Experimenting towards a low-carbon city: Policy evolution and nested structure of innovation

Cities can play a key role in the low-carbon transition, with an increasing number of cities engaging in carbon mitigation actions. The literature on urban low-carbon transition shows that low-carbon urban development is an inevitable trend of urban sustainable future; there is a great potential albeit with some limitations for cities to reduce its carbon footprints, and there are diverse pathways for cities to achieve low-carbon development. There is, however, a limited understanding in terms of the internal mechanism of urban low-carbon transition, especially in rapidly developing economies. This paper attempts to address this gap. We examine how low-carbon policies emerge and evolve, and what are the enabling mechanisms, taking Shanghai as a case study. We developed an analytical framework drawing on system innovation theory and sustainability experiments for this purpose. A total of 186 relevant policies were selected and analyzed, which is supplemented by the interviews with stakeholders in the government to gain a deeper insight into the policy contexts in Shanghai. We found that the city's low-carbon initiatives are embedded and integrated into its existing policy frameworks. A strong vertical linkage between the central and the local governments, and more importantly, a nested structure for innovative policy practices were identified, where a top-down design is met with bottom-up innovation and proactive adoption of enabling mechanism. The structure includes two layers of experiments that facilitate learning through policy experiments across scales. The uniqueness, effectiveness, applicability and limitations of these efforts are discussed. The findings provide new theoretical and empirical insights into the multilevel governance of low-carbon transition in cities

EGFAFS:A Novel Feature Selection Algorithm Based on Explosion Gravitation Field Algorithm

Feature selection (FS) is a vital step in data mining and machine learning, especially for analyzing the data in high-dimensional feature space. Gene expression data usually consist of a few samples characterized by high-dimensional feature space. As a result, they are not suitable to be processed by simple methods, such as the filter-based method. In this study, we propose a novel feature selection algorithm based on the Explosion Gravitation Field Algorithm, called EGFAFS. To reduce the dimensions of the feature space to acceptable dimensions, we constructed a recommended feature pool by a series of Random Forests based on the Gini index. Furthermore, by paying more attention to the features in the recommended feature pool, we can find the best subset more efficiently. To verify the performance of EGFAFS for FS, we tested EGFAFS on eight gene expression datasets compared with four heuristic-based FS methods (GA, PSO, SA, and DE) and four other FS methods (Boruta, HSICLasso, DNN-FS, and EGSG). The results show that EGFAFS has better performance for FS on gene expression data in terms of evaluation metrics, having more than the other eight FS algorithms. The genes selected by EGFAGS play an essential role in the differential co-expression network and some biological functions further demonstrate the success of EGFAFS for solving FS problems on gene expression data

Accuracy improvement on fatigue test of megawatt wind turbine blades by adaptive fuzzy control

A single-point fatigue loading system of wind turbine blade driven by an unbalanced shaft was designed. To determine whether the vibrating performance of the loading system satisfied the fatigue test demanding, the blade was driven by different frequency under open-loop control mode in on-site flapwise fatigue test. The results showed that the more the driven frequency close to the blade’s natural frequency, the more the amplitude of the blade increase. In resonance mode, the amplitude of the blade can reach the maximum value certainly. However, the peak values of the vibration have some fluctuation, which will influence the accuracy of fatigue test. To solve the unstable problem of blade’s amplitude, the amplitude of blade’s loading point obtained by laser range meter was taken as the control index, the deviation of the amplitude and its variation tendency were taken as the input and the loading frequency as the output, then an adaptive fuzzy control system based on multistage network was built to realize blade’s constant amplitude vibrating. The on-site test showed the adaptive fuzzy control algorithm put forward in this paper could maintain the error of the peak value of vibration less than 5 mm, which satisfied the fatigue test requirement

Coupling mechanism of dual-excitation fatigue loading system of wind turbine blades

A new dual-excitation fatigue loading system of wind turbine blades was designed in this paper. However, the two excitations and blade constituted a complicated non-liner energy transferring system in which the vibration coupling effect would influence the sequent accurate control of fatigue test. To study the mechanism of the coupling system mentioned above, the electromechanical coupling mathematical model was established by simplifying the loading system rationally and the factors affecting the vibration coupling were obtained accordingly. Then the simulation model of the system was built in Matlab/Simulink environment to mainly analyze the basic influence laws of the motor speed and the initial phase difference of two excitations. Finally, a small dual-excitation fatigue loading system was established to verify the correctness of the mathematical and simulation model. It could be concluded that the results of on-site test were consistent with the results of simulation

Empirical Research on Debt Restructuring Gains in China’s Listed Companies

China’s Ministry of Finance issued New Accounting Standards of debt restructurings in 2006. According to the new standards, fair value was introduced again and debt restructuring gains were recognized as non-operating income. This paper uses empirical study to discuss the correlation between debt restructuring gains and financial indicators. This paper selects 2009 A-Share listed companies on Shanghai and Shenzhen Stock Exchanges as research sample, using descriptive statistics, linear regression analysis and paired samples T test analysis to identify the influencing factors of debt restructuring gains. Based on the research conclusions, the paper proposes corresponding suggestions to improve debt restructurings standards and perfect accounting supervisory system.Key words: Debt restructurings; Accounting standards; China’s listed companies; Gains; Empirical researc

5-{2-(4-Chloro­phen­yl)-1-[2-(4-chloro­phen­yl)-1-(3,4,5-trimeth­oxy­phen­yl)eth­oxy]eth­yl}-1,2,3-trimeth­oxy­benzene

The title compound, C34H36Cl2O7, is a by-product from the reaction of 4-chloro­benzyl­zinc chloride with 3,4,5-trimeth­oxy­benzaldehyde. In each of the two 1,2-diphenyl­ethyl moieties, the two benzene rings are arranged in a trans conformation and make Car—C—C—Car torsion angles of 163.64 (19) and 174.43 (18)°. The crystal structure is stabilized by van der Waals inter­actions only

Intergenic transcription by RNA Polymerase II coordinates Pol IV and Pol V in siRNA-directed transcriptional gene silencing in \u3ci\u3eArabidopsis\u3c/i\u3e

Intergenic transcription by RNA Polymerase II (Pol II) is widespread in plant and animal genomes, but the functions of intergenic transcription or the resulting noncoding transcripts are poorly understood. Here, we show that Arabidopsis Pol II is indispensable for endogenous siRNA-mediated transcriptional gene silencing (TGS) at intergenic low-copy-number loci, despite the presence of two other polymerases—Pol IV and Pol V—that specialize in TGS through siRNAs. We show that Pol II produces noncoding scaffold transcripts that originate outside of heterochromatic, siRNA-generating loci. Through these transcripts and physical interactions with the siRNA effector protein ARGONAUTE4 (AGO4), Pol II recruits AGO4/siRNAs to homologous loci to result in TGS. Meanwhile, Pol II transcription also recruits Pol IV and Pol V to different locations at heterochromatic loci to promote siRNA biogenesis and siRNA-mediated TGS, respectively. This study establishes that intergenic transcription by Pol II is required for siRNA-mediated TGS, and reveals an intricate collaboration and division of labor among the three polymerases in gene silencing

Antigenic analysis of classical swine fever virus E2 glycoprotein using pig antibodies identifies residues contributing to antigenic variation of the vaccine C-strain and group 2 strains circulating in China

BACKGROUND: Glycoprotein E2, the immunodominant protein of classical swine fever virus (CSFV), can induce neutralizing antibodies and confer protective immunity in pigs. Our previous phylogenetic analysis showed that subgroup 2.1 viruses branched away from subgroup 1.1, the vaccine C-strain lineage, and became dominant in China. The E2 glycoproteins of CSFV C-strain and recent subgroup 2.1 field isolates are genetically different. However, it has not been clearly demonstrated how this diversity affects antigenicity of the protein. RESULTS: Antigenic variation of glycoprotein E2 was observed not only between CSFV vaccine C-strain and subgroup 2.1 strains, but also among strains of the same subgroup 2.1 as determined by ELISA-based binding assay using pig antisera to the C-strain and a representative subgroup 2.1 strain QZ-07 currently circulating in China. Antigenic incompatibility of E2 proteins markedly reduced neutralization efficiency against heterologous strains. Single amino acid substitutions of D705N, L709P, G713E, N723S, and S779A on C-strain recombinant E2 (rE2) proteins significantly increased heterologous binding to anti-QZ-07 serum, suggesting that these residues may be responsible for the antigenic variation between the C-strain and subgroup 2.1 strains. Notably, a G713E substitution caused the most dramatic enhancement of binding of the variant C-strain rE2 protein to anti-QZ-07 serum. Multiple sequence alignment revealed that the glutamic acid residue at this position is conserved within group 2 strains, while the glycine residue is invariant among the vaccine strains, highlighting the role of the residue at this position as a major determinant of antigenic variation of E2. A variant Simpson's index analysis showed that both codons and amino acids of the residues contributing to antigenic variation have undergone similar diversification. CONCLUSIONS: These results demonstrate that CSFV vaccine C-strain and group 2 strains circulating in China differ in the antigenicity of their E2 glycoproteins. Systematic site-directed mutagenesis of the antigenic units has revealed residues that limit cross-reactivity. Our findings may be useful for the development of serological differential assays and improvement of immunogenicity of novel classical swine fever vaccines

Effects of Full-Length Borealin on the Composition and Protein-Protein Interaction Activity of a Binary Chromosomal Passenger Complex

The chromosomal passenger complex (CPC) comprises at least four protein components and functions at various cellular localizations during different mitotic stages to ensure correct chromosome segregation and completion of cytokinesis. Borealin, the most recently identified member of the CPC, is an intrinsically unstructured protein of low solubility and stability. Recent reports have demonstrated the formation binary or ternary CPC sub-complexes incorporating short Borealin fragments in vitro. Using isothermal titration calorimetry, we show that full-length Borealin, instead of a Borealin fragment possessing the complete Survivin and INCENP-recognition sequence, is required for the composition of a Borealin-Survivin complex competent to interact with INCENP. In addition, we show evidence that full-length Borealin, which forms high-order oligomers in its isolated form, is a monomer in the Borealin-Survivin CPC sub-complex

MTR4 drives liver tumorigenesis by promoting cancer metabolic switch through alternative splicing.

The metabolic switch from oxidative phosphorylation to glycolysis is required for tumorigenesis in order to provide cancer cells with energy and substrates of biosynthesis. Therefore, it is important to elucidate mechanisms controlling the cancer metabolic switch. MTR4 is a RNA helicase associated with a nuclear exosome that plays key roles in RNA processing and surveillance. We demonstrate that MTR4 is frequently overexpressed in hepatocellular carcinoma (HCC) and is an independent diagnostic marker predicting the poor prognosis of HCC patients. MTR4 drives cancer metabolism by ensuring correct alternative splicing of pre-mRNAs of critical glycolytic genes such as GLUT1 and PKM2. c-Myc binds to the promoter of the MTR4 gene and is important for MTR4 expression in HCC cells, indicating that MTR4 is a mediator of the functions of c-Myc in cancer metabolism. These findings reveal important roles of MTR4 in the cancer metabolic switch and present MTR4 as a promising therapeutic target for treating HCC