Search

Your search keyword '"Xu, Junhua"' showing total 780 results
Start Over Author "Xu, Junhua"
780 results on '"Xu, Junhua"'

175. Realizing the Ultralow Lattice Thermal Conductivity of Cu 3 SbSe 4 Compound via Sulfur Alloying Effect.

Author

Zhao, Lijun, Han, Haiwei, Lu, Zhengping, Yang, Jian, Wu, Xinmeng, Ge, Bangzhi, Yu, Lihua, Shi, Zhongqi, Karami, Abdulnasser M., Dong, Songtao, Hussain, Shahid, Qiao, Guanjun, and Xu, Junhua

Subjects
COPPER, THERMAL conductivity, SULFUR compounds, SEEBECK coefficient, SOLID solutions, THERMOELECTRIC materials
Abstract

Cu3SbSe4 is a potential p-type thermoelectric material, distinguished by its earth-abundant, inexpensive, innocuous, and environmentally friendly components. Nonetheless, the thermoelectric performance is poor and remains subpar. Herein, the electrical and thermal transport properties of Cu3SbSe4 were synergistically optimized by S alloying. Firstly, S alloying widened the band gap, effectively alleviating the bipolar effect. Additionally, the substitution of S in the lattice significantly increased the carrier effective mass, leading to a large Seebeck coefficient of ~730 μVK−1. Moreover, S alloying yielded point defect and Umklapp scattering to significantly depress the lattice thermal conductivity, and thus brought about an ultralow κlat ~0.50 Wm−1K−1 at 673 K in the solid solution. Consequently, multiple effects induced by S alloying enhanced the thermoelectric performance of the Cu3SbSe4-Cu3SbS4 solid solution, resulting in a maximum ZT value of ~0.72 at 673 K for the Cu3SbSe2.8S1.2 sample, which was ~44% higher than that of pristine Cu3SbSe4. This work offers direction on improving the comprehensive TE in solid solutions via elemental alloying. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

177. Acoustic metamaterials driven transdermal drug delivery for rapid and on-demand management of acute disease

Author

Xu, Junhua, primary, Cai, Hongwei, additional, Wu, Zhuhao, additional, Tian, Chunhui, additional, Li, Xiang, additional, Ao, Zheng, additional, Niu, Vivian, additional, Xiao, Xiao, additional, Jiang, Lei, additional, Khodoun, Marat, additional, Rothenberg, Marc, additional, Mackie, Ken, additional, Chen, Jun, additional, Lee, Luke, additional, and Guo, Feng, additional

Published
2022
Full Text
View/download PDF

179. QoS-Centric Diversified Web Service Recommendation Based on Personalized Determinantal Point Process.

Author

Kang, Guosheng, Liang, Bowen, Xu, Junhua, Liu, Jianxun, Wen, Yiping, and Kang, Yun

Subjects
WEB services, POINT processes, BUSINESS software, QUALITY of service, COMPUTER software development, PROBLEM solving
Abstract

With the popularity and widespread adoption of the SOA (Service-Oriented Architecture), the number of Web services has increased exponentially. Users tend to use online services for their daily business and software development needs. With the large number of Web service candidates, recommending desirable Web services that meet users' personalized QoS (Quality of Service) requirements becomes a challenging research issue, as the QoS preference is usually difficult to satisfy for users, i.e., the QoS preference is uncertain. To solve this problem, some recent works have aimed to recommend QoS-diversified services to enhance the probability of fulfilling the user's latent QoS preferences. However, the existing QoS-diversified service recommendation methods recommend services with a uniform diversity degree for different users, while the personalized diversity preference requirements are not considered. To this end, this paper proposes to mine a user's diversity preference from the their service invocation history and provides a Web service recommendation algorithm, named PDPP (Personalized Determinantal Point Process), through which a personalized service recommendation list with preferred diversity is generated for the user. Comprehensive experimental results show that the proposed approach can provide personalized and diversified Web services while ensuring the overall accuracy of the recommendation results. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

180. Methylation-mediated silencing of PTPRD induces pulmonary hypertension by promoting pulmonary arterial smooth muscle cell migration via the PDGFRB/PLCγ1 axis

Author

Xu, Junhua, primary, Zhong, Yanfeng, additional, Yin, Haoyang, additional, Linneman, John, additional, Luo, Yixuan, additional, Xia, Sijian, additional, Xia, Qinyi, additional, Yang, Lei, additional, Huang, Xingtao, additional, Kang, Kang, additional, Wang, Jun, additional, Niu, Yanqin, additional, Li, Li, additional, and Gou, Deming, additional

Published
2022
Full Text
View/download PDF

183. Relaxin inhibits 177 Lu-EDTMP associated cell death in osteosarcoma cells through notch-1 pathway

Author

XU, JUNHUA, WAN, SONG, CHEN, WEI, ZHANG, YI, JI, ZHENZHONG, XU, JUNHUA, WAN, SONG, CHEN, WEI, ZHANG, YI, and JI, ZHENZHONG

Abstract

177Lu-EDTMP (Ethylenediamine tetramethylene phosphonic acid) is the most used radioactive agent for pain palliation in bone cancer patients. The present study aims to study the impact of relaxin-2 on the 177Lu-EDTMP associated cell toxicity and death in osteosarcoma cells. MG63 and Saos-2 cells were cultured with 177Lu-EDTMP (37 MBq) for 24 h with and without pretreatment of recombinant relaxin 2 (RLXH2) for 12 h and 24 h. 177Lu-EDTMP associated cellular deterioration and death was determined by LDH, MTT, and trypan blue dye assays. ELISA-based kit was used to determine apoptotic DNA fragmentation. Western blotting was used to determine expression levels of apoptotic-related signalling pathway proteins like bcl2, poly(ADP-ribose) polymerase (PARP), and MAPK (mitogen-activated protein kinase). Our results found that RLXH2 counters 177Lu-EDTMP associated cellular toxicity. Similarly, RLXH2 was able to counter 177Lu-EDTMP induced cell death in a concentration and time-dependent manner. Furthermore, it was found that RLXH2 treatment prevents apoptosis in 177Lu-EDTMP challenged cells through activation of the notch-1 pathway in a concentration- and time-dependent manner. We reported that RLXH2 significantly declined cellular toxicity and apoptosis associated with 177Lu-EDTMP in MG63 and Saos-2 cells through the notch-1 pathway.

Published
2022

184. Forecasting Water Demand With the Long Short-Term Memory Deep Learning Mode

Author

Xu, Junhua

Abstract

Traditional methods often fall short in modeling the nonlinear, seasonally variable nature of urban water demand. This proposed solution is an integrated ARIMA-LSTM deep learning model, combining ARIMA's proficiency in linear trend and seasonal modeling with LSTM's strength in capturing nonlinear time dependencies. In these experiments, the authors trained and evaluated using daily water demand data from 2015 to 2020, with its performance validated for the year 2021. The ARIMA-LSTM model demonstrates promising results, outperforming individual models in terms of accuracy. In validation, it achieves a high coefficient of determination (R2) of 0.98 and a significantly low root mean square error (RMSE) of 2.94. These metrics indicate an excellent fit to the data and a high level of precision in its predictions. The significance of this research lies in its potential to advance the field of urban water demand forecasting, ultimately contributing to better water resource management and sustainability in urban areas.

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results