Miracle-dz/UniFAR-FTUs huggingface dataset:
SPARQL basic graph pattern processing with iterative MapReduce

There have been a number of approaches to adopt the RDF data model and the MapReduce framework for a data warehouse, as the data model is suitable for data integration and the data processing framework is good for large-scale fault-tolerant data analyses. Nevertheless, most approaches consider the data model and the framework separately. It has been difficult to create synergy because there have been only a few algorithms which connects the data model and the framework. In this paper, we offer a general and efficient MapReduce algorithm for SPARQL Basic Graph Pattern which is a set of triple patterns to be joined. In a MapReduce world, it is known that the join operation requires computationally expensive MapReduce iterations. For this reason, we minimize the number of iterations with the followings. First, we adopt traditional multi-way join into MapReduce instead of multiple individual joins. Second, by analyzing a given query, we select a good join-key to avoid unnecessary iterations. As a result, the algorithm shows good performance and scalability in terms of time and data size.
The Roles of Short-Run and Long-Run Volatility Factors in Options Market: A Term Structure Perspective

This paper examines the option pricing implications of short-run and long-run volatility factors, which are assumed to be driven by short-run and long-run news events, respectively. Using a comprehensive dataset of S&P 500 index options over 1993-2008, I find that the proposed two-factor volatility models have two desirable properties that help capture the term structures of option-implied volatility and skewness. First, the options data show evidence of time-variation in the long-run expectation of volatility, which may be caused by long-run news events. While this feature is inconsistent with a single-factor volatility assumption, the two-factor volatility models do a good job of matching the entire term structure of implied volatility. Second, the options data reveal that the term structure of implied skewness is nearly flat on average. This feature is hard to reconcile with single-factor volatility models and jumps in returns. In contrast, I find that the two-factor volatility models can generate flat term structures much like those seen in the data. In particular, the short-run volatility factor is dominant in generating short-term skewness, while the long-run volatility factor plays a pivotal role in generating long-term skewness.
Characterization of a C—C Bond Hydrolase from Sphingomonas wittichii RW1 with Novel Specificities towards Polychlorinated Biphenyl Metabolites

ABSTRACT Sphingomonas wittichii RW1 degrades chlorinated dibenzofurans and dibenzo-p-dioxins via meta cleavage. We used inverse PCR to amplify dxnB2, a gene encoding one of three meta-cleavage product (MCP) hydrolases identified in the organism that are homologues of BphD involved in biphenyl catabolism. Purified DxnB2 catalyzed the hydrolysis of 8-OH 2-hydroxy-6-oxo-6-phenylhexa-2,4-dienoate (HOPDA) approximately six times faster than for HOPDA at saturating substrate concentrations. Moreover, the specificity of DxnB2 for HOPDA (k cat/Km = 1.2 × 107 M−1 s−1) was about half that of the BphDs of Burkholderia xenovorans LB400 and Rhodococcus globerulus P6, two potent polychlorinated biphenyl (PCB)-degrading strains. Interestingly, DxnB2 transformed 3-Cl and 4-OH HOPDAs, compounds that inhibit the BphDs and limit PCB degradation. DxnB2 had a higher specificity for 9-Cl HOPDA than for HOPDA but a lower specificity for 8-Cl HOPDA (k cat/Km = 1.7 × 106 M−1 s−1), the chlorinated analog of 8-OH HOPDA produced during dibenzofuran catabolism. Phylogenetic analyses based on structure-guided sequence alignment revealed that DxnB2 belongs to a previously unrecognized class of MCP hydrolases, evolutionarily divergent from the BphDs although the physiological substrates of both enzyme types are HOPDAs. However, both classes of enzymes have mainly small hydrophobic residues lining the subsite that binds the C-6 phenyl of HOPDA, in contrast to the bulky hydrophobic residues (Phe106, Phe135, Trp150, and Phe197) found in the class II enzymes that prefer substrates possessing a C-6 alkyl. Thr196 and/or Asn203 appears to be an important determinant of specificity for DxnB2, potentially forming hydrogen bonds with the 8-OH substituent. This study demonstrates that the substrate specificities of evolutionarily divergent hydrolases may be useful for degrading mixtures of pollutants, such as PCBs.
Deconstructing multi-sensory enhancement 2 in detection

5 The mechanisms responsible for the integration of sensory information from different modali6 ties have become a topic of intense interest in psychophysics and neuroscience. Many authors 7 now claim that early, sensory-based cross-modal convergence improves performance in detection 8 tasks. An important strand of supporting evidence for this claim is based on statistical models 9 such as the Pythagorean model or the probabilistic summation model. These models establish 10 statistical benchmarks representing the best predicted performance under the assumption that 11 there are no interactions between the two processing paths. Following this logic, when observed 12 detection performances surpass the predictions of these models, it is often inferred that such 13 improvement indicates early cross-modal convergence. We present a theoretical analyses scru14 tinizing some of these models and the statistical criteria most frequently used to infer early 15 cross-modal interactions during detection tasks. Our current analysis shows how common mis16 interpretations of these models lead to their inadequate use and, in turn, to contradictory results 17 and misleading conclusions. To further illustrate the latter point, we introduce a model that 18 accounts for detection performances in multimodal detection tasks, but for which surpassing of 19 the Pythagorean or probabilistic summation benchmark can be explained without resorting to 20 early sensory interactions. Finally, we report three experiments that put our theoretical inter21 pretation to the test, and further clarify how to adequately measure multimodal interactions in 22 audio-tactile detection tasks. 23
Strong magnetophonon resonance induced triple G-mode splitting in graphene on graphite probed by micromagneto Raman spectroscopy

The resonance between the G-band phonon excitation and Landau level optical transitions in graphene has been systematically studied by micromagneto Raman mapping. In purely decoupled graphene regions on a graphite substrate, eight traces of anticrossing spectral features with G-mode peaks are observed as a function of magnetic ﬁelds up to 9 T, and these traces correspond to either symmetric or asymmetric Landau level transitions. Three distinct split peaks of the G mode, named G − , G i , and G + , are observed at the strong magnetophonon resonance condition corresponding to a magnetic ﬁeld of ∼ 4.65 T. These three special modes are attributed to (i) the coupling between the G phonon and the magneto-optical transitions, which is responsible for G + and G − and can be well described by the two coupled mode model and (ii) the magnetic ﬁeld-dependent oscillation of the G i band, which is currently explained by the G band of graphite modiﬁed by the interaction with G + and G − . The pronounced interaction between Dirac fermions and phonons demonstrates a dramatically small Landau level width ( ∼ 1.3 meV), which is a signature of the ultrahigh quality graphene obtained on the surface of graphite.
Association of Cystatin C With Left Ventricular Structure and Function: The Dallas Heart Study

Background—Cystatin C, a novel marker of renal function, has been associated with heart failure and cardiovascular mortality in older individuals. We tested the hypothesis that cystatin C is associated with preclinical cardiac structural and functional abnormalities in a younger population-based sample. Methods and Results—The study included participants in the Dallas Heart Study (ages 30 to 65 years) who had measurements of cystatin C and cardiac MRI. The associations of cystatin C with left ventricular (LV) mass, LV end-systolic and -diastolic volumes, concentricity (LV mass/LV end-diastolic volume), LV wall thickness, and LV ejection fraction were evaluated. Cystatin C levels ranged from 0.46 to 6.55 mg/L. In univariable analyses, increasing levels of cystatin C correlated with higher LV mass, concentricity, and wall thickness (P<0.001), but not with LV end-systolic volume, LV end-diastolic volume, or LV ejection fraction. After adjustment with traditional covariates and estimated glomerular filtration rate by the modification of diet in renal disease formula, log-transformed cystatin C remained independently associated with LV mass (P<0.001), concentricity (P=0.027), and wall thickness (P<0.001). These associations persisted when creatinine or estimated glomerular filtration rate by the Cockcroft-Gault formula were included in the models. Conclusions—Higher levels of cystatin C were associated with increased LV mass and a concentric LV hypertrophy phenotype. These findings were independent of potential confounding variables including standard measurements of renal function, supporting the hypothesis that cystatin C may be useful to identify individuals with preclinical structural heart abnormalities.
Incorporating Both Undesirable Outputs and Uncontrollable Variables into Dea: the Performance of Chinese Coal-fired Power Plants Incorporating Both Undesirable Outputs and Uncontrollable Variables into Dea: the Performance of Chinese Coal-fired Power Plants

There are two difficulties in doing an objective evaluation of the performance of decision-making units (DMUs). The first one is how to treat undesirable outputs jointly produced with the desirable outputs, and the second one is how to treat uncontrollable variables, which often capture the impact of the operating environment. Given difficulties in both model construction and data availability, very few published papers simultaneously consider the above two problems. This article attempts to do so by proposing six DEA-based performance evaluation models based on a research sample of the Chinese coal-fired power plants. The finding of this paper not only contributes for the performance measurement methodology, but also has policy implications for the Chinese coal-fired power sector.
An automatic wave detection algorithm applied to Pc1 pulsations in California, and results of a 6-year statistical survey

[1] A new technique designed to automatically identify and characterize waves in three-axis data is presented, which can be applied in a variety of settings, including triaxial ground-magnetometer data or satellite wave data (particularly when transformed to a field-aligned coordinate system). This technique is demonstrated on a single Pc1 event recorded on a triaxial search coil magnetometer in Parkfield, California (35.945°,−120.542°), and then applied to a 6-month period between 1 June 2003 and 31 December 2003. The technique begins with the creation of a standard dynamic spectrogram and consists of three steps: (1) for every column of the spectrogram (which represents the spectral content of a short period in the time series), spectral peaks are identified whose power content significantly exceeds the ambient noise; (2) the series of spectral peaks from step 1 are grouped into continuous blocks representing discrete wave events using a “spectral-overlap” criterion; and (3) for each identified event, wave parameters (e.g., wave normal angles, polarization ratio) are calculated which can be used to check the continuity of individual identified wave events or to further filter wave events (e.g., by polarization ratio).
Frequency and Characteristics of Infections Caused by Extended-Spectrum Beta-Lactamase-Producing Organisms in Neonates: A Prospective Cohort Study

This prospective cohort study was conducted to determine the frequency of infections caused by extended-spectrum beta-lactamase- (ESBL-) producing organisms, various bacteria producing ESBL, antibiotic susceptibility of these organisms, and the risk factors associated with these infections in a neonatal intensive care unit in a tertiary care hospital in North India. Of the 150 neonates enrolled in the study, 47 culture-positive neonates were included in the study cohort and were divided into two groups: ESBL-positive (8 neonates) and ESBL-negative (39 neonates) cohorts. Various organisms were isolated from 72 culture samples in these 47 neonates. Of these, 10 culture samples grew ESBL-positive organisms and 62 samples grew ESBL-negative organisms. The frequency of ESBL-producing organisms was found to be 5.3%. ESBL infection incidence densities were found to be 3.4 per 1000 patient-days. Klebsiella (60%) was the most common organism producing ESBL followed by Escherichia coli (30%) and Pseudomonas (10%). Eighty percent of the ESBL-producing organisms were sensitive to piperacillin-tazobactam. Risk factors found significant by univariate analysis (P < 0.05) were preterm, low birthweight, perinatal asphyxia, respiratory distress syndrome, anaemia, metabolic acidosis, prolonged mechanical ventilation (>7 days), length of hospitalization, length of level 3 stay, prior antibiotic use, central venous catheter duration, peripherally inserted central venous catheter duration, and total parenteral nutrition duration. Factors that retained significance in the logistic regression model were duration of hospital stay (adjusted OR: 0.958, CI: 0.920–0.997, and P value = 0.037) and gestational age (adjusted OR: 1.39, CI: 1.037–1.865, and P value = 0.028). There was no significant difference in the mortality between the two groups.
Histological and immunohistochemical characterization of feline renal cell carcinoma: a case series

Four feline renal cell carcinomas (RCCs) were examined using histopathological and immunohistochemical procedures. Specimens were classified by predominant histological pattern according to WHO criteria. A panel of antibodies including β-catenin, C-KIT, VEGF and VEGF-R2 and double immunostaining for vimentin/cytokeratin and for E-cadherin/CD10 was selected to characterize the tumors. Neoplasms were classified as tubular (3/4) and papillary (1/4). Neoplastic epithelial cells were cytokeratin, vimentin, E-cadherin, VEGF-R2 positive and C-KIT negative; 3 cases were β-catenin positive, whereas only 2 tumors were CD10 and VEGF positive. No correlation with histotype was evident. Our results confirm the low frequency of RCCs in cats and suggest a histological pattern similar to canine RCCs. In contrast, a peculiar immunohistochemical profile different from both canine and human RCCs is identified.
An Efficient Object Tracking Algorithm in Wireless Sensor Networks

In this paper, we develop a heuristic algorithm to construct an efficient object tracking in wireless sensor networks (WSNs). Such wireless sensor network has to be designed to achieve efficient object tracking for given arbitrary topology of wireless sensor networks. We consider the two-way object moving frequency of each pair of sensor nodes and link transmission cost. This problem is formulated as 0/1 integerprogramming problem. A Lagrangean Relaxationbased (LR-based) heuristic algorithm is proposed for solving the optimization problem. The experimental results showed that the proposed algorithm gets a near optimization in the efficient object tracking. Furthermore, the algorithm is very efficient and scalable in terms of the solution time.
A Common Origin for Quasar Extended Emission-Line Regions and Their Broad-Line Regions

We present a correlation between the presence of luminous extended emission-line regions (EELRs) and the metallicity of the broad-line regions (BLRs) of low-redshift quasars. The result is based on ground-based [O III] λ5007 narrowband imaging and Hubble Space Telescope UV spectra of 12 quasars at 0.20 ≤ z ≤ 0.45. Quasars showing luminous EELRs have low-metallicity BLRs (Z ≲ 0.6 Z☉), while the remaining quasars show typical metal-rich gas (Z > Z☉). Previous studies have shown that EELRs themselves also have low metallicities (Z ≲ 0.5 Z☉). The correlation between the occurrence of EELRs and the metallicity of the BLRs, strengthened by the subsolar metallicity in both regions, indicates a common external origin for the gas, almost certainly from the merger of a gas-rich galaxy. Our results provide the first direct observational evidence that the gas from a merger can indeed be driven down to the immediate vicinity (<1 pc) of the central black hole.
Core Microbiota and Metabolome of Vitis vinifera L. cv. Corvina Grapes and Musts

The composition and changes of the fungal population and of the metabolites present in grapes and in ferments of Vitis vinifera L. cv. Corvina, one of the major components of the Amarone musts, were dissected aiming at the identification of constant characteristics possibly influenced by the productive process. The fungal populations and metabolomic profiles were analyzed in three different vintages. 454-pyrosequencing on the ribosomal ITS1 region has been used to identify the fungal population present in Corvina grapes and fresh must. Samples were also subjected to metabolomics analysis measuring both free volatile compounds and glycosylated aroma precursors through an untargeted approach with comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry. Albeit strongly dependent on the climate, both the mycobiota and metabolome of Corvina grapes and fresh musts show some characteristics recursive in different vintages. Such persistent characteristics are likely determined by the method adopted to produce Amarone or other dry wines made from partially dried grapes. In particular, the harsh conditions imposed by the prolonged withering appear to contribute to the shaping of the fungal populations. The fungal genera and metabolites present in different vintages in V. vinifera L. cv. Corvina grapes and fresh musts represent core components of the peculiar technique of production of Amarone. Their identification allows the in-depth understanding and improved control of the process of production of this economically and culturally relevant wine.
On the efficiency and reliability of cluster mass estimates based on member galaxies

Aims. We study the efficiency and reliability of cluster mass estimators that are based on the projected phase-space distribution of galaxies in a cluster region. Methods. We analyse a data-set of 62 clusters extracted from a concordance Λ CDM cosmological hydrodynamical simulation. We consider both dark matter (DM) particles and simulated galaxies as tracers of the clusters gravitational potential. Two cluster mass estimators are considered: the virial mass estimator, corrected for the surface-pressure term, and a mass estimator (that we call $M_{\sigma}$) based entirely on the velocity dispersion estimate of the cluster. In order to simulate observations, galaxies (or DM particles) are first selected in cylinders of given radius (from 0.5 to 1.5 h -1 Mpc) and $\simeq$$200h^{-1}$ Mpc length. Cluster members are then identified by applying a suitable interloper removal algorithm. Results. The virial mass estimator overestimates the true mass by $\simeq$10% on average, for sample sizes of $\ga$60 cluster members. For similar sample sizes, $M_{\sigma}$ underestimates the true mass by $\simeq$15%, on average. For smaller sample sizes, the bias of the virial mass estimator substantially increases, while the $M_{\sigma}$ estimator becomes essentially unbiased. The dispersion of both mass estimates increases by a factor ~2 as the number of cluster members decreases from ~400 to ~20. It is possible to reduce the bias in the virial mass estimates either by removing clusters with significant evidence for subclustering or by selecting early-type galaxies, which substantially reduces the interloper contamination. Early-type galaxies cannot however be used to improve the $M_{\sigma}$ estimates since their intrinsic velocity distribution is slightly biased relative to that of the DM particles. Radially-dependent incompleteness can drastically affect the virial mass estimates, but leaves the $M_{\sigma}$ estimates almost unaffected. Other observational effects, like centering and velocity errors and different observational apertures, have little effect on the mass estimates.
Neuroprotective Effects of Propofol in a Model of Ischemic Cortical Cell Cultures: Role of Glutamate and Its Transporters

Background During cerebral ischemia, excess of glutamate release and dysfunction of its high affinity transport induce an accumulation of extracellular glutamate, which plays an important role in neuronal death. The authors studied the relationship among propofol neuroprotection, glutamate extracellular concentrations, and glutamate transporter activity in a model of ischemic cortical cell cultures. Methods Thirteen-day-old primary cortical neuronal-glial cultures were exposed to a 90-min combined oxygen–glucose deprivation (OGD) in an anaerobic chamber, followed by reoxygenation. Propofol was added only during the OGD period, and its effect was compared to that of the N-methyl-d-aspartate receptor antagonist dizocilpine (MK-801). Twenty-four hours after the injury, cell death was quantified by lactate dehydrogenase release and cell viability by reduction of 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT). Extracellular concentrations of glutamate in culture supernatants and glutamate uptake were performed at the end of OGD period by high-performance liquid chromatography and incorporation of l-[3H]glutamate into cells, respectively. Results At clinically relevant concentrations (0.05–10 &mgr;m), propofol offered protection equivalent to that of MK-801. It significantly reduced lactate dehydrogenase release and increased the reduction of MTT. At the end of the ischemic injury, propofol was able to reverse the OGD-induced increase in glutamate extracellular concentrations and decrease of glutamate uptake. The inhibition of the glial GLT1 transporter by 3-methyl-glutamate did not further modify the effect of propofol on glutamate uptake, suggesting that GLT1 was not the major target of propofol. Conclusion Propofol showed a neuroprotective effect in this in vitro model of OGD, which was apparently mediated by a GLT1-independent restoration of the glutamate uptake impaired during the injury.
Glutamate Racemase Is the Primary Target of β-Chloro-d-Alanine in Mycobacterium tuberculosis

ABSTRACT The increasing global prevalence of drug resistance among many leading human pathogens necessitates both the development of antibiotics with novel mechanisms of action and a better understanding of the physiological activities of preexisting clinically effective drugs. Inhibition of peptidoglycan (PG) biosynthesis and cross-linking has traditionally enjoyed immense success as an antibiotic target in multiple bacterial pathogens, except in Mycobacterium tuberculosis, where it has so far been underexploited. d-Cycloserine, a clinically approved antituberculosis therapeutic, inhibits enzymes within the d-alanine subbranch of the PG-biosynthetic pathway and has been a focus in our laboratory for understanding peptidoglycan biosynthesis inhibition and for drug development in studies of M. tuberculosis. During our studies on alternative inhibitors of the d-alanine pathway, we discovered that the canonical alanine racemase (Alr) inhibitor β-chloro–d-alanine (BCDA) is a very poor inhibitor of recombinant M. tuberculosis Alr, despite having potent antituberculosis activity. Through a combination of enzymology, microbiology, metabolomics, and proteomics, we show here that BCDA does not inhibit the d-alanine pathway in intact cells, consistent with its poor in vitro activity, and that it is instead a mechanism-based inactivator of glutamate racemase (MurI), an upstream enzyme in the same early stage of PG biosynthesis. This is the first report to our knowledge of inhibition of MurI in M. tuberculosis and thus provides a valuable tool for studying this essential and enigmatic enzyme and a starting point for future MurI-targeted antibacterial development.