Mergers and acquisitions as strategies of business expansion in the pharmaceutical industry

Introduction: The present paper deals with the issue of the increasing usage of corporation mergers and acquisitions strategies within pharmaceutical industry environment. The aim is to identify the triggers of such business phenomenon and the immediate impact on the financial outcome of two powerful biopharmaceutical corporations: Pfizer and GlaxoSmithKline, which have been sampled due to their successful approach of the tactics in question. Materials and Methods: In order to create an overview of the development steps through mergers and acquisitions, the historical data of the two corporations has been consulted, from their official websites. The most relevant events were then associated with adequate information from the financial reports and statements of the two corporations indulged by web-based financial data providers. Results and Discussions: In the past few decades Pfizer and GlaxoSmithKline have purchased or merged with various companies in order to monopolize new markets, diversify products and services portfolios, survive and surpass competitors. The consequences proved to be positive although this approach implies certain capital availability. Conclusions: Results reveal the fact that, as far as the two sampled companies are concerned, acquisitions and mergers are reactions at the pressure of the highly competitive environment. Moreover, the continuous diversification of the market’s needs is also a consistent motive. However, the prevalence and the eminence of mergers and acquisition strategies are conditioned by the tender offer, the announcer’s caliber, research and development status and further other factors determined by the internal and external actors of the market.

LMP triggered real time demand response events

Recent changes in power systems mainly due to the substantial increase of distributed generation and to the operation in competitive environments has created new challenges to operation and planning. In this context, Virtual Power Players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Demand response market implementation has been done in recent years. Several implementation models have been considered. An important characteristic of a demand response program is the trigger criterion. A program for which the event trigger depends on the Locational Marginal Price (LMP) used by the New England Independent System operator (ISO-NE) inspired the present paper. This paper proposes a methodology to support VPP demand response programs management. The proposed method has been computationally implemented and its application is illustrated using a 32 bus network with intensive use of distributed generation. Results concerning the evaluation of the impact of using demand response events are also presented.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Demand response in electrical energy supply: an optimal real time pricing approach

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer’s profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer’s profit. The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers’ decision making.

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

VirtualECare: group decision supported by idea generation and argumentation

In the last years there has been a considerable increase in the number of people in need of intensive care, especially among the elderly, a phenomenon that is related to population ageing (Brown 2003). However, this is not exclusive of the elderly, as diseases as obesity, diabetes, and blood pressure have been increasing among young adults (Ford and Capewell 2007). As a new fact, it has to be dealt with by the healthcare sector, and particularly by the public one. Thus, the importance of finding new and cost effective ways for healthcare delivery are of particular importance, especially when the patients are not to be detached from their environments (WHO 2004). Following this line of thinking, a VirtualECare Multiagent System is presented in section 2, being our efforts centered on its Group Decision modules (Costa, Neves et al. 2007) (Camarinha-Matos and Afsarmanesh 2001).On the other hand, there has been a growing interest in combining the technological advances in the information society - computing, telecommunications and knowledge – in order to create new methodologies for problem solving, namely those that convey on Group Decision Support Systems (GDSS), based on agent perception. Indeed, the new economy, along with increased competition in today’s complex business environments, takes the companies to seek complementarities, in order to increase competitiveness and reduce risks. Under these scenarios, planning takes a major role in a company life cycle. However, effective planning depends on the generation and analysis of ideas (innovative or not) and, as a result, the idea generation and management processes are crucial. Our objective is to apply the GDSS referred to above to a new area. We believe that the use of GDSS in the healthcare arena will allow professionals to achieve better results in the analysis of one’s Electronically Clinical Profile (ECP). This attainment is vital, regarding the incoming to the market of new drugs and medical practices, which compete in the use of limited resources.

Introduction to the special issue on real world applications of intelligent tutoring systems

The idea behind creating this special issue on real world applications of intelligent tutoring systems was to bring together in a single publication some of the most important examples of success in the use of ITS technology. This will serve as a reference to all researchers working in the area. It will also be an important resource for the industry, showing the maturity of ITS technology and creating an atmosphere for funding new ITS projects. Simultaneously, it will be valuable to academic groups, motivating students for new ideas of ITS and promoting new academic research work in the area.

Cluster Analysis of Business Data

This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.

Remoção hierárquica de geometria por oclusão em simulações em tempo real

Mestrado em Engenharia Electrotécnica e de Computadores

Real-time rheology of actively growing bacteria

The population growth of a Staphylococcus aureus culture, an active colloidal system of spherical cells, was followed by rheological measurements, under steady-state and oscillatory shear flows. We observed a rich viscoelastic behavior as a consequence of the bacteria activity, namely, of their multiplication and density-dependent aggregation properties. In the early stages of growth (lag and exponential phases), the viscosity increases by about a factor of 20, presenting several drops and full recoveries. This allows us to evoke the existence of a percolation phenomenon. Remarkably, as the bacteria reach their late phase of development, in which the population stabilizes, the viscosity returns close to its initial value. Most probably, this is caused by a change in the bacteria physiological activity and in particular, by the decrease of their adhesion properties. The viscous and elastic moduli exhibit power-law behaviors compatible with the "soft glassy materials" model, whose exponents are dependent on the bacteria growth stage. DOI: 10.1103/PhysRevE.87.030701.

Desenvolvimento de uma ferramenta de pré-selecção de recursos para empresas ágeis/virtuais

Mestrado em Engenharia Electrotécnica e de Computadores

The importance of qualitative methodology in management empirical research

Purpose: The aim of this paper is to highlight the importance of qualitative research within the scope of management scientific studies, referring to its philosophy, nature and instruments. It also confronts it with quantitative methodology, approaching its differences as well as its complementariness and synergies, with the purpose of explaining, from a more analytic point of view, the relevance of qualitative methodology in the course of an authentic and real research despite its complexity. Design/methodology/approach: Regardless of its broad application, one may attest the scarcity literature that focuses on qualitative research applied to the management scientific area, as opposed to the large amount that refers to quantitative research. Findings: The paper shows the influence that qualitative research has on management scientific research. Originality/value:. Qualitative research assumes an important role within qualitative research by allowing for the study and analysis of certain types of phenomena that occur inside organisations, and in respect of which quantitative studies cannot provide an answer.

Differential expression of the eukaryotic release factor 3 (eRF3/GSPT1) according to gastric cancer histological types

Background: There are now several lines of evidence to suggest that protein synthesis and translation factors are involved in the regulation of cell proliferation and cancer development. Aims: To investigate gene expression patterns of eukaryotic releasing factor 3 (eRF3) in gastric cancer. Methods: RNA was prepared from 25 gastric tumour biopsies and adjacent non-neoplastic mucosa. Real time TaqMan reverse transcription polymerase chain reaction (RT-PCR) was performed to measure the relative gene expression levels. DNA was isolated from tumour and normal tissues and gene dosage was determined by a quantitative real time PCR using SYBR Green dye. Results: Different histological types of gastric tumours were analysed and nine of the 25 tumours revealed eRF3/GSPT1 overexpression; moreover, eight of the 12 intestinal type carcinomas analysed overexpressed the gene, whereas eRF3/GSPT1 was overexpressed in only one of the 10 diffuse type carcinomas (Kruskal-Wallis Test; p , 0.05). No correlation was found between ploidy and transcript expression levels of eRF3/GSPT1. Overexpression of eRF3/GSPT1 was not associated with increased translation rates because the upregulation of eRF3/GSPT1 did not correlate with increased eRF1 levels. Conclusions: Overexpression of eRF3/GSPT1 in intestinal type gastric tumours may lead to an increase in the translation efficiency of specific oncogenic transcripts. Alternatively, eRF3/GSPT1 may be involved in tumorigenesis as a result of its non-translational roles, namely (dis)regulating the cell cycle, apoptosis, or transcription.

Arquitecturas e ferramentas para gestão de redes e sistemas: estudo de um caso

Mestrado em Engenharia Informática - Área de Especialização em Arquitecturas, Sistemas e Redes

Distributed process execution in collaborative networks

Processes are a central entity in enterprise collaboration. Collaborative processes need to be executed and coordinated in a distributed Computational platform where computers are connected through heterogeneous networks and systems. Life cycle management of such collaborative processes requires a framework able to handle their diversity based on different computational and communication requirements. This paper proposes a rational for such framework, points out key requirements and proposes it strategy for a supporting technological infrastructure. Beyond the portability of collaborative process definitions among different technological bindings, a framework to handle different life cycle phases of those definitions is presented and discussed. (c) 2007 Elsevier Ltd. All rights reserved.