A kind of method of modal identification subject to ambient excitation is presented. A new synthesis stationary signal based on structural response wavelet transform and wavelet coefficient processes co-integration is...A kind of method of modal identification subject to ambient excitation is presented. A new synthesis stationary signal based on structural response wavelet transform and wavelet coefficient processes co-integration is obtained. The new signal instead of structural response is used in identifying the modal parameters of a non- stationary system, combined with the method of modal identification under stationary random excitation-the NExT method and the adjusted continuous least square method. The numerical results show that the method can eliminate the non-stationarity of structural response subject to non-stationary random excitation to a great extent, and is highly precise and robust.展开更多
Based on the statistical data of Huixian from 1992 to 2010, we analyze the long-term and short-term relationship between Huixian's methane energy development and GDP by using co-integration test and error correcti...Based on the statistical data of Huixian from 1992 to 2010, we analyze the long-term and short-term relationship between Huixian's methane energy development and GDP by using co-integration test and error correction model. The empirical results show that there is a long-term equilibrium relationship between methane energy and GDP in the city of Huixian, and which is the one-way Granger causality of methane and GDP. In conclusion, the paper puts forward some steps about spurring economic growth, methane development and utilization in Huixian.展开更多
The thesis selects freight volume and passenger capacity from 1978 to 2008 in Zhejiang Province and the total output value of the primary industry as the object of research,uses quantitative method of co-integration a...The thesis selects freight volume and passenger capacity from 1978 to 2008 in Zhejiang Province and the total output value of the primary industry as the object of research,uses quantitative method of co-integration analysis to analyze the freight volume and passenger capacity,and the total output value of the primary industry in Zhejiang Province.After the stationary test of the time sequence,I conduct the regression analysis of the relationship between freight volume and the total output value of agriculture,and the relationship between passenger capacity and the total output value of agriculture.In addition,I conduct Granger causality test of the relationship between freight volume and passenger capacity,and the total output value of agriculture.The results show that the transportation of Zhejiang Province has promoted the development of agricultural economy prominently,and the development of agricultural economy plays indistinctive role in promoting the transportation volume in Zhejiang Province.展开更多
This article describes a study by co-integration test and Granger causality test on the relationships between China's services trades and employment using the data of services trade from the WTO website and the em...This article describes a study by co-integration test and Granger causality test on the relationships between China's services trades and employment using the data of services trade from the WTO website and the employment data from China Statistic Yearbook for the years from 1982 to 2003. Co-integration test showed that 1% increase in export value and import value of services created respectively 0.205% and 0.068 7% more job opportunities in the service sector. Both export and import of services impacted positively on employment in service industry, and export did more than import. However, in the short run, the impacts of services export and import on employment in service industry were both very small, though positive; and the impacts of employment in service industry on both export and import of services were very big, but not stable. Granger causality test indicated that employment in service industry was a Granger cause of services export. The findings highlight the importance of facilitating services import and reducing import barriers, and suggest that the competitiveness of China's labor- intensive services trade can be exploited to boost services export and help employment in service sector, and that the structure of services trade should be optimized by shifting from labor-intensive to knowledge-and technology-intensive services thus to enhance China's competitiveness of services export.展开更多
A vector autoregressive model was developed for a sample of container carrier time charter rates. Although the series of time charter rates are themselves found non-stationary, thus precluding the use of many modeling...A vector autoregressive model was developed for a sample of container carrier time charter rates. Although the series of time charter rates are themselves found non-stationary, thus precluding the use of many modeling methodologies, evidence provided by co-integration tests points to the existence of stable long-term relationships between the series. An assessment of the forecasts derived from the model suggests that the spec-ification of these long-term relationships does not improve the accuracy of long-term forecasts. These results are interpreted as a corroboration of the efficient market hypothesis.展开更多
In accordance with the economic data from Statistical Communique on National Economy and Social Development in Hubei Province in the period 1980-2009,we use co-integration analysis method to research the impact of GDP...In accordance with the economic data from Statistical Communique on National Economy and Social Development in Hubei Province in the period 1980-2009,we use co-integration analysis method to research the impact of GDP growth on residents'consumer spending.Result shows that although there are differences between GDP and residents'consumer spending in the short term,the equilibrium relationship exists between them,namely,the co-integration relationship,showing consistency in trends.展开更多
Koyna region, a seismically active region, has many time series observations such as seismicity, reservoir water levels, and many bore well water levels. One of these series is used to predict others since these param...Koyna region, a seismically active region, has many time series observations such as seismicity, reservoir water levels, and many bore well water levels. One of these series is used to predict others since these parameters are interlinked. If these series were stationary, we used correlation analysis. However, it is seen that maximum of these time series are nonstationary. In this case, co-integration method is used that is extracted from econometrics and forecast is possible. We have applied this methodology to study time series of reservoir water levels of this region and we find them to be co-integrated. Therefore, forecast of water levels for one of the reservoir is done from the other as these will never drift apart too much. The outcomes demonstrate that a joint modelling of both data sets based on underlying physics resolves to be sparingly useful for understanding predictability issues in reservoir induced seismicity.展开更多
By applying co-integration analysis,the Granger causality test and an error correction model,the dependency between the energy consumption and the gross domestic product of China was examined.In a further step an anal...By applying co-integration analysis,the Granger causality test and an error correction model,the dependency between the energy consumption and the gross domestic product of China was examined.In a further step an analysis was done to establish a correlation between the economic growth of different industries and China's energy consumption.An evidence-based study showed that a co-integration relationship exists between the gross energy consumption and the GDP of China and that the two variables possess bi-directional causality.The energy consumption for the secondary industry has a markedly stimulative effect to the economic growth.This paper also uses an error correction model(ECM)to explain the short-term behavior of energy demands.展开更多
The purpose of this paper is to puts forward suggestions for the sustainable development of mineral resources by combining the benefit of economy from mineral resources with the introduction of concept of circular eco...The purpose of this paper is to puts forward suggestions for the sustainable development of mineral resources by combining the benefit of economy from mineral resources with the introduction of concept of circular economic development.展开更多
Objective To study the possible relationship between the output of new products in China’s pharmaceutical industry and the investment in research and development(R&D),and to provide a theoretical basis for the de...Objective To study the possible relationship between the output of new products in China’s pharmaceutical industry and the investment in research and development(R&D),and to provide a theoretical basis for the decision-making of relevant enterprises and institutions.Methods The econometric software Stata 14 was used to perform unit root test on the relevant data.Then,a co-integration regression equation was established after stabilization,which was analyzed through co-integration test(E-G two-step method).Results and Conclusion There is a long-term equilibrium and short-term error correction relationship between the output of new products and the investment of R&D funds in China’s pharmaceutical industry.During the lagging periods from 1 to 6,R&D investment is the Granger reason for the output of new products.The investment of R&D funds has a positive effect on the output of new products and the effect is significant.Therefore,more investment should be made in R&D to enhance the output of new products.展开更多
Memristors have a synapse-like two-terminal structure and electrical properties,which are widely used in the construc-tion of artificial synapses.However,compared to inorganic materials,organic materials are rarely us...Memristors have a synapse-like two-terminal structure and electrical properties,which are widely used in the construc-tion of artificial synapses.However,compared to inorganic materials,organic materials are rarely used for artificial spiking synapses due to their relatively poor memrisitve performance.Here,for the first time,we present an organic memristor based on an electropolymerized dopamine-based memristive layer.This polydopamine-based memristor demonstrates the improve-ments in key performance,including a low threshold voltage of 0.3 V,a thin thickness of 16 nm,and a high parasitic capaci-tance of about 1μF·mm^(-2).By leveraging these properties in combination with its stable threshold switching behavior,we con-struct a capacitor-free and low-power artificial spiking neuron capable of outputting the oscillation voltage,whose spiking fre-quency increases with the increase of current stimulation analogous to a biological neuron.The experimental results indicate that our artificial spiking neuron holds potential for applications in neuromorphic computing and systems.展开更多
With the increasing popularity of blockchain applications, the security of data sources on the blockchain is gradually receiving attention. Providing reliable data for the blockchain safely and efficiently has become ...With the increasing popularity of blockchain applications, the security of data sources on the blockchain is gradually receiving attention. Providing reliable data for the blockchain safely and efficiently has become a research hotspot, and the security of the oracle responsible for providing reliable data has attracted much attention. The most widely used centralized oracles in blockchain, such as Provable and Town Crier, all rely on a single oracle to obtain data, which suffers from a single point of failure and limits the large-scale development of blockchain. To this end, the distributed oracle scheme is put forward, but the existing distributed oracle schemes such as Chainlink and Augur generally have low execution efficiency and high communication overhead, which leads to their poor applicability. To solve the above problems, this paper proposes a trusted distributed oracle scheme based on a share recovery threshold signature. First, a data verification method of distributed oracles is designed based on threshold signature. By aggregating the signatures of oracles, data from different data sources can be mutually verified, leading to a more efficient data verification and aggregation process. Then, a credibility-based cluster head election algorithm is designed, which reduces the communication overhead by clarifying the function distribution and building a hierarchical structure. Considering the good performance of the BLS threshold signature in large-scale applications, this paper combines it with distributed oracle technology and proposes a BLS threshold signature algorithm that supports share recovery in distributed oracles. The share recovery mechanism enables the proposed scheme to solve the key loss issue, and the setting of the threshold value enables the proposed scheme to complete signature aggregation with only a threshold number of oracles, making the scheme more robust. Finally, experimental results indicate that, by using the threshold signature technology and the cluster head election algorithm, our scheme effectively improves the execution efficiency of oracles and solves the problem of a single point of failure, leading to higher scalability and robustness.展开更多
Objective: To study the relationship between cortical auditory evoked potential (CAEP) thresholds and behavioral thresholds in pediatric populations with sensorineural hearing loss (SNHL). Methods: Fifteen children (m...Objective: To study the relationship between cortical auditory evoked potential (CAEP) thresholds and behavioral thresholds in pediatric populations with sensorineural hearing loss (SNHL). Methods: Fifteen children (mean age 6.8 years) with bilateral SNHL underwent behavioral pure-tone audiometry and CAEP testing at 0.5, 1, 2, and 4 kHz. CAEP thresholds were determined using tone bursts, and correlations between CAEP and pure-tone thresholds were analyzed using Pearson correlation and t-tests. Results: A strong positive correlation was observed between P1 thresholds and behavioral thresholds across all test frequencies: 0.5 kHz (r = 0.765, p Conclusion: The strong correlation between P1 and behavioral thresholds demonstrates the reliability of CAEP testing for estimating auditory thresholds in children. These findings support the use of CAEP testing as a reliable objective tool for threshold estimation, particularly in cases where behavioral responses cannot be reliably obtained. When adjusted with frequency-specific correction values, CAEP testing provides a reliable method for assessing hearing thresholds in pediatric populations.展开更多
To better capture the characteristics of asymmetry and structural fluctuations observed in count time series,this study delves into the application of the quantile regression(QR)method for analyzing and forecasting no...To better capture the characteristics of asymmetry and structural fluctuations observed in count time series,this study delves into the application of the quantile regression(QR)method for analyzing and forecasting nonlinear integer-valued time series exhibiting a piecewise phenomenon.Specifically,we focus on the parameter estimation in the first-order Self-Exciting Threshold Integer-valued Autoregressive(SETINAR(2,1))process with symmetry,asymmetry,and contaminated innovations.We establish the asymptotic properties of the estimator under certain regularity conditions.Monte Carlo simulations demonstrate the superior performance of the QR method compared to the conditional least squares(CLS)approach.Furthermore,we validate the robustness of the proposed method through empirical quantile regression estimation and forecasting for larceny incidents and CAD drug call counts in Pittsburgh,showcasing its effectiveness across diverse levels of data heterogeneity.展开更多
The societal risk related to rainfalltriggered rapid debris flows is commonly managed in urbanized areas by means of early warning systems based on monitoring of hydrological parameters(such as rainfall or soil moistu...The societal risk related to rainfalltriggered rapid debris flows is commonly managed in urbanized areas by means of early warning systems based on monitoring of hydrological parameters(such as rainfall or soil moisture) and thresholds values.In Alpine catchments,this type of landslides is recurrent and represent one of the major geohazards.Debris flows are typically initiated by high-intensity rainstorms,prolonged rainfall with moderate intensity or snow melting.They frequently happen in situations of temporary infiltration into soils that are initially unsaturated.During significant rainfall events,the rise in pore water pressure can become crucial for the stability of slopes in particular areas.This phenomenon relies on hydraulic and geotechnical characteristics,along with the thickness of the involved soils.This procedure can result in a local drop in shear strength,as both apparent cohesion and effective stress decline,while driving forces rise because of the increase in unit weight.Accordingly,this study estimates Intensity-Duration(I-D) rainfall thresholds at the site-specific and distributed scales by combining empirical and physics-based approaches and modeling of soil coverings involved in soil slips or debris slides inducing debris flows.The approach was tested for mountain slopes of the Valtellina valley(Lombardia region,northern Italy),which suffered several catastrophic landslide events in the last decades.The empirical approach was adopted to reconstruct physics-based slope models of representative source areas of past debris flows events.To such a scope,nonpunctual but distributed data of hydro-mechanical soil properties and thicknesses were considered.Thus,to reconstruct the unsaturated/saturated critical conditions leading the slope instability,a combined hydrological modeling and infinite-slope stability analysis was adopted.This combined hydromechanical numerical model was used to attempt to determine a three-dimensional Intensity-Duration threshold for landslide initiation considering plausible rainfall for the Valtellina valley.Due to the lack of reliable records of past landslide hindering a thorough empirical analysis,the presented approach can be considered as a feasible approach for establishing a warning standard in urbanized areas at risk of shallow landslides triggered by rainfall.Moreover,findings highlight the importance of having access to spatially distributed soil characteristics to define and enhance input data for physics-based modelling.Finally,the proposed approach can aid an early warning system for the onset of shallow landslides by utilizing real-time rainfall monitoring or now-casting through a meteorological radar technique.展开更多
Radio environment plays an important role in radio astronomy observations.Further analysis is needed on the time and intensity distributions of interference signals for long-term radio environment monitoring.Sample va...Radio environment plays an important role in radio astronomy observations.Further analysis is needed on the time and intensity distributions of interference signals for long-term radio environment monitoring.Sample variance is an important estimate of the interference signal decision threshold.Here,we propose an improved algorithm for calculating data sample variance relying on four established statistical methods:the variance of the trimmed data,winsorized sample variance,median absolute deviation,and median of the trimmed data pairwise averaged squares method.The variance and decision threshold in the protected section of the radio astronomy L-band are calculated.Among the four methods,the improved median of the trimmed data pairwise averaged squares algorithm has higher accuracy,but in a comparison of overall experimental results,the cleanliness rate of all algorithms is above 96%.In a comparison between the improved algorithm and the four methods,the cleanliness rate of the improved algorithm is above 98%,verifying its feasibility.The time-intensity interference distribution in the radio protection band is also obtained.Finally,we use comprehensive monitoring data of radio astronomy protection bands,radio interference bands,and interfered frequency bands to establish a comprehensive evaluation system for radio observatory sites,including the observable time proportion in the radio astronomy protection band,the occasional time-intensity distribution in the radio interference frequency band,and the intensity distribution of the interfered frequency band.展开更多
Low-pressure mercury lamps,with a main emission of about 254 nm,have been used for disinfecting air,water and surfaces for nearly a century.However,only a few studies on the corneal damage threshold at the wavelength ...Low-pressure mercury lamps,with a main emission of about 254 nm,have been used for disinfecting air,water and surfaces for nearly a century.However,only a few studies on the corneal damage threshold at the wavelength of 254nm exist.In this paper,the in vivo corneal damage threshold was determined inchinchilla rabbit model using a laser system at 254 nm.The irradiance of the laser spot was nearly flat-top distributed and the beam diameter on the animal corneal surface was about 3.44mm and 3.28 mm along the horizontal and vertical directions.Damage lesion determinations were performed at 12 h post-exposure using fluorescein sodium staining.TheED50 was17.7 mJ/cm^(2)with a 95%confidence interval of 15.3-20.1 mJ/cm^(2).The obtained results may contribute to the knowledge base for the refinement of the UV hazard function.展开更多
Atmospheric aerosols are the primary contributors to environmental pollution.As such aerosols are micro-to nanosized particles invisible to the naked eye,it is necessary to utilize LiDAR technology for their detection...Atmospheric aerosols are the primary contributors to environmental pollution.As such aerosols are micro-to nanosized particles invisible to the naked eye,it is necessary to utilize LiDAR technology for their detection.The laser radar echo signal is vulnerable to background light and electronic thermal noise.While single-photon LiDAR can effectively reduce background light interference,electronic thermal noise remains a significant challenge,especially at long distances and in environments with a low signal-to-noise ratio(SNR).However,conventional denoising methods cannot achieve satisfactory results in this case.In this paper,a novel adaptive continuous threshold wavelet denoising algorithm is proposed to filter out the noise.The algorithm features an adaptive threshold and a continuous threshold function.The adaptive threshold is dynamically adjusted according to the wavelet decomposition level,and the continuous threshold function ensures continuity with lower constant error,thus optimizing the denoising process.Simulation results show that the proposed algorithm has excellent performance in improving SNR and reducing root mean square error(RMSE)compared with other algorithms.Experimental results show that denoising of an actual LiDAR echo signal results in a 4.37 dB improvement in SNR and a 39.5%reduction in RMSE.The proposed method significantly enhances the ability of single-photon LiDAR to detect weak signals.展开更多
A clock bias data processing method based on interval correlation coefficient wavelet threshold denoising is suggested for minor mistakes in clock bias data in order to increase the efficacy of satellite clock bias pr...A clock bias data processing method based on interval correlation coefficient wavelet threshold denoising is suggested for minor mistakes in clock bias data in order to increase the efficacy of satellite clock bias prediction.Wavelet analysis was first used to break down the satellite clock frequency data into several levels,producing high and low frequency coefficients for each layer.The correlation coefficients of the high and low frequency coefficients in each of the three sub-intervals created by splitting these coefficients were then determined.The major noise region—the sub-interval with the lowest correlation coefficient—was chosen for thresholding treatment and noise threshold computation.The clock frequency data was then processed using wavelet reconstruction and reconverted to clock data.Lastly,three different kinds of satellite clock data—RTS,whu-o,and IGS-F—were used to confirm the produced data.Our method enhanced the stability of the Quadratic Polynomial(QP)model’s predictions for the C16 satellite by about 40%,according to the results.The accuracy and stability of the Auto Regression Integrated Moving Average(ARIMA)model improved up to 41.8%and 14.2%,respectively,whilst the Wavelet Neural Network(WNN)model improved by roughly 27.8%and 63.6%,respectively.Although our method has little effect on forecasting IGS-F series satellites,the experimental findings show that it can improve the accuracy and stability of QP,ARIMA,and WNN model forecasts for RTS and whu-o satellite clock bias.展开更多
In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This...In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper.展开更多
基金The National Natural Science Foundation of China(No50278017)
文摘A kind of method of modal identification subject to ambient excitation is presented. A new synthesis stationary signal based on structural response wavelet transform and wavelet coefficient processes co-integration is obtained. The new signal instead of structural response is used in identifying the modal parameters of a non- stationary system, combined with the method of modal identification under stationary random excitation-the NExT method and the adjusted continuous least square method. The numerical results show that the method can eliminate the non-stationarity of structural response subject to non-stationary random excitation to a great extent, and is highly precise and robust.
文摘Based on the statistical data of Huixian from 1992 to 2010, we analyze the long-term and short-term relationship between Huixian's methane energy development and GDP by using co-integration test and error correction model. The empirical results show that there is a long-term equilibrium relationship between methane energy and GDP in the city of Huixian, and which is the one-way Granger causality of methane and GDP. In conclusion, the paper puts forward some steps about spurring economic growth, methane development and utilization in Huixian.
基金Supported by the Program of Characteristic Major(International Economy and Trade)of Zhejiang Province in the Year 2009(TZZ09084)
文摘The thesis selects freight volume and passenger capacity from 1978 to 2008 in Zhejiang Province and the total output value of the primary industry as the object of research,uses quantitative method of co-integration analysis to analyze the freight volume and passenger capacity,and the total output value of the primary industry in Zhejiang Province.After the stationary test of the time sequence,I conduct the regression analysis of the relationship between freight volume and the total output value of agriculture,and the relationship between passenger capacity and the total output value of agriculture.In addition,I conduct Granger causality test of the relationship between freight volume and passenger capacity,and the total output value of agriculture.The results show that the transportation of Zhejiang Province has promoted the development of agricultural economy prominently,and the development of agricultural economy plays indistinctive role in promoting the transportation volume in Zhejiang Province.
文摘This article describes a study by co-integration test and Granger causality test on the relationships between China's services trades and employment using the data of services trade from the WTO website and the employment data from China Statistic Yearbook for the years from 1982 to 2003. Co-integration test showed that 1% increase in export value and import value of services created respectively 0.205% and 0.068 7% more job opportunities in the service sector. Both export and import of services impacted positively on employment in service industry, and export did more than import. However, in the short run, the impacts of services export and import on employment in service industry were both very small, though positive; and the impacts of employment in service industry on both export and import of services were very big, but not stable. Granger causality test indicated that employment in service industry was a Granger cause of services export. The findings highlight the importance of facilitating services import and reducing import barriers, and suggest that the competitiveness of China's labor- intensive services trade can be exploited to boost services export and help employment in service sector, and that the structure of services trade should be optimized by shifting from labor-intensive to knowledge-and technology-intensive services thus to enhance China's competitiveness of services export.
文摘A vector autoregressive model was developed for a sample of container carrier time charter rates. Although the series of time charter rates are themselves found non-stationary, thus precluding the use of many modeling methodologies, evidence provided by co-integration tests points to the existence of stable long-term relationships between the series. An assessment of the forecasts derived from the model suggests that the spec-ification of these long-term relationships does not improve the accuracy of long-term forecasts. These results are interpreted as a corroboration of the efficient market hypothesis.
基金Supported by National Natural Science Foundation(60873021/F0201)
文摘In accordance with the economic data from Statistical Communique on National Economy and Social Development in Hubei Province in the period 1980-2009,we use co-integration analysis method to research the impact of GDP growth on residents'consumer spending.Result shows that although there are differences between GDP and residents'consumer spending in the short term,the equilibrium relationship exists between them,namely,the co-integration relationship,showing consistency in trends.
文摘Koyna region, a seismically active region, has many time series observations such as seismicity, reservoir water levels, and many bore well water levels. One of these series is used to predict others since these parameters are interlinked. If these series were stationary, we used correlation analysis. However, it is seen that maximum of these time series are nonstationary. In this case, co-integration method is used that is extracted from econometrics and forecast is possible. We have applied this methodology to study time series of reservoir water levels of this region and we find them to be co-integrated. Therefore, forecast of water levels for one of the reservoir is done from the other as these will never drift apart too much. The outcomes demonstrate that a joint modelling of both data sets based on underlying physics resolves to be sparingly useful for understanding predictability issues in reservoir induced seismicity.
基金Projects TSFZLXKF2006-3 supported by the China Lixin Risk Management Research Institute Foundation of Shanghai Municipal Education Commission90210035 by the National Natural Science Foundation of China
文摘By applying co-integration analysis,the Granger causality test and an error correction model,the dependency between the energy consumption and the gross domestic product of China was examined.In a further step an analysis was done to establish a correlation between the economic growth of different industries and China's energy consumption.An evidence-based study showed that a co-integration relationship exists between the gross energy consumption and the GDP of China and that the two variables possess bi-directional causality.The energy consumption for the secondary industry has a markedly stimulative effect to the economic growth.This paper also uses an error correction model(ECM)to explain the short-term behavior of energy demands.
文摘The purpose of this paper is to puts forward suggestions for the sustainable development of mineral resources by combining the benefit of economy from mineral resources with the introduction of concept of circular economic development.
基金Research on Innovation and Development Strategy of Pharmaceutical Industry in Liaoning Province(2020lslktyb-095).
文摘Objective To study the possible relationship between the output of new products in China’s pharmaceutical industry and the investment in research and development(R&D),and to provide a theoretical basis for the decision-making of relevant enterprises and institutions.Methods The econometric software Stata 14 was used to perform unit root test on the relevant data.Then,a co-integration regression equation was established after stabilization,which was analyzed through co-integration test(E-G two-step method).Results and Conclusion There is a long-term equilibrium and short-term error correction relationship between the output of new products and the investment of R&D funds in China’s pharmaceutical industry.During the lagging periods from 1 to 6,R&D investment is the Granger reason for the output of new products.The investment of R&D funds has a positive effect on the output of new products and the effect is significant.Therefore,more investment should be made in R&D to enhance the output of new products.
基金support from the Beijing Natural Science Foundation-Xiaomi Innovation Joint Fund(No.L233009)National Natural Science Foundation of China(NSFC Nos.62422409,62174152,and 62374159)from the Youth Innovation Promotion Association of Chinese Academy of Sciences(No.2020115).
文摘Memristors have a synapse-like two-terminal structure and electrical properties,which are widely used in the construc-tion of artificial synapses.However,compared to inorganic materials,organic materials are rarely used for artificial spiking synapses due to their relatively poor memrisitve performance.Here,for the first time,we present an organic memristor based on an electropolymerized dopamine-based memristive layer.This polydopamine-based memristor demonstrates the improve-ments in key performance,including a low threshold voltage of 0.3 V,a thin thickness of 16 nm,and a high parasitic capaci-tance of about 1μF·mm^(-2).By leveraging these properties in combination with its stable threshold switching behavior,we con-struct a capacitor-free and low-power artificial spiking neuron capable of outputting the oscillation voltage,whose spiking fre-quency increases with the increase of current stimulation analogous to a biological neuron.The experimental results indicate that our artificial spiking neuron holds potential for applications in neuromorphic computing and systems.
基金supported by the National Natural Science Foundation of China(Grant No.62102449)the Central Plains Talent Program under Grant No.224200510003.
文摘With the increasing popularity of blockchain applications, the security of data sources on the blockchain is gradually receiving attention. Providing reliable data for the blockchain safely and efficiently has become a research hotspot, and the security of the oracle responsible for providing reliable data has attracted much attention. The most widely used centralized oracles in blockchain, such as Provable and Town Crier, all rely on a single oracle to obtain data, which suffers from a single point of failure and limits the large-scale development of blockchain. To this end, the distributed oracle scheme is put forward, but the existing distributed oracle schemes such as Chainlink and Augur generally have low execution efficiency and high communication overhead, which leads to their poor applicability. To solve the above problems, this paper proposes a trusted distributed oracle scheme based on a share recovery threshold signature. First, a data verification method of distributed oracles is designed based on threshold signature. By aggregating the signatures of oracles, data from different data sources can be mutually verified, leading to a more efficient data verification and aggregation process. Then, a credibility-based cluster head election algorithm is designed, which reduces the communication overhead by clarifying the function distribution and building a hierarchical structure. Considering the good performance of the BLS threshold signature in large-scale applications, this paper combines it with distributed oracle technology and proposes a BLS threshold signature algorithm that supports share recovery in distributed oracles. The share recovery mechanism enables the proposed scheme to solve the key loss issue, and the setting of the threshold value enables the proposed scheme to complete signature aggregation with only a threshold number of oracles, making the scheme more robust. Finally, experimental results indicate that, by using the threshold signature technology and the cluster head election algorithm, our scheme effectively improves the execution efficiency of oracles and solves the problem of a single point of failure, leading to higher scalability and robustness.
文摘Objective: To study the relationship between cortical auditory evoked potential (CAEP) thresholds and behavioral thresholds in pediatric populations with sensorineural hearing loss (SNHL). Methods: Fifteen children (mean age 6.8 years) with bilateral SNHL underwent behavioral pure-tone audiometry and CAEP testing at 0.5, 1, 2, and 4 kHz. CAEP thresholds were determined using tone bursts, and correlations between CAEP and pure-tone thresholds were analyzed using Pearson correlation and t-tests. Results: A strong positive correlation was observed between P1 thresholds and behavioral thresholds across all test frequencies: 0.5 kHz (r = 0.765, p Conclusion: The strong correlation between P1 and behavioral thresholds demonstrates the reliability of CAEP testing for estimating auditory thresholds in children. These findings support the use of CAEP testing as a reliable objective tool for threshold estimation, particularly in cases where behavioral responses cannot be reliably obtained. When adjusted with frequency-specific correction values, CAEP testing provides a reliable method for assessing hearing thresholds in pediatric populations.
基金supported by Social Science Planning Foundation of Liaoning Province(Grand No.L22ZD065)National Natural Science Foundation of China(Grand Nos.12271231,1247012719,12001229)。
文摘To better capture the characteristics of asymmetry and structural fluctuations observed in count time series,this study delves into the application of the quantile regression(QR)method for analyzing and forecasting nonlinear integer-valued time series exhibiting a piecewise phenomenon.Specifically,we focus on the parameter estimation in the first-order Self-Exciting Threshold Integer-valued Autoregressive(SETINAR(2,1))process with symmetry,asymmetry,and contaminated innovations.We establish the asymptotic properties of the estimator under certain regularity conditions.Monte Carlo simulations demonstrate the superior performance of the QR method compared to the conditional least squares(CLS)approach.Furthermore,we validate the robustness of the proposed method through empirical quantile regression estimation and forecasting for larceny incidents and CAD drug call counts in Pittsburgh,showcasing its effectiveness across diverse levels of data heterogeneity.
文摘The societal risk related to rainfalltriggered rapid debris flows is commonly managed in urbanized areas by means of early warning systems based on monitoring of hydrological parameters(such as rainfall or soil moisture) and thresholds values.In Alpine catchments,this type of landslides is recurrent and represent one of the major geohazards.Debris flows are typically initiated by high-intensity rainstorms,prolonged rainfall with moderate intensity or snow melting.They frequently happen in situations of temporary infiltration into soils that are initially unsaturated.During significant rainfall events,the rise in pore water pressure can become crucial for the stability of slopes in particular areas.This phenomenon relies on hydraulic and geotechnical characteristics,along with the thickness of the involved soils.This procedure can result in a local drop in shear strength,as both apparent cohesion and effective stress decline,while driving forces rise because of the increase in unit weight.Accordingly,this study estimates Intensity-Duration(I-D) rainfall thresholds at the site-specific and distributed scales by combining empirical and physics-based approaches and modeling of soil coverings involved in soil slips or debris slides inducing debris flows.The approach was tested for mountain slopes of the Valtellina valley(Lombardia region,northern Italy),which suffered several catastrophic landslide events in the last decades.The empirical approach was adopted to reconstruct physics-based slope models of representative source areas of past debris flows events.To such a scope,nonpunctual but distributed data of hydro-mechanical soil properties and thicknesses were considered.Thus,to reconstruct the unsaturated/saturated critical conditions leading the slope instability,a combined hydrological modeling and infinite-slope stability analysis was adopted.This combined hydromechanical numerical model was used to attempt to determine a three-dimensional Intensity-Duration threshold for landslide initiation considering plausible rainfall for the Valtellina valley.Due to the lack of reliable records of past landslide hindering a thorough empirical analysis,the presented approach can be considered as a feasible approach for establishing a warning standard in urbanized areas at risk of shallow landslides triggered by rainfall.Moreover,findings highlight the importance of having access to spatially distributed soil characteristics to define and enhance input data for physics-based modelling.Finally,the proposed approach can aid an early warning system for the onset of shallow landslides by utilizing real-time rainfall monitoring or now-casting through a meteorological radar technique.
基金supported by the Ministry of Science and Technology SKA Special Project(2020SKA0110202)the Special Project on Building a Science and Technology Innovation Center for South and Southeast Asia-International Joint Innovation Platform in Yunnan Province:“Yunnan Sino-Malaysian International Joint Laboratory of HF-VHF Advanced Radio Astronomy Technology”(202303AP140003)+4 种基金the National Natural Science Foundation of China(NSFC)Joint Fund for Astronomy(JFA)incubator program(U2031133)the International Partnership Program Project of the International Cooperation Bureau of the Chinese Academy of Sciences:“Belt and Road”Cooperation(114A11KYSB20200001)the Kunming Foreign(International)Cooperation Base Program:“Yunnan Observatory of the Chinese Academy of Sciences-University of Malaya Joint R&D Cooperation Base for Advanced Radio Astronomy Technology”(GHJD-2021022)the China-Malaysia Collaborative Research on Space Remote Sensing and Radio Astronomy Observation of Space Weather at Low and Middle Latitudes under the Key Special Project of the State Key R&D Program of the Ministry of Science and Technol ogy for International Cooperation in Science,Technology and Innovation among Governments(2022YFE0140000)the High-precision calibration method for low-frequency radio interferometric arrays for the SKA project of the Ministry of Science and Technology(2020SKA0110300).
文摘Radio environment plays an important role in radio astronomy observations.Further analysis is needed on the time and intensity distributions of interference signals for long-term radio environment monitoring.Sample variance is an important estimate of the interference signal decision threshold.Here,we propose an improved algorithm for calculating data sample variance relying on four established statistical methods:the variance of the trimmed data,winsorized sample variance,median absolute deviation,and median of the trimmed data pairwise averaged squares method.The variance and decision threshold in the protected section of the radio astronomy L-band are calculated.Among the four methods,the improved median of the trimmed data pairwise averaged squares algorithm has higher accuracy,but in a comparison of overall experimental results,the cleanliness rate of all algorithms is above 96%.In a comparison between the improved algorithm and the four methods,the cleanliness rate of the improved algorithm is above 98%,verifying its feasibility.The time-intensity interference distribution in the radio protection band is also obtained.Finally,we use comprehensive monitoring data of radio astronomy protection bands,radio interference bands,and interfered frequency bands to establish a comprehensive evaluation system for radio observatory sites,including the observable time proportion in the radio astronomy protection band,the occasional time-intensity distribution in the radio interference frequency band,and the intensity distribution of the interfered frequency band.
基金supported by the National Natural Science Foundation of China(No.61575221).
文摘Low-pressure mercury lamps,with a main emission of about 254 nm,have been used for disinfecting air,water and surfaces for nearly a century.However,only a few studies on the corneal damage threshold at the wavelength of 254nm exist.In this paper,the in vivo corneal damage threshold was determined inchinchilla rabbit model using a laser system at 254 nm.The irradiance of the laser spot was nearly flat-top distributed and the beam diameter on the animal corneal surface was about 3.44mm and 3.28 mm along the horizontal and vertical directions.Damage lesion determinations were performed at 12 h post-exposure using fluorescein sodium staining.TheED50 was17.7 mJ/cm^(2)with a 95%confidence interval of 15.3-20.1 mJ/cm^(2).The obtained results may contribute to the knowledge base for the refinement of the UV hazard function.
基金funded by the National Key R&D Program of China(Grant No.2022YFC3300705)the National Natural Science Foundation of China(Grant Nos.62203056,12202048,and 62201056).
文摘Atmospheric aerosols are the primary contributors to environmental pollution.As such aerosols are micro-to nanosized particles invisible to the naked eye,it is necessary to utilize LiDAR technology for their detection.The laser radar echo signal is vulnerable to background light and electronic thermal noise.While single-photon LiDAR can effectively reduce background light interference,electronic thermal noise remains a significant challenge,especially at long distances and in environments with a low signal-to-noise ratio(SNR).However,conventional denoising methods cannot achieve satisfactory results in this case.In this paper,a novel adaptive continuous threshold wavelet denoising algorithm is proposed to filter out the noise.The algorithm features an adaptive threshold and a continuous threshold function.The adaptive threshold is dynamically adjusted according to the wavelet decomposition level,and the continuous threshold function ensures continuity with lower constant error,thus optimizing the denoising process.Simulation results show that the proposed algorithm has excellent performance in improving SNR and reducing root mean square error(RMSE)compared with other algorithms.Experimental results show that denoising of an actual LiDAR echo signal results in a 4.37 dB improvement in SNR and a 39.5%reduction in RMSE.The proposed method significantly enhances the ability of single-photon LiDAR to detect weak signals.
基金2023 Liaoning Institute of Science and Technology Doctoral Program Launch fund(No.2307B29).
文摘A clock bias data processing method based on interval correlation coefficient wavelet threshold denoising is suggested for minor mistakes in clock bias data in order to increase the efficacy of satellite clock bias prediction.Wavelet analysis was first used to break down the satellite clock frequency data into several levels,producing high and low frequency coefficients for each layer.The correlation coefficients of the high and low frequency coefficients in each of the three sub-intervals created by splitting these coefficients were then determined.The major noise region—the sub-interval with the lowest correlation coefficient—was chosen for thresholding treatment and noise threshold computation.The clock frequency data was then processed using wavelet reconstruction and reconverted to clock data.Lastly,three different kinds of satellite clock data—RTS,whu-o,and IGS-F—were used to confirm the produced data.Our method enhanced the stability of the Quadratic Polynomial(QP)model’s predictions for the C16 satellite by about 40%,according to the results.The accuracy and stability of the Auto Regression Integrated Moving Average(ARIMA)model improved up to 41.8%and 14.2%,respectively,whilst the Wavelet Neural Network(WNN)model improved by roughly 27.8%and 63.6%,respectively.Although our method has little effect on forecasting IGS-F series satellites,the experimental findings show that it can improve the accuracy and stability of QP,ARIMA,and WNN model forecasts for RTS and whu-o satellite clock bias.
基金Supported by the Natural Science Foundation of Fujian Province(2022J011177,2024J01903)the Key Project of Fujian Provincial Education Department(JZ230054)。
文摘In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper.
