Video Conferencing for Opening Classroom Doors in Initial Teacher Education: Sociocultural Processes of Mimicking and Improvisation

In this article, we present an alternative framework for conceptualising video-conferencing uses in initial teacher education and in Higher Education (HE) more generally. This alternative framework takes into account the existing models in the field, but – based on a set of interviews conducted with teacher trainees and wider analysis of the related literature – we suggest that there is a need to add to existing models the notions of ‘mimicking’ (copying practice) and improvisation (unplanned and spontaneous personal learning moments). These two notions are considered to be vital, as they remain valid throughout teachers’ careers and constitute key affordances of video-conferencing uses in HE. In particular, we argue that improvisational processes can be considered as key for developing professional practice and lifelong learning and that video-conferencing uses in initial teacher education can contribute to an understanding of training and learning processes. Current conceptualisations of video conferencing as suggested by Coyle (2004) and Marsh et al. (2009) remain valid, but also are limited in their scope with respect to focusing predominantly on pragmatic and instrumental teacher-training issues. Our article suggests that the theoretical conceptualisations of video conferencing should be expanded to include elements of mimicking and ultimately improvisation. This allows us to consider not just etic aspects of practice, but equally emic practices and related personal professional development. We locate these arguments more widely in a sociocultural-theory framework, as it enables us to describe interactions in dialectical rather than dichotomous terms (Lantolf & Poehner, 2008)

Risk distribution and benefit analysis of PPP projects based on public participation

This paper aims to formulate a new PPP project public-participation mechanism that uses “public satisfaction” as a direct influencing factor in conjunction with the public-private benefit model to achieve a substantial response from project stakeholders regarding public satisfaction and ensure the transparency of PPP project operation. The proposed model, combined public satisfaction assessment with the principal-agent model, investigates the influence of public satisfaction on investors’ efforts and the benefit or risk distribution between the government and private investors. The results show that the public’s satisfaction level with the project directly affects the proportion of public and private income distribution, which provides a way for the public to directly play a substantive and positive role in PPP projects to guarantee public benefits and the smooth implementation. The increase in the public satisfaction evaluation of either the government or the investors, helps improve the overall effectiveness of PPP projects

Hyperspectral Imaging and Their Applications in the Nondestructive Quality Assessment of Fruits and Vegetables

Over the past decade, hyperspectral imaging has been rapidly developing and widely used as an emerging scientific tool in nondestructive fruit and vegetable quality assessment. Hyperspectral imaging technique integrates both the imaging and spectroscopic techniques into one system, and it can acquire a set of monochromatic images at almost continuous hundreds of thousands of wavelengths. Many researches based on spatial image and/or spectral image processing and analysis have been published proposing the use of hyperspectral imaging technique in the field of quality assessment of fruits and vegetables. This chapter presents a detailed overview of the introduction, latest developments and applications of hyperspectral imaging in the nondestructive assessment of fruits and vegetables. Additionally, the principal components, basic theories, and corresponding processing and analytical methods are also reported in this chapter

Effect of Glow Discharge Cold Plasma Treatment on Improvement of Wheat Processing Quality

In order to improve the processing quality of wheat, newly harvested wheat was treated with glow discharge cold plasma. The changes in the physicochemical properties of wheat flour and the rheological properties of wheat flour dough after the treatment were studied, and the molecular mass distribution and secondary structure of wheat flour proteins were furthermore analyzed. The results showed that the gluten index of wheat was significantly increased after cold plasma treatment with oxygen or argon as the gas source. Dough development time and stability time were improved, and the mixographic parameters midline integral at 8 min (MTxI) and midline width at 8 min (MTxW) were significantly increased (P < 0.05), while weakening slope (WS) was significantly decreased (P < 0.05). The content of macromolecular polymeric storage protein fraction F1 was increased, and the ratio between macromolecular polymeric storage protein fraction F1 and small-molecule polymeric storage protein fraction F2 was significantly increased (P < 0.05). The protein secondary structure was transformed from β-sheet and β-turn to more ordered intermolecular β-sheet. In conclusion, glow discharge cold plasma treatment changed the molecular mass distribution and secondary structure of wheat storage proteins, significantly enhanced the elasticity and mixing tolerance of dough, and improved the tensile resistance of dough, thereby enhancing the processing quality of wheat to some extent

Government subsidies in public-private partnership projects based on altruistic theory

Nowadays, the public-private partnership (PPP) scheme has been widely adopted in infrastructure projects around the world. In PPP projects, the governments participate as a principal and the investors play the role of an agent, and therefore their behaviours and incentive strategies can be explained and designed by the principal-agent theory. As “economic men” with limited rationality, both the governments and the investors have altruistic preferences during cooperation. This paper studies how project participants’ altruistic preferences affect government subsidies based on the principal-agent theory. To this end, a principal-agent model in the presence of altruism is developed. The results show that the amount of government compensation is related to the altruistic preferences, the expected revenue, costs and investors’ efforts. Contrary to intuition, the governments’ altruism actually undermines the investors’ enthusiasm in cooperation and the risk-sharing propensity, although it increases the utilities of both parties. Moreover, when selecting the investors, governments should examine their operating capacity carefully, which has a significant impact on the sustainable development of the projects and even PPP arrangements. The findings contribute new insights into the development of incentive mechanisms between governments and private investors from the perspective of the behavioural preferences. First published online 27 January 202

Study on the Emission Characteristics in Renewable Energy Combustion under Different Working Conditions of Marine Two-Stroke Diesel Engine

In this paper, MAN 6S35ME-B9 two-stroke diesel engine is taken as the research object. By constructing a detailed combustion reaction mechanism including CH4, C4H10O, nitrides and other substances, CHEMKIN-PRO is used to simulate the same fuel mixing ratio and excess air coefficient. Under the condition of 1.5, the temperature, NO mole fraction and NH3 mole fraction in the reactor change and study the factors affecting the pollutant emission of marine diesel engine with the crank angle under different working conditions. The simulation shows that with the decrease of diesel engine speed, the maximum temperature of combustion reaction and the temperature at exhaust opening are obviously reduced. At the same time, mole fraction of NO and NH3 decreases with the decrease of rotational speed, and there is no nitride production in the combustion reaction at 25%

Developing a multi-epitope vaccine candidate to combat porcine epidemic diarrhea virus and porcine deltacoronavirus co-infection by employing an immunoinformatics approach

Coinfection of porcine epidemic diarrhea virus (PEDV) and porcine deltacoronavirus (PDCoV) is common in pig farms, but there is currently no effective vaccine to prevent this co-infection. In this study, we used immunoinformatics tools to design a multi-epitope vaccine against PEDV and PDCoV co-infection. The epitopes were screened through a filtering pipeline comprised of antigenic, immunogenic, toxic, and allergenic properties. A new multi-epitope vaccine named rPPMEV, comprising cytotoxic T lymphocyte-, helper T lymphocyte-, and B cell epitopes, was constructed. To enhance immunogenicity, the TLR2 agonist Pam2Cys and the TLR4 agonist RS09 were added to rPPMEV. Molecular docking and dynamics simulation were performed to reveal the stable interactions between rPPMEV and TLR2 as well as TLR4. Additionally, the immune stimulation prediction indicated that rPPMEV could stimulate T and B lymphocytes to induce a robust immune response. Finally, to ensure the expression of the vaccine protein, the sequence of rPPMEV was optimized and further performed in silico cloning. These studies suggest that rPPMEV has the potential to be a vaccine candidate against PEDV and PDCoV co-infection as well as a new strategy for interrupting the spread of both viruses

Identification of ferroptosis-related genes in the progress of NASH

BackgroundNon-alcoholic steatohepatitis (NASH) is becoming more widespread, and some similarities exist between its etiology and ferroptosis. However, there are limited investigations on which ferroptosis-related genes (FRGs) are regulated in NASH and how to regulate them. We screened and validated the pivotal genes linked to ferroptosis in NASH to comprehend the function of ferroptosis in the development of NASH.MethodsTwo mRNA expression data were obtained from the Gene Expression Omnibus (GEO) as the training set and validation set respectively. FRGs were downloaded from FerrDb. The candidate genes were obtained from the intersection between differentially expressed genes (DEGs) and FRGs, and further analyzed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The hub genes were identified by the protein-protein interaction (PPI) network and Cytoscape. Then, FRGs closely related to the severity of NASH were identified and further confirmed using the validation set and mouse models. Ultimately, based on these genes, a diagnostic model was established to differentiate NASH from normal tissues using another data set from GEO.ResultsA total of 327 FRGs in NASH were acquired and subjected to GSEA. And 42 candidate genes were attained by overlapping the 585 FRGs with 2823 DEGs, and enrichment analysis revealed that these genes were primarily engaged in the fatty acid metabolic, inflammatory response, and oxidative stress. A total of 10 hub genes (PTGS2、IL1B、IL6、NQO1、ZFP36、SIRT1、ATF3、CDKN1A、EGR1、NOX4) were then screened by PPI network. The association between the expression of 10 hub genes and the progress of NASH was subsequently evaluated by a training set and verified by a validation set and mouse models. CDKN1A was up-regulated along with the development of NASH while SIRT1 was negatively correlated with the course of the disease. And the diagnostic model based on CDKN1A and SIRT1 successfully distinguished NASH from normal samples.ConclusionIn summary, our findings provide a new approach for the diagnosis, prognosis, and treatment of NASH based on FRGs, while advancing our understanding of ferroptosis in NASH

Computer-aided drug design for the double-membrane vesicle pore complex inhibitors against SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of the ongoing global pandemic, has constituted the worst global health disaster in recent years. However, no antiviral drugs have proved clinically efficacious to combat SARS-CoV-2 infection. The SARS-CoV-2 double-membrane vesicle (DMV) pore complex, particularly for its positively charged residues R1613, R1614, R303, R305, and R306, which are highly conserved across β-coronaviruses and play a critical role in mediating RNA transport and virus replication, has been validated as an effective drug target. Here, we employed computer-aided drug design (CADD) techniques for the first time to screen the antiviral compounds against SARS-CoV-2 by targeting the crystal structure of the SARS-CoV-2 DMV nsp3-4 pore complex. A total of 486,387 drug compounds were subjected to virtual screening, such as toxicity prediction, ADMET prediction, molecular docking, and target analysis. The six compounds (three for each binding site) were selected based on their lowest binding energies. Notably, Compound 391 demonstrated the strongest binding affinity to the critical positively charged residues R1613 and R1614 at binding site 1, meanwhile, Compound 5,157 exhibited the most stable interactions with the essential positively charged residues R303, R305, and R306 at binding site 2. These results demonstrate that Compound 391 and Compound 5,157 exhibit greater potential antiviral effects, which provide a theoretical basis for further confirmation against SARS-CoV-2 in vitro and in vivo studies