987 resultados para Anesthetic techniques, regional: subarachnoid
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The aim of this study was to group temporal profiles of 10-day composites NDVI product by similarity, which was obtained by the SPOT Vegetation sensor, for municipalities with high soybean production in the state of Paraná, Brazil, in the 2005/2006 cropping season. Data mining is a valuable tool that allows extracting knowledge from a database, identifying valid, new, potentially useful and understandable patterns. Therefore, it was used the methods for clusters generation by means of the algorithms K-Means, MAXVER and DBSCAN, implemented in the WEKA software package. Clusters were created based on the average temporal profiles of NDVI of the 277 municipalities with high soybean production in the state and the best results were found with the K-Means algorithm, grouping the municipalities into six clusters, considering the period from the beginning of October until the end of March, which is equivalent to the crop vegetative cycle. Half of the generated clusters presented spectro-temporal pattern, a characteristic of soybeans and were mostly under the soybean belt in the state of Paraná, which shows good results that were obtained with the proposed methodology as for identification of homogeneous areas. These results will be useful for the creation of regional soybean "masks" to estimate the planted area for this crop.
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The use of intensity-modulated radiotherapy (IMRT) has increased extensively in the modern radiotherapy (RT) treatments over the past two decades. Radiation dose distributions can be delivered with higher conformality with IMRT when compared to the conventional 3D-conformal radiotherapy (3D-CRT). Higher conformality and target coverage increases the probability of tumour control and decreases the normal tissue complications. The primary goal of this work is to improve and evaluate the accuracy, efficiency and delivery techniques of RT treatments by using IMRT. This study evaluated the dosimetric limitations and possibilities of IMRT in small (treatments of head-and-neck, prostate and lung cancer) and large volumes (primitive neuroectodermal tumours). The dose coverage of target volumes and the sparing of critical organs were increased with IMRT when compared to 3D-CRT. The developed split field IMRT technique was found to be safe and accurate method in craniospinal irradiations. By using IMRT in simultaneous integrated boosting of biologically defined target volumes of localized prostate cancer high doses were achievable with only small increase in the treatment complexity. Biological plan optimization increased the probability of uncomplicated control on average by 28% when compared to standard IMRT delivery. Unfortunately IMRT carries also some drawbacks. In IMRT the beam modulation is realized by splitting a large radiation field to small apertures. The smaller the beam apertures are the larger the rebuild-up and rebuild-down effects are at the tissue interfaces. The limitations to use IMRT with small apertures in the treatments of small lung tumours were investigated with dosimetric film measurements. The results confirmed that the peripheral doses of the small lung tumours were decreased as the effective field size was decreased. The studied calculation algorithms were not able to model the dose deficiency of the tumours accurately. The use of small sliding window apertures of 2 mm and 4 mm decreased the tumour peripheral dose by 6% when compared to 3D-CRT treatment plan. A direct aperture based optimization (DABO) technique was examined as a solution to decrease the treatment complexity. The DABO IMRT technique was able to achieve treatment plans equivalent with the conventional IMRT fluence based optimization techniques in the concave head-and-neck target volumes. With DABO the effective field sizes were increased and the number of MUs was reduced with a factor of two. The optimality of a treatment plan and the therapeutic ratio can be further enhanced by using dose painting based on regional radiosensitivities imaged with functional imaging methods.
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Changes in the electroencephalography (EEG) signal have been used to study the effects of anesthetic agents on the brain function. Several commercial EEG based anesthesia depth monitors have been developed to measure the level of the hypnotic component of anesthesia. Specific anesthetic related changes can be seen in the EEG, but still it remains difficult to determine whether the subject is consciousness or not during anesthesia. EEG reactivity to external stimuli may be seen in unconsciousness subjects, in anesthesia or even in coma. Changes in regional cerebral blood flow, which can be measured with positron emission tomography (PET), can be used as a surrogate for changes in neuronal activity. The aim of this study was to investigate the effects of dexmedetomidine, propofol, sevoflurane and xenon on the EEG and the behavior of two commercial anesthesia depth monitors, Bispectral Index (BIS) and Entropy. Slowly escalating drug concentrations were used with dexmedetomidine, propofol and sevoflurane. EEG reactivity at clinically determined similar level of consciousness was studied and the performance of BIS and Entropy in differentiating consciousness form unconsciousness was evaluated. Changes in brain activity during emergence from dexmedetomidine and propofol induced unconsciousness were studied using PET imaging. Additionally, the effects of normobaric hyperoxia, induced during denitrogenation prior to xenon anesthesia induction, on the EEG were studied. Dexmedetomidine and propofol caused increases in the low frequency, high amplitude (delta 0.5-4 Hz and theta 4.1-8 Hz) EEG activity during stepwise increased drug concentrations from the awake state to unconsciousness. With sevoflurane, an increase in delta activity was also seen, and an increase in alpha- slow beta (8.1-15 Hz) band power was seen in both propofol and sevoflurane. EEG reactivity to a verbal command in the unconsciousness state was best retained with propofol, and almost disappeared with sevoflurane. The ability of BIS and Entropy to differentiate consciousness from unconsciousness was poor. At the emergence from dexmedetomidine and propofol induced unconsciousness, activation was detected in deep brain structures, but not within the cortex. In xenon anesthesia, EEG band powers increased in delta, theta and alpha (8-12Hz) frequencies. In steady state xenon anesthesia, BIS and Entropy indices were low and these monitors seemed to work well in xenon anesthesia. Normobaric hyperoxia alone did not cause changes in the EEG. All of these results are based on studies in healthy volunteers and their application to clinical practice should be considered carefully.
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Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.
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Metodología: se realizó un estudio descriptivo para evaluar las ventajas de la técnica regional sobre la técnica general en mujeres ASA 1 y 2 en Hospital Occidente de Kennedy. Se evaluaron los signos vitales, tiempo de recuperación, analgesia postoperatoria y efectos colaterales. Resultados: se incluyeron un total de 177 pacientes, 79 con anestesia regional y 98 pacientes con anestesia general. Los resultados en el postoperatorio mostraron que no hay diferencias estadísticamente significativas en cuanto a manejo de dolor, efectos colaterales, variación en signos vitales. Se encontró una diferencia significativa en el tiempo de recuperación p=0,02 siendo la técnica espinal 20 minutos en promedio más prolongada. Discusión: ambas técnicas suponen una buena opción como técnica anestésica para pacientes llevadas a legrado obstétrico, a pesar que el tiempo de recuperación fue mayor en el grupo de técnica espinal, se obtuvo un mejor manejo del dolor, sin el requerimiento de otros analgésicos durante el postoperatorio.
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Por sus múltiples causas y su sintomatología inespecífica, el síndrome doloroso regional complejo es una de las situaciones clínicas que mayor dificultad genera en el tratamiento fisioterapéutico. Este síndrome se define como una disfunción vasomotora, mediada por el sistema simpático en donde su manifestación primaria es un dolor que aumenta y permanece en el tiempo y que no tolera las diferentes modalidades y técnicas utilizadas por los Fisioterapeutas como herramientas de intervención. A través del tiempo el Fisioterapeuta ha tenido una acción relevante en el manejo del usuario con dolor, sin importar la causa o consecuencia del mismo. Por esta razón con esta revisión se quiere, integrar acciones terapéuticas como la carga de peso, la desensibilización y la relajación, que han dado excelentes resultados, a las prácticas tradicionales (medios físicos, ultrasonido, masaje sedativo y diferentes tipos de corrientes) aplicables a quienes padecen dolor secundario, traumático o visceral que compromete el sistema simpático en forma refleja.
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Introducción: La herniorrafia inguinal se asocia hasta en un 50% de los casos con dolor crónico posoperatorio (DCP), y en algunos puede ser incapacitante. En este estudio se evaluaron los factores asociados al DCP en pacientes llevados a herniorrafia inguinal. Métodología: Se realizó un estudio de cohorte multicéntrico. Se obtuvo información sociodemográfica y de antecedentes personales. Se determinó la presencia e intensidad de dolor agudo posoperatorio (DAP) y se evaluaron los factores asociados al DCP con seguimiento a los dos meses del posoperatorio. Se establecieron asociaciones con la prueba chi cuadrado. Mediante una regresión lineal se evaluó el papel de los factores de confusión. Resultados: Se analizaron 108 pacientes. 54.7% presentaron DCP. La edad menor de 40 años, el DAP no controlado, el DAP severo, y el dolor no controlado entre la primera y tercera semanas del POP se relacionaron con mayor riesgo de DCP. La edad mayor a 65, el uso de opioides intratecales, la visualización y preservación de los nervios durante la cirugía, y el uso de tres o más analgésicos intravenosos con bloqueo ilioinguinal/iliohipogástrico fueron factores protectores. Discusión: El DCP es frecuente en nuestro medio. La prevención y manejo eficientes del DAP utilizando analgesia multimodal, el uso de opioide intratecal, y la identificación y preservación de los nervios en el área quirúrgica ayudan a prevenir el desarrollo de DCP. Estudios de este tipo realizados a una escala más grande, permitirán identificar otros factores relacionados con esta patología. Palabras clave: Dolor crónico postoperatorio, herniorrafia inguinal, inguinodina, factores asociados.
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Species rich semi-natural grasslands are an important but threatened habitat throughout Europe and much of the former area has been lost since the 1950s. However, in some countries large areas have been preserved and the demand for meadow recreation by sowing seed mixtures is increasing. In the White Carpathians Protected Landscape Area (Czech Republic) the use of commercial seed mixtures is undesirable and the use of regional mixtures has been investigated. The costs for seeding large areas are high and lower cost techniques are needed. In 1999 a field experiment was set up to investigate the establishment of hay meadow vegetation comparing sowing a regional mixture all over a plot with sowing narrow 2.5 In strips of regional seed mixtures into a matrix of a commercial grass mixture or into natural regeneration. The results after five seasons showed good establishment of the sown species in the meadow treatment. Spread of sown species from the sown strips into the surrounding matrix occurred but the cover of species was lower in the commercial grass matrix compared with the natural regeneration matrix. Colonisation of some plots by unsown desirable grassland species from adjacent grassland habitats also occurred, but more species colonised the natural regeneration matrix than the commercial grasses or the sown meadow matrix itself. Overall, the results indicate that, in appropriate situations, sown strips can provide a lower cost but slower and longer-term alternative to field scale sowing of regional seed mixtures for recreation of hay meadow vegetation. (C) 2007 Elsevier Ltd. All rights reserved.
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[1] High-elevation forests represent a large fraction of potential carbon uptake in North America, but this uptake is not well constrained by observations. Additionally, forests in the Rocky Mountains have recently been severely damaged by drought, fire, and insect outbreaks, which have been quantified at local scales but not assessed in terms of carbon uptake at regional scales. The Airborne Carbon in the Mountains Experiment was carried out in 2007 partly to assess carbon uptake in western U.S. mountain ecosystems. The magnitude and seasonal change of carbon uptake were quantified by (1) paired upwind-downwind airborne CO2 observations applied in a boundary layer budget, (2) a spatially explicit ecosystem model constrained using remote sensing and flux tower observations, and (3) a downscaled global tracer transport inversion. Top-down approaches had mean carbon uptake equivalent to flux tower observations at a subalpine forest, while the ecosystem model showed less. The techniques disagreed on temporal evolution. Regional carbon uptake was greatest in the early summer immediately following snowmelt and tended to lessen as the region experienced dry summer conditions. This reduction was more pronounced in the airborne budget and inversion than in flux tower or upscaling, possibly related to lower snow water availability in forests sampled by the aircraft, which were lower in elevation than the tower site. Changes in vegetative greenness associated with insect outbreaks were detected using satellite reflectance observations, but impacts on regional carbon cycling were unclear, highlighting the need to better quantify this emerging disturbance effect on montane forest carbon cycling.
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As wind generation increases, system impact studies rely on predictions of future generation and effective representation of wind variability. A well-established approach to investigate the impact of wind variability is to simulate generation using observations from 10 m meteorological mast-data. However, there are problems with relying purely on historical wind-speed records or generation histories: mast-data is often incomplete, not sited at a relevant wind generation sites, and recorded at the wrong altitude above ground (usually 10 m), each of which may distort the generation profile. A possible complimentary approach is to use reanalysis data, where data assimilation techniques are combined with state-of-the-art weather forecast models to produce complete gridded wind time-series over an area. Previous investigations of reanalysis datasets have placed an emphasis on comparing reanalysis to meteorological site records whereas this paper compares wind generation simulated using reanalysis data directly against historic wind generation records. Importantly, this comparison is conducted using raw reanalysis data (typical resolution ∼50 km), without relying on a computationally expensive “dynamical downscaling” for a particular target region. Although the raw reanalysis data cannot, by nature of its construction, represent the site-specific effects of sub-gridscale topography, it is nevertheless shown to be comparable to or better than the mast-based simulation in the region considered and it is therefore argued that raw reanalysis data may offer a number of significant advantages as a data source.
Conditioning model output statistics of regional climate model precipitation on circulation patterns
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Dynamical downscaling of Global Climate Models (GCMs) through regional climate models (RCMs) potentially improves the usability of the output for hydrological impact studies. However, a further downscaling or interpolation of precipitation from RCMs is often needed to match the precipitation characteristics at the local scale. This study analysed three Model Output Statistics (MOS) techniques to adjust RCM precipitation; (1) a simple direct method (DM), (2) quantile-quantile mapping (QM) and (3) a distribution-based scaling (DBS) approach. The modelled precipitation was daily means from 16 RCMs driven by ERA40 reanalysis data over the 1961–2000 provided by the ENSEMBLES (ENSEMBLE-based Predictions of Climate Changes and their Impacts) project over a small catchment located in the Midlands, UK. All methods were conditioned on the entire time series, separate months and using an objective classification of Lamb's weather types. The performance of the MOS techniques were assessed regarding temporal and spatial characteristics of the precipitation fields, as well as modelled runoff using the HBV rainfall-runoff model. The results indicate that the DBS conditioned on classification patterns performed better than the other methods, however an ensemble approach in terms of both climate models and downscaling methods is recommended to account for uncertainties in the MOS methods.
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Cities, which are now inhabited by a majority of the world's population, are not only an important source of global environmental and resource depletion problems, but can also act as important centres of technological innovation and social learning in the continuing quest for a low carbon future. Planning and managing large-scale transitions in cities to deal with these pressures require an understanding of urban retrofitting at city scale. In this context performative techniques (such as backcasting and roadmapping) can provide valuable tools for helping cities develop a strategic view of the future. However, it is also important to identify ‘disruptive’ and ‘sustaining’ technologies which may contribute to city-based sustainability transitions. This paper presents research findings from the EPSRC Retrofit 2050 project, and explores the relationship between technology roadmaps and transition theory literature, highlighting the research gaps at urban/city level. The paper develops a research methodology to describe the development of three guiding visions for city-regional retrofit futures, and identifies key sustaining and disruptive technologies at city scale within these visions using foresight (horizon scanning) techniques. The implications of the research for city-based transition studies and related methodologies are discussed.
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Time series of global and regional mean Surface Air Temperature (SAT) anomalies are a common metric used to estimate recent climate change. Various techniques can be used to create these time series from meteorological station data. The degree of difference arising from using five different techniques, based on existing temperature anomaly dataset techniques, to estimate Arctic SAT anomalies over land and sea ice were investigated using reanalysis data as a testbed. Techniques which interpolated anomalies were found to result in smaller errors than non-interpolating techniques relative to the reanalysis reference. Kriging techniques provided the smallest errors in estimates of Arctic anomalies and Simple Kriging was often the best kriging method in this study, especially over sea ice. A linear interpolation technique had, on average, Root Mean Square Errors (RMSEs) up to 0.55 K larger than the two kriging techniques tested. Non-interpolating techniques provided the least representative anomaly estimates. Nonetheless, they serve as useful checks for confirming whether estimates from interpolating techniques are reasonable. The interaction of meteorological station coverage with estimation techniques between 1850 and 2011 was simulated using an ensemble dataset comprising repeated individual years (1979-2011). All techniques were found to have larger RMSEs for earlier station coverages. This supports calls for increased data sharing and data rescue, especially in sparsely observed regions such as the Arctic.
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This article highlights the potential benefits that the Kohonen method has for the classification of rivers with similar characteristics by determining regional ecological flows using the ELOHA (Ecological Limits of Hydrologic Alteration) methodology. Currently, there are many methodologies for the classification of rivers, however none of them include the characteristics found in Kohonen method such as (i) providing the number of groups that actually underlie the information presented, (ii) used to make variable importance analysis, (iii) which in any case can display two-dimensional classification process, and (iv) that regardless of the parameters used in the model the clustering structure remains. In order to evaluate the potential benefits of the Kohonen method, 174 flow stations distributed along the great river basin “Magdalena-Cauca” (Colombia) were analyzed. 73 variables were obtained for the classification process in each case. Six trials were done using different combinations of variables and the results were validated against reference classification obtained by Ingfocol in 2010, whose results were also framed using ELOHA guidelines. In the process of validation it was found that two of the tested models reproduced a level higher than 80% of the reference classification with the first trial, meaning that more than 80% of the flow stations analyzed in both models formed invariant groups of streams.
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Identificar, compartilhar e gerenciar os riscos de contratar são preocupações que impedem o estabelicmento e a administração das Parcerias Públicos Particulares (PPP). Porem, gerentes das entidades públicas, bancos de formento, construtoras e seguradoras pesquisam e utilizam muitas técnicas para enfrentar a avaliação e gerenciamento dos riscos. A transferência de risco é uma indicação dos chamados benefícios que são inspirados pelos PPP, contudo devido às realidades contratuais e conceptuais, a entidade de cede o risco (o partido público) permanece quase sempre como o portador final do risco. Conseqüentemente, o partido público retem um interesse de resistência na gerência total destes riscos cedidos. Esta dissertação explora alguns defeitos das aproximações comuns a conceituar a gestão de risco no contexto de um PPP. Focalizando os conceitos da interdependência e da reciprocidade e usando na decisão para transferir o risco do projeto, esta dissertação molda a decisão para transferir o risco nos termos das realidades interdependentes de relacionamentos sistemáticos, alargam os conceitos técnicos do risco e da avaliação de risco, considerando o uso reflexivo das diferenças na analise de um estudo de caso. O autor explora estes conceitos em uma análise da decisão de um gerente de risco da empresa de construção civil brasileira Construtora Norberto Odebrecht (ODB) para projetar uma facilidade inovadora da ligação de garantia com Inter-American Development Bank (BID) e uma seguradora, American International Group (AIG), um negócio que ganhe o reconhecimento Trade Finance Magazine’s 2007 deal of the year. O autor mostra que por compreender a transferência de risco nos termos abordados nesta dissertação, um atore que transfere o risco pode identificar e criar mais oportunidades de estabelecer relacionamentos em longo prazo, através dos processos que a literatura atual do PPP ainda não considere. Os resultados devem fornecer contribuições para a pesquisas sobre a transferência do risco do projeto, na cooperação entre organizações e na seleção do sócio do projeto do potencial.