Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Ding-bang CHEN"'
Autor:
Xiang‐xue Zhou, Xun‐hua Li, Ding‐bang Chen, Chao Wu, Li Feng, Hao‐lin Qin, Xiao‐Yong Pu, Xiu‐ling Liang
Publikováno v:
Brain and Behavior, Vol 9, Iss 12, Pp n/a-n/a (2019)
Abstract Objective To evaluate different injury factors and pathological characteristics of the brain at different disease stages in toxic milk (TX) mice, an animal model of Wilson's disease (WD). Methods Thirty TX mice (10 each at 3, 6 and 12 months
Externí odkaz:
https://doaj.org/article/934656f1bb3b48708226b1291c85877e
Publikováno v:
Chinese Journal of Contemporary Neurology and Neurosurgery, Vol 17, Iss 7, Pp 477-483 (2017)
Neurogenetic diseases are difficult to diagnose due to complicated phenotypes. Genetic testing is always the option for final diagnosis. With the progress and update of molecular diagnostic techniques, especially widely usage of next - generation seq
Externí odkaz:
https://doaj.org/article/4562f16e40384900b66e6793497e1d4b
Autor:
Ding-bang CHEN, Chao WU, Li FENG, Gui-ling MO, Bing LIAO, Da-wei LIU, Jin-lang WU, Qiang WU, Xun-hua LI
Publikováno v:
Chinese Journal of Contemporary Neurology and Neurosurgery, Vol 14, Iss 6, Pp 485-489 (2014)
Objective To study the muscular pathological characteristics in riboflavin-responsive lipid storage myopathy before and after treatment. Methods A 10-year follow-up visit was made on a patient with riboflavin-responsive lipid storage myopathy, and th
Externí odkaz:
https://doaj.org/article/867ba418ff974c5f8f3d3bec52a84f03
Publikováno v:
PLoS ONE, Vol 7, Iss 8 (2012)
Externí odkaz:
https://doaj.org/article/b465a770f46d451c90e266ba90a5087b
Publikováno v:
PLoS ONE, Vol 7, Iss 5, p e37709 (2012)
Wilson disease (WD) is characterized by the accumulation of copper arising from a mutation in the ATP7B gene. Penicillamine (PA) makes 10-50% of the patients with neurologic symptoms neurologically worse at the early stage of administration. The aim
Externí odkaz:
https://doaj.org/article/b8cf70287f8b4762acec8906b1128dc4
Autor:
Ding-Bang Chen, 陳定邦
99
This study uses mixed data sampling (MIDAS) and the rolling window method (RW) that conditions of volatility into the CARR model. We propose an augmented CARR model that combine advantage of both range-based volatility and high frequency date
This study uses mixed data sampling (MIDAS) and the rolling window method (RW) that conditions of volatility into the CARR model. We propose an augmented CARR model that combine advantage of both range-based volatility and high frequency date
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/57521056928632824872
Publikováno v:
COMPUTING AND INFORMATICS; Vol. 40 No. 6 (2021): Computing and Informatics; 1263–1294
During the Covid pandemic, the importance of wearing mask has been noted globally. Additionally, crowded human clusters facilitated the transmission of the virus, which brings up the need for new systems for monitoring such situations. To address suc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f8a1b58cc79eb5da9b51d978d85aead4
https://www.cai.sk/ojs/index.php/cai/article/view/2021_6_1263
https://www.cai.sk/ojs/index.php/cai/article/view/2021_6_1263
Publikováno v:
2020 International Automatic Control Conference (CACS)
In this paper a visual system equipped with state of the art in Deep Learning is presented which could be employed in the robotics platforms for the pandemic situation where human – human contact needs to be limited in order to perform various dete
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d779af108c7dab8d8dacf5f5d55fa35
Publikováno v:
PacificVis
In this paper, we present a visualization system for users to study multivariate time series data. They first identify trends or anomalies from a global view and then examine details in a local view. Specifically, we train a neural network to project
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::daf0ad5617d464a2f5a8744c186f4e6e
https://doi.org/10.1109/pacificvis48177.2020.9915
https://doi.org/10.1109/pacificvis48177.2020.9915
Publikováno v:
Computing & Informatics; 2021, Vol. 40 Issue 6, p1263-1294, 32p