A Photometric Study of Five Open Clusters in the SDSS

We present a photometric study of five open clusters (Czernik 5, Alessi 53, Berkeley 49, Berkeley 84, and Pfleiderer 3) in the Sloan Digital Sky Survey. The position and size of these clusters are determined using the radial number density profiles of the stars, and the member stars of the clusters are selected using the proper motion data in the literature. We estimate the reddening, distance, and age of the clusters based on the isochrone fitting in the color-magnitude diagram. The foreground reddenings for these clusters are estimated to be E(B-V) = 0.71 - 1.55 mag. The distances to these clusters are derived to be 2.0 - 4.4 kpc, and their distances from the Galactic center range from 7.57 kpc to 12.35 kpc. Their ages are in the range from 250 Myr to 1 Gyr. Berkeley 49 and Berkeley 84 are located in the Orion spur, Czernik 5 is in the Perseus arm, and Pfleiderer 3 and Alessi 53 are at beyond the Perseus arm.Comment: 18 pages, 21 figures, accepted for publication in JKA

Web Users\u27 Implicit Feedback Inference Based on Amount of Simple Interaction Logs at Browser Side

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Look at the First Sentence: Position Bias in Question Answering

Many extractive question answering models are trained to predict start and end positions of answers. The choice of predicting answers as positions is mainly due to its simplicity and effectiveness. In this study, we hypothesize that when the distribution of the answer positions is highly skewed in the training set (e.g., answers lie only in the k-th sentence of each passage), QA models predicting answers as positions can learn spurious positional cues and fail to give answers in different positions. We first illustrate this position bias in popular extractive QA models such as BiDAF and BERT and thoroughly examine how position bias propagates through each layer of BERT. To safely deliver position information without position bias, we train models with various de-biasing methods including entropy regularization and bias ensembling. Among them, we found that using the prior distribution of answer positions as a bias model is very effective at reducing position bias, recovering the performance of BERT from 37.48% to 81.64% when trained on a biased SQuAD dataset.Comment: 13 pages, EMNLP 202

Understanding β-Hairpin Formation by Molecular Dynamics Simulations of Unfolding

AbstractWe have studied the mechanism of formation of a 16-residue β-hairpin from the protein GB1 using molecular dynamics simulations in an aqueous environment. The analysis of unfolding trajectories at high temperatures suggests a refolding pathway consisting of several transient intermediates. The changes in the interaction energies of residues are related with the structural changes during the unfolding of the hairpin. The electrostatic energies of the residues in the turn region are found to be responsible for the transition between the folded state and the hydrophobic core state. The van der Waals interaction energies of the residues in the hydrophobic core reflect the behavior of the radius of gyration of the core region. We have examined the opposing influences of the protein-protein (PP) energy, which favors the native state, and the protein-solvent (PS) energy, which favors unfolding, in the formation of the β-hairpin structure. It is found that the behavior of the electrostatic components of PP and PS energies reflects the structural changes associated with the loss of backbone hydrogen bonding. Relative changes in the PP and PS van der Waals interactions are related with the disruption of the hydrophobic core of a protein. The results of the simulations support the hydrophobic collapse mechanism of β-hairpin folding