Comparison of fungal contamination between hospitals and companies food units

A descriptive study was developed to compare air and surfaces fungal contamination in ten hospitals’ food units and two food units from companies. Fifty air samples of 250 litres through impaction method were collected from hospitals’ food units and 41 swab samples from surfaces were also collected, using a 10 by 10 cm square stencil. Regarding the two companies, ten air samples and eight surface samples were collected. Air and surface samples were collected in food storage facilities, kitchen, food plating and canteen. Outdoor air was also collected since this is the place regarded as a reference. Simultaneously, temperature, relative humidity and meal numbers were registered. Concerning air from hospitals’ food units, 32 fungal species were identified, being the two most commonly isolated genera Penicillium sp.

Risk assessment of exposure to multiple mycotoxins in food

Moulds may produce a diversity of toxins such as aflatoxins, ochratoxins, trichothecenes, zearalenone, fumonisins and others. Although toxicological, environmental and epidemiological studies have addressed the problem of these toxins one by one, more than one mycotoxin are found usually in the same contaminated food. Risk assessment for humans potentially exposed to multimycotoxins suffers very much from the lack of adequate food consumption data. Furthermore, for a given mycotoxin, synergism and antagonism with other mycotoxins, found in the same food commodities, are not taken into account. Aflatoxin B1 and ochratoxin A belong to the most frequently occurring mycotoxins. This has repeatedly been demonstrated, however, normally, the risk resulting from their simultaneous occurrence is not considered. A descriptive study was developed to monitor air fungal contamination in one hospital food unit.

Air fungal contamination in ten hospitals’ food units from Lisbon

A descriptive study was developed to monitor air fungal contamination in ten food units from hospitals. Fifty air samples of 250 litres were collected through impaction method. Samples were collected in food storage facilities, kitchen, food plating, canteen and also, outside premises, since this is the place regarded as reference. Simultaneously, environmental parameters were also monitored, including temperature and relative humidity through the equipment Babouc, LSI Sistems and according to the International Standard ISO 7726.

Fast optimum-predictive control and capacitor voltage balancing strategy for bipolar back-to-back NPC converters in high-voltage direct current transmission systems

Multilevel power converters have been introduced as the solution for high-power high-voltage switching applications where they have well-known advantages. Recently, full back-to-back connected multilevel neutral point diode clamped converters (NPC converter) have been used inhigh-voltage direct current (HVDC) transmission systems. Bipolar-connected back-to-back NPC converters have advantages in long-distance HVDCtransmission systems over the full back-to-back connection, but greater difficulty to balance the dc capacitor voltage divider on both sending and receiving end NPC converters. This study shows that power flow control and dc capacitor voltage balancing are feasible using fast optimum-predictive-based controllers in HVDC systems using bipolar back-to-back-connected five-level NPC multilevel converters. For both converter sides, the control strategytakes in account active and reactive power, which establishes ac grid currents in both ends, and guarantees the balancing of dc bus capacitor voltages inboth NPC converters. Additionally, the semiconductor switching frequency is minimised to reduce switching losses. The performance and robustness of the new fast predictive control strategy, and its capability to solve the DC capacitor voltage balancing problem of bipolar-connected back-to-back NPCconverters are evaluated.

Vertex component analysis: a fast algorithm to extract endmembers spectra from hyperspectral data

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Vertex component analysis: a fast algorithm to unmix hyperspectral data

Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.

Fast growing fungi: a problem to be solved to achieve characterization of occupational exposure to fungi in cork industry

Chrysonilia sitophila is a common mould in cork industry and has been identified as a cause of IgE sensitization and occupational asthma. This fungal species have a fast growth rate that may inhibit others species’ growth causing underestimated data from characterization of occupational fungal exposure. Aiming to ascertain occupational exposure to fungi in cork industry, were analyzed papers from 2000 about the best air sampling method, to obtain quantification and identification of all airborne culturable fungi, besides the ones that have fast-growing rates. Impaction method don’t allows the collection of a representative air volume, because even with some media that restricts the growth of the colonies, in environments with higher fungal load, such as cork industry, the counting of the colonies is very difficult. Otherwise, impinger method permits the collection of a representative air volume, since we can make dilution of the collected volume. Besides culture methods that allows fungal identification trough macro- and micro-morphology, growth features, thermotolerance and ecological data, we can apply molecular biology with the impinger method, to detect the presence of non-viable particles and potential mycotoxin producers’ strains, and also to detect mycotoxins presence with ELISA or HPLC. Selection of the best air sampling method in each setting is crucial to achieve characterization of occupational exposure to fungi. Information about the prevalent fungal species in each setting and also the eventual fungal load it’s needed for a criterious selection.

Diethydithiocarbamate complexes with metals used as food suplements show diferente effects in cancer cells

Diethyldithiocarbamate (ditiocarb), a metabolite of the old anti-alcoholic drug disulfiram (Antabuse), forms proteasome-inhibiting metal complexes with copper or zinc that suppress cancer cells both in vitro and in vivo. The drug has been used in a clinical trial (NCT00742911) along with copper gluconate as a dietary supplement in patients with cancer spreading to the liver. In this study, we demonstrate the effect of synthetic complexes of disulfiram with four various metals (Mn, Fe, Cr and Cu) used as food supplements. These complexes may be spontaneously formed in the blood during the use of disulfiram with divalent metals and thus may suppress the growth of cancer in vivo. The cytotoxic effect of the compounds and the compounds' ability to inhibit the cellular proteasome were tested in the osteosarcoma cell line U2OS. After 48 h, copper and manganese complexes exhibited cytotoxic effect on the cell line, in sharp contrast to both iron and chromium complexes. (C) 2014 Faculty of Health and Social Studies, University of South Bohemia in Ceske Budejovice. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

25 kV bipolar solid-state Marx generator for industrial food applications

The preliminary results from a bipolar industrial solidstate based Marx generator, developed for the food industry, capable of delivering 25 kV/250 A positive and negative pulses with 12 kW average power, are presented and discussed. This modular topology uses only four controlled switches per cell, 27 cells in total that can be charged up to 1000V each, the two extra cells are used for droop compensation. The triggering signals for all the switches are generated by a FPGA. Considering that biomaterials are similar to resistive type loads, experimental results from this new bipolar 25 kV modulator into resistive loads are presented and discussed.

Reversible current power supply for fast-field cycling nuclear magnetic resonance equipment

The Fast Field-Cycling Nuclear Magnetic Resonance (FFC-NMR) is a technique used to study the molecular dynamics of different types of materials. The main elements of this equipment are a magnet and its power supply. The magnet used as reference in this work is basically a ferromagnetic core with two sets of coils and an air-gap where the materials' sample is placed. The power supply should supply the magnet being the magnet current controlled in order to perform cycles. One of the technical issues of this type of solution is the compensation of the non-linearities associated to the magnetic characteristic of the magnet and to parasitic magnetic fields. To overcome this problem, this paper describes and discusses a solution for the FFC-NMR power supply based on a four quadrant DC/DC converter.

Fast unsupervised technique for extraction of endmembers spectra from hyperspectral data

One of the most challenging task underlying many hyperspectral imagery applications is the linear unmixing. The key to linear unmixing is to find the set of reference substances, also called endmembers, that are representative of a given scene. This paper presents the vertex component analysis (VCA) a new method to unmix linear mixtures of hyperspectral sources. The algorithm is unsupervised and exploits a simple geometric fact: endmembers are vertices of a simplex. The algorithm complexity, measured in floating points operations, is O (n), where n is the sample size. The effectiveness of the proposed scheme is illustrated using simulated data.

Fast unsupervised extraction of endmembers spectra from hyperspectral data

Linear unmixing decomposes an hyperspectral image into a collection of re ectance spectra, called endmember signatures, and a set corresponding abundance fractions from the respective spatial coverage. This paper introduces vertex component analysis, an unsupervised algorithm to unmix linear mixtures of hyperpsectral data. VCA exploits the fact that endmembers occupy vertices of a simplex, and assumes the presence of pure pixels in data. VCA performance is illustrated using simulated and real data. VCA competes with state-of-the-art methods with much lower computational complexity.