Zobrazeno 1 - 10
of 1 064
pro vyhledávání: '"ZHANG Boya"'
Autor:
Xu, Gang, Zhou, Xin, Wang, Molin, Zhang, Boya, Jiang, Wenhao, Laden, Francine, Suh, Helen H., Szpiro, Adam A., Spiegelman, Donna, Wang, Zuoheng
One way to quantify exposure to air pollution and its constituents in epidemiologic studies is to use an individual's nearest monitor. This strategy results in potential inaccuracy in the actual personal exposure, introducing bias in estimating the h
Externí odkaz:
http://arxiv.org/abs/2410.07135
Publikováno v:
Nuclear Engineering and Technology, Vol 52, Iss 7, Pp 1409-1416 (2020)
The study of heat transfer coefficient of supercritical water plays an important role in improving the heat transfer efficiency of the reactor. Taking the supercritical natural circulation experimental bench as the research object, the effects of pow
Externí odkaz:
https://doaj.org/article/b66c6eea3dbe437080c769471764eef6
Publikováno v:
Zhongliu Fangzhi Yanjiu, Vol 47, Iss 2, Pp 135-140 (2020)
In recent years, more and more attention has been paid to the development of cancer diagnosis and treatment, including nanoparticles-based methods. Silica nanoparticles show great potential in the field of tumor diagnosis and treatment because of its
Externí odkaz:
https://doaj.org/article/2c9e018683ae443fb575a7143a42befa
Autor:
Yazdani, Anthony, Bornet, Alban, Khlebnikov, Philipp, Zhang, Boya, Rouhizadeh, Hossein, Amini, Poorya, Teodoro, Douglas
Adverse drug events (ADEs) significantly impact clinical research, causing many clinical trial failures. ADE prediction is key for developing safer medications and enhancing patient outcomes. To support this effort, we introduce CT-ADE, a dataset for
Externí odkaz:
http://arxiv.org/abs/2404.12827
Publikováno v:
Frontiers in Energy Research, Vol 8 (2020)
The study of the commonness and differences of natural circulation of different liquid metals plays an important role in improving the safety of reactors. The numerical simulation of liquid metal natural circulation heat transfer was carried out by C
Externí odkaz:
https://doaj.org/article/5219eae781384d3abc917147995f538a
Adversarial attacks can mislead neural network classifiers. The defense against adversarial attacks is important for AI safety. Adversarial purification is a family of approaches that defend adversarial attacks with suitable pre-processing. Diffusion
Externí odkaz:
http://arxiv.org/abs/2310.18762
Adversarial attacks have the potential to mislead deep neural network classifiers by introducing slight perturbations. Developing algorithms that can mitigate the effects of these attacks is crucial for ensuring the safe use of artificial intelligenc
Externí odkaz:
http://arxiv.org/abs/2307.04333
Efficiently sampling from un-normalized target distributions is a fundamental problem in scientific computing and machine learning. Traditional approaches like Markov Chain Monte Carlo (MCMC) guarantee asymptotically unbiased samples from such distri
Externí odkaz:
http://arxiv.org/abs/2306.04952
Publikováno v:
In Science of the Total Environment 15 November 2024 951
Autor:
Dai, Yiming, Ding, Jiayun, Wang, Zheng, Zhang, Boya, Guo, Qin, Guo, Jianqiu, Qi, Xiaojuan, Lu, Dasheng, Chang, Xiuli, Wu, Chunhua, Zhang, Jiming, Zhou, Zhijun
Publikováno v:
In Environmental Research 15 November 2024 261