The risk-return trade-off in Europe: A temporal and cross-sectional analysis

This paper analyzes the risk-return trade-off in European equities considering both temporal and cross-sectional dimensions. In our analysis, we introduce not only the market portfolio but also 15 industry portfolios comprising the entire market. Several bivariate GARCH models are estimated to obtain the covariance matrix between excess market returns and the industrial portfolios and the existence of a risk-return trade-off is analyzed through a cross-sectional approach using the information in all portfolios. It is obtained evidence for a positive and significant risk-return trade-off in the European market. This conclusion is robust for different GARCH specifications and is even more evident after controlling for the main financial crisis during the sample period.

Analysis of the interference of endogenous circadian rhythms on 3'- deoxy- 3'- [18F]Fluorothymidine physiological uptake at the human bone marrow

The main purpose of the present study is to determine if the circadian rhythms present in the human bone marrow are likely to influence 3’- deoxy- 3’-[18F] Fluorothymidine (18F-FLT) uptake in the same organ. The 18F-FLT is a Thymidine analogous proliferation agent. The relatively high physiological uptake of this tracer in the bone marrow diminishes the Tumor/Background (T/B) ratio, decreasing the detection accuracy of PET/CT and possibly affecting SUV quantifications.

Temporal patterns of TV watching for Portuguese viewers

Audiometer systems provide enormous amounts of detailed TV watching data. Several relevant and interdependent factors may influence TV viewers' behavior. In this work we focus on the time factor and derive Temporal Patterns of TV watching, based on panel data. Clustering base attributes are originated from 1440 binary minute-related attributes, capturing the TV watching status (watch/not watch). Since there are around 2500 panel viewers a data reduction procedure is first performed. K-Means algorithm is used to obtain daily clusters of viewers. Weekly patterns are then derived which rely on daily patterns. The obtained solutions are tested for consistency and stability. Temporal TV watching patterns provide new insights concerning Portuguese TV viewers' behavior.

Risk factors for metabolic bone disease in Crohn's disease patients

Background: The aim was to evaluate the presence of metabolic bone disease (MBD) in patients with Crohn’s disease (CD) and to identify potential etiologic factors. Methods: The case–control study included 99 patients with CD and 56 controls with a similar age and gender distribution. Both groups had dual-energy x-ray absorptionmetry and a nutritional evaluation. Single nucleotide polymorphisms at the IL1, TNF-a, LTa, and IL-6 genes were analyzed in patients only. Statistical analysis was performed using SPSS software. Results: The prevalence of MBD was significantly higher in patients (P ¼ 0.006). CD patients with osteoporosis were older (P < 0.005), small bowel involvement and surgical resections were more frequent (P < 0.005), they more often exhibited a penetrating or stricturing phenotype (P < 0.05), duration of disease over 15 years (P < 0.005), and body mass index (BMI) under 18.5 kg/m2 (P < 0.01) were more often found. No association was found with steroid use. Patients with a Z-score < 2.0 more frequently had chronic active disease (P < 0.05). With regard to diet, low vitamin K intake was more frequent (P ¼ 0.03) and intake of total, monounsaturated, and polyunsaturated fat was higher in patients with Z-score < 2.0 (P < 0.05). With respect to genetics, carriage of the polymorphic allele for LTa252 A/G was associated with a higher risk of osteoporosis (P ¼ 0.02). Regression analysis showed that age over 40 years, chronic active disease, and previous colonic resections were independently associated with the risk of developing MBD. Conclusions: The prevalence of MBD was significantly higher in CD patients. Besides the usual risk factors, we observed that factors related to chronic active and long-lasting disease increased the risk of MBD.

Pulmonary tuberculosis in Continental Portugal 2000-2010: temporal trends clustering as a tool for control evaluation

Clustering analysis is a useful tool to detect and monitor disease patterns and, consequently, to contribute for an effective population disease management. Portugal has the highest incidence of tuberculosis in the European Union (in 2012, 21.6 cases per 100.000 inhabitants), although it has been decreasing consistently. Two critical PTB (Pulmonary Tuberculosis) areas, metropolitan Oporto and metropolitan Lisbon regions, were previously identified through spatial and space-time clustering for PTB incidence rate and risk factors. Identifying clusters of temporal trends can further elucidate policy makers about municipalities showing a faster or a slower TB control improvement.

Optimizing the renewable generation mix in the Portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.

Optimizing the renewable generation mix in the portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.