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This paper aims to figure out the conundrum that the corrosion resistance longevity of steel wires for bridge cables was arduous to meet the requirements.

The “two-step” hot-dip coating process for cable steel wires was developed, which involved first hot-dip galvanizing and then hot-dip galvanizing of aluminum magnesium alloy. The corrosion rate, polarization curve and impedance of Zn–6Al–1Mg and Zn–10Al–3Mg alloy-coated steel wires were compared through acetate spray test and electrochemical test, and the corrosion mechanism of Zn–Al–Mg alloy-coated steel wires was revealed.

The corrosion resistance of Zn–10Al–3Mg alloy-coated steel wires had the best corrosion resistance, which was more than seven times that of pure zinc-coated steel wires. The corrosion current of Zn–10Al–3Mg alloy-coated steel wires was lower than that of Zn–6Al–1Mg alloy-coated steel wires, whereas the capacitive arc and impedance value of the former were higher than that of the latter, making it clear that the corrosion resistance of Zn–10Al–3Mg was better than that of Zn–6Al–1Mg alloy coating. Moreover, the Zn–Al–Mg alloy-coated steel wires for bridge cables had the function of coating “self-repairing.”

Controlling the temperature and time of the hot dip galvanizing stage can reduce the thickness of transition layer and solve the problem of easy cracking of the transition layer in the Zn–Al–Mg alloy coating due to the Sandelin effect.

The “what is beautiful is good” (WIBIG) effect implies that observers tend to perceive physically attractive people in a positive light. The authors investigate how the WIBIG effect applies to user personas, measuring designers' perceptions and task performance when employing user personas for the design of information technology (IT) solutions.

In a user experiment, the authors tested six different personas with 235 participants that were asked to develop remote work solutions based on their interaction with a fictitious user persona.

The findings showed that a user persona's perceived attractiveness was positively correlated with other perceptions of the persona. The personas' completeness, credibility, empathy, likability and usefulness increased with attractiveness. More attractive personas were also perceived as more agreeable, emotionally stable, extraverted and open, and the participants spent more time engaging with personas they perceived attractive. A linguistic analysis indicated that the IT solutions created for more attractive user personas demonstrated a higher degree of affect, but for the most part, task outputs did not vary by the personas' perceived attractiveness.

The WIBIG effect applies when designing IT solutions with user personas, but its effect on task outputs appears limited. The perceived attractiveness of a user persona can impact how designers interact with and engage with the persona, which can influence the quality or the type of the IT solutions created based on the persona. Also, the findings point to the need to incorporate hedonic qualities into the persona creation process. For example, there may be contexts where it is helpful that the personas be attractive; there may be contexts where the attractiveness of the personas is unimportant or even a distraction.

The findings point to the need to incorporate hedonic qualities into the persona creation process. For example, there may be contexts where it is helpful that the personas be attractive; there may be contexts where the attractiveness of the personas is unimportant or even a distraction.

Because personas are created to closely resemble real people, the authors might expect the WIBIG effect to apply. The WIBIG effect might lead decision makers to favor more attractive personas when designing IT solutions. However, despite its potential relevance for decision making with personas, as far as the authors know, no prior study has investigated whether the WIBIG effect extends to the context of personas. Overall, it is important to understand how human factors apply to IT system design with personas, so that the personas can be created to minimize potentially detrimental effects as much as possible.

This paper aims to discuss the suitability of topic modeling as a review method, identifies and compares the machine learning (ML) research trends in five primary business organization verticals.

This study presents a review framework of published research about adopting ML techniques in a business organization context. It identifies research trends and issues using topic modeling through the Latent Dirichlet allocation technique in conjunction with other text analysis techniques in five primary business verticals – human resources (HR), marketing, operations, strategy and finance.

The results identify that the ML adoption is maximum in the marketing domain and minimum in the HR domain. The operations domain witnesses the application of ML to the maximum number of distinct research areas. The results also help to identify the potential areas of ML applications in future.

This paper contributes to the existing literature by finding trends of ML applications in the business domain through the review of published research. Although there is a growth of research publications in ML in the business domain, literature review papers are scarce. Therefore, the endeavor of this study is to do a thorough review of the current status of ML applications in business by analyzing research articles published in the past ten years in various journals.

During the COVID-19 pandemic, transitory unemployment insurance (UI) policies substantially increased unemployment benefits (UBs) and the number of eligible groups in Russia. The procedure for registering as unemployed was moved to an online platform. The present paper aims to distinguish the effect of anti-COVID-19 restrictions on unemployment from that of the transitory unemployment insurance policies.

Using 553,627 approved claims for unemployment benefits from the Russian Public Employment Service (PES) administrative records (June 2019–December 2020), monthly data on the number of individuals registered as unemployed are aggregated in a pseudo panel. A double-difference approach is employed to identify the effects of the social interaction intensity and teleworkability (TW) of the latest occupation on unemployment. The first is associated with a direct effect of anti-COVID-19 restrictions and the latter with the simplified application procedure.

The face-to-face (F2F) intensity of the latest occupation did not lead to any increase in the number of unemployed persons as could be expected in response to anti-COVID-19 restrictions. Job TW had two opposite effects on unemployment: it decreased individuals' risk of job loss and increased their likelihood of claiming unemployment benefits. Surprisingly, however, in line with the typical response of the Russian labour market to downturns, the latter dominated. The largest response was found among men and individuals with primary education.

This study is the first to attempt to distinguish the effect of anti-COVID-19 restrictions from that of the transitory UI policies on unemployment in Russia.