Heterogeneity effects of environmental regulation policy synergy on ecological resilience: considering the moderating role of industrial structure.

Given the great importance attached to ecological civilization and green development, exploring the heterogeneous effects of environmental regulation policy synergy on ecological resilience holds significance for improving environmental protection and the design of environmental policies. Based on the policy synergy perspective, this paper uses 30 provinces (municipalities and autonomous) in China as the research sample. Bayesian quantile regression is employed to explore the heterogeneous effects of environmental regulation policy synergy on ecological resilience from 2007 to 2021, and the moderating effect of the industrial structure is examined. The results indicate the following: (1) there is significant heterogeneity and variability in the effect of environmental regulation policy synergy on ecological resilience. Specifically, the effects of policy mixes 12, 13, and 23 on ecological resilience shows a U-shaped trend, while the impact of policy mix 123 on ecological resilience shows a positive effect. (2) There are significant differences in the effects of environmental regulation policy synergy under different quantiles of ecological resilience. Taking policy mix 12 as an example, we find that the effect of policy synergy on ecological resilience tends to decrease and then increase at a lower quantile. Additionally, the effect of policy synergy on ecological resilience tends to be positive at a higher quantile. (3) There are significant differences in the moderating effects of the industrial structure. Policy mix 12 can effectively enhance ecological resilience through industrial structure upgrading, while the moderating effects of alternative policy combinations are deemed insufficient. Finally, relevant policy recommendations are proposed to effectively improve ecological resilience.

Impact of corporate carbon emission reduction on financing constraints.

The carbon emission reduction behaviour of enterprises is a crucial element for achieving the "double-carbon" target. Based on the panel data of China's Shanghai and Shenzhen A-share nonfinancial listed companies from 2008 to 2022, this paper explores the impact of corporate carbon emission reduction on financing constraints using the fixed effect model and further dissects the path and heterogeneity of its impact. The results show that carbon emission reduction can significantly alleviate the level of financing constraints. The path test shows that corporate carbon emission reduction alleviates financing constraints through gaining business credit, improving information transparency, and increasing government subsidies. The heterogeneity analysis shows that carbon emission reduction in less economically developed regions, non-heavily polluting industries, and nonstate-owned enterprises has a better effect on alleviating financing constraints than in economically developed regions, heavily polluting industries and state-owned enterprises. Additionally, relevant policy recommendations are put forward, which are conducive to promoting enterprises to actively reduce carbon emissions and facilitate the achievement of the dual carbon goal.

Effect of environmental regulation policy synergy on carbon emissions in China under consideration of the mediating role of industrial structure.

A comprehensive understanding of the effect of environmental regulation policy synergy on carbon emissions is essential for the design and decision-making of the other policy combinations. In this paper, the panel data from 30 provinces in China during 2000-2019 are used as samples to investigate the heterogeneity of different policy combinations and compare the differences using a Bayesian non-parametric generalized additive quantile method. The research results imply that the environmental regulation policy synergy has a significant heterogeneous effect on carbon emissions on different levels. Specifically, the effect of environmental regulation policy synergy on carbon emissions has an inverted U-shape trend at the low quintiles, i.e., before the turning point, it shows a "green paradox" effect, and after the turning point, it shows an "emission reduction" effect. However, the effect of environmental regulation policy synergy on carbon emissions shows a significant N-shape trend at the high quintiles, i.e., before the second turning point, it shows an "emission reduction" effect, and after the second turning point, it shows a "green paradox" effect. Moreover, the effect of environmental regulation policy combinations on carbon emissions reduction has been found to vary significantly across regions.

Heterogeneity and threshold effects of environmental regulation on health expenditure: Considering the mediating role of environmental pollution.

A comprehensive understanding of the heterogeneity and threshold effects of environmental regulation on health expenditure is essential for policy design and decision-making. This case study seeks to analyze the heterogeneity and threshold effects using panel data, which covers 30 Chinese provinces from 2007 to 2017. We examine the linear and nonlinear impacts of environmental regulation on health expenditure by using the Bayesian quantile regression and panel threshold regression, respectively. The empirical research results indicate a significant heterogeneous effect of environmental regulation on health expenditure in provinces where health expenditure falls in different quintiles. It shows mainly two effects: a positive effect of environmental regulation on health expenditure in provinces in the low quintiles and high quintiles of health expenditure; and a negative interrelationship between environmental regulation and health expenditure for provinces in the medium quintiles of health expenditure. A single threshold effect of environmental regulation on health expenditure is found to be different among three regions: the eastern, central and western regions. Specifically, in eastern and western China, the environmental regulations are stricter, and this helps reduce the health expenditures relating to environmental pollution. However, it was found that stricter environmental regulations do not reduce health expenditures in central China.

Pronounced Enhancement of Superconductivity in ZrN via Strain Engineering.

Zirconium nitride (ZrN) exhibits excellent mechanical and electronic properties and hosts a superconducting transition temperature (Tc) of 10.0 K that is on the high end among transition-metal nitrides. Here, we report on a first-principles study of tuning superconductivity of ZrN via strain engineering under extensive tensile and shear deformation modes. Our results reveal strikingly effective strain-induced enhancement of Tc up to 17.1 K, which is achieved under tensile strains along the high-symmetry crystallographic [001] deformation path. A systematic analysis of the calculated results indicates that such pronounced strain modulation of superconductivity stems from simultaneous increase of electronic density of states and softening of lattice vibration in the strain-deformed ZrN crystal. The present findings show that strain engineering offers an effective tool for optimizing superconductivity in transition-metal compounds, opening a fresh avenue for improving a major functionality of this class of materials that may find applications in advanced devices.

Short-term and long-term exposure to hexavalent chromium alters 53BP1 via H3K18ac and H3K27ac.

Hexavalent chromium (Cr(VI)) is a well-known human carcinogen and a strong oxidizer that causes severe DNA damage. However, the associations between epigenetic dysregulation and DNA damage have not been well-characterized. In this study, we evaluated the effects of short-term and long-term exposure to Cr(VI) in human bronchial epithelial (16HBE) cells. Then, we explored the role of epigenetic modification in Cr(VI)-induced DNA damage. We found that short- and long-term exposure to Cr(VI) induced DNA damage and reduced the expression 53BP1, but increased the expression of other DNA repair mediators. Short- and long-term exposure to Cr(VI) reduced the levels of H3K18ac and H3K27ac and reduced their enrichment at the promoter of 53BP1. Long-term Cr(VI) exposure resulted in multiple malignant characteristics including cell invasion, migration, and tumorgenicity. These data demonstrated that reduced H3K18ac and H3K27ac following Cr(VI) treatment contributed to the suppression of 53BP1. Our study demonstrated that epigenetic changes and DNA damage responses are involved in short-term toxicity and long-term carcinogenesis induced by Cr(VI).

SET promotes H2Ak9 acetylation by suppressing HDAC1 in trichloroethylene-induced hepatic cytotoxicity.

Trichloroethylene (TCE) was widely used as an industrial solvent which could cause severe liver damage. The histone chaperone SET have been identified as an important mediator of TCE-induced hepatic cytotoxicity in our previous study; however, the underlying regulatory mechanisms remain poorly understood. In this study, we found a total of 136 histone acetylation sites involved in TCE-induced hepatic cytotoxicity with the technique of Triton-acid-urea polyacrylamide gel electrophoresis (TAU-PAGE) coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Importantly, 17 histone acetylation sites were revealed to be mediated by SET in TCE-induced cytotoxicity. The acetylation of histone H2AK9 (H2AK9ac) was further validated by Western-blot analysis. The data showed that TCE treatment increased the acetylation of H2AK9 in hepatic L-02 cell and decreased the one in SET-knockdown L-02 cells. Besides, levels of the histone deacetylases (HDACs, including HDAC1, HDAC2, and HDAC3) was also analyzed. Interestingly, the level of HDAC1 was aberrantly suppressed in TCE-treated L-02 cells while enhanced in SET-knockdown L-02 cells. To further explore the potential role of HDAC1 in SET-mediated hepatic cytotoxicity of TCE, we employed RNA interference (RNAi) to knockdown HDAC1 in both wide type L-02 and SET-knockdown cells. The results showed that the siRNA inhibition of HDAC1 increased the acetylation of H2AK9. Taken together, our data suggested that SET promoted the acetylation of H2AK9 via suppressing the level of HDAC1, which was involved in SET-mediated hepatic cytotoxicity of TCE.

Early detection of dynamic harmful cascades in large-scale networks.

Quickly detecting harmful cascades in networks can allow us to analyze the causes and prevent further spreading of destructive influence. Since it is often impossible to observe the state of all nodes in a network, a common method is to detect harmful cascades from sparsely placed sensors. However, the harmful cascades are usually dynamic (e.g., the cascade initiators and diffusion trajectories can change over the time), which can severely destroy the robustness of selected sensors. Meanwhile the large scale of current networks greatly increases the time complexity of sensor selection. Motivated by the observation, in this paper we investigate the scalable sensor selection problem for early detection of dynamic harmful cascades in networks. Specifically, we first put forward a dynamic susceptible-infected model to describe harmful cascades, and formally define a detection time minimization (DTM) problem which focuses on effective sensors placement for early detection of dynamic cascades. We prove that it is #P-hard to calculate the objective function exactly and propose two Monte-Carlo methods to estimate it efficiently. We prove the NP-hardness of DTM problem and design a corresponding greedy algorithm. Based on that, we propose an efficient upper bound based greedy (UBG) algorithm with the theoretical performance guarantee reserved. To further meet different types of large-scale networks, we propose two accelerations of UBG: Quickest-Path-UBG for sparse networks and Local-Reduction-UBG for dense networks to improve the time complexity. The experimental results on synthetic and real-world social networks demonstrate the practicality of our approaches.

[Review: Segmentation and classification methods of 3D medical images].

This paper presents a survey of recent publications (published in 1990 or later) concerning segmentation and classification of medical images. These methods will be classified into six types: cluster (threshold), statistics methods, deformable contour, region growing, mathematics morphology, nonlinear methods (fuzzy segmentation, neural networks, genetic algorithm) and 3D model. Each of the major classes of image segmentation and classification techniques and several specific examples of each class of algorithm are described respectively in detail. At last, the developing trend of 3D medical image is also discussed.