A numerical study of a semi‐algebraic multilevel preconditioner for the local discontinuous Galerkin method

In this work, we consider the local discontinuous Galerkin (LDG) method applied to second‐order elliptic problems arising in the modeling of single‐phase flows in porous media. It has been recently proven that the spectral condition number of the stiffness matrix exhibits an asymptotic behavior of ??(h^?2) on structured and unstructured meshes, where h is the mesh size. Thus, efficient preconditioners are mandatory. We present a semi‐algebraic multilevel preconditioner for the LDG method using local Lagrange‐type interpolatory basis functions. We show, numerically, that its performance does not degrade, or at least the number of iterations increases very slowly, as the number of unknowns augments. The preconditioner is tested on problems with high jumps in the coefficients, which is the typical scenario of problems arising in porous media. Copyright © 2007 John Wiley & Sons, Ltd.     

Can porous polymeric scaffolds be functionalized by stem cells leading to osteogenic differentiation? A systematic review of in vitro studies

The aim of this study was to analyze the influence of nanoporous structure of polymeric biomaterials on the in vitro osteogenic induction of human stem cells. An electronic search in three databases (MEDLINE, SCOPUS, and Web of Science) was performed for articles that were published before May 2018. In vitro studies were included if they met the following criteria: (1) the use of polymeric scaffolds (natural or synthetic); (2) the co-culture of human stem cells with the scaffold; and (3) cell viability, proliferation, and osteogenic differentiation assays. The main characteristics of the published studies were summarized, and a quality assessment tool was used to analyze methodological features. Eighty-eight potential articles were firstly retrieved. Thirteen were eligible for qualitative analysis. Only three studies characterized cell stemness. Nanostructure of the scaffolds showed a significant influence on viability, proliferation, and osteogenic differentiation of human stem cells. Combination of porosity between 72 and 93% and a large range diameter between 50 and 224 μm resulted in more remarkable cellular proliferation and differentiation. Porous polymeric scaffolds can be functionalized by stem cells leading to osteogenic induction. High standards of laboratory practice and accurate methodological reporting are essential for the credibility of the results.     

Learning Structure from Data and Its Application to Ozone Prediction

In this paper we propose an algorithm for structure learning in predictive expert systems based on a probabilistic network representation. The idea is to have the simplest structure (minimum number of links) with acceptable predictive capability. The algorithm starts by building a tree structure based on measuring mutual information between pairs of variables, and then it adds links as necessary to obtain certain predictive performance. We have applied this method for ozone prediction in México City, where the ozone level is used as a global indicator for the air quality in different parts of the city. It is important to predict the ozone level a day, or at least several hours in advance, to reduce the health hazards and industrial losses that occur when the ozone reaches emergency levels. We obtained as a first approximation a tree-structured dependency model for predicting ozone in one part of the city. We observe that even with only three parameters, its estimations are acceptable.A causal network representation and the structure learning techniques produced some very interesting results for the ozone prediction problem. Firstly, we got some insight into the dependence structure of the phenomena. Secondly, we got an indication of which are the important and not so important variables for ozone forecasting. Taking this into account, the measurement and computational costs for ozone prediction could be reduced. And thirdly, we have obtained satisfactory short term ozone predictions based on a small set of the most important parameters.     

Localization-limited exciton oscillator strength in colloidal CdSe nanoplatelets revealed by the optically induced stark effect

2D materials are considered for applications that require strong light-matter interaction because of the apparently giant oscillator strength of the exciton tra...     

From latex specifications to parallel codes

The advent of multicore systems, joined to the potential acceleration of the graphics processing units, has given us a low cost computation capability unprecedented. The new systems alleviate some well-known important architectural problems at the expense of a considerable increment of the programmability wall. Heterogeneity, at both the architectural and programming levels, poses a great challenge to programmers. As a contribution, we propose a development methodology for the automatic source-to-source transformation on specific domains. This methodology is successfully instantiated as a framework to solve Dynamic Programming problems. As a result of applying our framework, the end user (a physicist, a mathematician or a biologist) can express her problem through a latex equation and automatically derive efficient parallel codes for current homogeneous or heterogeneous architectures. The approach allows an easy portability to new emergent architectures.     

Collective intelligence as mechanism of medical diagnosis: The iPixel approach

Collective intelligence (CI) is an active field of research, which capitalizes the knowledge of human collectives in order to create, to innovate and to invent. There are two important mechanisms to implement CI: recommender and reputation systems. Recommender systems are used to provide filtered information from a large amount of elements. The recommendations are intended to provide interesting elements to users. Recommendation systems can be developed using different techniques and algorithms where the selection of these techniques depends on the area in which they will be applied. This work presents iPixel Recommender Engine, which is focused on the medical field. iPixel Recommendation Engine supports the process of differential diagnosis by recommending mammographic evaluations. Each mammogram is collectively tagged by the users’ community with a semantic sense; this feature allows iPixel acquires collective knowledge. iPixel can associate more than one feature with each mammogram. This work also presents a qualitative evaluation, where the basic features that a recommendation system should have in the medical field were obtained. Finally, a comparison was carried out with other similar recommender systems in order to know the Pixel advantages.     

Control of attendance applied in higher education through mobile NFC technologies

This paper presents an improved attendance control system, required for continuous evaluation which has become compulsory following the Bologna Process. It provides a solution based on NFC technology and is based on a real project developed and pilot tested at the “Universidad Pontificia de Salamanca, Campus Madrid”.     

Using frames to disambiguate prepositions

In natural language processing (NLP), disambiguation is the procedure used to solve name conflicts of polysemic concepts (different meanings); in fact, phrase disambiguation is a problem not totally solved in NLP. Several disambiguation types exist; for instance, noun disambiguation (bank is a word with several meanings) or when a word is both used as a noun and as a preposition. Work herein reported describes an algorithm and its implementation to disambiguate prepositions in Spanish phrases; some of them are: a {to} (Translation to English are in bold for explanation purposes; they give only one of the senses of the Spanish word, which usually have multiple meanings.), ante {before}, bajo {under}, cabe {fits}, desde {from}, contra {against}, en {in}, por {by}, según {according to}, sin {without}, entre {between}, so {under}, con {with}, hacia {towards}, sobre {about}, hasta {until}, de {of}, tras {after}, para {for}. This tool will be used in a text analyzer (being built) that converts a text document to its corresponding ontology representation, with the goal of allowing another program to use the information to answer non trivial questions (**).     

A cluster-DEE-based strategy to empower protein design

The Medical and Pharmaceutical industries have shown high interest in the precise engineering of protein hormones and enzymes that perform existing functions under a wide range of conditions. Proteins are responsible for the execution of different functions in the cell: catalysis in chemical reactions, transport and storage, regulation and recognition control. Computational Protein Design (CPD) investigates the relationship between 3-D structures of proteins and amino acid sequences and looks for all sequences that will fold into such 3-D structure. Many computational methods and algorithms have been proposed over the last years, but the problem still remains a challenge for Mathematicians, Computer Scientists, Bioinformaticians and Structural Biologists. In this article we present a new method for the protein design problem. Clustering techniques and a Dead-End-Elimination algorithm are combined with a SAT problem representation of the CPD problem in order to design the amino acid sequences. The obtained results illustrate the accuracy of the proposed method, suggesting that integrated Artificial Intelligence techniques are useful tools to solve such an intricate problem.     

Efficient implementation of the implicit error correction nVoD schema

Implicit Error Correction is a near Video-on-Demand (nVoD) schema that trades bandwidth utilization for initial playback delay while potentially allowing an infinite number of users. Additionally, it provides error protection without further bandwidth increase by exploiting the implicit redundancy of nVoD protocols, using linear combinations of the segments transmitted in a given time slot. This paper introduces a new implementation that outperforms the original schema by adding two new mechanisms: redundancy channels and feedback error correction.