Designation of natural monuments by the local administration: the example of Viana do Castelo municipality and its engagement with geoconservation (NW Portugal)

"First online: 11 April 2016"

Evaluation of zearalenone in vitro removal by Saccharomyces cerevisiae strains isolated from bovine forage

Zearalenone (ZEN) is a mycotoxin that has relatively low acute toxicity. However, it is a potent oestrogen, interfering with the reproductive tract of animals. Among other effects, ZEN decreases animals fertility, and induces fibrosis in the uterus, breast cancer and endometrial carcinoma (Zinedine et al., 2007). Anti-mycotoxin additives (AMA) are defined as a group of products that, when added to animal feed, are capable of adsorbing, inactivating, or neutralizing mycotoxins in the gastrointestinal tract of animals. One example of these products are adsorbents based on yeast cell walls, a safe and beneficial animal feed additive (Abreu et al., 2008). When based on active cells, yeast based products also act as a probiotic, contributing to improve the general animal health because it stimulates their immune system and promotes the integrity of intestinal mucosa (Albino et al., 2006). Strains of Saccharomyces cerevisiae isolated from silage were tested for their ZEN removal capability. Their effect on - and b-zearalenol (-ZOL and b-ZOL) was also tested. Strains were grown on YPD separately supplemented with ZEN, -ZOL and b-ZOL, and their elimination from culture media was quantified over time by HPLC-FL.

Lard as a suitable and cheap substrate for microbial lipids production by Yarrowia lipolytica

[Excerpt] Current agricultural and industrial practices have led to the generation of large amounts of various low-value or negative cost crude wastes, which are difficult and economically notattractive to treat and valorize. One important example of waste generation is animal fat, commonly found in tanning process and slaughterhouses. These wastes, in which the lipids are often the main and most problematic components, are not currently used effectively and there are almost no application methods to recover the respective value. (...)

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.