No abstract

Background: Right heart catheterization is the gold standard for evaluating hemodynamic parameters of pulmonary circulation, especially pulmonary artery pressure (PAP) for diagnosis of pulmonary hypertension (PH). However, the invasive and costly nature of RHC limits its widespread application in daily practice. Purpose: To develop a fully automatic framework for PAP assessment via machine learning based on computed tomography pulmonary angiography (CTPA). Materials and Methods: A machine learning model was developed to automatically extract morphological features of pulmonary artery and the heart on CTPA cases collected between June 2017 and July 2021 based on a single center experience. Patients with PH received CTPA and RHC examinations within 1 week. The eight substructures of pulmonary artery and heart were automatically segmented through our proposed segmentation framework. Eighty percent of patients were used for the training data set and twenty percent for the independent testing data set. PAP parameters, including mPAP, sPAP, dPAP, and TPR, were defined as ground-truth. A regression model was built to predict PAP parameters and a classification model to separate patients through mPAP and sPAP with cut-off values of 40 mm Hg and 55 mm Hg in PH patients, respectively. The performances of the regression model and the classification model were evaluated by analyzing the intraclass correlation coefficient (ICC) and the area under the receiver operating characteristic curve (AUC). Results: Study participants included 55 patients with PH (men 13; age 47.75 ± 14.87 years). The average dice score for segmentation increased from 87.3% ± 2.9 to 88.2% ± 2.9 through proposed segmentation framework. After features extraction, some of the AI automatic extractions (AAd, RVd, LAd, and RPAd) achieved good consistency with the manual measurements. The differences between them were not statistically significant (t = 1.222, p = 0.227; t = −0.347, p = 0.730; t = 0.484, p = 0.630; t = −0.320, p = 0.750, respectively). The Spearman test was used to find key features which are highly correlated with PAP parameters. Correlations between pulmonary artery pressure and CTPA features show a high correlation between mPAP and LAd, LVd, LAa (r = 0.333, p = 0.012; r = −0.400, p = 0.002; r = −0.208, p = 0.123; r = −0.470, p = 0.000; respectively). The ICC between the output of the regression model and the ground-truth from RHC of mPAP, sPAP, and dPAP were 0.934, 0.903, and 0.981, respectively. The AUC of the receiver operating characteristic curve of the classification model of mPAP and sPAP were 0.911 and 0.833. Conclusion: The proposed machine learning framework on CTPA enables accurate segmentation of pulmonary artery and heart and automatic assessment of the PAP parameters and has the ability to accurately distinguish different PH patients with mPAP and sPAP. Results of this study may provide additional risk stratification indicators in the future with non-invasive CTPA data.

In order to analyze the vibration characteristics of mistuned multistage bladed disks of an aero-engine compressor, a finite element reduction model of mistuned multistage bladed disks is established based on substructure modal synthesis method. The accuracy of the substructure model was verified by comparing calculation accuracy of the substructure model and the integral model. The influence of different modal truncation numbers on the calculation results are discussed. The vibration modes of each stage of the bladed disks are obtained, the forced response is analyzed from the perspective of strain energy. The result shows that modal truncation number, rotation softening effect, and speed have significant effects on the dynamic frequency calculation results of the multistage bladed disks. The typical mode shapes of the first 200 orders of multistage bladed disks are obtained. With the increase of mistuning standard deviation, the strain energy of multistage bladed disk system decreases gradually.

Limited by traditional construction project management ideas and systems, the implementation of the PMC model in China still has serious problems such as opposition and frequent conflicts. How to reveal the causes of organizational conflicts and explore the key mechanism of the implementation of the PMC model from the system perspective are urgent problems to be solved. Based on the idea of engineering system view, this paper abstracts the PMC project participants with self-organizing characteristics of the organizational management system, in which the internal structure is closely related, and defines the connotation of synergy and synergistic evolution of the PMC project organizational management system. Using the Cucker–Smale model to describe the group movement, the hierarchical system and the acceleration efficiency function of the project legal person’s free will are constructed, and the structure, movement, and development law of the system itself are emphasized to simulate the ordered evolution trend of PMC project organizational management system and reveal the intrinsic causes of conflicts in PMC project and the key mechanisms of the PMC model application. The results show that first, the intensity of information communication between PMC subjects has a significant positive contribution to the orderliness of the organizational management system; second, too much acceleration of the project legal person’s free will causes group chaos in the system, while too little slows down the group stabilization time, which has a negative impact on cost and schedule; third, the more the organizational structure of PMC contractors tends to the whole-process integrated control, the more it can drive the group to gather in an orderly manner and form a synergistic control mode combining self-organization and other organizations; and fourth, the implementation of the PMC model should focus on eliminating the traditional institutional and conceptual barriers, forming a project management model with integrated control of the whole process of the PMC project contractor and effective macro supervision of the project legal person. The research results of this paper revealed the intrinsic causes of conflicts in PMC projects and the key mechanisms of PMC model application; it can help solve the confrontational situation of PMC project participants, promote the development of the PMC model, and give full play to the investment benefits.