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1.
Am J Transl Res ; 15(11): 6621-6625, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-38074813

RESUMO

At present, traditional music therapy based on "white noise" is commonly used to treat tinnitus patients. This study aims to apply "pink noise", which has a more balanced frequency distribution than white noise, to the field of tinnitus rehabilitation treatment to study its inhibitory effect on tinnitus. Fractal technology (fractal mathematics) was used to generate semi-repetitive tones as the basic tone of music therapy. This clinical study recruited 43 adult tinnitus patients with varying degrees of hearing loss as the study subjects. All patients received fractal music therapy with hearing aids. The study evaluated the Tinnitus Handicap Inventory (THI) of patients' usage and tested the indicators with paired sample T-tests. The results indicate that "pink noise" is effective in the treatment of tinnitus, and the differences in the scores are statistically significant before and after treatment (P<0.05). In addition, by comparing the tone spectra of "white noise" and "pink noise", we found that the frequency component power of "pink noise" is mainly concentrated in the middle and low frequency range. Its slope is -3 dB/Oct, which means that the frequency decays downwards as the ratio increases. In this study, a tinnitus music therapy based on the "pink noise" tone was developed, which mainly solved the awkward problem of no specific drugs or special tinnitus treatment equipment. At the same time, it helps to accelerate the development of related medical devices and improve the quality of life of tinnitus patients.

2.
PLoS One ; 15(5): e0233093, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32433705

RESUMO

OBJECTIVE: There is a huge technology gap between regions in Chinese pharmaceutical manufacturing industry, which is the reality that must be faced. However, most of the available researches on innovation efficiency are based on the logic of a given technology level, ignoring the regional technological gap. This paper will stand from the perspective of technology gap and re-examine the innovation efficiency of pharmaceutical manufacturing industry in different regions of China and its impact on regional industrial competitiveness. METHODS: We use the DEA-BCC input-oriented model to measure innovation efficiency of 28 provinces from the data of China's pharmaceutical manufacturing industry. The threshold model is constructed, with technology level as the threshold variable, innovation efficiency as the main explanatory variable, and industrial competitiveness as the dependent variable. In the threshold model, 28 regions are divided into three technical groups, and further, the impact of innovation efficiency on industrial competitiveness in different groups is analyzed and compared. RESULTS: According to the empirical research results, an U-shaped efficiency trap has been found in Chinese pharmaceutical manufacturing industry, and the areas with medium technical level are at the bottom of the trap. The improvement of innovation efficiency does not necessarily promote the improvement of regional industrial competitiveness. Only in high-level and low-level technology groups, innovation efficiency has effectively promoted the improvement of industrial competitiveness. In addition, the intensity of R&D investment has a similar impact on industrial competitiveness. CONCLUSIONS: The findings suggest that, regions in the efficiency trap should strive to seek opportunities for industrial transformation and focus on the industrial transformation of new technology, new industry and new opportunities, instead of blindly pursuing R&D investment intensity and superstitious innovation efficiency. So as to free up innovation resources for high-quality technological innovation in other regions. In addition, the Chinese government should make use of its public hospital system to normalize and expand the centralized drug procurement and eliminate the low-quality innovation.


Assuntos
Indústria Farmacêutica/estatística & dados numéricos , Indústria Manufatureira/estatística & dados numéricos , China , Invenções/estatística & dados numéricos
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