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"Wang, Hongpeng"
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Does charitable giving reduce firms’ willingness to invest in green innovation?
While corporate charitable giving(CG) can help firms obtain external innovation resource support, it can also crowd out internal innovation resources. The purpose of this study is to clarify the mechanism of CG and government green subsidies(GS) on green innovation(GI). In this regard, we integrated signaling theory and principal-agent theory to provide a new theoretical perspective for simultaneously focus on the impact of external resource acquisition and internal resource allocation on GI. We conducted a threshold regression analysis on the balanced panel data of 863 listed companies of China from 2016 to 2019 to clarify the input boundary between the promoting and inhibiting effects of corporate CG on corporate GI. And we further explored the relationship between GS and GI under the effect of different CG thresholds. Our findings indicate that there is an inverted U-shaped threshold effect of CG on GI. The impact of GS on GI shows a decreasing marginal benefit as the intensity of CG increases. Based on the findings, we propose corresponding countermeasures for the management of enterprises and the government.
Journal Article
Does charitable giving reduce firms' willingness to invest in green innovation?
While corporate charitable giving(CG) can help firms obtain external innovation resource support, it can also crowd out internal innovation resources. The purpose of this study is to clarify the mechanism of CG and government green subsidies(GS) on green innovation(GI). In this regard, we integrated signaling theory and principal-agent theory to provide a new theoretical perspective for simultaneously focus on the impact of external resource acquisition and internal resource allocation on GI. We conducted a threshold regression analysis on the balanced panel data of 863 listed companies of China from 2016 to 2019 to clarify the input boundary between the promoting and inhibiting effects of corporate CG on corporate GI. And we further explored the relationship between GS and GI under the effect of different CG thresholds. Our findings indicate that there is an inverted U-shaped threshold effect of CG on GI. The impact of GS on GI shows a decreasing marginal benefit as the intensity of CG increases. Based on the findings, we propose corresponding countermeasures for the management of enterprises and the government.
Journal Article
Threshold effects of environmental regulation types on green investment by heavily polluting enterprises
BackgroundIn the stage of sustainable development, enterprises should not only focus on economic efficiency, but also on ecological protection, for which the governments of various countries has adopted various environmental regulation methods to promote green investment by enterprises. However, there are many types of environmental regulations, and the relationship between policy formulation and implementation effects is complicated. Heavily polluting enterprises as the main carrier of resource consumption and pollutant emissions is the main target of environmental regulation. Based on this, we took China's heavily polluting listed companies as examples to explore the impact of different types of environmental regulations on green investment in heavily polluting enterprises.ResultsIn this paper, environmental regulations were divided into formal and informal types, of which formal environmental regulations (FER) were subdivided into command-control and market-incentive types. The empirical results showed that the relationship between command-control environmental regulations and green investment by heavily polluting enterprises presents an inverted “U” shape, and market-incentive environmental regulations first have no effect on and then promote green investment by heavily polluting enterprises. Besides, informal environmental regulations (IER) have maintained a positive effect on green investment by heavily polluting enterprises.ConclusionsHeavily polluting enterprises, respectively, employ passive, active and voluntary green investment strategies under the three types of environmental regulations, providing a reference for the government to promote green investment by enterprises by environmental regulations more effectively.
Journal Article
Identification of the immune-associated enhancer RNA SATB1-AS1 as a novel biomarker for thymic cancer prognosis
To screen key enhancer RNAs (eRNAs) in thymoma (THYM) through The Cancer Genome Atlas (TCGA) database and explore their potential as prognostic molecules and therapeutic targets in THYM.
Gene expression RNA-seq profiles of 33 cancer types were retrieved and downloaded from the TCGA database, and Kaplan-Meier survival analysis and Spearman correlation analysis were applied to screen eRNAs and target genes associated with survival in THYM patients. The correlation of target eRNAs with clinical features was assessed. Gene set enrichment analysis was performed to investigate the potential biological functions of target eRNAs. Finally, the prognostic potential of the eRNA was validated in other cancer types.
In THYM, SATB1-AS1 and the target gene SATB1 high expression were associated with a positive patient prognosis, and SATB1-AS1 expression was negatively correlated with patient stage (P < 0.05). Gene and pathway enrichment analyses revealed that SATB1-AS1 was associated with leukocyte transendothelial migration, natural killer cell-mediated cytotoxicity, neutrophil extracellular trap formation, PD-L1 expression and the PD-1 checkpoint pathway in cancer.
SATB1-AS1 may be a key eRNA in THYM and has the potential to be a marker and therapeutic target for the early diagnosis and prognosis of THYM.
Journal Article
A Review and Perspective of Techniques for Autonomous Robotic Ultrasound Acquisitions
Ultrasound (US) imaging is a widely used diagnostic method in clinics. Real-time-generated US images are used for rapid diagnosis without harm to patients. The quality of US imaging highly depends on the skill of the physician due to the differences among physicians. Techniques for autonomous robotic ultrasound (AU-RUS) acquisitions are expected to become an effective means to improve the level of US diagnosis, reduce the workload of physicians, and improve the standardization of US imaging quality. This paper aims to summarize the current research status of techniques for AU-RUS acquisitions, and to discuss the research trends and challenges regarding related technologies. Firstly, the techniques for AU-RUS acquisitions and systems are outlined. The techniques for teleoperated or autonomous US acquisitions are briefly discussed. Representative RUS acquisition systems are introduced. Then, the current research status of AU-RUS acquisitions is reviewed from four research directions: force sensitivity and control, scanning path-planning and positioning, US treatment guidance, and US image processing technology and quality assessment optimization. This review provides a decision-oriented autonomy perspective by mapping typical methods to workflow components across the stages of perception, decision-making, and execution. We identify major deployment bottlenecks, including safety-verifiable autonomy and failure recovery, motion compensation under deformation, and the lack of standardized, clinically meaningful US image quality metrics. Finally, the shortcomings of current research are summarized and analyzed, and the research trends and challenges for AU-RUS acquisitions are prospected.
Journal Article
The Detection of Yarn Roll’s Margin in Complex Background
Online detection of yarn roll’s margin is one of the key issues in textile automation, which is related to the speed and scheduling of bobbin (empty yarn roll) replacement. The actual industrial site is characterized by uneven lighting, restricted shooting angles, diverse yarn colors and cylinder yarn types, and complex backgrounds. Due to the above characteristics, the neural network detection error is large, and the contour detection extraction edge accuracy is low. In this paper, an improved neural network algorithm is proposed, and the improved Yolo algorithm and the contour detection algorithm are integrated. First, the image is entered in the Yolo model to detect each yarn roll and its dimensions; second, the contour and dimensions of each yarn roll are accurately detected based on Yolo; third, the diameter of the yarn rolls detected by Yolo and the contour detection algorithm are fused, and then the length of the yarn rolls and the edges of the yarn rolls are calculated as measurements; finally, in order to completely eliminate the error detection, the yarn consumption speed is used to estimate the residual yarn volume and the measured and estimated values are fused using a Kalman filter. This method overcomes the effects of complex backgrounds and illumination while being applicable to different types of yarn rolls. It is experimentally verified that the average measurement error of the cylinder yarn diameter is less than 8.6 mm, and the measurement error of the cylinder yarn length does not exceed 3 cm.
Journal Article
Promoting and inhibiting: Corporate charitable donations and innovation investment under different motivation orientations——Evidence from Chinese listed companies
Corporate charitable donations under different motivations will have different effects on innovation investment through different action paths, which provides a new perspective to solve the inconsistency of existing research results. Based on the resource-dependent and principal-agent theories, this paper compares and discusses the relationship between charitable donations and innovation investment under different motivations. Using 2008 ~2019 relevant data of listed companies as research samples, a mixed regression model is established for the hypothesis test, and further examines the state-ownership of its moderating role. The results show that the altruistic motivation-oriented corporate donations have a significant inverted u-shaped effect on innovation investment. The tool motivation-oriented corporate donations have a significant U-shaped effect on innovation investment. Moreover, it is further found that for ST (Special Treatment) corporates with the risk of delisting in the tool motivation-oriented charitable donations type, the corporate charitable donations have a significant negative effect on innovation investment. State-ownership can enhance the inverted U-shaped relationship between altruistic motivation-oriented corporate donations and innovation investment but weaken the U-shaped relationship between tool motivation-oriented corporate donations and innovation investment.
Journal Article
Insight to the enhanced microwave absorption of porous N-doped carbon driven by ZIF-8: Competition between graphitization and porosity
Porous carbon-based materials are promised to be lightweight dielectric microwave absorbents. Deeply understanding the influence of graphitization grade and porous structure on the dielectric parameters is urgently required. Herein, utilizing the low boiling point of Zn, porous N-doped carbon was fabricated by carbonization of ZIF-8 (Zn) at different temperature, and the microwave absorption performance was investigated. The porous N-doped carbon inherits the high porosity of ZIF-8 precursor. By increasing the carbonization temperature, the contents of Zn and N elements are decreased; the graphitization degree is improved; however, the specific surface area and porosity are increased first and then decreased. When the carbonization temperature is 1000°C, the porous N-doped carbon behaves enhanced microwave absorption. With an ultrathin thickness of 1.29 mm, the ideal RL reaches −50.57 dB at 16.95 GHz and the effective absorption bandwidth is 4.17 GHz. The mechanism of boosted microwave absorption is ascribed to the competition of graphitization and porosity as well as N dopants, resulting in high dielectric loss capacity and good impedance matching. The porous structure can prolong the pathways and raise the contact opportunity between microwaves and porous carbon, causing multiple scattering, interface polarization, and improved impedance matching. Besides, the N dopants can induce electron polarization and defect polarization. These results give a new insight to construct lightweight carbon-based microwave absorbents by regulating the graphitization and porosity.
Journal Article
An ensemble feature selection method for high-dimensional data based on sort aggregation
With the rapid development of the Internet, big data has been applied in a large amount of application. However, there are often redundant or irrelevant features in high dimensional data, so feature selection is particularly important. Because the feature subset obtained by a single feature selection method may be biased, an ensemble feature selection method named SA-EFS based on sort aggregation is proposed in this paper, and this method is oriented to classification tasks. For high-dimensional data sets, the results of three feature selection methods, chi-square test, maximum information coefficient and XGBoost, are aggregated by specific strategy. The integration effects of arithmetic mean and geometric mean aggregation strategy on this model are analyzed. In order to evaluate the classification and prediction performance of feature subset, three classifiers with excellent performance, KNN, Random Forest and XGBoost, are tested respectively, and the influence of threshold on classification performance is analyzed. The experimental results show that compared with the single feature selection method, the arithmetic mean aggregation ensemble feature selection can effectively improve the classification accuracy, and the threshold interval setting of 0.1 is a better choice.
Journal Article