Consistent and Flexible Selectivity Estimation for High-dimensional Data

Selectivity estimation aims at estimating the number of database objects that satisfy a selection criterion. Answering this problem accurately and efficiently is essential to many applications, such as density estimation, outlier detection, query optimization, and data integration. The estimation problem is especially challenging for large-scale high-dimensional data due to the curse of dimensionality, the large variance of selectivity across different queries, and the need to make the estimator consistent (i.e., the selectivity is non-decreasing in the threshold). We propose a new deep learning-based model that learns a query-dependent piecewise linear function as selectivity estimator, which is flexible to fit the selectivity curve of any query object and threshold, while guaranteeing that the output is non-decreasing in the threshold. To improve the accuracy for large datasets, we propose to partition the dataset into multiple disjoint subsets and build a local model on each of them. We perform experiments on real datasets and show that the proposed model significantly outperforms state-of-the-art models in accuracy and is competitive in efficiency

Intramolecular Torque, an Indicator of the Internal Rotation Direction of Rotor Molecules and Similar Systems

Torque is ubiquitous in many molecular systems, including collisions, chemical reactions, vibrations, electronic excitations and especially rotor molecules. We present a straightforward theoretical method based on forces acting on atoms and obtained from atomistic quantum mechanics calculations, to quickly and qualitatively determine whether a molecule or sub-unit thereof has a tendency to rotation and, if so, around which axis and in which sense: clockwise or counterclockwise. The method also indicates which atoms, if any, are predominant in causing the rotation. Our computational approach can in general efficiently provide insights into the rotational ability of many molecules and help to theoretically screen or modify them in advance of experiments or before analyzing their rotational behavior in more detail with more extensive computations guided by the results from the torque approach. As an example, we demonstrate the effectiveness of the approach using a specific light-driven molecular rotary motor which was successfully synthesized and analyzed in prior experiments and simulations.Comment: 11 pages, 4 figures, 1 SI fil

Method of determining cosmological parameter ranges with samples of candles with an intrinsic distribution

In this paper, the effect of the intrinsic distribution of cosmological candles is investigated. We find that, in the case of a narrow distribution, the deviation of the observed modulus of sources from the expected central value could be estimated within a ceratin range. We thus introduce a lower and upper limits of $\chi ^{2}$, $\chi_{\min}^{2}$ and $\chi_{\max}^{2}$, to estimate cosmological parameters by applying the conventional minimizing $\chi ^{2}$ method. We apply this method to a gamma-ray burst (GRB) sample as well as to a combined sample including this GRB sample and an SN Ia sample. Our analysis shows that: a) in the case of assuming an intrinsic distribution of candles of the GRB sample, the effect of the distribution is obvious and should not be neglected; b) taking into account this effect would lead to a poorer constraint of the cosmological parameter ranges. The analysis suggests that in the attempt of constraining the cosmological model with current GRB samples, the results tend to be worse than what previously thought if the mentioned intrinsic distribution does exist.Comment: 6 pages,4 figures,1 tables.Data updated. Main conclusion unchange

Sphingosine kinase 2 activates autophagy and protects neurons against ischemic injury through interaction with Bcl-2 via its putative BH3 domain

Our previous findings suggest that sphingosine kinase 2 (SPK2) mediates ischemic tolerance and autophagy in cerebral preconditioning. The aim of this study was to determine by which mechanism SPK2 activates autophagy in neural cells. In both primary murine cortical neurons and HT22 hippocampal neuronal cells, overexpression of SPK2 increased LC3II and enhanced the autophagy flux. SPK2 overexpression protected cortical neurons against oxygen glucose deprivation (OGD) injury, as evidenced by improvement of neuronal morphology, increased cell viability and reduced lactate dehydrogenase release. The inhibition of autophagy effectively suppressed the neuroprotective effect of SPK2. SPK2 overexpression reduced the co-immunoprecipitation of Beclin-1 and Bcl-2, while Beclin-1 knockdown inhibited SPK2-induced autophagy. Both co-immunoprecipitation and GST pull-down analysis suggest that SPK2 directly interacts with Bcl-2. SPK2 might interact to Bcl-2 in the cytoplasm. Notably, an SPK2 mutant with L219A substitution in its putative BH3 domain was not able to activate autophagy. A Tat peptide fused to an 18-amino acid peptide encompassing the native, but not the L219A mutated BH3 domain of SPK2 activated autophagy in neural cells. The Tat-SPK2 peptide also protected neurons against OGD injury through autophagy activation. These results suggest that SPK2 interacts with Bcl-2 via its BH3 domain, thereby dissociating it from Beclin-1 and activating autophagy. The observation that Tat-SPK2 peptide designed from the BH3 domain of SPK2 activates autophagy and protects neural cells against OGD injury suggest that this structure may provide the basis for a novel class of therapeutic agents against ischemic stroke

Sky Subtraction for LAMOST

Sky subtraction is the key technique in data reduction of multi-fiber spectra. Knowledge of the related instrument character is necessary to determine the method adopted in sky subtraction. In this study, we described the sky subtraction method designed for LAMOST(Large sky Area Multi-Object fiber Spectroscopic Telescope) survey. The method has been intergrated into LAMOST 2D Pipeline v2.6 and applied to data of LAMOST DR3 and later. For LAMOST, sky emission line calibration is used to alleviate the position-dependent (thus time-dependent) ~4% fiber throughput uncertainty and the small wavelength instability (0.1\AA ) during observation. PCA (Principal Component Analysis) sky subtraction further reduces 25% of the sky line residual of the OH lines in the red part of the LAMOST spectra after the mater sky spectrum, which is derived from a B-spline fit of 20 sky fibers in each spectrograph, is adjusted by sky emission line and subtracted from each fiber. Further analysis shows that our wavelength calibration accuracy is about 4.5km/s, and the average sky subtraction residuals are about 3% for sky emission lines and 3% for continuum region. The relative sky subtraction residuals vary with the moon light background brightness, could reach as low as 1.5% for the sky emission line regions in the dark night. Tests on the F stars of both similar sky emission line strength and similar object continuum intensity show that the sky emission line residual of LAMOST is smaller than those of SDSS survey.Comment: 28 pages, 13 figures, 2 tables, accepted by RA