Automatic mass spectra recognition for Ultra High Vacuum systems using multilabel classification

Abstract In Ultra High-Vacuum (UHV) systems it is common to find a mixture of many gases originating from surface outgassing, leaks and permeation that contaminate vacuum chambers and cause issues to reach ultimate pressures. The identification of these contaminants is, in general, done manually by trained technicians from the analysis of mass spectra. This task is time consuming and can lead to misinterpretation or partial understanding of issues. The challenge resides in the rapid identification of these contaminants by using some automatic gas identification technique. This paper explores the automatic and simultaneous identification of 80 molecules, including some of the most commonly p…

Comparative Study of Several Machine Learning Algorithms for Classification of Unifloral Honeys

Unifloral honeys are highly demanded by honey consumers, especially in Europe. To ensure that a honey belongs to a very appreciated botanical class, the classical methodology is palynological analysis to identify and count pollen grains. Highly trained personnel are needed to perform this task, which complicates the characterization of honey botanical origins. Organoleptic assessment of honey by expert personnel helps to confirm such classification. In this study, the ability of different machine learning (ML) algorithms to correctly classify seven types of Spanish honeys of single botanical origins (rosemary, citrus, lavender, sunflower, eucalyptus, heather and forest honeydew) was investi…

Changes in ochratoxin A and type B trichothecenes contained in wheat flour during dough fermentation and bread baking processes

Ochratoxin A (OTA) and type B trichothecenes are mycotoxins that occur frequently in cereals and thus can be found in cereal by-products such as bread. The aim of this work was to study the variation of the levels of OTA, deoxynivalenol (DON), 3-acetyldeoxynivalenol (3-ADON) and nivalenol (NIV) during the bread-making process. This was done by using wheat flour spiked with different levels of toxins. Mycotoxin levels were controlled after fermentation of the dough with yeasts (Saccharomyces cerevisiae) and after further baking at different temperature-time combinations. Analysis of variance (ANOVA) of the results showed a significant reduction in OTA level (p < 0.05) during fermentation of …

HemoKinect: A Microsoft Kinect V2 Based Exergaming Software to Supervise Physical Exercise of Patients with Hemophilia

Patients with hemophilia need to strictly follow exercise routines to minimize their risk of suffering bleeding in joints, known as hemarthrosis. This paper introduces and validates a new exergaming software tool called HemoKinect that intends to keep track of exercises using Microsoft Kinect V2&rsquo

Approaching sales forecasting using recurrent neural networks and transformers

Accurate and fast demand forecast is one of the hot topics in supply chain for enabling the precise execution of the corresponding downstream processes (inbound and outbound planning, inventory placement, network planning, etc). We develop three alternatives to tackle the problem of forecasting the customer sales at day/store/item level using deep learning techniques and the Corporaci\'on Favorita data set, published as part of a Kaggle competition. Our empirical results show how good performance can be achieved by using a simple sequence to sequence architecture with minimal data preprocessing effort. Additionally, we describe a training trick for making the model more time independent and…

Study on mycotoxin contamination of maize kernels in Spain

Abstract Mycotoxins are secondary metabolites produced mainly by fungal species belonging to the genera Fusarium, Aspergillus and Penicillium and belong to the most relevant contaminants of food and feed. Cereals are the main source of mycotoxins in the diet. The most prominent mycotoxins are aflatoxins B1, B2, G1 and G2 (AFB1, AFB2, AFG1 and AFG2), fumonisins B1 and B2 (FB1 and FB2), ochratoxin A (OTA), zearalenone (ZEA), deoxynivalenol (DON), 3- and 15-acetyl-deoxynivalenol (3- and 15-ADON), and T-2 and HT-2 toxins. Maximum levels allowed in food are very different depending on mycotoxin and food type, consumer susceptibility and current legislation in each country. Among cereals, maize a…

Predictive assessment of ochratoxin A accumulation in grape juice based-medium by Aspergillus carbonarius using neural networks

Aims: To study the ability of multi-layer perceptron artificial neural networks (MLP-ANN) and radial-basis function networks (RBFNs) to predict ochratoxin A (OTA) concentration over time in grape-based cultures of Aspergillus carbonarius under different conditions of temperature, water activity (a(w)) and sub-inhibitory doses of the fungicide carbendazim. Methods and Results: A strain of A. carbonarius was cultured in a red grape juice-based medium. The input variables to the network were temperature (20-28 degrees C), a(w) (0 center dot 94-0 center dot 98), carbendazim level (0-450 ng ml(-1)) and time (3-15 days after the lag phase). The output of the ANNs was OTA level determined by liqui…

Potential use of machine learning methods in assessment of Fusarium culmorum and Fusariumproliferatum growth and mycotoxin production in treatments with antifungal agents.

Abstract The use of Fusarium-controlling fungicides is necessary to limit crop loss. Little is known about the effect of commercial antifungal formulations at sub-lethal doses, and their interaction with abiotic factors, on Fusarium culmorum and F. proliferatum development and on zearalenone and fumonisin biosynthesis, respectively. In the present study different treatments based on sulfur, trifloxystrobin and demethylation inhibitor fungicides (cyproconazole, tebuconazole and prothioconazole) under different environmental conditions, in Maize Extract Medium (MEM), are assayed in vitro. Then, several machine learning methods (neural networks, random forest and extreme gradient boosted trees…

Position sensitive scintillator based detector improvements by means of an integrated front-end

PESIC is an integrated front-end for multianode photomultiplier based nuclear imaging devices. Its architecture has been designed to improve position sensitive detectors behavior by equalizing its response over its whole area. Its preamplying stage introduces two main benefits: digitally programmable gain adjustment for every photomultiplier output, and isolation from other front-end electronics by means of current buffers. This last feature allows to use different types of photomultipliers and optimizes front-end deadtime, reducing impact position dependent output delay. PESIC also includes an indirect measurement of the depth of interaction of the gamma ray inside the scintillator crystal…

An overview of ochratoxin A in beer and wine.

Ochratoxin A (OTA) is a mycotoxin produced mainly by several fungal species of the genera Aspergillus and Penicillium. This mycotoxin has been shown to be nephrotoxic, hepatotoxic, teratogenic and carcinogenic to animals and has been classified as a possible carcinogen to humans. OTA occurs in a variety of foods, including beer and wine. Reports on OTA occurrence in beer indicate that this is a worldwide problem due to the widespread consumption of this beverage. At present, the European Union (EU) has not set a maximum allowable limit (MAL) for this mycotoxin in beer, although there is a limit in barley and malt. Studies carried out in different countries agree in the high proportion of sa…

Multiprocessor SoC Implementation of Neural Network Training on FPGA

Software implementations of artificial neural networks (ANNs) and their training on a sequential processor are inefficient because they do not take advantage of parallelism. ASIC and FPGA implementations employ specific hardware structures to exploit parallelism in order to improve processing speed; however, optimizing resource usage requires the use of fixed-point arithmetic, thereby losing precision, and the final system is restricted to a particular network topology. This paper presents a mixed approach based on a multiprocessor system-on-chip (SoC) on a FPGA. The use of software-driven embedded microprocessors with custom floating-point extensions for ANN related functions allows for gr…

Analysis of computer user behavior, security incidents and fraud using Self-Organizing Maps

Abstract This paper addresses several topics of great interest in computer security in recent years: computer users’ behavior, security incidents and fraud exposure on the Internet, due to their high economic and social cost. Traditional research has been based mainly on gathering information about security incidents and fraud through surveys. The novelty of the present study is given by the use of Self-Organizing Maps (SOMs), a visual data mining technique. SOMs are applied to two data sets acquired using two different methodologies for collecting data about computer security. First, a traditional online survey about fraud exposure, security and user behavior was used. Second, in addition …

Antifungal effect of engineered silver nanoparticles on phytopathogenic and toxigenic Fusarium spp. and their impact on mycotoxin accumulation.

Abstract Cereal grains are essential ingredient in food, feed and industrial processing. One of the major causes of cereal spoilage and mycotoxin contamination is the presence of toxigenic Fusarium spp. Nanoparticles have immense applications in agriculture, nutrition, medicine or health but their possible impact on the management of toxigenic fungi and mycotoxins have been very little explored. In this report, the potential of silver nanoparticles (AgNPs) (size 14–100 nm) against the major toxigenic Fusarium spp. affecting crops and their effect on mycotoxin accumulation is evaluated for the first time. The studied Fusarium spp. (and associated mycotoxins) were F. graminearum and F. culmor…

Survey of the mycobiota of Spanish malting barley and evaluation of the mycotoxin producing potential of species of Alternaria, Aspergillus and Fusarium

The present work deals with the toxigenic mycobiota occurring in Spanish malting barley and the capability for producing mycotoxins by several important toxigenic fungi. One hundred and eighty seven samples of malting barley were gathered from Spanish breweries before processing. One hundred and fifty kernels per sample were surface-sanitized with a 2% sodium hypochlorite solution and incubated on three culture media. The most abundant fungi were species of Alternaria, Aspergillus, Penicillium and Fusarium, which were present in 93%, 82.3%, 57.8% and 27.8% of the samples, respectively. To evaluate their mycotoxin producing potential a number of isolates belonging to each genus, except Penic…

SoC-Based Implementation of the Backpropagation Algorithm for MLP

The backpropagation algorithm used for the training of multilayer perceptrons (MLPs) has a high degree of parallelism and is therefore well-suited for hardware implementation on an ASIC or FPGA. However, most implementations are lacking in generality of application, either by limiting the range of trainable network topologies or by resorting to fixed-point arithmetic to increase processing speed. We propose a parallel backpropagation implementation on a multiprocessor system-on-chip (SoC) with a large number of independent floating-point processing units, controlled by software running on embedded processors in order to allow flexibility in the selection of the network topology to be traine…

Lactic acid bacteria: a potential tool to reduce ochratoxin A in wine

E. M. Mateo, A. Medina, F. Mateo, F.M. Valle Algarra, R. Mateo, and M. Jimenez 1 Dpto. de Microbiologia i Ecologia. Universitat de Valencia. Dr. Moliner 50, E-46100, Burjassot, Valencia, Spain. 2 Dpto. de Quimica Analitica. Universitat de Valencia. Dr. Moliner 50, E-46100, Burjassot, Valencia, Spain. 3 Dpto. de Ingenieria Electronica, Universitat Politecnica de Valencia, Camino de Vera, 14. E-46022, Valencia, Spain.

Ochratoxin A removal in synthetic media by living and heat-inactivated cells of Oenococcus oeni isolated from wines

The capacity of Oenococcus oeni to eliminate ochratoxin A (OTA) from synthetic media in different conditions was studied. Ten tested O. oeni strains removed OTA from the medium but with significant differences depending on the strain, incubation period, and initial OTA level in the medium. Mycotoxin reductions higher than 60% were recorded in 14-day cultures spiked with 2 mu g OTA/l. Toxin removal was independent of bacterial viability and culture medium composition. This is the first study carried out to study OTA removal dynamics by living and heat-inactivated cells of O. oeni. The results aim that this bacterium may be a very useful tool to control OTA in food and beverages. (C) 2009 Els…

Multilayer perceptron neural networks and radial-basis function networks as tools to forecast accumulation of deoxynivalenol in barley seeds contaminated with Fusarium culmorum

The capacity of multi-layer perceptron artificial neural networks (MLP-ANN) and radial-basis function networks (RBFNs) to predict deoxynivalenol (DON) accumulation in barley seeds contaminated with Fusarium culmorum under different conditions has been assessed. Temperature (20-28 °C), water activity (0.94-0.98), inoculum size (7-15 mm diameter), and time were the inputs while DON concentration was the output. The dataset was used to train, validate and test many ANNs. Minimizing the mean-square error (MSE) was used to choose the optimal network. Single-layer perceptrons with low number of hidden nodes proved better than double-layer perceptrons, but the performance depended on the training …

Maximum likelihood positioning for gamma-ray imaging detectors with depth of interaction measurement

Abstract The center of gravity algorithm leads to strong artifacts for gamma-ray imaging detectors that are based on monolithic scintillation crystals and position sensitive photo-detectors. This is a consequence of using the centroids as position estimates. The fact that charge division circuits can also be used to compute the standard deviation of the scintillation light distribution opens a way out of this drawback. We studied the feasibility of maximum likelihood estimation for computing the true gamma-ray photo-conversion position from the centroids and the standard deviation of the light distribution. The method was evaluated on a test detector that consists of the position sensitive …

Optimal Pruned K-Nearest Neighbors: OP-KNN Application to Financial Modeling

The paper proposes a methodology called OP-KNN, which builds a one hidden-layer feed forward neural network, using nearest neighbors neurons with extremely small computational time. The main strategy is to select the most relevant variables beforehand, then to build the model using KNN kernels. Multi-response sparse regression (MRSR) is used as the second step in order to rank each k-th nearest neighbor and finally as a third step leave-one-out estimation is used to select the number of neighbors and to estimate the generalization performances. This new methodology is tested on a toy example and is applied to financial modeling.

Machine learning approach for predicting Fusarium culmorum and F. proliferatum growth and mycotoxin production in treatments with ethylene-vinyl alcohol copolymer films containing pure components of essential oils

Fusarium culmorum and F. proliferatum can grow and produce, respectively, zearalenone (ZEA) and fumonisins (FUM) in different points of the food chain. Application of antifungal chemicals to control these fungi and mycotoxins increases the risk of toxic residues in foods and feeds, and induces fungal resistances. In this study, a new and multidisciplinary approach based on the use of bioactive ethylene-vinyl alcohol copolymer (EVOH) films containing pure components of essential oils (EOCs) and machine learning (ML) methods is evaluated. Bioactive EVOH-EOC films were made incorporating cinnamaldehyde (CINHO), citral (CIT), isoeugenol (IEG) or linalool (LIN). Several ML methods (neural networ…

Ciberseguridad : el reto del siglo XXI

El siglo XXI es el siglo del dato, su análisis y de la conectividad; en definitiva, el siglo de la información en tiempo real y disponible para cualquiera en cualquier lugar del mundo. Dichos datos están impactando en todos los ámbitos de la sociedad y de la economía de tal forma que no se entiende ningún sector productivo ni ninguna relación social sin dato; todos tenemos algún lugar en las redes sociales desde donde intercambiamos experiencias personales o profesionales. Si a este hecho se le suma el auge de la Inteligencia Artificial, se tiene un siglo en el que los avances tecnológicos van a ser totalmente disruptivos para todos nosotros.

Influence of nitrogen and carbon sources on the production of ochratoxin A by ochratoxigenic strains of Aspergillus spp. isolated from grapes.

This work studies the influence of nitrogen and carbon source on ochratoxin A production by three Aspergillus isolates A. ochraceus (Aso2), A. carbonarius (Ac25) and A. tubingensis (Bo66), all isolated from grapes. A basal medium (0.01 g/l FeSO4.7H2O, 0.5 g/l MgSO4.7H2O, 0.5 g/l Na2HPO4.2H2O, 1.0 g/l KCl) was prepared. This medium was supplemented with different nitrogen sources, both inorganic [(NH4)3PO(4), 0.3 g/l plus NH4NO3, 0.2 g/l] and organic (histidine, proline, arginine, phenylalanine, tryptophan or tyrosine) at two concentrations (0.05 g/l or 0.3 g/l), and different carbon sources (sucrose, glucose, maltose, arabinose or fructose) at three concentrations (10 g/l, 50 g/l or 150 g/l…

Machine learning methods to forecast temperature in buildings

Efficient management of energy in buildings saves a very important amount of resources (both economic and technological). As a consequence, there is a very active research in this field. One of the keys of energy management is the prediction of the variables that directly affect building energy consumption and personal comfort. Among these variables, one can highlight the temperature in each room of a building. In this work we apply different machine learning techniques along with other classical ones for predicting the temperatures in different rooms. The obtained results demonstrate the validity of these techniques for predicting temperatures and, therefore, for the establishment of optim…

New method for determination of ochratoxin A in beer using zinc acetate and solid-phase extraction silica cartridges

Abstract A new method for the determination of ochratoxin A (OTA) in beer has been developed. The new method has been compared with a reference method currently accepted as AOAC official first action. The limits of detection and quantification of the proposed method were 0.0008 and 0.0025 ng/ml, respectively, while they were 0.0025 and 0.0075 ng/ml, respectively, in the AOAC method used as reference. The recovery levels in the 0.025–0.40 ng OTA/ml spiking range for the proposed and the reference methods were 80.6–87.6% and 78.2–83.8%, respectively. The relative standard deviations of recoveries were 2.6–7.5% for the proposed method and 0.7–6.1% for the reference method. Passing and Bablok r…

Potential impact of engineered silver nanoparticles in the control of aflatoxins, ochratoxin A and the main aflatoxigenic and ochratoxigenic species affecting foods

Abstract The potential use of nanotechnology in the control of toxigenic fungi and mycotoxin production has been little explored. In this report, engineered silver nanoparticles (AgNPs) were synthesized and characterized by single particle Inductively Coupled Plasma Mass Spectrometry. Then, their effectiveness in the control of the growth of the main aflatoxigenic and ochratoxigenic species affecting foods and aflatoxins (AFs) and ochratoxin A (OTA) production was studied. The target species and their associated mycotoxins were Aspergillus flavus (AFB1 and AFB2), A. parasiticus (AFB1, AFB2, AFG1 and AFG2), A. carbonarius, A. niger, A. ochraceus, A. steynii, A. westerdijkiae and Penicillium …

Analysis of the Pre and Post-COVID-19 Lockdown Use of Smartphone Apps in Spain

The global pandemic of COVID-19 has changed our daily habits and has undoubtedly affected our smartphone usage time. This paper attempts to characterize the changes in the time of use of smartphones and their applications between the pre-lockdown and post-lockdown periods in Spain, during the first COVID-19 confinement in 2020. This study analyzes data from 1940 participants, which was obtained both from a survey and from a tracking application installed on their smartphones. We propose manifold learning techniques such as clustering, to assess, both in a quantitative and in a qualitative way, the behavioral and social effects and implications of confinement in the Spanish population. We al…

Neural network models for prediction of trichothecene content in wheat

Fusarium graminearum is a mould that causes serious diseases in cereals worldwide and that synthesises mycotoxins such as deoxynivalenol (DON), which can seriously affect human and animal health. Predicting the level of mycotoxin accumulation in food is very difficult, because of the complexity of the influencing parameters. In this work, we have studied the possibility of using artificial neural networks (NN) to predict DON level attained in F. graminearum wheat cultures taking as inputs the fungal contamination level of the cereal, the water activity as a measure of the available water for fungal growth in the cereal, the temperature and time. DON analysis was performed by gas chromatogr…

Potential Health Risk Associated with Mycotoxins in Oat Grains Consumed in Spain

Spain is a relevant producer of oats (Avena sativa), but to date there has been no study on the occurrence/co-occurrence of mycotoxins in oats marketed in Spain. The present study is addressed to overcome this lack of knowledge. One hundred oat kernel samples were acquired across different Spanish geographic regions during the years 2015–2019 and analyzed for mycotoxin content using an ultra-high performance liquid chromatography electrospray ionization tandem mass spectrometry (UPLC–ESI–MS/MS) method and matrix-matched calibration. The focus was on the regulated mycotoxins although other relevant mycotoxins were considered. The percentage of incidence (levels ≥ limit of detection), mean an…

Forecasting Techniques for Energy Optimization in Buildings

Assessment of Kinect V2 for elbow range of motion estimation in people with haemophilia using an angle correction model

Introduction The joint range of motion (ROM) is an important clinical parameter used to assess the loss of functionality resulting from joint bleedings in people with haemophilia. These episodes require a close follow-up and, to decrease patients' hospital dependence, telemedicine tools are needed. Therefore, this study is aimed to analyse the validity of the Microsoft Kinect V2 sensor with corrected angle measurement to be used in the monitoring of elbow ROM in people with haemophilia. Methods A convenience sample of 10 healthy controls (CG) and 10 patients with haemophilia with elbow arthropathy (HG) participated in this study. Full ROM of elbow joints was measured in the frontal view wit…

Comparison of different analytical processes for patulin determination in apple juice

F. M. Valle-Algarra, R. Mateo, A. Medina, F. Mateo, E. M. Mateo, E. Sanchis Blanco, J.V. Gimeno-Adelantado, J. Peris-Vicente and M. Jimenez 1 Dpto. de Quimica Analitica, Facultad de Quimica, Universidad de Valencia, Dr. Moliner 50, E-46100 Burjassot, Valencia, Spain 2 Dpto. de Microbiologia y Ecologia, Facultad de Biologia, Universidad de Valencia, Dr. Moliner 50, E-46100 Burjassot, Valencia, Spain 3 Dpto. de Ingenieria Electronica, Universidad Politecnica de Valencia, Camino de Vera 14, E-46022, Valencia, Spain

Learning Structures in Earth Observation Data with Gaussian Processes

Gaussian Processes (GPs) has experienced tremendous success in geoscience in general and for bio-geophysical parameter retrieval in the last years. GPs constitute a solid Bayesian framework to formulate many function approximation problems consistently. This paper reviews the main theoretical GP developments in the field. We review new algorithms that respect the signal and noise characteristics, that provide feature rankings automatically, and that allow applicability of associated uncertainty intervals to transport GP models in space and time. All these developments are illustrated in the field of geoscience and remote sensing at a local and global scales through a set of illustrative exa…

Comparative Analysis of Machine Learning Methods to Predict Growth of F. sporotrichioides and Production of T-2 and HT-2 Toxins in Treatments with Ethylene-Vinyl Alcohol Films Containing Pure Components of Essential Oils

The efficacy of ethylene-vinyl alcohol copolymer films (EVOH) incorporating the essential oil components cinnamaldehyde (CINHO), citral (CIT), isoeugenol (IEG), or linalool (LIN) to control growth rate (GR) and production of T-2 and HT-2 toxins by Fusarium sporotrichioides cultured on oat grains under different temperature (28, 20, and 15 °C) and water activity (aw) (0.99 and 0.96) regimes was assayed. GR in controls/treatments usually increased with increasing temperature, regardless of aw, but no significant differences concerning aw were found. Toxin production decreased with increasing temperature. The effectiveness of films to control fungal GR and toxin production was as follows: EVOH…