A Comparison of Eu-Doped -Fe2O3 Nanotubes and Nanowires for Acetone Sensing

Yali Cheng,Yifang Wang,Jinbao Zhang,Haiying Li,Li Liu,Yu Lina,Liting Du,Haojie Duan 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2017 NANO Vol.12 No.11

Pure and Eu-doped (1.0, 3.0, 5.0 wt.%) α-Fe2O3 (PFO and EFO) nanotubes and nanowires have been successfully synthesized through the combination of electrospinning and calcination techniques. The structures, morphologies and chemical compositions of the as-obtained products were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetric and differential scanning calorimetry (TG-DSC) and energy dispersive spectrum (EDS), respectively. To demonstrate the superior gas sensing performance of the doped nanotubes, a contrastive gas sensing study between PFO (EFO) nanotubes and nanowires was performed. It turned out that Eu doping could magnify the impact of morphology on gas sensitivity. Specifically, at the optimum operating temperature of 240 ℃, the response value of PFO nanotubes to 100 ppm acetone is slightly higher than that of nanowires (3.59/2.20). EFO (3.0 wt.%) nanotubes have a response of 84.05, which is almost 2.7 times as high as that of nanowires (31.54). Moreover, they possess more rapid response/recovery time (11 s and 36 s, respectively) than nanowires (17 s and 40 s, respectively). The lowest detection limit for acetone is 0.1 ppm and its response is 2.15. In addition, both of EFO nanotubes and nanowires sensors have a good linearity (0.1–500 ppm) and favorable selectivity in acetone detection.

Design and Implementation of Vibration Isolation System for Mobile Doppler Wind LIDAR

Xiaoquan Song,Chao Chen,Bingyi Liu,Jinbao Xia,Samo Stanič 한국광학회 2013 Current Optics and Photonics Vol.17 No.1

The operation of a Doppler wind LIDAR in a mobile environment is very sensitive to shocks and vibrations, which can cause critical failures such as misalignment of the optical path and damage to optical components. To be able to stabilize the LIDAR and to perform wind field measurements in motion, a shock absorption and vibration isolation system was designed and implemented. The performance of the vehicle-mounted Doppler wind LIDAR was tested in motion, first in a circular test route with a diameter of about 30 m and later in regular expressway traffic. The vibration isolation efficiency of the system was found to be higher than 82% in the main vibration area and shock dynamic deflection was smaller than maximal deflection of the isolator. The stability of the laser locking frequency in the same mobile environment before and after the vibration isolation system installation was also found to be greatly improved. The reliability of the vibration isolation system was confirmed by good results of the analysis of the LIDAR data, in particular the plane position indicator of the line of sight velocity and the wind profile.

A novel and effective approach to enhance the interfacial interactions of meta-aramid fibers

Hui Zhang,Xiaoyun Du,Jiawei Liu,YunHong Bai,Jingyi Nie,Jiaojun Tan,Zhibin He,Meiyun Zhang,Jinbao Li,Yonghao Ni 한국공업화학회 2023 Journal of Industrial and Engineering Chemistry Vol.120 No.-

Meta-aramid paper exhibits some unique properties, including high temperature resistance, electricalinsulation. However, due to the inherent chemical inertness of aramid fibers, the interfacial bondingbetween fibers is weak, which negatively affect the properties of aramid paper. Herein, we report a simple,effective and scalable process for substantially improving the interfacial bonding between aramidfibers, thus, mechanical and insulating properties of the meta-aramid composite paper, and it wasachieved by surface coating of aramid paper with meta-aramid stock solution that contains N, N dimethylacetamide(DMAc)-CaCl2 and high molecular weight poly (m-phenylene isophthalamide) polymers. Results show that the tensile strength, modulus, internal bond strength and tearing index of the resultantall-PMIA paper increased by 83 %, 58 %, 173 % and 89 %, respectively, in comparison with those of the control. The breakdown strength of the improved aramid paper is 190 % higher than that of the control paper,attaining 26.46 KV/mm. This work provides a simple, economical, efficient, and scalable method toimprove the overall performance of meta-aramid paper, which has great potential to be implementedat the industrial scale.

The deubiquitinating enzyme STAMBP is a newly discovered driver of triple-negative breast cancer progression that maintains RAI14 protein stability

Yang Qianqian,Yan Ding,Zou Chaoying,Xue Qian,Lin Shuhui,Huang Qingtian,Li Xiaofen,Tang Daolin,Chen Xin,Liu Jinbao 생화학분자생물학회 2022 Experimental and molecular medicine Vol.54 No.-

Triple-negative breast cancer (TNBC) is a heterogeneous malignancy in women. It is associated with poor prognosis, aggressive malignant behavior, and limited treatment options. In the ubiquitin‒proteasome system (UPS), deubiquitinases (DUBs) are potential therapeutic targets for various tumors. In this study, by performing unbiased siRNA screening, we identified STAMBP, a JAMM metalloprotease in the DUB family, as a driver of human TNBC tumor growth. Functionally, the knockdown of STAMBP inhibited the proliferation, migration, and invasion of multiple TNBC cell lines. Immunoprecipitation–mass spectrometry combined with functional and morphological analysis verified the interaction between STAMBP and the actin-binding protein RAI14. Mechanistically, STAMBP stabilized the RAI14 protein by suppressing the K48-linked ubiquitination of RAI14 and thus prevented its proteasomal degradation. Therefore, knocking down STAMBP resulted in the reduction in RAI14 protein levels and suppression of tumor growth in vitro and in vivo. Importantly, high levels of STAMBP were correlated with poor prognosis in TNBC patients. In summary, we reveal a previously unrecognized DUB pathway that promotes TNBC progression and provides a rationale for potential therapeutic interventions for the treatment of TNBC.

Artificial Intelligence in the Prediction of Gastrointestinal Stromal Tumors on Endoscopic Ultrasonography Images: Development, Validation and Comparison with Endosonographers

Lu Yi,Wu Jiachuan,Hu Minhui,Zhong Qinghua,Er Limian,Shi Huihui,Cheng Weihui,Chen Ke,Liu Yuan,Qiu Bingfeng,Xu Qiancheng,Lai Guangshun,Wang Yufeng,Luo Yuxuan,Mu Jinbao,Zhang Wenjie,Zhi Min,Sun Jiachen 거트앤리버 소화기연관학회협의회 2023 Gut and Liver Vol.17 No.6

Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers. The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions: We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.