Tsinghua University

About: Tsinghua University is a education organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: Computer science & Catalysis. The organization has 129978 authors who have published 200506 publications receiving 4549561 citations. The organization is also known as: Tsinghua & THU.

Tagoram: real-time tracking of mobile RFID tags to high precision using COTS devices

Abstract: In many applications, we have to identify an object and then locate the object to within high precision (centimeter- or millimeter-level). Legacy systems that can provide such accuracy are either expensive or suffering from performance degradation resulting from various impacts, e.g., occlusion for computer vision based approaches. In this work, we present an RFID-based system, Tagoram, for object localization and tracking using COTS RFID tags and readers. Tracking mobile RFID tags in real time has been a daunting task, especially challenging for achieving high precision. Our system achieves these three goals by leveraging the phase value of the backscattered signal, provided by the COTS RFID readers, to estimate the location of the object. In Tagoram, we exploit the tag's mobility to build a virtual antenna array by using readings from a few physical antennas over a time window. To illustrate the basic idea of our system, we firstly focus on a simple scenario where the tag is moving along a fixed track known to the system. We propose Differential Augmented Hologram (DAH) which will facilitate the instant tracking of the mobile RFID tag to a high precision. We then devise a comprehensive solution to accurately recover the tag's moving trajectories and its locations, relaxing the assumption of knowing tag's track function in advance. We have implemented the Tagoram system using COTS RFID tags and readers. The system has been tested extensively in the lab environment and used for more than a year in real airline applications. For lab environment, we can track the mobile tags in real time with a millimeter accuracy to a median of 5mm and 7.29mm using linear and circular track respectively. In our year- long large scale baggage sortation systems deployed in two airports, our results from real deployments show that Tagoram can achieve a centimeter-level accuracy to a median of 6.35cm in these real deployments.

Decontamination of Bisphenol A from Aqueous Solution by Graphene Adsorption

Abstract: The decontamination of bisphenol A (BPA) from aqueous solution by graphene adsorption was investigated. The maximum adsorption capacity (qm) of graphene for BPA obtained from a Langmuir isotherm was 182 mg/g at 302.15 K, which was among the highest values of BPA adsorption compared with other carbonaceous adsorbents according to the literature. Both π–π interactions and hydrogen bonds might be responsible for the adsorption of BPA on graphene, and the excellent adsorption capacity of graphene was due to its unique sp2-hybridized single-atom-layer structure. Therefore, graphene could be regarded as a promising adsorbent for BPA removal in water treatment. The kinetics and isotherm data can be well described by the pseudo-second-order kinetic model and the Langmuir isotherm, respectively. The thermodynamic studies indicated that the adsorption reaction was a spontaneous and exothermic process. Besides, the presence of NaCl in the solution could facilitate the adsorption process, whereas the alkaline pH rang...

Does Stock Liquidity Enhance or Impede Firm Innovation

Abstract: We aim to tackle the longstanding debate on whether stock liquidity enhances or impedes firm innovation This topic is of interest because innovation is crucial for firm- and national-level competitiveness and stock liquidity can be altered by financial market regulations Using a difference-in-differences approach that relies on the exogenous variation in liquidity generated by regulatory changes, we find that an increase in liquidity causes a reduction in future innovation We identify two possible mechanisms through which liquidity impedes innovation: increased exposure to hostile takeovers and higher presence of institutional investors who do not actively gather information or monitor

Phylogenetic Molecular Ecological Network of Soil Microbial Communities in Response to Elevated CO2

Abstract: Understanding the interactions among different species and their responses to environmental changes, such as ele- vated atmospheric concentrations of CO2, is a central goal in ecology but is poorly understood in microbial ecology. Here we describe a novel random matrix theory (RMT)-based conceptual framework to discern phylogenetic molecular ecological net- works using metagenomic sequencing data of 16S rRNA genes from grassland soil microbial communities, which were sampled from a long-term free-air CO2enrichment experimental facility at the Cedar Creek Ecosystem Science Reserve in Minnesota. Our experimental results demonstrated that an RMT-based network approach is very useful in delineating phylogenetic molecu- lar ecological networks of microbial communities based on high-throughput metagenomic sequencing data. The structure of the identified networks under ambient and elevated CO 2levels was substantially different in terms of overall network topology, net- work composition, node overlap, module preservation, module-based higher-order organization, topological roles of individual nodes, and network hubs, suggesting that the network interactions among different phylogenetic groups/populations were markedly changed. Also, the changes in network structure were significantly correlated with soil carbon and nitrogen contents, indicating the potential importance of network interactions in ecosystem functioning. In addition, based on network topology, microbial populations potentially most important to community structure and ecosystem functioning can be discerned. The novel approach described in this study is important not only for research on biodiversity, microbial ecology, and systems micro- biology but also for microbial community studies in human health, global change, and environmental management. IMPORTANCE The interactions among different microbial populations in a community play critical roles in determining ecosys- tem functioning, but very little is known about the network interactions in a microbial community, owing to the lack of appro- priate experimental data and computational analytic tools. High-throughput metagenomic technologies can rapidly produce a massive amount of data, but one of the greatest difficulties is deciding how to extract, analyze, synthesize, and transform such a vast amount of information into biological knowledge. This study provides a novel conceptual framework to identify microbial interactions and key populations based on high-throughput metagenomic sequencing data. This study is among thefirst to doc- ument that the network interactions among different phylogenetic populations in soil microbial communities were substantially changed by a global change such as an elevated CO2level. The framework developed will allow microbiologists to address re- search questions which could not be approached previously, and hence, it could represent a new direction in microbial ecology research.