An online data access prediction and optimization approach for distributed systems

Current scientific applications have been producing large amounts of data. The processing, handling and analysis of such data require large-scale computing infrastructures such as clusters and grids. In this area, studies aim at improving the performance of data-intensive applications by optimizing data accesses. In order to achieve this goal, distributed storage systems have been considering techniques of data replication, migration, distribution, and access parallelism. However, the main drawback of those studies is that they do not take into account application behavior to perform data access optimization. This limitation motivated this paper which applies strategies to support the online prediction of application behavior in order to optimize data access operations on distributed systems, without requiring any information on past executions. In order to accomplish such a goal, this approach organizes application behaviors as time series and, then, analyzes and classifies those series according to their properties. By knowing properties, the approach selects modeling techniques to represent series and perform predictions, which are, later on, used to optimize data access operations. This new approach was implemented and evaluated using the OptorSim simulator, sponsored by the LHC-CERN project and widely employed by the scientific community. Experiments confirm this new approach reduces application execution time in about 50 percent, specially when handling large amounts of data.

The erosion and abrasion-inhibiting effect of TiF4 and NaF varnishes and solutions on enamel in vitro

Objective. Previous in vitro study has shown that TiF(4) varnish might reduce enamel erosion. No data regarding the effect of this experimental varnish on enamel erosion plus abrasion, however, are available so far. Thus, this in vitro study aimed to analyse the effect of TiF4 compared with NaF varnishes and solutions, to protect against enamel erosion with or without abrasion. Methods. Enamel specimens were pre-treated with experimental-TiF4 (2.45% F), experimentalNaF (2.45% F), NaF-Duraphat (2.26% F), and placebo varnishes; NaF (2.26% F) and TiF4 (2.45% F) solutions. Controls remained untreated. The erosive challenge was performed using a soft drink (pH 2.6) 4 u 90 s / day (ERO) and the toothbrushing abrasion (ERO+ ABR) 2 u 10 s / day, for 5 days. Between the challenges, the specimens were exposed to artificial saliva. Enamel loss was measured profilometrically (lm). Results. Kruskal-Wallis / Dunn tests showed that all fluoridated varnishes (TiF4-ERO: 0.53 +/- 0.20, ERO+ ABR: 0.65 +/- 0.19/ NaF-ERO: 0.94 +/- 0.18, ERO+ ABR: 1.74 +/- 0.37 / Duraphat-ERO: 1.00 +/- 0.37, ERO+ ABR: 1.72 +/- 0.58) were able to significantly reduce enamel loss when compared with placebo varnish (ERO: 3.45 +/- 0.41 / ERO+ ABR: 3.20 +/- 0.66) (P < 0.0001). Placebo varnish, control (ERO: 2.68 +/- 0.53 / ERO+ ABR: 3.01 +/- 0.34), and fluoridated (NaF-ERO: 2.84 +/- 0.09 / ERO+ ABR: 2.40 +/- 0.21 / TiF4-ERO: 3.55 +/- 0.59 / ERO+ ABR: 4.10 +/- 0.38) solutions did not significantly differ from each other. Conclusion. Based on the results, it can be concluded that the TiF4 varnish seems to be a promising treatment to reduce enamel loss under mild erosive and abrasive conditions in vitro.

Computational framework to support integration of biomolecular and clinical data within a translational approach

Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado – the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different “omics” technologies with patient’s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.

A quantitative analysis of current security concerns and solutions for cloud computing

The development of cloud computing services is speeding up the rate in which the organizations outsource their computational services or sell their idle computational resources. Even though migrating to the cloud remains a tempting trend from a financial perspective, there are several other aspects that must be taken into account by companies before they decide to do so. One of the most important aspect refers to security: while some cloud computing security issues are inherited from the solutions adopted to create such services, many new security questions that are particular to these solutions also arise, including those related to how the services are organized and which kind of service/data can be placed in the cloud. Aiming to give a better understanding of this complex scenario, in this article we identify and classify the main security concerns and solutions in cloud computing, and propose a taxonomy of security in cloud computing, giving an overview of the current status of security in this emerging technology.

Effect of fluoride sodium mouthwash solutions on cpTI: evaluation of physicochemical properties

The effects of fluoride, which is present in different oral hygiene products, deserve more investigation because little is known about their impact on the surface of titanium, which is largely used in Implantology. This study evaluated the surface of commercially pure titanium (cpTi) after exposure to different concentrations of sodium fluoride (NaF). The hypothesis tested in this study was that different concentrations of NaF applied at different time intervals can affect the titanium surface in different ways. The treatments resulted in the following groups: GA (control): immersion in distilled water; GB: immersion in 0.05% NaF for 3 min daily; GC: immersion in 0.2% NaF for 3 min daily; GD: immersion in 0.05% NaF for 3 min every 2 weeks; and GE: immersion in 0.2% NaF for 3 min every 2 weeks. The experiment lasted 60 days. Roughness was measured initially and every 15 days subsequently up to 60 days. After 60 days, corrosion analysis and anodic polarization were done. The samples were examined by scanning electron microscopy (SEM). The roughness data were analyzed by ANOVA and there was no significant difference among groups and among time intervals. The corrosion data (i corr) were analyzed by the Mann-Whitney test, and significant differences were found between GA and GC, GB and GC, GC and GD, GC and GE. SEM micrographs showed that the titanium surface exposed to NaF presented corrosion that varied with the different concentrations. This study suggests that the use of 0.05% NaF solution on cpTi is safe, whereas the 0.2% NaF solution should be carefully evaluated with regard to its daily use.

Ontology for Data Representation in the Production of Cotton Fiber in Brazil

An important feature in computer systems developed for the agricultural sector is to satisfy the heterogeneity of data generated in different processes. Most problems related with this heterogeneity arise from the lack of standard for different computing solutions proposed. An efficient solution for that is to create a single standard for data exchange. The study on the actual process involved in cotton production was based on a research developed by the Brazilian Agricultural Research Corporation (EMBRAPA) that reports all phases as a result of the compilation of several theoretical and practical researches related to cotton crop. The proposition of a standard starts with the identification of the most important classes of data involved in the process, and includes an ontology that is the systematization of concepts related to the production of cotton fiber and results in a set of classes, relations, functions and instances. The results are used as a reference for the development of computational tools, transforming implicit knowledge into applications that support the knowledge described. This research is based on data from the Midwest of Brazil. The choice of the cotton process as a study case comes from the fact that Brazil is one of the major players and there are several improvements required for system integration in this segment.