A qualidade de vida urbana tem sido estudada pelas mais diversas áreas do conhecimento e é uma temática complexa. O tema qualidade de vida envolve questões multidisciplinares apresentadas por meio de perspectivas diferenciadas, de acordo com a relevância do momento histórico, das condições sociais, bem como da ideologia dominante a partir dos objetivos propostos. Isso posto, a abordagem adotada no presente estudo está focada na satisfação das necessidades básicas da população, de modo a garantir o pleno desenvolvimento físico, mental e social. Para isso, foram abordadas quatro dimensões: condições de saneamento, situação socioeconômica e demografia, por meio da utilização dos dados censitários (IBGE, 2000) e as zonas residenciais homogêneas, por meio de técnicas de interpretação de imagens de satélite com alta resolução espacial. Para a espacialização e processamento dos dados quantitativos e qualitativos foram utilizadas técnicas de Geoprocessamento, por meio do uso de um Sistema de Informação Geográfica e técnicas estatísticas, que garantiram a distribuição espacial dos dados levantados. A partir dos resultados alcançados por meio dessas técnicas, foi possível elaborar o mapa síntese da qualidade de vida do distrito da Cachoeirinha, zona norte da cidade de São Paulo. / The quality of urban life has been studied in various areas of academic specialization and is a complex theme. The subject\'s quality of life involves multi-disciplinary questions presented with different perspectives, according to the relevance of the historical moment, social conditions, as well as the dominant ideology shaping the objectives in question. The approach adopted in the present study is focused on the satisfaction of the basics needs of the population, in order to guarantee complete physical, mental and social development. For this, four dimensions were considered: conditions of sanitation; the socioeconomic situation and demography; using data of the last demographic Census in 2000 (IBGE, 2000); and homogeneous residential zones, by means of technical interpretation of satellite images with high spatial resolution. For the spatial results and processing of quantitative and qualitative data, techniques of Geoprocessing had been used, using Geographic Information System and statistical techniques, which had guaranteed the spatial distribution of the listed data. From the results obtained with these techniques, it was possible to elaborate the map synthesis of the quality of life of Cachoeirinha District, northern zone of São Paulo, Brazil.

The fundamental components of a coral reef are coral, algae, and sand. At its simplest assessing the status of a coral reef may be reduced to quantifying the relative benthic cover of these three bottom-types. While in situ surveys can provide an accurate census on an individual reef scale (10s of meters), the only feasible method to surveys coral reefs on a reef tract (10-100s of kilometers) or worldwide scale is through the use of remote sensing. Remote sensing is a means of surveying entire ecosystems. A major issue in remote sensing of coastal environments is the confounding effects of the water column on the signal emerging from the water column. We used a simulation method to model differing levels of environmental parameters, which occur in marine ecosystems, with HydrolightEcolight 5. Simulated data were interpolated with actual bottom; type spectra to determine the accuracy of a classification function developed in MATLAB. The aim was to distinguish bottom-types as well as predict levels of water column parameters. The results of this study demonstrate that bottom-type (78% algae, 84% coral, and 94% sand) and chlorophyll concentration (85-90% across range) are well determined, while depth and suspended sediment load are not as well predicted (<70%) and has a tendency to slightly over predict depth.

A banana é altamente susceptível a injúrias causadas pelo frio, mas o efeito da refrigeração nos atributos que caracterizam a qualidade do fruto maduro é ainda pouco explorado. Neste trabalho, alguns desses atributos foram analisados em duas cultivares de banana escolhidas por sua diferença em relação à susceptibilidade ao frio: Nanicão e Prata. As duas cultivares foram armazenadas a baixas temperaturas (cv. Nanicão a 13 ºC e cv. Prata a 13 ºC e 10 ºC) por 15 dias e o efeito do frio sobre os compostos voláteis responsáveis pelo aroma e sabor, índices de cor da casca, níveis de carotenoides, açúcares e amido foram analisados comparativamente durante a maturação dos frutos e o perfil de proteínas diferentemente abundantes foi analisado na cultivar Nanicão. Com o auxílio das ferramentas da estatística multivariada, verificou-se que a produção dos compostos voláteis é altamente sensível as baixas temperaturas. A cv. Prata apresentou uma maior resistência ao efeito negativo do armazenamento, mesmo armazenada a 10 ºC. Na cv. Nanicão, as amostras maduras do grupo frio (13 ºC) foram caracterizadas pela presença dos carotenoides majoritários devido ao fato de que as vias metabólicas que utilizam carotenoides terem sido afetadas pelo armazenamento em baixas temperaturas. Para a cv. Prata teve um efeito negativo com o armazenamento, com redução dos níveis de carotenoides tanto a 13 ºC quanto a 10 ºC. Em relação à cor da casca dos frutos não foi observado um efeito evidente nas amostras submetidas a baixas temperaturas. Pela análise proteômica, foi possível entender como o frio causou um impacto negativo na síntese de sacarose, uma vez que as proteínas mais afetadas foram associadas ao metabolismo de energia e de carboidratos. / Bananas are fruits highly susceptible to injuries caused by cold temperatures, but the effect of refrigeration on the attributes that characterize the quality of ripe fruit is still underexplored. In this work, some of these attributes were analyzed in two banana cultivars chosen for their difference in susceptibility to cold temperatures: Nanicão and Prata. Both cultivars were stored at low temperatures (cv. Nanicão at 13 ºC and cv. Prata at 13 °C and 10 °C) for 15 days and the effect of the cold on the volatile compounds responsible for aroma, skin color index, levels of carotenoids, sugars, and starch were comparatively analyzed during fruit maturation and different abundant protein profiles of the Nanicão cultivar were analyzed. By using multivariate statistic tools, it was found that the production of volatile compounds is highly susceptible to low temperatures. However, cv. Prata showed greater resistance to the negative effects of storage even when stored at 10 °C. For cv. Nanicão, ripe samples from the cold group kept at 13 ºC were characterized by the presence of majority carotenoids due to the fact that the metabolic pathways that use carotenoids were affected by the storage at such a low temperature. Conversely, cv. Prata experienced a negative effect with the storage, with reduced levels of carotenoids in both cold groups kept at 13 ºC and 10 ºC. In relation the skin color of the fruit, no effect on the samples held at low temperatures was observed. For proteomics analysis, it was possible to understand how the cold storage caused a negative impact on the synthesis of sucrose, since most of the affected proteins were associated with energy and carbohydrate metabolism.

This thesis uses the case study of the Fallas festival in the city of Valencia (Spain), to assess the value of intangible cultural heritage. Within this framework the thesis explores a number of different issues: for example how social agents frame different qualities and benefits of cultural heritage in order to describe the value and claims for funding the arts. It finds that value assessment for claiming funds presents many challenges such as: identifying the values of the heritage in question; describing them; and ranking them according to their contribution to the public welfare. It examines the methodological techniques for assessing heritage values and goes on to discuss a number of tools that are, or could be, used for assessment. The thesis also explores how public bodies legitimise cultural funding. It examines the role of non-government arts organisations in supporting the arts. It proposes the analysis of donor decisions through a multi-attribute technique where donors state their importance to donor situations under specific conditions or attributes. Finally, it describes how the stakeholder approach can be applied for searching new ways of funding festivals. It also considers how intangible cultural heritage goods can be assessed within the process of cost-benefit evaluation. It also analyses how public bodies, as the principal supporters of culture, deal with the problem of valuing intangibles on social investments. The study uses the Fallas festival to test the research hypothesis. It uses a number of economic and statistical techniques to evaluate the Fallas Festival, these include Contingent Valuation, Choice Experiment and Descriptive and Multiatribute Statistics. The statistical techniques reveal that historical benefits are intrinsically valuable in the Fallas festival. The historical value that the members of the neighbourhood associations place on the Fallas festival justify that local social agents should support this festival. / Sánchez Royo, B. (2011). AN APPROACH TOWARDS HOLISTIC ASSESSMENT OF SOCIO-ECONOMIC IMPACTS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/12269 / Palancia

Le séquençage du génome humain, il y a maintenant 12 ans, a mis en lumière la complexité des mécanismes des processus nucléaires tels que la transcription, la réplication ou l'organisation de la chromatine. Depuis, afin de mieux comprendre ces processus, un ensemble sans cesse croissant de données sur le noyau cellulaire a été produit et mis en ligne par un nombre important de laboratoires de par le monde. Ces données sont à la fois d'une richesse extraordinaire et d'une complexité embarrassante. Dans cette thèse, nous mettons à profit l'ensemble de ces données afin de mieux comprendre les déterminants nucléaires du programme spatio-temporel de réplication. Pour cela nous utilisons pas moins d'une centaine de profils épigénétiques ChiP-seq le long des chromosomes humains et dans diverses lignées cellulaires pour caractériser la structure primaire de la chromatine. Nous démontrons, à l'aide d'outils issus des statistiques multivariées, que l'immense complexité potentielle de ces jeux de données peut être réduite à quatre états chromatiniens principaux et ce dans toutes les lignées cellulaires somatiques étudiées. Cette classification simple, robuste et néanmoins complète est un excellent point d'appui pour l'étude de la réplication. Les quatre états principaux de chromatine sont répliqués à des moments distinct de la phase S (leur « timing » de réplication est différent) et ont un contenu en gènes drastiquement différents. Leur répartition spatiale le long du génome est structurée et est particulièrement visible dans les domaines où le « timing » de réplication dessine un U comme signature de l'existence d'un gradient de polarité des fourches de réplication. Ces U-domaines de la taille du Mpb recouvrent 50% du génome humain et les quatre états chromatiniens principaux se succèdent du bord au centre de ces U-domaines. Les mêmes techniques statistiques appliquées au cas d'une lignée embryonnaire révèlent aussi l'existence de quatre états principaux de chromatine mais de nature différente. La classification en quatre états s'avèrent alors très utile pour comparer l'épigénétique d'une lignée somatique à celle d'une lignée embryonnaire. Aussi, les spécificités du programme de réplication embryonnaire sont mises en rapport avec les spécificités de l'organisation de la chromatine dans cette lignée cellulaire. En particulier, notre étude révèle le rôle majeur de l'histone variant H2AZ dans la pluripotence. / The sequencing of the human genome, twelve years ago, revealed the complexity of the mechanisms underlying nuclear process such as transcription, replication and chromatin organization. In the past few years, to delineate better these processes, datasets on the cell nucleus were gathered and made available online by numerous laboratories around the world. These datasets are, at once, extraordinarily rich and daunting to handle. In this thesis, we take advantage of these datasets to understand better the nuclear determinants of the replication program. We analyze not less than a hundred ChiP-seq profiles along human chromosomes in several cell lines to characterize the primary structure of chromatin. We demonstrate, when using tools from multivariate statistics, that the immense potential complexity of these datasets can be reduced to four prevalent chromatin states in all studied somatic cell lines. This simple and comprehensive classification is an excellent starting point for the study of replication. The four prevalent chromatin states are replicated at different moments of the S-phase (they have a different replication “timing”) and have drasticaly different gene contents. Their spatial repartition along the genome is structured, especially in domains where the timing replication is U-shaped. These megabase sized U-domains cover 50% of the human genome and the four prevalent chromatin states succeed each other from their borders to their center. The same statistical techniques applied on an embryonic stem cell (ESC) also reduced the epigenetic complexity to four prevalent chromatin states which are qualitatively different from the ones in somatic cells. We further show that the specificities of embryonic replication program are link to the specificities of embryonic chromatin. Importantly, our study reveals that the histone variant H2AZ plays a major role in pluripotency.

No description available.

No description available.

This study aims to determine the concentration of 16 Polycyclic Aromatic Hydrocarbons (PAHs) in urban soils from West Yorkshire in order to determine what the factors are controlling their distribution and abundances. Although PAHs have been reported before from soils and sediments, the majority of these studies have come from China, sometimes with contrasting results, which emphasises the need to obtain equivalent data from other areas. Therefore this work provides the first measurements of their type from the area studied. Soil samples were collected from one hundred sites across an area from Bradford to Leeds on two occasions, one in autumn and one in the following summer. The soil samples were analyzed by X-ray diffraction and all found to have similar mineralogical composition, which was mainly silica and calcite. Trials using iodine as a marker for PAHs showed there were notable interactions between the minerals and PAHs, with calcium carbonate absorbing PAHs much more than silica. There is a negative correlation between the soil organic content (determined by loss on ignition) and PAHs, which confirms the PAH-mineral interaction. Gas chromatography with mass spectrometry (GC-MS) using targeted selected ion monitoring was used to determine and quantify PAHs in the one hundred soil samples with the aid of PAH external standards. The results showed highest concentrations of total PAHs in the same sample from Leeds from the autumn (1,525 ng/g) and in the summer (1,768 ng/g). In Bradford there was only moderate pollution of PAHs, the maximum being 122 ng/g. However the majority of data from Bradford showed lower levels of pollution in both summer and autumn. On the basis of prior published information, the ratio of these compounds has been used to help in identifying sources. In the samples collected from Bradford in both seasons and Leeds in autumn the PAH pollution originated from pyrogenic, biomass and petroleum combustion, however in the summer the source appeared more to be from a petrogenic source. These ratios in the samples which were collected from the area between Bradford and Leeds implied pyrogenic, biomass source of pollution in the autumn, but in the summer another source of organic compounds was indicated namely petroleum combustion. When the locations were resampled nine months later, after taking into account within-site variability, there was a strong indication that the PAH concentrations were higher. This might have been due to a seasonal effect, but when a further (third) subsample was taken at a later date it showed a further increase in PAH level which suggests the effect is accumulative rather than seasonal. The results were analysed using Principal Component Analysis (PCA) to determine whether the type of road had an effect on the concentration of the 16 PAHs compounds, but it was concluded that there was no such effect. However, the distance from the soil sample to the nearest road did have an effect on the concentration of the 16 PAH compounds, especially in soil samples having the shortest distance to the road. Traffic volume was also tested and found to influence the PAH concentrations. It is notable that, comparing the groupings from autumn with those from summer by cluster analyses, they largely had the same compounds grouping together in both cases; only two compounds differed at all in where they occurred in the clusters, with consistent patterns of grouping found for the other compounds. These analyses indicate that PAH compounds behave in a consistent way amongst groups of PAH compounds. The grouping of PAHs appears linked to their sources rather than number of rings or molecular weight. / Libyan Government and Embassy

Diese Dissertation stellt drei sich ergänzende Fortschritte in der statistischen Modellierung multivariater Daten vor und behandelt Herausforderungen im Bereich des modellbasierten Clusterings für hochdimensionale Daten, der Analyse longitudinaler Daten sowie der multivariaten Verteilungsregression. Der erste Forschungszweig konzentriert sich auf tiefe Gaußsche Mischmodelle, eine leistungsfähige Erweiterung herkömmlicher Gaußscher Mischmodelle. Wir erforschen Bayessche Inferenz mit Sparsamkeitsprioris zur Regularisierung der Schätzung tiefer Mischmodelle und stellen ein innovatives tiefes Mischmodell von Faktormodellen vor, das in der Lage ist, hochdimensionale Probleme zu bewältigen. Der zweite Forschungsstrang erweitert tiefe Mischmodelle von Clustering zu Regression. Unter Verwendung des tiefen Mischmodells von Faktormodellen als Prior für Zufallseffekte stellen wir einen innovativen Ansatz vor: tiefe Mischmodelle von linearen gemischten Modellen, der lineare gemischte Modelle so erweitert, dass er den Komplexitäten longitudinaler Daten mit vielen Beobachtungen pro Subjekt und komplexen zeitlichen Trends gerecht wird. Dieser Forschungszweig überwindet Beschränkungen gegenwärtiger Modelle und präsentiert eine anpassungsfähige Lösung für hochdimensionale Szenarien. Der dritte Forschungszweig setzt sich mit der Herausforderung auseinander, wahrhaft multivariate Verteilungen im Kontext von Generalisierten Additiven Modellen für Ort, Skala und Form zu modellieren. Wir präsentieren einen innovativen Ansatz, der Copula-Regression nutzt, um die Abhängigkeitsstruktur mittels einer Gauß-Copula zu modellieren. Dies ermöglicht die gemeinsame Modellierung hochdimensionaler Vektoren mit flexiblen marginalen Verteilungen. Hier erleichtert bayessche Inferenz die effiziente Schätzung des stark parametrisierten Modells und führt zu einem äußerst flexiblen Ansatz im Vergleich zu bestehenden Modellen. / This thesis introduces three complementary advancements in statistical modeling for multivariate data, addressing challenges in model-based clustering for high-dimensional data, longitudinal data analysis, and multivariate distributional regression. The first research strand focuses on deep Gaussian mixture models, a powerful extension of ordinary Gaussian mixture models. We explore the application of Bayesian inference with sparsity priors to regularize the estimation of deep mixtures, presenting a novel Bayesian deep mixtures of factor analyzers model capable of handling high-dimensional problems. The inclusion of sparsity-inducing priors in the model contributes to improved clustering results. A scalable natural gradient variational inference algorithm is developed to enhance computational efficiency. The second research strand extends deep mixture models from clustering towards regression. Leveraging the deep mixtures of factor analyzers model as a prior for random effects, we introduce a novel framework, deep mixtures of linear mixed models that extends mixtures of linear mixed models to accommodate the complexities of longitudinal data with many observations per subject and intricate temporal trends. We describe an efficient variational inference approach. This research addresses the limitations of current models and provides a flexible solution for high-dimensional settings. The third research strand tackles the challenge of modeling truly multivariate distributions in the context of Generalized Additive Models for Location, Scale, and Shape. We propose a novel approach utilizing copula regression to model the dependence structure through a Gaussian copula, allowing for joint modeling of high-dimensional response vectors with flexible marginal distributions. Here, Bayesian inference facilitates efficient estimation of the highly parameterized model, introducing a highly flexible and complementary approach to existing models.

Sociotechnical systems (STSs) rely on the collaboration between humans and autonomous decision-making units to fulfill their objectives. Highly intertwined social and technical contextual factors influence the collaboration between these human and engineered elements, and consequently the performance characteristics of the STS. In the next two decades, the role allocated to STSs in our society will drastically increase. Thus, the effective design of STSs requires an improved understanding of the human-autonomy interdependency. This dissertation brings together management science along with systems thinking and uses a mixed-methods approach to investigate the interdependencies between people and the autonomous systems they collaborate within complex socio-technical enterprises. The dissertation is organized in three mutually exclusive essays, each investigating a distinct facet of STSs: safe management, collaboration, and efficiency measurement. The first essay investigates the amount of work allocated to safety-critical decision makers and quantifies Rasmussen's workload boundary that represents the limit of attainable workload. The major contribution of this study is to quantify the qualitative theoretical construct of the workload boundary through a Pareto-Koopmans frontier. This frontier allows one to capture the aggregate impact of the social and technical factors that originate from operational conditions on workload. The second essay studies how teams of humans and their autonomous partners share work, given their subjective preferences and contextual operational conditions. This study presents a novel integration of machine learning algorithms in an efficiency measurement framework to understand the influence of contextual factors. The results demonstrate that autonomous units successfully handle relatively simple operational conditions, while complex operational conditions require both workers and their autonomous counterparts to collaborate towards common objectives. The third essay explores the complementary and contrasting roles of efficiency measurement approaches that deal with the influence of contextual factors and their sensitivity to sample size. The results are organized in a structured taxonomy of their fundamental assumptions, limitations, mathematical structure, sensitivity to sample size, and their practical usefulness. To summarize, this dissertation provides an interdisciplinary and pragmatic research approach that benefits from the strengths of both theoretical and data-driven empirical approaches. Broader impacts of this dissertation are disseminated among the literatures of systems engineering, operations research, management science, and mechanical design. / Doctor of Philosophy / A system is an integrated set of elements that achieve a purpose or goal. An autonomous system (ADS) is an engineered element that often substitutes for a human decision-maker, such as in the case of an autonomous vehicle. Sociotechnical systems (STSs) are systems that involve the collaboration of a human decision-maker with an ADS to fulfill their objectives. Historically, STSs have been used primarily for handling safety critical tasks, such as management of nuclear power plants. By design, STSs rely heavily on a collaboration between humans and ADS decision-makers. Therefore, the overall characteristics of a STS, such as system safety, performance, or reliability; is fully dependent on human decisions. The problem with that is that people are independent entities, who can be influenced by operational conditions. Unlike their engineered counterparts, people can be cognitively challenged, tired, or distracted, and consequently make mistakes. The current dependency on human decisions, incentivize business owners and engineers alike to increase the level of automation in engineered systems. This allows them to reduce operational costs, increase performance, and minimize human errors. However, the recent commercial aircraft accidents (e.g., Boeing 737-MAX) have indicated that increasing the level of automation is not always the best strategy. Given that increasing technological capabilities will spread the adoption of STSs, vast majority of existing jobs will either be fully replaced by an ADS or will change from a manual set-up into a STS. Therefore, we need a better understanding of the relationships between social (human) and engineered elements. This dissertation, brings together management science with systems thinking to investigate the dependencies between people and the autonomous systems they collaborate within complex socio-technical enterprises. The dissertation is organized in three mutually exclusive essays, each investigating a distinct facet of STSs: safe management, collaboration, and efficiency measurement. The first essay investigates the amount of work handled by safety-critical decision makers in STSs. Primary contribution of this study is to use an analytic method to quantify the amount of work a person could safely handle within a STSs. This method also allows to capture the aggregate impact of the social and technical factors that originate from operational conditions on workload. The second essay studies how teams of humans and their autonomous partners share work, given their preferences and operational conditions. This study presents a novel integration of machine learning algorithms to understand operational influences that propel a human-decision maker to handle the work manually or delegate it to ADSs. The results demonstrate that autonomous units successfully handle simple operational conditions. More complex conditions require both workers and their autonomous counterparts to collaborate towards common objectives. The third essay explores the complementary and contrasting roles of data-driven analytical management approaches that deal with the operational factors and investigates their sensitivity to sample size. The results are organized based on their fundamental assumptions, limitations, mathematical structure, sensitivity to sample size, and their practical usefulness. To summarize, this dissertation provides an interdisciplinary and pragmatic research approach that benefits from the strengths of both theoretical and data-driven empirical approaches. Broader impacts of this dissertation are disseminated among the literatures of systems engineering, operations research, management science, and mechanical design.