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Nanotechnology (NT) advancements in personal protective textiles (PPT) or personal protective equipment (PPE) have alleviated spread and transmission of this highly contagious viral disease, and enabled enhancement of PPE, thereby fortifying antiviral behavior.

Review of a series of state of the art research papers on the subject matter.

This paper expounds on novel nanotechnological advancements in polymeric textile composites, emerging applications and fight against COVID-19 pandemic.

As a panacea to “public droplet prevention,” textiles have proven to be potentially effective as environmental droplet barriers (EDBs).

PPT in form of healthcare materials including surgical face masks (SFMs), gloves, goggles, respirators, gowns, uniforms, scrub-suits and other apparels play critical role in hindering the spreading of COVID-19 and other “oral-respiratory droplet contamination” both within and outside hospitals.

When used as double-layers, textiles display effectiveness as SFMs or surgical-fabrics, which reduces droplet transmission to <10 cm, within circumference of ∼0.3%.

NT advancements in textiles through nanoparticles, and sensor integration within textile materials have enhanced versatile sensory capabilities, robotics, flame retardancy, self-cleaning, electrical conductivity, flexibility and comfort, thereby availing it for health, medical, sporting, advanced engineering, pharmaceuticals, aerospace, military, automobile, food and agricultural applications, and more. Therefore, this paper expounds on recently emerging trends in nanotechnological influence in textiles for engineering and fight against COVID-19 pandemic.

Asteroids have the characteristics of noncooperative, irregular gravity and complex terrain on the surface, which cause difficulties in successful landing for conventional landers. The purpose of this paper is to study the trajectory tracking problem of a multi-node flexible lander with unknown flexible coefficient and space disturbance.

To facilitate the stability analysis, this paper constructs a simplified dynamic model of the multi-node flexible lander. By introducing the nonlinear transformation, a concurrent learning-based adaptive trajectory tracking guidance law is designed to ensure tracking performance, which uses both real-time information and historical data to estimate the parameters without persistent excitation (PE) conditions. A data selection algorithm is developed to enhance the richness of historical data, which can improve the convergence rate of the parameter estimation and the guidance performance.

Finally, Lyapunov stability theory is used to prove that the unknown parameters can converge to their actual value and, meanwhile, the closed-loop system is stable. The effectiveness of the proposed algorithm is further verified through simulations.

This paper provides a new design idea for future asteroid landers, and a trajectory tracking controller based on concurrent learning and preset performance is first proposed.

This study aims to analyze the impact mechanism of typical environments in China's western mountainous areas on the durability of railway concrete and propose measures to improve durability.

With the continuous promotion of infrastructure construction, the focus of China's railway construction has gradually shifted to the western region. The four typical environments of large temperature differences, strong winds and dryness, high cold and low air pressure unique to the western mountainous areas of China have adverse effects on the durability of typical railway structure concrete (bridges, ballastless tracks and tunnels). This study identified the characteristics of four typical environments in the western mountainous areas of China through on-site research. The impact mechanism of the four typical environments on the durability of concrete in different structural parts of railways has been explored through theoretical analysis and experimental research; Finally, a strategy for improving the durability of railway concrete suitable for the western mountainous areas of China was proposed.

The daily temperature difference in the western mountainous areas of China is more than twice that of the plain region, which will lead to significant temperature deformation and stress in the multi-layered structure of railway ballastless tracks. It will result in cracking. The wind speed in the western plateau region is about 2.5 to 3 times that of the plain region, and the average annual rainfall is only 1/5 of that in the plain region. The drying effect on the surface of casting concrete will significantly accelerate its cracking process, leading to serious durability problems. The environmental temperature in the western mountainous areas of China is generally low, and there are more freeze-thaw cycles, which will increase the risk of freeze-thaw damage to railway concrete. The environmental air pressure in the western plateau region is only 60% of that in the plain region. The moisture inside the concrete is more likely to diffuse into the surrounding environment under the pressure difference, resulting in greater water loss and shrinkage deformation of the concrete in the plateau region. The above four issues will collectively lead to the rapid deterioration of concrete durability in the western plateau region. The corresponding durability improvement suggestions from theoretical research, new technology development and standard system was proposed in this paper.

The research can provide the mechanism of durability degradation of railway concrete in the western mountainous areas of China and corresponding improvement strategies.

The purpose of this paper is to optimize the degradation test for products subject to multiple types of inherent stresses and external random shocks. The mechanism that shows how the variables to be optimized influence the considered multiple objectives is also aimed to be explored by using the grey incidence analysis (GIA) model.

The Gamma process is employed to model the influences of different types of stresses and external random shocks. The GIA model is introduced to transfer multiple considered objectives as a comprehensive degree of grey incidence. The particle swarm optimization is integrated to search the globally optimal value of the characteristic variables to be optimized.

The acceleration of tested stresses and external random shocks both make the engineering systems become more vulnerable to the inherent degradation. And, the Kriging model can provide guidance of searching the optimal values of test characteristic variables and mitigate the computation burden. The grey incidence model can make the optimization focused and improve the optimality of objective values.

The proposed method can effectively overcome the drawbacks brought by the limitation of test data and can specify the dependence strength between the inherent degradation and external random shock. The computation cost and accuracy of optimization can be simultaneously ensured by the proposed model.

There have been numerous publications on human monkeypox since it was reported. With the help of bibliometric analysis, this study examined research hotspots and future trends related to human monkeypox. Science mapping was used in this study to identify influential monkeypox researchers, institutions, articles, keywords, thematic structures, and clusters of articles.

Based on a validated search query, bibliometric analysis of data collected from Web of Science from 1989 to September 2022 was conducted. Using the “Title-Keyword-Abstract” search option, the search query consisted of keywords “Monkeypox” OR “Monkeypox virus” OR “monkeypox” OR “monkey pox” OR “MPXV.” With the state-of-the-art tools Bibliometrix package of R Studio and VOSviewer, performance analysis and science mapping, as a part of standard bibliometric research of monkeypox research were conducted.

Researchers published 708 monkeypox papers from 1989 to September 2022, with American researchers publishing 460 papers. Further, USA had the highest international cooperation in terms of collaborative research output. Centers for Disease Control and Prevention (CDC) is a global leader in monkeypox research since it is the most prolific and collaborative organization. There have been the most published papers on monkeypox in the Journal of Virology. Damon Inger K is also the most prolific and influential researcher in monkeypox research, with the highest number of publications and citations. In total, 1,679 keywords were identified in the study. From the cluster analysis four themes were identified in monkeypox research. They are (1) clinical features, (2) monkeypox virus epidemiology, (3) monkeypox virus vaccine defense, and (4) monkeypox virus-related treatment measures.

Analysis of collaboration, findings, networks of research, and visualization separates this study from traditional metrics analysis. Currently, there are no similar studies with similar objectives based on the authors' knowledge.

This study aims to predict customers’ intention (INT) to visit green hotels through an extended norm activation model (NAM) framework. The extended NAM includes environmental concern (EC), price consciousness (PC) and aesthetic values (AEV).

A quantitative survey design was used to collect 340 valid responses from customers in Pakistan. Partial least square - structural equation modeling was used to assess the hypothesized relationships.

The results show that EC and awareness of consequences have a significant ascription of responsibility (AR) and personal norms (PN) towards INT. The results confirmed the moderating effect of PC on the relationship between PN and INT and the moderating effect of AEV on relationship between PN and INT and AR and INT. The findings indicate that PN does not mediate the relationship between AR and INT. These findings indicate that customers are aware of the consequences of resource depletion and environmental pollution that result from the unsustainable hotel practices. Therefore, customers tend to visit aesthetically green hotels at affordable prices.

The study proposes that green hotels should design marketing strategies in a way that increases customers’ awareness and concern towards environmental issues. Marketing campaigns focusing on environmental aspects of green hotels enhance its green reputation and motivate customers to visit green hotels. In addition, managers must consider enhancing the beauty of hotels at a competitive price.

This is the first study to use an extended NAM by integrating EC, average variance extracted and PC to predict customers’ INT towards green hotels. The extended NAM framework provides comprehensive understanding of the relationships between EC, AR and PN regarding visiting green hotels. In addition, the study emphasizes on AEV’s crucial role in influencing customers’ INT to visit green hotels.

This paper investigates the ways digital media applications in rural areas have transformed the influence of social networks (SN) on farmers' adoption of various climate change mitigation measures (CCMM), and explores the key mechanisms behind this transformation.

The study analyzes data from 1,002 farmers’ surveys. First, a logit model is used to measure the impact of SN on the adoption of different types of CCMM. Then, the interaction term between digital media usage (DMU) and SN is introduced to analyze the moderating effect of digital media on the impact of SN. Finally, a conditional process model is used to explore the mediating mechanism of agricultural socialization services (ASS) and the validity of information acquisition (VIA).

The results reveal that: (1) SN significantly promotes the adoption of CCMM and the marginal effect of this impact varies with different kinds of technologies. (2) DMU reinforces the effectiveness of SN in promoting farmers' adoption of CCMM. (3) The key mechanisms of the process in (2) are the ASS and the VIA.

This study shows that in the context of DMU, SN’s promotion effect on farmers' adoption of CCMM is strengthened.