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Yinuo Liu on Muck Rack

Yinuo Liu

As seen in: Nature, Wiley Online Library, MDPI, Taylor & Francis Online, ACS Publications, Arthritis Research & Therapy, Royal Society of Chemistry, BioRxiv, Canadian Journal of Infectious Diseases & Medical Microbiology, Physiological Research and
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Articles

3D-printed living materials for anammox–denitrification coupling in wastewater treatment

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By Yinuo Liu, Huilin Wan, Jiaojiao Niu, Yiwen Liu, Yindong Tong, Guanyi Chen, Yingxin Zhao, Enlei Liang, Xuezhuang Liu, Chunfang Chao, Bibek Bamanu
| Nature Verified
Abstract Wastewater treatment, especially nitrogen removal, is a major contributor to global energy consumption and greenhouse gas emissions, driving the need for more sustainable nitrogen removal technologies. However, the practical application of anaerobic ammonium oxidation (anammox) systems is limited by persistent nitrate accumulation, as efficient cross-feeding between anammox bacteria and denitrifiers is hindered by metabolite diffusion and retention challenges.
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A Risk-Averse Principal-Agent Framework: Private Security Companies in China’s Overseas Interest Protection

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By Chuchu Zhang, Yinuo Liu, Yixiong Huang
| Taylor & Francis Online
ABSTRACT As China’s investments under the Belt and Road Initiative proliferate, securing its extraterritorial interests has assumed urgency. With a military footprint abroad lagging behind its economic clout, Beijing has advocated for state-owned enterprises to entrust protective responsibilities to Chinese private security companies (PSCs).
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The effectiveness of CBT-based NLP-enabled AI conversational agents for mental health intervention: a systematic review and meta-analysis

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By Yaming Hang, Wenzhi Wu, Yi Feng, Kai Yan, Yinuo Liu, Xiyao Xiao, Zhihong Qiao
| Nature Verified
Abstract Natural language processing (NLP)-enabled artificial intelligence (AI) conversational agents (CAs) are increasingly adopted in digital mental health interventions, yet the efficacy of such CAs grounded in cognitive behavioral therapy (CBT) remains unclear. This study aims to examine the intervention effectiveness of CBT-based NLP-enabled AI CAs in various mental health problems. A total of 15 randomized controlled trials with 1737 participants were included in the analysis.
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