Detection of microbial contamination in potable water by Nanowire technology

It is well known that the lack of control and sanitation of water in developing countries has cause very significant epidemiological events. In the last decades the situation of water supplies and sanitation has improve all over the world. Despite of it, in the European Union there are a considerable number of confirmed cases of water-borne infections even though the restrictive law. Electronic Noses (ENs) has shown to be a very effective and fast tool for monitoring microbiological spoilage and quality control. The aim of this study was test the ability of a novel EN for the detection of bacterial presence in potable water in cooperation with analytical (pH) and optical (photometer) techniques. The achieved results notably advocate the use of EN in industry laboratories as a very important tool in water quality control

A practical algorithmic approach to mature aggressive B cell lymphoma diagnosis in the double/triple hit era. Selecting cases, matching clinical benefit. A position paper from the Italian Group of Haematopathology (G.I.E.)

An accurate diagnosis of clinically distinct subgroups of aggressive mature B cell lymphomas is crucial for the choice of proper treatment. Presently, precise recognition of these disorders relies on the combination of morphological, immunophenotypical, and cytogenetic/molecular features. The diagnostic workup in such situations implies the application of costly and time-consuming analyses, which are not always required, since an intensified treatment option is reasonably reserved to fit patients. The Italian Group of Haematopathology proposes herein a practical algorithm for the diagnosis of aggressive mature B cell lymphomas based on a stepwise approach, aimed to select cases deserving molecular analysis, in order to optimize time and resources still assuring the optimal management for any patient

Computer-aided design of polymeric materials: Computational study for characterization of databases for prediction of mechanical properties under polydispersity

In Polymer Informatics, quantitative structure-property relationship (QSPR) modeling is an emerging approach for predicting relevant properties of polymers in the context of computer-aided design of industrial materials. Nevertheless, most QSPR models available in the literature use simplistic computational representations of polymers based on their structural repetitive unit. The aim of this work is to evaluate the effect of this simplification and to analyze new strategies to achieve alternative characterizations that capture the phenomenon of polydispersity. In particular, the experiments reported in this work are focused on three mechanical properties derived from the tensile test. The reported results revealed the disadvantages of using these simplified representations. Besides, we contributed with alternative representations for the databases of polymer molecular descriptors that achieved more realistic and accurate QSPR models.Fil: Cravero, Fiorella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Schustik, Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Martínez, María Jimena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Barranco, Carlos D.. Universidad Pablo de Olavide; EspañaFil: Diaz, Monica Fatima. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Química; ArgentinaFil: Ponzoni, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentin

Online ECG-based Features for Cognitive Load Assessment

This study was concerned with the development and testing of online cognitive-load monitoring methods by means of a working-memory experiment using electrocardiogram (ECG) analyses for future applications in mixed-initiative human-machine interaction (HMI). To this end, we first identified potentially reliable cognitive-workload-related cardiac metrics and algorithms for online processing. We then compared our online results to those conventionally obtained with state-of-the-art offline methods. Finally, we evaluated the possibility of classifying low versus high working-memory load using different classification algorithms. Our results show that both offline and online methods reliably estimate the workload associated with a multi-level working-memory task at the group level, whether it is with the heart rhythm or the heart rate variation (standard deviation of the RR interval). Moreover, we found significant working-memory load classification accuracy using both two-dimensional linear discriminant analyses (LDA) or a support vector machine (SVM). We hence argue that our online algorithm is reliable enough to provide online electrocardiographic metrics as a tool for real-life workload evaluation and can be a valuable feature for mixed-initiative systems

Monitoring environmental catastrophe area through change detection techniques

The use of satellite images has been very effective for monitoring the dynamics of the land use and occupation over time. For this purpose , the change detection techniques have been strong allies. These techniques have multiple complexities depending on the objective to be achieved. This study aims to evaluate the technique for land use and land cover changing detection in areas affected by the environmental disaster of November 2008 in the region of Morro do Baú, Santa Catarina, Brazil. A total of 04 (four) images from different dates between 1992 and 2009 (post-disaster) were used. The images were processed in vegetation index using bands 7 and 4 in order to minimize atmospheric and radiometric distortions. Shadow mask, construted from the digital terrain model, was developed to avoid false changes caused by shade. It was concluded that the georeferencing must be very accurate in applying these techniques. The vegetation index by using bands 7 and 4and the shadow mask, were effective in minimizing false changes. It showed that the techniques applied are effective to detect changes in areas affected by the disaster