928 resultados para E16 - Aggregate Input-Output Analysis
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies
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BACKGROUND: The use of cardiac output monitoring may improve patient outcomes after major surgery. However, little is known about the use of this technology across nations. METHODS: This is a secondary analysis of a previously published observational study. Patients aged 16 years and over undergoing major non-cardiac surgery in a 7-day period in April 2011 were included into this analysis. The objective is to describe prevalence and type of cardiac output monitoring used in major surgery in Europe. RESULTS: Included in the analysis were 12,170 patients from the surgical services of 426 hospitals in 28 European nations. One thousand four hundred and sixteen patients (11.6 %) were exposed to cardiac output monitoring, and 2343 patients (19.3 %) received a central venous catheter. Patients with higher American Society of Anesthesiologists (ASA) scores were more frequently exposed to cardiac output monitoring (ASA I and II, 643 patients [8.6 %]; ASA III-V, 768 patients [16.2 %]; p < 0.01) and central venous catheter (ASA I and II, 874 patients [11.8 %]; ASA III-V, 1463 patients [30.9 %]; p < 0.01). In elective surgery, 990 patients (10.8 %) were exposed to cardiac output monitoring, in urgent surgery 252 patients (11.7 %) and in emergency surgery 173 patients (19.8 %). A central venous catheter was used in 1514 patients (16.6 %) undergoing elective, in 480 patients (22.2 %) undergoing urgent and in 349 patients (39.9 %) undergoing emergency surgery. Nine hundred sixty patients (7.9 %) were monitored using arterial waveform analysis, 238 patients (2.0 %) using oesophageal Doppler ultrasound, 55 patients (0.5 %) using a pulmonary artery catheter and 44 patients (2.0 %) using other technologies. Across nations, cardiac output monitoring use varied from 0.0 % (0/249 patients) to 27.5 % (19/69 patients), whilst central venous catheter use varied from 5.6 % (7/125 patients) to 43.2 % (16/37 patients). CONCLUSIONS: One in ten patients undergoing major surgery is exposed to cardiac output monitoring whilst one in five receives a central venous catheter. The use of both technologies varies widely across Europe.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
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Cement & Concrete Composites 45 (2014) 264–271
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies
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Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.
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In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.
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We investigate the role of permanent and transitory shocks for firms and aggregate dynamics. We find that permanent shocks to productivity and permanent shifts in the composition of output explain at least four-fifths of firms’ dynamics. However, these permanent shocks are almost uncorrelated across firms and are therefore less relevant for aggregate dynamics. Transitory shocks, on the other hand, are not very important at the firm level,but they account for most of the volatility of aggregate hours and output, because they are significantly correlated across firms. Finally, we try to make some progress on the interpretation of the shocks.
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Double Degree Masters in Economics Program from Insper and NOVA School of Business and Economics
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Based on the report for the unit “Métodos Interactivos de Participação e Decisão A” (Interactive methods of participation and decision A), coordinated by Prof. Lia Maldonado Teles de Vasconcelos and Prof. Nuno Miguel Ribeiro Videira Costa. This unit was provided for the PhD Program in Technology Assessment in 2015/2016.
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O transporte marítimo tem vindo a adquirir uma considerável importância na economia mundial desde o século XV. O transporte marítimo é visto como um dos meios de transporte mais viáveis, que engloba um largo número de destinos no mundo e representa, para uma determinada distância a percorrer, o menor custo por tonelada. É, também, comparativamente com o transporte aéreo e rodoviário, o meio de transporte menos poluente, tornando-o, assim, uma alternativa “amiga do ambiente”. Em particular, o transporte via contentores tem vindo a ser cada vez mais utilizado devido às suas inúmeras vantagens. O contentor permite o transporte de qualquer tipo de mercadoria em boas condições de acondicionamento e permitiu otimizar as operações efetuadas através da redução de tempo de trabalho, custos e espaço. Ademais, com a globalização, a evolução do mercado, a construção de navios de maiores dimensões e a maior tecnologia investida no setor, a competição entre os portos alcançou níveis que exigem uma maior eficiência de toda a estrutura portuária. Neste contexto, a presente dissertação visa avaliar a eficiência dos terminais de contentores do grupo TERTIR, nomeadamente os de Lisboa, Leixões e Setúbal, utilizando o método Data Envelopment Analaysis (DEA). De um modo geral, o método DEA avalia a capacidade dos terminais em converter inputs em outputs. Mais especificamente os inputs selecionados nesta dissertação dizem respeito às infraestruturas e equipamentos dos terminais em estudo, e o output considera a carga movimentada por cada terminal, sendo neste caso representada pelo número de TEUs movimentados. O modelo proposto é aplicado a um conjunto de 30 terminais de contentores Europeus de 6 países diferentes, nomeadamente, Alemanha, Bélgica, Espanha, França, Holanda e Portugal. De um modo geral, os terminais TERTIR apresentam níveis de eficiência baixos quando comparados com outros terminais Europeus. Os resultados contribuem, também, para auxiliar o grupo TERTIR no debate de algumas questões atuais com as autoridades portuárias, nomeadamente no que se refere à descida dos tarifários praticados aos seus clientes e à enunciada construção do terminal de contentores do Barreiro.
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Dissertação de mestrado em Structural Analysis of Monuments and Historical Constructions
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The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and uneven- ness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.
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The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2016.00390
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Surgeons may use a number of cutting instruments such as osteotomes and chisels to cut bone during an operative procedure. The initial loading of cortical bone during the cutting process results in the formation of microcracks in the vicinity of the cutting zone with main crack propagation to failure occuring with continued loading. When a material cracks, energy is emitted in the form of Acoustic Emission (AE) signals that spread in all directions, therefore, AE transducers can be used to monitor the occurrence and development of microcracking and crack propagation in cortical bone. In this research, number of AE signals (hits) and related parameters including amplitude, duration and absolute energy (abs-energy) were recorded during the indentation cutting process by a wedge blade on cortical bone specimens. The cutting force was also measured to correlate between load-displacement curves and the output from the AE sensor. The results from experiments show AE signals increase substantially during the loading just prior to fracture between 90% and 100% of maximum fracture load. Furthermore, an amplitude threshold value of 64dB (with approximate abs-energy of 1500 aJ) was established to saparate AE signals associated with microcracking (41 – 64dB) from fracture related signals (65 – 98dB). The results also demonstrated that the complete fracture event which had the highest duration value can be distinguished from other growing macrocracks which did not lead to catastrophic fracture. It was observed that the main crack initiation may be detected by capturing a high amplitude signal at a mean load value of 87% of maximum load and unsteady crack propagation may occur just prior to final fracture event at a mean load value of 96% of maximum load. The author concludes that the AE method is useful in understanding the crack initiation and fracture during the indentation cutting process.