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Background Cardiotoxicity is a leading cause of mortality among breast cancer patients treated with chemotherapy. Therefore, an early risk assessment is vital for the clinical prevention and treatment of cardiotoxicity in breast cancer patients treated with chemotherapy, although a recognized tool is scant in our country. Objective To develop a cardiotoxic risk assessment scale for breast cancer patients undergoing chemotherapy and to test its reliability and validity. Methods Through reviewing relevant domestic and international literatures, a pool involving items to assess the risk of cardiotoxicity in breast cancer patients treated with chemotherapy was created. Semi-structured interviews with healthcare providers at Jiangsu Cancer Hospital from September to October 2022 were performed by purposive sampling, thus primarily forming a tool of items for the cardiotoxic risk assessment scale. In addition, breast cancer patients treated with chemotherapy in Jiangsu Cancer Hospital were randomly selected for a pre-survey and validation of the reliability and validity of the scale. Ranked by the score of the cardiotoxic risk assessment scale, the top 27% of participants were assigned into the high-score group, and the remaining were in the low-score group. Cronbach's α coefficient was used to evaluate the internal consistency of the scale. Validity of the scale was verified by measuring the item-level content validity index (I-CVI) and scale-level content validity index (S-CVI). Exploratory factor analysis was performed to assess the structural validity. Receiver operating characteristic (ROC) curves were plotted, and the area under tcurve (AUC) was calculated to determine the predictive validity. Results Twenty healthcare providers were included in the semi-structured interviews. After two rounds of expert consultations, a 19-item cardiotoxic risk assessment scale in breast cancer patients treated with chemotherapy was developed. In this study, there were 79 patients in the low-score group and 83 in the high-score group. No significant differences in the history of smoking, endocrine treatment and immunotherapy were detected between the two groups (P>0.05). Correlation analysis showed that the history of smoking and immunotherapy was not significantly correlated with the total scores (P>0.05). Eventually, three items of smoking history, history of endocrine treatment and history of immunotherapy were removed, forming a 16-item scale. The Cronbach's α coefficient, test-retest reliability and inter-rater reliability were 0.739, 0.983 and 0.984, respectively. Content validity results showed that I-CVI ranged from 0.83 to 1.00, and S-CVI was 0.98. Predictive validity results showed the AUC of 0.887 (95%CI=0.827-0.947, P

As an important branch in the field of computer vision,object tracking has been widely used in many fields such as intelligent video surveillance,human-computer interaction and autonomous driving.Although object tracking has achieved good development in recent years,tracking in complex environment is still a challenge.Due to problems such as occlusion,object deformation and illumination change,tracking performance will be inaccurate and unstable.In this paper,an effective object tracking method AFTM,is proposed with attention features.Firstly,this paper constructs an adaptively generated attention weight factor group,which implements an efficient adaptive fusion strategy for response map to improve the accuracy of object positioning and bounding box scale calculation in the process of classification and regression.Secondly,aiming at the class imbalance in the data set,the proposed method uses the dynamically scaled cross entropy loss as the loss function of the object positioning network,which can modify the optimization direction of the model and make the tracking performance more stable and reliable.Finally,this paper designs a corresponding learning rate adjustment strategy to stochastically average the weight of a number of models,which can enhance the generalization ability of the model.Experimental results on public data sets show that the proposed method has higher accuracy and more stable tracking performance in complex tracking environment.

The numerical simulation of spray lubrication and improvement of lubricant condition in a complex gearbox are researched. An experimental rig for spray lubrication of a pair of high-speed gears is set up and relevant experiments are carried out firstly. The experimental results are used to verify the correctness of numerical simulation method. Then numeric model of spray lubrication in a complex gearbox is established and simulation as well as analysis are conducted. The results show that overlong spray distance,angle of end face and jet flow on out of mesh side make against to lubrication. Then optimization of spray angle based on single-phase flow computational method is studied. Result show that,there is a weakest trace of air in the center plane of meshed gears. And if the axis of the nozzle lays on this trace,the meshed gears will have their best lubricant performance.