A methodology for evacuation route planning inside buildings using geospatial technology

Evacuation route planning is a fundamental task for building engineering projects. Safety regulations are established so that all occupants are driven on time out of a building to a secure place when faced with an emergency situation. As an example, Spanish building code requires the planning of evacuation routes on large and, usually, public buildings. Engineers often plan these routes on single building projects, repeatedly assigning clusters of rooms to each emergency exit in a trial-and-error process. But problems may arise for a building complex where distribution and use changes make visual analysis cumbersome and sometimes unfeasible. This problem could be solved by using well-known spatial analysis techniques, implemented as a specialized software able to partially emulate engineer reasoning. In this paper we propose and test an easily reproducible methodology that makes use of free and open source software components for solving a case study. We ran a complete test on a building floor at the University of Alicante (Spain). This institution offers a web service (WFS) that allows retrieval of 2D geometries from any building within its campus. We demonstrate how geospatial technologies and computational geometry algorithms can be used for automating the creation and optimization of evacuation routes. In our case study, the engineers’ task is to verify that the load capacity of each emergency exit does not exceed the standards specified by Spain’s current regulations. Using Dijkstra’s algorithm, we obtain the shortest paths from every room to the most appropriate emergency exit. Once these paths are calculated, engineers can run simulations and validate, based on path statistics, different cluster configurations. Techniques and tools applied in this research would be helpful in the design and risk management phases of any complex building project.

Avaliação do reflexo baroreceptor em doentes com insuficiência cardíaca crónica submetidos a terapêutica de ressincronização cardíaca

Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Lisboa, 2014

ECB Policy and Eurozone Fragility: Was De Grauwe Right? CEPS Working Document No. 397, June 2014

Paul De Grauwe’s fragility hypothesis states that member countries of a monetary union such as the eurozone are highly vulnerable to a self-fulfilling mechanism by which the efforts of investors to avoid losses from default can end up triggering the very default they fear. The authors test this hypothesis by applying an eclectic methodology to a time window around Mario Draghi’s “whatever it takes” (to keep the eurozone on firm footing) pledge on 26 July 2012. This pledge was soon followed by the announcement of the Outright Monetary Transactions (OMT) programme (the prospective and conditional purchase by the European Central Bank of sovereign bonds of eurozone countries having difficulty issuing debt). The principal components of eurozone credit default swap spreads validate this choice of time frame. An event study reveals significant pre announcement contagion emanating from Spain to Italy, Belgium, France and Austria. Furthermore, time-series regression confirms frequent clusters of large shocks affecting the credit default swap spreads of the four eurozone countries but solely during the pre-announcement period. The findings of this report support the fragility hypothesis for the eurozone and endorse the Outright Monetary Transactions programme.

Is Regulatory Convergence Efficient? CES Germany & Europe Working Papers, No. 02.3, May 1992

One of the important themes in the new institutionalism is the convergence of market regulations in a world with three powerful clusters of countries (Western Europe, North America, and East Asia) on a small number of regimes, like disorganized capitalism, free market capitalism, and coordinated market capitalism. This paper examines the political-economic theory of regulatory convergence. It reconstructs and compares three welfarist approaches: the optimal regulatory regime (Tinbergen), the rule of constitutional law (Buchanan), and regulatory rivalry (Hayek). The paper concludes that most plausible results of convergence theory are completely opposite to the expressed political intentions of the theorists. Tinbergen's theory predicts neoliberalism, not social democracy. The theories of Buchanan and Hayek predict respectively a consensual or spontaneous formation of corporatist regulations, not the return of classical constitutionalism or liberalism. The paper summons new institutionalists to repair the weak scientific elements of convergence theory and to make a distinction between the ideological origins of this theory and its unintended ideological consequences.

Methods to Control for Bias in Observational Studies

Thesis (Master's)--University of Washington, 2016-06

Statistical Hurdle Models for Single Cell Gene Expression: Differential Expression and Graphical Modeling

Thesis (Ph.D.)--University of Washington, 2016-06

Fine-scale spatial genetic correlation analyses reveal strong female philopatry within a brush-tailed rock-wallaby colony in southeast Queensland

We combine spatial data on home ranges of individuals and microsatellite markers to examine patterns of fine-scale spatial genetic structure and dispersal within a brush-tailed rock-wallaby (Petrogale penicillata) colony at Hurdle Creek Valley, Queensland. Brush-tailed rock-wallabies were once abundant and widespread throughout the rocky terrain of southeastern Australia; however, populations are nearly extinct in the south of their range and in decline elsewhere. We use pairwise relatedness measures and a recent multilocus spatial autocorrelation analysis to test the hypotheses that in this species, within-colony dispersal is male-biased and that female philopatry results in spatial clusters of related females within the colony. We provide clear evidence for strong female philopatry and male-biased dispersal within this rock-wallaby colony. There was a strong, significant negative correlation between pairwise relatedness and geographical distance of individual females along only 800 m of cliff line. Spatial genetic autocorrelation analyses showed significant positive correlation for females in close proximity to each other and revealed a genetic neighbourhood size of only 600 m for females. Our study is the first to report on the fine-scale spatial genetic structure within a rock-wallaby colony and we provide the first robust evidence for strong female philopatry and spatial clustering of related females within this taxon. We discuss the ecological and conservation implications of our findings for rock-wallabies, as well as the importance of fine-scale spatial genetic patterns in studies of dispersal behaviour.

Wired communities in the city: Sydney, Australia

Questions relating to the ability of particular groups in society to access information and communications technologies (ICTs) have become a growing part of the academic and policy literature. The issues raised in this literature have revolved around a number of themes, many of which can be subsumed under concerns about a growing digital divide whereby society is being divided into information rich and information poor sectors. This differentiation can be between particular social groups irrespective of place, or between people in particular places be these large regional areas (e.g. metropolitan versus non-metropolitan) or localities and communities within an urban area. This paper focuses on the existence of a 'digital divide' across the Sydney metropolitan area. Using ABS 2001 census data the paper presents an analysis of computer and internet access and use for clusters of local communities and focuses on how usage differs across communities as differentiated by socio-economic status, household and family status and ethnic background

Design options for sample-based mortality surveillance

Background Reliable information on causes of death is a fundamental component of health development strategies, yet globally only about one-third of countries have access to such information. For countries currently without adequate mortality reporting systems there are useful models other than resource-intensive population-wide medical certification. Sample-based mortality surveillance is one such approach. This paper provides methods for addressing appropriate sample size considerations in relation to mortality surveillance, with particular reference to situations in which prior information on mortality is lacking. Methods The feasibility of model-based approaches for predicting the expected mortality structure and cause composition is demonstrated for populations in which only limited empirical data is available. An algorithm approach is then provided to derive the minimum person-years of observation needed to generate robust estimates for the rarest cause of interest in three hypothetical populations, each representing different levels of health development. Results Modelled life expectancies at birth and cause of death structures were within expected ranges based on published estimates for countries at comparable levels of health development. Total person-years of observation required in each population could be more than halved by limiting the set of age, sex, and cause groups regarded as 'of interest'. Discussion The methods proposed are consistent with the philosophy of establishing priorities across broad clusters of causes for which the public health response implications are similar. The examples provided illustrate the options available when considering the design of mortality surveillance for population health monitoring purposes.

A Mixture model with random-effects components for clustering correlated gene-expression profiles

Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.

Structural evolution in a hydrothermal reaction between Nb2O5 and NaOH solution: From Nb2O5 grains to microporous Na2Nb2O6 center dot(2)/3H2O fibers and NaNbO3 cubes

Niobium pentoxide reacts actively with concentrate NaOH solution under hydrothermal conditions at as low as 120 degrees C. The reaction ruptures the corner-sharing of NbO7 decahedra and NbO6 octahedra in the reactant Nb2O5, yielding various niobates, and the structure and composition of the niobates depend on the reaction temperature and time. The morphological evolution of the solid products in the reaction at 180 degrees C is monitored via SEM: the fine Nb2O5 powder aggregates first to irregular bars, and then niobate fibers with an aspect ratio of hundreds form. The fibers are microporous molecular sieve with a monoclinic lattice, Na2Nb2O6 center dot(2)/3H2O. The fibers are a metastable intermediate of this reaction, and they completely convert to the final product NaNbO3 Cubes in the prolonged reaction of 1 h. This study demonstrates that by carefully optimizing the reaction condition, we can selectively fabricate niobate structures of high purity, including the delicate microporous fibers, through a direct reaction between concentrated NaOH solution and Nb2O5. This synthesis route is simple and suitable for the large-scale production of the fibers. The reaction first yields poorly crystallized niobates consisting of edge-sharing NbO6 octahedra, and then the microporous fibers crystallize and grow by assembling NbO6 octahedra or clusters of NbO6 octahedra and NaO6 units. Thus, the selection of the fibril or cubic product is achieved by control of reaction kinetics. Finally, niobates with different structures exhibit remarkable differences in light absorption and photoluminescence properties. Therefore, this study is of importance for developing new functional materials by the wet-chemistry process.

Machine learning for matching astronomy catalogues

An emerging issue in the field of astronomy is the integration, management and utilization of databases from around the world to facilitate scientific discovery. In this paper, we investigate application of the machine learning techniques of support vector machines and neural networks to the problem of amalgamating catalogues of galaxies as objects from two disparate data sources: radio and optical. Formulating this as a classification problem presents several challenges, including dealing with a highly unbalanced data set. Unlike the conventional approach to the problem (which is based on a likelihood ratio) machine learning does not require density estimation and is shown here to provide a significant improvement in performance. We also report some experiments that explore the importance of the radio and optical data features for the matching problem.

Autonomia de Gestão dos Agrupamentos dos Centros de Saúde

The National Health Service is one of the portuguese social progress pillars and as a key role in terms of health services, organized around a universal service, general and tend to free, provided for the Portuguese Republic Constitution, in order to promote people's access to health care,adequate and adaptively to their needs and expectations, seeking economic efficiency in a control context of public expenditure and budget. Primary Health Care are considered fundamental piece for the National Health Service, as they are the first users accessibility to health care, being the health center a unit to serve and providing the essential first treatments, preventive and/or curative, assuming important functions of promotion of health and prevention of disease, cooperating with other services for continuity of caring. The implementation of the Health Centers Groupings aims to decentralize the management and allow decision making on key resources to the provision of care, absorbing the district offices of the extinct Health Sub-Regions and having the task of ensuring the provision of health care primary the population of a given geographical area, based on a multidisciplinary team with organization and technical autonomy and is guaranteed intercooperation with other functional units. However, these district offices were attached to the Regional Health Administrations following the reverse path, causing dysfunctional positions and making health centers Groupings their dependents. Thus, before the reform of Primary Health Care, all the structural changes were made, except to check the Health Centers Groupings proper management autonomy, currently one of the biggest obstacles to the implementation of such reform. It is intended in this work through a inquiry by forms done at 21 Health Centers Groupings North Regional Health Authority, IP, evidence can the management autonomy in Health Centers Groupings provide greater efficiency in the provision of Primary health Care to citizens and ensure greater sustainability of the National health Service, better managing existing resources, human and financial, showing a growing responsibility in its management and ensuring appropriate practices, more quality in health care and better accessibility, providing the ability to apply more adjusted measures in providing health care to the population of their geographical área.

Spatial correlations between beta-amyloid (Abeta) deposits and blood vessels in early-onset Alzheimer's disease

In cases of late-onset Alzheimer’s disease (AD), there is a spatial correlation between the classsic ‘cored’ type of Beta-amyloid (Abeta) deposit and the large vertically penetrating arterioles in the cerebral cortex suggesting that blood vessels are involved in the pathogenesis of the classic deposits. In this chapter, the spatial correlations between the diffuse, primitive, and classic Abeta deposits and blood vessels were studied in 10 cases of early-onset AD in the age range 40 – 65 years. Sections of frontal cortex were immunostained with antibodies against Abeta?and with collagen IV to reveal the Abeta deposits and blood vessel profiles. In the early-onset cases as a whole, all types of Abeta? deposit and blood vessel profiles were distributed in clusters. There was a positive spatial correlation between the clusters of the diffuse Abeta deposits and the larger (>10µm) and smaller diameter (<10?m) blood vessel profiles in one and three cases respectively. The primitive and classic Abeta deposits were spatially correlated with larger and smaller blood vessels both in three and four cases respectively. Spatial correlations between the Abeta deposits and blood vessels may be more prevalent in cases expressing amyloid precursor protein (APP) than presenilin 1 (PSEN1) mutations. Apolipoprotein E (Apo E) genotype of the patient did not appear to influence the spatial correlation with blood vessel profiles. The data suggest that the larger diameter blood vessels are less important in the pathogenesis of the classic Abeta deposits in early-onset compared with late-onset AD.

A hierarchical latent variable model for data visualization

Visualization has proven to be a powerful and widely-applicable tool the analysis and interpretation of data. Most visualization algorithms aim to find a projection from the data space down to a two-dimensional visualization space. However, for complex data sets living in a high-dimensional space it is unlikely that a single two-dimensional projection can reveal all of the interesting structure. We therefore introduce a hierarchical visualization algorithm which allows the complete data set to be visualized at the top level, with clusters and sub-clusters of data points visualized at deeper levels. The algorithm is based on a hierarchical mixture of latent variable models, whose parameters are estimated using the expectation-maximization algorithm. We demonstrate the principle of the approach first on a toy data set, and then apply the algorithm to the visualization of a synthetic data set in 12 dimensions obtained from a simulation of multi-phase flows in oil pipelines and to data in 36 dimensions derived from satellite images.