Anthropotechnological analysis of industrial accidents in Brazil

The Brazilian Ministry of Labour has been attempting to modify the norms used to analyse industrial accidents in the country. For this purpose, in 1994 it tried to make compulsory use of the causal tree approach to accident analysis, an approach developed in France during the 1970s,without having previously determined whether it is suitable for use under the industrial safety conditions that prevail in most Brazilian firms. In addition, apposition from Brazilian employers has blocked the proposed changes to the norms. The present study employed anthropotechnology to analyse experimental application of the causal tree method to work-related accidents in industrial firms in the region of Botucatu, São Paulo. Three work-related accidents were examined in three industrial firms representative of local, national and multinational companies. on the basis of the accidents analysed in this study, the rationale for the use of the causal tree method in Brazil can be summarized for each type of firm as follows:the method is redundant if there is a predominance of the type of risk whose elimination or neutralization requires adoption of conventional industrial safety measures (firm representative of local enterprises); the method is worth while if the company's specific technical risks have already largely been eliminated (firm representative of national enterprises); and the method is particularly appropriate if the firm has a good safety record and the causes of accidents are primarily related to industrial organization and management (multinational enterprise).

Reação de 16 porta-enxertos sob laranjeira 'Valência' ao agente causal, Candidatus Liberibacter asiaticus

Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV

Caracterização morfométrica, patogênica e genética de isolados de Colletrotrichum gloeosporioides, agente causal da antracnose em manga (Mangifera indica L.)

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Podridão floral dos citros: variabilidade, sobrevivência e controle do agente causal, Colletotrichum acutatum

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fenômenos emocionais no contexto explicativo do modo causal de seleção por conseqüências

B. F. Skinner deu início ao behaviorismo radical, enquanto filosofia de uma ciência do comportamento, e reuniu os argumentos experimentais e teóricos que fundamentaram tal ciência. A proposta skinneriana distinguiu-se da psicologia da primeira metade do século XX por instituir o monismo físico como visão de homem e recomendar a abordagem de respostas abertas e encobertas no contexto de relações indivíduoambiente. No entanto, a adoção do modo causal de seleção por conseqüências para a explicação do comportamento pode ser tida como controversa no âmbito de análise de fenômenos emocionais, por estes apresentarem componentes operantes, mas também respondentes. Tendo em vista que a seleção ao nível filogenético permite a compreensão do estabelecimento de relações respondentes incondicionadas, objetivou-se analisar até que ponto um modelo selecionista permite a explicação de relações respondentes condicionadas, nos casos referentes a fenômenos emocionais. A investigação de elaborações da análise do comportamento resultou na proposição de um modelo interpretativo de fenômenos emocionais por meio de inter-relações entre processos respondentes e operantes. A coerência interna do sistema explicativo skinneriano é preservada por manter-se o pressuposto básico de que, em se tratando da ontogênese, relações historicamente estabelecidas com o ambiente explicam a ocorrência de respostas abertas, encobertas, respondentes, operantes ou com ambos os componentes. Considerando que clareza conceitual tende a ser um pré-requisito para o desenvolvimento de alternativas de intervenção, contrastou-se o modelo interpretativo proposto ao contexto de realização de análises funcionais na literatura da análise do comportamento. Preliminarmente, tal modelo demonstrou ser uma ferramenta útil, na medida em que favorece a compreensão de diferentes funções das variáveis que participam das relações comportamentais em foco, de uma perspectiva contextualizada e histórica.

Comparative proteomic analysis reveals that T3SS, Tfp, and xanthan gum are key factors in initial stages of Citrus sinensis infection by Xanthomonas citri subsp citri

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Do Academic and Private Entrepreneurs differ? An empirical analysis of the Micro-Foundation of Entrepreneurial Orientation

This Doctoral Thesis focuses on the study of individual behaviours as a result of organizational affiliation. The objective is to assess the Entrepreneurial Orientation of individuals proving the existence of a set of antecedents to that measure returning a structural model of its micro-foundation. Relying on the developed measurement model, I address the issue whether some Entrepreneurs experience different behaviours as a result of their academic affiliation, comparing a sample of ‘Academic Entrepreneurs’ to a control sample of ‘Private Entrepreneurs’ affiliated to a matched sample of Academic Spin-offs and Private Start-ups. Building on the Theory of the Planned Behaviour, proposed by Ajzen (1991), I present a model of causal antecedents of Entrepreneurial Orientation on constructs extensively used and validated, both from a theoretical and empirical perspective, in sociological and psychological studies. I focus my investigation on five major domains: (a) Situationally Specific Motivation, (b) Personal Traits and Characteristics, (c) Individual Skills, (d) Perception of the Business Environment and (e) Entrepreneurial Orientation Related Dimensions. I rely on a sample of 200 Entrepreneurs, affiliated to a matched sample of 72 Academic Spin-offs and Private Start-ups. Firms are matched by Industry, Year of Establishment and Localization and they are all located in the Emilia Romagna region, in northern Italy. I’ve gathered data by face to face interviews and used a Structural Equation Modeling technique (Lisrel 8.80, Joreskog, K., & Sorbom, D. 2006) to perform the empirical analysis. The results show that Entrepreneurial Orientation is a multi-dimensional micro-founded construct which can be better represented by a Second-Order Model. The t-tests on the latent means reveal that the Academic Entrepreneurs differ in terms of: Risk taking, Passion, Procedural and Organizational Skills, Perception of the Government, Context and University Supports. The Structural models also reveal that the main differences between the two groups lay in the predicting power of Technical Skills, Perceived Context Support and Perceived University Support in explaining the Entrepreneurial Orientation Related Dimensions.

A partial dependence factorial analysis to deal with selection bias in observational studis

This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Epidemiology and population genetics of Podosphaera fusca and Golovinomyces orontii, causal agents of cucurbit powdery mildew

In 2010, 2011 and 2012 growing seasons, the occurrence of the ascomycetes Podosphaera fusca and Golovinomyces orontii, causal agents of powdery mildew disease, was monitored on cultivated cucurbits located in Bologna and Mantua provinces to determine the epidemiology of the species. To identify the pathogens, both morphological and molecular identifications were performed on infected leaf samples and a Multiplex-PCR was performed to identify the mating type genes of P. fusca isolates. The investigations indicated a temporal succession of the two species with the earlier infections caused by G. orontii, that seems to be the predominant species till the middle of July when it progressively disappears and P. fusca becomes the main species infecting cucurbits till the end of October. The temporal variation is likely due to the different overwintering strategies of the two species instead of climatic conditions. Only chasmothecia of P. fusca were recorded and mating type alleles ratio tended to be 1:1. Considering that only chasmothecia of P. fusca were found, molecular-genetic analysis were carried out to find some evidence of recombination within this species by MLST and AFLP methods. Surprisingly, no variations were observed within isolates for the 8 MLST markers used. According to this result, AFLP analysis showed a high similarity within isolates, with SM similarity coefficient ranging between 0.91-1.00 and also, sequencing of 12 polymorphic bands revealed identity to some gene involved in mutation and selection. The results suggest that populations of P. fusca are likely to be a clonal population with some differences among isolates probably due to agricultural practices such as fungicides treatments and cultivated hosts. Therefore, asexual reproduction, producing a lot of fungal biomass that can be easily transported by wind, is the most common and useful way to the spread and colonization of the pathogen.

Gene expression analysis in ‘Candidatus Phytoplasma mali’-resistant and -susceptible Malus genotypes

Apple proliferation (AP) disease is the most important graft-transmissible and vector-borne disease of apple in Europe. ‘Candidatus Phytoplasma mali’ (Ca. P. mali) is the causal agent of AP. Apple (Malus x domestica) and other Malus species are the only known woody hosts. In European apple orchards, the cultivars are mainly grafted on one rootstock, M. x domestica cv. M9. M9 like all other M. x domestica cultivars is susceptible to ‘Ca. P. mali’. Resistance to AP was found in the wild genotype Malus sieboldii (MS) and in MS-derived hybrids but they were characterised by poor agronomic value. The breeding of a new rootstock carrying the resistant and the agronomic traits was the major aim of a project of which this work is a part. The objective was to shed light into the unknown resistance mechanism. The plant-phytoplasma interaction was studied by analysing differences between the ‘Ca. P. mali’-resistant and -susceptible genotypes related to constitutively expressed genes or to induced genes during infection. The cDNA-Amplified Fragment Length Polymorphism (cDNA-AFLP) technique was employed in both approaches. Differences related to constitutively expressed genes were identified between two ‘Ca. P. mali’-resistant hybrid genotypes (4551 and H0909) and the ‘Ca. P. mali’-susceptible M9. 232 cDNA-AFLP bands present in the two resistant genotypes but absent in the susceptible one were isolated but several different products associated to each band were found. Therefore, two different macroarray hybridisation experiments were performed with the cDNA-AFLP fragments yielding 40 sequences encoding for genes of unknown function or a wide array of functions including plant defence. In the second approach, individuation and analysis of the induced genes was carried out exploiting an in vitro system in which healthy and ‘Ca. P. mali’-infected micropropagated plants were maintained under controlled conditions. Infection trials using in vitro grafting of ‘Ca. P. mali’ showed that the resistance phenotype could be reproduced in this system. In addition, ex vitro plants were generated as an independent control of the genes differentially expressed in the in vitro plants. The cDNA-AFLP analysis in in vitro plants yielded 63 bands characterised by over-expression in the infected state of both the H0909 and MS genotypes. The major part (37 %) of the associated sequences showed homology with products of unknown function. The other genes were involved in plant defence, energy transport/oxidative stress response, protein metabolism and cellular growth. Real-time qPCR analysis was employed to validate the differential expression of the genes individuated in the cDNA-AFLP analysis. Since no internal controls were available for the study of the gene expression in Malus, an analysis on housekeeping genes was performed. The most stably expressed genes were the elongation factor-1 α (EF1) and the eukaryotic translation initiation factor 4-A (eIF4A). Twelve out of 20 genes investigated through qPCR were significantly differentially expressed in at least one genotype either in in vitro plants or in ex vitro plants. Overall, about 20% of the genes confirmed their cDNA-AFLP expression pattern in M. sieboldii or H0909. On the contrary, 30 % of the genes showed down-regulation or were not differentially expressed. For the remaining 50 % of the genes a contrasting behaviour was observed. The qPCR data could be interpreted as follows: the phytoplasma infection unbalance photosynthetic activity and photorespiration down-regulating genes involved in photosynthesis and in the electron transfer chain. As result, and in contrast to M. x domestica genotypes, an up-regulation of genes of the general response against pathogens was found in MS. These genes involved the pathway of H2O2 and the production of secondary metabolites leading to the hypothesis that a response based on the accumulation of H2O2 in MS would be at the base of its resistance. This resembles a phenomenon known as “recovery” where the spontaneous remission of the symptoms is observed in old susceptible plants but occurring in a stochastic way while the resistance in MS is an inducible but stable feature. As additional product of this work three cDNA-AFLP-derived markers were developed which showed independent distribution among the seedlings of two breeding progenies and were associated to a genomic region characteristic of MS. These markers will contribute to the development of molecular markers for the resistance as well as to map the resistance on the Malus genome.

Obsessed With Work: A multi-causal and multi-rater approach to workaholism

Workaholism is defined as the combination of two underlying dimensions: working excessively and working compulsively. The present thesis aims at achieving the following purposes: 1) to test whether the interaction between environmental and personal antecedents may enhance workaholism; 2) to develop a questionnaire aimed to assess overwork climate in the workplace; 3) to contrast focal employees’ and coworkers’ perceptions of employees’ workaholism and engagement. Concerning the first purpose, the interaction between overwork climate and person characteristics (achievement motivation, perfectionism, conscientiousness, self-efficacy) was explored on a sample of 333 Dutch employees. The results of moderated regression analyses showed that the interaction between overwork climate and person characteristics is related to workaholism. The second purpose was pursued with two interrelated studies. In Study 1 the Overwork Climate Scale (OWCS) was developed and tested using a principal component analysis (N = 395) and a confirmatory factor analysis (N = 396). Two overwork climate dimensions were distinguished, overwork endorsement and lacking overwork rewards. In Study 2 the total sample (N = 791) was used to explore the association of overwork climate with two types of working hard: work engagement and workaholism. Lacking overwork rewards was negatively associated with engagement, whereas overwork endorsement showed a positive association with workaholism. Concerning the third purpose, using a sample of 73 dyads composed by focal employees and their coworkers, a multitrait-multimethod matrix and a correlated trait-correlated method model, i.e. the CT-C(M–1) model, were examined. Our results showed a considerable agreement between raters on focal employees' engagement and workaholism. In contrast, we observed a significant difference concerning the cognitive dimension of workaholism, working compulsively. Moreover, we provided further evidence for the discriminant validity between engagement and workaholism. Overall, workaholism appears as a negative work-related state that could be better explained by assuming a multi-causal and multi-rater approach.

A sequential Cox approach for estimating the causal effect of treatment in the presence of time-dependent confounding applied to data from the Swiss HIV Cohort Study

When estimating the effect of treatment on HIV using data from observational studies, standard methods may produce biased estimates due to the presence of time-dependent confounders. Such confounding can be present when a covariate, affected by past exposure, is both a predictor of the future exposure and the outcome. One example is the CD4 cell count, being a marker for disease progression for HIV patients, but also a marker for treatment initiation and influenced by treatment. Fitting a marginal structural model (MSM) using inverse probability weights is one way to give appropriate adjustment for this type of confounding. In this paper we study a simple and intuitive approach to estimate similar treatment effects, using observational data to mimic several randomized controlled trials. Each 'trial' is constructed based on individuals starting treatment in a certain time interval. An overall effect estimate for all such trials is found using composite likelihood inference. The method offers an alternative to the use of inverse probability of treatment weights, which is unstable in certain situations. The estimated parameter is not identical to the one of an MSM, it is conditioned on covariate values at the start of each mimicked trial. This allows the study of questions that are not that easily addressed fitting an MSM. The analysis can be performed as a stratified weighted Cox analysis on the joint data set of all the constructed trials, where each trial is one stratum. The model is applied to data from the Swiss HIV cohort study.

A causal model of mathematics performance in early adolescence: the role of sex

Using path analysis, the present investigation was done to clarify possible causal linkages among general scholastic aptitude, academic achievement in mathematics, self-concept of ability, and performance on a mathematics examination. Subjects were 122 eighth-grade students who completed a mathematics examination as well as a measure of self-concept of ability. Aptitude and achievement measures were obtained from school records. Analysis showed sex differences in prediction of performance on the mathematics examination. For boys, this performance could be predicted from scholastic aptitude and previous achievement in mathematics. For girls, performance only could be predicted from previous achievement in mathematics. These results indicate that the direction, strength, and magnitude of relations among these variables differed for boys and girls, while mean levels of performance did not.

An empirical examination of the integration of causal attribution and social learning theories in achievement situations

Using path analysis, the present investigation sought to clarify possible operational linkages among constructs from social learning and attribution theories within the context of a self-esteem system. Subjects were 300 undergraduate university students who completed a measure of self-esteem and indicated expectancies for success and minimal goal levels for an experimental task. After completing the task and receiving feedback about their performance, subjects completed causal attribution and self-esteem questionnaires. Results revealed gender differences in the degree and strength of the proposed relations, but not in the mean levels of the variables studied. Results suggested that the integration of social learning and attribution theories within a single conceptual model provides a better understanding of students' behaviors and self-esteem in achievement situations.