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Institution

Tongji University

EducationShanghai, China
About: Tongji University is a education organization based out in Shanghai, China. It is known for research contribution in the topics: Population & Adsorption. The organization has 76116 authors who have published 81176 publications receiving 1248911 citations. The organization is also known as: Tongji & Tóngjì Dàxué.


Papers
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Journal ArticleDOI
TL;DR: In this paper, several Bayesian models were developed to model the crash data from 170 signalized intersections in the state of Florida and the safety impacts of risk factors such as geometric design features, traffic control, and traffic flow characteristics were evaluated.

226 citations

Journal ArticleDOI
TL;DR: To report the performance of massively parallel sequencing (MPS) based prenatal noninvasive fetal trisomy test based on cell‐free DNA sequencing from maternal plasma in a routine clinical setting in China.
Abstract: Objective To report the performance of massively parallel sequencing (MPS) based prenatal noninvasive fetal trisomy test based on cell-free DNA sequencing from maternal plasma in a routine clinical setting in China. Method The MPS-based test was offered as a prenatal screening test for trisomies 21 and 18 to pregnant women in 49 medical centers over 2years. A total of 11263 participants were recruited and the MPS-based test was performed in 11105 pregnancies. Fetal outcome data were obtained after the expected date of confinement. Results One hundred ninety cases were classified as positive, including 143 cases of trisomy 21 and 47 cases of trisomy 18. With the karyotyping results and the feed back of fetal outcome data, we observed one false positive case of trisomy 21, one false positive case of trisomy 18 and no false negative cases, indicating 100% sensitivity and 99.96% specificity for the detection of trisomies 21 and 18. Conclusion Our large-scale multicenter study proved that the MPS-based test is of high sensitivity and specificity in detecting fetal trisomies 21 and 18. The introduction of this screening test into a routine clinical setting could avoid about 98% of invasive prenatal diagnostic procedures. © 2012 John Wiley & Sons, Ltd. Supporting information may be found in the online version of this article.

226 citations

Journal ArticleDOI
TL;DR: In this article, the authors demonstrate that by manipulating the carrier scattering mechanism in n-type Mg3Sb2-based materials, a substantial improvement in carrier mobility, and hence the power factor, can be achieved.
Abstract: Achieving higher carrier mobility plays a pivotal role for obtaining potentially high thermoelectric performance. In principle, the carrier mobility is governed by the band structure as well as by the carrier scattering mechanism. Here, we demonstrate that by manipulating the carrier scattering mechanism in n-type Mg3Sb2-based materials, a substantial improvement in carrier mobility, and hence the power factor, can be achieved. In this work, Fe, Co, Hf, and Ta are doped on the Mg site of Mg3.2Sb1.5Bi0.49Te0.01, where the ionized impurity scattering crosses over to mixed ionized impurity and acoustic phonon scattering. A significant improvement in Hall mobility from ∼16 to ∼81 cm2⋅V-1⋅s-1 is obtained, thus leading to a notably enhanced power factor of ∼13 μW⋅cm-1⋅K-2 from ∼5 μW⋅cm-1⋅K-2 A simultaneous reduction in thermal conductivity is also achieved. Collectively, a figure of merit (ZT) of ∼1.7 is obtained at 773 K in Mg3.1Co0.1Sb1.5Bi0.49Te0.01 The concept of manipulating the carrier scattering mechanism to improve the mobility should also be applicable to other material systems.

226 citations

Journal ArticleDOI
TL;DR: In this paper, a pulsed laser deposition process using ozone as an oxidant is developed to grow NiO nanoparticles on highly conductive three-dimensional (3D) graphene foam (GF).
Abstract: A pulsed laser deposition process using ozone as an oxidant is developed to grow NiO nanoparticles on highly conductive three-dimensional (3D) graphene foam (GF). The excellent electrical conductivity and interconnected pore structure of the hybrid NiO/GF electrode facilitate fast electron and ion transportation. The NiO/GF electrode displays a high specific capacitance (1225 F g−1 at 2 A g−1) and a superb rate capability (68% capacity retention at 100 A g−1). A novel asymmetric supercapacitor with high power and energy densities is successfully fabricated using NiO/GF as the positive electrode and hierarchical porous nitrogen-doped carbon nanotubes (HPNCNTs) as the negative electrode in aqueous KOH solution. Because of the high individual capacitive performance of NiO/GF and HPNCNTs, as well as the synergistic effect between the two electrodes, the asymmetric capacitor exhibits an excellent energy storage performance. At a voltage range from 0.0 to 1.4 V, an energy density of 32 W h kg−1 is achieved at a power density of 700 W kg−1. Even at a 2.8 s charge–discharge rate (42 kW kg−1), an energy density as high as 17 W h kg−1 is retained. Additionally, the NiO/GF//HPNCNT asymmetric supercapacitor exhibits excellent cycling durability, with 94% specific capacitance retained after 2000 cycles.

226 citations

Journal ArticleDOI
TL;DR: An increase in remote sensing and ancillary data sets opens up the possibility of utilizing multimodal data sets in a joint manner to further improve the performance of the processing approaches with respect to applications at hand.
Abstract: The recent, sharp increase in the availability of data captured by different sensors, combined with their considerable heterogeneity, poses a serious challenge for the effective and efficient processing of remotely sensed data. Such an increase in remote sensing and ancillary data sets, however, opens up the possibility of utilizing multimodal data sets in a joint manner to further improve the performance of the processing approaches with respect to applications at hand. Multisource data fusion has, therefore, received enormous attention from researchers worldwide for a wide variety of applications. Moreover, thanks to the revisit capability of several

226 citations


Authors

Showing all 76610 results

NameH-indexPapersCitations
Gang Chen1673372149819
Yang Yang1642704144071
Georgios B. Giannakis137132173517
Jian Li133286387131
Jianlin Shi12785954862
Zhenyu Zhang118116764887
Ju Li10962346004
Peng Wang108167254529
Qian Wang108214865557
Yan Zhang107241057758
Richard B. Kaner10655766862
Han-Qing Yu10571839735
Wei Zhang104291164923
Fabio Marchesoni10460774687
Feng Li10499560692
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023238
20221,051
20219,713
20208,502
20197,517
20186,352