A Nomadic Cloud

The fast-paced modern urban social lifestyle not only brings us convenience but also a huge amount of stress and anxiety. It may come from work, family, or society, etc. Under the environment of the crazy pursuit of efficiency, employees in the workplace will have a sense of anxiety and insecurity, which will bring a greater sense of powerlessness. Society is becoming more and more McDonaldization, as George Ritzer said. Meanwhile, at Emory University, Sharon Bergquist pointed out in the research that excessive stress will damage our immune system and bring some corresponding health problems. People usually use the word 'heavy' to describe stress, but could we make ourselves temporarily forget about it, space out ourselves. Or maybe we could escape it in some artistic way. 'A Nomadic Cloud' is a temporary street-based installation aim to reduce people's daily stress. It will mainly present it in an inflatable cloud form, which shows a strong contrast by combining the heavy daily stress and the fluffy air-feel freedom. Meanwhile by linking the new form of digital lighting technology, and finally display it in a cosmopolitan area all over the world as a nomadic contemporary street installation

Neighborhood Matching Network for Entity Alignment

Structural heterogeneity between knowledge graphs is an outstanding challenge for entity alignment. This paper presents Neighborhood Matching Network (NMN), a novel entity alignment framework for tackling the structural heterogeneity challenge. NMN estimates the similarities between entities to capture both the topological structure and the neighborhood difference. It provides two innovative components for better learning representations for entity alignment. It first uses a novel graph sampling method to distill a discriminative neighborhood for each entity. It then adopts a cross-graph neighborhood matching module to jointly encode the neighborhood difference for a given entity pair. Such strategies allow NMN to effectively construct matching-oriented entity representations while ignoring noisy neighbors that have a negative impact on the alignment task. Extensive experiments performed on three entity alignment datasets show that NMN can well estimate the neighborhood similarity in more tough cases and significantly outperforms 12 previous state-of-the-art methods.Comment: 11 pages, accepted by ACL 202

Free-standing MoS2/carbon nanotube composite buckypaper electrode for lithium-ion battery

As demand grows on portable electronic devices and electrical vehicles, the weight-reduction becomes a significant challenge in energy saving. Conductive buckypaper, also known as carbon nanotube (CNT) thin film, is one of the possible solutions by replacing the metal elements in these electronic devices with light weight buckypaper. Especially, it is proposed here that the cost-effective free-standing and binder-free buckypaper can be used as electrodes in lithium-ion batteries (LIBs), therefore no heavy metal substrate and binder are needed. Here, both CNT buckypaper and MoS2/CNT composite buckypaper were applied in lithium-ion battery. The buckypaper were fabricated using multi-walled carbon nanotubes (MWCNTs) and 2 um MoS2 powders via a simple vacuum filtration method, which was an environmentally friendly fabrication method with low cost. The electrical and electrochemical properties of both CNT buckypaper and MoS2/CNT composite buckypaper were investigated. To evaluate and compare the electrical conductivity of the MoS2/CNT composite buckypaper electrodes, the conductivity of buckypapers with and without MoS2 were tested using a four-point probe method (FPP). The content of MoS2 in each composite buckypaper electrode was analyzed by Inductively Coupled Plasma mass spectrometry (ICP). Electrochemical properties and related mechanisms were investigated by Cyclic Voltammetry (CV), and Electrochemical Impedance Spectroscopy (EIS) tests. Cycling performance and rate capability were also included in the electrochemical properties study. The microstructure and morphology were examined by Raman Microspectroscopy, X-Ray diffraction (XRD), Scanning Electron Microscopy (SEM), and Energy Dispersive X-Ray Spectroscopy (EDS). In addition, several MoS2 standard electrodes, which was made by dispersing MoS2 on copper, were tested for comparison of electrochemical properties and reaction mechanisms. It has been shown in this research that a new low-cost, binder-free, and free-standing MoS2/CNT composite buckypaper electrode for lithium-ion battery was accomplished. The highest electrical conductivity of the CNT buckypaper reached 14.98 S/cm, and the electrical conductivities of MoS2/CNT composite buckypaper varied between 2 S/cm to 6 S/cm, due to different MoS2/CNT ratios. The highest mass loading of MoS2 in composite buckypaper electrodes reached 8.17 mg/cm2, which was four times higher than the mass loading in MoS2 standard electrodes by removing the copper foil substrate in electrodes. For electrochemical properties, the highest first discharge specific capacity of MoS2/CNT composite buckypaper was 1800 mAh/g in a wide potential window, which was two times higher than that of MoS2 Cu foil electrodes. Although the batteries in this study were charged to 2.0 V to prevent side reactions caused by sulfur shuttle effect, MoS2/CNT composite buckypaper still held a high reservable capacity of 600 mAh/g, which was also two times higher than the MoS2 Cu foil electrode. For rate capability, the MoS2/CNT composite buckypaper electrodes delivered a reservable capacity of 100 mAh/g when the current density was increased to 5 C (5000 mA/g). The effective contact between carbon nanotubes and MoS2 powders reduced the internal resistance of the electrodes during cycling. The carbon nanotubes provided abundant reaction sites limiting side reactions of between reaction product like polysulfur and lithium salt, due to the ultra-high electrical conductivity and large specific surface area of CNTs. The side reactions between polysulfur and binder in MoS2Cu foil electrodes was also eliminated as buckypaper was a binder-free electrode. Therefore, high specific capacity of MoS2/CNT composite buckypaper and good rate capability were obtained in this project. The high electrical and electrochemical properties accomplished in this project provided a promising prospect of applying MoS2/CNT composite buckypaper electrode in lithium-ion batteries

Improving first order temporal fact extraction with unreliable data

In this paper, we deal with the task of extracting first order temporal facts from free text. This task is a subtask of relation extraction and it aims at extracting relations between entity and time. Currently, the field of relation extraction mainly focuses on extracting relations between entities. However, we observe that the multi-granular nature of time expressions can help us divide the dataset constructed by distant supervision to reliable and less reliable subsets, which can help to improve the extraction results on relations between entity and time. We accordingly contribute the first dataset focusing on the first order temporal fact extraction task using distant supervision. To fully utilize both the reliable and the less reliable data, we propose to use curriculum learning to rearrange the training procedure, label dropout to make the model be more conservative about less reliable data, and instance attention to help the model distinguish important instances from unimportant ones. Experiments show that these methods help the model outperform the model trained purely on the reliable dataset as well as the model trained on the dataset where all subsets are mixed together