Objective: To investigate a new class of solutions to the isotropic/homogeneous scalar wave equation, which termed limited diffraction beams and realize ultrasonic 3D imaging. Methods: Limited diffraction beams were derived. We performed the study of 3D pulse-echo imaging with limited diffraction array beam. To obtain high frame rate images, a single plane wave pulse (broadband) was transmitted with the arrays. Echoes received with the same arrays were processed with Fourier method to construct 3D images. Results: Compared with traditional pulse-echo imaging, this method has a larger depth of field, high frame rate, and high signal-to-noise ratio. Conclusion: The new method has prospect of high frame rate 3D imaging. In addition, the imaging system based this method is easily implemented and has high quality image.

Objective: To evaluate the occupational health risk of key posts exposed to cement dust in four cement production enterprises, and to provide reference for cement pneumoconiosis prevention and control. Methods: Four Chinese typical cement enterprises and key posts exposed to cement dust were selected to carry out occupational health investigation and detection, and three risk assessment methods were used to assess their occupational health risk levels, including semi-quantitative comprehensive index method, semi-quantitative contact ratio method and risk rating method of International Mining and Metal Commission ( ICMM ). Meanwhile, the differences and consistencies among different assessment methods were compared. Results: Dust free silica content ranged from ( 4.70±2.01 ) % to ( 5.63±2.48 ) %,and the total and respirable dust concentrations exposed by bagged cement loaders and cement baggers exceeded Chinese permissible concentration-time weighted average（ PC-TWA ）. The results of semi-quantitative comprehensive index method showed that all the types of work were at high risk of total and respirable dust, while the results of the other two assessment methods showed that bagged cement loaders and cement baggers were at a extremely high or intolerable risk. There were no significant differences among three risk assessment methods whether in terms of total dust or respirable dust ( P>0.05 ). ICMM risk rating method and contact ratio method showed highly positive correlation in term of respirable dust ( rs=0.894, P=0.016 ), but not in term of total dust ( rs=0.733, P=0.097 ). However, the correlations of comprehensive index method with the other two methods were unable to conduct. Conclusion Bagged cement loaders and cement baggers are at high occupational health risk levels. Moreover, semi-quantitative contact ratio method and ICMM risk rating method have high positive correlation in term of respirable dust, the applicability of comprehensive index method still needs further study.

Objective:To investigate the features, changing trend, and rules of pneumoconiosis in Jiangsu Province, China, as well as the health status of patients with pneumoconiosis.Methods:From July to October 2019, the patients with pneumoconiosis, reported up to the end of 2018 in Jiangsu Province, were enrolled as respondents, and follow-up and retrospective investigation were performed. A total of 24405 patients with pneumoconiosis were investigated, and related data were collected from the monitoring system of cause of death for residents, pneumoconiosis network reporting system, occupational disease diagnosis institution, management institutions for the reporting of occupational diseases, and related residents' committee or village committee. The patients with pneumoconiosis, who had been reported, were followed up by telephone or on-site visit to obtain the information on their conditions. A descriptive analysis was performed for age of onset, working years, sex, category of industry, type of pneumoconiosis, annual disease onset, geographic distribution, and medical security.Results:Among the 24405 patients, a male/female ratio was 16.81∶1. Of all 24405 patients, 15948 (65.35%) had stage 1 pneumoconiosis, 5289 (21.67%) had stage 2 pneumoconiosis, and 1637 (6.71%) had stage 3 pneumoconiosis. The mean working years for dust exposure was 16.25±9.95 years for all patients, and the mean working years for dust exposure was 15.80±9.95 years for patients with stage 1 pneumoconiosis, 17.82±9.80 years for patients with stage 2 pneumoconiosis, and 16.31±9.90 years for patients with stage 3 pneumoconiosis. The highest number of cases of pneumoconiosis was reported in Wuxi (5744 cases, accounting for 23.54%) , followed by Zhenjiang (4160 cases, accounting for 17.05%) , Xuzhou (3851 cases, accounting for 15.78%) , Yancheng (3340 cases, accounting for 13.69%) , and Suzhou (2948 cases, accounting for 12.08%) . Major types of pneumoconiosis included silicosis (15392 cases, accounting for 63.07%) and coal workers' pneumoconiosis (5253 cases, accounting for 21.52%) . In this survey, 21115 completed follow-up, among whom 15924 survived and 5191 died, 15924 patients with pneumoconiosis survived, among whom 7461 (46.85%) had an age of ≥70 years and 2515 (15.79%) were exposed to dust for 5-9 years. The industries involved were mainly coal mining and washing industry (5687 cases, accounting for 35.71%) and public management, social security, and social organization (3349 cases, accounting for 21.03%) ; in terms of security, 7999 patients (50.23%) were covered by occupational injury insurance, 946 (5.94%) were compensated by employers, 4537 (28.49%) were covered by basic medical insurance for urban and rural residents, 1590 (9.98%) were covered by critical illness insurance, and 5458 (34.28%) were covered by other types of social security, such as medical assistance and poverty relief.Conclusion:Silicosis and coal worker's pneumoconiosis are the key points for the prevention and treatment of pneumoconiosis in Jiangsu Province, and supervision should be strengthened for industries and regions with serious dust hazards.

Objective:To investigate the features, changing trend, and rules of pneumoconiosis in Jiangsu Province, China, as well as the health status of patients with pneumoconiosis.Methods:From July to October 2019, the patients with pneumoconiosis, reported up to the end of 2018 in Jiangsu Province, were enrolled as respondents, and follow-up and retrospective investigation were performed. A total of 24405 patients with pneumoconiosis were investigated, and related data were collected from the monitoring system of cause of death for residents, pneumoconiosis network reporting system, occupational disease diagnosis institution, management institutions for the reporting of occupational diseases, and related residents' committee or village committee. The patients with pneumoconiosis, who had been reported, were followed up by telephone or on-site visit to obtain the information on their conditions. A descriptive analysis was performed for age of onset, working years, sex, category of industry, type of pneumoconiosis, annual disease onset, geographic distribution, and medical security.Results:Among the 24405 patients, a male/female ratio was 16.81∶1. Of all 24405 patients, 15948 (65.35%) had stage 1 pneumoconiosis, 5289 (21.67%) had stage 2 pneumoconiosis, and 1637 (6.71%) had stage 3 pneumoconiosis. The mean working years for dust exposure was 16.25±9.95 years for all patients, and the mean working years for dust exposure was 15.80±9.95 years for patients with stage 1 pneumoconiosis, 17.82±9.80 years for patients with stage 2 pneumoconiosis, and 16.31±9.90 years for patients with stage 3 pneumoconiosis. The highest number of cases of pneumoconiosis was reported in Wuxi (5744 cases, accounting for 23.54%) , followed by Zhenjiang (4160 cases, accounting for 17.05%) , Xuzhou (3851 cases, accounting for 15.78%) , Yancheng (3340 cases, accounting for 13.69%) , and Suzhou (2948 cases, accounting for 12.08%) . Major types of pneumoconiosis included silicosis (15392 cases, accounting for 63.07%) and coal workers' pneumoconiosis (5253 cases, accounting for 21.52%) . In this survey, 21115 completed follow-up, among whom 15924 survived and 5191 died, 15924 patients with pneumoconiosis survived, among whom 7461 (46.85%) had an age of ≥70 years and 2515 (15.79%) were exposed to dust for 5-9 years. The industries involved were mainly coal mining and washing industry (5687 cases, accounting for 35.71%) and public management, social security, and social organization (3349 cases, accounting for 21.03%) ; in terms of security, 7999 patients (50.23%) were covered by occupational injury insurance, 946 (5.94%) were compensated by employers, 4537 (28.49%) were covered by basic medical insurance for urban and rural residents, 1590 (9.98%) were covered by critical illness insurance, and 5458 (34.28%) were covered by other types of social security, such as medical assistance and poverty relief.Conclusion:Silicosis and coal worker's pneumoconiosis are the key points for the prevention and treatment of pneumoconiosis in Jiangsu Province, and supervision should be strengthened for industries and regions with serious dust hazards.

Both feature representation and classifier performance are important factors that determine the performance of computer-aided diagnosis (CAD) systems. In order to improve the performance of ultrasound-based CAD for breast cancers, a novel multiple empirical kernel mapping (MEKM) exclusivity regularized machine (ERM) ensemble classifier algorithm based on self-paced learning (SPL) is proposed, which simultaneously promotes the performance of both feature representation and the classifier. The proposed algorithm first generates multiple groups of features by MEKM to enhance the ability of feature representation, which also work as the kernel transform in multiple support vector machines embedded in ERM. The SPL strategy is then adopted to adaptively select samples from easy to hard so as to gradually train the ERM classifier model with improved performance. This algorithm is verified on a B-mode ultrasound dataset and an elastography ultrasound dataset, respectively. The results show that the classification accuracy, sensitivity and specificity on B-mode ultrasound are (86.36±6.45)%, (88.15±7.12)%, and (84.52±9.38)%, respectively, and the classification accuracy, sensitivity and specificity on elastography ultrasound are (85.97±3.75)%, (85.93±6.09)%, and (86.03±5.88)%, respectively. It indicates that the proposed algorithm can effectively improve the performance of ultrasound-based CAD for breast cancers with the potential for application.
Algorithms ; Breast Neoplasms/diagnostic imaging* ; Computers ; Diagnosis, Computer-Assisted ; Humans ; Support Vector Machine ; Ultrasonography