93 resultados para knowledge mapping


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OBJECTIVE Implementing cross-mapping of Nursing language terms with the terminology of NANDA International, contained in records of patients with Parkinson's disease in rehabilitation. METHOD Descriptive study of cross mapping, carried out in three steps. A simple random sample of 67 files of patients who participated in the rehabilitation in the period between March 2009 and April 2013. RESULTS We identified 454 terms of Nursing language that resulted in 54 diagnoses after cross-mapping, present in 11 of the 13 taxonomy domains. The most mapped diagnosis was "Impaired urinary elimination" (59.7%), followed by "Urgent urinary incontinence" (55.2%), "Willingness to self-control improved health" (50.7%), "Constipation" (47.8%) and "Compromised physical mobility" (29.9%). Seven described terms were not mapped due to a corresponding defining characteristic being absent. CONCLUSION It was possible to determine the profile of patients, as well as the complexity of nursing care in the rehabilitation of patients with Parkinson's disease.

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OBJECTIVETo identify the exposure of rural workers to the sun's ultraviolet radiation and pesticides; to identify previous cases of skin cancer; and to implement clinical and communicative nursing actions among rural workers with a previous diagnosis of skin cancer.METHODObservational-exploratory study conducted with rural workers exposed to ultraviolet radiation and pesticides in a rural area in the extreme south of Brazil. A clinical judgment and risk communication model properly adapted was used to develop interventions among workers with a previous history of skin cancer.RESULTSA total of 123 (97.7%) workers were identified under conditions of exposure to the sun's ultraviolet radiation and pesticides; seven (5.4%) were identified with a previous diagnosis of skin cancer; four (57.1%) of these presented potential skin cancer lesions.CONCLUSIONThis study's results enabled clarifying the combination of clinical knowledge and risk communication regarding skin cancer to rural workers.

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OBJECTIVETo evaluate the level of knowledge and the availability of the Portuguese population to attend training in Basic Life Support (BLS) and identify factors related to their level of knowledge about BLS.METHODObservational study including 1,700 people who responded to a questionnaire containing data on demography, profession, training, interest in training and knowledge about BLS.RESULTSAmong 754 men and 943 women, only 17.8% (303) attended a course on BLS, but 95.6% expressed willingness to carry out the training. On average, they did not show good levels of knowledge on basic life support (correct answers in 25.9 ± 11.5 of the 64 indicators). Male, older respondents who had the training and those who performed BLS gave more correct answers, on average (p<0.01).CONCLUSIONThe skill levels of the Portuguese population are low, but people are available for training, hence it is important to develop training courses and practice to improve their knowledge.

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Abstract OBJECTIVE Check the relationship between the users' contact time in educational programs and self-care and knowledge variables in diabetes mellitus. METHOD A longitudinal study with a quantitative approach with the participation, in the initial phase, of 263 users linked to Basic Health Units in Belo Horizonte, Brazil during the years 2012 and 2013. The data were collected with respect to the total contact time of the users' participation in the educational program as regards knowledge and self-care in acquired diabetes mellitus. The data were analyzed using the Student t-test for comparison of means, considering a 0.05 significance level. RESULTS The final sample included 151 users. The analysis showed that the improvement in self-care scores was statistically higher during an educational intervention of eight hours or more (p-value <0.05). In relation to the scores for knowledge, there was a statistically significant improvement at the end of the educational program. It was not possible to identify a value for the contact time from which there was an increase in mean scores for the ability of knowledge. CONCLUSION To improve the effectiveness of the promotion of skills related to knowledge and self-care in diabetes mellitus, it is necessary to consider the contact time as a relevant factor of the educational program.

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Contributions to the knowledge of Banasa Stål (Hemiptera, Heteroptera, Pentatomidae): Banasa chaca Thomas. The male of Banasa chaca Thomas is described with emphasis on external and internal genitalia and the female internal genitalia is described. Banasa chaca is newly recorded from Buenos Aires Province (Argentina).

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Geobiota are defined by taxic assemblages (i.e., biota) and their defining abiotic breaks, which are mapped in cross-section to reveal past and future biotic boundaries. We term this conceptual approach Temporal Geobiotic Mapping (TGM) and offer it as a conceptual approach for biogeography. TGM is based on geological cross-sectioning, which creates maps based on the distribution of biota and known abiotic factors that drive their distribution, such as climate, topography, soil chemistry and underlying geology. However, the availability of abiotic data is limited for many areas. Unlike other approaches, TGM can be used when there is minimal data available. In order to demonstrate TGM, we use the well-known area in the Blue Mountains, New South Wales (NSW), south-eastern Australia and show how surface processes such as weathering and erosion affect the future distribution of a Moist Basalt Forest taxic assemblage. Biotic areas are best represented visually as maps, which can show transgressions and regressions of biota and abiota over time. Using such maps, a biogeographer can directly compare animal and plant distributions with features in the abiotic environment and may identify significant geographical barriers or pathways that explain biotic distributions.

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Peatlands form in areas where net primary of organic matter production exceeds losses due to the decomposition, leaching or disturbance. Due to their chemical and physical characteristics, bogs can influence water dynamics because they can store large volumes of water in the rainy season and gradually release this water during the other months of the year. In Diamantina, Minas Gerais, Brazil, a peatland in the environmental protection area of Pau-de-Fruta ensures the water supply of 40,000 inhabitants. The hypothesis of this study is that the peat bogs in Pau-de-Fruta act as an environment for carbon storage and a regulator of water flow in the Córrego das Pedras basin. The objective of this study was to estimate the water volume and organic matter mass in this peatland and to study the influence of this environment on the water flow in the Córrego das Pedras basin. The peatland was mapped using 57 transects, at intervals of 100 m. Along all transects, the depth of the peat bog, the Universal Transverse Mercator (UTM) coordinates and altitude were recorded every 20 m and used to calculate the area and volume of the peatland. The water volume was estimated, using a method developed in this study, and the mass of organic matter based on samples from 106 profiles. The peatland covered 81.7 hectares (ha), and stored 497,767 m³ of water, representing 83.7 % of the total volume of the peat bog. The total amount of organic matter (OM) was 45,148 t, corresponding to 552 t ha-1 of OM. The peat bog occupies 11.9 % of the area covered by the Córrego das Pedras basin and stores 77.6 % of the annual water surplus, thus controlling the water flow in the basin and consequently regulating the water course.

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The region of greatest variability on soil maps is along the edge of their polygons, causing disagreement among pedologists about the appropriate description of soil classes at these locations. The objective of this work was to propose a strategy for data pre-processing applied to digital soil mapping (DSM). Soil polygons on a training map were shrunk by 100 and 160 m. This strategy prevented the use of covariates located near the edge of the soil classes for the Decision Tree (DT) models. Three DT models derived from eight predictive covariates, related to relief and organism factors sampled on the original polygons of a soil map and on polygons shrunk by 100 and 160 m were used to predict soil classes. The DT model derived from observations 160 m away from the edge of the polygons on the original map is less complex and has a better predictive performance.

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Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

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Peatlands are soil environments that store carbon and large amounts of water, due to their composition (90 % water), low hydraulic conductivity and a sponge-like behavior. It is estimated that peat bogs cover approximately 4.2 % of the Earth's surface and stock 28.4 % of the soil carbon of the planet. Approximately 612 000 ha of peatlands have been mapped in Brazil, but the peat bogs in the Serra do Espinhaço Meridional (SdEM) were not included. The objective of this study was to map the peat bogs of the northern part of the SdEM and estimate the organic matter pools and water volume they stock. The peat bogs were pre-identified and mapped by GIS and remote sensing techniques, using ArcGIS 9.3, ENVI 4.5 and GPS Track Maker Pro software and the maps validated in the field. Six peat bogs were mapped in detail (1:20,000 and 1:5,000) by transects spaced 100 m and each transect were determined every 20 m, the UTM (Universal Transverse Mercator) coordinates, depth and samples collected for characterization and determination of organic matter, according to the Brazilian System of Soil Classification. In the northern part of SdEM, 14,287.55 ha of peatlands were mapped, distributed over 1,180,109 ha, representing 1.2 % of the total area. These peatlands have an average volume of 170,021,845.00 m³ and stock 6,120,167 t (428.36 t ha-1) of organic matter and 142,138,262 m³ (9,948 m³ ha-1) of water. In the peat bogs of the Serra do Espinhaço Meridional, advanced stages of decomposing (sapric) organic matter predominate, followed by the intermediate stage (hemic). The vertical growth rate of the peatlands ranged between 0.04 and 0.43 mm year-1, while the carbon accumulation rate varied between 6.59 and 37.66 g m-2 year-1. The peat bogs of the SdEM contain the headwaters of important water bodies in the basins of the Jequitinhonha and San Francisco Rivers and store large amounts of organic carbon and water, which is the reason why the protection and preservation of these soil environments is such an urgent and increasing need.

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Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

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Ethnopedological studies have mainly focused on agricultural land uses and associated practices. Nevertheless, peasant and indigenous populations use soil and land resources for a number of additional purposes, including pottery. In the present study, we describe and analyze folk knowledge related to the use of soils in non-industrial pottery making by peasant potters, in the municipality of Altinho, Pernambuco State, semiarid region at Brazil. Ethnoscientific techniques were used to record local knowledge, with an emphasis on describing the soil materials recognized by the potters, the properties they used to identify those soil materials, and the criteria employed by them to differentiate and relate such materials. The potters recognized three categories of soil materials: “terra” (earth), “barro” (clay) and, “piçarro” (soft rock). The multi-layered arrangement of these materials within the soil profiles was similar to the arrangement of the soil horizon described by formal pedologists. “Barro vermelho” (red clay) was considered by potters as the principal ceramic resource. The potters followed morphological and utilitarian criteria in distinguishing the different soil materials. Soils from all of these sites were sodium-affected Alfisols and correspond to Typic Albaqualf and Typic Natraqualf in the Soil Taxonomy (Soil Survey Staff, 2010).

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The aim of this article is to substantiate, in the sociological point of view, the distinction between the social and cognitive processes that produce knowledge in knowledge abstract systems - KAS - to generate cultural inequality and the micro processes of knowledge usage, which build local and cultural knowledge from common sense. It is circumscribed to this aim a problematization of knowledge usage developed by middle class salaried professional groups, rich in cultural capital but without equivalent symbolical capital, in a capitalist society at risk. In order to achieve this goal, the classical contributions of Pierre Bourdieu, Boaventura Sousa Santos, Donald Schön and Basil Bernstein (among others) are taken as a basis regarding the limitation of critical and reflexive thinking and the virtues of professional knowledge to support an epistemology of professional practice.

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This paper presents a process of mining research & development abstract databases to profile current status and to project potential developments for target technologies, The process is called "technology opportunities analysis." This article steps through the process using a sample data set of abstracts from the INSPEC database on the topic o "knowledge discovery and data mining." The paper offers a set of specific indicators suitable for mining such databases to understand innovation prospects. In illustrating the uses of such indicators, it offers some insights into the status of knowledge discovery research*.

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The comments related to the sustainability of knowledge management (KM) have shown signs that it possibly can be a discourse which determines a quick style, but otherwise have also allowed the building of a better understanding about the limits and weaknesses of the knowlege management. In addition to the criticisms, the conceptual bases of knowledge management have been undermined by a contradictory combination of paradigms; there are also contradictions between the theoretical perspective jubjacent to the knwoledge management and its operationality. As a way of minimizing the possibility that the knowledge management may be turned into an umbrella concept and fail, it is suggested that its approaches embody a more interpretative perspective, taking up the role of an instrument which enables and facilitates the processes and practices in building up knowledge and information, enhancing their focus on the support to the establishment of human competences in order to deal intelligently with the present overcharge of information resources and need for building up information in the organizations.