Generating Questions Based on Semi-Automated and End-to-End Neural Network

With the emergence of large-scale knowledge base, how to use triple information to generate natural questions is a key technology in question answering systems. The traditional way of generating questions require a lot of manual intervention and produce lots of noise. To solve these problems, we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions. The semi-automated model can generate question templates and real questions combining the knowledge base and center graph. The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network. Meanwhile, the attention mechanism is utilized in the decoding layer, which makes the triples and generated questions more relevant. Finally, the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach.     

A framework for discovering health disparities among cohorts in an influenza epidemic

World Wide Web - Infectious diseases such as Influenza and Ebola pose a serious threat to everyone but certain demographics and cohorts face a higher risk of infection than others. This research...     

Multimodal sensing and active continuous closed‐loop feedback for achieving reliable manipulation in the outdoor physical world

The use of field robots can greatly decrease the amount of time, effort, and associated risk compared to if human workers were to carryout certain tasks such as disaster response. However, transportability and reliability remain two main issues for most current robot systems. To address the issue of transportability, we have developed a lightweight modularizable platform named AeroArm. To address the issue of reliability, we utilize a multimodal sensing approach, combining the use of multiple sensors and sensor types, and the use of different detection algorithms, as well as active continuous closed‐loop feedback to accurately estimate the state of the robot with respect to the environment. We used Challenge 2 of the 2017 Mohammed Bin Zayed International Robotics Competition as an example outdoor manipulation task, demonstrating the capabilities of our robot system and approach in achieving reliable performance in the fields, and ranked fifth place internationally in the competition.     

MPE: a mobility pattern embedding model for predicting next locations

World Wide Web - The wide spread use of positioning and photographing devices gives rise to a deluge of traffic trajectory data (e.g., vehicle passage records and taxi trajectory data), with each...     

Macroscopic and Microscopic Structures of Cesium Lead Iodide Perovskite from Atomistic Simulations

A first‐principles‐based effective Hamiltonian is developed and employed to investigate finite‐temperature structural properties of a prototype of perovskite halides, that is CsPbI₃. Such simulations, when using first‐principles‐extracted coefficients, successfully reproduce the existence of an orthorhombic Pnma state and its iodine octahedral tilting angles around room temperature. However, they also yield a direct transformation from Pnma to cubic $Pm\overline{3}m$ upon heating, unlike measurements that reported the occurrence of an intermediate long‐range‐tilted tetragonal P4/mbm phase in‐between the orthorhombic and cubic phases. Such disagreement, which may cast some doubts about the extent to which first‐principle methods can be trusted to mimic hybrid perovskites, can be resolved by “only” changing one short‐range tilting parameter in the whole set of effective Hamiltonian coefficients. In such a case, some reasonable values of this specific parameter result in the predictions that i) the intermediate P4/mbm state originates from fluctuations over many different tilted states; and ii) the cubic $Pm\overline{3}m$ phase is highly locally distorted and develops strong transverse antiphase correlation between first‐nearest neighbor iodine octahedral tiltings, before undergoing a phase transition to P4/mbm under cooling.     

Achieving Rich and Active Alkaline Hydrogen Evolution Heterostructures via Interface Engineering on 2D 1T‐MoS2 Quantum Sheets

Large‐scale production of hydrogen from water‐alkali electrolyzers is impeded by the sluggish kinetics of hydrogen evolution reaction (HER) electrocatalysts. The hybridization of an acid‐active HER catalyst with a cocatalyst at the nanoscale helps boost HER kinetics in alkaline media. Here, it is demonstrated that 1T–MoS₂ nanosheet edges (instead of basal planes) decorated by metal hydroxides form highly active ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ heterostructures, which significantly enhance HER performance in alkaline media. Featured with rich ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ sites, the fabricated 1T–MoS₂ QS/Ni(OH)₂ hybrid (quantum sized 1T–MoS₂ sheets decorated with Ni(OH)₂ via interface engineering) only requires overpotentials of 57 and 112 mV to drive HER current densities of 10 and 100 mA cm^?2, respectively, and has a low Tafel slope of 30 mV dec^?1 in 1 m KOH. So far, this is the best performance for MoS₂‐based electrocatalysts and the 1T–MoS₂ QS/Ni(OH)₂ hybrid is among the best‐performing non‐Pt alkaline HER electrocatalysts known. The HER process is durable for 100 h at current densities up to 500 mA cm^?2. This work not only provides an active, cost‐effective, and robust alkaline HER electrocatalyst, but also demonstrates a design strategy for preparing high‐performance catalysts based on edge‐rich 2D quantum sheets for other catalytic reactions.     

落葵浆果天然染料提取及对羊毛织物的染色性能

文章主要研究用水浸法提取落葵浆果天然染料及研究浸提液对羊毛织物的染色性能。以水为提取剂提取落葵浆果天然染料,探讨提取工艺中料液比、提取温度及时间等因素对落葵浆果天然染料提取效果的影响。研究结果表明,落葵浆果水浸提法优化工艺为:料液比1∶20、提取温度70℃、提取时间30 min。落葵浆果天然染料可以对羊毛织物进行染色,媒染染色与直接染色相比,染色深度深且会呈现不同的颜色。由于媒染剂的络合作用,媒染染色色牢度比直接染色普遍高1~2级。