Seed image analysis and taxonomy of Diplotaxis DC. (Brassicaceae, Brassiceae)

The genus Diplotaxis, comprising 32 or 34 species, plus several additional infraspecific taxa, displays a considerable degree of heterogeneity in the morphology, molecular markers, chromosome numbers and geographical amplitude of the species. The taxonomic relationships within the genus Diplotaxis were investigated by phenetic characterisation of germplasm belonging to 27 taxa of the genus, because there is an increasing interest in Diplotaxis, since some of its species (D. tenuifolia, D. muralis) are gathered or cultivated for human consumption, whereas others are frequent arable weeds (D. erucoides) in many European vineyards. Using a computer-aided vision system, 33 morpho-colorimetric features of seeds were electronically measured. The data were used to implement a statistical classifier, which is able to discriminate the taxa within the genus Diplotaxis, in order to compare the resulting species grouping with the current infrageneric systematics of this genus. Despite the high heterogeneity of the samples, due to the great intra-population variability, the stepwise Linear Discriminant Analysis method, applied to distinguish the groups, was able to reach over 80% correct identification. The results obtained allowed us to confirm the current taxonomic position of most taxa and suggested the taxonomic position of others for reconsideration.

Data mining applied to the cognitive rehabilitation of patients with acquired brain injury

Acquired brain injury (ABI) is one of the leading causes of death and disability in the world and is associated with high health care costs as a result of the acute treatment and long term rehabilitation involved. Different algorithms and methods have been proposed to predict the effectiveness of rehabilitation programs. In general, research has focused on predicting the overall improvement of patients with ABI. The purpose of this study is the novel application of data mining (DM) techniques to predict the outcomes of cognitive rehabilitation in patients with ABI. We generate three predictive models that allow us to obtain new knowledge to evaluate and improve the effectiveness of the cognitive rehabilitation process. Decision tree (DT), multilayer perceptron (MLP) and general regression neural network (GRNN) have been used to construct the prediction models. 10-fold cross validation was carried out in order to test the algorithms, using the Institut Guttmann Neurorehabilitation Hospital (IG) patients database. Performance of the models was tested through specificity, sensitivity and accuracy analysis and confusion matrix analysis. The experimental results obtained by DT are clearly superior with a prediction average accuracy of 90.38%, while MLP and GRRN obtained a 78.7% and 75.96%, respectively. This study allows to increase the knowledge about the contributing factors of an ABI patient recovery and to estimate treatment efficacy in individual patients.

A Lagrangian descriptor applied to the Kuroshio current

The understanding of the circulation of ocean currents, the exchange of CO2 between atmosphere and oceans, and the in uence of the oceans on the distribution of heat on a global scale is key to our ability to predict and assess the future evolution of climate.

Ultraintense lasers applied to laser fusion material testing: production of ions, X rays and neutrons

Due to the particular characteristics of the fusion products, i.e. very short pulses (less than a few μs long for ions when arriving to the walls; less than 1 ns long for X-rays), very high fluences ( 10 13 particles/cm 2 for both ions and X rays photons) and broad particle energy spectra (up to 10 MeV ions and 100 keV photons), the laser fusion community lacks of facilities to accurately test plasma facing materials under those conditions. In the present work, the ability of ultraintese lasers to create short pulses of energetic particles and high fluences is addressed as a solution to reproduce those ion and X-ray bursts. Based on those parameters, a comparison between fusion ion and laser driven ion beams is presented and discussed, describing a possible experimental set-up to generate with lasers the appropriate ion pulses. At the same time, the possibility of generating X-ray or neutron beams which simulate those of laser fusion environments is also indicated and assessed under current laser intensities. It is concluded that ultraintense lasers should play a relevant role in the validation of materials for laser fusion facilities.

Ultraintense Lasers Applied to Laser Fusion Material Testing: Production of Ions, X rays and Neutrons

The ability of ultraintese lasers to create short pulses of energetic particles and high fluences is addressed as a solution to reproduce ion and X-ray ICF bursts for the characterization and validation of plasma facing components. The possibility of using a laser neutron source for material testing will also be discussed.

ANN and Fuzzy c-Means applied to environmental pollution prediction

Salamanca, situated in center of Mexico is among the cities which suffer most from the air pollution in Mexico. The vehicular park and the industry, as well as orography and climatic characteristics have propitiated the increment in pollutant concentration of Sulphur Dioxide (SO2). In this work, a Multilayer Perceptron Neural Network has been used to make the prediction of an hour ahead of pollutant concentration. A database used to train the Neural Network corresponds to historical time series of meteorological variables and air pollutant concentrations of SO2. Before the prediction, Fuzzy c-Means and K-means clustering algorithms have been implemented in order to find relationship among pollutant and meteorological variables. Our experiments with the proposed system show the importance of this set of meteorological variables on the prediction of SO2 pollutant concentrations and the neural network efficiency. The performance estimation is determined using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results showed that the information obtained in the clustering step allows a prediction of an hour ahead, with data from past 2 hours.

Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm

This work evaluates a spline-based smoothing method applied to the output of a glucose predictor. Methods:Our on-line prediction algorithm is based on a neural network model (NNM). We trained/validated the NNM with a prediction horizon of 30 minutes using 39/54 profiles of patients monitored with the Guardian® Real-Time continuous glucose monitoring system The NNM output is smoothed by fitting a causal cubic spline. The assessment parameters are the error (RMSE), mean delay (MD) and the high-frequency noise (HFCrms). The HFCrms is the root-mean-square values of the high-frequency components isolated with a zero-delay non-causal filter. HFCrms is 2.90±1.37 (mg/dl) for the original profiles.

E-MIS validity applied to TELMA enhanced learning environment

Enhanced learning environments are arising with great success within the field of cognitive skills training in minimally invasive surgery (MIS) because they provides multiple benefits since they avoid time, spatial and cost constraints. TELMA [1,2] is a new technology enhanced learning platform that promotes collaborative and ubiquitous training of surgeons. This platform is based on four main modules: an authoring tool, a learning content and knowledge management system, an evaluation module and a professional network. TELMA has been designed and developed focused on the user; therefore it is necessary to carry out a user validation as final stage of the development. For this purpose, e-MIS validity [3] has been defined. This validation includes usability, contents and functionality validities both for the development and production stages of any e-Learning web platform. Using e-MIS validity, the e-Learning is fully validated since it includes subjective and objective metrics. The purpose of this study is to specify and apply a set of objective and subjective metrics using e-MIS validity to test usability, contents and functionality of TELMA environment within the development stage.

Functional modeling applied to HAZOP automation

In this paper we present a new tool to perform guided HAZOP analyses. This tool uses a functional model of the process that merges its functional and its structural information in a natural way. The functional modeling technique used is called D-higraphs. This tool solves some of the problems and drawbacks of other existing methodologies for the automation of HAZOPs. The applicability and easy understanding of the proposed methodology is shown in an industrial case.

New control architecturebased on PXI for a 3-finger haptic device applied to virtual manipulation

To perform advanced manipulation of remote environments such as grasping, more than one finger is required implying higher requirements for the control architecture. This paper presents the design and control of a modular 3-finger haptic device that can be used to interact with virtual scenarios or to teleoperate dexterous remote hands. In a modular haptic device, each module allows the interaction with a scenario by using a single finger; hence, multi-finger interaction can be achieved by adding more modules. Control requirements for a multifinger haptic device are analyzed and new hardware/software architecture for these kinds of devices is proposed. The software architecture described in this paper is distributed and the different modules communicate to allow the remote manipulation. Moreover, an application in which this haptic device is used to interact with a virtual scenario is shown.

A global Lagrangian descriptor applied to the Kuroshio current

A global Lagrangian descriptor applied to the Kuroshio current

A comparative study of Monte Carlo-coupled depletion codes applied to a Sodium Fast Reactor design loaded with minor actinides

inor actinides (MAs) transmutation is a main design objective of advanced nuclear systems such as generation IV Sodium Fast Reactors (SFRs). In advanced fuel cycles, MA contents in final high level waste packages are main contributors to short term heat production as well as to long-term radiotoxicity. Therefore, MA transmutation would have an impact on repository designs and would reduce the environment burden of nuclear energy. In order to predict such consequences Monte Carlo (MC) transport codes are used in reactor design tasks and they are important complements and references for routinely used deterministic computational tools. In this paper two promising Monte Carlo transport-coupled depletion codes, EVOLCODE and SERPENT, are used to examine the impact of MA burning strategies in a SFR core, 3600 MWth. The core concept proposal for MA loading in two configurations is the result of an optimization effort upon a preliminary reference design to reduce the reactivity insertion as a consequence of sodium voiding, one of the main concerns of this technology. The objective of this paper is double. Firstly, efficiencies of the two core configurations for MA transmutation are addressed and evaluated in terms of actinides mass changes and reactivity coefficients. Results are compared with those without MA loading. Secondly, a comparison of the two codes is provided. The discrepancies in the results are quantified and discussed.

Unconformity-bounded stratigraphic units (UBSUs) in an italian alluvial-plain area: recognizing and dating

We studied the coastal zone of the Tavoliere di Puglia plain, (Puglia region, southern Italy) with the aim to recognize the main unconformities, and therefore, the unconformity-bounded stratigraphic units (UBSUs; Salvador 1987, 1994) forming its Quaternary sedimentary fill. Recognizing unconformities is particularly problematic in an alluvial plain, due to the difficulties in distinguishing the unconformities that bound the UBSUs. So far, the recognition of UBSUs in buried successions has been made mostly by using seismic profiles. Instead, in our case, the unavailability of the latter has prompted us to address the problem by developing a methodological protocol consisting of the following steps: I) geological survey in the field; II) draft of a preliminary geological setting based on the field-survey results; III) dating of 102 samples coming from a large number of boreholes and some outcropping sections by means of the amino acid racemization (AAR) method applied to ostracod shells and 14C dating, filtering of the ages and the selection of valid ages; IV) correction of the preliminary geological setting in the light of the numerical ages; definition of the final geological setting with UBSUs; identification of a ‘‘hypothetical’’ or ‘‘attributed time range’’ (HTR or ATR) for each UBSU, the former very wide and subject to a subsequent modification, the latter definitive; V) cross-checking between the numerical ages and/or other characteristics of the sedimentary bodies and/or the sea-level curves (with their effects on the sedimentary processes) in order to restrict also the hypothetical time ranges in the attributed time ranges. The successful application of AAR geochronology to ostracod shells relies on the fact that the ability of ostracods to colonize almost all environments constitutes a tool for correlation, and also allow the inclusion in the same unit of coeval sediments that differ lithologically and paleoenvironmentally. The treatment of the numerical ages obtained using the AAR method required special attention. The first filtering step was made by the laboratory (rejection criteria a and b). Then, the second filtering step was made by testing in the field the remaining ages. Among these, in fact, we never compared an age with a single preceding and/or following age; instead, we identified homogeneous groups of numerical ages consistent with their reciprocal stratigraphic position. This operation led to the rejection of further numerical ages that deviate erratically from a larger, homogeneous age population which fits well with its stratigraphic position (rejection criterion c). After all of the filtering steps, the valid ages that remained were used for the subdivision of the sedimentary sequences into UBSUs together with the lithological and paleoenvironmental criteria. The numerical ages allowed us, in the first instance, to recognize all of the age gaps between two consecutive samples. Next, we identified the level, in the sedimentary thickness that is between these two samples, that may represent the most suitable UBSU boundary based on its lithology and/or the paleoenvironment. The recognized units are: I) Coppa Nevigata sands (NEA), HTR: MIS 20–14, ATR: MIS 17–16; II) Argille subappennine (ASP), HTR: MIS 15–11, ATR: MIS 15–13; III) Coppa Nevigata synthem (NVI), HTR: MIS 13–8, ATR: MIS 12–11; IV) Sabbie di Torre Quarto (STQ), HTR: MIS 13–9.1, ATR: MIS 11; V) Amendola subsynthem (MLM1), HTR: MIS 12–10, ATR: MIS 11; VI) Undifferentiated continental unit (UCI), HTR: MIS 11–6.2, ATR: MIS 9.3–7.1; VII) Foggia synthem (TGF), ATR: MIS 6; VIII) Masseria Finamondo synthem (TPF), ATR: Upper Pleistocene; IX) Carapelle and Cervaro streams synthem (RPL), subdivided into: IXa) Incoronata subsynthem (RPL1), HTR: MIS 6–3; ATR: MIS 5–3; IXb) Marane La Pidocchiosa–Castello subsynthem (RPL3), ATR: Holocene; X) Masseria Inacquata synthem (NAQ), ATR: Holocene. The possibility of recognizing and dating Quaternary units in an alluvial plain to the scale of a marine isotope stage constitutes a clear step forward compared with similar studies regarding other alluvial-plain areas, where Quaternary units were dated almost exclusively using their stratigraphic position. As a result, they were generically associated with a geological sub-epoch. Instead, our method allowed a higher detail in the timing of the sedimentary processes: for example, MIS 11 and MIS 5.5 deposits have been recognized and characterized for the first time in the study area, highlighting their importance as phases of sedimentation.

MedVir: 3D visual interface applied to gene profile analysis

The use of data mining techniques for the gene profile discovery of diseases, such as cancer, is becoming usual in many researches. These techniques do not usually analyze the relationships between genes in depth, depending on the different variety of manifestations of the disease (related to patients). This kind of analysis takes a considerable amount of time and is not always the focus of the research. However, it is crucial in order to generate personalized treatments to fight the disease. Thus, this research focuses on finding a mechanism for gene profile analysis to be used by the medical and biologist experts. Results: In this research, the MedVir framework is proposed. It is an intuitive mechanism based on the visualization of medical data such as gene profiles, patients, clinical data, etc. MedVir, which is based on an Evolutionary Optimization technique, is a Dimensionality Reduction (DR) approach that presents the data in a three dimensional space. Furthermore, thanks to Virtual Reality technology, MedVir allows the expert to interact with the data in order to tailor it to the experience and knowledge of the expert.

A cost-effective methodology applied to videoconference services over hybrid clouds

This paper tackles the optimization of applications in multi-provider hybrid cloud scenarios from an economic point of view. In these scenarios the great majority of solutions offer the automatic allocation of resources on different cloud providers based on their current prices. However our approach is intended to introduce a novel solution by making maximum use of divide and rule. This paper describes a methodology to create cost aware cloud applications that can be broken down into the three most important components in cloud infrastructures: computation, network and storage. A real videoconference system has been modified in order to evaluate this idea with both theoretical and empirical experiments. This system has become a widely used tool in several national and European projects for e-learning and collaboration purposes.