Gated Convolutional Bidirectional Attention-based Model for Off-topic Spoken Response Detection

Off-topic spoken response detection, the task aiming at predicting whether a response is off-topic for the corresponding prompt, is important for an automated speaking assessment system. In many real-world educational applications, off-topic spoken response detectors are required to achieve high recall for off-topic responses not only on seen prompts but also on prompts that are unseen during training. In this paper, we propose a novel approach for off-topic spoken response detection with high off-topic recall on both seen and unseen prompts. We introduce a new model, Gated Convolutional Bidirectional Attention-based Model (GCBiA), which applies bi-attention mechanism and convolutions to extract topic words of prompts and key-phrases of responses, and introduces gated unit and residual connections between major layers to better represent the relevance of responses and prompts. Moreover, a new negative sampling method is proposed to augment training data. Experiment results demonstrate that our novel approach can achieve significant improvements in detecting off-topic responses with extremely high on-topic recall, for both seen and unseen prompts.Comment: ACL2020 long pape

Multiple Disk Gaps and Rings Generated by a Single Super-Earth: II. Spacings, Depths, and Number of Gaps, with Application to Real Systems

ALMA has found multiple dust gaps and rings in a number of protoplanetary disks in continuum emission at millimeter wavelengths. The origin of such structures is in debate. Recently, we documented how one super-Earth planet can open multiple (up to five) dust gaps in a disk with low viscosity ($\alpha\lesssim10^{-4}$). In this paper, we examine how the positions, depths, and total number of gaps opened by one planet depend on input parameters, and apply our results to real systems. Gap locations (equivalently, spacings) are the easiest metric to use when making comparisons between theory and observations, as positions can be robustly measured. We fit the locations of gaps empirically as functions of planet mass and disk aspect ratio. We find that the locations of the double gaps in HL Tau and TW Hya, and of all three gaps in HD 163296, are consistent with being opened by a sub-Saturn mass planet. This scenario predicts the locations of other gaps in HL Tau and TW Hya, some of which appear consistent with current observations. We also show how the Rossby wave instability may develop at the edges of several gaps and result in multiple dusty vortices, all caused by one planet. A planet as low in mass as Mars may produce multiple dust gaps in the terrestrial planet forming region.Comment: 16 pages; ApJ accepte

Multiple Disk Gaps and Rings Generated by a Single Super-Earth

We investigate the observational signatures of super-Earths (i.e., Earth-to-Neptune mass planets) in their natal disks of gas and dust. Combining two-fluid global hydrodynamics simulations with a radiative transfer code, we calculate the distributions of gas and of sub-mm-sized dust in a disk perturbed by a super-Earth, synthesizing images in near-infrared scattered light and the mm-wave thermal continuum for direct comparison with observations. In low viscosity gas ($\alpha\lesssim10^{-4}$), a super-Earth opens two annular gaps to either side of its orbit by the action of Lindblad torques. This double gap and its associated gas pressure gradients cause dust particles to be dragged by gas into three rings: one ring sandwiched between the two gaps, and two rings located at the gap edges farthest from the planet. Depending on system parameters, additional rings may manifest for a single planet. A double gap located at tens of AUs from a host star in Taurus can be detected in the dust continuum by the Atacama Large Millimeter Array (ALMA) at an angular resolution of ~0".03 after two hours of integration. Ring and gap features persist in a variety of background disk profiles, last for thousands of orbits, and change their relative positions and dimensions depending on the speed and direction of planet migration. Candidate double gaps have been observed by ALMA in systems like HL Tau (D5 and D6) and TW Hya (at 37 and 43 AU); we submit that each double gap is carved by one super-Earth in nearly inviscid gas.Comment: 23 pages, 1 table, 14 figures, ApJ accepte

Development of U-model enhanced nonlinear dynamic control systems —Framework, algorithms and validation

This study aims to develop the classical model-based U-control design framework to enhance its robustness and reduce its dependence on model accuracy. By absorbing the design concepts of other advanced control algorithms, firstly, based on the discrete-time U-control algorithm, a continuous-time (CT) U-model based dynamic inversion algorithm is proposed. Then the CT U-control system design procedures are presented and explained step by step with numerical and simulation demonstrations of the linear and nonlinear U-control system design examples. Secondly, the U-control algorithm develops two mainstream nonlinear robust control algorithms, disturbances suppression and disturbances compensation, while maintaining its system dynamic cancellation characteristics, including two-degree-of-freedom U-model-based internal model control (UTDF-IMC), Disturbance observer-based U-control (DOBUC), sliding mode enhanced U-control (U-SMC) and U-model based double sliding mode control (UDSMC) algorithms. At the same time this study first developed and applied the U-control method to a practical industry application: robust quadrotor trajectory tracking control. The proposed UDSMC method and multiple-input and multiple-output extended-state-observer (MIMO-ESO) established the quadrotor flight control system. The difficulties associated with quadrotor velocity measurement disturbances and uncertain aerodynamics are successfully addressed in this control design. A rigorous theoretical analysis has been carried out to determine whether the proposed control system can achieve stable trajectory tracking performance, and a comparative real-time experimental study has also been carried out to verify the better effectiveness of the proposed control system than the classical SMC and built-in PID control system. This study is clearly novel as the methods and experiments it proposed have not been researched before

MiR-452 negatively regulates osteoblast differentiation in periodontal ligament stem cells by targeting the polycomb-group protein, BMI1

Purpose: To determine whether miR-452 regulates osteoblast differentiation (OD) in human periodontal ligament stem cells (hPDLSCs) by targeting polycomb-group protein BMI1. Methods: hPDLSCs were stimulated to differentiate upon treatment with mineralization liquid. Quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting were used to measure mRNA and protein expressions, respectively. Alkaline phosphatase (ALP) activity and Alizarin red staining were used to determine the osteogenic differentiation (OD) of hPDLSCs. The bioinformatics software, Targetscan, was used to predict the potential target of miR-452, while luciferase assay, qRT- PCR, and western blot were employed to verify the target gene of miR-452, BMI1. Results: MiR-452 was downregulated during the OD of hPDLSCs, but miR-452 overexpression inhibited the OD of hPDLSCs. BMI1 was identified as a direct target gene of miR-452 during the OD of hPDLSCs, while miR-452 overexpression correlated inversely with BMI1 expression during OD of hPDLSCs. Conclusion: Overexpression of miR-452 suppresses the OD of hPDLSCs by targeting BMI1.This study may provide potential diagnostic and therapeutic basis for OD in hPDLSCs

Searching for Majorana Neutrinos at a Same-Sign Muon Collider

Majorana properties of neutrinos have long been a focus in the pursuit of possible new physics beyond the standard model, which has motivated lots of dedicated theoretical and experimental studies. A future same-sign muon collider is an ideal platform to search for Majorana neutrinos through the Lepton Number Violation process. Specifically, this t-channel kind of process is less kinematically suppressed and has a good advantage in probing Majorana neutrinos at high mass regions up to 10 TeV. In this paper, we perform a detailed fast Monte Carlo simulation study through examining three different final states: 1) pure-leptonic state with electrons or muons, 2) semi-leptonic state, and 3) pure-hadronic state in the resolved or merged categories. Furthermore, we perform a full simulation study on the pure-leptonic final state to validate our fast simulation results.Comment: 15 pages, 8 figure

Distance-rank Aware Sequential Reward Learning for Inverse Reinforcement Learning with Sub-optimal Demonstrations

Inverse reinforcement learning (IRL) aims to explicitly infer an underlying reward function based on collected expert demonstrations. Considering that obtaining expert demonstrations can be costly, the focus of current IRL techniques is on learning a better-than-demonstrator policy using a reward function derived from sub-optimal demonstrations. However, existing IRL algorithms primarily tackle the challenge of trajectory ranking ambiguity when learning the reward function. They overlook the crucial role of considering the degree of difference between trajectories in terms of their returns, which is essential for further removing reward ambiguity. Additionally, it is important to note that the reward of a single transition is heavily influenced by the context information within the trajectory. To address these issues, we introduce the Distance-rank Aware Sequential Reward Learning (DRASRL) framework. Unlike existing approaches, DRASRL takes into account both the ranking of trajectories and the degrees of dissimilarity between them to collaboratively eliminate reward ambiguity when learning a sequence of contextually informed reward signals. Specifically, we leverage the distance between policies, from which the trajectories are generated, as a measure to quantify the degree of differences between traces. This distance-aware information is then used to infer embeddings in the representation space for reward learning, employing the contrastive learning technique. Meanwhile, we integrate the pairwise ranking loss function to incorporate ranking information into the latent features. Moreover, we resort to the Transformer architecture to capture the contextual dependencies within the trajectories in the latent space, leading to more accurate reward estimation. Through extensive experimentation, our DRASRL framework demonstrates significant performance improvements over previous SOTA methods