Double Threshold Research Articles

R&D investment and regional innovation performance – threshold effects based on intellectual property protection

ABSTRACT Based on the panel data of 24 provinces and cities in China from 2009 to 2017, this paper uses panel threshold regression model with regional intellectual property protection intensity as the threshold variable to investigate the effect of R&D investment on regional innovation performance from two perspectives of human resource investment and R&D funding investment with different threshold effects. The results show that human resource investment and R&D investment have a significant contribution to regional innovation performance with a lag of three periods, and there is a significant double threshold effect. The optimal intellectual property protection intensity range of human resource input on regional innovation performance promotion is (0.8698, 0.8712). The optimal intellectual property protection intensity range for R&D investment on regional innovation performance is (0.8698, 0.8781), and R&D investment on regional innovation performance shows an increasing and then decreasing effect. This paper constructs a system of indicators to measure the intensity of intellectual property protection in China based on the “dual-track parallelism” of intellectual property protection management in China. It also measures the intensity of intellectual property protection in each region of China. A non-linear relationship between R&D investment, intellectual property protection and regional innovation is found.

Energy internet, digital economy, and green economic growth: Evidence from China

Taking the data of 30 provinces in China from 2006 to 2018, the spatial dynamic Durbin model is applied to exploit the influence of energy internet (EI) and digital economy (DE) on green economic growth (GEG). This paper confirms that: Not only does the GEG in the previous phase significantly contributes to the GEG in the subsequent phase, but the GEG in the local region also significantly contributes to the GEG in the adjacent area. EI and DE can significantly promote GEG, and their interaction term has a positive effect on GEG. A significant non-linear nexus is observed for the influence of the EI and the DE on GEG. Specifically, the impact of the EI on GEG is characterized by a non-linear single threshold with increasing positive marginal effects, while the impact of the DE on GEG is characterized by a non-linear double threshold that first inhibits and then promotes GEG.

Threshold Effect of Two-Way FDI Synergy on Regional Green Technology Innovation under Heterogeneous Environmental Regulation: Evidence from China’s Provincial Panel Data

The green technology innovation system is a fundamental method for China to achieve its goals of carbon peak and carbon neutrality. Clarifying the relationship between two-way foreign direct investment (FDI) synergy and regional green technology innovation is key to the green transformation and sustainable development of regional innovation systems. Based on panel data from 30 provinces in China from 2009 to 2020, a threshold-panel-regression technique is used. Command-controlled environmental regulation (CER), market-incentive environmental regulation (MER), and public-participation environmental regulation (PER) are taken as threshold variables, and the threshold effect of two-way FDI synergy on regional green technology innovation under heterogeneous environmental regulation is empirically explored. The results show the following. (i) The effects of two-way FDI synergy on regional green technology innovation exhibit significant threshold characteristics with heterogeneous environmental regulation as a double threshold. (ii) As the threshold values of CER and PER increase, the promoting effect of two-way FDI synergy on regional green technology innovation first increases and then decreases. (iii) As the MER threshold value increases, the promoting effect of two-way FDI synergy on regional green technology innovation continues to increase. (iv) Under the medium-threshold condition of PER, the promoting effect of two-way FDI synergy reaches its greatest value. (v) The intensity of intellectual property protection, the number of regional innovation institutions, and the level of transportation infrastructure all have significant positive effects on regional green technology innovation, and the number of regional innovation institutions exhibits the greatest promoting effect. This study provides new insights into two-way FDI synergy and methods to promote green technology innovation, and these findings can help the government formulate future policies and strategies to promote regional green technology innovation.

Getting rid of 'rain' and 'stars': Mitigating inhibition effects on ddPCR data analysis, the case study of the invasive crayfish Pacifastacus leniusculus in the streams of Luxembourg.

ddPCR is becoming one of the most widely used tool in the field of eDNA-based aquatic monitoring. Although emulsion PCR used in ddPCR confers a partial mitigation to inhibition due to the high number of reactions for a single sample (between 10K and 20K), it is not impervious to it. Our results showed that inhibition impacts the amplitude of fluorescence in positive droplets with a different intensity among rivers. This signal fluctuation could jeopardize the use of a shared threshold among samples from different origin, and thus the accurate assignment of the positive droplets which is particularly important for low concentration samples such as eDNA ones: amplification events are scarce, thus their objective discrimination as positive is crucial. Another issue, related to target low concentration, is the artifactual generation of high fluorescence droplets ('stars'). Indeed, these could be counted as positive with a single threshold solution, which in turn could produce false positive and incorrect target concentration assessments. Approximating the positive and negative droplets distribution as normal, we proposed here a double threshold method accounting for both high fluorescence droplets ('stars') and PCR inhibition impact in delineating positive droplets clouds. In the context of low concentration template recovered from environmental samples, the application of this method of double threshold establishment could allow for a consistent sorting of the positive and negative droplets throughout ddPCR data generated from samples with varying levels of inhibitor contents. Due to low concentrations template and inhibition effects, Quantasoft software produced an important number of false negatives and positive comparatively to the double threshold method developed here. This case study allowed the detection of the invasive crayfish P. leniusculus in 32 out of 34 sampled sites from two main rivers (Alzette and Sûre) and five of their tributaries (Eisch, Attert, Mamer, Wiltz and Clerve).

The Impact of the Digital Economy on Innovation: New Evidence from Panel Threshold Model

The digital economy has aroused widespread concern. This paper studies the impact of the digital economy on innovation using a panel threshold model. Taking 30 provinces, municipalities, and autonomous regions in China as the research object, the time span is from 2013 to 2019. The data are from the National Bureau of Statistics of China (NBSC), China National Intellectual Property Administration (CAIPA), the China Stock Market and Accounting Research (CSMAR), and the Ministry of Industry and Information Technology (MIIT)of China. Data analysis is performed with ArcGIS 10.2 and STATA 16 software. The influence mechanism of digital economy on innovation is innovatively analyzed from the aspects of innovation elements, innovation tools, innovation subjects, and innovation environment. A digital economy development level index system is constructed using the entropy method, and the development level of China’s digital economy in time and space is analyzed. On this basis, the nonlinear impact of digital economy on innovation, i.e., the threshold effect, is innovatively studied using the panel threshold model. It is found that China’s digital economy develops rapidly, but there is a serious spatial imbalance, and there are great differences in the different dimensions of the digital economy. At the same time, the impact of digital economy on innovation has a double threshold effect with industrial structure as the threshold variable and a single threshold effect with urbanization level as the threshold variable. Specifically, the promoting effect of digital economy on innovation increases with the optimization of industrial structure or the improvement of urbanization level. This study enriches the theoretical research on the impact of digital economy on innovation, and it has important support and reference value for China’s development of digital economy and improvement of innovation capacity.

Does haze aggravate urban sprawl?

Urban sprawl is becoming increasingly serious in China. Existing studies have rarely analysed its causes from the perspective of environmental change. This study investigates the impact of air pollution on urban sprawl. On the basis of the panel data of China's prefecture-level cities, an empirical test is conducted. Results indicate that in every 1% increase of PM2.5, urban sprawl increases by 0.484. The influence path result shows that air pollution aggravates urban sprawl by inducing discrete industrial distribution and decreasing labour supply, stimulating real estate developers' investment and land finance. Air pollution also inhibits urban sprawl by forcing industrial upgrading and increasing resident health demand. In addition, air pollution has a double threshold effect on urban sprawl, has no obvious effect on urban sprawl when the PM2.5 index is lower than 57.74, inhibits urban sprawl when PM2.5 is 57.74–86.8 and aggravates urban sprawl when PM2.5 is higher than 86.8. Moreover, air pollution has a spatial spillover effect on the urban sprawl of surrounding cities. As the distance between two cities is within 200 km, air pollution has a positive spillover effect; otherwise, it has a negative one. The conclusions are expected to provide suggestions on pollution control for restraining urban sprawl.

The Impact of Scientific and Technological Innovation on High-Quality Economic Development in the Yangtze River Delta Region

According to the new development pattern, implementing the development strategy driven by scientific and technological innovation (STI) is an important measure for each region to improve the quality of regional economic development. Exploring the effect of STI on the regional high-quality economic development (HED) is helpful to break the bottleneck and enhance the momentum of regional economic development. The Yangtze River Delta, located in the east coast of China, is the frontier of STI and economic development. Based on theoretical analysis, this paper uses the entropy method to calculate the STI index of the Yangtze River Delta from 2009 to 2018, and systematically investigates the impact of STI on HED in Yangtze River Delta by using two-way fixed effect, spatial Dubin model, panel threshold model and moderation effect model. The research finds that: First, under the control of other factors, STI has significantly promoted the HED of Yangtze River Delta region, while it also produces a spatial spillover effect. Second, the impact of STI on HED in the Yangtze River Delta has a double threshold effect based on the advanced industrial structure. Third, the analysis of adjustment mechanism shows that the scale of higher education has a positive adjustment effect in the relationship between STI and HED. Fourth, with the further analysis of regional heterogeneity, the economic effect of STI in central cities is significantly greater than that in noncentral cities. These findings provide theory-based direction and policy inspiration for improving the institutional mechanism of STI and accelerating the promotion of HED in Yangtze River Delta region.

Bayesian inference for order determination of double threshold variables autoregressive models

Abstract The reversible-jump Markov chain Monte Carlo (RJMCMC) algorithm can generate a jump Markov chain in the parameter space of different dimensions, and select a suitable model effectively. In this paper, when the order of the double threshold variables autoregressive (DT-AR) is unknown, the RJMCMC method is designed to identify the order of the DT-AR model in this paper. The simulation experiments and the real example show that the proposed method works well in identifying the order and estimating the parameters of the DT-AR model simultaneously.

Capitalisation of research and development investment and enterprise value: a study on the threshold effect based on level of financialisation

This study uses a mathematical model to explore how enterprises’ financialisation levels affect the role of research and development (R&D) investment capitalisation in enterprise value. We construct a mathematical model involving the financialisation level, capitalised R&D investment, and enterprise value. The sample comprises A-share listed companies that disclosed the capitalisation of R&D investment in the Shanghai and Shenzhen stock markets from 2014 to 2020. The results suggest that R&D investment capitalisation positively impacts enterprise value, especially in the current phase. With financialisation level as the threshold variable, R&D investment capitalisation has a double threshold effect on enterprise value in the current and next phases. Additionally, corporate financial investment behaviour has a timely impact on capitalised R&D investment but does not significantly impact enterprise value in a future phase. Enterprises evidently choose financial investment to enhance enterprise value by increasing capitalised R&D investment. These results can help enterprises formulate financial asset investment strategies and promote their development from virtual to real. The government should standardise enterprises’ financial investment behaviour, prevent excessive financialisation, and promote high-quality development of the real economy.

A pressure pulse recognition method based on flow-adaptive double threshold for pressure pulse telemetry

Pressure pulse telemetry as a novel and effective method of communication has received more and more attention in the field of separate layer water injection for the intelligent oilfield, and identification of the effective pulses and their positions is one of the key technologies. For the logging while drilling process, the fixed threshold method is widely used to identify the pressure pulse. However, in the process of water injection, the amplitude of pressure pulse changes with the change of flowrate controlled by process, which will lead to low recognition rate of traditional fixed threshold pressure pulse. Therefore, a pressure pulse recognition method based on flow-adaptive double threshold with fixed time window is proposed. The packet length of instructions and responses is designed to be short and fixed in order to reduce communication time and failure cost, and the fixed time window method is adopted to improve the decoding efficiency of for a frame of data. The pressure pulse recognition method based on flow-adaptive double threshold is used to identify the effective pulses and their positions to adapt to the change of pressure pulse amplitude induced by different flowrates. The first threshold which is set to fixed and lower than the pulse peak with minimum possible flowrate, is used to filter the most of noise and catch the effective pulses with little noise pulses. The second threshold which is adaptive to changes of the flowrates, is determined by average of three maximum peaks of caught pulses from the first threshold, and is used to identify the effective pulses and their positions. In the experimental well with 2000 m deep, the test results show that the error rate of pulse recognition reduce to 0.003% and communication success rate significantly increase from 50% to more than 96.5%. It means that the proposed double threshold method can be adaptive to identify effective pressure pulse under different flowrates, and then can significantly reduce the error rate of pulse recognition and improve two-way communication performance between the wellhead controller and downhole distributors.

Evaluating the influencing factors of food imports within belt and road initiatives (BRI) countries: An economic threshold model approach

International food chains and trade usually support many vulnerable and food-insecure developing countries to ensure stable access to food and sufficient resources to maintain and enhance economic growth. However, the smooth transition of uninterrupted food trade and supply is one of the major concerns for almost every country. Based on the economic threshold model grouping tactics, the study evaluates the influencing factors of global food imports and how different countries foster food imports in different conditions. The empirical data has been comprised of panel data from 91 countries along the “Belt and Road” for the last 21 years. The results show that: (i) Population size and arable land endowment have single and double threshold effects on food imports. (ii) Economic development has different effects on the food imports of each group of countries. It has an inverted U-shaped relationship with countries with large populations and high arable land endowments and a “U-shaped relationship” with countries with low arable land endowments. There is a linear relationship between the food imports of countries with small populations and medium arable land endowments, and there is no significant impact on food imports of countries with large populations and medium arable land endowments. (iii) The impact of infrastructure, technological progress, food stocks, and industrial structure on food imports varies from country to country, but tariff policies have no significant impact on food imports. All member countries should utilize the platform of “Belt and Road Initiatives” to capture the resource endowment and exchange associated science and technology of food production, processing, transport, and storage. Food productivity and self-dependency on food should also be increased.

Accelerating efficiency of green technology innovation on carbon mitigation under low-carbon regulation

According to the transaction cost theory for carbon mitigation, green technology innovation must achieve energy conservation and emission reduction through appropriate low-carbon regulation. As a consequence, this study compared the punishment effect of the carbon tax and the reward effect of carbon subsidy on the performance of green technology innovation in China’s provincial industries from 2006 to 2017. We also elucidated that the enterprises’ green technology innovation restricts and stimulates the role of low-carbon regulation on green efficiency in the case of the double threshold effect of carbon dioxide emission. Based on this framework, the integrated tax-subsidy policy for carbon mitigation has a significant differential effect on green efficiency, which changed from an inhibition effect in the high-carbon stage to a promotion effect in the low-carbon stage. And the validity of low-carbon regulations increases with the reduction degree of carbon dioxide emission. But it all depends on whether low-carbon regulations stimulate the enterprises’ willingness to green technology innovation, and whether innovations generate incentives that both increase carbon dioxide emissions and compensate for their innovation cost. Otherwise, enterprise performance should adopt follow strategy more than green technology innovation. Therefore, we further suggested that offsetting the costs of green technology innovation through carbon subsidies would improve the willingness of enterprises to make technological progress and increase the likelihood of carbon reductions which can help the peak in China’s carbon emissions.

The Effects of Tourism Industry Agglomeration on Tourism Environmental Carrying Capacity: Evidence from a Panel Threshold Model

By utilizing the panel data of 26 cities in the Yangtze River Delta urban agglomeration of China from 2000 to 2018, this study constructs a panel threshold model to examine the nonlinear relationship between Tourism Environmental Carrying Capacity (TECC) and Tourism Industry Agglomeration (TIA). TECC is evaluated based on the Driver-Pressure-State-Impact-Response (DPSIR) model, and TIA is estimated by the location quotient index. The analysis reveals that TIA and TECC both show growth trends and significant regional differences among the 26 cities, but the latter fluctuates at certain stages. Moreover, TIA has a significant double threshold effect on TECC, which shows that the positive impact of TIA is enhanced initially but then weakens afterwards. Theoretically, this study contributes to enriching the current literature on TECC from the perspective of TIA. Practically, it could help local governments effectively arrange agglomerations to promote the sustainable development of the tourism industry in China.

Manufacturing agglomeration, urban form, and haze pollution.

Manufacturing agglomeration promotes rapid economic development while also causing severe environmental pollution. This paper investigates the impact and mechanism of manufacturing agglomeration on haze pollution from the Chinese city level. Furthermore, we discuss the moderating effect and threshold effect of the three urban forms of urban external shape complexity, urban compactness, and urban fragmentation on the relationship between the two. The result shows the following: (1) The aggregation of the manufacturing industry presents an inverted U-shaped characteristic of promoting first and then inhibiting haze pollution in China's overall, eastern and central regions. (2) The complexity of the city's external shape and the city's fragmentation has a positive moderating effect on the relationship between manufacturing agglomeration and haze pollution. And urban fragmentation shows a negative moderating effect on the relationship between the two when the level of manufacturing agglomeration is on the right side of the inverted U-shaped curve. (3) The urban form shows a significant double threshold characteristic for haze pollution, increasing the complexity of the city's external shape and the city's fragmentation. The agglomeration of manufacturing shows the characteristics of first inhibiting and then promoting haze pollution. As urban compactness increases, the inhibitory effect of manufacturing agglomeration on haze pollution increases.

Research on the impacts of dual environmental regulation on regional carbon emissions under the goal of carbon neutrality-the intermediary role of green technology innovation

As an important means to promote regional low-carbon development, environmental regulation has great theoretical and practical significance for achieving the goal of carbon-neutral development in China. Based on the panel data of 30 provinces and cities in China from 2005 to 2019, this paper first uses the intermediary effect model to analyze the impact of the implementation of environmental regulation policies on regional carbon emissions, discusses the relationship between environmental regulation, green technology innovation and carbon emissions, and further uses the threshold effect model to discuss the nonlinear relationship between environmental regulation and regional carbon emissions. The results show that: the improvement of formal and informal environmental regulation can play a role in “forced emission reduction”; Green technology innovation plays a complete intermediary role in the impact of environmental regulation on regional carbon emissions; At the same time, the impact of formal and informal environmental regulation on regional carbon emissions has a threshold effect. Among them, formal environmental regulation has a double threshold effect, the threshold values are 0.429 and 0.502 respectively, while informal environmental regulation has a single threshold effect, the threshold value is 1.803. The results of heterogeneity analysis show that there are obvious differences in the implementation effects of environmental regulation policies under different economic development levels and industrialization development stages. Therefore, we should pay attention to the mutual promotion effect of different types of environmental regulation, strengthen the collaborative emission reduction of environmental regulation and green technology innovation, and improve the level of regional green technology innovation, so as to better promote the realization of regional carbon neutrality goals.

The impact of clean energy development on economic growth in China: from the perspectives of environmental regulation.

Given the finite nature of fossil energy and rising environmental pressures, countries are increasing focus on clean energy. By employing provincial panel data from 2003 to 2019 in China, this study sheds light on the effect of clean energy development on economic growth and the role of environmental regulation in the relationship. The study utilized moderating and threshold effect models for empirical estimation. Results show that clean energy development has a positive impact on economic growth in general. In terms of region heterogeneity, the contribution of clean energy development to economic growth is more pronounced in regions with higher levels of economic development. Furthermore, we provide evidence that market-based environmental regulation has a single threshold, which has a positive regulating effect on the relationship between clean energy development and economic growth, while administrative environmental regulation has a double threshold, which has a negative regulating effect on the relationship between the two. The findings of our study provide useful policy directions for maintaining a balance between economic growth and environmental prosperity.

Novel Non-Convex Regularization for Generating Double Threshold Value in Penalized Least Squares Regression

A lot of works in machine learning (ML) usually use components which are built by signal processing, such as wavelet and Fourier coefficients, for computations; therefore, many problems in signal processing affect ML algorithms. Consequently, we try to solve linear inverse problems in signal processing, such as the classical denoising and deconvolution problems, in this work. The penalized least squares regression (PLSR), also called as the proximity operator, of the non-convex regularization, can solve various problems in signal processing. In the classical denoising problem, the PLSR with the double threshold value is more flexible than the PLSR with the single threshold value. Therefore, we propose the novel non-convex regularization which can build the PLSR with the double threshold value. The proposed regularization is based on good properties of the minimax-concave (MC) regularization. We also present novel PLSRs of the MC and proposed regularizations where these PLSRs have closed-form solutions and the relationship to the group of considered components, also known as the multivariate case, together. We compare proposed methods with state-of-the-art methods in the classical denoising and deconvolution problems. Here, we use the majorization-minimization (MM) method for comparing the performance of regularizations in the deconvolution problem. Experimental results show that proposed methods give trustworthy results.

A comparison of single- and double-threshold ROC plots for mixture distributions

The receiver operating characteristics (ROC) analysis is commonly used in clinical settings to check the performance of a single threshold for distinguishing population-wise bimodal-distributed test results. However, for population-wise three-modal distributed test results, a single threshold ROC (stROC) analysis showed poor discriminative performance. The purpose of this study is to use a double-threshold ROC analysis for the three-modal distributed test results to provide better discriminative performance than the stROC analysis. A double-threshold receiver operating characteristic plot (dtROC) is constructed by replacing the single threshold with a double threshold. The sensitivity and specificity coordinates are chosen to maximize sensitivity for a given specificity value. Besides a simulation study assuming a mixture of lognormal, Poisson, and Weibull distributions, a clinical application is examined by a secondary data analysis of palpation test results of the C7 spinous process using the modified thorax–rib static technique. For the assumed mixture models, the discrimination performance of dtROC analysis outperforms the stROC analysis (area under ROC (AUROC) increased from 0.436 to 0.983 for lognormal distributed test results, 0.676 to 0.752 for the Poisson distribution, and 0.674 to 0.804 for Weibull distribution).

Specialization versus diversity: The role of city size in tourist cities

The paper examines the impact of specialization and diversity on economic growth of tourist cities. Industrial diversity is decomposed into two parts, related and unrelated diversity (UV). The paper constructs a panel threshold model with city size as the threshold variable, and empirically tests the nonlinear effects of specialization and diversity on economic growth of tourist cities from the perspective of city size. The results show that: First, tourism specialization has a positive impact on economic growth of tourist cities, and there is a double threshold effect based on city size. When the city size exceeds two thresholds, tourism specialization plays a significant role in promoting economic growth of tourist cities. Second, related diversity (RV) has a positive impact on economic growth of tourist cities, and there is no threshold effect based on city size. Third, the impact of unrelated diversity on economic growth of tourist cities has a single threshold effect based on city size. Specifically, when the city size is lower than the threshold value, unrelated diversity inhibits economic growth of tourist cities. Otherwise, unrelated diversity will promote economic growth of tourist cities. The conclusions are still valid after a series of robustness tests. The paper highlights that local governments of tourist cities should not pursue absolute tourism specialization or industrial diversity, but should design and adjust industrial structure reasonably according to the city size.

Detection of microcracks in silicon solar cells using Otsu-Canny edge detection algorithm

The necessity for photovoltaic (PV) arrays has expanded due to the rising demand for solar electrical energy. The demand for solar cells has grown as they are a key component of the PV array. Recent years have seen a rise in solar cell production as a result of this demand. The quality of a silicon panel affects its lifespan and effectiveness in the production of solar power. The picture edge-detection method is regularly employed to identify silicon solar panel flaws. On the other hand, defect identification is impacted by the panel's grid shadow. The most modern defect detection technique uses artificial neural networks, and pre-training the model requires a large number of potential samples from picture data sets. This paper offers the innovative Otsu-Canny operator method as a fault discovery strategy to address this problem. Rapid and accurate identification of microcracks enhances the effectiveness of fault detection. The Otsu algorithm is used in this method to improve edge detection performance for microcracks by modifying the canny operator with a double threshold and eliminating the impact of grids on detection. The process was finished by performing noise removal with morphological operation, picture segmentation, and image binarization. The experimental findings demonstrate a significant improvement in purity and integrity of the image processing algorithm used in this research. The Otsu-Canny edge detection technique is more accurate than other conventional edge detection algorithms for detecting microcracks, with a 92.83 % detection rate.