Workplace aggression in organizational changing processes: The mediation role of leader political (soft and hard) behavior

One of the main trends in workplace aggression research is studying its antecedents. But the literature also reveals that some predictors remain understudied, like organizational change [1]. Additionally, possible mediators of this relationship were not investigated. The main objective of this research is studding the mediating effect of the leader political behavior (soft and hard version) on the relationship between organizational change and workplace aggression. Participants representing a wide variety of jobs across many organizations were surveyed. The measures used in this research are an Organizational Change Questionnaire climate of change, processes, and readiness [2], a Workplace Aggression Scale [e.g. 3, 4] and a Political Behavior Questionnaire [5]. The results of the study and its theoretical and practical implications will be presented and discussed.

Supporting conceptualisation processes in collaborative networks: a case study on an R&D project

The development of new products or processes involves the creation, re-creation and integration of conceptual models from the related scientific and technical domains. Particularly, in the context of collaborative networks of organisations (CNO) (e.g. a multi-partner, international project) such developments can be seriously hindered by conceptual misunderstandings and misalignments, resulting from participants with different backgrounds or organisational cultures, for example. The research described in this article addresses this problem by proposing a method and the tools to support the collaborative development of shared conceptualisations in the context of a collaborative network of organisations. The theoretical model is based on a socio-semantic perspective, while the method is inspired by the conceptual integration theory from the cognitive semantics field. The modelling environment is built upon a semantic wiki platform. The majority of the article is devoted to developing an informal ontology in the context of a European R&D project, studied using action research. The case study results validated the logical structure of the method and showed the utility of the method.

Campanha de comunicação de Ambient Media para a marca Leroy Merlin

Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

The use of information and interactive processes in growth management

Tese de doutoramento em Engenharia do Ambiente, especialidade em Sistemas Sociais

Detection of quasi-periodic processes in complex systems: how do we quantitatively describe their properties?

It has been shown that in reality at least two general scenarios of data structuring are possible: (a) a self-similar (SS) scenario when the measured data form an SS structure and (b) a quasi-periodic (QP) scenario when the repeated (strongly correlated) data form random sequences that are almost periodic with respect to each other. In the second case it becomes possible to describe their behavior and express a part of their randomness quantitatively in terms of the deterministic amplitude–frequency response belonging to the generalized Prony spectrum. This possibility allows us to re-examine the conventional concept of measurements and opens a new way for the description of a wide set of different data. In particular, it concerns different complex systems when the ‘best-fit’ model pretending to be the description of the data measured is absent but the barest necessity of description of these data in terms of the reduced number of quantitative parameters exists. The possibilities of the proposed approach and detection algorithm of the QP processes were demonstrated on actual data: spectroscopic data recorded for pure water and acoustic data for a test hole. The suggested methodology allows revising the accepted classification of different incommensurable and self-affine spatial structures and finding accurate interpretation of the generalized Prony spectroscopy that includes the Fourier spectroscopy as a partial case.

Change Processes and Future Perspectives in the Knowledge Society. The Example of Clothing and Textile Industry

The paper examines change processes und future perspectives in the knowledge society. It presents the clothing and textile industry as an example for a transforming industry in a global economy. The paper reviews existing future studies, which have surveyed change processes and future developments in the clothing and textile industry. Main goals of the review are the identification of changes in work and the description of the restructuring of global value chains within the clothing and textile sector. The paper also highlights major current trends, drivers of change and future prospects in this sector.

Management Structure and Work Team Processes; Responsibilities and Responsiveness

This paper explores the management structure of the team-based organization. First it provides a theoretical model of structures and processes of work teams. The structure determines the team’s responsibilities in terms of authority and expertise about specific regulation tasks. The responsiveness of teams to these responsibilities are the processes of teamwork, in terms of three dimensions, indicating to what extent teams indeed use the space provided to them. The research question that this paper addresses is to what extent the position of responsibilities in the team-based organization affect team responsiveness. This is done by two hypotheses. First, the effect of the so-called proximity of regulation tasks is tested. It is expected that the responsibility for tasks positioned higher in the organization (i.e. further from the team) generally has a negative effect on team responsiveness, whereas tasks positioned lower in the organization (i.e. closer to the team) will have a positive effect on the way in which teams respond. Second, the relationship between the number of tasks for which the team is responsible with team responsiveness is tested. Theory suggests that teams being responsible for a larger number of tasks perform better, i.e. show higher responsiveness. These hypotheses are tested by a study of 109 production teams in the automotive industry. The results show that, as the theory predicts, increasing numbers of responsibilities have positive effects on team responsiveness. However, the delegation of expertise to teams seems to be the most important predictor of responsiveness. Also, not all regulation tasks show to have effects on team responsiveness. Most tasks do not show to have any significant effect at all. A number of tasks affects team responsiveness positively, when their responsibility is positioned lower in the organization, but also a number of tasks affects team responsiveness positively when located higher in the organization, i.e. further from the teams in the production. The results indicate that more attention can be paid to the distribution of responsibilities, in particular expertise, to teams. Indeed delegating more expertise improve team responsiveness, however some tasks might be located better at higher organizational levels, indicating that there are limitations to what responsibilities teams can handle.

Impacto dos sistemas colaborativos nas organizações: estudo de casos de adopção e utilização de sistemas workflow

Dissertação apresentada na Universidade do Minho com vista à obtenção do grau de Doutor em Tecnologias e Sistemas de Informação (Engenharia e Gestão de Sistemas de Informação)

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

A web-based tool to evaluate the iterative processes of direct search methods

Constrained and unconstrained Nonlinear Optimization Problems often appear in many engineering areas. In some of these cases it is not possible to use derivative based optimization methods because the objective function is not known or it is too complex or the objective function is non-smooth. In these cases derivative based methods cannot be used and Direct Search Methods might be the most suitable optimization methods. An Application Programming Interface (API) including some of these methods was implemented using Java Technology. This API can be accessed either by applications running in the same computer where it is installed or, it can be remotely accessed through a LAN or the Internet, using webservices. From the engineering point of view, the information needed from the API is the solution for the provided problem. On the other hand, from the optimization methods researchers’ point of view, not only the solution for the problem is needed. Also additional information about the iterative process is useful, such as: the number of iterations; the value of the solution at each iteration; the stopping criteria, etc. In this paper are presented the features added to the API to allow users to access to the iterative process data.

Future gender relations in global restructuring processes case study evidence from knowledge-intensive, manufacturing and service occupations

Global restructuring processes have not only strong implications for European working and living realities, but also have specific outcomes with regard to gender relations. The following contribution analyses in which way global restructuring shapes current gender relations in order to identify important trends and developments for future gender (in)equalities at the workplace. On the basis of a large qualitative study on global restructuring and impacts on different occupational groups it argues that occupational belonging in line with skill and qualification levels are crucial factors to assess the further development of gender relations at work. Whereas global restructuring in knowledge-based occupations may provide new opportunities for female employees, current restructuring is going to deteriorate female labour participation in service occupations. In contrast, manufacturing occupations can be characterised by persistent gender relations, which do not change in spite of major restructuring processes at the work place. Taking the institutional perspective into account, it seems to be crucial to integrate the occupational perspective in order to apply adequate policy regulations to prevent the reinforcement of gender related working patterns in the near future.

Voltammetric quantification of fluoxetine: application to quality control and quality assurance processes

The oxidative behaviour of fluoxetine was studied at a glassy carbon electrode in various buffer systems and at different pH using cyclic, differential pulse and square wave voltammetry. A new square wave voltammetric method suitable for the quality control of fluoxetine in commercial formulations has been developed using a borate pH 9 buffer solution as supporting electrolyte. Under optimized conditions, a linear response was obtained in the range 10 to 16 μM with a detection limit of 1.0 μM. Validation parameters such as sensitivity, precision and accuracy were evaluated. The proposed method was successfully applied to the determination of fluoxetine in pharmaceutical formulations. The results were statistically compared with those obtained by the reference high-performance liquid chromatographic method. No significant differences were found between the methods.

Development of biocompatible and “smart” porous structures using CO2-assisted processes

Dissertação apresentada para a obtenção do grau de Doutor em Engenharia Química, especialidade Engenharia da Reacção Química, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Segmentation of striatal brain structures from high resolution pet images

Dissertation presented at the Faculty of Science and Technology of the New University of Lisbon in fulfillment of the requirements for the Masters degree in Electrical Engineering and Computers

Synthesis of Sub-5 NM Co-Doped SnO2 nanoparticles and their structural microstructural, optical and photocatalytic properties

A swift chemical route to synthesize Co-doped SnO2 nanopowders is described. Pure and highly stable Sn1-xCoxO2-delta (0 <= x <= 0.15) crystalline nanoparticles were synthesized, with mean grain sizes <5 nm and the dopant element homogeneously distributed in the SnO2 matrix. The UV-visible diffuse reflectance spectra of the Sn1-xCoxO2-delta samples reveal red shifts, the optical bandgap energies decreasing with increasing Co concentration. The samples' Urbach energies were calculated and correlated with their bandgap energies. The photocatalytic activity of the Sn1-xCoxO2-delta samples was investigated for the 4-hydroxylbenzoic acid (4-HBA) degradation process. A complete photodegradation of a 10 ppm 4-HBA solution was achieved using 0.02% (w/w) of Sn0.95Co0.05O2-delta nanoparticles in 60 min of irradiation. (C) 2014 Elsevier B.V. All rights reserved.