A Doença de Machado Joseph(DMJ) é uma doença genética autossômica dominante de início na vida adulta que afeta a coordenação motora e cursa com sintomas neurodegenerativos. É causada por uma expansão da repetição CAG no gene ATXN3. Há várias hipóteses a respeito da sua fisiopatogenia, e uma delas envolve a resposta inflamatória. O objetivo deste estudo foi descrever as concentrações séricas das citocinas em indivíduos sintomáticos, assintomáticos e compará-los com os controles saudáveis. Após a confirmação molecular dos pacientes e controles pareados por sexo e idade, os indivíduos foram convidados a participar do estudo. A idade de início e a duração da doença foram obtidas, e as escalas clínicas Scale for the Assessment and Rating of Ataxia (SARA), Neurological Examination Score for Spinocerebellar Ataxias (NESSCA), SCA Functional Index (SCAFI), and Composite Cerebellar Functional Score (CCFS), aplicadas. O soro dos indivíduos foi coletado e um painel de citocina foi realizado, incluindo a Eotaxina, GM-CSF, IFN-a, IFN-γ, IL-1b, IL-1Ra, IL-2, IL-2R, IL-4, IL- 5, IL-6, IL-7, IL-8, IL-10, IL-12, IL-13, IL-15, IL-17, IP-10, MCP-1, MIG, MIP1a, MIP1b, RANTES e O TNF-a. Entre os indivíduos sintomáticos, o painel foi repetido após 90 e 360 dias. O perfil das citocinas no baseline foi estudado por análise discriminante. Aquelas que apresentaram alterações relevantes entre os grupos tiveram seus níveis sérico reavaliados após 90 e 360 dias e estes dados foram avaliados pela equação de estimação generalizada (GEE). Sessenta e seis sintomáticos, 13 assintomáticos e 43 controles foram estudados. Quando comparados os sintomáticos e assintomáticos com seus respectivos controles saudáveis, não se observou diferenças nos padrões das citocinas. No entanto, apenas uma citocina teve destaque: os níveis séricos de Eotaxina foram significativamente mais elevados em assintomáticos (p = 0,001, ANCOVA) e entre os sintomáticos seus níveis foram menores após 360 dias do que naquelas obtidas no início do estudo (p = 0,039, GEE). A idade, a duração da doença, a expansão CAG, e as escalas NESSCA e SARA não se correlacionaram com os níveis das citocinas. O padrão relativamente benigno de citocinas em portadores sintomáticos sugere que a ativação do micróglia não seja primordial na DMJ. Entretanto, os níveis de eotaxina, um peptídeo secretado por astrócitos para repelir as células imunes circulantes, foram elevados no grupo assintomático, o que sugere que uma resposta específica destas células pode estar relacionada com a ausência de sintomas e/ou que a perda de astrócitos estaria relacionada à progressão da doença em DMJ. / Machado Joseph Disease (MJD) is an autosomal dominant genetic disease of adulthood which affects motor coordination and progresses with neurodegenerative symptoms. It is caused by an expansion of the CAG repeat at ATXN3 gene. There are several hypotheses about its pathogenesis, and one of them involves the inflammatory response. The aim of the present study is to describe the serum concentrations of a broad spectrum of cytokines in symptomatic and asymptomatic carriers of Machado Joseph disease (SCA3/MJD) CAG expansions. Molecularly confirmed carriers and controls were studied. Age at onset, disease duration, and clinical scales Scale for the Assessment and Rating of Ataxia (SARA), Neurological Examination Score for Spinocerebellar Ataxias (NESSCA), SCA Functional Index (SCAFI), and Composite Cerebellar Functional Score (CCFS) were obtained from the symptomatic carriers. Serum was obtained from all individuals and a cytokine panel consisted of eotaxin, granulocyte-macrophage colony-stimulating factor (GM-CSF), interferon (IFN)-α, IFN-γ, interleukin (IL)-1β, IL-1RA, IL-2, IL-2R, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL- 12, IL-13, IL-15, IL-17, interferon gamma-induced protein (IP)-10, monocyte chemoattractant protein (MCP)-1, monokine induced by gamma interferon (MIG), macrophage inflammatory protein (MIP)-a, MIP-b, regulated on activation, normal T cell expressed and secreted (RANTES) and tumor necrosis factor (TNF)-α was analyzed. In a subgroup of symptomatic carriers, the cytokine panel was repeated after 90 and 360 days. Cytokine distribution among groups was studied by discriminant analysis; changes in serum levels after 90 and 360 days were studied by generalized estimation equation. Sixty-six symptomatic carriers, 13 asymptomatic carriers, and 43 controls were studied. No differences in cytokine patterns were found between controls and carriers of the CAG expansions or between controls and symptomatic carriers only. In contrast, eotaxin concentrations were significantly higher in asymptomatic than in symptomatic carriers or in controls (p = 0.001, ANCOVA). Eotaxin did not correlate with age, disease duration, CAG expansion, NESSCA score, and SARA score. Among symptomatic carriers, eotaxin dropped after 360 days (p = 0.039, GEE). SCA3/ MJD patients presented a benign pattern of serum cytokines. In contrast, levels of eotaxin, a peptide secreted by astrocytes, were elevated in the asymptomatic carriers, suggesting that a specific response of these cells can be related to symptom progression, in SCA3/MJD.

Finite mixture modeling is a useful statistical technique for clustering individuals based on patterns of responses. The fundamental idea of the mixture modeling approach is to assume there are latent clusters of individuals in the population which each generate their own distinct distribution of observations (multivariate or univariate) which are then mixed up together in the full population. Hence, the name mixture comes from the fact that what we observe is a mixture of distributions. The goal of this model-based clustering technique is to identify what the mixture of distributions is so that, given a particular response pattern, individuals can be clustered accordingly. Commonly, finite mixture models, as well as the special case of latent class analysis, are used on data that inherently involve repeated measures. The purpose of this dissertation is to extend the finite mixture model to allow for the number of repeated measures to be incorporated and contribute to the clustering of individuals rather than measures. The dimension of the repeated measures or simply the count of responses is assumed to follow a truncated Poisson distribution and this information can be incorporated into what we call a dimension informative finite mixture model (DIMM). The outline of this dissertation is as follows. Paper 1 is entitled, "Dimension Informative Mixture Modeling (DIMM) for questionnaire data with an informative number of repeated measures." This paper describes the type of data structures considered and introduces the dimension informative mixture model (DIMM). A simulation study is performed to examine how well the DIMM fits the known specified truth. In the first scenario, we specify a mixture of three univariate normal distributions with different means and similar variances with different and similar counts of repeated measurements. We found that the DIMM predicts the true underlying class membership better than the traditional finite mixture model using a predicted value metric score. In the second scenario, we specify a mixture of two univariate normal distributions with the same means and variances with different and similar counts of repeated measurements. We found that that the count-informative finite mixture model predicts the truth much better than the non-informative finite mixture model. Paper 2 is entitled, "Patterns of Physical Activity in the Northern Manhattan Study (NOMAS) Using Multivariate Finite Mixture Modeling (MFMM)." This is a study that applies a multivariate finite mixture modeling approach to examining and elucidating underlying latent clusters of different physical activity profiles based on four dimensions: total frequency of activities, average duration per activity, total energy expenditure and the total count of the number of different activities conducted. We found a five cluster solution to describe the complex patterns of physical activity levels, as measured by fifteen different physical activity items, among a US based elderly cohort. Adding in a class of individuals who were not doing any physical activity, the labels of these six clusters are: no exercise, very inactive, somewhat inactive, slightly under guidelines, meet guidelines and above guidelines. This methodology improves upon previous work which utilized only the total metabolic equivalent (a proxy of energy expenditure) to classify individuals into inactive, active and highly active. Paper 3 is entitled, "Complex Drug Use Patterns and Associated HIV Transmission Risk Behaviors in an Internet Sample of US Men Who Have Sex With Men." This is a study that applies the count-informative information into a latent class analysis on nineteen binary drug items of drugs consumed within the past year before a sexual encounter. In addition to the individual drugs used, the mixture model incorporated a count of the total number of drugs used. We found a six class solution: low drug use, some recreational drug use, nitrite inhalants (poppers) with prescription erectile dysfunction (ED) drug use, poppers with prescription/non-prescription ED drug use and high polydrug use. Compared to participants in the low drug use class, participants in the highest drug use class were 5.5 times more likely to report unprotected anal intercourse (UAI) in their last sexual encounter and approximately 4 times more likely to report a new sexually transmitted infection (STI) in the past year. Younger men were also less likely to report UAI than older men but more likely to report an STI.

The concern of this thesis is to discuss classification of different objects based on longitudinal observations. In the first instance the reader is introduced to a linear mixed-effects model which is useful for longitudinal data modeling. Description of discriminant analysis methods follows. These methods ares usually used for classification based on longitudinal observations. Individual methods are introduced in the theoretic aspect. Random effects approach is generalized to continuous time. Subsequently the methods and features of the linear mixed-effects model are applied to real data. Finally features of the methods are studied with help of simulations.

The resource-based view of the firm (RBV) is one the most important areas of research content to emerge in the field of strategic management in the last 15 years. The RBV is prescriptive. That is, the RBV prescribes that competitive advantage stems from those resources that are valuable, rare, inimitable, and nonsubstitutable (VRIN). With rare exception, resources that meet the VRIN criteria are widely purported to be intangible in nature. From a research perspective, the RBV stream tends to be dominated by conceptual discussions and advancements. However, empirical tests of the core premises, or the main prescription, of the theory are argued to be very limited in quantity. To add to the body of empirical research that seeks to verify the main prescription of the RBV, this research undertakes a new and different level of analysis, one that has not been previously tested. Given that firms compete with both tangible and intangible resources, the present study is interested in determining if, as the RBV implicitly prescribes, resources that are intangible in nature are more important determinants of firm success than tangible resources. Although the research question is basic and fundamental, it has rarely been appropriately or adequately tested within the RBV stream, as is demonstrated by this thesis. To carry out the research, this study offers a conceptual model of the firm’s resource pool that includes tangible assets (financial and physical assets), intangible assets (intellectual property assets, organizational assets, reputational assets), and capabilities. A series of hypotheses are posited to explore the proposition that intangible resources contribute more greatly to firm success, on the dimensions of sales turnover, market share, and profitability, than tangible resources. / A field survey, administered to 2000 manufacturing and services businesses operating in Australia, is used to gather the data. Of the 2000 surveys sent, the hypotheses are empirically tested using multiple hierarchical regression analysis on a final sample of 291 firms. Control variables include firm age and Porter’s five forces of industry structure. Based on the results, verification of the RBV’s main prescription can not be supported unequivocally. Intellectual property assets, for example, do not have a statistically significant association with firm success, after accounting for the effects of tangible resources and the control variables. Organizational assets, however, not only explain additionally significant variation in firm success, after accounting for the effects of tangible resources and the control variables, but make among the greatest, unique contribution to firm success based on the size of the beta coefficients. Reputational assets offer additional explanatory power to predicting firm success after accounting for the effects of tangible assets and the control variables, but only with respect to one measure of firm success does its beta coefficient make a larger, unique contribution than financial assets. Lastly, contrary to theory, capabilities are not the single most important determinant of firm success, after accounting for the effects of intangible assets, and tangible and intangible assets, in two separate hierarchical regression equations. This finding is surprising and explanations are provided. Overall, the study raises some questions with respect to just which resources are the most important determinants of a firm’s market and financial success and offers a fruitful avenue for further research.

高級人力的培育和充分利用, 是政府施政的基本目標,當我們論及高級人 力的運用時,具有大專(含)以上學歷的工作者對目前職業的滿意程度是不 能忽略的一項因素。「職業滿意度」是指就業者在工作情境中所得到的心 理反應狀態而言。滿意程度的高低, 會影響到工作的效率,以至於整個工 作單位的績效。因此, 工作者滿意程度與否,亦為探討人力運用問題時重 要的一環。本文以實際問卷調查資料,就影響職業滿意度的因素對就業者 的職業滿意度作判別分析。傳統上的判別分析方法,都是用來處理連續性 資料, 而本文所要分析的資料都是離散資料 , 即屬質化(qualitative)的 變數。文中介紹一種離散資料的判別分析方法, 及應用在實際資料的分析 結果;另外,本文進而嘗試以一般用於處理連續性資料的常態假設及無母數 統計法來分析離散資料, 所得的判別結果與離散資料 判別法相比較。最 後本文以叢聚分析法, 來討論職業別對職業滿意度的叢聚狀況。

<p>Corporate failures pose a problem for banks, investors, customers, employees andinsurers. With a multivariate discrimination method, the study aims to find the specificfinancial ratios that most accurate reveals a company's financial health, which is ofinterest to all of the above parties. The data consist of 1042 Swedish small enterprisesand 30 different financial ratios between the years 2005‐2007. The result shows thatbankrupt firms three years before bankruptcy have a disadvantaged capital structurewith poor solvency and high debt. The year before bankruptcy, profitability and liquiditydeclined for bankruptcy group, and rates vary considerably in comparison with thesurviving companies. Our model can correctly classify 91,2 % of the total sample one yearbefore bankruptcy.</p> / <p>Företagskonkurser är dyrt för samhället och utgör ett problem för bland annat banker,investerare, kunder, anställda, försäkringsbolag och leverantörer. Studien syftar till attfinna de specifika nyckeltal vilka avslöjar ett företags finansiella hälsa, vilket är av intresseför alla ovanstående parter. Med en kvantitativ multivariat analysmetod har 30 olikanyckeltal från sammanlagt 1042 svenska mindre aktiebolag mellan åren 2005 och 2007studerats.Resultatet visar att konkursföretagen tre år innan konkurs har en missgynnandekapitalstruktur med svag soliditet och hög skuldsättning. Året innan konkurs harlönsamheten och likviditeten minskat för konkursgruppen och talen uppvisar storaskillnader i jämförelse med de överlevande företagen. Modellen klassificerar 91,2 % avföretagen korrekt ett år innan konkurs.</p>

Effective management of forest resources requires reliable and timely information on their status. In this regard, remote sensing techniques have played an important role, as they allow collection of data on extensive, remote and inaccessible areas. Historically, aerial photographs were the primary remote sensing data source in forest inventory and mapping, and they are still extensively for visual photo-interpretation. In this thesis, we show that their use can be improved thanks to automatic processing and an application using digitised orthophotos is provided. Satellite-based remote sensing has been regarded as an alternative, low-cost and rapid, data source to aerial photography and ground survey. Indeed, it has proved to be effective at the continental and global scales, but applications for local forest management purposes are still rare. The main reason for this is that the spatial resolution of satellite remote sensing data that was available until recently (mainly from Landsat TM/ETM and SPOT HRV) was too coarse for stand level information. Satellite images with enhanced spatial resolution (such as IKONOS) should overcome this limitation. This thesis investigates their actual capabilities for forest stand mapping and characterisation. We show that they are well suited for forest stand type classification and for retrieval of several dendrometric variables in coniferous stands with an accuracy similar to that of field sampling. For the sake of solutions to provide more precise and detailed information on forest stand, we assessed also the contribution of hyperspectral and multiple-view angle data acquired by CHRIS/PROBA. Although the winter season scene did not fully permit utilisation of the hyperspectral dimension of this dataset, the study provides insights into directional effects. This work makes, hopefully, a step towards automated processing and effective integration of satellite-based remote sensing data into the forest management information system and, by upscaling, into the national forest inventories.

Corporate failures pose a problem for banks, investors, customers, employees andinsurers. With a multivariate discrimination method, the study aims to find the specificfinancial ratios that most accurate reveals a company's financial health, which is ofinterest to all of the above parties. The data consist of 1042 Swedish small enterprisesand 30 different financial ratios between the years 2005‐2007. The result shows thatbankrupt firms three years before bankruptcy have a disadvantaged capital structurewith poor solvency and high debt. The year before bankruptcy, profitability and liquiditydeclined for bankruptcy group, and rates vary considerably in comparison with thesurviving companies. Our model can correctly classify 91,2 % of the total sample one yearbefore bankruptcy. / Företagskonkurser är dyrt för samhället och utgör ett problem för bland annat banker,investerare, kunder, anställda, försäkringsbolag och leverantörer. Studien syftar till attfinna de specifika nyckeltal vilka avslöjar ett företags finansiella hälsa, vilket är av intresseför alla ovanstående parter. Med en kvantitativ multivariat analysmetod har 30 olikanyckeltal från sammanlagt 1042 svenska mindre aktiebolag mellan åren 2005 och 2007studerats.Resultatet visar att konkursföretagen tre år innan konkurs har en missgynnandekapitalstruktur med svag soliditet och hög skuldsättning. Året innan konkurs harlönsamheten och likviditeten minskat för konkursgruppen och talen uppvisar storaskillnader i jämförelse med de överlevande företagen. Modellen klassificerar 91,2 % avföretagen korrekt ett år innan konkurs.

Face recognition is a popular research area where there are different approaches studied in the literature. In this thesis, a holistic Principal Component Analysis (PCA) based method, namely Eigenface method is studied in detail and three of the methods based on the Eigenface method are compared. These are the Bayesian PCA where Bayesian classifier is applied after dimension reduction with PCA, the Subspace Linear Discriminant Analysis (LDA) where LDA is applied after PCA and Eigenface where Nearest Mean Classifier applied after PCA. All the three methods are implemented on the Olivetti Research Laboratory (ORL) face database, the Face Recognition Technology (FERET) database and the CNN-TURK Speakers face database. The results are compared with respect to the effects of changes in illumination, pose and aging. Simulation results show that Subspace LDA and Bayesian PCA perform slightly well with respect to PCA under changes in pose / however, even Subspace LDA and Bayesian PCA do not perform well under changes in illumination and aging although they perform better than PCA.

From different points of view, including Resource-Based Theory, Resource-Advantage Theory, and Structure Conduct Performance, the research was firstly discussed if the iron and steel enterprises would have different competitive advantages with different strategy segmentations. In addition, how investors make investment decision and how management level distribute resource into which financial indicator in order to strengthen competitive advantage were discussed as well. The research was collected financial data (from year 2004 to 2008) of 40 domestic iron and steel companies which are listed in public stock market (including OTC) as sample pool. The sample pool was segmented into four groups, such as products, value chain of upstream to downstream, and top-to-down consolidated strategic groups. Competitive advantage was classified by average of equity return ratios of shareholders, and financial ratios were applied to analyze the source of competitive advantage in iron and steel industry. Firstly, started to analyze financial ratios of each group by description statistic method and implemented factor analysis to figure out common factors. Furthermore, from investors point of view, to clarify how those factors to be reflected on operating performance by applying multiple regression analysis. Moreover, from business operating level¡¦s eyes, to distinguish enterprises with competitive advantage from each strategic group. The result was shown that each strategic group has different sources of competitive advantage. Therefore, recommendations of the research are listed: I. Investors should invest in enterprises with better current ratio, quick ratio, and guarantee of multiplied interest. II. Aggressive investors should invest in enterprises that have stainless steel products and consolidated business from upstream, mid-stream, to downstream. III. Conservative investors should invest in enterprises that have plate steel products and consolidated business from upstream, mid-stream, to downstream. IV. In order to create resources of competitive advantage, management level of each strategic group should increase financial signals as first priority: 1. Plate steel and downstream enterprises: value-added of unit salary and percentage of employee bonus out of profit. 2. Bar iron, stainless enterprises with consolidation of upstream to mid-stream and top-to ¡Vdown conformity: current ratio, quick ratio and guarantee of multiplied interest. 3. Alloy steel enterprises: ratio of debt out of net assets, percentage of loan, stock and account receivable out of net assets ratio, and net assets out of assets ratio.