Low temperature microwave emission from molecular clusters

We investigate the experimental detection of the electromagnetic radiation generated in the fast magnetization reversal in Mn12-acetate at low temperatures. In our experiments we used large single crystals and assemblies of several small single crystals of Mn12-acetate placed inside a cylindrical stainless steel waveguide in which an InSb hot electron device was also placed to detect the radiation. All this was set inside a SQUID magnetometer that allowed to change the magnetic field and measure the magnetic moment and the temperature of the sample as the InSb detected simultaneously the radiation emitted from the molecular magnets. Our data show a sequential process in which the fast inversion of the magnetic moment first occurs, then the radiation is detected by the InSb device, and finally the temperature of the sample increases during 15 ms to subsequently recover its original value in several hundreds of milliseconds.Comment: changed conten

Quantum Magnetic Deflagration in Mn12 Acetate

We report controlled ignition of magnetization reversal avalanches by surface acoustic waves in a single crystal of Mn12 acetate. Our data show that the speed of the avalanche exhibits maxima on the magnetic field at the tunneling resonances of Mn12. Combined with the evidence of magnetic deflagration in Mn12 acetate (Suzuki et al., cond-mat/0506569) this suggests a novel physical phenomenon: deflagration assisted by quantum tunneling.Comment: 4 figure

Au/CeO2 metallic monolith catalysts: Influence of the metallic substrate

Ceria-based gold catalysts were successfully deposited on ferritic stainless steel (Fecralloy) and aluminium monoliths. The prepared monolithic and reference powder catalysts were characterized by means of S BET, X-ray diffraction, glow discharge optical emission spectroscopy and scanning electron microscopy-energy dispersive X-ray analysis techniques and tested in the CO oxidation reaction. Characterization results put in evidence the diffusion of cations from the catalytic layer on the surface of the monoliths to the metallic oxide scale and inversely, from the oxide scale to the catalysts, thus altering the catalytic formulation and affecting the CO oxidation properties of the catalytic device. The extension and nature of the modifications produced depend on the nature of the catalysts and the metallic substrate, as well as the reaction conditions applied. These facts must be considered when gold catalysts are supported on metallic-structured devices. © 2013 The Author(s).Peer Reviewe

Método de extracción y detección de antígenos de Anisakis en alimentos destinados al consumo humano o animal

Método de extracción y detección de antígenos de Anisakis en alimentos destinados al consumo humano o animal. La presente invención se refiere a un método de extracción y detección de alérgenos de parásitos de pescado en muestras alimentarias para el consumo humano o animal. La extracción se basa en aplicar soluciones con baja fuerza iónica, homogeneización, sonicación y diferentes pH a diversos tipos de pescado ya sean frescos o tratados. La detección se basa en métodos inmunoquímicos mediante el uso de anticuerpos policlonales que permiten detectar proteínas antigénicas del parásito así como anticuerpos policlonales que permiten detectar el alérgeno Ani s 4, que por sus características físico-químicas resiste el tratamiento térmico del alimento. El método es sensible, ya que se puede detectar Ani s 4 en cantidades inferiores a 1ppm con tasas de recuperación mayores a un 65%. El método descrito es específico ya que no muestra reactividad cruzada con componentes de las distintas matrices ensayadas.Peer reviewedConsejo Superior de Investigaciones Científicas (España), Fundación para la Investigación Biomédica del Hospital Carlos IIIB1 Patente sin examen previ

Multivariate Radiological-Based Models for the Prediction of Future Knee Pain: Data from the OAI

In this work, the potential of X-ray based multivariate prognostic models to predict the onset of chronic knee pain is presented. Using X-rays quantitative image assessments of joint-space-width (JSW) and paired semiquantitative central X-ray scores from the Osteoarthritis Initiative (OAI), a case-control study is presented. The pain assessments of the right knee at the baseline and the 60-month visits were used to screen for case/control subjects. Scores were analyzed at the time of pain incidence (T-0), the year prior incidence (T-1), and two years before pain incidence (T-2). Multivariate models were created by a cross validated elastic-net regularized generalized linear models feature selection tool. Univariate differences between cases and controls were reported by AUC, C-statistics, and ODDs ratios. Univariate analysis indicated that the medial osteophytes were significantly more prevalent in cases than controls: C-stat 0.62, 0.62, and 0.61, at T-0, T-1, and T-2, respectively. The multivariate JSW models significantly predicted pain: AUC = 0.695, 0.623, and 0.620, at T-0, T-1, and T-2, respectively. Semiquantitative multivariate models predicted paint with C-stat = 0.671, 0.648, and 0.645 at T-0, T-1, and T-2, respectively. Multivariate models derived from plain X-ray radiography assessments may be used to predict subjects that are at risk of developing knee pain

Método de extracción y detección de antígenos de Anisakis en alimentos destinados al consumo humano o animal

Método de extracción y detección de antígenos de Anisakis en alimentos destinados al consumo humano o animal. La presente invención se refiere a un método de extracción y detección de alérgenos de parásitos de pescado en muestras alimentarias para el consumo humano o animal. La extracción se basa en aplicar soluciones con baja fuerza iónica, homogeneización, sonicación y diferentes pH a diversos tipos de pescado ya sean frescos o tratados. La detección se basa en métodos inmunoquímicos mediante el uso de anticuerpos policlonales que permiten detectar proteínas antigénicas del parásito así como anticuerpos policlonales que permiten detectar el alérgeno Ani s 4, que por sus características físico-químicas resiste el tratamiento térmico del alimento. El método es sensible, ya que se puede detectar Ani s 4 en cantidades inferiores a 1ppm con tasas de recuperación mayores a un 65%. El método descrito es específico ya que no muestra reactividad cruzada con componentes de las distintas matrices ensayadas.Consejo Superior de Investigaciones Científicas (España), Fundación para la Investigación Biomédica del Hospital Carlos IIIA1 Solicitud de patente con informe sobre el estado de la técnic

Digital filter implementation over FPGA platform with LINUX OS

AbstractThe embedded processors on FPGA's are a good tool to specific propose works. In this work we present how the FPGA is used to apply a Sobel filter to a set of images, also the step needed to set-up the entire system is described. An embedded processor, with a Linux distribution implemented is used to run a special compilation of C filter program, the filter is compared with the results obtained with a PC running the same filter, in the embedded system all the process runs in the FPGA and the exit file can be accessed by ftp or http server embedded into the Linux system

Feature Selection Using Genetic Algorithms for the Generation of a Recognition and Classification of Children Activities Model Using Environmental Sound

In the area of recognition and classification of children activities, numerous works have been proposed that make use of different data sources. In most of them, sensors embedded in children’s garments are used. In this work, the use of environmental sound data is proposed to generate a recognition and classification of children activities model through automatic learning techniques, optimized for application on mobile devices. Initially, the use of a genetic algorithm for a feature selection is presented, reducing the original size of the dataset used, an important aspect when working with the limited resources of a mobile device. For the evaluation of this process, five different classification methods are applied, k-nearest neighbor (k-NN), nearest centroid (NC), artificial neural networks (ANNs), random forest (RF), and recursive partitioning trees (Rpart). Finally, a comparison of the models obtained, based on the accuracy, is performed, in order to identify the classification method that presents the best performance in the development of a model that allows the identification of children activity based on audio signals. According to the results, the best performance is presented by the five-feature model developed through RF, obtaining an accuracy of 0.92, which allows to conclude that it is possible to automatically classify children activity based on a reduced set of features with significant accuracy.In the area of recognition and classification of children activities, numerous works have been proposed that make use of different data sources. In most of them, sensors embedded in children’s garments are used. In this work, the use of environmental sound data is proposed to generate a recognition and classification of children activities model through automatic learning techniques, optimized for application on mobile devices. Initially, the use of a genetic algorithm for a feature selection is presented, reducing the original size of the dataset used, an important aspect when working with the limited resources of a mobile device. For the evaluation of this process, five different classification methods are applied, k-nearest neighbor (k-NN), nearest centroid (NC), artificial neural networks (ANNs), random forest (RF), and recursive partitioning trees (Rpart). Finally, a comparison of the models obtained, based on the accuracy, is performed, in order to identify the classification method that presents the best performance in the development of a model that allows the identification of children activity based on audio signals. According to the results, the best performance is presented by the five-feature model developed through RF, obtaining an accuracy of 0.92, which allows to conclude that it is possible to automatically classify children activity based on a reduced set of features with significant accuracy