs G of (N, D, lambda)-graphs Lambda, as long as G contains a positive fraction of the edges of Lambda and lambda/D is small enough. In several applications of the Friedman-Pippenger theorem, including the ones in the original paper of those authors, the (n, d)-expander G is a subgraph of an (N, D, lambda)-graph as above. Therefore, our result suffices to provide efficient algorithms for such previously non-constructive applications. As an example, we discuss a recent result of Alon, Krivelevich, and Sudakov (2007) concerning embedding nearly spanning bounded degree trees, the proof of which makes use of the Friedman-Pippenger theorem. We shall also show a construction inspired on Wigderson-Zuckerman expander graphs for which any sufficiently dense subgraph contains all trees of sizes and maximum degrees achieving essentially optimal parameters. Our algorithmic approach is based on a reduction of the tree embedding problem to a certain on-line matching problem for bipartite graphs, solved by Aggarwal et al. (1996).

Elderly online: Effects of a digital inclusion program in cognitive performance

There is little empirical data about the impact of digital inclusion on cognition among older adults. This paper aimed at investigating the effects of a digital inclusion program in the cognitive performance of older individuals who participated in a computer learning workshop named ""Idosos On-Line`` (Elderly Online). Forty-two aged individuals participated in the research study: 22 completed the computer training workshop and 20 constituted the control group. All subjects answered a sociodemographic questionnaire and completed the Addenbrooke`s cognitive examination, revised (ACE-R), which examines five cognitive domains: orientation and attention, memory, verbal fluency, language, and visuo-spatial skills. It was noted that the experimental group`s cognitive performance significantly improved after the program, particularly in the language and memory domains, when compared to the control group. These findings suggest that the acquisition of new knowledge and the use of a new tool, that makes it possible to access the Internet, may bring gains to cognition. (C) 2010 Elsevier Ireland Ltd. All rights reserved.