Environmental problems caused by human behaviors have become increasingly serious in recent decades, thereby driving global green governance issue to become an important research agenda. The proper governance structure design and governance mechanism arrangement can effectively coordinate the relationship between human and nature. Literatures have provided mixed evidence of harmonious development of economy, society and environment. However, few studies have examined the balance of interests between human appeal and natural environment from the perspective of governance. Open innovation activities can effectively deal with the externalities of resources and environment and then relatively balance the economic value and green value of organizations, which is an effective green governance mode, reflecting the characteristics of the main subject composition and mechanism operation of green governance. This paper attempts to build a green governance framework for the cooperation based on sustainable development among enterprises, governments, social organizations, the public and the nature. This paper examines the synergy between human and nature by presenting a framework, including related theories of green governance, innovation subjects, innovation mechanisms and innovation mode. Each country and region could use the suggested framework to develop green governance guidelines that are suitable for the environmental carrying capacity of their own countries or regions. Enterprises could use the suggested framework to develop green development strategies to coordinate the economic values and green values.

Bacterial trapping using nanonets is a ubiquitous immune defense mechanism against infectious microbes. These nanonets can entrap microbial cells, effectively arresting their dissemination and rendering them more vulnerable to locally secreted microbicides. Inspired by this evolutionarily conserved anti‐infective strategy, a series of 15 to 16 residue‐long synthetic β‐hairpin peptides is herein constructed with the ability to self‐assemble into nanonets in response to the presence of bacteria, enabling spatiotemporal control over microbial killing. Using amyloid‐specific K114 assay and confocal microscopy, the membrane components lipoteichoic acid and lipopolysaccharide are shown to play a major role in determining the amyloid‐nucleating capacity as triggered by Gram‐positive and Gram‐negative bacteria respectively. These nanonets displayed both trapping and killing functionalities, hence offering a direct improvement from the trap‐only biomimetics in literature. By substituting a single turn residue of the non‐amyloidogenic BTT1 peptide, the nanonet‐forming BTT1‐3A analog is produced with comparable antimicrobial potency. With the same sequence manipulation approach, BTT2‐4A analog modified from BTT2 peptide showed improved antimicrobial potency against colistin‐resistant clinical isolates. The peptide nanonets also demonstrated robust stability against proteolytic degradation, and promising in vivo efficacy and biosafety profile. Overall, these bacteria‐responsive peptide nanonets are promising clinical anti‐infective alternatives for circumventing antibiotic resistance.

The choice of the reference electrode scheme is an important step in event-related potential (ERP) analysis. In order to explore the optimal electroencephalogram reference electrode scheme for the ERP signal related to facial recognition, we investigated the influence of average reference (AR), mean mastoid reference (MM), and Reference Electrode Standardization Technique (REST) on the N170 component via statistical analysis, statistical parametric scalp mappings (SPSM) and source analysis. The statistical results showed that the choice of reference electrode scheme has little effect on N170 latency ( p > 0.05), but has an significant impact on N170 amplitude ( p < 0.05). ANOVA results show that, for the three references scheme, there was statistically significant difference between N170 latency and amplitude induced by the unfamiliar face and that induced by the scrambled face ( p < 0.05). Specifically, the SPSM results show an anterior and a temporo-occipital distribution for AR and REST, whereas just anterior distribution shown for MM. However, the circumstantial evidence provided by source analysis is more consistent with SPSM of AR and REST, compared with that of MM. These results indicate that the experimental results under the AR and REST references are more objective and appropriate. Thus, it is more appropriate to use AR and REST reference scheme settings in future facial recognition experiments.

Like courts in democratic regimes, courts under authoritarianism play an important role in the regulation of complex economies. In particular, scholars suggest that authoritarian judiciaries are commonly encouraged to provide independent adjudication in the context of economic disputes between firms. Yet because regime insiders are often connected to firms, judges have strong incentives to consider the political implications of their decisions even in areas of the law where they are allegedly more independent. In this article, I propose a new theory about the role of corporations’ political background in commercial lawsuits. Using a data set on the litigation outcomes of firms in China, I find that the composition of a firm’s board membership is a significant predictor of its lawsuit outcomes. A higher percentage of corporate board members with political connections leads to a higher probability of lawsuit success. The results point to the limitations of the selective judicial independence theory.

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