Universiẗat, Diss., 2004--Stuttgart.

In this thesis we present LaSLAT, a sensor network algorithm thatsimultaneously localizes sensors, calibrates sensing hardware, andtracks unconstrained moving targets using only range measurementsbetween the sensors and the target. LaSLAT is based on a Bayesian filter, which updates a probabilitydistribution over the quantities of interest as measurementsarrive. The algorithm is distributable, and requires only a constantamount of space with respect to the number of measurementsincorporated. LaSLAT is easy to adapt to new types of hardware and newphysical environments due to its use of intuitive probabilitydistributions: one adaptation demonstrated in this thesis uses amixture measurement model to detect and compensate for bad acousticrange measurements due to echoes.We also present results from a centralized Java implementation ofLaSLAT on both two- and three-dimensional sensor networks in whichranges are obtained using the Cricket ranging system. LaSLAT is ableto localize sensors to within several centimeters of their groundtruth positions while recovering a range measurement bias for eachsensor and the complete trajectory of the mobile.

abstract: The tracking of multiple targets becomes more challenging in complex environments due to the additional degrees of nonlinearity in the measurement model. In urban terrain, for example, there are multiple reflection path measurements that need to be exploited since line-of-sight observations are not always available. Multiple target tracking in urban terrain environments is traditionally implemented using sequential Monte Carlo filtering algorithms and data association techniques. However, data association techniques can be computationally intensive and require very strict conditions for efficient performance. This thesis investigates the probability hypothesis density (PHD) method for tracking multiple targets in urban environments. The PHD is based on the theory of random finite sets and it is implemented using the particle filter. Unlike data association methods, it can be used to estimate the number of targets as well as their corresponding tracks. A modified maximum-likelihood version of the PHD (MPHD) is proposed to automatically and adaptively estimate the measurement types available at each time step. Specifically, the MPHD allows measurement-to-nonlinearity associations such that the best matched measurement can be used at each time step, resulting in improved radar coverage and scene visibility. Numerical simulations demonstrate the effectiveness of the MPHD in improving tracking performance, both for tracking multiple targets and targets in clutter. / Dissertation/Thesis / M.S. Electrical Engineering 2011

Reproductive endpoints are generally not considered in regulatory risk assessments used to inform registration decisions for pesticides, and relatively few studies have examined effects of herbicides on reproduction in non-target plants. In two sets of greenhouse experiments using three wild species (Rudbeckia hirta L., Centaurea cyanus L. and Trifolium pratense L), effects on flowering phenology and inflorescence characteristics were investigated following low, drift-equivalent glyphosate exposure at an early bud stage. Weekly post-spray observations included the number of inflorescences, aborted buds and malformed inflorescences. In the experiment focusing on inflorescence characteristics (C. cyanus and T. pratense only), inflorescences and pollen were collected at five weeks post-spray to measure inflorescence dry weight, count the number of reproductive florets, estimate the amount of pollen per floret, and assess pollen germination in vitro. Flower production was adversely affected in all three species, including delays in flowering, significant increases in the number of aborted buds and malformed inflorescences, an overall reduction in the number of inflorescences produced, as well as a reduction in the duration of individual inflorescence bloom time (R. hirta and T. pratense assessed only). Inflorescence dry weight and in vitro pollen germination were significantly reduced for C. cyanus exposed to glyphosate, but not for T. pratense. However, both species experienced a significant reduction in the number of reproductive florets produced per inflorescence in response to glyphosate exposure. Neither species was observed to have significant reductions in the amount of pollen produced per reproductive floret. These results have important implications for risk assessment, demonstrating that current glyphosate use in Canada and elsewhere could be adversely affecting non-target flowering plants in field margins, as well as other taxa that rely on them, particularly pollinators. Les effets sur la reproduction des plantes ne sont généralement pas pris en ligne de compte dans les évaluations réglementaires sur les risques des pesticides lors de leur homologation. De plus, relativement peu d'études ont examiné les effets des herbicides sur la reproduction des plantes non ciblées. Dans deux séries d'expériences en serres avec trois espèces sauvages (Rudbeckia hirta L., Centaurea cyanus L. et Trifolium pratense L), les effets sur la phénologie florale et les caractéristiques des inflorescences ont été étudiés après une faible exposition au glyphosate équivalente à la dérive durant la pulvérisation lorsque les plantes sont au début des boutons floraux. Des observations hebdomadaires post-pulvérisation ont été effectuées sur le nombre d'inflorescences, de bourgeons avortés et d’inflorescences malformées. Dans l'expérience portant sur les caractéristiques des inflorescences (C. cyanus et T. pratense seulement), les inflorescences et le pollen ont été recueillis cinq semaines après la pulvérisation pour mesurer le poids sec des inflorescences, compter le nombre de fleurons reproducteurs, estimer la quantité de pollen par fleur et évaluer la germination du pollen in vitro. La production de fleurs a été affectée chez les trois espèces, y compris des retards de floraison, des augmentations significatives du nombre de bourgeons avortés et d’inflorescences malformées, une réduction globale du nombre d'inflorescences produites et une diminution de la durée de floraison par inflorescence. (R. hirta et T. pratense évalués seulement). Le poids sec des inflorescences et la germination in vitro du pollen ont été significativement réduits chez C. cyanus exposé au glyphosate, mais pas chez T. pratense. Cependant, les deux espèces ont subi une réduction significative du nombre de fleurons reproducteurs produits par inflorescence en réponse à l'exposition au glyphosate. Aucune des deux espèces n'a montré de réduction significative de la quantité de pollen produit par fleuron. Ces résultats ont des implications importantes pour l'évaluation de risques, démontrant que le glyphosate, tel qu’utilisé présentement au Canada et ailleurs, pourrait nuire aux plantes à fleurs non ciblées retrouvées en bordure de champs, ainsi qu'à d'autres taxons qui en dépendent, particulièrement les pollinisateurs.

This thesis explores the implementation of an area-based health improvement initiative in the north west of England called Target Wellbeing. In the decades before Target Wellbeing was commissioned in 2007, health inequalities between people living in different areas of the UK had been widening. ABIs were identified by the Labour Government as a key tool for improving the health and wellbeing of residents in areas of socio-economic disadvantage and addressing inequalities in health. ABIs such as this have been well evaluated but there remains no firm evidence about the ability of such initiatives to improve health or to reduce health inequalities. In addition to the problems associated with evaluation, the processes through which ABIs might be used to influence change are not well understood and the value of using area-based services to improve health has been taken for granted. There is little understanding about the processes through which service provider partnerships might develop and limited knowledge about the processes through which residents might develop relations with providers. The key aim of this research was to examine the social processes through which ABIs develop over time. Using a case study approach, the research examined one Target Wellbeing programme as a social figuration of interdependent people. Ethnographic methods, including documentary analysis, non-participant observation and interviews, were used to explore the processes and networks that mediated the planned public health development. The study also drew on relevant quantitative data to describe changes over time. Ideas from figurational sociology were used as sensitising concepts in the development of a substantive theory about the processes through which ABIs develop. The study developed theoretical insight into processes of joint working that helps to explain why, in the context in which services are commissioned and performance managed, provider co-ordination is unlikely to be implemented as planned. It also provided a more sociologically adequate account of the ways in which relations between residents and providers were influenced by the history of relations in the town. Changes to residents’ relations with other residents and providers in the town influenced a greater sense of control over their circumstances. These findings demonstrate that, in relation to public health policy and practice, ABIs might more usefully be conceptualised as a series of interrelated processes that might be used to establish the preconditions for influencing change among residents. However, the study showed that interventions targeted at a small part of much wider networks of interconnected people are unlikely to influence sustained changes for residents in deprived areas.

No description available.

In the design of new, more sophisticated missile systems, simulations need to be realistic and fast. Realistic target models are just as important as realistic models of the missile, but have often been overlooked in the past. Existing methods for creating realistic target models require considerable computational resources. This thesis addresses the problem of using limited resources to create realistic target models for simulating engagements with radar guided homing missiles. A multiple genetic algorithm approach is presented for converting inverse synthetic aperture radar images of targets into scatterer models. The models produced are high fidelity and fast to process. Results are given that demonstrate the generation of a model from real data using a desktop computer. Realistic models are used to investigate the effects of target fidelity on the missile performance. The results of the investigation allow the model complexity to be traded against the fidelity of the representation to optimise simulation speed. Finally, a realistic target model is used in a feasibility study to investigate the potential use of glint for target manoeuvre detection. Target glint is considered as noise in conventional missile systems and filtered to reduce its effects on the tracking performance- The use of glint for target manoeuvre detection would provide a cheap and novel alternative to the optical techniques currently being developed. The feasibility study has shown that target manoeuvre detection using glint may be as fast as optical techniques and very reliable.

abstract: Technological advances have enabled the generation and collection of various data from complex systems, thus, creating ample opportunity to integrate knowledge in many decision making applications. This dissertation introduces holistic learning as the integration of a comprehensive set of relationships that are used towards the learning objective. The holistic view of the problem allows for richer learning from data and, thereby, improves decision making. The first topic of this dissertation is the prediction of several target attributes using a common set of predictor attributes. In a holistic learning approach, the relationships between target attributes are embedded into the learning algorithm created in this dissertation. Specifically, a novel tree based ensemble that leverages the relationships between target attributes towards constructing a diverse, yet strong, model is proposed. The method is justified through its connection to existing methods and experimental evaluations on synthetic and real data. The second topic pertains to monitoring complex systems that are modeled as networks. Such systems present a rich set of attributes and relationships for which holistic learning is important. In social networks, for example, in addition to friendship ties, various attributes concerning the users' gender, age, topic of messages, time of messages, etc. are collected. A restricted form of monitoring fails to take the relationships of multiple attributes into account, whereas the holistic view embeds such relationships in the monitoring methods. The focus is on the difficult task to detect a change that might only impact a small subset of the network and only occur in a sub-region of the high-dimensional space of the network attributes. One contribution is a monitoring algorithm based on a network statistical model. Another contribution is a transactional model that transforms the task into an expedient structure for machine learning, along with a generalizable algorithm to monitor the attributed network. A learning step in this algorithm adapts to changes that may only be local to sub-regions (with a broader potential for other learning tasks). Diagnostic tools to interpret the change are provided. This robust, generalizable, holistic monitoring method is elaborated on synthetic and real networks. / Dissertation/Thesis / Doctoral Dissertation Industrial Engineering 2014

A técnica de análises PIXE (Particle Induced X-ray Emission) de alvos finos é rotineiramente usado no Instituto de Física da Universidade de São Paulo (USP) pelo Lamfi (Laboratório de Materiais e Feixes Iônicos) em análises quantitativas elementares. A calibração do arranjo experimental do Lamfi é realizada através da irradiação de filmes finos padrões evaporados, sendo o rendimento de produção de raios X ajustado a partir deprimeiros princípios. Em análises PIXE de alvos espessos (TTPIXE), a composição daparticular amostra introduz efeitos de perda de energia das partículas incidentes e autoabsorção dos raios X produzidos. Estes efeitos são inexistentes na análise PIXE de alvosfinos. Paradoxalmente há a necessidade de se conhecer a composição da amostra, paracomputar estes efeitos, numa análise elementar quantitativa de alvos espessos. Este trabalhopropõe a diluição de amostras sólidas numa matriz conhecida onde as características de perda de energia das partículas incidentes e auto absorção da radiação produzida estejam caracterizadas (exemplo: ácido bórico, grafite) e supostamente não sofram alterações devido à introdução da amostra (diluição). Para o cálculo do rendimento de produção de raios X em análises TTPIXE é proposto um fator de correção para alvos espessos, dependente exclusivamente da matriz diluidora, aplicado ao rendimento de produção de raios X de alvos finos. Este procedimento viabiliza a utilização da curva de resposta para análises de alvos finos, já calibrada, do arranjo. Utilizando os modelos mais aceitos para o poder de freamento para prótons incidentes, seções de choque de produção de raios X e coeficientes de absorção de radiação pela matéria, o software (Clara) foi desenvolvido para o cálculo do rendimento de produção de raios X em alvos espessos, bem como os fatores de correção para dado raio X e determinada matriz. Alvos espessos foram confeccionados a partir de amostra padrão de referência (SRM-IAEA356 Marine sediment) para verificar os valores calculados pelo Clara e da metodologia de análise proposta. Os valores experimentais encontram-se em concordância com os valores certificados para um coeficiente de intervalo de confiança de 95% considerando o novo limite de detecção imposto pela diluição. Um roteiro para preparação de alvos espessos a partir de amostras sólidas, bem como a descrição do arranjo experimental, estão inclusos. / Thin film PIXE (Particle Induced X-ray Emission) analysis is been routinely used in the Institute of Physics of the University of Sao Paulo (USP) for quantitative analysis of materials. The X-ray production yield of the PIXE-SP setup is calibrated with monoelementary evaporated thin film standards, and fitted with a first principles yield function. However, in thick target PIXE (TTPIXE) analysis, the particular sample composition needs to be known in advance to calculate the stopping power and the X-ray absorption coefficients. In this work, a matrix standardization is proposed, in which a powdered solid sample is diluted in a known light element matrix (like graphite, boric acid, etc.) whose energy loss and selfabsorption are known and supposed almost unchanged. Furthermore, a scheme is proposed where elementary TTPIXE yields are calculated applying a pre-determined thick target correction factor to the thin target PIXE yields. This procedure enables the use of the already calibrated thin film X-ray yields also for thick target analysis. Using the most accepted stopping power model, ionization cross-sections and X-ray attenuation coefficients, a software (Clara) was developed to calculate the elementary TTPIXE X-ray yields and the corresponding thick target correction factors, for a given and pre-determined matrix. The program also allows testing the addition of any contaminant to the primary matrix and to compute the corresponding change in the thick target PIXE X-ray yields. This option was used to calculate the effect of increasing sample mass in the light element matrix, on the calculated yields, the effect of small changes in target composition, and the quantitative limitations of the proposed scheme. Thick test targets were prepared with a standard reference material (SRM-IAEA356 Marine sediment) and used to verify the accuracy of Clara and of the proposed scheme. The experimental values of the sample composition agreed with the certified values for 95% confidence interval coefficient to the new detection limit imposed by dilution. A protocol for target preparation of solid samples using this technique as well as the description of the experimental setup, are included.

Long interspersed nuclear elements-1 (Line-1 or L1) accounts for approximately 17% of the human genome. The majority of L1s are inactive, but ~100 remain retrotransposon competent (RC-L1) and retrotranspose through RNA intermediates to different locations of the genome. It is well established that L1 is involved in both disease initiation and progression via retrotransposition dependent and independent mechanisms. Retrotransposed L1 sequences disrupt loci (e.g. gene structure) in ways that lead to human disease, and activities of L1 si/piRNA, ORF1 and ORF2 proteins are implicated in the etiology and progression of human diseases such as in breast and colon cancer (Miki et al., 1992; Ohms et al., 2014). Despite these implications, very little is known about pharmacological molecules that inhibit and reverse L1’s harmful effects. The clinical utility of L1 as a player in tumorigenesis and as a biomarker for disease initiation and progression is not thoroughly understood. In this review, we analyzed the life cycle of L1, its roles in disease initiation and progression, clinical utilities and potential as a pharmacological target and a biomarker for the diagnosis and treatment of human diseases, such as cancer.