University of Madeira

About: University of Madeira is a education organization based out in Funchal, Portugal. It is known for research contribution in the topics: Population & Dendrimer. The organization has 1014 authors who have published 2759 publications receiving 59457 citations.

Polylactic acid/nano chitosan composite fibers and their morphological, physical characterization for the removal of cadmium(II) from water

Abstract: International and Interuniversity Centre for Nanoscience and Nanotechnology, Mahatma Gandhi University, Kottayam, India Department of Chemistry, Mar Thoma College, Tiruvalla, India Department of Chemistry, C.M.S. College, Kottayam, India Food and Bioproduct Sciences, University of Saskatchewan, Saskatoon, Saskatchewan, Canada Faculty of Exact Science and Engineering, University of Madeira, Funchal, Portugal Materials and Surface Science Institute, University of Limerick, Limerick, Ireland School of Pure and Applied Physics, Mahatma Gandhi University, Kottayam, India School of Chemical Sciences, Mahatma Gandhi University, Kottayam, India Department of Chemistry, Bishop Moore College, Kallumala, India

Forensic analysis of dog (Canis lupus familiaris) mitochondrial DNA sequences: an inter-laboratory study of the GEP-ISFG working group.

Abstract: A voluntary collaborative exercise aiming at the mitochondrial analysis of canine biological samples was carried out in 2006-2008 by the Non-Human Forensic Genetics Commission of the Spanish and Portuguese Working Group (GEP) of the International Society for Forensic Genetics (ISFG). The participating laboratories were asked to sequence two dog samples (one bloodstain and one hair sample) for the mitochondrial D-loop region comprised between positions 15,372 and 16,083 using suggested primers and PCR conditions, and to compare their results against a reference sequence. Twenty-one participating laboratories reported a total of 67.5% concordant results, 15% non-concordant results, and 17.5% no results. The hair sample analysis presented more difficulty to the participants than the bloodstain analysis, with a high percentage (29%) failing to obtain a result. The high level of participation showed the interest of the community in the analysis of dog forensic samples but the results reveal that crucial methodological issues need to be addressed and further training is required in order to respond proficiently to the demands of forensic casework.

PhysioLab - a multivariate physiological computing toolbox for ECG, EMG and EDA signals: a case of study of cardiorespiratory fitness assessment in the elderly population

Abstract: The exponential increase of wearable health-tracking technologies offers new possibilities but also poses new challenges in signal processing to enable fitness monitoring through multimodal physiological recordings. Although there are several software tools used for post-processing in physiological computing applications, limitations in the analysis, incorporating signals from multiple sources, integrating contextual information and providing information visualization tools prevent a widespread use of this technology. To address these issues, we introduce PhysioLab, a multimodal processing Matlab tool for the data analysis of Electromyography (EMG), Electrocardiography (ECG) and Electrodermal Activity (EDA). The software is intended to facilitate the processing and comprehension of multimodal physiological data with the aim of assessing fitness in several domains. A unique feature of PhysioLab is that is informed by normative data grouped by age and sex, allowing contextualization of data based on users’ demographics. Besides signal processing, PhysioLab includes a novel approach to multivariable data visualization with the aim of simplifying interpretation by non-experts users. The system computes a set of ECG features based on heart rate variability analysis, EMG parameters to quantify force and fatigue levels, and galvanic skin level/responses from EDA signals. Furthermore, PhysioLab provides compatibility with data from multiple low-cost wearable sensors. We conducted an experiment with 17 community-dwelling older adults (64.5 ± 6.4) to assess the feasibility of the tool in characterizing cardiorespiratory profiles during physical activity. Correlation analyses and regression models showed significant interactions between physiology and fitness evaluations. Our results suggest novel ways that physiological parameters could be effectively used to complement traditional fitness assessment.