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43 results on '"Wang, Xianqi"'

1. IGEV++: Iterative Multi-range Geometry Encoding Volumes for Stereo Matching

Author

Xu, Gangwei, Wang, Xianqi, Zhang, Zhaoxing, Cheng, Junda, Liao, Chunyuan, and Yang, Xin

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Stereo matching is a core component in many computer vision and robotics systems. Despite significant advances over the last decade, handling matching ambiguities in ill-posed regions and large disparities remains an open challenge. In this paper, we propose a new deep network architecture, called IGEV++, for stereo matching. The proposed IGEV++ builds Multi-range Geometry Encoding Volumes (MGEV) that encode coarse-grained geometry information for ill-posed regions and large disparities and fine-grained geometry information for details and small disparities. To construct MGEV, we introduce an adaptive patch matching module that efficiently and effectively computes matching costs for large disparity ranges and/or ill-posed regions. We further propose a selective geometry feature fusion module to adaptively fuse multi-range and multi-granularity geometry features in MGEV. We then index the fused geometry features and input them to ConvGRUs to iteratively update the disparity map. MGEV allows to efficiently handle large disparities and ill-posed regions, such as occlusions and textureless regions, and enjoys rapid convergence during iterations. Our IGEV++ achieves the best performance on the Scene Flow test set across all disparity ranges, up to 768px. Our IGEV++ also achieves state-of-the-art accuracy on the Middlebury, ETH3D, KITTI 2012, and 2015 benchmarks. Specifically, IGEV++ achieves a 3.23% 2-pixel outlier rate (Bad 2.0) on the large disparity benchmark, Middlebury, representing error reductions of 31.9% and 54.8% compared to RAFT-Stereo and GMStereo, respectively. We also present a real-time version of IGEV++ that achieves the best performance among all published real-time methods on the KITTI benchmarks. The code is publicly available at https://github.com/gangweiX/IGEV-plusplus, Comment: 12 pages, 10 figures

Published
2024

2. Histology Virtual Staining with Mask-Guided Adversarial Transfer Learning for Tertiary Lymphoid Structure Detection

Author

Wang, Qiuli, Liu, Yongxu, Ma, Li, Wang, Xianqi, Chen, Wei, and Yao, Xiaohong

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Histological Tertiary Lymphoid Structures (TLSs) are increasingly recognized for their correlation with the efficacy of immunotherapy in various solid tumors. Traditionally, the identification and characterization of TLSs rely on immunohistochemistry (IHC) staining techniques, utilizing markers such as CD20 for B cells. Despite the specificity of IHC, Hematoxylin-Eosin (H&E) staining offers a more accessible and cost-effective choice. Capitalizing on the prevalence of H&E staining slides, we introduce a novel Mask-Guided Adversarial Transfer Learning method designed for virtual pathological staining. This method adeptly captures the nuanced color variations across diverse tissue types under various staining conditions, such as nucleus, red blood cells, positive reaction regions, without explicit label information, and adeptly synthesizes realistic IHC-like virtual staining patches, even replicating the positive reaction. Further, we propose the Virtual IHC Pathology Analysis Network (VIPA-Net), an integrated framework encompassing a Mask-Guided Transfer Module and an H&E-Based Virtual Staining TLS Detection Module. VIPA-Net synergistically harnesses both H\&E staining slides and the synthesized virtual IHC patches to enhance the detection of TLSs within H&E Whole Slide Images (WSIs). We evaluate the network with a comprehensive dataset comprising 1019 annotated slides from The Cancer Genome Atlas (TCGA). Experimental results compellingly illustrate that the VIPA-Net substantially elevates TLS detection accuracy, effectively circumventing the need for actual CD20 staining across the public dataset., Comment: 8 pages, 8 figures

Published
2024

3. Selective-Stereo: Adaptive Frequency Information Selection for Stereo Matching

Author

Wang, Xianqi, Xu, Gangwei, Jia, Hao, and Yang, Xin

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Stereo matching methods based on iterative optimization, like RAFT-Stereo and IGEV-Stereo, have evolved into a cornerstone in the field of stereo matching. However, these methods struggle to simultaneously capture high-frequency information in edges and low-frequency information in smooth regions due to the fixed receptive field. As a result, they tend to lose details, blur edges, and produce false matches in textureless areas. In this paper, we propose Selective Recurrent Unit (SRU), a novel iterative update operator for stereo matching. The SRU module can adaptively fuse hidden disparity information at multiple frequencies for edge and smooth regions. To perform adaptive fusion, we introduce a new Contextual Spatial Attention (CSA) module to generate attention maps as fusion weights. The SRU empowers the network to aggregate hidden disparity information across multiple frequencies, mitigating the risk of vital hidden disparity information loss during iterative processes. To verify SRU's universality, we apply it to representative iterative stereo matching methods, collectively referred to as Selective-Stereo. Our Selective-Stereo ranks $1^{st}$ on KITTI 2012, KITTI 2015, ETH3D, and Middlebury leaderboards among all published methods. Code is available at https://github.com/Windsrain/Selective-Stereo., Comment: Accepted to CVPR 2024

Published
2024

5. Iterative Geometry Encoding Volume for Stereo Matching

Author

Xu, Gangwei, Wang, Xianqi, Ding, Xiaohuan, and Yang, Xin

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Recurrent All-Pairs Field Transforms (RAFT) has shown great potentials in matching tasks. However, all-pairs correlations lack non-local geometry knowledge and have difficulties tackling local ambiguities in ill-posed regions. In this paper, we propose Iterative Geometry Encoding Volume (IGEV-Stereo), a new deep network architecture for stereo matching. The proposed IGEV-Stereo builds a combined geometry encoding volume that encodes geometry and context information as well as local matching details, and iteratively indexes it to update the disparity map. To speed up the convergence, we exploit GEV to regress an accurate starting point for ConvGRUs iterations. Our IGEV-Stereo ranks $1^{st}$ on KITTI 2015 and 2012 (Reflective) among all published methods and is the fastest among the top 10 methods. In addition, IGEV-Stereo has strong cross-dataset generalization as well as high inference efficiency. We also extend our IGEV to multi-view stereo (MVS), i.e. IGEV-MVS, which achieves competitive accuracy on DTU benchmark. Code is available at https://github.com/gangweiX/IGEV., Comment: Accepted to CVPR 2023

Published
2023

6. Establishment of a chest-CT-image-based classification deep learning model for pneumonia prediction

Author

ZENG Meng, ZHAO Na, and WANG Xianqi

Subjects
pneumonia, covid-19, artificial intelligence, deep learning, prediction model, Medicine (General), R5-920
Abstract

Objective To establish an AI model based on chest CT images to achieve rapid classification prediction for bacterial, fungal, and viral (including COVID-19) infectious pneumonia. Methods Chest CT imaging data of 559 bacterial, fungal and non-COVID-19 viral pneumonia patients admitted to the First Affiliated Hospital of Army Medical University from 2013 to 2020 and 53 COVID-19 patients to the Chongqing University Three Gorges Hospital from January 2020 to December 2020 were collected and analyzed retrospectively.Firstly, 4 typical deep neural networks (Resnet_18, Efficientnet_b5, ViT, and Swin-Transformer) were used to construct image-level triple and quadruple classification prediction models, and the optimal model was selected by validation in an independent test set.Then, the effects of single-image and three-fused-images to construct dataset on the models were analyzed.Finally, voting by image category and random forest were carried out to make the patient-level classification prediction, respectively.The precision, recall rate, specificity, F1 value, AUC, and accuracy were employed to evaluate the performance of the models in order to screen out the best performing AI prediction model. Results The Swin Transformer model performed best in image-level classification, with a triple classification accuracy of 0.932 and a quadruple classification accuracy of 0.948.After the model was constructed with single-image and three-fused-images, a model, named as Swin-Transformer_C, which was further improved with fused images, showed good performance, with a triple classification accuracy and AUC of 0.931 and 0.989, and with a quadruple classification accuracy and AUC of 0.952 and 0.990, respectively, in the test set.Patient-level categorization using the Swin-transformer_C model integrated with random forest was more effective, with a triple classification accuracy and AUC of 0.984 and 0.987, and with a quadruple classification accuracy and AUC of 0.967 and 0.971, respectively.Three other networks, Resnet_18, Efficientent_b5 and Vit, also achieved good results, but the overall effectiveness was lower than that of the Swin-transformer network. Conclusion The deep learning model Swin-transformer_C, built on fused dataset, shows best performance in image-level classification when compared to the other 4 models, and it achieves optimal performance by integrating with random forest classifier in patient-level classification.Our study demonstrates that deep learning can be used for rapid classification prediction of pneumonia types due to different pathogen infections.

Published
2023
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9. Establishment and evaluation of an image-based clinical prediction model for invasive pulmonary fungal infection

Author

PANG Xiaoli, WANG Xianqi, CHEN Wei, and XIONG Wei

Subjects
invasive pulmonary fungal infection, clinical characteristics, image features, prediction model, Medicine (General), R5-920
Abstract

Objective To establish and evaluate a prediction model for invasive pulmonary fungal infection based on clinical images in order to provide reference for early identification of the disease. Methods A case-control trial was designed and conducted on 187 hospitalized patients with invasive pulmonary fungal infection and 190 patients with pulmonary infection of other pathogens in our department from January 1, 2016 to September 30, 2021. Their clinical and imaging data were collected and analyzed. The participants were randomly assigned into training set (n=264) and verification set (n=113) at a ratio of 7 ∶3. Univariate and multivariate analyses were conducted through binary logistic regression, and a nomograph prediction model was constructed using R software package. The validity and application value of the model were evaluated through receiver operating characteristic (ROC) curve, area under ROC curve (AUC), calibration curve, and decision curve (DCA). Results Multivariate logistic regression analysis showed that anemia (OR=6.41, 95%CI: 1.62~25.43), diabetes (OR=6.77, 95%CI: 1.20~38.11), COPD (OR=12.82, 95%CI: 2.71~60.55), malnutrition after admission (OR=8.78, 95%CI: 2.17~35.55), mask/nasal oxygen inhalation (OR=3.53, 95%CI: 0.911~13.66), cholinesterase (OR=7.47, 95%CI: 1.66~33.57), right lung lower lobe (OR=11.17, 95%CI: 2.07~60.16), left lung lower lobe (OR=16.25, 95%CI: 3.31~79.71), ground glass opacity (OR=19.22, 95%CI: 4.17~88.48), air bronchogram (OR=6.44, 95%CI: 1.27~32.68), and bronchiectasis (OR=11.58, 95%CI: 1.50~89.25) were related factors of pulmonary fungal infection. The nomogram was constructed from the above 11 factors (R2=0.830, C-index=0.97, 95%CI: 0.96~0.99). The AUC of the training and verification sets were 0.972 (95%CI: 0.955~0.988) and 0.945 (95%CI: 0.905~0.985), respectively, indicating a high efficiency of differentiation. The calibration curves of the training set and the verification set were distributed along the 45° line basically, and the DCA curves showed that there was a net benefit when the threshold probability was 10%~90%. Conclusion Based on 11 parameters, anemia, COPD, diabetes, malnutrition after admission, mask/nasal oxygen inhalation, cholinesterase, right lung lower lobe, left lung lower lobe, ground glass opacity, air bronchogram sign and bronchiectasis, our prediction model of invasive pulmonary fungal infection is of high accuracy in clinical practice.

Published
2023
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10. Contrast-enhanced CT radiomics for predicting lymph node metastasis in pancreatic ductal adenocarcinoma: a pilot study.

Author

Li, Ke, Yao, Qiandong, Xiao, Jingjing, Li, Meng, Yang, Jiali, Hou, Wenjing, Du, Mingshan, Chen, Kang, Qu, Yuan, Li, Lian, Li, Jing, Wang, Xianqi, Luo, Haoran, Yang, Jia, Zhang, Zhuoli, and Chen, Wei

Subjects
Humans, Carcinoma, Pancreatic Ductal, Pancreatic Neoplasms, Lymphatic Metastasis, Tomography, X-Ray Computed, Pilot Projects, Decision Support Techniques, Models, Theoretical, Aged, Middle Aged, Female, Male, CT, Lymph node metastasis, Pancreatic ductal adenocarcinoma, Radiomics, Digestive Diseases, Cancer, Biomedical Imaging, Pancreatic Cancer, Rare Diseases, Patient Safety, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, Good Health and Well Being, Oncology and Carcinogenesis, Nuclear Medicine & Medical Imaging
Abstract

BACKGROUND:We developed a computational model integrating clinical data and imaging features extracted from contrast-enhanced computed tomography (CECT) images, to predict lymph node (LN) metastasis in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS:This retrospective study included 159 patients with PDAC (118 in the primary cohort and 41 in the validation cohort) who underwent preoperative contrast-enhanced computed tomography examination between 2012 and 2015. All patients underwent surgery and lymph node status was determined. A total of 2041 radiomics features were extracted from venous phase images in the primary cohort, and optimal features were extracted to construct a radiomics signature. A combined prediction model was built by incorporating the radiomics signature and clinical characteristics selected by using multivariable logistic regression. Clinical prediction models were generated and used to evaluate both cohorts. RESULTS:Fifteen features were selected for constructing the radiomics signature based on the primary cohort. The combined prediction model for identifying preoperative lymph node metastasis reached a better discrimination power than the clinical prediction model, with an area under the curve of 0.944 vs. 0.666 in the primary cohort, and 0.912 vs. 0.713 in the validation cohort. CONCLUSIONS:This pilot study demonstrated that a noninvasive radiomics signature extracted from contrast-enhanced computed tomography imaging can be conveniently used for preoperative prediction of lymph node metastasis in patients with PDAC.

Published
2020

11. Managing the mass production for the LAD instrument onboard eXTP

Author

Egner, Sébastien E., Roberts, Scott, Minervini, G., Argan, A., Feroci, M., Trois, A., Del Monte, E., Brienza, D., Ambrosi, G., Antonelli, M., Barbera, M., Baudin, D., Bayer, J., Bellutti, P., Bertucci, B., Bi, Xingzi, Bonvicini, W., Bozzo, E., Bouyjou, F., Cadoux, F., Campana, R., Cao, Jiewei, Cavazzuti, E., Ceraudo, F., Chen, Tianxiang, Chen, Wen, Cirrincione, D., Collura, A., D'Anca, F., De Angelis, N., De Rosa, A., Di Cosimo, S., Didillo, G., Evangelista, Y., Favre, Y., Fiandrini, E., Ficorella, F., Gao, Na, Gevin, O., Guedel, M., Han, Xingbo, He, Huilin, Hedderman, P., Hynek, R., Kole, M., Karas, V., Komarek, M., La Marra, D., Liang, Hong, Limousin, O., Liu, Rui, Lo Cicero, U., Loehring, J., Lombardi, G., Lu, Fang-Jun, Luo, Tao, Merkl, M., Meuris, A., Michalska, M., Morgante, G., Munini, R., Mussolin, L., Novák, P., Nowosielski, W., Nuti, A., Orleanski, P., Ottensamer, R., Pacciani, L., Paltani, S., Pepponi, G., Piazzolla, R., Picciotto, A., Pliego Caballero, S., Putz, A., Rachevski, A., Rashevskaya, I., Samusenko, A., Santangelo, A., Schanne, S., Sciortino, L., Skup, K., Sveda, L., Svoboda, J., Tenzer, C., Todaro, M., Vacchi, A., Xiong, Hao, Wang, Jian, Wang, Xianqi, Winter, B., Wu, Xin, Zampa, G., Zampa, N., Zdziarski, A. A., Zhang, Shu-Nan, Zhang, Xiaoli, Zhang, Zhen, Zhao, Zijian, Zhou, Yupeng, and Zorzi, N.

Published
2024
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13. CD317+ MSCs expanded with chemically defined media have enhanced immunological anti-inflammatory activities.

Author

Song, Jun, Ma, Qi, Li, Yumeng, Wang, Xianqi, Chen, Si, Liang, Bowei, Lin, Xiaoqi, Chen, Jieting, Xu, Shiru, Shi, Shaoquan, Zhang, Jingting, Diao, Lianghui, Zeng, Yong, and Xu, Jianyong

Subjects
MESENCHYMAL stem cells, CELL populations, ANTI-inflammatory agents, STROMAL cells, EXTRACELLULAR matrix, IMMUNOSUPPRESSION
Abstract

Background: Although both preclinical and clinical studies have shown the great application potential of MSCs (mesenchymal stem/stromal cells) in treating many kinds of diseases, therapeutic inconsistency resulting from cell heterogeneity is the major stumbling block to their clinical applications. Cell population diversity and batch variation in the cell expansion medium are two major inducers of MSC heterogeneity. Methods: Cell population diversity was investigated through single-cell RNA sequencing analysis of human MSCs derived from the umbilical cord and expanded with fully chemically defined medium in the current study. Then, the MSC subpopulation with enhanced anti-inflammatory effects was studied in vitro and in vivo. Results: Our data showed that MSCs contain different populations with different functions, including subpopulations with enhanced functions of exosome secretion, extracellular matrix modification and responses to stimuli (regeneration and immune response). Among them, CD317+ MSCs have improved differentiation capabilities and enhanced immune suppression activities. Underlying mechanism studies showed that higher levels of TSG6 confer enhanced anti-inflammatory functions of CD317+ MSCs. Conclusions: Thus, CD317+ MSCs might be a promising candidate for treating immunological disorder-related diseases. [ABSTRACT FROM AUTHOR]

Published
2024
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17. Longitudinal relations among perceived parental warmth, self‐esteem and social behaviours from middle childhood to early adolescence in China: Disentangling between‐ and within‐person associations.

Author

Wang, Xianqi, Huebner, E. Scott, and Tian, Lili

Subjects
*SAMPLE size (Statistics), *CONFIDENCE intervals, *CHILD behavior, *PARENTING, *SELF-perception in children, *CHI-squared test, *QUESTIONNAIRES, *DESCRIPTIVE statistics, *RESEARCH funding, *PARENT-child relationships, *SOCIAL skills, *STATISTICAL sampling, *ELEMENTARY schools, *SCHOOL children, *STATISTICAL correlation, *DATA analysis software
Abstract

Although several studies have addressed the relations between perceived parental warmth and social behaviours, few have distinguished their between‐ and within‐person effects or explored their within‐person mediating mechanisms. This study examined the transactional relations among perceived parental warmth (i.e. maternal warmth and paternal warmth), children's self‐esteem and children's positive/negative social behaviours (i.e. prosocial behaviour and delinquent behaviour) along with the mediating role of self‐esteem after disentangling between‐ and within‐person effects. A total of 4315 Chinese elementary children (44.9% girls; Mage = 9.93 years, SD = 0.73) completed relevant measures on four occasions employing 6‐month intervals. Results of random‐intercept cross‐lagged panel models showed that (a) perceived parental warmth reciprocally and positively predicted prosocial behaviour and self‐esteem; (b) perceived paternal warmth reciprocally and negatively predicted delinquent behaviour; (c) self‐esteem reciprocally predicted prosocial and delinquent behaviour; (d) perceived maternal warmth reciprocally and positively predicted prosocial behaviour through self‐esteem; (e) perceived parental warmth reciprocally and negatively predicted delinquent behaviour through self‐esteem; and (f) perceived maternal and paternal warmth differed in their relations with prosocial and delinquent behaviours through self‐esteem. These findings illuminated the complicated longitudinal within‐person interactions among perceived parental warmth, self‐esteem, and social behaviours, the specific mediating mechanism of self‐esteem, and the differing results associated with perceived maternal and paternal warmth, all of which yield significant implications for assessments and early interventions aimed to promote positive social behaviour. [ABSTRACT FROM AUTHOR]

Published
2023
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18. The enhanced x-ray timing and polarimetry mission: eXTP: an update on its scientific cases, mission profile and development status

Author

Zhang, Shuang Nan, Santangelo, Andrea, Xu, Yupeng, Feroci, Marco, Hernanz, Margarita, Lu, Fangjun, Chen, Yong, Feng, Hua, Nandra, Kirpal, Jiang, Weichun, Svoboda, Jiri, Brandt, Søren, Schanne, Stéphane, Zand, Jean, Michalska, Malgorzata, Bozzo, Enrico, Kalemci, Emrah, Agudo, Ivan, Ahangarianabhari, Mahdi, Aitink-Kroes, Gabby, Ambrosi, Giovanni, Ambrosino, Filippo, An, Zhenghua, Perez Torres, Miguel Angel, Antonelli, Matias, Argan, Andrea, Babinec, Viktor, Baldini, Luca, Barbera, Marco, van Baren, Coen, Baudin, David, Bayer, Jörg, Bellazzini, Ronaldo, Bellutti, Pierluigi, Bertucci, Bruna, Bertuccio, Giuseppe, Bi, Xingzi, Boezio, Mirko, Bonvicini, Valter, Bonvicini, Walter, Bordas, Pol, Borghese, Alice, Borghi, Giacomo, Bouyjou, Florent, Bozkurt, Ayhan, Brez, Alessandro, Brienza, Daniele, Cadoux, Franck, Campana, Riccardo, Cao, Jiewei, Cao, Xuelei, Casares, Jorge, Cavazzuti, Elisabetta, Ceraudo, Francesco, Chen, Tianxiang, Chen, Wen, Chen, Can, Chen, Yupeng, Chen, Xin, Chen, Yehai, Chenevez, Jerome, Cheng, Yaodong, Cirrincione, Daniela, Civitani, Marta, Cong, Min, Zelati, Francesco Coti, Cui, Weiwei, Cui, Tao, Cui, Wei, Dai, Boyu, Dauser, Thomas, De Angelis, Nicolas, De Marco, Barbara, De Rosa, Alessandra, Monte, Ettore Del, Cosimo, Sergio Di, Diebold, Sebastian, Dilillo, Giuseppe, Ding, Fei, Dohnal, Roman, Dong, Zefang, Donnarumma, Immacolata, Dovciak, Michal, Du, Yuanyuan, Ducci, Lorenzo, Evangelista, Yuri, Fan, Qingmei, Favre, Yannick, Ferrés, Patrícia, Fiandrini, Emanuele, Ficorella, Francesco, Fuschino, Fabio, Gálvez, José Luis, Gao, Na, Gao, Min, Ge, Yuqiang, Ge, Mingyu, Gevin, Olivier, Grassi, Marco, Gu, Yudong, Gu, Quanying, Guan, Ju, Guedel, Manuel, Han, Xingbo, Han, Dawei, He, Huilin, He, Junwang, Hedderman, Paul, den Herder, Jan Willem, Hong, Bin, Hormaetxe, Ander, Hou, Dongjie, Hu, Zexun, Hu, Hao, Hu, Qingbao, Hu, Yu, Huang, Yue, Huang, Jiangjiang, Huang, Qiushi, Huo, Jia, Hynek, Richard, Iwasawa, Kazumi, Izzo, Lucca, Ji, Long, Jia, Shumei, Jiang, Bowen, Jiang, Wei, Jiang, Jiechen, Jiang, Xiaowei, Jiao, Yang, Jin, Ge, Jin, Fan, Jose, Jordi, Karas, Vladimir, Kennedy, Thomas, Kirsch, Christian, Kole, Merlin, Komarek, Martin, Kreykenbohm, Ingo, Kuiper, Lucien, Kuvvetli, Irfan, Labanti, Claudio, Latronico, Luca, Laubert, Phillip, Li, Tao, Li, Longhui, Li, Hong, Li, Duo, Li, Wei, Li, Maoshun, Li, Gang, Li, Xiaobo, Li, Chengkui, Li, Bing, Li, Haibo, Liang, Hong, Liao, Qiuyan, Liao, Jinyuan, Limousin, Olivier, Lin, Yanjian, Linares, Manuel, Liu, Rui, Liu, Yichen, Liu, Zhihao, Liu, Hongwei, Liu, Xiaojing, Liu, Xiaohua, Cicero, Ugo Lo, Loehring, Jens, Lombardi, Giovanni, Lorenz, Maximilian, Lu, Bing, Lucchesi, Leonardo, Luo, Tao, Luo, Laidan, Ma, Jia, Ma, Xiang, Macera, Daniele, Malcovati, Piero, Manfreda, Alberto, Paredes, Josep Maria, Marinucci, Andrea, Martindale, Adrian, Meidinger, Norbert, Mele, Filippo, Mendes, Vasco, Meng, Bin, Merkl, Martin, Meuris, Aline, Miniutti, Giovanni, Minuti, Massimo, Morbidini, Alfredo, Morgante, Gianluca, Muleri, Fabio, Munini, Riccardo, Mussolin, Lorenzo, Negri, Barbara, Nie, Jianyin, Novák, Petr, Nowosielski, Witold, Nuti, Alessio, Onat, Ahmet, Orleanski, Piotr, Orsini, Leonardo, Ottensamer, Roland, Ou, Ge, Pacciani, Luigi, Paltani, Stephane, Pan, Teng, Pan, Kai, Pareschi, Giovanni, Patruno, Alessandro, Pepponi, Giancarlo, Perinati, Emanuele, Piazzolla, Raffaele, Picciotto, Antonino, Piemonte, Claudio, Pinchera, Michele, Pliego, Samuel, Poutanen, Juri, Qi, Liqiang, Qi, Fazhi, Qiang, Pengfei, Qiao, Fangjian, Qiao, Zheng, Qiu, Xiangbiao, Qiu, Chengbo, Qu, Jinlu, Rachevski, Alexandre, Rashevskaia, Irina, Rea, Nanda, Ribo, Marc, de la Rie, Rob, Rodriguez, Jerome, Gil, Pablo Rodríguez, Sala, Gloria, Schanz, Thomas, Serafinelli, Roberto, Sgro, Carmelo, Shen, Zhengxiang, Sheng, Lizhi, Shi, Jingyan, Sironi, Giorgia, Skup, Konrad, Song, Liming, Song, Zeyu, Song, Jiangbo, Spandre, Gloria, Spiga, Daniele, Su, Yongquan, Sun, Liang, Sungur, Müberra, Svéda, Libor, Tagliaferri, Gianpiero, Tan, Ying, Tao, Lian, Tcherniak, Denis, Tenzer, Chris, Todaro, Michela, Tolos, Laura, Torok, Gabriel, Torres, Diego F., Trois, Alessio, Turhan, Onur, Uttley, Phil, Vacchi, Andrea, Virgilli, Enrico, Vogel, Channah, Walton, Dave, Wang, Jian, Wang, Xianqi, Wang, Bo, Wang, Langping, Wang, Xiaofeng, Wang, Dianlong, Wang, Yusa, Wang, Juan, Wang, Hao, Wang, Ruijie, Wang, Ping, Wang, Lingjun, Wang, Wenshuai, Wang, Tian, Wang, Haoyu, Wang, Zhanshan, Watts, Anna L., Wen, Xiangyang, Wilms, Jörn, Winter, Berend, Wu, Xin, Wu, Chao, Wu, Zhenyu, Wu, Qiong, Wu, Kaiji, Xiong, Hao, Xiong, Shaolin, Xu, Wei, Xu, Zhao, Xu, Jingjing, Xu, Xiongwei, Xue, Jiadai, Yan, Yongqing, Yan, Xingtao, Yang, Xianghui, Yang, Yanji, Yang, Xiongtao, Yang, Sheng, Yang, Jiawei, Yang, Yingquan, Yi, Shuxu, Yu, Yonggao, Yu, Ke, Zampa, Ganluigi, Zampa, Nicola, Zane, Silvia, Zdziarski, Andrzej A., Zhang, Long, Zhang, Shu, Zhang, Wenda, Zhang, Xiaoli, Zhang, Zhen, Zhang, Jiawei, Zhang, Fan, Zhang, Ziliang, Zhang, Dali, Zhang, Honglin, Zhang, Aimei, Zhang, Tong, Zhang, Hongmei, Zhang, Juan, Zhang, Liang, Zhang, Yueting, Zhao, Li, Zhao, Baosheng, Zhao, Zijian, Zhao, Xiaofan, Zhao, Haisheng, Zhao, Xiaoyun, Zheng, Shijie, Zhou, Yupeng, Zhou, Xiaohong, Zhu, Jiahuan, Zhu, Yuxuan, Zhu, Cheng, Zhu, Zhencai, Zorzi, Nicola, Zwart, Frans, den Herder, Jan-Willem A., Nikzad, Shouleh, Nakazawa, Kazuhiro, Chinese Academy of Sciences, Agenzia Spaziale Italiana, Ministerio de Ciencia e Innovación (España), Federal Ministry of Economics and Technology (Germany), and Foundation for Polish Science

Subjects
Equation of state, Extreme gravity, Black hole, X-ray timing, X-ray polarimetry, Neutron star, Extreme magnetism, Extreme density
Abstract

Space Telescopes and Instrumentation 2022: Ultraviolet to Gamma Ray (2022), Montreal, Jul 17-22, 2022.--Proceedings of SPIE - The International Society for Optical Engineering vol. 12181 Article number 121811W.-- Full list of authors: Zhang, Shuang-Nan; Santangelo, Andrea; Xu, Yupeng; Feroci, Marco; Hernanz, Margarita; Lu, Fangjun; Chen, Yong; Feng, Hua; Nandra, Kirpal; Jiang, Weichun; Svoboda, Jiri; Brandt, Soren; Schanne, Stephane; in't Zand, Jean; Michalska, Malgorzata; Bozzo, Enrico; Kalemci, Emrah; Agudo, Ivan; Ahangarianabhari, Mahdi; Aitink-Kroes, Gabby; Ambrosi, Giovanni; Ambrosino, Filippo; An, Zhenghua; Perez Torres, Miguel Angel; Antonelli, Matias; Argan, Andrea; Babinec, Viktor; Baldini, Luca; Barbera, Marco; van Baren, Coen; Baudin, David; Bayer, Joerg; Bellazzini, Ronaldo; Bellutti, Pierluigi; Bertucci, Bruna; Bertuccio, Giuseppe; Bi, Xingzi; Boezio, Mirko; Bonvicini, Valter; Bonvicini, Walter; Bordas, Pol; Borghese, Alice; Borghi, Giacomo; Bouyjou, Florent; Bozkurt, Ayhan; Brez, Alessandro; Brienza, Daniele; Cadoux, Franck; Campana, Riccardo; Cao, Jiewei; Cao, Xuelei; Casares, Jorge; Cavazzuti, Elisabetta; Ceraudo, Francesco; Chen, Tianxiang; Chen, Wen; Chen, Can; Chen, Yupeng; Chen, Xin; Chen, Yehai; Chenevez, Jerome; Cheng, Yaodong; Cirrincione, Daniela; Civitani, Marta; Cong, Min; Coti Zelati, Francesco; Cui, Weiwei; Cui, Tao; Cui, Wei; Dai, Boyu; Dauser, Thomas; De Angelis, Nicolas; De Marco, Barbara; De Rosa, Alessandra; Del Monte, Ettore; Di Cosimo, Sergio; Diebold, Sebastian; Dilillo, Giuseppe; Ding, Fei; Dohnal, Roman; Dong, Zefang; Donnarumma, Immacolata; Dovciak, Michal; Du, Yuanyuan; Ducci, Lorenzo; Evangelista, Yuri; Fan, Qingmei; Favre, Yannick; Ferres, Patricia; Fiandrini, Emanuele; Ficorella, Francesco; Fuschino, Fabio; Luis Galvez, Jose; Gao, Na; Gao, Min; Ge, Yuqiang; Ge, Mingyu; Gevin, Olivier; Grassi, Marco; Gu, Yudong; Gu, Quanying; Guan, Ju; Guedel, Manuel; Han, Xingbo; Han, Dawei; He, Huilin; He, Junwang; Hedderman, Paul; den Herder, Jan-Willem; Hong, Bin; Hormaetxe, Ander; Hou, Dongjie; Hu, Zexun; Hu, Hao; Hu, Qingbao; Hu, Yu; Huang, Yue; Huang, Jiangjiang; Huang, Qiushi; Huo, Jia; Hynek, Richard; Iwasawa, Kazumi; Izzo, Lucca; Ji, Long; Jia, Shumei; Jiang, Bowen; Jiang, Wei; Jiang, Jiechen; Jiang, Xiaowei; Jiao, Yang; Jin, Ge; Jin, Fan; Jose, Jordi; Karas, Vladimir; Kennedy, Thomas; Kirsch, Christian; Kole, Merlin; Komarek, Martin; Kreykenbohm, Ingo; Kuiper, Lucien; Kuvvetli, Irfan; Labanti, Claudio; Latronico, Luca; Laubert, Phillip; Li, Tao; Li, Longhui; Li, Hong; Li, Duo; Li, Wei; Li, Maoshun; Li, Gang; Li, Xiaobo; Li, Chengkui; Li, Bing; Li, Haibo; Liang, Hong; Liao, Qiuyan; Liao, Jinyuan; Limousin, Olivier; Lin, Yanjian; Linares, Manuel; Liu, Rui; Liu, Yichen; Liu, Zhihao; Liu, Hongwei; Liu, Xiaojing; Liu, Xiaohua; Lo Cicero, Ugo; Loehring, Jens; Lombardi, Giovanni; Lorenz, Maximilian; Lu, Bing; Lucchesi, Leonardo; Luo, Tao; Luo, Laidan; Ma, Jia; Ma, Xiang; Macera, Daniele; Malcovati, Piero; Manfreda, Alberto; Maria Paredes, Josep; Marinucci, Andrea; Martindale, Adrian; Meidinger, Norbert; Mele, Filippo; Mendes, Vasco; Meng, Bin; Merkl, Martin; Meuris, Aline; Miniutti, Giovanni; Minuti, Massimo; Morbidini, Alfredo; Morgante, Gianluca; Muleri, Fabio; Munini, Riccardo; Mussolin, Lorenzo; Negri, Barbara; Nie, Jianyin; Novak, Petr; Nowosielski, Witold; Nuti, Alessio; Onat, Ahmet; Orleanski, Piotr; Orsini, Leonardo; Ottensamer, Roland; Ou, Ge; Pacciani, Luigi; Paltani, Stephane; Pan, Teng; Pan, Kai; Pareschi, Giovanni; Patruno, Alessandro; Pepponi, Giancarlo; Perinati, Emanuele; Piazzolla, Raffaele; Picciotto, Antonino; Piemonte, Claudio; Pinchera, Michele; Pliego, Samuel; Poutanen, Juri; Qi, Liqiang; Qi, Fazhi; Qiang, Pengfei; Qiao, Fangjian; Qiao, Zheng; Qiu, Xiangbiao; Qiu, Chengbo; Qu, Jinlu; Rachevski, Alexandre; Rashevskaia, Irina; Rea, Nanda; Ribo, Marc; de la Rie, Rob; Rodriguez, Jerome; Rodriguez Gil, Pablo; Sala, Gloria; Schanz, Thomas; Serafinelli, Roberto; Sgro, Carmelo; Shen, Zhengxiang; Sheng, Lizhi; Shi, Jingyan; Sironi, Giorgia; Skup, Konrad; Song, Liming; Song, Zeyu; Song, Jiangbo; Spandre, Gloria; Spiga, Daniele; Su, Yongquan; Sun, Liang; Sungur, Muberra; Sveda, Libor; Tagliaferri, Gianpiero; Tan, Ying; Tao, Lian; Tcherniak, Denis; Tenzer, Chris; Todaro, Michela; Tolos, Laura; Torok, Gabriel; Torres, Diego F.; Trois, Alessio; Turhan, Onur; Uttley, Phil; Vacchi, Andrea; Virgilli, Enrico; Vogel, Channah; Walton, Dave; Wang, Jian; Wang, Xianqi; Wang, Bo; Wang, Langping; Wang, Xiaofeng; Wang, Dianlong; Wang, Yusa; Wang, Juan; Wang, Hao; Wang, Ruijie; Wang, Ping; Wang, Lingjun; Wang, Wenshuai; Wang, Tian; Wang, Haoyu; Wang, Zhanshan; Watts, Anna L.; Wen, Xiangyang; Wilms, Joern; Winter, Berend; Wu, Xin; Wu, Chao; Wu, Zhenyu; Wu, Qiong; Wu, Kaiji; Xiong, Hao; Xiong, Shaolin; Xu, Wei; Xu, Zhao; Xu, Jingjing; Xu, Xiongwei; Xue, Jiadai; Yan, Yongqing; Yan, Xingtao; Yang, Xianghui; Yang, Yanji; Yang, Xiongtao; Yang, Sheng; Yang, Jiawei; Yang, Yingquan; Yi, Shuxu; Yu, Yonggao; Yu, Ke; Zampa, Ganluigi; Zampa, Nicola; Zane, Silvia; Zdziarski, Andrzej A.; Zhang, Long; Zhang, Shu; Zhang, Wenda; Zhang, Xiaoli; Zhang, Zhen; Zhang, Jiawei; Zhang, Fan; Zhang, Ziliang; Zhang, Dali; Zhang, Honglin; Zhang, Aimei; Zhang, Tong; Zhang, Hongmei; Zhang, Juan; Zhang, Liang; Zhang, Yueting; Zhao, Li; Zhao, Baosheng; Zhao, Zijian; Zhao, Xiaofan; Zhao, Haisheng; Zhao, Xiaoyun; Zheng, Shijie; Zhou, Yupeng; Zhou, Xiaohong; Zhu, Jiahuan; Zhu, Yuxuan; Zhu, Cheng; Zhu, Zhencai; Zorzi, Nicola; Zwart, Frans, The enhanced X-ray Timing and Polarimetry mission (eXTP) is a flagship observatory for X-ray timing, spectroscopy and polarimetry developed by an International Consortium. Thanks to its very large collecting area, good spectral resolution and unprecedented polarimetry capabilities, eXTP will explore the properties of matter and the propagation of light in the most extreme conditions found in the Universe. eXTP will, in addition, be a powerful X-ray observatory. The mission will continuously monitor the X-ray sky, and will enable multiwavelength and multi-messenger studies. The mission is currently in phase B, which will be completed in the middle of 2022. © 2022 SPIE. All rights reserved., The Chinese team acknowledges support by the Chinese Academy of Sciences through the Strategic Priority Research Program, Grant No. XDA15020100. The Italian authors acknowledge funding support by the Italian Space Agency (under agreement n. 2020-3-HH.0 and ASI-INAF n.2017-14-H.O) and INFN (project XRO -X-ray Observatories). The Spanish authors acknowledge funding support from the MICIN/AEI grant PID2019-108709GB-I00. The German team acknowledges support from the Bundesministerium fur Wirtschaft und Technologie through the Deutsches Zentrum fur Luft-und Raumfahrt e.V. (DLR) under the grant number FKZ 50 OO 1902. The Polish team acknowledges FNP grant POIR.04.04.00-00-5C65/17. The Czech team acknowledges support from the GACR project 21-06825X. The Turkish team acknowledges support from the Turkish Space Agency., With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709

Published
2022

19. The digital data processing concepts of the large area detector and the wide field monitor onboard eXTP

Author

Xiong, Hao, primary, Argan, Andrea, additional, Baudin, David, additional, Bayer, Jörg, additional, Bouyjou, Florent, additional, De Angelis, Nicolas, additional, Del Monte, Ettore, additional, Evangelista, Yuri, additional, Favre, Yannick, additional, Feroci, Marco, additional, Galvez, José-Luis, additional, Gevin, Olivier, additional, Hedderman, Paul, additional, Hernanz, Margarita, additional, Kole, Merlin R., additional, Meuris, Aline, additional, Pliego-Caballero, Samuel, additional, Santangelo, Andrea, additional, Tenzer, Chris, additional, Trois, Alessio, additional, Wang, Xianqi, additional, and Zampa, Gianluigi, additional

Published
2022
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20. The large area detector onboard the eXTP mission

Author

Feroci, Marco, primary, Ambrosi, Giovanni, additional, Ambrosino, Filippo, additional, Antonelli, Matias, additional, Argan, Andrea, additional, Babinec, Viktor, additional, Barbera, Marco, additional, Bayer, Jörg, additional, Bellutti, Pierluigi, additional, Bertucci, Bruna, additional, Bertuccio, Giuseppe, additional, Bi, Xingzi, additional, Boezio, Mirko, additional, Bonvicini, Walter, additional, Borghi, Giacomo, additional, Bozzo, Enrico, additional, Baudin, David, additional, Bouyjou, Florent, additional, Brienza, Daniele, additional, Cadoux, Franck, additional, Campana, Riccardo, additional, Cao, Jiewei, additional, Cavazzuti, Elisabetta, additional, Ceraudo, Francesco, additional, Chen, Tianxiang, additional, Chen, Wen, additional, Cirrincione, Daniela, additional, De Angelis, Nicolas, additional, De Rosa, Alessandra, additional, Del Monte, Ettore, additional, Di Cosimo, Sergio, additional, Dilillo, Giuseppe, additional, Dohnal, Roman, additional, Donnarumma, Immacolata, additional, Evangelista, Yuri, additional, Fan, Qingmei, additional, Favre, Yannick, additional, Fiandrini, Emanuele, additional, Ficorella, Francesco, additional, Fuschino, Fabio, additional, Gao, Na, additional, Gevin, Olivier, additional, Grassi, Marco, additional, Guedel, Manuel, additional, Han, Xingbo, additional, He, Huilin, additional, Hedderman, Paul, additional, den herder, jan-willem, additional, Hynek, Richard, additional, Hong, Bing, additional, Jin, Ge, additional, Kole, Merlin, additional, Karas, Vladimír, additional, Komarek, Martin, additional, Labanti, Claudio, additional, Li, Loghui, additional, Li, Tianming, additional, Liang, Hong, additional, Limousin, Olivier, additional, Liu, Rui, additional, Lo Cicero, Ugo, additional, Lohering, Jens, additional, Lombardi, Giovanni, additional, Lu, Fang-Jun, additional, Luo, Tao, additional, Malcovati, Piero, additional, Mao, Hanqi, additional, Marinucci, Andrea, additional, Mele, Filippo, additional, Mendes, Vasco, additional, Merkl, Martin, additional, Meuris, Aline, additional, Michalska, Małgorzata, additional, Morbidini, Alfredo, additional, Morgante, Gianluca, additional, Muleri, Fabio, additional, Munini, Riccardo, additional, Mussolin, Lorenzo, additional, Negri, Barbara, additional, Novak, Petr, additional, Nowosielski, Witold, additional, Nuti, Alessio, additional, Orleanski, Piotr, additional, Ottensamer, Roland, additional, Pacciani, Luigi, additional, Paltani, Stephane, additional, Pan, Teng, additional, Pepponi, Giancarlo, additional, Perinati, Emanuele, additional, Piazzolla, Raffaele, additional, Picciotto, Antonino, additional, Pliego, Samuel, additional, Rachevski, Alexandre, additional, Rashevskaia, Irina, additional, Santangelo, Andrea, additional, Serafinelli, Roberto, additional, Schanne, Stéphane, additional, Skup, Konrad, additional, Sveda, Libor, additional, Svoboda, Jiri, additional, Tenzer, Christopher, additional, Todaro, Michela, additional, Torok, Gabreil, additional, Trois, Alessio, additional, Vacchi, Andrea, additional, Virgilli, Enrico, additional, Xiong, Hao, additional, Wang, Jian, additional, Wang, Xianqi, additional, Winter, Berend, additional, Wu, Xin, additional, Xu, Yupeng, additional, Zampa, Gianluigi, additional, Zampa, Nicola, additional, Zdziarski, Andrei, additional, Zhang, Long, additional, Zhang, Shu, additional, Zhang, Shuang-Nan, additional, Zhang, Wenda, additional, Zhang, Xiaoli, additional, Zhang, Zhen, additional, Zhou, Yupeng, additional, and Zorzi, Nicola, additional

Published
2022
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21. Quantitative MRI evaluation of articular cartilage in patients with meniscus tear

Author

Chen, Enqi, primary, Hou, Wenjing, additional, Wang, Hu, additional, Li, Jing, additional, Lin, Yangjing, additional, Liu, He, additional, Du, Mingshan, additional, Li, Lian, additional, Wang, Xianqi, additional, Yang, Jing, additional, Yang, Rui, additional, Zhou, Changru, additional, Chen, Pinzhen, additional, Zeng, Meng, additional, Yao, Qiandong, additional, and Chen, Wei, additional

Published
2022
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23. CT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study

Author

Hu, Xiaofei, primary, Zeng, Wenbing, additional, Zhang, Yuhan, additional, Zhen, Zhiming, additional, Zheng, Yalan, additional, Cheng, Lin, additional, Wang, Xianqi, additional, Luo, Haoran, additional, Zhang, Shu, additional, Wu, Zifeng, additional, Sun, Zeyu, additional, Li, Xiuli, additional, Cao, Yang, additional, Xu, Ming, additional, Wang, Jian, additional, and Chen, Wei, additional

Published
2020
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24. The digital data processing concepts of the large area detector and the wide field monitor onboard eXTP

Author

den Herder, Jan-Willem A., Nikzad, Shouleh, Nakazawa, Kazuhiro, Xiong, Hao, Argan, Andrea, Baudin, David, Bayer, Jörg, Bouyjou, Florent, De Angelis, Nicolas, Del Monte, Ettore, Evangelista, Yuri, Favre, Yannick, Feroci, Marco, Galvez, José-Luis, Gevin, Olivier, Hedderman, Paul, Hernanz, Margarita, Kole, Merlin Reynaard, Meuris, Aline, Pliego-Caballero, Samuel, Santangelo, Andrea, Tenzer, Chris, Trois, Alessio, Wang, Xianqi, and Zampa, Gianluigi

Published
2022
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25. The large area detector onboard the eXTP mission

Author

den Herder, Jan-Willem A., Nikzad, Shouleh, Nakazawa, Kazuhiro, Feroci, Marco, Ambrosi, Giovanni, Ambrosino, Filippo, Antonelli, Matias, Argan, Andrea, Babinec, Viktor, Barbera, Marco, Bayer, Joerg, Bellutti, Pierluigi, Bertucci, Bruna, Bertuccio, Giuseppe, Bi, Xingzi, Boezio, Mirko, Bonvicini, Walter, Borghi, Giacomo, Bozzo, Enrico, Baudin, David, Bouyjou, Florent, Brienza, Daniele, Cadoux, Franck, Campana, Riccardo, Cao, Jiewei, Cavazzuti, Elisabetta, Ceraudo, Francesco, Chen, Tianxiang, Chen, Wen, Cirrincione, Daniela, De Angelis, Nicolas, De Rosa, Alessandra, Del Monte, Ettore, Di Cosimo, Sergio, Dilillo, Giuseppe, Dohnal, Roman, Donnarumma, Immacolata, Evangelista, Yuri, Fan, Qingmei, Favre, Yannick, Fiandrini, Emanuele, Ficorella, Francesco, Fuschino, Fabio, Gao, Na, Gevin, Olivier, Grassi, Marco, Guedel, Manuel, Han, Xingbo, He, Huilin, Hedderman, Paul, den Herder, Jan-Willem, Hynek, Richard, Hong, Bin, Jin, Ge, Kole, Merlin, Karas, Vladimir, Komarek, Martin, Labanti, Claudio, Li, Loghui, Li, Tianming, Liang, Hong, Limousin, Olivier, Liu, Rui, Lo Cicero, Ugo, Lohering, Jens, Lombardi, Giovanni, Lu, Fang-Jun, Luo, Tao, Malcovati, Piero, Mao, Hanqi, Marinucci, Andrea, Mele, Filippo, Mendes, Vasco, Merkl, Martin, Meuris, Aline, Michalska, Malgorzata, Morbidini, Alfredo, Morgante, Gianluca, Muleri, Fabio, Munini, Riccardo, Mussolin, Lorenzo, Negri, Barbara, Novák, Petr, Nowosielski, Witold, Nuti, Alessio, Orleanski, Piotr, Ottensamer, Roland, Pacciani, Luigi, Paltani, Stephane, Pan, Teng, Pepponi, Giancarlo, Perinati, Emanuele, Piazzolla, Raffaele, Picciotto, Antonino, Pliego, Samuel, Rachevski, Alexandre, Rashevskaia, Irina, Santangelo, Andrea, Schanne, Stéphane, Serafinelli, Roberto, Skup, Konrad, Sveda, Libor, Svoboda, Jiri, Tenzer, Chris, Todaro, Michela, Torok, Gabriel, Trois, Alessio, Vacchi, Andrea, Virgilli, Enrico, Xiong, Hao, Wang, Jian, Wang, Xianqi, Winter, Berend, Wu, Xin, Xu, Yupeng, Zampa, Ganluigi, Zampa, Nicola, Zdziarski, Andrzej A., Zhang, Long, Zhang, Shu, Zhang, Shuang-Nan, Zhang, Wenda, Zhang, Xiaoli, Zhang, Zhen, Zhou, Yupeng, and Zorzi, Nicola

Published
2022
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26. Clinical and CT Features of Corona Virus Disease 2019 in Different Age Groups

Author

Zhang, Yuhan, primary, Zeng, Wenbing, additional, Hu, Xiaofei, additional, Shi, Yanshu, additional, Liu, Chen, additional, Cheng, Lin, additional, Wang, Xianqi, additional, Luo, Haoran, additional, Lang, Ye, additional, Mao, Li, additional, Li, Xiuli, additional, Du, Mingshan, additional, Hou, Wenjing, additional, Li, Xiang, additional, Chen, Haonan, additional, Cao, Yang, additional, Xu, Ming, additional, Wang, Jian, additional, and Chen, Wei, additional

Published
2020
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27. CT Imaging Features of Different Clinical Types of COVID-19: A Chinese Multicenter Study

Author

Hu, Xiaofei, primary, Zeng, Wenbing, additional, Zhang, Yuhan, additional, Zhen, Zhiming, additional, Cheng, Lin, additional, Wang, Xianqi, additional, Luo, Haoran, additional, Liu, Chen, additional, Zhang, Shu, additional, Wu, Zifeng, additional, Sun, Zeyu, additional, Li, Xiuli, additional, Cao, Yang, additional, Xu, Ming, additional, Wang, Jian, additional, and Chen, Wei, additional

Published
2020
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28. LIgand-induced ring slippage of eta(super6)- to eta(super4)-naphthalene

Author

Bennett, Marti A., Lu, Zhaobin, Wang, Xianqi, Brown, Mark, and Hockless, David C.R.

Subjects
Naphthalene -- Research, Chemical reactions -- Observations, Aromatic compounds -- Observations, Chemistry
Abstract

Coordinated aromatic hydrocarbons in the presence of acetonitrile, in the compound (eta(super6)-naphthalene)(eta(super4)-1,5-cyclooctadiene)ruthenium(O), Ru(eta(super6)-C(sub10)H(sub8))-(eta(super4)-1,5-C(sub8)H(sub12)), (1), are labilized. This allows (1) to catalyze the hydrogenation of alkenes. If certain Group 15 donors are used instead of acetonitrile, structurally eta(super4)-naphthalene compounds from (1) can be isolating and characterized.

Published
1998

29. Asymmetric catalysis: asymmetric catalytic intramolecular hydroacylation of 4-pentenals using chiral rhodium diphosphine catalysts

Author

Barnhart, Richard W., Wang, Xianqi, Noheda, Pedro, Bergens, Steven H., Whelan, John, and Bosnich, B.

Subjects
Rhodium -- Research, Chirality -- Analysis, Acylation -- Analysis, Cyclic compounds -- Research, Chemistry
Abstract

Chiral rhodium diphosphines catalyze hydroacylation of 4-substituted 4-pentenals, yielding related 3-substituted cyclo-pentanones. The binap catalyst yields almost total enantioselectivity for 4-pentenals with tertiary substituents. Ketonic substituents give good enantioselectivity.

Published
1994

30. Therapeutic effects of CXCR4+ subpopulation of transgene‐free induced cardiosphere‐derived cells on experimental myocardial infarction.

Author

Xu, Jianyong, Wu, Huimei, Mai, Zhigang, Yi, Junbo, Wang, Xianqi, Li, Lingyun, and Huang, Zhong

Subjects
TREATMENT effectiveness, LABORATORY mice, STEM cell treatment, SURVIVAL rate, CHEMOKINE receptors, MYOCARDIAL infarction, TRANSGENE expression
Abstract

Objectives: Myocardial infarction (MI) is the most predominant type of cardiovascular diseases with high mortality and morbidity. Stem cell therapy, especially cardiac progenitor cell therapy, has been proposed as a promising approach for cardiac regeneration and MI treatment. Previously, we have successfully generated cardiac progenitor‐like cells, induced cardiosphere (iCS), via somatic reprogramming. However, the genome integration characteristic of virus‐based reprogramming approach hampered their therapeutic applications due to the risk of tumour formation. In the current study, we aim to establish a safer iCS generation strategy with transgene‐free approaches. Materials and Methods: Four transgene‐free approaches for somatic reprogramming, including episome, minicircle, self‐replicative RNA, and sendai virus, were compared, from the perspective of cardiac progenitor marker expression, iCS formation, and cardiac differentiation. The therapeutic effects were assessed in the mouse model of MI, from the perspective of survival rate, cardiac function, and structural alterations. Results: The self‐replicative RNA approach produced more iCS, which had cardiomyocyte differentiation ability and therapeutic effects on the mouse model of MI with comparable levels with endogenous cardiospheres and iCS generated with retrovirus. In addition, the CXCR4 (C‐X‐C chemokine receptor 4) positive subpopulation of iCS derived cells (iCSDC) delivered by intravenous injection was found to have similar therapeutic effects with intramyocardial injection on the mouse model of MI, representing a safer delivery approach. Conclusion: Thus, the optimized strategy for iCS generation is safer and has more therapeutic potentials. [ABSTRACT FROM AUTHOR]

Published
2021
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31. Composition and Associated Factors of Radiological Examination in Major Trauma Patients

Author

Liu Shanshou, Xie Jiangang, Zhu Chaojuan, Wang Qianmei, Yin Wen, Wang Xianqi, Li Junjie, and Zhao Wei

Subjects
Adult, China, medicine.medical_specialty, Radiography, Severity of injury, Computed tomography, Hospitals, General, law.invention, Tertiary Care Centers, 03 medical and health sciences, Injury Severity Score, 0302 clinical medicine, Trauma Centers, law, medicine, Humans, Prospective Studies, 030212 general & internal medicine, medicine.diagnostic_test, business.industry, Major trauma, General surgery, 030208 emergency & critical care medicine, Original Articles, General Medicine, Middle Aged, Radiological examination, medicine.disease, prospective observational study, Intensive care unit, Surgery, major trauma, radiological examination, Radiological weapon, Pediatrics, Perinatology and Child Health, Emergency Medicine, Wounds and Injuries, Observational study, Tomography, X-Ray Computed, business
Abstract

The care of major trauma patients continues to be a challenge for emergency physicians and trauma surgeons. We found that the total number of radiological examinations for major trauma patients in this study was high and mainly comprised radiography and computed tomography (CT), with CT being more commonly adopted. The number of CT scans was positively correlated with severity of injury and intensive care unit length of stay. Further study is warranted to optimize radiological examinations involving major trauma patients.

Published
2017

32. Effect of Er on Characteristics of Oxide Coating on 7075 Aluminum Alloy by Micro-arc Oxidation.

Author

ZHANG Xianju, WANG Xianqi, DENG Weihao, and HE Jiajing

Abstract

The 7075 aluminum alloys with 0%, 0.2% and 0.4% Er were subjected to micro-arc oxidation under the same parameters. The surface morphology and the phases of the oxide coating were analyzed using SEM and XRD respectively. The micro-hardness, thickness and corrosion resistance of the oxide coating were also studied simultaneously. The results show that the micro-arc oxidation coating of 7075 aluminum alloy with different Er contents is composed of gamma-Al2O3 phase. With the increase of Er content, the peak of γ-Al2O3 phase is enhanced. Er enters the oxide coating with the form of Al17Er2, which is an unbalanced phase after micro-arc action. With the increase of Er content, the surface roughness of oxide coating decreases firstly and then increases. When Er content is 0.2%, the surface deposit is fine and uniform, the diameter of pore is small, and the roughness is the lowest. As the Er content increases from 0% to 0.4%, the micro-hardness and thickness of the oxide coating also increases, and then the corrosion resistance increases significantly. Consequently, the self-corrosion current density decreases from 4.280x10-6 A/cm² to 2.405x10-9 A/cm². [ABSTRACT FROM AUTHOR]

Published
2020
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42. Development Key Point of Antibacterial & Deodorized Hemp Pulp Fiber Blended Yarn.

Author

Li Junhua, Wang Xianqi, Guan Yan, and Ma Junzhi

Subjects
YARN, SPINNING (Textiles), DEODORIZATION, HEMP, MIXING
Abstract

Development process of antibacterial & deodorized hemp pulp fiber blended yarn was discussed. The properties of deodorized hemp pulp fiber were studied. The key processing technology of deodorized hemp pulp fiber/cotton 50/5014.8texblendedyarnwasintroduced. The combinationofcardclothingwasoptimized. Sliverblendingtechnologywas adoptedtoensureuniformmixing. Theweightandlengthofrovingweresmallercontrolled. Finally, deodorizedhemppulp fiber/cotton 50/50 14.8 tex siro blended yarn that meet the quality requirement was successfully spun. It is considered that deodorized hemp pulp fiber is one kind of high-tech functional &environment friendly fiber. It can be used for the development of antibacterial & deodorized functional fabric. [ABSTRACT FROM AUTHOR]

Published
2017

43. The Large Area Detector onboard the eXTP mission

Author

Marco Feroci, Giovanni Ambrosi, Filippo Ambrosino, Matias Antonelli, Andrea Argan, Viktor Babinec, Marco Barbera, Jörg Bayer, Pierluigi Bellutti, Bruna Bertucci, Giuseppe Bertuccio, Xingzi Bi, Mirko Boezio, Walter Bonvicini, Giacomo Borghi, Enrico Bozzo, David Baudin, Florent Bouyjou, Daniele Brienza, Franck Cadoux, Riccardo Campana, Jiewei Cao, Elisabetta Cavazzuti, Francesco Ceraudo, Tianxiang Chen, Wen Chen, Daniela Cirrincione, Nicolas De Angelis, Alessandra De Rosa, Ettore Del Monte, Sergio Di Cosimo, Giuseppe Dilillo, Roman Dohnal, Immacolata Donnarumma, Yuri Evangelista, Qingmei Fan, Yannick Favre, Emanuele Fiandrini, Francesco Ficorella, Fabio Fuschino, Na Gao, Olivier Gevin, Marco Grassi, Manuel Guedel, Xingbo Han, Huilin He, Paul Hedderman, jan-willem den herder, Richard Hynek, Bing Hong, Ge Jin, Merlin Kole, Vladimír Karas, Martin Komarek, Claudio Labanti, Loghui Li, Tianming Li, Hong Liang, Olivier Limousin, Rui Liu, Ugo Lo Cicero, Jens Lohering, Giovanni Lombardi, Fang-Jun Lu, Tao Luo, Piero Malcovati, Hanqi Mao, Andrea Marinucci, Filippo Mele, Vasco Mendes, Martin Merkl, Aline Meuris, Małgorzata Michalska, Alfredo Morbidini, Gianluca Morgante, Fabio Muleri, Riccardo Munini, Lorenzo Mussolin, Barbara Negri, Petr Novak, Witold Nowosielski, Alessio Nuti, Piotr Orleanski, Roland Ottensamer, Luigi Pacciani, Stephane Paltani, Teng Pan, Giancarlo Pepponi, Emanuele Perinati, Raffaele Piazzolla, Antonino Picciotto, Samuel Pliego, Alexandre Rachevski, Irina Rashevskaia, Andrea Santangelo, Roberto Serafinelli, Stéphane Schanne, Konrad Skup, Libor Sveda, Jiri Svoboda, Christopher Tenzer, Michela Todaro, Gabreil Torok, Alessio Trois, Andrea Vacchi, Enrico Virgilli, Hao Xiong, Jian Wang, Xianqi Wang, Berend Winter, Xin Wu, Yupeng Xu, Gianluigi Zampa, Nicola Zampa, Andrei Zdziarski, Long Zhang, Shu Zhang, Shuang-Nan Zhang, Wenda Zhang, Xiaoli Zhang, Zhen Zhang, Yupeng Zhou, Nicola Zorzi, den Herder, Jan-Willem A., Feroci, Marco, Ambrosi, Giovanni, Ambrosino, Filippo, Antonelli, Matia, Argan, Andrea, Babinec, Viktor, Barbera, Marco, Bayer, Jörg, Bellutti, Pierluigi, Bertucci, Bruna, Bertuccio, Giuseppe, Bi, Xingzi, Boezio, Mirko, Bonvicini, Walter, Borghi, Giacomo, Bozzo, Enrico, Baudin, David, Bouyjou, Florent, Brienza, Daniele, Cadoux, Franck, Campana, Riccardo, Cao, Jiewei, Cavazzuti, Elisabetta, Ceraudo, Francesco, Chen, Tianxiang, Chen, Wen, Cirrincione, Daniela, De Angelis, Nicola, De Rosa, Alessandra, Del Monte, Ettore, Di Cosimo, Sergio, Dilillo, Giuseppe, Dohnal, Roman, Donnarumma, Immacolata, Evangelista, Yuri, Fan, Qingmei, Favre, Yannick, Fiandrini, Emanuele, Ficorella, Francesco, Fuschino, Fabio, Gao, Na, Gevin, Olivier, Grassi, Marco, Guedel, Manuel, Han, Xingbo, He, Huilin, Hedderman, Paul, den herder, jan-willem, Hynek, Richard, Hong, Bing, Jin, Ge, Kole, Merlin, Karas, Vladimír, Komarek, Martin, Labanti, Claudio, Li, Loghui, Li, Tianming, Liang, Hong, Limousin, Olivier, Liu, Rui, Lo Cicero, Ugo, Lohering, Jen, Lombardi, Giovanni, Lu, Fang-Jun, Luo, Tao, Malcovati, Piero, Mao, Hanqi, Marinucci, Andrea, Mele, Filippo, Mendes, Vasco, Merkl, Martin, Meuris, Aline, Michalska, Małgorzata, Morbidini, Alfredo, Morgante, Gianluca, Muleri, Fabio, Munini, Riccardo, Mussolin, Lorenzo, Negri, Barbara, Novak, Petr, Nowosielski, Witold, Nuti, Alessio, Orleanski, Piotr, Ottensamer, Roland, Pacciani, Luigi, Paltani, Stephane, Pan, Teng, Pepponi, Giancarlo, Perinati, Emanuele, Piazzolla, Raffaele, Picciotto, Antonino, Pliego, Samuel, Rachevski, Alexandre, Rashevskaia, Irina, Santangelo, Andrea, Serafinelli, Roberto, Schanne, Stéphane, Skup, Konrad, Sveda, Libor, Svoboda, Jiri, Tenzer, Christopher, Todaro, Michela, Torok, Gabreil, Trois, Alessio, Vacchi, Andrea, Virgilli, Enrico, Xiong, Hao, Wang, Jian, Wang, Xianqi, Winter, Berend, Wu, Xin, Xu, Yupeng, Zampa, Gianluigi, Zampa, Nicola, Zdziarski, Andrei, Zhang, Long, Zhang, Shu, Zhang, Shuang-Nan, Zhang, Wenda, Zhang, Xiaoli, Zhang, Zhen, Zhou, Yupeng, and Zorzi, Nicola

Subjects
Settore FIS/05 - Astronomia E Astrofisica, EXTP, LAD, Silicon Drift Detector, X-ray timing
Abstract

The Large Area Detector (LAD) is the high-throughput, spectral-timing instrument onboard the eXTP mission, a flagship mission of the Chinese Academy of Sciences and the China National Space Administration, with a large European participation coordinated by Italy and Spain. The eXTP mission is currently performing its phase B study, with a target launch at the end-2027. The eXTP scientific payload includes four instruments (SFA, PFA, LAD and WFM) offering unprecedented simultaneous wide-band X-ray timing and polarimetry sensitivity. The LAD instrument is based on the design originally proposed for the LOFT mission. It envisages a deployed 3.2 m2 effective area in the 2-30 keV energy range, achieved through the technology of the large-area Silicon Drift Detectors - offering a spectral resolution of up to 200 eV FWHM at 6 keV - and of capillary plate collimators - limiting the field of view to about 1 degree. In this paper we will provide an overview of the LAD instrument design, its current status of development and anticipated performance.

Published
2022

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