Interventions to prevent HIV and Hepatitis C among people who inject drugs:Latest evidence of effectiveness from a systematic review (2011 to 2020)

Autor: Norah Palmateer, Victoria Hamill, Anne Bergenstrom, Harriet Bloomfield, Lara Gordon, Jack Stone, Hannah Fraser, Thomas Seyler, Yuejiao Duan, Richard Tran, Kirsten Trayner, Christopher Biggam, Shanley Smith, Peter Vickerman, Matt Hickman, Sharon Hutchinson

Publikováno v: Palmateer, N, Hamill, V, Bergenstrom, A, Bloomfield, H, Gordon, L, Stone, J, Fraser, H, Seyler, T, Duan, Y, Tran, R, Trayner, K, Biggam, C, Smith, S, Vickerman, P T, Hickman, M & Hutchinson, S 2022, ' Interventions to prevent HIV and Hepatitis C among people who inject drugs : Latest evidence of effectiveness from a systematic review (2011 to 2020) ', International Journal of Drug Policy, vol. 109, 103872 . https://doi.org/10.1016/j.drugpo.2022.103872

BackgroundHepatitis C virus (HCV) and HIV remain prevalent among people who inject drugs (PWID) and transmission is usually associated with injecting risk behaviour (IRB). We update a 2011 review of reviews (RoR) to assess the latest evidence on the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b8f8d86df7456ba9683e04b9eef4772
https://research-information.bris.ac.uk/en/publications/e60ff12b-71db-4523-8ad8-6e5641181e8a

International taxation sentiment and COVID-19 crisis

Autor: Chenjiang Bai, Yuejiao Duan, Congya Liu, Leiju Qiu

Publikováno v: Research in international business and finance. 63

Investigating public sentiment regarding tax policy during the COVID-19 pandemic could be useful for understanding the experiences across societies. Using Linguistic Inquiry and Word Count to investigate and quantitatively measure the pandemic's effe

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ae0d1ee2c7c9589c0812c75089e4e2d
https://pubmed.ncbi.nlm.nih.gov/36250041

Assessing machine learning for forecasting economic risk: Evidence from an expanded Chinese financial information set

Autor: John W. Goodell, Haoran Li, Yuejiao Duan, Xinming Li

Publikováno v: Finance Research Letters. 46:102273

While data sets used for forecasting can now be greatly improved, expanding data and information size also exposes weaknesses in traditional forecast models. We assess machine learning methods for forecasting monetary policy actions and concomitant m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ca36407982993a325bbec5947a8966ed
https://doi.org/10.1016/j.frl.2021.102273

COVID-19 Sentiment and the Chinese Stock Market: Evidence from the Official News Media and Sina Weibo

Autor: Lanbiao Liu, Yuejiao Duan, Zhuo Wang

Publikováno v: Research in International Business and Finance. 58:101432

This study quantitatively measures the Chinese stock market’s reaction to sentiments regarding the Novel Coronavirus 2019 (COVID-19). Using 6.3 million items of textual data extracted from the official news media and Sina Weibo blogsite, we develop

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9e73f3dd07998ef3fa59e68822b41ac2
https://doi.org/10.1016/j.ribaf.2021.101432

Does the Quantile Regression Forest Learn More Information on Chinese Systemic Risk?

Autor: Haoran Li, Yuejiao Duan, Xiaoyun Fan

Publikováno v: SSRN Electronic Journal.

This article applies the quantile regression forest (QRF), which is an improved method for predicting future monetary policy and macroeconomic downside risks in China. The information used to forecast is derived from Chinese systemic risk. We constru

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3657b2208b5149bbc039162aa304b285
https://doi.org/10.2139/ssrn.3556400