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OBJECTIVE：To explore th e influential factors of the price fluctuation of Chinese crud drug ，and to provide reference for the healthy development of tranditional Chinese medicine industry in China. METHODS ：Based on the relevant statistics from 1992 to 2019，a structural vector autoregressive model was established. After data stationarity test ，cointegration relationship test ，model estimation and stability test ，impulse response function and variance decomposition were used to investigate the impact of supply ，demand，cost of implantation and production and inflation on the price of Chinese crud drug. RESULTS & CONCLUSIONS：There was a long-term equilibrium relationship among the price of Chinese crud drug ，planting area of Chinese crud drug ，output of Chinese patent medicine ，market turnover of Chinese crud drug ，export volume of Chinese crud drug ，price index of agricultural means of production and consumer price index. The price of Chinese crud drug had the greatest impact and contribution rate on itself ，followed by planting area of Chinese crud drug ，export volume of Chinese crud drug and price index of agricultural means of production. However ，the output of Chinese patent medicine ，the turnover of Chinese crud drug market and consumer price index had weak influence. It is suggested to make full use of Internet information technology ，strengthen the price monitoring and early warning of Chinese crud drug ，promote the supply side structural reform of tranditional Chinese medicine industry，improve the scientific and technological level of Chinese crud drug planting and promote large-scale production of Chinese herbal medicine so as to stabilize the price of Chinese crud drug.
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The study of the acoustic field generated by an ultrasonic transducer is fundamental to its construction and characterization, because it defines how it will behave before being built. It also defines whether it is feasible or not, for the application to which it was designed. It can also lead to modifications to the project so it behaves as expected. In this work, a software was implemented in MATLAB®, for computational simulation of acoustic fields generated by ultrasonic transducers of different configurations. Two models were used, Zemanek and Stepanishen. Transducers with focus and apodization and transmission medium with attenuation may also be simulated. For the simulation of Zemanek's model, the mathematical method of discretization was used. The Stepanishen's model used an analytical solution for the impulse response. The developed programs were aggregated into a computer package, named FSIM, and a graphic interface was created. The user can choose among some of the transducer configurations and simulation parameters already implemented. FSIM has a modular architecture and allows further simulation modules to be added. The simulations were validated comparing results to those previously published in classical papers from Zemanek, and from Lockwood and Willete, in addition to prior results from research studies conducted at the Biomedical Engineering Department of the School of Electrical and Computing Engineering at the Universidade Estadual de Campinas (UNICAMP).
El estudio del campo acústico generado por un transductor ultrasónico es fundamental para su construcción y caracterización, ya que define cómo se comportará antes de ser construido. También define si realmente es factible para la aplicación a la que fue diseñado, y también puede sugerir modificaciones al proyecto, para que se comporte como se espera. En este trabajo un software fue implementado en MATLAB®, para la simulación computacional de los campos acústicos generados por los transductores ultrasónicos de diferentes configuraciones. Dos modelos fueran usados, Zemanek y Stepanishen. Transductores con el enfoque y apodización y medios con atenuación también pueden ser simulados. Para la simulación del modelo de Zemanek, se utilizó el método matemático de discretización y para el modelo de Stepanishen, se empleó una solución analítica para la respuesta impulsiva. Los programas desarrollados fueron agregados en un paquete computacional, llamado FSIM, y una interfaz gráfica fue creada. El usuario puede elegir entre algunas configuraciones del transductor y parámetros de simulación ya implementados; FSIM tiene una arquitectura modular y permite que otros módulos de simulación sean añadidos. Las simulaciones fueron validadas comparando resultados obtenidos previamente por otros trabajos de investigación del Departamento de Ingeniería Biomédica de la Facultad de Ingeniería Eléctrica y Computación de la UNICAMP y por los artículos clásicos de Zemanek y Lockwood y Willette.
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Objective To evaluate the feasibility of renal artery angiography with interpolated finite impulse response (IRFR) sequence on 1.5T MR. Methods A total of 122 subjects underwent MR scan with IFIR sequence. On axial image of IFIR, bilateral signal-to-noise ratio (SNR) and breath artifact of renal artery were measured and 3D maximum intensity projection (MIP) images were reconstructed on workstation ADW 4.3, and each branch was scored according to its displaying quality. Influence of SNR, age and breath artifact on the displaying of renal artery were compared and analyzed. Results Renal segmental artery could be seen in 112 subjects (91.80%). Among them, segmental artery was showed clearly in 78 subjects (63.93%), post-segmental artery was showed in 54 subjects (44.26%) and branches of post-segmental artery was showed in 22 subjects (18.03%). There was statistical difference of renal artery scores mean rank between ≥60 years group and ＜60 years group (49.25 vs 67.48, P=0.006), as well as between the group without and with breath artifact (66.66 vs 43.35, P=0.002). No statistical difference of SNR was found among renal artery scores from 1-5 (P=0.177). Conclusion IFIR sequence is simple and safe for renal artery angiography on 1.5T MR, and different grades of renal artery branch can be showed clearly.
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A novel method based on independent component analyzing (ICA) in frequency domain to distinguish the frequency characteristics of multi-sensor system is presented. The conditions of this type of ICA are considered and each step of resolving the problem is discussed. For a two gas sensor array, the frequency characteristics including amplitude-frequency and phase-frequency are recognized by this method, and cross-sensitivity between them is also eliminated. From the principle of similarity, the recognition mean square error is no more than 0.085.
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A novel method based on independent component analyzing (ICA) in frequency domain to distinguish the frequency characteristics of multi-sensor system is presented. The conditions of this type of ICA are considered and each step of resolving the problem is discussed. For a two gas sensor array, the frequency characteristics including amplitude-frequency and phase-frequency are recognized by this method, and cross-sensitivity between them is also eliminated. From the principle of similarity, the recognition mean square error is no more than 0.085.
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BACKGROUND: In contrast to classic drug injection method, various types of noninvasive spontaneous baroreflex sensitivity (SBRS) methods have been developed using the computer analysis of the spontaneous fluctuation of heart rate and arterial blood pressure for baroreflex evaluation. In this study, we evaluated the effects of sevoflurane anesthesia on SBRS by comparing various SBRS estimates and their correlations before and after sevoflurane anesthesia. METHODS: Radial arterial pressure and electrocardiography were recorded in 50 patients before and after sevoflurane anesthesia. We derived six SBRS indices from the methods including sequence, alpha-index, transfer function analysis and impulse response function. The sequence method measured an average of baroreflex sequences. The alpha-index used the average of the square roots of the ratios between the RRI and SBP spectral power. The transfer function index used RRI and SBP cross-spectral magnitude for this index. The impulse response function method employed an inverse Fourier transform. RESULTS: All SBRS and accompanying correlations were reduced after sevoflurane anesthesia. Low (44%) and high (4%) frequency transfer function gain and sequence SBRS (4%) failed to be computed out of some patients after sevoflurane anesthesia due to poor coherence and absence of a valid sequence. CONCLUSIONS: Sevoflurane anesthesia caused marked depression of SBRS and weakened their correlations. Therefore, it is necessary to understand the characteristics of each SBRS method for selecting an appropriate method during anesthesia.