Study of the electromyographic signal dynamic behavior in Amyotrophic Lateral Sclerosis (ALS)

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by motor neurons degeneration, which reduces muscular force, being very difficult to diagnose. Mathematical methods are used in order to analyze the surface electromiographic signal’s dynamic behavior (Fractal Dimension (FD) and Multiscale Entropy (MSE)), evaluate different muscle group’s synchronization (Coherence and Phase Locking Factor (PLF)) and to evaluate the signal’s complexity (Lempel-Ziv (LZ) techniques and Detrended Fluctuation Analysis (DFA)). Surface electromiographic signal acquisitions were performed in upper limb muscles, being the analysis executed for instants of contraction for ipsilateral acquisitions for patients and control groups. Results from LZ, DFA and MSE analysis present capability to distinguish between the patient group and the control group, whereas coherence, PLF and FD algorithms present results very similar for both groups. LZ, DFA and MSE algorithms appear then to be a good measure of corticospinal pathways integrity. A classification algorithm was applied to the results in combination with extracted features from the surface electromiographic signal, with an accuracy percentage higher than 70% for 118 combinations for at least one classifier. The classification results demonstrate capability to distinguish members between patients and control groups. These results can demonstrate a major importance in the disease diagnose, once surface electromyography (sEMG) may be used as an auxiliary diagnose method.

How can Impresa increase the traffic of expresso website?

This report aims at describing the project developed in the Customer Relationship Management Field Lab, under a partnership established between Nova SBE and the group IMPRESA. The major goal was to elaborate on possible initiatives to increase the traffic on the website of Expresso, which were supported by evidences found through structured interviews and the company’s internal data. As the main findings are the increasing role of mobile devices and social media on the news’ consumption habits. These encourage an integrated improvement of the overall digital offer of Expresso, in a perspective of brand and audience development that should be a goal for the whole company.

Electrohysterogram signal component cataloging with spectral and time-frequency methods

The Electrohysterogram (EHG) is a new instrument for pregnancy monitoring. It measures the uterine muscle electrical signal, which is closely related with uterine contractions. The EHG is described as a viable alternative and a more precise instrument than the currently most widely used method for the description of uterine contractions: the external tocogram. The EHG has also been indicated as a promising tool in the assessment of preterm delivery risk. This work intends to contribute towards the EHG characterization through the inventory of its components which are: • Contractions; • Labor contractions; • Alvarez waves; • Fetal movements; • Long Duration Low Frequency Waves; The instruments used for cataloging were: Spectral Analysis, parametric and non-parametric, energy estimators, time-frequency methods and the tocogram annotated by expert physicians. The EHG and respective tocograms were obtained from the Icelandic 16-electrode Electrohysterogram Database. 288 components were classified. There is not a component database of this type available for consultation. The spectral analysis module and power estimation was added to Uterine Explorer, an EHG analysis software developed in FCT-UNL. The importance of this component database is related to the need to improve the understanding of the EHG which is a relatively complex signal, as well as contributing towards the detection of preterm birth. Preterm birth accounts for 10% of all births and is one of the most relevant obstetric conditions. Despite the technological and scientific advances in perinatal medicine, in developed countries, prematurity is the major cause of neonatal death. Although various risk factors such as previous preterm births, infection, uterine malformations, multiple gestation and short uterine cervix in second trimester, have been associated with this condition, its etiology remains unknown [1][2][3].

The effect of energy and traffic light labeling on parents purchasing decisions of cereals for their children

Objective: Nutritional labeling systems are considered a tool to fight obesity since they aim to contribute for more informed food choices as well as assist consumers to make healthier nutrition options and in this manner, contribute to a decrease in the obesity rate. This study intends to analyze the effect of different types of labeling systems on parents’ purchasing decisions for their children on a specific product: breakfast cereals. More precisely, how labels affect parents’ perception of healthiness regarding cereals and if the nutritional information has an effect on intended purchases for their children. Participants and methods: We conducted a study with 135 Portuguese parents of children aged 4 to12 years. Parents answered a questionnaire with one of three hypothetical cereals menus. Menus only differed in their nutritional labeling technique: no labels (control group), reference intake labels or traffic light labels. In addition, we conducted 20 face-to-face interviews to a different group of parents in order to perform a recall task. Findings: This paper provides no evidence to suggest that energy labeling or traffic light labeling systems alone were successful in helping parents making healthy purchases of cereals for their children. Therefore, there is the need to promote supplementary policies to encourage the consumption of healthier food and help fight obesity.

Exploiting the cointrgration between vix and CDS in a credit market timing model

We investigate the cointegration between VIX and CDS indices, and the possibility of exploiting it in an existing credit market timing investment model. We find cointegration over most of the sample period and the leadership of VIX over the CDS in the price discovery process. We present two methods for including cointegration into the model. Both strategies improve the in-sample and out-of-sample model performances, even though out-of-sample results are weaker. We find that in-sample better performances are explained by a stronger cointegration, concluding that in the presence of cointegration our strategies can be profitable in an investment model that considers transaction costs.