Parallel and scalable processing of spatio-temporal RDF queries using Spark

The ever-increasing size of data emanating from mobile devices and sensors, dictates the use of distributed systems for storing and querying these data. Typically, such data sources provide some spatio-temporal information, alongside other useful data. The RDF data model can be used to interlink and exchange data originating from heterogeneous sources in a uniform manner. For example, consider the case where vessels report their spatio-temporal position, on a regular basis, by using various surveillance systems. In this scenario, a user might be interested to know which vessels were moving in a specific area for a given temporal range. In this paper, we address the problem of efficiently storing and querying spatio-temporal RDF data in parallel. We specifically study the case of SPARQL queries with spatio-temporal constraints, by proposing the DiStRDF system, which is comprised of a Storage and a Processing Layer. The DiStRDF Storage Layer is responsible for efficiently storing large amount of historical spatio-temporal RDF data of moving objects. On top of it, we devise our DiStRDF Processing Layer, which parses a SPARQL query and produces corresponding logical and physical execution plans. We use Spark, a well-known distributed in-memory processing framework, as the underlying processing engine. Our experimental evaluation, on real data from both aviation and maritime domains, demonstrates the efficiency of our DiStRDF system, when using various spatio-temporal range constraints.

     

On the discovery of subsumption relations for the alignment of ontologies

For the effective alignment of ontologies, the subsumption mappings between the elements of the source and target ontologies play a crucial role, as much as equivalence mappings do. This paper presents the “Classification-Based Learning of Subsumption Relations” (CSR) method for the alignment of ontologies. Given a pair of two ontologies, the objective of CSR is to learn patterns of features that provide evidence for the subsumption relation among concepts, and thus, decide whether a pair of concepts from these ontologies is related via a subsumption relation. This is achieved by means of a classification task, using state of the art supervised machine learning methods. The paper describes thoroughly the method, provides experimental results over an extended version of benchmarking series of both artificially created and real world cases, and discusses the potential of the method.     

On the survivability and pyrosynthesis of PAH during combustion of pulverized coal and tire crumb

Results are presented on the emissions of semivolatile polycyclic aromatic hydrocarbons (PAH) from the combustion of a pulverized bituminous coal and ground waste automobile tires. Streams of fuel particles were injected at steady-state steady-flow conditions, and burned inside an isothermal drop-tube furnace, in air, at a gas temperature and gas residence time of 1150°C and 0.75 s, respectively. Combustion occurred under either very fuel-lean conditions (bulk equivalence ratio, φ < 0.5) or substantially fuel-rich conditions (φ = 1.6–1.9). Emissions from fuel pyrolysis, in the absence of oxygen, were also examined. The survivability of the fuel-PAHs during combustion/pyrolysis was assessed by examining the reactants (fuels) and the products of their oxidation/pyrolysis. The PAH species in the effluent of combustion were: 1) qualitatively compared with indigenous PAH constituents of the input fuels, and 2) quantitatively contrasted with known amounts of deuterium-labeled PAH standards, which were absorbed on the input fuels. No PAHs were detected in the effluent of combustion of either fuel under sufficiently fuel-lean conditions, e.g., φ < 0.5. This indicated that the PAH constituents of the input fuels, either indigenous or adsorbed, as well as those formed by pyrosynthesis in either the diffusion volatile flames or during the heterogeneous oxidation of the chars were destroyed. Significant amounts of PAHs were detected in the effluent of the combustion of both fuels under sufficiently fuel-rich conditions, e.g., φ > 1.6 and, especially, under pyrolytic conditions in N₂. These PAHs were mostly attributed to pyrosynthesis since none of the deuterated PAHs, adsorbed on the fuels, survived the combustion process. Small amounts of the labeled compounds, however, survived under purely pyrolytic conditions. These results were confirmed with separate experiments, where deuterium-labeled PAH standards were adsorbed on highly porous calcium/magnesium oxide or mullite particles. Again, small amounts of some PAHs survived in high-temperature pyrolytic conditions, but none in oxidative environments. These observations suggest that pyrosynthesis is the major contributing mechanism to the PAH emissions from the combustion of these fuels. Survivability of parent PAHs may be a minor mechanism at very high equivalence ratios.

Finally, both fuels were mixed with powders of calcium magnesium acetate (CMA), calcium carbonate (CaCO₃), and calcium oxide (CaO), all of which are known sulfur reduction agents, at a molar Ca/S ratio of 1. Combustion of the fuels mixed with CMA or CaCO₃ generated enhanced amounts of PAHs, while combustion with CaO had no effect on the PAH emissions.     

Optical study of twin‐tanked ICS solar heaters combined with asymmetrical CPC‐type reflectors

The distribution of solar irradiance on the absorbing surface of a typical integrated collector storage (ICS) system combined with reflector troughs is commonly studied by means of ray tracing techniques. A conceptually different alternative is offered by the method of the average number of reflections (ANR). In the present work, the latter is employed for the systematic optical study of realistic ICS models. In all cases, the solar devices consist of twin cylindrical storage tanks which are mounted on top of stationary asymmetrical CPC‐type reflectors. The emphasis of the current research is mainly placed on the evaluation of the ANR reliability for the calculation of the optical efficiency of the related twin‐tanked devices. Additionally, useful operational parameters, such as the optical performance of the proposed geometries, are also determined. The behavior of the tested ICS systems reveals that the optical efficiency may vary in the range of 0.75 to 0.91, exhibiting a strong dependence on the geometric parameters of the solar devices. The highest efficiency is achieved by the systems which combine large reflecting area and storage tanks in close proximity.     

Quantification of N-(deoxyguanosin-8-yl)-4-aminobiphenyl adducts in human lymphoblastoid TK6 cells dosed with N-hydroxy-4-acetylaminobiphenyl and their relationship to mutation, toxicity, and gene expression profiling

Gene expression profiles that are anchored to phenotypic endpoints may lead to the identification of signatures that predict mutagenicity or carcinogenicity. The study presented here describes the analysis of DNA adducts in the human TK6 lymphoblastoid cell line after exposure to N-hydroxy-4-aminobiphenyl, a mutagenic metabolite of 4-aminobiphenyl. A validated nano-LC microelectrospray mass spectrometry assay is reported for the detection and quantification of N-(deoxyguanosin-8-yl)-4-aminobiphenyl (dG-C8-ABP), the principal DNA adduct of 4-aminobiphenyl. Limits of quantification, based on a signal-to-noise ratio of 10:1, are determined to correspond to approximately 27 fg of dG-C8-ABP injected on-column. The assay has been used to measure the steady-state levels of the adduct in the human TK6 lymphoblastoid cell line as a function of dose (0.5, 1.0, and 10.0 microM) and time (2, 6, and 27 h) after exposure to N-hydroxy-4-aminobiphenyl. The levels of dG-C8-ABP adducts in the cells, ranging from 18 to 500 adducts in 10(9) nucleotides, were then correlated to cell toxicity, induced mutation at the TK (thymidine kinase) and HPRT loci, and gene expression profiling through microarray analysis. Cell cultures were evaluated for toxicity by growth curve extrapolation, mutation assays were performed on the HPRT and TK loci, and gene expression profiles were generated by analyses using microarray technology. In the mutation assay analysis, as the toxicant concentration increased, there was an increase in mutation fraction, indicating a direct correlation to metabolite dosing level and mutations occurring at these two loci. Statistical analysis of the gene expression data determined that a total of 2250 genes exhibited statistically significant changes in expression after treatment with N-OH-AABP (P < 0.05). Among the genes identified, 2245 were up-regulated, whereas 5 genes that had functions in cell survival and cell growth and, hence, could be indicators of toxicity, were down-regulated relative to controls. The results demonstrate the value of anchoring gene expression patterns to phenotypic markers, such as DNA adduct levels, toxicity, and mutagenicity.     

Characterization of gas-phase molecular interactions on differential mobility ion behavior utilizing an electrospray ionization-differential mobility-mass spectrometer system

Differential mobility spectrometry (DMS) is a rapidly advancing technology for gas-phase ion separation. The interfacing of DMS with mass spectrometry (MS) offers potential advantages over the use of mass spectrometry alone. Such advantages include improvements to mass spectral signal/noise ratios, orthogonal/complementary ion separation to mass spectrometry, enhanced ion and complexation structural analysis, and potential for rapid analyte quantitation. The introduction of a new ESI-DMS-MS system and its utilization to aid in the understanding of DMS separation theory is described. A current contribution to DMS separation theory is one of an association/dissociation process between ions/molecules in the gas phase during the differential mobility separation. A model study was designed to investigate the molecular dynamics and chemical factors influencing the theorized association/dissociation process, and the mechanisms by which these gas-phase interactions affect an ion's DM behavior. Five piperidine analogues were selected as model analytes, and three alcohol drift gas dopants/modifiers were used to interrogate the analyte ions in the gas phase. Two proposed DMS separation mechanisms, introduced as Core and Fa?ade, corresponding to strong and weak attractions between ions/molecules in the gas phase, are detailed. The proposed mechanisms provide explanation for the observed changes in analyte separation by the various drift gas modifiers. Molecular modeling of the proposed mechanisms provides supportive data and demonstrates the potential for predictive optimization of analyte separation based on drift gas modifier effects.     

Metabolite identification using a nanoelectrospray LC-EC-array-MS integrated system

A novel approach to the parallel coupling of normal-bore high-performance liquid chromatography (LC) with electrochemical-array detection (EC-array) and nanoelectrospray mass spectrometry (MS), based on the use of a nanosplitting interface, is described where both detectors are utilized at their optimal detection mode for parallel configuration. The dual detection platform was shown to maintain full chromatographic integrity with retention times and peak widths at half-height between the EC-array and MS displaying high reproducibility with relative standard deviations of <2%. Detection compatibility between the two detectors at the part per billion level injected on-column was demonstrated using selected metabolites representative of the diversity typically encountered in physiological systems. Metabolites were detected with equal efficiency whether neat or in serum, demonstrating the system's ability to handle biological samples with limited sample cleanup and reduced concern for biological matrix effects. Direct quantification of known analytes from the EC-array signal using Faraday's law can eliminate the need for isotopically labeled internal standards. The system was successfully applied to the detection and characterization of metabolites of phenylbutyrate from serum samples of Huntington's disease patients in an example that illustrates the complementarity of the dual detection nanoelectrospray LC-EC-array-MS system.