More than Classification: A Unified Framework for Event Temporal Relation Extraction

Event temporal relation extraction~(ETRE) is usually formulated as a multi-label classification task, where each type of relation is simply treated as a one-hot label. This formulation ignores the meaning of relations and wipes out their intrinsic dependency. After examining the relation definitions in various ETRE tasks, we observe that all relations can be interpreted using the start and end time points of events. For example, relation \textit{Includes} could be interpreted as event 1 starting no later than event 2 and ending no earlier than event 2. In this paper, we propose a unified event temporal relation extraction framework, which transforms temporal relations into logical expressions of time points and completes the ETRE by predicting the relations between certain time point pairs. Experiments on TB-Dense and MATRES show significant improvements over a strong baseline and outperform the state-of-the-art model by 0.3\% on both datasets. By representing all relations in a unified framework, we can leverage the relations with sufficient data to assist the learning of other relations, thus achieving stable improvement in low-data scenarios. When the relation definitions are changed, our method can quickly adapt to the new ones by simply modifying the logic expressions that map time points to new event relations. The code is released at \url{https://github.com/AndrewZhe/A-Unified-Framework-for-ETRE}

RDMAS: a web server for RNA deleterious mutation analysis

BACKGROUND: The diverse functions of ncRNAs critically depend on their structures. Mutations in ncRNAs disrupting the structures of functional sites are expected to be deleterious. RNA deleterious mutations have attracted wide attentions because some of them in cells result in serious disease, and some others in microbes influence their fitness. RESULTS: The RDMAS web server we describe here is an online tool for evaluating structural deleteriousness of single nucleotide mutation in RNA genes. Several structure comparison methods have been integrated; sub-optimal structures predicted can be optionally involved to mitigate the uncertainty of secondary structure prediction. With a user-friendly interface, the web application is easy to use. Intuitive illustrations are provided along with the original computational results to facilitate quick analysis. CONCLUSION: RDMAS can be used to explore the structure alterations which cause mutations pathogenic, and to predict deleterious mutations which may help to determine the functionally critical regions. RDMAS is freely accessed via

Accurate power sharing of hybrid energy storage system in DC shipboard power system based on quadratic programming algorithm

The DC shipboard power system (DC-SPS) can be regarded as an island microgrid, supplying energy to propulsion systems, service devices and advanced equipment in future ships. Ensuring accurate power sharing among distributed power sources and maintaining the stability of DC bus voltage in DCSPS are prerequisites to run system in security and economy. Therefore, an accurate power sharing method based on the quadratic programming algorithm is proposed in this paper. That method aims at minimizing the cost of voltage regulation in the consideration of state of charge (SoC) of each energy storage device (ESD). In detail, the target power is determined by the DC bus voltage deviation, and further distributed among various energy storage by quadratic programming accurately. With the control method, the DC bus voltage is maintained within the desired voltage range. Moreover, the method can meet the plug-and-play requirements of distributed power. The effectiveness of the proposed control method is verified by real-time simulation

The Application of Approximate Entropy Theory in Defects Detecting of IGBT Module

Defect is one of the key factors in reducing the reliability of the insulated gate bipolar transistor (IGBT) module, so developing the diagnostic method for defects inside the IGBT module is an important measure to avoid catastrophic failure and improves the reliability of power electronic converters. For this reason, a novel diagnostic method based on the approximate entropy (ApEn) theory is presented in this paper, which can provide statistical diagnosis and allow the operator to replace defective IGBT modules timely. The proposed method is achieved by analyzing the cross ApEn of the gate voltages before and after the occurring of defects. Due to the local damage caused by aging, the intrinsic parasitic parameters of packaging materials or silicon chips inside the IGBT module such as parasitic inductances and capacitances may change over time, which will make remarkable variation in the gate voltage. That is to say the gate voltage is close coupled with the defects. Therefore, the variation is quantified and used as a precursor parameter to evaluate the health status of the IGBT module. Experimental results validate the correctness of the proposed method

Investigating behavior inhibition in obsessive‐compulsive disorder: Evidence from eye movements

We investigated the role of inhibition failure in Obsessive Compulsive Disorder (OCD) through an eye tracking experiment. Twenty‐five subjects with OCD were recruited, as well as 25 with Generalized Anxiety Disorder (GAD) and 25 healthy controls. A 3 (group: OCD group, GAD group and control group) × 2 (target eccentricity: far and near) × 2 (saccade task: prosaccade and antisaccade) mixed design was used, with all participants completing two sets of tasks involving both prosaccade (eye movement towards a target) and antisaccade (eye movement away from a target). The main outcome was the eye movement index, including the saccade latency (the time interval from the onset of the target screen to the first saccade) and the error rate of saccade direction. The antisaccade latency and antisaccade error rates for OCDs were much higher than those for GADs and healthy controls. OCDs had longer latency and error rates for antisaccades than for prosaccades, and for far‐eccentricity rather than near‐eccentricity stimuli. These results suggest that OCDs experience difficulty with behavior inhibition, and that they have higher visual sensitivity to peripheral stimuli. In particular, they show greatest difficulty in inhibiting behavior directed towards peripheral stimuli

RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars

Synthesizing high-fidelity head avatars is a central problem for computer vision and graphics. While head avatar synthesis algorithms have advanced rapidly, the best ones still face great obstacles in real-world scenarios. One of the vital causes is inadequate datasets -- 1) current public datasets can only support researchers to explore high-fidelity head avatars in one or two task directions; 2) these datasets usually contain digital head assets with limited data volume, and narrow distribution over different attributes. In this paper, we present RenderMe-360, a comprehensive 4D human head dataset to drive advance in head avatar research. It contains massive data assets, with 243+ million complete head frames, and over 800k video sequences from 500 different identities captured by synchronized multi-view cameras at 30 FPS. It is a large-scale digital library for head avatars with three key attributes: 1) High Fidelity: all subjects are captured by 60 synchronized, high-resolution 2K cameras in 360 degrees. 2) High Diversity: The collected subjects vary from different ages, eras, ethnicities, and cultures, providing abundant materials with distinctive styles in appearance and geometry. Moreover, each subject is asked to perform various motions, such as expressions and head rotations, which further extend the richness of assets. 3) Rich Annotations: we provide annotations with different granularities: cameras' parameters, matting, scan, 2D/3D facial landmarks, FLAME fitting, and text description. Based on the dataset, we build a comprehensive benchmark for head avatar research, with 16 state-of-the-art methods performed on five main tasks: novel view synthesis, novel expression synthesis, hair rendering, hair editing, and talking head generation. Our experiments uncover the strengths and weaknesses of current methods. RenderMe-360 opens the door for future exploration in head avatars.Comment: Technical Report; Project Page: 36; Github Link: https://github.com/RenderMe-360/RenderMe-36

The influence of model quality on self-other mate choice copying

We explored, through two experiments, the influence of model quality and gender on mate choice copying (MCC) behavior for oneself and for others. In the first experiment, we used a 3 (decision-making role: self, stranger, close friend) × 2 (gender: male, female) between-subjects design. The phenomenon of MCC was only found in females. There was no significant difference between making decisions for oneself and for close friends, but there was a significant difference between making decisions for oneself and for strangers. In the second experiment, we used a 2 (model quality: higher, lower) × 3 (decision-making role: self, stranger, close friend) × 2 (gender: male, female) mixed experimental design. Results showed an MCC effect under the condition of high-quality models for both males and females, but no MCC effect for low quality models, either for males or females. Again, there was no significant difference between making decisions for oneself and for close friends, but there was a significant difference between making decisions for oneself and for strangers. These results reveal that context is important for the manifestation of MCC behavior: both women and men are influenced by the choices of high quality models, but ignore the behavior of low quality models

Network Pharmacology-Based Validation of Caveolin-1 as a Key Mediator of Ai Du Qing Inhibition of Drug Resistance in Breast Cancer

Chinese formulas have been paid increasing attention in cancer multidisciplinary therapy due to their multi-targets and multi-substances property. Here, we aim to investigate the anti-breast cancer and chemosensitizing function of Ai Du Qing (ADQ) formula made up of Hedyotis diffusa, Curcuma zedoaria (Christm.) Rosc., Astragalus membranaceus (Fisch.) Bunge, and Glycyrrhiza uralensis Fisch. Our findings revealed that ADQ significantly inhibited cell proliferation in both parental and chemo-resistant breast cancer cells, but with little cytotoxcity effects on the normal cells. Besides, ADQ was found to facilitate the G2/M arresting and apoptosis induction effects of paclitaxel. Network pharmacology and bioinformatics analysis further demonstrated that ADQ yielded 132 candidate compounds and 297 potential targets, and shared 22 putative targets associating with breast cancer chemoresponse. Enrichment analysis and experimental validation demonstrated that ADQ might improve breast cancer chemosensitivity via inhibiting caveolin-1, which further triggered expression changes of cell cycle-related proteins p21/cyclinB1 and apoptosis-associated proteins PARP1, BAX and Bcl-2. Besides, ADQ enhanced in vivo paclitaxel chemosensitivity on breast cancer. Our study not only uncovers the novel function and mechanisms of ADQ in chemosensitizing breast cancer at least partly via targeting caveolin-1, but also sheds novel light in utilizing network pharmacology in Chinese Medicine research

Quantum critical point in SmO1−xFxFeAs and oxygen vacancy induced by high fluorine dopant

The local lattice and electronic structure of the high-T(c) superconductor SmO(1-x)F(x)FeAs as a function of F-doping have been investigated by Sm L(3)-edge X-ray absorption near-edge structure and multiple-scattering calculations. Experiments performed at the L(3)-edge show that the white line (WL) is very sensitive to F-doping. In the under-doped region (x ≤ 0.12) the WL intensity increases with doping and then it suddenly starts decreasing at x = 0.15. Meanwhile, the trend of the WL linewidth versus F-doping levels is just contrary to that of the intensity. The phenomenon is almost coincident with the quantum critical point occurring in SmO(1-x)F(x)FeAs at x ≃ 0.14. In the under-doped region the increase of the intensity is related to the localization of Sm-5d states, while theoretical calculations show that both the decreasing intensity and the consequent broadening of linewidth at high F-doping are associated with the content and distribution of oxygen vacancies