Jian Yang

Jan 7, 2025 | onlinelibrary.wiley.com | Yiwei Wang |Yuliang Ma |Yang Liu |Jian Yang

1 Introduction Mitral annular calcification (MAC) is a degenerative process affecting the mitral annulus, with prevalence rates between 4.3% and 15%, increasing with age and other risk factors [1, 2]. Greater anatomical severity of MAC may indicate advanced disease progression. Over half of patients with mitral stenosis (MS) and MAC are estimated to forgo surgery, even when indicated [3-5].

Dec 21, 2024 | mdpi.com | Jian Yang

Open AccessArticle by Hanxuan Yang 1, Chao Geng 1, Majia Zheng 1, Zhiwei Zheng 1, Hui Long 1, Zijing Chang 2,3, Jieke Li 2,3, Hong Pang 2,3,* and Jian Yang 1 1 Southern Sichuan Gas District of PetroChina Southwest Oil & Gasfield Company, Luzhou 646000, China 2 State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China 3 College of Geosciences, China University of Petroleum, Beijing 102249, China * Author to whom correspondence should be...

Nov 9, 2024 | mdpi.com | Jian Yang |Xin Ding

This is an early access version, the complete PDF, HTML, and XML versions will be available soon. Open AccessArticle by Jian Yang Jian Yang Scilit Preprints.org Google Scholar * and Xin Ding Xin Ding Scilit Preprints.org Google Scholar School of Management, Anhui University, Hefei 230093, China *Author to whom correspondence should be addressed.

Nov 4, 2024 | postguam.com | Jian Yang

As we prepare for feasting on Thanksgiving Day, we look forward to the golden roasted turkey coming out of the oven. But we don’t look forward to possible food poisoning. Turkey, if not properly prepared, may have foodborne illness–causing disease organisms present, such as Salmonella, Clostridium perfringens, Campylobacter and other germs. Knowing a few food safety basics when handling turkey will ease your fears and bring you a safe and delicious turkey meal for the holidays.

Oct 27, 2024 | nature.com | Jian Yang

AbstractLeaf chlorophyll content (LCC) is crucial for monitoring the physiological processes of crops. Many studies have utilized spectral features to develop regression models for accurate LCC estimation, enabling the quantitative assessment and evaluation of crop growth status. The selection of optimal spectral features and regression algorithms significantly affects the precision of LCC estimation.