Analytical Processing Over XML and XLink

Current commercial and academic OLAP tools do not process XML data that contains XLink. Aiming at overcoming this issue, this paper proposes an analytical system composed by LMDQL, an analytical query language. Also, the XLDM metamodel is given to model cubes of XML documents with XLink and to deal with syntactic, semantic and structural heterogeneities commonly found in XML documents. As current W3C query languages for navigating in XML documents do not support XLink, XLPath is discussed in this article to provide features for the LMDQL query processing. A prototype system enabling the analytical processing of XML documents that use XLink is also detailed. This prototype includes a driver, named sql2xquery, which performs the mapping of SQL queries into XQuery. To validate the proposed system, a case study and its performance evaluation are presented to analyze the impact of analytical processing over XML/XLink documents.

Processing of high resolution magic angle spinning spectra of breast cancer cells by the filter diagonalization method

Proton nuclear magnetic resonance (H-1 NMR) spectroscopy for detection of biochemical changes in biological samples is a successful technique. However, the achieved NMR resolution is not sufficiently high when the analysis is performed with intact cells. To improve spectral resolution, high resolution magic angle spinning (HR-MAS) is used and the broad signals are separated by a T-2 filter based on the CPMG pulse sequence. Additionally, HR-MAS experiments with a T-2 filter are preceded by a water suppression procedure. The goal of this work is to demonstrate that the experimental procedures of water suppression and T-2 or diffusing filters are unnecessary steps when the filter diagonalization method (FDM) is used to process the time domain HR-MAS signals. Manipulation of the FDM results, represented as a tabular list of peak positions, widths, amplitudes and phases, allows the removal of water signals without the disturbing overlapping or nearby signals. Additionally, the FDM can also be used for phase correction and noise suppression, and to discriminate between sharp and broad lines. Results demonstrate the applicability of the FDM post-acquisition processing to obtain high quality HR-MAS spectra of heterogeneous biological materials.

The SB-index and the HSB-index: efficient indices for spatial data warehouses

Spatial data warehouses (SDWs) allow for spatial analysis together with analytical multidimensional queries over huge volumes of data. The challenge is to retrieve data related to ad hoc spatial query windows according to spatial predicates, avoiding the high cost of joining large tables. Therefore, mechanisms to provide efficient query processing over SDWs are essential. In this paper, we propose two efficient indices for SDW: the SB-index and the HSB-index. The proposed indices share the following characteristics. They enable multidimensional queries with spatial predicate for SDW and also support predefined spatial hierarchies. Furthermore, they compute the spatial predicate and transform it into a conventional one, which can be evaluated together with other conventional predicates by accessing a star-join Bitmap index. While the SB-index has a sequential data structure, the HSB-index uses a hierarchical data structure to enable spatial objects clustering and a specialized buffer-pool to decrease the number of disk accesses. The advantages of the SB-index and the HSB-index over the DBMS resources for SDW indexing (i.e. star-join computation and materialized views) were investigated through performance tests, which issued roll-up operations extended with containment and intersection range queries. The performance results showed that improvements ranged from 68% up to 99% over both the star-join computation and the materialized view. Furthermore, the proposed indices proved to be very compact, adding only less than 1% to the storage requirements. Therefore, both the SB-index and the HSB-index are excellent choices for SDW indexing. Choosing between the SB-index and the HSB-index mainly depends on the query selectivity of spatial predicates. While low query selectivity benefits the HSB-index, the SB-index provides better performance for higher query selectivity.

Qualitative analysis by online nuclear magnetic resonance using Carr-Purcell-Meiboom-Gill sequence with low refocusing flip angles

The Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence has been used in many applications of magnetic resonance imaging (MRI) and low-resolution NMR (LRNMR) spectroscopy. Recently. CPMG was used in online LRNMR measurements that use long RF pulse trains, causing an increase in probe temperature and, therefore, tuning and matching maladjustments. To minimize this problem, the use of a low-power CPMG sequence based on low refocusing pulse flip angles (LRFA) was studied experimentally and theoretically. This approach has been used in several MRI protocols to reduce incident RF power and meet the specific absorption rate. The results for CPMG with LRFA of 3 pi/4 (CPMG(135)), pi/2 (CPMG(90)) and pi/4 (CPMG(45)) were compared with conventional CPMG with refocusing pi pulses. For a homogeneous field, with linewidth equal to Delta nu = 15 Hz, the refocusing flip angles can be as low as pi/4 to obtain the transverse relaxation time (T(2)) value with errors below 5%. For a less homogeneous magnetic field. Delta nu = 100 Hz, the choice of the LRFA has to take into account the reduction in the intensity of the CPMG signal and the increase in the time constant of the CPMG decay that also becomes dependent on longitudinal relaxation time (T(1)). We have compared the T(2) values measured by conventional CPMG and CPMG(90) for 30 oilseed species, and a good correlation coefficient, r = 0.98, was obtained. Therefore, for oilseeds, the T(2) measurements performed with pi/2 refocusing pulses (CPMG(90)), with the same pulse width of conventional CPMG, use only 25% of the RF power. This reduces the heating problem in the probe and reduces the power deposition in the samples. (C) 2011 Elsevier B.V. All rights reserved.

From Sample Processing to Quantification: A Full Electrochemical Approach for Neutral Analyte Derivatization, Capillary Electrophoresis Separation, and Contactless Conductivity Detection

A thin-layer electrochemical flow cell coupled to capillary electrophoresis with contactless conductivity detection (EC-CE-(CD)-D-4) was applied for the first time to the derivatization and quantification of neutral species using aliphatic alcohols as model compounds. The simultaneous electrooxidation of four alcohols (ethanol, 1-propanol, 1-butanol, and 1-pentanol) to the corresponding carboxylates was carried out on a platinum working electrode in acid medium. The derivatization step required 1 min at 1.6 V vs. Ag/AgCl under stopped flow conditions, which was preceded by a 10 s activation at 0 V. The solution close to the electrode surface was then hydrodynamically injected into the capillary, and a 2.5 min electrophoretic separation was carried out. The fully automated flow system operated at a frequency of 12 analyses per hour. Simultaneous determination of the four alcohols presented detection limits of about 5 x 10(-5) mol As a practical application with a complex matrix, ethanol concentrations were determined in diluted pale lager beer and in nonalcoholic beer. No statistically significant difference was observed between the EC-CE-(CD)-D-4 and gas chromatography with flame ionization detection (GC-FID) results for these samples. The derivatization efficiency remained constant over several hours of continuous operation with lager beer samples (n = 40).

Determination of anticonvulsants in human plasma using SPME in a heated interface coupled online to liquid chromatography (SPME-LC)

A simple and sensitive method using solid phase microextraction (SPME) and liquid chromatography (LC) with heated online desorption (SPME-LC) was developed and validated to analyze anticonvulsants (AEDs) in human plasma samples. A heated lab-made interface chamber was used in the desorption procedure, which allowed the transference of the whole extracted sample. The SPME conditions were optimized by applying an experimental design. Important factors are discussed such as fiber coating types, pH, extraction time and desorption conditions. The drugs were analyzed by LC, using a C18 column (150 mm x 4.6 mm x 5 mm); and 50 mmol L-1, pH 5.50 ammonium acetate buffer : acetonitrile : methanol (55 : 22 : 23 v/v) as the mobile phase with a flow rate of 0.8 mL min(-1). The suggested method presented precision (intra-assay and inter-assay), linearity and limit of quantification (LOQ) all adequate for the therapeutic drug monitoring (TDM) of AEDs in plasma.

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.

Uso da RMN como um sensor online em processos industriais

Nuclear magnetic resonance (NMR) is one of the most versatile analytical techniques for chemical, biochemical and medical applications. Despite this great success, NMR is seldom used as a tool in industrial applications. The first application of NMR in flowing samples was published in 1951. However, only in the last ten years Flow NMR has gained momentum and new and potential applications have been proposed. In this review we present the historical evolution of flow or online NMR spectroscopy and imaging, and current developments for use in the automation of industrial processes.