Discrete Event Systems based Design Patterns for Diagnosability Analysis of Automated Manufacturing Systems

The main goal of this thesis is to facilitate the process of industrial automated systems development applying formal methods to ensure the reliability of systems. A new formulation of distributed diagnosability problem in terms of Discrete Event Systems theory and automata framework is presented, which is then used to enforce the desired property of the system, rather then just verifying it. This approach tackles the state explosion problem with modeling patterns and new algorithms, aimed for verification of diagnosability property in the context of the distributed diagnosability problem. The concepts are validated with a newly developed software tool.

A Bayesian changepoint analysis on spatio-temporal point processes

Changepoint analysis is a well established area of statistical research, but in the context of spatio-temporal point processes it is as yet relatively unexplored. Some substantial differences with regard to standard changepoint analysis have to be taken into account: firstly, at every time point the datum is an irregular pattern of points; secondly, in real situations issues of spatial dependence between points and temporal dependence within time segments raise. Our motivating example consists of data concerning the monitoring and recovery of radioactive particles from Sandside beach, North of Scotland; there have been two major changes in the equipment used to detect the particles, representing known potential changepoints in the number of retrieved particles. In addition, offshore particle retrieval campaigns are believed may reduce the particle intensity onshore with an unknown temporal lag; in this latter case, the problem concerns multiple unknown changepoints. We therefore propose a Bayesian approach for detecting multiple changepoints in the intensity function of a spatio-temporal point process, allowing for spatial and temporal dependence within segments. We use Log-Gaussian Cox Processes, a very flexible class of models suitable for environmental applications that can be implemented using integrated nested Laplace approximation (INLA), a computationally efficient alternative to Monte Carlo Markov Chain methods for approximating the posterior distribution of the parameters. Once the posterior curve is obtained, we propose a few methods for detecting significant change points. We present a simulation study, which consists in generating spatio-temporal point pattern series under several scenarios; the performance of the methods is assessed in terms of type I and II errors, detected changepoint locations and accuracy of the segment intensity estimates. We finally apply the above methods to the motivating dataset and find good and sensible results about the presence and quality of changes in the process.

Microscopic and spectroscopic analysis of biogenic aerosols

Aerosol particles are important actors in the Earth’s atmosphere and climate system. They scatter and absorb sunlight, serve as nuclei for water droplets and ice crystals in clouds and precipitation, and are a subject of concern for public health. Atmospheric aerosols originate from both natural and anthropogenic sources, and emissions resulting from human activities have the potential to influence the hydrological cycle and climate. An assessment of the extent and impacts of this human force requires a sound understanding of the natural aerosol background. This dissertation addresses the composition, properties, and atmospheric cycling of biogenic aerosol particles, which represent a major fraction of the natural aerosol burden. The main focal points are: (i) Studies of the autofluo-rescence of primary biological aerosol particles (PBAP) and its application in ambient measure-ments, and (ii) X-ray microscopic and spectroscopic investigations of biogenic secondary organic aerosols (SOA) from the Amazonian rainforest.rnAutofluorescence of biological material has received increasing attention in atmospheric science because it allows real-time monitoring of PBAP in ambient air, however it is associated with high uncertainty. This work aims at reducing the uncertainty through a comprehensive characterization of the autofluorescence properties of relevant biological materials. Fluorescence spectroscopy and microscopy were applied to analyze the fluorescence signatures of pure biological fluorophores, potential non-biological interferences, and various types of reference PBAP. Characteristic features and fingerprint patterns were found and provide support for the operation, interpretation, and further development of PBAP autofluorescence measurements. Online fluorescence detection and offline fluorescence microscopy were jointly applied in a comprehensive bioaerosol field measurement campaign that provided unprecedented insights into PBAP-linked biosphere-atmosphere interactions in a North-American semi-arid forest environment. Rain showers were found to trigger massive bursts of PBAP, including high concentrations of biological ice nucleators that may promote further precipitation and can be regarded as part of a bioprecipitation feedback cycle in the climate system. rnIn the pristine tropical rainforest air of the Amazon, most cloud and fog droplets form on bio-genic SOA particles, but the composition, morphology, mixing state and origin of these particles is hardly known. X-ray microscopy and spectroscopy (STXM-NEXAFS) revealed distinctly different types of secondary organic matter (carboxyl- vs. hydroxy-rich) with internal structures that indicate a strong influence of phase segregation, cloud and fog processing on SOA formation, and aging. In addition, nanometer-sized potassium-rich particles emitted by microorganisms and vegetation were found to act as seeds for the condensation of SOA. Thus, the influence of forest biota on the atmospheric abundance of cloud condensation nuclei appears to be more direct than previously assumed. Overall, the results of this dissertation suggest that biogenic aerosols, clouds and precipitation are indeed tightly coupled through a bioprecipitation cycle, and that advanced microscopic and spectroscopic techniques can provide detailed insights into these mechanisms.rn

Structural patterns for document engineering: from an empirical bottom-up analysis to an ontological theory

This thesis aims at investigating a new approach to document analysis based on the idea of structural patterns in XML vocabularies. My work is founded on the belief that authors do naturally converge to a reasonable use of markup languages and that extreme, yet valid instances are rare and limited. Actual documents, therefore, may be used to derive classes of elements (patterns) persisting across documents and distilling the conceptualization of the documents and their components, and may give ground for automatic tools and services that rely on no background information (such as schemas) at all. The central part of my work consists in introducing from the ground up a formal theory of eight structural patterns (with three sub-patterns) that are able to express the logical organization of any XML document, and verifying their identifiability in a number of different vocabularies. This model is characterized by and validated against three main dimensions: terseness (i.e. the ability to represent the structure of a document with a small number of objects and composition rules), coverage (i.e. the ability to capture any possible situation in any document) and expressiveness (i.e. the ability to make explicit the semantics of structures, relations and dependencies). An algorithm for the automatic recognition of structural patterns is then presented, together with an evaluation of the results of a test performed on a set of more than 1100 documents from eight very different vocabularies. This language-independent analysis confirms the ability of patterns to capture and summarize the guidelines used by the authors in their everyday practice. Finally, I present some systems that work directly on the pattern-based representation of documents. The ability of these tools to cover very different situations and contexts confirms the effectiveness of the model.

Longitudinal analysis of patterns and predictors of changes in self-reported adherence to antiretroviral therapy: Swiss HIV Cohort Study

Adherence to combination antiretroviral therapy (cART) is a dynamic process, however, changes in adherence behavior over time are insufficiently understood.

Combining spatial-temporal and phylogenetic analysis approaches for improved understanding on global H5N1 transmission

Background Since late 2003, the highly pathogenic influenza A H5N1 had initiated several outbreak waves that swept across the Eurasia and Africa continents. Getting prepared for reassortment or mutation of H5N1 viruses has become a global priority. Although the spreading mechanism of H5N1 has been studied from different perspectives, its main transmission agents and spread route problems remain unsolved. Methodology/Principal Findings Based on a compilation of the time and location of global H5N1 outbreaks from November 2003 to December 2006, we report an interdisciplinary effort that combines the geospatial informatics approach with a bioinformatics approach to form an improved understanding on the transmission mechanisms of H5N1 virus. Through a spherical coordinate based analysis, which is not conventionally done in geographical analyses, we reveal obvious spatial and temporal clusters of global H5N1 cases on different scales, which we consider to be associated with two different transmission modes of H5N1 viruses. Then through an interdisciplinary study of both geographic and phylogenetic analysis, we obtain a H5N1 spreading route map. Our results provide insight on competing hypotheses as to which avian hosts are responsible for the spread of H5N1. Conclusions/Significance We found that although South China and Southeast Asia may be the virus pool of avian flu, East Siberia may be the source of the H5N1 epidemic. The concentration of migratory birds from different places increases the possibility of gene mutation. Special attention should be paid to East Siberia, Middle Siberia and South China for improved surveillance of H5N1 viruses and monitoring of migratory birds.

Pre-Columbian human occupation patterns in the eastern plains of the Llanos de Moxos, Bolivian Amazonia

Despite an increasing number of publications regarding the Pre-Columbian earthworks of the Llanos de Moxos, there have been no serious attempts to undertake a systematic survey of the archaeological remains of this lowland region in the Bolivian Amazon. Based on the GIS analysis of data gathered in the field and retrieved from satellite images, we discuss the spatial distribution of the Pre-Columbian settlements in a 4500 Km2 area of the Llanos de Moxos to the east of Trinidad, capital of the Beni Department, and their relationship with the geographical settings. Our findings shed new light on the prehistory of the region and bear important implications for our understanding of the impact of Pre-Columbian human occupation.

Protective and risk factors in amateur equestrians and description of injury patterns: A retrospective data analysis and a case - control survey

Background In Switzerland there are about 150,000 equestrians. Horse related injuries, including head and spinal injuries, are frequently treated at our level I trauma centre. Objectives To analyse injury patterns, protective factors, and risk factors related to horse riding, and to define groups of safer riders and those at greater risk Methods We present a retrospective and a case-control survey at conducted a tertiary trauma centre in Bern, Switzerland. Injured equestrians from July 2000 - June 2006 were retrospectively classified by injury pattern and neurological symptoms. Injured equestrians from July-December 2008 were prospectively collected using a questionnaire with 17 variables. The same questionnaire was applied in non-injured controls. Multiple logistic regression was performed, and combined risk factors were calculated using inference trees. Results Retrospective survey A total of 528 injuries occured in 365 patients. The injury pattern revealed as follows: extremities (32%: upper 17%, lower 15%), head (24%), spine (14%), thorax (9%), face (9%), pelvis (7%) and abdomen (2%). Two injuries were fatal. One case resulted in quadriplegia, one in paraplegia. Case-control survey 61 patients and 102 controls (patients: 72% female, 28% male; controls: 63% female, 37% male) were included. Falls were most frequent (65%), followed by horse kicks (19%) and horse bites (2%). Variables statistically significant for the controls were: Older age (p = 0.015), male gender (p = 0.04) and holding a diploma in horse riding (p = 0.004). Inference trees revealed typical groups less and more likely to suffer injury. Conclusions Experience with riding and having passed a diploma in horse riding seem to be protective factors. Educational levels and injury risk should be graded within an educational level-injury risk index.

Macroevolutionary patterns in the diversification of parrots: effects of climate change, geological events and key innovations

Aim Parrots are thought to have originated on Gondwana during the Cretaceous. The initial split within crown group parrots separated the New Zealand taxa from the remaining extant species and was considered to coincide with the separation of New Zealand from Gondwana 82-85 Ma, assuming that the diversification of parrots was mainly shaped by vicariance. However, the distribution patterns of several extant parrot groups cannot be explained without invoking transoceanic dispersal, challenging this assumption. Here, we present a temporal and spatial framework for the diversification of parrots using external avian fossils as calibration points in order to evaluate the relative importance of the influences of past climate change, plate tectonics and ecological opportunity. Location Australasian, African, Indo-Malayan and Neotropical regions. Methods Phylogenetic relationships were investigated using partial sequences of the nuclear genes c-mos, RAG-1 and Zenk of 75 parrot and 21 other avian taxa. Divergence dates and confidence intervals were estimated using a Bayesian relaxed molecular clock approach. Biogeographic patterns were evaluated taking temporal connectivity between areas into account. We tested whether diversification remained constant over time and if some parrot groups were more species-rich than expected given their age. Results Crown group diversification of parrots started only about 58 Ma, in the Palaeogene, significantly later than previously thought. The Australasian lories and possibly also the Neotropical Arini were found to be unexpectedly species-rich. Diversification rates probably increased around the Eocene/Oligocene boundary and in the middle Miocene, during two periods of major global climatic aberrations characterized by global cooling. Main conclusions The diversification of parrots was shaped by climatic and geological events as well as by key innovations. Initial vicariance events caused by continental break-up were followed by transoceanic dispersal and local radiations. Habitat shifts caused by climate change and mountain orogenesis may have acted as a catalyst to the diversification by providing new ecological opportunities and challenges as well as by causing isolation as a result of habitat fragmentation. The lories constitute the only highly nectarivorous parrot clade, and their diet shift, associated with morphological innovation, may have acted as an evolutionary key innovation, allowing them to explore underutilized niches and promoting their diversification.

A Social Network Analysis Of Hamadryas Baboons

The study of animal sociality investigates the immediate and long-term consequences that a social structure has on its group members. Typically, social behavior is observed from interactions between two individuals at the dyadic level. However, a new framework for studying social behavior has emerged that allows the researcher to assess social complexity at multiple scales. Social Network Analysis has been recently applied in the field of ethology, and this novel tool enables an approach of focusing on social behavior in context of the global network rather than limited to dyadic interactions. This new technique was applied to a group of captive hamadryas baboons (Papio hamadryas hamadryas) in order to assess how overall network topology of the social group changes over time with the decline of an aging leader male. Observations on aggressive, grooming, and proximity spatial interactions were collected from three separate years in order to serve as `snapshots¿ of the current state of the group. Data on social behavior were collected from the group when the male was in prime health, when the male was at an old age, and after the male¿s death. A set of metrics was obtained from each time period for each type of social behavior and quantified a change in the patterns of interactions. The results suggest that baboon social behavior varies across context, and changes with the attributes of its individual members. Possible mechanisms for adapting to a changing social environment were also explored.

Limitations of Remotely-sensed Aerosol as a Spatial Proxy for Fine Particulate Matter

Recent research highlights the promise of remotely-sensed aerosol optical depth (AOD) as a proxy for ground-level PM2.5. Particular interest lies in the information on spatial heterogeneity potentially provided by AOD, with important application to estimating and monitoring pollution exposure for public health purposes. Given the temporal and spatio-temporal correlations reported between AOD and PM2.5 , it is tempting to interpret the spatial patterns in AOD as reflecting patterns in PM2.5 . Here we find only limited spatial associations of AOD from three satellite retrievals with PM2.5 over the eastern U.S. at the daily and yearly levels in 2004. We then use statistical modeling to show that the patterns in monthly average AOD poorly reflect patterns in PM2.5 because of systematic, spatially-correlated error in AOD as a proxy for PM2.5 . Furthermore, when we include AOD as a predictor of monthly PM2.5 in a statistical prediction model, AOD provides little additional information to improve predictions of PM2.5 when included in a model that already accounts for land use, emission sources, meteorology and regional variability. These results suggest caution in using spatial variation in AOD to stand in for spatial variation in ground-level PM2.5 in epidemiological analyses and indicate that when PM2.5 monitoring is available, careful statistical modeling outperforms the use of AOD.