The disposal of organic pollutants is one of the important research topics. Some of the studies in this field are based on the degradation of organic pollutants with a catalytic agent. The cobalt tetraoxide/peroxymonosulfate system is an important catalytic system used for the radical degradation of organic pollutants. To increase the catalytic efficiency of such reactions, graphitization of activated carbon used as a support solid and nitrogen doping to the carbon structure are commonly used methods. In this study, cobalt tetraoxide production, N-doping and graphitization were carried out in a single step by heat treatment of activated carbon doped with the phthlocyanine cobalt (II) complex. The catalytic performance of the catalyst/ peroxymonosulfate system was investigated by changing the pH, catalyst, and PMS concentration parameters on rhodamine B and 1,3,5 trichlorophenol, which were used as models. It was seen that the catalysts had 97% activity on rhodamine B in 16 min and 100% on 1,3,5 trichlorophenol in 6 min. It was observed that the catalysts continued to show high catalytic activity for five cycles in reusability studies and had a very low cobalt leaching rate. These results are in good agreement with previously published studies. In line with these results, the synthesized N-doped graphitic carbon/Co3O4 catalyst can be used as an effective catalyst for wastewater treatments.

There has been a tectonic shift in the trade relationship between the United States (US) and China. This can be seen in the passage of new US legislation, recent US trade restrictions on exports and investment transactions with China, and worsening US relations with the World Trade Organization (WTO), particularly with its dispute resolution system. The Trump administration initiated a haphazard tariff and trade war with China, reversing decades of US trade policy pursuant to its long-standing stances of supporting free trade. To the dismay of many in the trade community within the US and globally, the trade actions by President Trump have been significantly extended and broadened by the Biden administration in its first two years, despite the expectation that it would reverse many of Trump’s policies. In this article, I present seven observations concerning President Trump’s and President Biden’s trade policies.

Customer loyalty is tested every day in the retail sector and the past years have been challenging for retailers to keep their existing, loyal customers. Covid-19 outbreak caused significant changes in consumers’ purchasing behavior because during the pandemic, consumers were forced to adapt new patterns of shopping which is likely to reflect also in customer loyalty. To better understand the temporal development of customer loyalty, we investigate how cognitive, affective, and social drivers of loyalty differ between 10,044 Trustpilot reviews before, during and after the Covid-19 pandemic. We investigate customer loyalty in the retail sector using an objective and a novel approach; thus we based this study on user-generated content in the form of online reviews in contrast to the traditional survey-based measures of customer loyalty.

Social media has become popular in both business and research as many studies have explored the impact of this medium on the purchase behavior of consumers but surprisingly not in the domain of counterfeiting. Social media has become a significant part of today's lifestyle and it has created new channels for brand manufacturers and consumers to communicate. The present study tries to assess the impact of social media determinants on counterfeit purchase intention. The study explored three factors of social media namely social media platform, user-generated content, and social media word of mouth. Further, the study checks for the mediation effect of consumer attitude between social media determinants and purchase intention. The data for the present study were collected from three metropolitan cities of India namely Delhi, Kolkata, and Mumbai. The PLS-SEM was used on 406 respondents for further analysis and validation. The results revealed that there is a significant relationship between social media platforms, user-generated content, and purchase intention. However, an insignificant relationship was found between social media word of mouth and purchase intention. Further, the study suggested that attitude mediates the relationship between social media determinants and the purchase intention of consumers towards the purchase of counterfeit products in India.

The subscription model, prominent within the ‘subscription economy’ (SE), is now a popular form of business within many industries. In simple terms, a subscription model entails two parties (customers and firms) entering into an agreement whereby the patron commits to make regular payments to the supplier, who in exchange periodically delivers an agreed bundle of goods and/or services. Although mostly applied within Business-to-Consumer (B2C) markets (e.g. entertainment services, newspapers and media industry, software licences), the subscription model can be found in Business-to-Business (B2B) markets also (e.g. Rolls Royce ‘Power-by-the-hour model’). This unique form of commerce (i.e. committed repeat patronage) creates an alternative relationship between the buyer and seller to other more traditional forms of business.

The use of AI chatbots in frontline customer service is beneficial as it can provide quick service responses, cost-saving on human employees and accelerate customers’ decision-making process. However, implementing chatbots can be a double-edged sword. On the one hand, companies benefit from the use of chatbots. On the other hand, it may hurt customer experience as customers perceive chatbots are less trustworthy and show less social presence. Service failures today have become more unpredictable with the increasing complexity of social environments. Aligning with the trends of online customer service, customers are most likely to encounter a chatbot when seeking online customer service to solve service failures. With most of the previous literature investigating customers’ perceptions of chatbots and chatbot-related service failures, little research has focused on the area where chatbots as service recovery agents and how customers perceive the use of chatbots handling their service requests after service failures.

Over the last decade, the COBRAs have attracted the attention of researchers in relation to their motives or outcome for the brand. However, the corpus of literature on COBRAs still is at a nascent stage and has created new opportunities pertaining to knowledge development. Undoubtedly, there is a clear need for some structure through mapping the research terrain to guide future research and further its development. Thus, a systematic review methodology was performed producing a top-quality pool of 35 papers that forge a robust understanding of this phenomenon. This research is the first study to perform a systematic review to examine the literature on COBRAs. Based on this, the findings contribute to theoretical knowledge, with extensive opportunities for generating novel theory and new forms of marketing practices.

Today’s society has become increasingly sensitive to humanity’s impact on the environment. Corporations are now measured by their scores pertaining to the environment, sustainability, and governance, or benchmarked for their level of corporate social responsibility. Another dimension of individuals’ environmental practices is purchasing merchandise such as clothing in the secondhand market. Consumers’ intention to buy in the secondhand market is rarely just related to economic concerns regarding such purchases, but rather to a deliberate nod to utilizing products fully rather than wasting them, therefore helping to reduce the negative environmental impact caused by human activities.

The GMT-Consortium Large Earth Finder (G-CLEF) is the first instrument for the Giant Magellan Telescope (GMT). G-CLEF is a fiber feed, optical band echelle spectrograph that is capable of extremely precise radial velocity measurement. G-CLEF Flexure Control Camera (FCC) is included as a part in G-CLEF Front End Assembly (GCFEA), which monitors the field images focused on a fiber mirror to control the flexure and the focus errors within GCFEA. FCC consists of an optical bench on which five optical components are installed. The order of the optical train is: a collimator, neutral density filters, a focus analyzer, a reimager and a detector (Andor iKon-L 936 CCD camera). The collimator consists of a triplet lens and receives the beam reflected by a fiber mirror. The neutral density filters make it possible a broad range star brightness as a target or a guide. The focus analyzer is used to measure a focus offset. The reimager focuses the beam from the collimator onto the CCD detector focal plane. The detector module includes a linear translator and a field de-rotator. We performed thermoelastic stress analysis for lenses and their mounts to confirm the physical safety of the lens materials. We also conducted the global structure analysis for various gravitational orientations to verify the image stability requirement during the operation of the telescope and the instrument. In this article, we present the opto-mechanical detailed design of G-CLEF FCC and describe the consequence of the numerical finite element analyses for the design.

The incorporation of vertically aligned carbon nanotubes (VACNTs) between composites plies has been said to enhance the through-thickness strength, and it can also decrease the risk of interply delamination and reduce crack initiation. Thanks to these high mechanical performances, nano-engineered hybrid composites are seen as promising for highly demanding structural reinforcement applications. This paper is part of a study that focuses specifically on the methodology for transferring VACNTs onto a prepreg surface while maintaining their initial vertically aligned morphology. The chosen method involved bonding the VACNTs’ forest through capillary impregnation of the forest by the prepreg’s resin. Key parameters for an effective transfer and to achieve a partial capillary rise of the resin into the VACNTs will be discussed here.

This study investigated the role of competition in academic settings by conceptualizing competitive engagement and examining how competition self-efficacy defined as confidence in one’s ability to outperform others could mediate learner engagement and self-determination to learn English as a foreign language (EFL). Within the context of a videoconference EFL course, a cross-sectional research design was employed during the fourth semester of remote teaching in South Korea due to COVID-19. Statistically significant relationships existed among variables. Students reported high levels of cognitive and behavioral engagement but low levels of competitive engagement. Through structural modeling, competitive engagement emerged as a conceptually unique form of engagement. The relationship between competitive engagement and selfdetermination to learn English when attending an EFL videoconference course was fully mediated by competition self-efficacy. Partial mediation was observed in the relationship between cognitive engagement and self-determination. These findings suggest that both competitive and cognitive engagement are powerful indicators of learning outcomes, especially when learning EFL.

The ability to both assay the presence of, and to selectively remove ions in a solution is an important tool for waste water treatment in many industrial sectors, especially the nuclear industry. Nuclear waste streams contain high concentrations of heavy metals ions and radionuclides, which are extremely toxic and harmful to the environment, wildlife and humans. For the UK nuclear industry alone, it is estimated that there will be 4.9 million metric tonnes of radioactive waste by 2125, which contains a significant number of toxic radionuclides and heavy metals. This is exacerbated further by increased international growth of nuclear new build and decommissioning. Efforts to remove radionuclides have been focused on the development and optimisation of current separation and sequestering techniques as well as new technologies. Due to the large volumes of waste the techniques must be economical, simple to use and highly efficient in application. Magnetic nanoparticles (MNPs) offer a powerful enhancement of normal ion exchange materials in that they can be navigated to specific places using external magnetic fields and hence can be used to investigate challenges such as, pipework in preparation of decommissioning projects. They also have the potential to be fine-tuned to extract a variety of other radionuclides and toxic heavy metals. It has been demonstrated that with the right functional groups these particles become very strongly selective to radionuclides, such as Uranium. However, this new technology also has the potential to effectively aid nuclear waste remediation at a low cost for the separation of both radionuclides and heavy metals. In this work, we investigate the origin of the selectivity of superparamagnetic iron oxide nanoparticles (SPIONs) to Uranium by making systematic changes to the existing surface chemistry and determining how these changes influence the selectivity. Identifying the mechanism by which selected common nuclear related metals, such as Na(I), K(I), Cs(I), Ca(II), Cu(II), Co(II), Ni(II), Cd(II), Mg(II), Sr(II), Pb(II), Al(III), Mn(II), Eu(III) and Fe(III), are sorbed will allow for specific NP-target (nanoparticle) ion interactions to be revealed. Ultimately this understanding will provide guidance in the design of new targeted NP-ligand constructs for other environmental systems.