The European challenge of KMN and innovation: a skills and competence portfolio for knowledge worker in SME's

Versão editor: http://www.isegi.unl.pt/docentes/acorreia/documentos/European_Challenge_KM_Innovation_2004.pdf

Cardiorespiratory fitness is negatively associated with metabolic risk factors independently of the adherence to a healthy dietary pattern

Background and aim: Cardiorespiratory fitness (CRF) and diet have been involved as significant factors towards the prevention of cardio-metabolic diseases. This study aimed to assess the impact of the combined associations of CRF and adherence to the Southern European Atlantic Diet (SEADiet) on the clustering of metabolic risk factors in adolescents. Methods and Results: A cross-sectional school-based study was conducted on 468 adolescents aged 15-18, from the Azorean Islands, Portugal. We measured fasting glucose, insulin, total cholesterol (TC), HDL-cholesterol, triglycerides, systolic blood pressure, waits circumference and height. HOMA, TC/HDL-C ratio and waist-to-height ratio were calculated. For each of these variables, a Z-score was computed by age and sex. A metabolic risk score (MRS) was constructed by summing the Z scores of all individual risk factors. High risk was considered when the individual had 1SD of this score. CRF was measured with the 20 m-Shuttle-Run- Test. Adherence to SEADiet was assessed with a semi-quantitative food frequency questionnaire. Logistic regression showed that, after adjusting for potential confounders, unfit adolescents with low adherence to SEADiet had the highest odds of having MRS (OR Z 9.4; 95%CI:2.6e33.3) followed by the unfit ones with high adherence to the SEADiet (OR Z 6.6; 95% CI: 1.9e22.5) when compared to those who were fit and had higher adherence to SEADiet.

Targeting specific nutrient deficiencies in proteinrestricted diets: some practical facts in PKU dietary management

Among aminoacidopathies, phenylketonuria (PKU) is the most prevalent one. Early diagnosis in the neonatal period with a prompt nutritional therapy (low natural-protein and phenylalanine diet, supplemented with phenylalanine-free amino acid mixtures and special low-protein foods) remains the mainstay of the treatment. Data considering nutrient contents of cooked dishes is lacking. In this study, fourteen dishes specifically prepared for PKU individuals were analysed, regarding the lipid profile and iron and zinc contents. These dishes are poor sources of essential nutrients like Fe, Zn or n-3 fatty acids, reinforcing the need for adequate supplementation to cover individual patients’ needs. This study can contribute to a more accurate adjustment of PKU diets and supplementation in order to prevent eventual nutritional deficiencies. This study contributes to a better understanding of nutrient intake from PKU patients’ meals, showing the need for dietary supplementation.

Electricity Markets Portfolio Optimization using a Particle Swarm Approach

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.