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1,156 results on '"Li, Wen-Bin"'

6. MFV approach to robust estimate of neutron lifetime

Author

Zhang, Jiang, Zhang, Sen, Zhang, Zhen-Rong, Zhang, Pu, Li, Wen-Bin, and Hong, Yan

Subjects
Physics - Data Analysis, Statistics and Probability, Astrophysics - Cosmology and Nongalactic Astrophysics, Nuclear Experiment
Abstract

Aiming at evaluating the lifetime of the neutron, we introduce a novel statistical method to analyse the updated compilation of precise measurements including the 2022 dataset of Particle Data Group (PDG). Based on the minimization for the information loss principle, unlike the median statistics method, we apply the most frequent value (MFV) procedure to estimate the neutron lifetime, irrespective of the Gaussian or non-Gaussian distributions. Providing a more robust way, the calculated result of the MFV is $\tau_n=881.16^{+2.25}_{-2.35}$ s with statistical bootstrap errors, while the result of median statistics is $\tau_n=881.5^{+5.5}_{-3}$ s according to the binomial distribution. Using the different central estimates, we also construct the error distributions of neutron lifetime measurements and find the non-Gaussianity, which is still meaningful.

Published
2022
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17. CTNI-08. DB102-01 ENGAGE STUDY: A BIOMARKER-GUIDED, RANDOMIZED, DOUBLE-BLIND, PLACEBO-CONTROLLED, MULTI-CENTER PHASE 3 CLINICAL TRIAL OF DB102 IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA (GBM)

Author

Bota, Daniela, Butowski, Nicholas, Piccioni, David, De la Fuente, Macarena, Mao, Ying, Li, Wen-Bin, Trusheim, John, Fink, Karen, Campian, Jian, Lobbous, Mina, Portnow, Jana, Zhu, Jay-Jiguang, Pearlman, Michael, Rudnick, Jeremy, Lesser, Glen, Drappatz, Jan, Vaillant, Brian, Sun, Show-Li, and Luo, Wen

Subjects
Clinical Research, Rare Diseases, Brain Disorders, Brain Cancer, Neurosciences, Clinical Trials and Supportive Activities, Genetics, Cancer, Patient Safety, Orphan Drug, Human Genome, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, Good Health and Well Being, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Abstract: Precision medicine is vital for treating many cancers. Lack of valid biomarkers might contribute to the failure of drug therapy for GBM. The Denovo Genomic Marker 1 (DGM1), a novel pharmacogenomic biomarker, has been discovered by a genome-wide screen of patients treated with DB102 (enzastaurin) in a trial for lymphoma. Similarly, retrospective analyses showed that DB102 significantly improved outcomes in the biomarker positive GBM patients treated with DB102, regardless of MGMT promoter methylation status. The ENGAGE Study (DB102-01, NCT03776071) is a global Phase 3 clinical trial to confirm clinical benefits in patients with newly diagnosed GBM who are DGM1 biomarker positive. This is a prospective, randomized, double-blind, placebo-controlled, multi-center study. A total of 318 patients with newly diagnosed GBM will be enrolled. After screening, patients will be randomized to receive radiation therapy (RT) and temozolomide (TMZ) plus either DB102 or a matched placebo for 6 weeks in the Concurrent Phase, followed by DB102 or placebo for approximately 5 weeks in the Single-Agent Phase and then TMZ plus DB102 or placebo in the Adjuvant Phase (up to 12 cycles). Thereafter DB102 or placebo may be continued as a single agent for up to 2 years. The primary endpoint is overall survival (OS). The secondary endpoints include progression free survival (PFS), objective response rate (ORR) and drug safety. By April 2021, the safety-run-in part was completed. The study is now open for enrollment in the US and soon in Canada and China.

Published
2021

18. Controlling core-hole lifetime through an x-ray planar cavity

Author

Huang, Xin-Chao, Kong, Xiang-Jin, Li, Tian-Jun, Ma, Zi-Ru, Wang, Hong-Chang, Liu, Gen-Chang, Wang, Zhan-Shan, Li, Wen-Bin, and Zhu, Lin-Fan

Subjects
Physics - Atomic Physics, Quantum Physics
Abstract

It has long been believed that core-hole lifetime (CHL) of an atom is an intrinsic physical property, and controlling it is significant yet is very hard. Here, CHL of the 2p state of W atom is manipulated experimentally through adjusting the emission rate of a resonant fluorescence channel with the assistance of an x-ray thin-film planar cavity. The emission rate is accelerated by a factor linearly proportional to the cavity field amplitude, that can be directly controlled by choosing different cavity modes or changing the angle offset in experiment. This experimental observation is in good agreement with theoretical predictions. It is found that the manipulated resonant fluorescence channel even can dominate the CHL. The controllable CHL realized here will facilitate the nonlinear investigations and modern x-ray scattering techniques in hard x-ray region., Comment: 5 pages, 4 figures

Published
2021
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29. Audio-only Bird Species Automated Identification Method with Limited Training Data Based on Multi-Channel Deep Convolutional Neural Networks

Author

Xie, Jiang-jian, Ding, Chang-qing, Li, Wen-bin, and Cai, Cheng-hao

Subjects
Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Based on the transfer learning, we design a bird species identification model that uses the VGG-16 model (pretrained on ImageNet) for feature extraction, then a classifier consisting of two fully-connected hidden layers and a Softmax layer is attached. We compare the performance of the proposed model with the original VGG16 model. The results show that the former has higher train efficiency, but lower mean average precisions(MAP). To improve the MAP of the proposed model, we investigate the result fusion mode to form multi-channel identification model, the best MAP reaches 0.9998. The number of model parameters is 13110, which is only 0.0082% of the VGG16 model. Also, the size demand of sample is decreased., Comment: 11 pages,11 figures

Published
2018

34. Corrigendum: ATP6V0C is associated with febrile seizures and epilepsy with febrile seizures plus

Author

Tian, Yang, primary, Zhai, Qiong-Xiang, additional, Li, Xiao-Jing, additional, Shi, Zhen, additional, Cheng, Chuan-Fang, additional, Fan, Cui-Xia, additional, Tang, Bin, additional, Zhang, Ying, additional, He, Yun-Yan, additional, Li, Wen-Bin, additional, Luo, Sheng, additional, Hou, Chi, additional, Chen, Wen-Xiong, additional, Liao, Wei-Ping, additional, and Wang, Jie, additional

Published
2024
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41. Metal‐Organic Framework Based Sensors for Benzene Vapor.

Author

Li, Wen‐Bin, Liang, Gang, Chen, De‐Jian, Ye, Jia‐Wen, Liu, Jie‐Wei, Li, Jing, Shao, Huai‐Yu, Mo, Zong‐Wen, and Chen, Xiao‐Ming

Subjects
*METAL-organic frameworks, *BENZENE, *VAPORS, *SIGNAL detection, *DETECTORS
Abstract

Sensing of benzene vapor is a hot spot due to the volatile drastic carcinogen even at trace concentration. However, achieving convenient and rapid detection is still a challenge. As a sort of functional porous material, metal‐organic frameworks (MOFs) have been developed as detection sensors by adsorbing benzene vapor and converting it into other signals (fluorescence intensity/wavelength, chemiresistive, weight or color, etc.). Supramolecular interaction between benzene molecules and the host framework, aperture size/shape and structural flexibility are influential factors in the performance of MOF‐based sensors. Therefore, enhancing the host‐guest interactions between the host framework and benzene molecules, or regulating the diffusion rate of benzene molecules by changing the aperture size/shape and flexibility of the host framework to enhance the detection signal are effective strategies for constructing MOF‐based sensors. This concept highlights several types of MOF‐based sensors for the detection of benzene vapor. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Molecular footprints of domestication and improvement in soybean revealed by whole genome re-sequencing.

Author

Li, Ying-hui, Zhao, Shan-cen, Ma, Jian-xin, Li, Dong, Yan, Long, Li, Jun, Qi, Xiao-tian, Guo, Xiao-sen, Zhang, Le, He, Wei-ming, Chang, Ru-zhen, Liang, Qin-si, Guo, Yong, Ye, Chen, Wang, Xiao-bo, Tao, Yong, Guan, Rong-xia, Wang, Jun-yi, Liu, Yu-lin, Jin, Long-guo, Zhang, Xiu-qing, Liu, Zhang-xiong, Zhang, Li-juan, Chen, Jie, Wang, Ke-jing, Li, Rui-qiang, Chen, Peng-yin, Li, Wen-bin, Reif, Jochen, Purugganan, Michael, Wang, Jian, Zhang, Meng-chen, Wang, Jun, Qiu, Li-juan, and Nielsen, Rasmus

Subjects
Bayes Theorem, Breeding, Evolution, Molecular, Genetics, Population, Genome, Plant, Haplotypes, Humans, INDEL Mutation, Molecular Sequence Annotation, Phylogeny, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Selection, Genetic, Sequence Analysis, DNA, Glycine max
Abstract

BACKGROUND: Artificial selection played an important role in the origin of modern Glycine max cultivars from the wild soybean Glycine soja. To elucidate the consequences of artificial selection accompanying the domestication and modern improvement of soybean, 25 new and 30 published whole-genome re-sequencing accessions, which represent wild, domesticated landrace, and Chinese elite soybean populations were analyzed. RESULTS: A total of 5,102,244 single nucleotide polymorphisms (SNPs) and 707,969 insertion/deletions were identified. Among the SNPs detected, 25.5% were not described previously. We found that artificial selection during domestication led to more pronounced reduction in the genetic diversity of soybean than the switch from landraces to elite cultivars. Only a small proportion (2.99%) of the whole genomic regions appear to be affected by artificial selection for preferred agricultural traits. The selection regions were not distributed randomly or uniformly throughout the genome. Instead, clusters of selection hotspots in certain genomic regions were observed. Moreover, a set of candidate genes (4.38% of the total annotated genes) significantly affected by selection underlying soybean domestication and genetic improvement were identified. CONCLUSIONS: Given the uniqueness of the soybean germplasm sequenced, this study drew a clear picture of human-mediated evolution of the soybean genomes. The genomic resources and information provided by this study would also facilitate the discovery of genes/loci underlying agronomically important traits.

Published
2013

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