A profile-based tool for finding pipeline parallelism in sequential programs

Traditional static analysis fails to auto-parallelize programs with a complex control and data flow. Furthermore, thread-level parallelism in such programs is often restricted to pipeline parallelism, which can be hard to discover by a programmer. In this paper we propose a tool that, based on profiling information, helps the programmer to discover parallelism. The programmer hand-picks the code transformations from among the proposed candidates which are then applied by automatic code transformation techniques.

This paper contributes to the literature by presenting a profiling tool for discovering thread-level parallelism. We track dependencies at the whole-data structure level rather than at the element level or byte level in order to limit the profiling overhead. We perform a thorough analysis of the needs and costs of this technique. Furthermore, we present and validate the belief that programs with complex control and data flow contain significant amounts of exploitable coarse-grain pipeline parallelism in the program’s outer loops. This observation validates our approach to whole-data structure dependencies. As state-of-the-art compilers focus on loops iterating over data structure members, this observation also explains why our approach finds coarse-grain pipeline parallelism in cases that have remained out of reach for state-of-the-art compilers. In cases where traditional compilation techniques do find parallelism, our approach allows to discover higher degrees of parallelism, allowing a 40% speedup over traditional compilation techniques. Moreover, we demonstrate real speedups on multiple hardware platforms.

Sequential versus non-sequential double ionization in strong laser fields

<p> The recollision model has been applied to separate the probability for double ionization into contributions from electron-impact ionization and electron-impact excitation for intensities at which the dielectronic interaction is important for generating double ionization. For a wavelength of 780 am, electron-impact excitation dominates just above the threshold intensity for double ionization, approximate to 1.2 x 10(14) W cm(-2), with electron-impact ionization becoming more important for higher intensities. For a wavelength of 390 nm, the ratio between electron-impact ionization and electron-impact excitation remains fairly constant for all intensities above the threshold intensity for double ionization, approximate to 6 x 10(14) W cm(-2). The results point to an explanation of the experimental results, but more detailed calculations on the behaviour of excited He+ ions are required.</p>

Web Data Extraction from Query Result Pages Based on Visual and Content Features

A rapidly increasing number of Web databases are now become accessible via
their HTML form-based query interfaces. Query result pages are dynamically generated
in response to user queries, which encode structured data and are displayed for human
use. Query result pages usually contain other types of information in addition to query
results, e.g., advertisements, navigation bar etc. The problem of extracting structured data
from query result pages is critical for web data integration applications, such as comparison
shopping, meta-search engines etc, and has been intensively studied. A number of approaches
have been proposed. As the structures of Web pages become more and more complex, the
existing approaches start to fail, and most of them do not remove irrelevant contents which
may a®ect the accuracy of data record extraction. We propose an automated approach for
Web data extraction. First, it makes use of visual features and query terms to identify data
sections and extracts data records in these sections. We also represent several content and
visual features of visual blocks in a data section, and use them to ¯lter out noisy blocks.
Second, it measures similarity between data items in di®erent data records based on their
visual and content features, and aligns them into di®erent groups so that the data in the
same group have the same semantics. The results of our experiments with a large set of
Web query result pages in di®erent domains show that our proposed approaches are highly
e®ective.

Max separation clustering for feature extraction from Optical Emission Spectroscopy Data

This paper proposes max separation clustering (MSC), a new non-hierarchical clustering method used for feature extraction from optical emission spectroscopy (OES) data for plasma etch process control applications. OES data is high dimensional and inherently highly redundant with the result that it is difficult if not impossible to recognize useful features and key variables by direct visualization. MSC is developed for clustering variables with distinctive patterns and providing effective pattern representation by a small number of representative variables. The relationship between signal-to-noise ratio (SNR) and clustering performance is highlighted, leading to a requirement that low SNR signals be removed before applying MSC. Experimental results on industrial OES data show that MSC with low SNR signal removal produces effective summarization of the dominant patterns in the data.

A sequential algorithm for sparse support vector classifiers

Support vector machines (SVMs), though accurate, are not preferred in applications requiring high classification speed or when deployed in systems of limited computational resources, due to the large number of support vectors involved in the model. To overcome this problem we have devised a primal SVM method with the following properties: (1) it solves for the SVM representation without the need to invoke the representer theorem, (2) forward and backward selections are combined to approach the final globally optimal solution, and (3) a criterion is introduced for identification of support vectors leading to a much reduced support vector set. In addition to introducing this method the paper analyzes the complexity of the algorithm and presents test results on three public benchmark problems and a human activity recognition application. These applications demonstrate the effectiveness and efficiency of the proposed algorithm.


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Development of a solid-phase extraction coupling chemiluminescent enzyme immunoassay for determination of organophosphorus pesticides in environmental water samples

Solid-phase extraction (SPE) and direct competitive chemiluminescence enzyme immunoassay (dcCL-EIA) were combined for the detection of organophosphorus pesticides (OPs) in environmental water samples. dcCL-EIA based on horseradish peroxidase labeled with a broad-specificity monoclonal antibody against OPs was developed, and the effects of several physicochemical parameters on dcCL-EIA performance were studied. SPE was used for the pretreatment of water samples to remove interfering substances and to concentrate the OP analytes. The coupling of SPE and dcCL-EIA can detect seven OPs (parathion, coumaphos, phoxim, quinalphos, triazophos, dichlofenthion, and azinphos-ethyl) with the limit of quantitation below 0.1 ng/mL. The recoveries of OPs from spiked water samples ranged from 62.5% to 131.7% by SPE-dcCL-EIA and 69.5% to 112.3% by SPE-HPLC-MS/MS. The screening of OP residues in real-world environmental water samples by the developed SPE-dcCL-EIA and their confirmatory analysis using SPE-HPLC-MS/MS demonstrated that the assay is ideally suited as a monitoring method for OP residues prior to chromatographic analysis.

Improving molecular detection of Candida DNA in whole blood:comparison of seven fungal DNA extraction protocols using real-time PCR

The limitations of classical diagnostic methods for invasive Candida infections have led to the development of molecular techniques such as real-time PCR to improve diagnosis. However, the detection of low titres of Candida DNA in blood from patients with candidaemia requires the use of extraction methods that efficiently lyse yeast cells and recover small amounts of DNA suitable for amplification. In this study, a Candida-specific real-time PCR assay was used to detect Candida albicans DNA in inoculated whole blood specimens extracted using seven different extraction protocols. The yield and quality of total nucleic acids were estimated using UV absorbance, and specific recovery of C. albicans genomic DNA was estimated quantitatively in comparison with a reference (Qiagen kit/lyticase) method currently in use in our laboratory. The extraction protocols were also compared with respect to sensitivity, cost and time required for completion. The TaqMan PCR assay used to amplify the DNA extracts achieved high levels of specificity, sensitivity and reproducibility. Of the seven extraction protocols evaluated, only the MasterPure yeast DNA extraction reagent kit gave significantly higher total nucleic acid yields than the reference method, although nucleic acid purity was highest using either the reference or YeaStar genomic DNA kit methods. More importantly, the YeaStar method enabled C. albicans DNA to be detected with highest sensitivity over the entire range of copy numbers evaluated, and appears to be an optimal method for extracting Candida DNA from whole blood.

Synthesis of caffeic acid and p-hydroxybenzoic acid molecularly imprinted polymers and their application for the selective extraction of polyphenols from olive mill waste waters

Using caffeic acid and p-hydroxybenzoic acid as templates, two molecularly imprinted polymers (MIPs) were prepared that were used for isolation of polyphenols from olive mill waste water samples (OMWWs) without previous pre-treatment. For the preparation of the caffeic acid MIPs 4-vinylpyridine, allylurea, allylaniline and methacrylic acid were tested as functional monomers, ethylene glycol dimethylacrylate (EDMA), pentaerythritol trimethylacrylate (PETRA) and divinylbenzene 80 (DVB80) as cross-linkers and tetrahydrofuran as porogen. For p-hydroxybenzoic acid 4-vinylpyridine, allylurea and allylaniline were tested as functional monomers, EDMA and PETRA as cross-linkers and acetonitrile as porogen. The performance of the synthesized polymers was evaluated against seven structurally related compounds by means of polymer-based HPLC. The two polymers that presented the most interesting properties were further evaluated by batch rebinding and from the derived isotherms their capacity and binding strength were determined. Using solid-phase extraction (SPE), their ability to recognize and bind the template molecule from an aqueous solution as well as the pH dependence of the binding strength were explored. After establishing the best SPE protocol, an aqueous model mixture of compounds and a raw OMWWs sample were loaded on the two best polymers. The result of the consecutive use of the two polymers on the same sample was explored. It was concluded that acidic conditions favour the recognition abilities of both polymers and that they can be used for a quick and efficient isolation of the polyphenol fraction directly from raw OMWW.

Selective solid-phase extraction sorbent for caffeine made by molecular imprinting

A molecularly imprinted polymer (MIP) was prepared with caffeine as the template molecule. Thermal polymerisation (60°C) was optimised, varying ratios of monomer, cross linker and template. The polymer was used as a solid-phase extraction (SPE) sorbent, for selective trapping and pre-concentration of caffeine. Caffeine was loaded on the MIP-SPE cartridge using different loading conditions (solvents, pH value). Washing and elution of the caffeine bound to the MIP was studied utilising different protocols. The extraction protocol was successfully applied to the direct extraction of caffeine from beverages and spiked human plasma.

Preparation of a molecularly imprinted polymer for the solid-phase extraction of scopolamine with hyoscyamine as a dummy template molecule

Molecularly imprinted polymers (MIPs) selective for scopolamine were produced using hyoscyamine (a close structural analogue) as template molecule. The produced polymers were used as media for solid-phase extraction, exhibiting selective binding properties for the analyte from biological samples. Human and calf urine and serum were processed on the MIP under various extraction protocols. The best performance was observed after loading the analyte in aqueous environment facilitating retention on the MIP by non-selective hydrophobic interactions. The MIPs were subsequently washed using an optimised solvent system to enable selective desorption of the analyte. Other related and non-related compounds were accessed to evaluate molecular recognition properties. Recoveries of up to 79% were achieved for the analyte of interest from biological samples.

Dioxouranium(VI) extraction in microchannels using ionic liquids

The extraction of uranium(VI) from aqueous nitric acid solutions by tributylphosphate {TBP; 30%(v/v)} dissolved in the ionic liquid 1-butyl-3-methylimidazolium bis{(trifluoromethyl)sulfonyl}amide was investigated. The experiments were performed in a Teflon microchannel of 0.5 mm internal diameter, while the dioxouranium(VI) concentrations in the aqueous and the ionic liquid phases were determined by UV-Vis spectroscopy. The effects of initial nitric acid concentration (0.01-3 M), residence time, and phase flow rate ratio were studied. It was found that, with increasing nitric acid concentration, the percentage of dioxouranium(VI) extracted decreased and then increased again, while the extraction efficiency followed a slightly different trend. Overall mass transfer coefficients varied between 0.049 s and 0.312 s . © 2012 Elsevier B.V. All rights reserved.