Institution
University of Macau
Education•Macao, Macau, China•
About: University of Macau is a education organization based out in Macao, Macau, China. It is known for research contribution in the topics: Population & Control theory. The organization has 6636 authors who have published 18324 publications receiving 327384 citations. The organization is also known as: UM & UMAC.
Papers published on a yearly basis
Papers
More filters
••
TL;DR: In this paper, a bifunctional catalyst based on phosphorus-doped LaFeO3-δ for ORR and OER in alkaline solutions was developed and the remarkable electrocatalytic performance was attributed to larger amount of O22−/O− species, trace amount of Fe4+ species, and optimized eg electron filling (≈ 1), benefiting from the doping effect of phosphorus.
173 citations
••
TL;DR: In vitro assays indicated that the cancer cells were destroyed by using a nanoparticle concentration at 0.2 μg/mL and a light dose of ∼120 J/cm2, indicating the significantly enhanced efficiency of the EEPT method when compared to typical PDT that requires a photosensitizer of >10 μg/ mL for effective cell killing under the same light dose.
Abstract: Light has been widely used for cancer therapeutics such as photodynamic therapy (PDT) and photothermal therapy. This paper describes a strategy called enzyme-enhanced phototherapy (EEPT) for cancer treatment. We constructed a nanoparticle platform by covalent conjugation of glucose oxidase (GOx) to small polymer dots, which could be persistently immobilized into a tumor. While the malignant tumors have high glucose uptake, the GOx efficiently catalyzes the glucose oxidation with simultaneous generation of H2O2. Under light irradiation, the in situ generated H2O2 was photolyzed to produce hydroxyl radical, the most reactive oxygen species, for killing cancer cells. In vitro assays indicated that the cancer cells were destroyed by using a nanoparticle concentration at 0.2 μg/mL and a light dose of ∼120 J/cm2, indicating the significantly enhanced efficiency of the EEPT method when compared to typical PDT that requires a photosensitizer of >10 μg/mL for effective cell killing under the same light dose. Furth...
172 citations
••
TL;DR: A methodology is presented for Bayesian structural model updating using noisy incomplete modal data corresponding to natural frequencies and partial mode shapes of some of the modes of a structural system to find the most probable model within a specified class of structural models.
Abstract: A methodology is presented for Bayesian structural model updating using noisy incomplete modal data
corresponding to natural frequencies and partial mode shapes of some of the modes of a structural system.
The procedure can be used to find the most probable model within a specified class of structural models,
based on the incomplete modal data, as well as the most probable values of the system natural frequencies
and the full system mode shapes. The method does not require matching measured modes with
corresponding modes from the structural model, which is in contrast to many existing methods. To find the
most probable values of the structural model parameters and system modal parameters, the method uses an
iterative scheme involving a series of coupled linear optimization problems. Furthermore, it does not
require solving the eigenvalue problem of any structural model; instead, the eigenvalue equations appear in
the prior probability distribution to provide soft constraints. The method appears to be computationally
efficient and robust, judging from its successful application to noisy simulated data for a ten-storey
building model and for a three-dimensional braced-frame model. This latter example is also used to
demonstrate an application to structural health monitoring.
171 citations
••
TL;DR: Examining the factors that an influence higher education students’ intention to use technology showed that perceived usefulness and attitude toward computer use were significant determinants of the intention toUse technology, while perceived ease of use influenced intention to Use technology through attitude towards computer use.
Abstract: The aim of this study is to examine the factors that an influence higher education students’ intention to use technology. Using an extended technology acceptance model as a research framework, a sample of 314 university students were surveyed on their responses to seven constructs hypothesized to explain their intention to use technology. Data were analyzed using structural equation modeling and the results showed that perceived usefulness and attitude toward computer use were significant determinants of the intention to use technology, while perceived ease of use influenced intention to use technology through attitude towards computer use. Computer self-efficacy and subjective norm acted as antecedents for perceived usefulness and attitude towards computer use, while facilitating conditions acted as antecedents for perceived ease of use and attitude towards computer use. Together these constructs explained 54.7 % of the variance in students’ intention to use technology. Implications of the findings were also discussed.
170 citations
••
TL;DR: Negative affectivity may be a key mechanism by which FOMO may drive PSU, but future research should clarify the directionality among these variables.
170 citations
Authors
Showing all 6766 results
Name | H-index | Papers | Citations |
---|---|---|---|
Henry T. Lynch | 133 | 925 | 86270 |
Chu-Xia Deng | 125 | 444 | 57000 |
H. Vincent Poor | 109 | 2116 | 67723 |
Peng Chen | 103 | 918 | 43415 |
George F. Gao | 102 | 793 | 82219 |
MengChu Zhou | 96 | 1124 | 36969 |
Gang Li | 93 | 486 | 68181 |
Rob Law | 81 | 714 | 31002 |
Zongjin Li | 80 | 630 | 22103 |
Han-Ming Shen | 80 | 237 | 27410 |
Heng Li | 79 | 745 | 23385 |
Lionel M. Ni | 75 | 466 | 28770 |
C. L. Philip Chen | 74 | 482 | 20223 |
Chun-Su Yuan | 72 | 397 | 21089 |
Joao P. Hespanha | 72 | 418 | 39004 |