Polytechnic Institute of Porto

About: Polytechnic Institute of Porto is a education organization based out in Porto, Portugal. It is known for research contribution in the topics: Computer science & Wireless sensor network. The organization has 1209 authors who have published 2422 publications receiving 35130 citations. The organization is also known as: Porto Polytechnic.

Microalgae for biodiesel production and other applications: A review

Abstract: Sustainable production of renewable energy is being hotly debated globally since it is increasingly understood that first generation biofuels, primarily produced from food crops and mostly oil seeds are limited in their ability to achieve targets for biofuel production, climate change mitigation and economic growth. These concerns have increased the interest in developing second generation biofuels produced from non-food feedstocks such as microalgae, which potentially offer greatest opportunities in the longer term. This paper reviews the current status of microalgae use for biodiesel production, including their cultivation, harvesting, and processing. The microalgae species most used for biodiesel production are presented and their main advantages described in comparison with other available biodiesel feedstocks. The various aspects associated with the design of microalgae production units are described, giving an overview of the current state of development of algae cultivation systems (photo-bioreactors and open ponds). Other potential applications and products from microalgae are also presented such as for biological sequestration of CO 2 , wastewater treatment, in human health, as food additive, and for aquaculture.

Biochemistry of adipose tissue: an endocrine organ

Abstract: Adipose tissue is no longer considered to be an inert tissue that stores fat. This tissue is capable of expanding to accommodate increased lipids through hypertrophy of existing adipocytes and by initiating differentiation of pre-adipocytes. Adipose tissue metabolism exerts an impact on whole-body metabolism. As an endocrine organ, adipose tissue is responsible for the synthesis and secretion of several hormones. These are active in a range of processes, such as control of nutritional intake (leptin, angiotensin), control of sensitivity to insulin and inflammatory process mediators (tumor necrosis factor α (TNF-α), interleukin-6 (IL-6), resistin, visfatin, adiponectin, among others) and pathways (plasminogen activator inhibitor 1 (PAI-1) and acylation stimulating protein (ASP) for example). This paper reviews some of the biochemical and metabolic aspects of adipose tissue and its relationship to inflammatory disease and insulin resistance.

Radio link quality estimation in wireless sensor networks: A survey

Abstract: Radio link quality estimation in Wireless Sensor Networks (WSNs) has a fundamental impact on the network performance and also affects the design of higher-layer protocols. Therefore, for about a decade, it has been attracting a vast array of research works. Reported works on link quality estimation are typically based on different assumptions, consider different scenarios, and provide radically different (and sometimes contradictory) results. This article provides a comprehensive survey on related literature, covering the characteristics of low-power links, the fundamental concepts of link quality estimation in WSNs, a taxonomy of existing link quality estimators, and their performance analysis. To the best of our knowledge, this is the first survey tackling in detail link quality estimation in WSNs. We believe our efforts will serve as a reference to orient researchers and system designers in this area.

An electric energy consumer characterization framework based on data mining techniques

Abstract: This paper presents an electricity consumer characterization framework based on a knowledge discovery in databases (KDD) procedure, supported by data mining (DM) techniques, applied on the different stages of the process. The core of this framework is a data mining model based on a combination of unsupervised and supervised learning techniques. Two main modules compose this framework: the load profiling module and the classification module. The load profiling module creates a set of consumer classes using a clustering operation and the representative load profiles for each class. The classification module uses this knowledge to build a classification model able to assign different consumers to the existing classes. The quality of this framework is illustrated with a case study concerning a real database of LV consumers from the Portuguese distribution company.