Zobrazeno 1 - 10
of 27 332
pro vyhledávání: '"YANG, JIN"'
Autor:
Zhao, Wan-Qian, Guo, Zhan-Yong, Guo, Yu-Qi, Li, Mei-Jun, Cao, Gang-Qiang, Tian, Zeng-Yuan, Chai, Ran, Qiu, Li-You, Zeng, Jin-Hua, Zhang, Xin-Ge, Qin, Tian-Cang, Yang, Jin-Yu, Chen, Ming-Jie, Song, Mei-Rong, Liang, Fei, Geng, Jun-Hui, Zhou, Chun-Yan, Zhang, Shu-Jie, Zhao, Li-Juan
This groundbreaking research extracted DNA from petroleum using nanoparticle affinity bead technology, yielding 3,159,020 petroleum DNA (pDNA) sequences, primarily environmental DNA. While most original in situ DNA (oriDNA) was lost, ancient DNA (aDN
Externí odkaz:
http://arxiv.org/abs/2412.06550
Autor:
Zhao, Wan-Qian, Guo, Zhan-Yong, Tian, Zeng-Yuan, Su, Tong-Fu, Cao, Gang-Qiang, Qi, Zi-Xin, Qin, Tian-Cang, Zhou, Wei, Yang, Jin-Yu, Chen, Ming-Jie, Zhang, Xin-Ge, Zhou, Chun-Yan, Zhu, Chuan-Jia, Tang, Meng-Fei, Wu, Di, Song, Mei-Rong, Guo, Yu-Qi, Qiu, Li-You, Liang, Fei, Li, Mei-Jun, Geng, Jun-Hui, Zhao, Li-Juan, Zhang, Shu-Jie
High quality ancient DNA (aDNA) is essential for molecular paleontology. Due to DNA degradation and contamination by environmental DNA (eDNA), current research is limited to fossils less than 1 million years old. The study successfully extracted DNA
Externí odkaz:
http://arxiv.org/abs/2412.06521
Autor:
Zhao, Wan-Qian, Zhang, Shu-Jie, Guo, Zhan-Yong, Tian, Zeng-Yuan, Cao, Gang-Qiang, Li, Mei-Jun, Qiu, Li-You, Yang, Jin-Yu, Wang, Yong-Kai, Zhang, Shu-Hui, Zheng, Zhi-Fang, Wu, Min-Zhi
This article critically examines the methodologies applied in ancient DNA (aDNA) research, particularly those developed by Dr. P\"a\"abo's team, which have significantly influenced the field. The focus is on the challenges of distinguishing original
Externí odkaz:
http://arxiv.org/abs/2412.06378
Deep learning (DL) has been widely applied into hyperspectral image (HSI) classification owing to its promising feature learning and representation capabilities. However, limited by the spatial resolution of sensors, existing DL-based classification
Externí odkaz:
http://arxiv.org/abs/2412.03893
Autor:
Yang, Jin-Lei, Li, Jie
The neutrino oscillation experiments provide definitive evidence of new physics beyond the Standard Model (SM), and the neutrino mass-squared differences and flavor mixing have been precisely measured. This study examines the neutrino sector within t
Externí odkaz:
http://arxiv.org/abs/2411.01744
The multi-modal posterior under unidentified nonparametric models yields poor mixing of Markov Chain Monte Carlo (MCMC), which is a stumbling block to Bayesian predictions. In this article, we conceptualize a prior informativeness threshold that is e
Externí odkaz:
http://arxiv.org/abs/2411.01382
We derived here the factor $\Upsilon$, which quantifies how the gravitational wave spectrum generated by sound waves in the radiation sector grows over time, in a universe with a generic expanding rate set by another dominant energy content. When the
Externí odkaz:
http://arxiv.org/abs/2410.23666
Self-interacting dark matter (SIDM) can address the small-scale anomalies and previous researches focused on such a SIDM heavier than GeV, for which the self-scattering cross-section is in the quantum resonance region and has a non-trivial velocity d
Externí odkaz:
http://arxiv.org/abs/2410.20645
Publikováno v:
Eur.Phys.J.C 84 (2024) 11, 1216
In an extension of MSSM with two triplets and a singlet, called the TNMSSM, there are seven neutralinos which can enrich the study of cold dark matter if one expects that the weakly interacting massive particle (WIMP) is responsible for the observati
Externí odkaz:
http://arxiv.org/abs/2410.13659
Convolutional neural networks (CNNs) have shown great effectiveness in medical image segmentation. However, they may be limited in modeling large inter-subject variations in organ shapes and sizes and exploiting global long-range contextual informati
Externí odkaz:
http://arxiv.org/abs/2410.02129