New insights into functional regulation in MS-based drug profiling

We present a novel data analysis strategy which combined with subcellular fractionation and liquid chromatography-mass spectrometry (LC-MS) based proteomics provides a simple and effective workflow for global drug profiling. Five subcellular fractions were obtained by differential centrifugation followed by high resolution LC-MS and complete functional regulation analysis. The methodology combines functional regulation and enrichment analysis into a single visual summary. The workflow enables improved insight into perturbations caused by drugs. We provide a statistical argument to demonstrate that even crude subcellular fractions leads to improved functional characterization. We demonstrate this data analysis strategy on data obtained in a MS-based global drug profiling study. However, this strategy can also be performed on other types of large scale biological data.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

A data-mining based methodology for wind forecasting

In many countries the use of renewable energy is increasing due to the introduction of new energy and environmental policies. Thus, the focus on the efficient integration of renewable energy into electric power systems is becoming extremely important. Several European countries have already achieved high penetration of wind based electricity generation and are gradually evolving towards intensive use of this generation technology. The introduction of wind based generation in power systems poses new challenges for the power system operators. This is mainly due to the variability and uncertainty in weather conditions and, consequently, in the wind based generation. In order to deal with this uncertainty and to improve the power system efficiency, adequate wind forecasting tools must be used. This paper proposes a data-mining-based methodology for very short-term wind forecasting, which is suitable to deal with large real databases. The paper includes a case study based on a real database regarding the last three years of wind speed, and results for wind speed forecasting at 5 minutes intervals.

Strategic bidding methodology for electricity markets using adaptive learning

The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players’ models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition.

Optimal methodology for distribution systems reconfiguration based on OPF and solved by decomposition technique

This paper presents a new and efficient methodology for distribution network reconfiguration integrated with optimal power flow (OPF) based on a Benders decomposition approach. The objective minimizes power losses, balancing load among feeders and subject to constraints: capacity limit of branches, minimum and maximum power limits of substations or distributed generators, minimum deviation of bus voltages and radial optimal operation of networks. The Generalized Benders decomposition algorithm is applied to solve the problem. The formulation can be embedded under two stages; the first one is the Master problem and is formulated as a mixed integer non-linear programming problem. This stage determines the radial topology of the distribution network. The second stage is the Slave problem and is formulated as a non-linear programming problem. This stage is used to determine the feasibility of the Master problem solution by means of an OPF and provides information to formulate the linear Benders cuts that connect both problems. The model is programmed in GAMS. The effectiveness of the proposal is demonstrated through two examples extracted from the literature.

Arrow Plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on samples subgroups

Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

Neurokinin-1 receptor, a new modulator of lymphangiogenesis in obese-asthma phenotype

Aims Obesity and asthma are widely prevalent and associated disorders. Recent studies of our group revealed that Substance P (SP) is involved in pathophysiology of obese-asthma phenotype in mice through its selective NK1 receptor (NK1-R). Lymphangiogenesis is impaired in asthma and obesity, and SP activates contractile and inflammatory pathways in lymphatics. Our aim was to study whether NK1-R expression was involved in lymphangiogenesis on visceral (VAT) and subcutaneous (SAT) adipose tissues and in the lungs, in obese-allergen sensitized mice. Main methods Diet-induced obese and ovalbumin (OVA)-sensitized Balb/c mice were treated with a selective NK1-R antagonist (CJ 12,255, Pfizer Inc., USA) or placebo. Lymphatic structures (LYVE-1 +) and NK1-R expression were analyzed by immunohistochemistry. A semi-quantitative score methodology was used for NK1-R expression. Key findings Obesity and allergen-sensitization together increased the number of LYVE-1 + lymphatics in VAT and decreased it in SAT and lungs. NK1-R was mainly expressed on adipocyte membranes of VAT, blood vessel areas of SAT, and in lung epithelium. Obesity and allergen-sensitization combined increased the expression of NK1-R in VAT, SAT and lungs. NK1-R antagonist treatment reversed the effects observed in lymphangiogenesis in those tissues. Significance The obese-asthma phenotype in mice is accompanied by increased expression of NK1-R on adipose tissues and lung epithelium, reflecting that SP released during inflammation may act directly on these tissues. Blocking NK1-R affects lymphangiogenesis, implying a role of SP, with opposite physiological consequences in VAT, and in SAT and lungs. Our results provide a clue for a novel SP role in the obese-asthma phenotype.

Corporate brand identity management – proposal of a new framework

The term “corporate brand” has been widely used in literature since the eighties. According to Balmer (1998) this concept tends to be used as an alternative to the concept of corporate identity. The author argues that the use of branding principles to discuss corporate identity has tended to align the area more closely with marketing. However, the literature on brand management (Aaker, 1991; Kapferer, 1991 and de Chernatony and McDonald, 1992), gives little attention to the corporate brand” (p. 985). Based on the concepts of corporate brand, brand identity and B2B relationship, the authors are interested in eliminating this gap in literature by designing a framework of corporate brand identity management. The aim of this investigation is to investigate the impact of B2B relationships in corporate brand identity management. The methodology used is quantitative analysis of surveys and scale development. The originality of this paper is to investigate the influence of the relationship between brands in corporate brand identity. This investigation is very important to help the decisions of the corporate brand managers and academics. According to literature, namely on corporate brands (Balmer 2002b, Hatch and Schultz, 2001, 2003) and on brand identity (Kapferer, 1991, 2008, Aaker, 1996, de Chernatony, 1999) the authors developed a corporate brand identity management framework considering relationships between brands a context variable with definite impact on identity management as stated by Hakansson and Snehota (1989, 1995). These authors consider that organisations´ identity management is pursued under a relational perspective with impact on identity management. Most researchers on identity and corporate brand emphasise the importance of external influences (Kennedy, 1977; King, 1991; de Chernatony, 1999; Balmer and Gray, 2000; Balmer, 2002a). Those influences concern legislation, concurrence, political issues... and stakeholders’ perceptions and reputations (due to the holistic approach demanded by corporate brands). In this context the authors claim the importance of another influence: B2B relationships. This decision is inspired in sociological studies (Mannheim, 1950; and Tajfel and Turner, 1979) regarding individual identity. These authors claim that individuals form their personality by interacting in the social field. The authors argue that corporate brand identity also develops itself under a relational approach. The relationships selected to pursue this investigation are the ones that are developed by Portuguese universities and investigation centres that cooperate by developing investigation. Those centres are administrative and financially autonomous

New xanthenodione: synthesis and antioxidant activity evaluation

6th Spanish-Portuguese-Japanese Organic Chemistry Symposium, Lisboa, de 18 a 20 de Julho de 2012 (Poster Communication).

Xanthenedione derivatives, new promising antioxidant and acetylcholinesterase inhibitor agents

Natural and synthetic xanthone derivatives are well-known for their ability to act as antioxidants and/or enzyme inhibitors. This paper aims to present a successful synthetic methodology towards xanthenedione derivatives and the study of their aromatization to xanthones. Additionally their ability to reduce Fe(III), to scavenge DPPH radicals and to inhibit AChE was evaluated. The results demonstrated that xanthenedione derivative 5e, bearing a catechol unit, showed higher reduction capacity than BHT and similar to quercetin, strong DPPH scavenging activity (EC50 = 3.79 ± 0.06 μM) and it was also showed to be a potent AChEI (IC50 = 31.0 ± 0.09 μM) when compared to galantamine (IC50 = 211.8 ± 9.5 μM).

Planning and implementing a new assessment strategy using an e-learning platform

One of the most difficult issues of e-Learning is the students’ assessment. Being this an outstanding task regarding theoretical topics, it becomes even more challenging when the topics under evaluation are practical. ISCAP’s Information Systems Department is composed of about twenty teachers who have been for several years using an e-learning environment (at the moment Moodle 2.3) combined with traditional assessment. They are now planning and implementing a new e-learning assessment strategy. This effort was undertaken in order to evaluate a practical topic (the use of spreadsheets to solve management problems) common to shared courses of several undergraduate degree programs. The same team group is already experienced in the assessment of theoretical information systems topics using the b-learning platform. Therefore, this project works as an extension to previous experiences being the team aware of the additional difficulties due to the practical nature of the topics. This paper describes this project and presents two cycles of the action research methodology, used to conduct the research. The first cycle goal was to produce a database of questions. When it was implemented in order to be used with a pilot group of students, several problems were identified. Subsequently, the second cycle consisted in solving the identified problems preparing the database and all the players to a broader scope implementation. For each cycle, all the phases, its drawbacks and achievements are described. This paper suits all those who are or are planning to be in the process of shifting their assessment strategy from a traditional to one supported by an e-learning platform.

An integrated recycling approach for GFRP pultrusion wastes: recycling and reuse assessment into new composite materials using Fuzzy Boolean Nets

In this study, efforts were made in order to put forward an integrated recycling approach for the thermoset based glass fibre reinforced polymer (GPRP) rejects derived from the pultrusion manufacturing industry. Both the recycling process and the development of a new cost-effective end-use application for the recyclates were considered. For this purpose, i) among the several available recycling techniques for thermoset based composite materials, the most suitable one for the envisaged application was selected (mechanical recycling); and ii) an experimental work was carried out in order to assess the added-value of the obtained recyclates as aggregates and reinforcement replacements into concrete-polymer composite materials. Potential recycling solution was assessed by mechanical behaviour of resultant GFRP waste modified concrete-polymer composites with regard to unmodified materials. In the mix design process of the new GFRP waste based composite material, the recyclate content and size grade, and the effect of the incorporation of an adhesion promoter were considered as material factors and systematically tested between reasonable ranges. The optimization process of the modified formulations was supported by the Fuzzy Boolean Nets methodology, which allowed finding the best balance between material parameters that maximizes both flexural and compressive strengths of final composite. Comparing to related end-use applications of GFRP wastes in cementitious based concrete materials, the proposed solution overcome some of the problems found, namely the possible incompatibilities arisen from alkalis-silica reaction and the decrease in the mechanical properties due to high water-cement ratio required to achieve the desirable workability. Obtained results were very promising towards a global cost-effective waste management solution for GFRP industrial wastes and end-of-life products that will lead to a more sustainable composite materials industry.

Neurokinin-1 receptor, a new modulator of lymphangiogenesis in obese-asthma phenotype

Aims: Obesity and asthma are widely prevalent and associated disorders. Recent studies of our group revealed that Substance P (SP) is involved in pathophysiology of obese-asthma phenotype in mice through its selective NK1 receptor (NK1-R). Lymphangiogenesis is impaired in asthma and obesity, and SP activates contractile and inflammatory pathways in lymphatics. Our aim was to study whether NK1-R expression was involved in lymphangiogenesis on visceral (VAT) and subcutaneous (SAT) adipose tissues and in the lungs, in obeseallergen sensitized mice. Main methods: Diet-induced obese and ovalbumin (OVA)-sensitized Balb/c mice were treated with a selective NK1-R antagonist (CJ 12,255, Pfizer Inc., USA) or placebo. Lymphatic structures (LYVE-1+) and NK1-R expression were analyzed by immunohistochemistry. A semi-quantitative score methodology was used for NK1-R expression. Key findings: Obesity and allergen-sensitization together increased the number of LYVE-1+ lymphatics in VAT and decreased it in SAT and lungs. NK1-R was mainly expressed on adipocyte membranes of VAT, blood vessel areas of SAT, and in lung epithelium. Obesity and allergen-sensitization combined increased the expression of NK1-R in VAT, SAT and lungs. NK1-R antagonist treatment reversed the effects observed in lymphangiogenesis in those tissues. Significance: The obese-asthma phenotype in mice is accompanied by increased expression of NK1-R on adipose tissues and lung epithelium, reflecting that SP released during inflammation may act directly on these tissues. Blocking NK1-R affects lymphangiogenesis, implying a role of SP, with opposite physiological consequences in VAT, and in SAT and lungs. Our results provide a clue for a novel SP role in the obese-asthma phenotype.

A genetic algorithm for the job shop scheduling with a new local search using Monte Carlo method

This paper presents a methodology for applying scheduling algorithms using Monte Carlo simulation. The methodology is based on a decision support system (DSS). The proposed methodology combines a genetic algorithm with a new local search using Monte Carlo Method. The methodology is applied to the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The methodology is tested on a set of standard instances taken from the literature and compared with others. The computation results validate the effectiveness of the proposed methodology. The DSS developed can be utilized in a common industrial or construction environment.

Risk management of new product development process

Dissertation submitted to Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa for the achievement of Integrated Master´s degree in Industrial Management Engineering