Oblix: An Efficient Oblivious Search Index

2018 ◽  
Author(s):  
Pratyush Mishra ◽  
Rishabh Poddar ◽  
Jerry Chen ◽  
Alessandro Chiesa ◽  
Raluca Ada Popa
Keyword(s):  
Search Index

scholarly journals Spatial Spillover Effect and Influencing Factors of Information Flow in Urban Agglomerations—Case Study of China Based on Baidu Search Index

2021 ◽  
Vol 13 (14) ◽  
pp. 8032
Author(s):  
Chengzhuo Wu ◽  
Li Zhuo ◽  
Zhuo Chen ◽  
Haiyan Tao
Keyword(s):  
Influencing Factors ◽  
Information Flow ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Urban Agglomeration ◽  
Coordinated Development ◽  
Spatial Spillover ◽  
Urban Agglomerations ◽  
Search Index ◽  
Spatial Spillover Effect

Cities in an urban agglomeration closely interact with each other through various flows. Information flow, as one of the important forms of urban interactions, is now increasingly indispensable with the fast development of informatics technology. Thanks to its timely, convenient, and spatially unconstrained transmission ability, information flow has obvious spillover effects, which may strengthen urban interaction and further promote urban coordinated development. Therefore, it is crucial to quantify the spatial spillover effect and influencing factors of information flows, especially at the urban agglomeration scale. However, the academic research on this topic is insufficient. We, therefore, developed a spatial interaction model of information flow (SIM-IF) based on the Baidu Search Index and used it to analyze the spillover effects and influencing factors of information flow in the three major urban agglomerations in China, namely Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) in the period of 2014–2019. The results showed that the SIM-IF performed well in all three agglomerations. Quantitative analysis indicated that the BTH had the strongest spillover effect of information flow, followed by the YRD and the PRD. It was also found that the hierarchy of cities had the greatest impact on the spillover effects of information flow. This study may provide scientific basis for the information flow construction in urban agglomerations and benefit the coordinated development of cities.

Building a robust and compact search index

2021 ◽  
Author(s):  
Vladislav Savchuk ◽  
Stanislav Protasov
Keyword(s):  
Search Index

Foscarnet-Associated Penile Ulcerations

1994 ◽  
Vol 10 (5) ◽  
pp. 215-217
Author(s):  
Richard M. Cadle ◽  
Richard J. Hamill
Keyword(s):  
Adverse Effect ◽  
Case Reports ◽  
Human Herpesvirus ◽  
Antiviral Agent ◽  
Review Literature ◽  
Data Sources ◽  
Data Synthesis ◽  
Manual Search ◽  
Search Index ◽  
Genital Hygiene

Objective: To report a case of foscarnet-induced penile ulcerations and review literature related to this adverse effect. Data Sources: Case reports and review articles identified by a computerized search (MEDLINE) and manual search (Index Medicus). Data Synthesis: Foscarnet is a pyrophosphate analog antiviral agent that is approved by the Food and Drug Administration for treating cytomegalovirus retinitis in patients with AIDS. It also is used investigationally for other indications and human herpesvirus infections. Adverse effects include nephrotoxicity, anemia, ionized calcium abnormalities, and penile ulcerations. The majority of penile ulcers have developed within two weeks following initiation of foscarnet therapy with dosages of 180–200 mg/kg/d. Most cases required discontinuation of foscarnet to resolve the penile lesions. A postulated mechanism for this effect is inflammatory contact dermatitis from exposure to urine with elevated concentrations of foscarnet. We report a case of foscarnet-induced penile ulcerations that resolved after discontinuing this agent. Conclusions: Foscarnet can induce penile ulcerations. Increased awareness of this phenomenon, along with meticulous genital hygiene and urination practices, are required for its prevention.

The application of meteorological data and search index data in improving the prediction of HFMD: A study of two cities in Guangdong Province, China

2019 ◽  
Vol 652 ◽  
pp. 1013-1021 ◽  
Author(s):  
Shaoxing Chen ◽  
Xiaojian Liu ◽  
Yongsheng Wu ◽  
Guangxing Xu ◽  
Xubin Zhang ◽  
...  
Keyword(s):  
Meteorological Data ◽  
Guangdong Province ◽  
Index Data ◽  
Two Cities ◽  
Search Index

scholarly journals On the factors of Bitcoin’s value at risk

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Ji Ho Kwon
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Trading Volume ◽  
Corporate Bond ◽  
Policy Uncertainty ◽  
Chinese Stock Market ◽  
Stock Market Index ◽  
Market Index ◽  
The Us ◽  
Search Index

AbstractThis study investigates the factors of Bitcoin’s tail risk, quantified by Value at Risk (VaR). Extending the conditional autoregressive VaR model proposed by Engle and Manganelli (2004), I examine 30 potential drivers of Bitcoin’s 5% and 1% VaR. For the 5% VaR, quantity variables, such as Bitcoin trading volume and monetary policy rate, were positively significant, but these effects were attenuated when new samples were added. The 5% VaR responds positively to the Internet search index and negatively to the fluctuation of returns on commodity variables and the Chinese stock market index. For the 1% VaR, variables related to the macroeconomy play a key role. The consumer sentiment index exerts a strong positive effect on the 1% VaR. I also find that the 1% VaR has positive relationships with the US economic policy uncertainty index and the fluctuation of returns on the corporate bond index.

scholarly journals Regional disparities in information-seeking response to the COVID-19 pandemic in China

2021 ◽  
Author(s):  
Zhicheng Wang ◽  
Hong Xiao ◽  
Leesa Lin ◽  
Kun Tang ◽  
Joseph Unger
Keyword(s):  
Time Series ◽  
Information Seeking ◽  
Preventive Measures ◽  
Interrupted Time Series ◽  
Regional Disparities ◽  
Public Response ◽  
The Public ◽  
Time Series Analyses ◽  
Search Index ◽  
Over Time

Abstract The emergence of the COVID-19 virus and the subsequent official announcement of human-to-human transmission of COVID-19 alarmed the public and initiated the uptake of preventive measures. We conducted interrupted time-series analyses using Baidu Search Index from Jan 1, 2017 to Mar 15, 2021 to investigate how information seeking changed over time and how changes in information seeking varied across regions in China. Our findings show that changes in the patterns of search interest in COVID-19 in each province of China occurred in a synchronous fashion during the first wave of the COVID-19 pandemic and subsequent local outbreaks, irrespective of the location and severity of each outbreak. However, inequalities in the magnitude of public response to and awareness of COVID-19 were evident, with lower-levels of information seeking regarding COVID-19 in less developed areas compared with developed areas.

Forecasting tourist arrivals with machine learning and internet search index

2019 ◽  
Vol 70 ◽  
pp. 1-10 ◽  
Author(s):  
Shaolong Sun ◽  
Yunjie Wei ◽  
Kwok-Leung Tsui ◽  
Shouyang Wang
Keyword(s):  
Machine Learning ◽  
Internet Search ◽  
Search Index

Investigating the correlation of COVID-19 spread with Baidu search data : Infoveillance Study (Preprint)

2021 ◽  
Author(s):  
Xiao Qi ◽  
Su-Zhen WANG ◽  
Jia-Ning Feng ◽  
Gao-Pei ZHu ◽  
Yu-Jie Liu ◽  
...  
Keyword(s):  
Public Health ◽  
Regression Model ◽  
Health System ◽  
Early Warning ◽  
Public Health System ◽  
Model Development ◽  
Real Time Analysis ◽  
Early Warning Mechanism ◽  
Search Data ◽  
Search Index

BACKGROUND The sudden outbreak of COVID-19 has placed an unprecedented pressure on China's public health system. It is imperative to strengthen the capacity of early surveillance and early warning to build a sound public health system. Therefore, it is necessary to improve the multi-channel monitoring and early warning mechanism to improve the ability of real-time analysis and judgment. OBJECTIVE To explore the correlation of COVID-19 spread with Baidu search data in Beijing, so as to evaluate the possibility of monitoring the epidemic situation of COVID-19 with Baidu search data. METHODS This study compared the daily case counts of COVID-19 outbreak from January 20 to March 1, 2020 with Baidu search data for the same period in Beijing. After keyword selection, filtering and composition, the most correlated lag of the COVID-19 Baidu Search Index (CBSI) was used for comparison and linear regression model development. RESULTS Our findings showed a positive relationship of CBSI and the confirmed cases of COVID-19 (ρ=0.711, P < .001). The strongest correlation between COVID-19 confirmed cases and indices, CBSI, was at a lag of -11 days. The regression coefficient β1 of the established regression model was equal to 1.042 (P<.001), R2 was equal to 0.7, which indicated that Baidu search data could reflect 70% of the variation in COVID-19 cases. CONCLUSIONS COVID-19 Baidu Search index may be a good monitoring indicator for early detection of COVID-19 outbreaks.

Sign in / Sign up

Export Citation Format

Share Document