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2 2023

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Financial development and environmental pollution control - an analysis of intermediary effect based on technological innovation

Han Li, Li Ting

Ecological Chemistry and Engineering. S

2023

Vol. 30, nr 2

251--258

Based on the rapid development of green finance and the panel data of 30 provinces in China (excluding Tibet, Taiwan, Hong Kong and Macao) from 2007 to 2020, to deeply discuss the relationship between financial development (FD), technological innovation and environmental pollution (EP) control is the centre of this article by using panel fixed-effect and intermediary effect model. The influence of FD on EP is tested by building a benchmark regression model. In addition, the intermediary effect model is adopted to explore how FD affects EP control through technological innovation mechanism. The conclusions show that China’s FD can effectively promote regional EP control on the whole, and FD can improve EP through technological innovation mechanism, but there is significant regional heterogeneity: compared with high government intervention areas, FD can promote EP control through technological innovation in low government intervention areas. Therefore, it is suggested that all regions promote the construction of financial infrastructure, upgrade the level of regional financial marketisation, speed up the realisation of regional technological innovation and EP control. This work is conducive to the formulation of appropriate government policies to promote the improvement of the financial system and the establishment of innovative mechanisms, and the reasonable reduction of government intervention and the improvement of the efficiency of financial resource allocation based on the needs of financial market players.

Automated detection of abnormal respiratory sound from electronic stethoscope and mobile phone using MobileNetV2

Liao Ximing, Wu Yin, Jiang Nana, Sun Jiaxing, Xu Wujian, Gao Shaoyong, Wang Jun, Li Ting, Wang Kun, Li Qiang

Biocybernetics and Biomedical Engineering

2023

Vol. 43, no. 4

763--775

Auscultation, a traditional clinical examination method using a stethoscope to quickly assess airway abnormalities, remains valuable due to its real-time, non-invasive, and easy-to-perform nature. Recent advancements in computerized respiratory sound analysis (CRSA) have provided a quantifiable approach for recording, editing, and comparing respiratory sounds, also enabling the training of artificial intelligence models to fully excavate the potential of auscultation. However, existing sound analysis models often require complex computations, leading to prolonged processing times and high calculation and memory requirements. Moreover, the limited diversity and scope of available databases limits reproducibility and robustness, mainly relying on small sample datasets primarily collected from Caucasians. In order to overcome these limitations, we developed a new Chinese adult respiratory sound database, LD-DF RSdb, using an electronic stethoscope and mobile phone. By enrolling 145 participants, 9,584 high quality recordings were collected, containing 6,435 normal sounds, 2,782 crackles, 208 wheezes, and 159 combined sounds. Subsequently, we utilized a lightweight neural network architecture, MobileNetV2, for automated categorization of the four types of respiratory sounds, achieving an appreciable overall performance with an AUC of 0.8923. This study demonstrates the feasibility and potential of using mobile phones, electronic stethoscopes, and MobileNetV2 in CRSA. The proposed method offers a convenient and promising approach to enhance overall respiratory disease management and may help address healthcare resource disparities.