Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks

We propose a distance supervised relation extraction approach for long-tailed, imbalanced data which is prevalent in real-world settings. Here, the challenge is to learn accurate "few-shot" models for classes existing at the tail of the class distribution, for which little data is available. Inspired by the rich semantic correlations between classes at the long tail and those at the head, we take advantage of the knowledge from data-rich classes at the head of the distribution to boost the performance of the data-poor classes at the tail. First, we propose to leverage implicit relational knowledge among class labels from knowledge graph embeddings and learn explicit relational knowledge using graph convolution networks. Second, we integrate that relational knowledge into relation extraction model by coarse-to-fine knowledge-aware attention mechanism. We demonstrate our results for a large-scale benchmark dataset which show that our approach significantly outperforms other baselines, especially for long-tail relations.Comment: To be published in NAACL 201

RG Hyperparameter Optimization Approach for Improved Indirect Prediction of Blood Glucose Levels by Boosting Ensemble Learning

This paper proposes an RG hyperparameter optimization approach, based on a sequential use of random search (R) and grid search (G), for improving the blood glucose level prediction of boosting ensemble learning models. An indirect prediction of blood glucose levels in patients is performed, based on historical medical data collected by means of physical examination methods, using 40 human body’s health indicators. The conducted experiments with real clinical data proved that the proposed RG double optimization approach helps improve the prediction performance of four state-of-the-art boosting ensemble learning models enriched by it, achieving 1.47% to 24.40% MSE improvement and 0.75% to 11.54% RMSE improvement.National Key Research and Development Program of China under the Grant No. 2017YFE0135700 and the Bulgarian National Science Fund (BNSF) under the Grant No. КП-06-ИП-КИТАЙ/1 (КP-06-IP-CHINA/1

The Classification of the Persistent Infection Risk for Human Papillomavirus among HIV-Negative Men Who Have Sex with Men: Trajectory Model Analysis

Objective. To classify the infection risk of human papillomavirus (HPV) among human immunodeficiency virus- (HIV-) negative men who have sex with men (MSM) using group-based trajectory modeling (GBTM). Methods. This study collected data on demographic and sexual behavior characteristics by questionnaires at semiannual visits from March 1st, 2016 to December 31th, 2017. Researchers collected anal exfoliated cells to finish HPV testing and blood samples to finish HIV testing at baseline and follow-up visits. Accumulative infection numbers of different types of HPV as the primary outcome and the follow-up visits as the independent predicator to build a GBTM model. Results. There were 500 potentially eligible HIV-negative participants at baseline, 361 (72.2%) of whom were included in this study after screening. Three trajectory groups were identified as the best-fitted GBTM model. Trajectory 1, defined as decreased group (DG) accounted for 44.6% (161/361) of the sample, showed a declining pattern with visits. Trajectory 2, defined as flat group (FG) accounted for 49.6% (179/361) of the sample, showed a flat pattern with visits. Trajectory 3, regarded as the increased group (IG) accounted for 5.8% (21/361) of the sample, showed an uptrend. Compared to the DG, risk factors for the FG included receptive anal intercourse (AOR, 2.24; 95% CI, 1.36-3.71), occasional condom use in anal sex during the past six months (AOR, 1.90; 95% CI, 1.16-3.14), experience of transactional sex with males in the past year (AOR, 3.60; 95% CI, 1.12-11.54), and substance use (AOR, 1.81; 95% CI, 1.08-3.04). Risk factors for the IG included receptive anal intercourse (AOR, 2.81; 95% CI, 1.04-7.70), occasional condom use in anal sex during the past six months (AOR, 3.93; 95% CI, 1.40-11.01), and history of other STIs (AOR, 5.72; 95% CI, 1.40-23.46). Conclusion. The MSM data in this study showed three distinct developmental trajectories (DG, FG, and IG) of HPV infection among HIV-negative MSM, with receptive anal intercourse and occasional condom use in anal sex during the past six months being the risk factors associated with FG and IG

Multi-tissue integrative analysis of personal epigenomes

Evaluating the impact of genetic variants on transcriptional regulation is a central goal in biological science that has been constrained by reliance on a single reference genome. To address this, we constructed phased, diploid genomes for four cadaveric donors (using long-read sequencing) and systematically charted noncoding regulatory elements and transcriptional activity across more than 25 tissues from these donors. Integrative analysis revealed over a million variants with allele-specific activity, coordinated, locus-scale allelic imbalances, and structural variants impacting proximal chromatin structure. We relate the personal genome analysis to the ENCODE encyclopedia, annotating allele- and tissue-specific elements that are strongly enriched for variants impacting expression and disease phenotypes. These experimental and statistical approaches, and the corresponding EN-TEx resource, provide a framework for personalized functional genomics

Numerical Investigation of the Oblique Detonation Waves and Stability in a Super-Detonative Ram Accelerator

This study numerically investigates the effects of diluent gas proportion, the overdrive factor, and throat width on the wave structure and thrust performance of a ram accelerator operating in super-detonative mode. For premixed gas of a high energy density, a typical unstart oblique detonation wave system is observed due to the ignition on the front wedge of the projectile, and the detonation waves move downstream to the shoulder as the energy density decreases. In the start range of the overdrive factor, the wave position also shows a tendency to move downstream as the projectile velocity increases, accompanied by oscillations of the wave surface and thrust. As the throat width increases, the wave standing position changes non-monotonously, with an interval of upstream movement and Mach reflection. The typical wave structure of a ram accelerator in super-detonative mode is identified, as well as the unstart stable wave features and the unstable process for choking, which can provide theoretical guidance for avoiding unstart issues in ram accelerators and optimizing their performance

Role of wind forcing and eddy activity in the intraseasonal variability of the barrier layer in the South China Sea

In addition to widely discussed seasonal variability, the barrier layer (BL) of the South China Sea (SCS) also exhibits significant intraseasonal variability (ISV) and plays an important role in the upper heat and salt balances. The characteristics and mechanisms of spatiotemporal variations in the BL are investigated using an eddy-resolving ocean model OFES (OGCM For the Earth Simulator) ouput and related atmospheric and oceanic processes. The active intraseasonal BL variability in the SCS occurs mainly during the late summer/autumn and winter and exhibits remarkable differences between these two periods. The BL ISV in late summer/autumn occurs in the southern basin, while in winter, it is limited to the northwestern basin. To further discuss the evolution and driving thermodynamic mechanisms, we quantify the processes that control the variability of intraseasonal BL. Different mechanisms for the intraseasonal BL variability for these two active periods are investigated based on the case study and composite analysis. During late summer/autumn, the active BL in the southern basin is generated by advected and local freshwater, and then decays rapidly with the enhanced wind. In winter, anticyclonic eddy activity is associated with the evolution of the BL by affecting the thermocline and halocline variations, while wind stress and wind stress curl have no obvious influence on BL

An energy-saving pumping system with novel springs energy storage devices: Design, modeling, and experiment

For the traditional reciprocating pumping unit, it generally starts at the bottom dead point with full load and is accelerated when starting and decelerated when stopping, which not only requires great energy from the motor but also impact on the output torque of motor. In order to tackle the above problems, we propose an energy-saving smooth reversing pumping system, which could store the energy in deceleration by making use of springs, and the stored energy could be reused in acceleration after reversion. This novel system targets to make the motor starting with light load, which could reduce the fluctuation in motor torque, decrease the starting time. In this article, a dynamic model and an efficiency model are established to compute the polished rod load dynamometer card and efficiency of the pumping unit. It is shown that the installed springs could help to reduce the impact on the system when reversing, and significantly decrease the energy consumption. In addition, we set up the real pumping system with load test system to verify the effectiveness of the model establishment. Through the experiment, the proposed pumping system could save energy up to 9.204% as compared to the traditional reciprocating pumping system