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Huaguo Zhang,1 Song Wang2 1Nursing Department, Beijing Shijitan Hospital, Capital Medical University, Beijing, People’s Republic of China; 2West China School of Nursing/West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of ChinaCorrespondence: Song Wang, West China School of Nursing/West China Hospital, Sichuan University, No. 37, Guoxue Alley, Wuhou District, Chengdu, Sichuan, 610041, People’s Republic of China, Email wangzhikang2018@126.com

Huaguo Zhang,1,* Song Wang,2,* Xiaolian Jiang2 1Department of Nursing, Beijing Shijitan Hospital, Capital Medical University, Beijing, People’s Republic of China; 2West China School of Nursing/West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiaolian Jiang, West China School of Nursing/West China Hospital, Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu, Sichuan, 610041, People’s Republic of China, Email jangxaolianhl@163.com

Huaguo Zhang,1 Song Wang2 1Nursing Department, Beijing Shijitan Hospital, Capital Medical University, Beijing, People’s Republic of China; 2West China School of Nursing/West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of ChinaCorrespondence: Song Wang, West China School of Nursing/West China Hospital, Sichuan University, No. 37, Guoxue Alley, Wuhou District, Chengdu, Sichuan, 610041, People’s Republic of China, Email wangzhikang2018@126.com

Song Wang,1 Yuanyuan Song,2 Huaguo Zhang,3 Jing Song,4 Xiaoyan Guo,5 Xiaolian Jiang1 1West China School of Nursing, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 2Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 3Department of Nursing, Beijing Shijitan Hospital, Capital Medical University, Beijing, People’s Republic of China; 4School of Stomatology, Bengbu Medical University, Bengbu, Anhui, People’s Republic of China; 5Department of Pharmacy, Dezhou Municipal Hospital, Dezhou, Shandong, People’s Republic of ChinaCorrespondence: Xiaolian Jiang, West China School of Nursing, West China Hospital, Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu, Sichuan, 610041, People’s Republic of China, Email jangxaolianhl@163.com; jiang_xiaolian@126.comPurpose: This study aimed to improve cancer-related fatigue (CRF) and health outcomes of colorectal cancer patients by understanding the status quo of CRF, exploring the relations of coping, anxiety symptoms, depressive symptoms, body image perception and CRF, and also identifying the factors affecting CRF based on a generalized linear modeling approach.Patients and Methods: An exploratory cross-sectional study was conducted on 370 colorectal cancer patients at two hospitals in Anhui Province, China, from July 2020 to February 2021. The data were collected by using general information questionnaire, cancer fatigue scale, simplified coping style questionnaire, generalized anxiety disorder-7 scale, patient health questionnaire-9, and body image scale. Descriptive statistics, t-tests, one-way analysis of variance, Pearson correlation analyses, and generalized linear model analyses were applied to analyze the data.Results: The average CRF score of the patients was 21.612 (SD=6.160), with a prevalence rate of 69.4% for clinically relevant fatigue. T

This study analyzed the noise equivalent sigma zero (NESZ) and ocean wind sensitivity for Chinese C-band Gaofen-3 (GF-3) quad-polarization synthetic aperture radar (SAR) measurements to facilitate further operational wind extraction from GF-3 data. Data from the GF-3 quad-polarization SAR and collocated winds from both NOAA/NCEP Global Forecast System (GFS) atmospheric model and National Data Buoy Center (NDBC) buoys were used in the analysis. For NESZ, the co-polarization was slightly higher compared to the cross-polarization. Regarding co-polarization and cross-polarization, NESZ was close to RadarSAT-2 and Sentinel-1 A. Wind sensitivity was analyzed by evaluating the dependence on winds in terms of normalized radar cross-sections (NRCS) and polarization combinations. The closest geophysical model function (GMF) and the polarization ratio (PR) model to GF-3 data were determined by comparing data and the model results. The dependence of co-polarized NRCS on wind speed and azimuth angle was consistent with the proposed GMF models. The combination of CMOD5 and CMOD5.N was considered to be the closest GMF in co-polarization. The cross-polarized NRCS exhibited a strong linear relationship with moderate wind speeds higher than 4 ms-1, but a weak correlation with the azimuth angle. The proposed model was considered as the closest GMF in cross-polarization. For polarization combinations, PR and polarization difference (PD) were considered. PR increased only with the incidence angle, whereas PD increased with wind speed and varied with azimuth angle. There were three very close PR models and each can be considered as the closest. Preliminary results indicate that GF-3 quad-polarization data are valid and have the ability to extract winds in each polarization.

It has been widely accepted that the security cryptosystems should be only dependent on the security of their secret keys. However, there are still secret ciphers with unknown components in their commercial applications due to various reasons. The existing reverse engineering analyzes are developed for analyzing specific ciphers, and cannot cope with secret algorithms with different structures. By looking into the common characteristics of the secret algorithms of ciphers implemented with unknown S-boxes, we proposed a novel reverse engineering analysis approach referred to as Signed Reverse Engineering based on Differential Power Analysis (SREDPA). It is a generic reverse engineering analysis and can recover the parameters of the secret S-boxes of the block ciphers in typical structures such as SPN, Feistel, and XFeistel (eXtended Feistel). By identifying the bias of the differential power analysis (DPA) traces, we build the theoretical model of SREDPA and prove its effectiveness. Experiments are performed on secret algorithms in different structures and further validate our SREDPA experimentally. The complexity of SREDPA only relies on the size of S-boxes and the reverse engineering analysis is efficient. As shown in the theoretical analysis and the conducted experiments, our SREDPA approach is readily to be extended for analyzing other secret ciphers with unknown S-boxes. This renders a new challenge on the design and implementation of secret ciphers. 2014 Science China Press and Springer-Verlag Berlin Heidelberg.