Although the Crowd-Sensing perception system brings great data value to people through the release and analysis of high-dimensional perception data, it causes great hidden danger to the privacy of ...participants in the meantime. Currently, various privacy protection methods based on differential privacy have been proposed, but most of them cannot simultaneously solve the complex attribute association problem between high-dimensional perception data and the privacy threat problems from untrustworthy servers. To address this problem, we put forward a local privacy protection based on Bayes network for high-dimensional perceptual data in this paper. This mechanism realizes the local data protection of the users at the very beginning, eliminates the possibility of other parties directly accessing the user's original data, and fundamentally protects the user's data privacy. During this process, after receiving the data of the user's local privacy protection, the perception server recognizes the dimensional correlation of the high-dimensional data based on the Bayes network, divides the high-dimensional data attribute set into multiple relatively independent low-dimensional attribute sets, and then sequentially synthesizes the new dataset. It can effectively retain the attribute dimension correlation of the original perception data, and ensure that the synthetic dataset and the original dataset have as similar statistical characteristics as possible. To verify its effectiveness, we conduct a multitude of simulation experiments. Results have shown that the synthetic data of this mechanism under the effective local privacy protection has relatively high data utility.
Differential privacy protection model provides strict and quantitative risk representation for privacy disclosure, which greatly ensures the availability of data. However, most existing methods do ...not consider the semantic context, so they are vulnerable to attacks based on semantic information. Therefore, dynamic social privacy protection based on graph pattern partitioning is designed to satisfy differential privacy protection. Firstly, the structure of social network is represented as a graph model, and the original graph is classified into several sub-graphs according to the characteristics of nodes. Then, the dense area of each sub-graph is divided by quad-tree method, and the noise of differential privacy protection is added to the leaf nodes of the tree, and the graph publishing is generated by sub-graph reconstruction. Finally, the feasibility and practicability of the model are verified by statistical analysis, such as degree distribution, shortest path, and clustering coefficient. The simulation results show the validity and applicability of the privacy protection method proposed in this paper.
In this era of artificial intelligence and information, the transformation and upgrading of enterprises plays a crucial role in their development. This study analyzes the regulatory penalties of ...listed companies published by the Shenzhen and Shanghai stock exchanges from 1996 to 2017, and explores the relationship between the number of enforcements of these companies and their innovation ability. Existing research literature confirms that board characteristics, including the gender of the CEO and whether the CEO has an overseas background, will have a significant impact on the company’s ability to innovate and the likelihood of corporate penalties. Therefore, this study selects the two moderator variables of the chairman’s gender and whether the chairman has overseas study background. This study uses the To bit model and establishes three hypotheses to verify whether the company’s ability to innovate can significantly affect the number of times they are enforced, whether the chairman’s gender and whether the chairman’s overseas background will have a moderator effect on this relationship. The analysis results confirm these three assumptions.
As individual investors who act independently can generate only limited influence on corporate decisions, this paper considers clustered institutional investors connected through investor networks as ...salient external stakeholders and investigates whether shared preferences for environmental, social, and governance (ESG) among clustered institutional investors induce more low-carbon innovation of family firms. Using a dataset with 9249 observations over the period of 2007–2019 of Chinese family firms, we develop a novel measurement for the shared preferences for ESG activities among clustered institutional investors and find that such shared preferences are positively related to corporate low-carbon innovation. From a stakeholder perspective, we explore the moderating effects of green finance and family control. Our findings suggest that green finance strengthens the above relationship, but this positive moderating effect is significant only in the low-uncertainty economic context. We also find that as family control increases, the positive impact of the shared preferences for ESG among clustered institutional investors on low-carbon innovation becomes less pronounced, and such a negative moderating effect disappears if a family successor is present in the top management team.
•Shared ESG preference of institutional investors (S_ESG) spur low-carbon innovation•Green finance positively moderates the effect of S_ESG on low-carbon innovation•Such moderating effect of green finance is pronounced in stable economic situation•Family control negatively moderates the effect of S_ESG on low-carbon innovation•Such moderating effect of family control weakens if young family member present in TMT
Using a dataset of Chinese private firms from 2002 to 2014, this study examines the impact of China’s SO2 emission trading schema pilot on industrial innovation. In particular, this study explores ...the moderating effects of institutional settings from the perspective of new structural economics. Our finding shows positive support for the Porter Hypothesis (Porter and Linde, 1995), demonstrating that institutional regulation may enhance its impact on industrial innovation. Furthermore, both regulatory system and regulation enforcement may positively moderate the policy effect of emission trading schema on industrial innovation. Our findings indicate that market-oriented environmental regulation should be enforced in the aid of institutional settings.
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•Porter hypothesis holds by enforcing market-oriented regulation instrument.•Environmental regulation towards industrial upgrading should evolve with institutional change.•Institutional systems of environmental regulation positively enhance Porter Hypothesis effect.•More stringent regulation enforcement leads to stronger Porter Hypothesis effect.
•There is Identity discrimination based on education and gender in Chinese P2P lending market.•Digital authentication alleviates statistical discrimination and increase financial inclusion.•Such ...authentication may increase taste-based discrimination and lead to pricing discrimination.•Underdog mentality explains psychological process of such financial behaviors of vulnerable groups.
Vulnerable social groups are often the recipients of statistical discrimination by financial institutions. They therefor try to access the P2P lending market through voluntary digital authentication, but the digital authentication requirements in P2P lending increase taste-based discrimination against these vulnerable groups. Empirical results in this study confirm the existence of education-based and gender-based statistical discrimination even in the Chinese P2P lending market. Digital authentication might alleviate statistical discrimination and increase financial inclusion for these vulnerable groups, but this authentication might also lead to members of vulnerable groups having to pay higher interest rates when seeking loans. The “underdog mentality” concept explains why vulnerable groups voluntarily accept digital authentication, and why they tolerate having to pay higher interest rates for loans P2P they receive.
Gu, Q.Y.; Wang, R., and Ju, C.H., 2020. Evaluation path selection of opening-up level of Chinese coastal cities based on entropy weight-topsis-grey correlation: From researches on ten coastal cities. ...In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 636-640. Coconut Creek (Florida), ISSN 0749-0208. The article provides a system to evaluate the opening-up level of coastal cities in China based on literatures and the national conditions of China's opening-up. Targeting relevant data and opening-up level of ten typical coastal cities in China, It solves performance differences and weights of indexes by using the entropy weight method, scores the cities' opening-up level through weighted TOPSIS method and make judgement on the correlation between samples and various indexes through grey correlation method. At last, it make propositions on further opening-up of coastal cities in China.
Existing literature tends to treat enterprises as a whole when measuring government intervention. However, in Chinese region-specific institutional development, ultimate control (i.e., local ...government) tends to control multiple enterprises. This paper considers the enterprises controlled by the same ultimate controller as a portfolio, which is used to measure government intervention by comparing the differences of the enterprises in the portfolio. This paper uses the data of Chinese listed local state-owned enterprises (LSOEs). and we assess whether local state ownership benefits or offsets LSOEs’ cross-border mergers and acquisitions (CBM & A) activities. We propose a new measurement of government intervention to explain the mechanisms through which government influences the cross-border mergers and acquisitions of local SOEs. The experimental results show that government intervention and region-specific marketization institutional development negatively moderate the effect of government internationalization subsidies and government intervention on CBM & A separately. However, government internationalization subsidies, government intervention, and region-specific marketization enhance the CBM & A effect of state ownership separately. This study explores the benefits of government involvement in local SOEs. The value of this paper is to provide a novel perspective, including the intermediary effect of government intervention and the market environment.
Programmed cell death is pivotal for several physiological processes, including immune defense. Further, it has been implicated in the pathogenesis of developmental disorders and the onset of ...numerous diseases. Multiple modes of programmed cell death, including apoptosis, pyroptosis, necroptosis, and ferroptosis, have been identified, each with their own unique characteristics and biological implications. In February 2023, Liu Xiaoguang and his team discovered "disulfidptosis," a novel pathway of programmed cell death. Their findings demonstrated that disulfidptosis is triggered in glucose-starved cells exhibiting high expression of a protein called SLC7A11. Furthermore, disulfidptosis is marked by a drastic imbalance in the NADPH/NADP+ ratio and the abnormal accumulation of disulfides like cystine. These changes ultimately lead to the destabilization of the F-actin network, causing cell death. Given that high SLC7A11 expression is a key feature of certain cancers, these findings indicate that disulfidptosis could serve as the basis of innovative anti-cancer therapies. Hence, this review delves into the discovery of disulfidptosis, its underlying molecular mechanisms and metabolic regulation, and its prospective applications in disease treatment.
User influence has always been a major topic in the field of social networking. At present, most of the research focuses on three aspects: topological structure, social-behavioral dimension, and ...topic dimension and most of them ignore the difference between the audience. These models do not consider the impact of personality differences on user influences. To meet this need, this paper introduces the personality traits factor and proposes a user influence model which integrates personality traits (IPUIM) under a strong connection. The user influence measurement is constructed through the information dimension, structural dimension, and user behavioral dimension. The personality report of the user group is obtained by means of NEO-PI-R (The big five personality inventory, Chinese edition) and machine learning method, and it is integrated into the user influence model. The experiment proves that the model proposed in this paper has good accuracy and applicability in measuring user influence, and can effectively identify the key opinion leaders of different personality trait clusters.
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