Gaussian deconvolution: a useful method for a form-free modeling of scattering data from mono- and multilayered planar systems

A new method for analysis of scattering data from lamellar bilayer systems is presented. The method employs a form-free description of the cross-section structure of the bilayer and the fit is performed directly to the scattering data, introducing also a structure factor when required. The cross-section structure (electron density profile in the case of X-ray scattering) is described by a set of Gaussian functions and the technique is termed Gaussian deconvolution. The coefficients of the Gaussians are optimized using a constrained least-squares routine that induces smoothness of the electron density profile. The optimization is coupled with the point-of-inflection method for determining the optimal weight of the smoothness. With the new approach, it is possible to optimize simultaneously the form factor, structure factor and several other parameters in the model. The applicability of this method is demonstrated by using it in a study of a multilamellar system composed of lecithin bilayers, where the form factor and structure factor are obtained simultaneously, and the obtained results provided new insight into this very well known system.

A Bayesian destructive weighted Poisson cure rate model and an application to a cutaneous melanoma data

In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis - latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.

Simcluster: clustering enumeration gene expression data on the simplex space

Abstract Background Transcript enumeration methods such as SAGE, MPSS, and sequencing-by-synthesis EST "digital northern", are important high-throughput techniques for digital gene expression measurement. As other counting or voting processes, these measurements constitute compositional data exhibiting properties particular to the simplex space where the summation of the components is constrained. These properties are not present on regular Euclidean spaces, on which hybridization-based microarray data is often modeled. Therefore, pattern recognition methods commonly used for microarray data analysis may be non-informative for the data generated by transcript enumeration techniques since they ignore certain fundamental properties of this space. Results Here we present a software tool, Simcluster, designed to perform clustering analysis for data on the simplex space. We present Simcluster as a stand-alone command-line C package and as a user-friendly on-line tool. Both versions are available at: http://xerad.systemsbiology.net/simcluster. Conclusion Simcluster is designed in accordance with a well-established mathematical framework for compositional data analysis, which provides principled procedures for dealing with the simplex space, and is thus applicable in a number of contexts, including enumeration-based gene expression data.

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Trends in aortic aneurysm- and dissection-related mortality in the state of São Paulo, Brazil, 1985–2009: multiple-cause-of-death analysis

Background: Aortic aneurysm and dissection are important causes of death in older people. Ruptured aneurysms show catastrophic fatality rates reaching near 80%. Few population-based mortality studies have been published in the world and none in Brazil. The objective of the present study was to use multiple-cause-of-death methodology in the analysis of mortality trends related to aortic aneurysm and dissection in the state of Sao Paulo, between 1985 and 2009. Methods: We analyzed mortality data from the Sao Paulo State Data Analysis System, selecting all death certificates on which aortic aneurysm and dissection were listed as a cause-of-death. The variables sex, age, season of the year, and underlying, associated or total mentions of causes of death were studied using standardized mortality rates, proportions and historical trends. Statistical analyses were performed by chi-square goodness-of-fit and H Kruskal-Wallis tests, and variance analysis. The joinpoint regression model was used to evaluate changes in age-standardized rates trends. A p value less than 0.05 was regarded as significant. Results: Over a 25-year period, there were 42,615 deaths related to aortic aneurysm and dissection, of which 36,088 (84.7%) were identified as underlying cause and 6,527 (15.3%) as an associated cause-of-death. Dissection and ruptured aneurysms were considered as an underlying cause of death in 93% of the deaths. For the entire period, a significant increased trend of age-standardized death rates was observed in men and women, while certain non-significant decreases occurred from 1996/2004 until 2009. Abdominal aortic aneurysms and aortic dissections prevailed among men and aortic dissections and aortic aneurysms of unspecified site among women. In 1985 and 2009 death rates ratios of men to women were respectively 2.86 and 2.19, corresponding to a difference decrease between rates of 23.4%. For aortic dissection, ruptured and non-ruptured aneurysms, the overall mean ages at death were, respectively, 63.2, 68.4 and 71.6 years; while, as the underlying cause, the main associated causes of death were as follows: hemorrhages (in 43.8%/40.5%/13.9%); hypertensive diseases (in 49.2%/22.43%/24.5%) and atherosclerosis (in 14.8%/25.5%/15.3%); and, as associated causes, their principal overall underlying causes of death were diseases of the circulatory (55.7%), and respiratory (13.8%) systems and neoplasms (7.8%). A significant seasonal variation, with highest frequency in winter, occurred in deaths identified as underlying cause for aortic dissection, ruptured and non-ruptured aneurysms. Conclusions: This study introduces the methodology of multiple-causes-of-death to enhance epidemiologic knowledge of aortic aneurysm and dissection in São Paulo, Brazil. The results presented confer light to the importance of mortality statistics and the need for epidemiologic studies to understand unique trends in our own population.

Functional clustering of time series gene expression data by Granger causality

Background: A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results: In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions: This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them.

Análise de concorrência no mercado mundial de café verde

A literatura argumenta que o Brasil, embora ainda seja o maior exportador mundial de café verde, tem perdido poder neste mercado, pois a concorrência (rivalidade e probabilidade de entrada) imposta por países como a Colômbia e o Vietnã é forte o suficiente para tornar este mercado bastante competitivo. Assim, este artigo avalia o padrão recente de concorrência do mercado mundial de café verde utilizando uma metodologia econométrica mais usualmente empregada em análise antitruste. Para avaliar o comportamento dos consumidores, foram estimadas as elasticidades-preço da demanda mundial de café verde, por tipo de café, usando o modelo de demanda Logit Multinomial Antitruste. Para avaliar o comportamento de equilíbrio de mercado foram realizados testes de instabilidade de share de quantidade por meio de análise de cointegração em painel. Os resultados apontam para aumento da concorrência à variedade de café brasileiro por parte da demanda e manutenção de sharede quantidades como configuração de equilíbrio de mercado.

Discretionary-based disclosure: evidence from the Brazilian market

The primary objective of this paper is to identify the factors that explain Brazilian companies level of voluntary disclosure. Underpinning this work is the Discretionary-based Disclosure theory. The sample is composed of the top 100 largest non-financial companies listed in the Bolsa de Valores de São Paulo (Brazilian Securities, Commodities, and Futures exchange - BOVESPA). Information was gathered from Financial Statements for the years ending in 2006, 2007, and 2008, with the use of content analysis. A disclosure framework based on 27 studies from these years was created, with a total of 92 voluntary items divided into two dimensions: economic (43) and socio-environmental (49). Based on the existing literature, a total of 12 hypotheses were elaborated and tested using a panel data approach. Results evidence that: (a) Sector and Origin of Control are statistically significant in all three models tested: economic, socio-environmental, and total; (b) Profitability is relevant in the economic model and in the total model; (c) Tobin s Q is relevant in the socio-environmental model and in the total disclosure model; (d) Leverage and Auditing Firm are only relevant in the economic disclosure model; (e) Size, Governance, Stock Issuing, Growth Opportunities and Concentration of Control are not statistically significant in any of the three models.

Multivariate spectroscopic methods for the analysis of solutions

In this thesis some multivariate spectroscopic methods for the analysis of solutions are proposed. Spectroscopy and multivariate data analysis form a powerful combination for obtaining both quantitative and qualitative information and it is shown how spectroscopic techniques in combination with chemometric data evaluation can be used to obtain rapid, simple and efficient analytical methods. These spectroscopic methods consisting of spectroscopic analysis, a high level of automation and chemometric data evaluation can lead to analytical methods with a high analytical capacity, and for these methods, the term high-capacity analysis (HCA) is suggested. It is further shown how chemometric evaluation of the multivariate data in chromatographic analyses decreases the need for baseline separation. The thesis is based on six papers and the chemometric tools used are experimental design, principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), partial least squares regression (PLS) and parallel factor analysis (PARAFAC). The analytical techniques utilised are scanning ultraviolet-visible (UV-Vis) spectroscopy, diode array detection (DAD) used in non-column chromatographic diode array UV spectroscopy, high-performance liquid chromatography with diode array detection (HPLC-DAD) and fluorescence spectroscopy. The methods proposed are exemplified in the analysis of pharmaceutical solutions and serum proteins. In Paper I a method is proposed for the determination of the content and identity of the active compound in pharmaceutical solutions by means of UV-Vis spectroscopy, orthogonal signal correction and multivariate calibration with PLS and SIMCA classification. Paper II proposes a new method for the rapid determination of pharmaceutical solutions by the use of non-column chromatographic diode array UV spectroscopy, i.e. a conventional HPLC-DAD system without any chromatographic column connected. In Paper III an investigation is made of the ability of a control sample, of known content and identity to diagnose and correct errors in multivariate predictions something that together with use of multivariate residuals can make it possible to use the same calibration model over time. In Paper IV a method is proposed for simultaneous determination of serum proteins with fluorescence spectroscopy and multivariate calibration. Paper V proposes a method for the determination of chromatographic peak purity by means of PCA of HPLC-DAD data. In Paper VI PARAFAC is applied for the decomposition of DAD data of some partially separated peaks into the pure chromatographic, spectral and concentration profiles.

The firm. Techno-organizational changes, industrial relations and performances. An enquiry on Reggio Emilia local industrial system

It is not unknown that the evolution of firm theories has been developed along a path paved by an increasing awareness of the organizational structure importance. From the early “neoclassical” conceptualizations that intended the firm as a rational actor whose aim is to produce that amount of output, given the inputs at its disposal and in accordance to technological or environmental constraints, which maximizes the revenue (see Boulding, 1942 for a past mid century state of the art discussion) to the knowledge based theory of the firm (Nonaka & Takeuchi, 1995; Nonaka & Toyama, 2005), which recognizes in the firm a knnowledge creating entity, with specific organizational capabilities (Teece, 1996; Teece & Pisano, 1998) that allow to sustaine competitive advantages. Tracing back a map of the theory of the firm evolution, taking into account the several perspectives adopted in the history of thought, would take the length of many books. Because of that a more fruitful strategy is circumscribing the focus of the description of the literature evolution to one flow connected to a crucial question about the nature of firm’s behaviour and about the determinants of competitive advantages. In so doing I adopt a perspective that allows me to consider the organizational structure of the firm as an element according to which the different theories can be discriminated. The approach adopted starts by considering the drawbacks of the standard neoclassical theory of the firm. Discussing the most influential theoretical approaches I end up with a close examination of the knowledge based perspective of the firm. Within this perspective the firm is considered as a knowledge creating entity that produce and mange knowledge (Nonaka, Toyama, & Nagata, 2000; Nonaka & Toyama, 2005). In a knowledge intensive organization, knowledge is clearly embedded for the most part in the human capital of the individuals that compose such an organization. In a knowledge based organization, the management, in order to cope with knowledge intensive productions, ought to develop and accumulate capabilities that shape the organizational forms in a way that relies on “cross-functional processes, extensive delayering and empowerment” (Foss 2005, p.12). This mechanism contributes to determine the absorptive capacity of the firm towards specific technologies and, in so doing, it also shape the technological trajectories along which the firm moves. After having recognized the growing importance of the firm’s organizational structure in the theoretical literature concerning the firm theory, the subsequent point of the analysis is that of providing an overview of the changes that have been occurred at micro level to the firm’s organization of production. The economic actors have to deal with challenges posed by processes of internationalisation and globalization, increased and increasing competitive pressure of less developed countries on low value added production activities, changes in technologies and increased environmental turbulence and volatility. As a consequence, it has been widely recognized that the main organizational models of production that fitted well in the 20th century are now partially inadequate and processes aiming to reorganize production activities have been widespread across several economies in recent years. Recently, the emergence of a “new” form of production organization has been proposed both by scholars, practitioners and institutions: the most prominent characteristic of such a model is its recognition of the importance of employees commitment and involvement. As a consequence it is characterized by a strong accent on the human resource management and on those practices that aim to widen the autonomy and responsibility of the workers as well as increasing their commitment to the organization (Osterman, 1994; 2000; Lynch, 2007). This “model” of production organization is by many defined as High Performance Work System (HPWS). Despite the increasing diffusion of workplace practices that may be inscribed within the concept of HPWS in western countries’ companies, it is an hazard, to some extent, to speak about the emergence of a “new organizational paradigm”. The discussion about organizational changes and the diffusion of HPWP the focus cannot abstract from a discussion about the industrial relations systems, with a particular accent on the employment relationships, because of their relevance, in the same way as production organization, in determining two major outcomes of the firm: innovation and economic performances. The argument is treated starting from the issue of the Social Dialogue at macro level, both in an European perspective and Italian perspective. The model of interaction between the social parties has repercussions, at micro level, on the employment relationships, that is to say on the relations between union delegates and management or workers and management. Finding economic and social policies capable of sustaining growth and employment within a knowledge based scenario is likely to constitute the major challenge for the next generation of social pacts, which are the main social dialogue outcomes. As Acocella and Leoni (2007) put forward the social pacts may constitute an instrument to trade wage moderation for high intensity in ICT, organizational and human capital investments. Empirical evidence, especially focused on the micro level, about the positive relation between economic growth and new organizational designs coupled with ICT adoption and non adversarial industrial relations is growing. Partnership among social parties may become an instrument to enhance firm competitiveness. The outcome of the discussion is the integration of organizational changes and industrial relations elements within a unified framework: the HPWS. Such a choice may help in disentangling the potential existence of complementarities between these two aspects of the firm internal structure on economic and innovative performance. With the third chapter starts the more original part of the thesis. The data utilized in order to disentangle the relations between HPWS practices, innovation and economic performance refer to the manufacturing firms of the Reggio Emilia province with more than 50 employees. The data have been collected through face to face interviews both to management (199 respondents) and to union representatives (181 respondents). Coupled with the cross section datasets a further data source is constituted by longitudinal balance sheets (1994-2004). Collecting reliable data that in turn provide reliable results needs always a great effort to which are connected uncertain results. Data at micro level are often subjected to a trade off: the wider is the geographical context to which the population surveyed belong the lesser is the amount of information usually collected (low level of resolution); the narrower is the focus on specific geographical context, the higher is the amount of information usually collected (high level of resolution). For the Italian case the evidence about the diffusion of HPWP and their effects on firm performances is still scanty and usually limited to local level studies (Cristini, et al., 2003). The thesis is also devoted to the deepening of an argument of particular interest: the existence of complementarities between the HPWS practices. It has been widely shown by empirical evidence that when HPWP are adopted in bundles they are more likely to impact on firm’s performances than when adopted in isolation (Ichniowski, Prennushi, Shaw, 1997). Is it true also for the local production system of Reggio Emilia? The empirical analysis has the precise aim of providing evidence on the relations between the HPWS dimensions and the innovative and economic performances of the firm. As far as the first line of analysis is concerned it must to be stressed the fundamental role that innovation plays in the economy (Geroski & Machin, 1993; Stoneman & Kwoon 1994, 1996; OECD, 2005; EC, 2002). On this point the evidence goes from the traditional innovations, usually approximated by R&D investment expenditure or number of patents, to the introduction and adoption of ICT, in the recent years (Brynjolfsson & Hitt, 2000). If innovation is important then it is critical to analyse its determinants. In this work it is hypothesised that organizational changes and firm level industrial relations/employment relations aspects that can be put under the heading of HPWS, influence the propensity to innovate in product, process and quality of the firm. The general argument may goes as follow: changes in production management and work organization reconfigure the absorptive capacity of the firm towards specific technologies and, in so doing, they shape the technological trajectories along which the firm moves; cooperative industrial relations may lead to smother adoption of innovations, because not contrasted by unions. From the first empirical chapter emerges that the different types of innovations seem to respond in different ways to the HPWS variables. The underlying processes of product, process and quality innovations are likely to answer to different firm’s strategies and needs. Nevertheless, it is possible to extract some general results in terms of the most influencing HPWS factors on innovative performance. The main three aspects are training coverage, employees involvement and the diffusion of bonuses. These variables show persistent and significant relations with all the three innovation types. The same do the components having such variables at their inside. In sum the aspects of the HPWS influence the propensity to innovate of the firm. At the same time, emerges a quite neat (although not always strong) evidence of complementarities presence between HPWS practices. In terns of the complementarity issue it can be said that some specific complementarities exist. Training activities, when adopted and managed in bundles, are related to the propensity to innovate. Having a sound skill base may be an element that enhances the firm’s capacity to innovate. It may enhance both the capacity to absorbe exogenous innovation and the capacity to endogenously develop innovations. The presence and diffusion of bonuses and the employees involvement also spur innovative propensity. The former because of their incentive nature and the latter because direct workers participation may increase workers commitment to the organizationa and thus their willingness to support and suggest inovations. The other line of analysis provides results on the relation between HPWS and economic performances of the firm. There have been a bulk of international empirical studies on the relation between organizational changes and economic performance (Black & Lynch 2001; Zwick 2004; Janod & Saint-Martin 2004; Huselid 1995; Huselid & Becker 1996; Cappelli & Neumark 2001), while the works aiming to capture the relations between economic performance and unions or industrial relations aspects are quite scant (Addison & Belfield, 2001; Pencavel, 2003; Machin & Stewart, 1990; Addison, 2005). In the empirical analysis the integration of the two main areas of the HPWS represent a scarcely exploited approach in the panorama of both national and international empirical studies. As remarked by Addison “although most analysis of workers representation and employee involvement/high performance work practices have been conducted in isolation – while sometimes including the other as controls – research is beginning to consider their interactions” (Addison, 2005, p.407). The analysis conducted exploiting temporal lags between dependent and covariates, possibility given by the merger of cross section and panel data, provides evidence in favour of the existence of HPWS practices impact on firm’s economic performance, differently measured. Although it does not seem to emerge robust evidence on the existence of complementarities among HPWS aspects on performances there is evidence of a general positive influence of the single practices. The results are quite sensible to the time lags, inducing to hypothesize that time varying heterogeneity is an important factor in determining the impact of organizational changes on economic performance. The implications of the analysis can be of help both to management and local level policy makers. Although the results are not simply extendible to other local production systems it may be argued that for contexts similar to the Reggio Emilia province, characterized by the presence of small and medium enterprises organized in districts and by a deep rooted unionism, with strong supporting institutions, the results and the implications here obtained can also fit well. However, a hope for future researches on the subject treated in the present work is that of collecting good quality information over wider geographical areas, possibly at national level, and repeated in time. Only in this way it is possible to solve the Gordian knot about the linkages between innovation, performance, high performance work practices and industrial relations.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

Perceptual maps analysis for organic food consumers in China: a study on Shanghai consumers

Although in Europe and in the USA many studies focus on organic, little is known on the topic in China. This research provides an insight on Shanghai consumers’ perception of organic, aiming at understanding and representing in graphic form the network of mental associations that stems from the organic concept. To acquire, process and aggregate the individual networks it was used the “Brand concept mapping” methodology (Roedder et al., 2006), while the data analysis was carried out also using analytic procedures. The results achieved suggest that organic food is perceived as healthy, safe and costly. Although these attributes are pretty much consistent with the European perception, some relevant differences emerged. First, organic is not necessarily synonymous with natural product in China, also due to a poor translation of the term in the Chinese language that conveys the idea of a manufactured product. Secondly, the organic label has to deal with the competition with the green food label in terms of image and positioning on the market, since they are easily associated and often confused. “Environmental protection” also emerged as relevant association, while the ethical and social values were not mentioned. In conclusion, health care and security concerns are the factors that influence most the food consumption in China (many people are so concerned about food safety that they found it difficult to shop), and the associations “Safe”, “Pure and natural”, “without chemicals” and “healthy” have been identified as the best candidates for leveraging a sound image of organic food .

Pyrolysis-Gas Chromatography-Mass Spectometry and Chemometric Analysis for the Characterization of Complex Matrices

The present PhD thesis was focused on the development and application of chemical methodology (Py-GC-MS) and data-processing method by multivariate data analysis (chemometrics). The chromatographic and mass spectrometric data obtained with this technique are particularly suitable to be interpreted by chemometric methods such as PCA (Principal Component Analysis) as regards data exploration and SIMCA (Soft Independent Models of Class Analogy) for the classification. As a first approach, some issues related to the field of cultural heritage were discussed with a particular attention to the differentiation of binders used in pictorial field. A marker of egg tempera the phosphoric acid esterified, a pyrolysis product of lecithin, was determined using HMDS (hexamethyldisilazane) rather than the TMAH (tetramethylammonium hydroxide) as a derivatizing reagent. The validity of analytical pyrolysis as tool to characterize and classify different types of bacteria was verified. The FAMEs chromatographic profiles represent an important tool for the bacterial identification. Because of the complexity of the chromatograms, it was possible to characterize the bacteria only according to their genus, while the differentiation at the species level has been achieved by means of chemometric analysis. To perform this study, normalized areas peaks relevant to fatty acids were taken into account. Chemometric methods were applied to experimental datasets. The obtained results demonstrate the effectiveness of analytical pyrolysis and chemometric analysis for the rapid characterization of bacterial species. Application to a samples of bacterial (Pseudomonas Mendocina), fungal (Pleorotus ostreatus) and mixed- biofilms was also performed. A comparison with the chromatographic profiles established the possibility to: • Differentiate the bacterial and fungal biofilms according to the (FAMEs) profile. • Characterize the fungal biofilm by means the typical pattern of pyrolytic fragments derived from saccharides present in the cell wall. • Individuate the markers of bacterial and fungal biofilm in the same mixed-biofilm sample.

Patterns of regional differentiation in post-Soviet Russia

This doctoral thesis aims at contributing to the literature on transition economies focusing on the Russian Federations and in particular on regional income convergence and fertility patterns. The first two chapter deal with the issue of income convergence across regions. Chapter 1 provides an historical-institutional analysis of the period between the late years of the Soviet Union and the last decade of economic growth and a presentation of the sample with a description of gross regional product composition, agrarian or industrial vocation, labor. Chapter 2 contributes to the literature on exploratory spatial data analysis with a application to a panel of 77 regions in the period 1994-2008. It provides an analysis of spatial patterns and it extends the theoretical framework of growth regressions controlling for spatial correlation and heterogeneity. Chapter 3 analyses the national demographic patterns since 1960 and provides a review of the policies on maternity leave and family benefits. Data sources are the Statistical Yearbooks of USSR, the Statistical Yearbooks of the Russian Soviet Federative Socialist Republic and the Demographic Yearbooks of Russia. Chapter 4 analyses the demographic patterns in light of the theoretical framework of the Becker model, the Second Demographic Transition and an economic-crisis argument. With national data from 1960, the theoretically issue of the pro or countercyclical relation between income and fertility is graphically analyzed and discussed, together with female employment and education. With regional data after 1994 different panel data models are tested. Individual level data from the Russian Longitudinal Monitoring Survey are employed using the logit model. Chapter 5 employs data from the Generations and Gender Survey by UNECE to focus on postponement and second births intentions. Postponement is studied through cohort analysis of mean maternal age at first birth, while the methodology used for second birth intentions is the ordered logit model.

Institutional Processes and Discursive Strategies: Rhetoric and Vocabulary Analysis of CSR and Sustainability

The candidate tackled an important issue in contemporary management: the role of CSR and Sustainability. The research proposal focused on a longitudinal and inductive research, directed to specify the evolution of CSR and contribute to the new institutional theory, in particular institutional work framework, and to the relation between institutions and discourse analysis. The documental analysis covers all the evolution of CSR, focusing also on a number of important networks and associations. Some of the methodologies employed in the thesis have been employed as a consequence of data analysis, in a truly inductive research process. The thesis is composed by two section. The first section mainly describes the research process and the analyses results. The candidates employed several research methods: a longitudinal content analysis of documents, a vocabulary research with statistical metrics as cluster analysis and factor analysis, a rhetorical analysis of justifications. The second section puts in relation the analysis results with theoretical frameworks and contributions. The candidate confronted with several frameworks: Actor-Network-Theory, Institutional work and Boundary Work, Institutional Logic. Chapters are focused on different issues: a historical reconstruction of CSR; a reflection about symbolic adoption of recurrent labels; two case studies of Italian networks, in order to confront institutional and boundary works; a theoretical model of institutional change based on contradiction and institutional complexity; the application of the model to CSR and Sustainability, proposing Sustainability as a possible institutional logic.