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The objective of this study is to investigate how the coronavirus disease 2019 (COVID-19) pandemic affects firms' financial management in China's manufacturing sector. In addition, the authors analyze the changes in various financial indicators before and during the COVID-19 pandemic. Further, the authors make a cross-country comparison of the COVID-19's impact on financial management between China and Romania.

The study uses the balanced panel data of 2,272 manufacturing listed companies from 2019 to 2020, and applies the t-test method and multiple regression method.

The results show that firms' financial performance in most manufacturing sub-sectors decreased during the observed period. In addition, the authors find that equity financing, proper liquidity management and an expanded firm scale can improve firms' financial performance. The authors further compare the results with the Romanian results, and find that the negative impact of debt-to-equity ratio on firms' financial performance in Romania is greater than that in China and the positive impact of financial autonomy ratio and working capital ratios is greater in China than that in Romania.

The findings can help corporate managers make the best financial management decision in response to crisis.

This study is one of the pioneers that analyze how manufacturing companies carried out their financial management during the COVID-19 crisis in the Chinese context, and provides a cross-country analysis of corporate financial management practices in China and Romania.

This study aims to explore the pandemic's opportunities for enhancing the environmental practices of the food and beverages green supply chains and its effect on the supply chains' viability by exploring the relationship between fear and uncertainty of COVID-19, food and beverages green supply chain management (F&B-GSCM) and supply chains’ viability based on the two dimensions (robustness and resilience) and examine the moderating effect of innovative technology adoption like big data analysis (BDA) capabilities and blockchain technologies (BCT) on this relationship.

This study adopted partial least squares structural equation modeling (PLS-SEM) on a sample of 362 F&B small and medium enterprises (SMEs)’ managers in the Egyptian market for data analysis and hypothesis testing.

The empirical results show that the fear and uncertainty of the pandemic have a significant positive effect on green supply chain management (GSCM). Also, BDA moderates the relationship between fear and uncertainty of COVID-19 and GSCM. However, BCT do not moderate that relationship. Similarly, GSCM positively affects supply chain viability dimensions (robustness and resilience). In addition, F&B-GSCM significantly mediates the relationship between fear and uncertainty of COVID-19 and supply chain viability dimensions (robustness and resilience).

Food and beverages (F&B) managers could develop a consistent strategy for applying BCT and BDA to provide clear information and focus on their procedures to meet their stakeholders' needs during COVID-19. Governments and managers should develop a consistent strategy to apply food and beverages supply chains (F&B SCs)' green practices to achieve F&B SCs' resilience and robustness, especially during the pandemic.

The Egyptian F&B SCs have been linked directly with many European countries as a main source of many basic food and agriculture products, which have been affected lately by the pandemic. Based on the “social-cognitive,” “stakeholder” and “resource-based view” theories, this study sheds light on the optimistic side of the COVID-19 pandemic, as it also brings the concepts of F&B-GSCM, SC resilience, SC robustness and innovative technologies back into the light, which helps in solving F&B SC issues and helps to achieve their viability.

The study aims to pioneer an innovative approach for the evaluation of government portal websites (GPWs) by introducing an eye-tracking-based method. The research meticulously pinpoints and analyses the distinct usability issues and challenges that users encounter while navigating and interacting with GPWs.

This study devises an eye-tracking-based GPW usability evaluation approach, which focuses on the major functions (i.e. government information disclosure, government services and interactive responses) of GPWs. An Entropy Weighted Technique for Order Preference by Similarity to an Ideal Solution (EW-TOPSIS) method is employed to process eye-tracking indicator results for deriving GPW usability results.

The proposed approach is demonstrated to assess the usability of 12 GPWs in pilot smart cities in China, and it is found that most GPWs have lower-than-average usability. GPWs with low usability require more cognitive load that exhibit increased fixation and saccade. The comparisons among the GPW usability results from (1) the eye-tracking experiment, (2) questionnaire surveys and (3) the ready-made performance evaluation report validate the effectiveness of eye-tracking-based GPW usability evaluation.

The work contributes to shifting the GPW usability evaluation approach from a subjective judgment paradigm to an objective paradigm, as well as provides implications for enhancing GPW usability, including improving search function, reducing website complexity and prioritizing user needs.

Human group behavior is the driving force behind many complex social and economic phenomena. Few studies have integrated multi-dimensional travel patterns and city interest points to construct urban security risk indicators. This paper combines traffic data and urban alarm data to analyze the safe travel characteristics of the urban population. The research results are helpful to explore the diversity of human group behavior, grasp the temporal and spatial laws and reveal regional security risks. It provides a reference for optimizing resource deployment and group intelligence analysis in emergency management.

Based on the dynamics index of group behavior, this paper mines the data of large shared bikes and ride-hailing in a big city of China. We integrate the urban interest points and travel dynamic characteristics, construct the urban traffic safety index based on alarm behavior and further calculate the urban safety index.

This study found significant differences in the travel power index among ride-sharing users. There is a positive correlation between user shared bike trips and the power-law bimodal phenomenon in the logarithmic coordinate system. It is closely related to the urban public security index.

Based on group-shared dynamic index integrated alarm, we innovatively constructed an urban public safety index and analyzed the correlation of travel alarm behavior. The research results fully reveal the internal mechanism of the group behavior safety index and provide a valuable supplement for the police intelligence analysis.

This study aims to examine the current state of academic research pertaining to the role played by artificial intelligence (AI) in the achievement of a critical sustainable development goal (SDG) – poverty alleviation and describe the field’s development by identifying themes, trends, roadblocks and promising areas for the future.

The authors analysed a corpus of 253 studies collected from the Scopus database to examine the current state of the academic literature using bibliometric methods.

This paper identifies and analyses key trends in the evolution of this domain. Further, the paper distils the extant literature to unpack the intermediary mechanisms through which AI and related technologies help tackle the critical global issue of poverty.

The corpus of literature used for the analysis is limited to English language studies from the Scopus database. The paper contributes to the extant research on AI for social good, and more broadly to the research on the value of emerging technologies such as AI.

Policymakers and government agencies will get an understanding of how technological interventions such as AI can help achieve critical SDGs such as poverty alleviation (SDG-1).

The primary focus of this paper is on the role of AI-related technological interventions to achieve a significant social objective – poverty alleviation.

To the best of the authors’ knowledge, this is the first study to conduct a comprehensive bibliometric analysis of a critical research domain such as AI and poverty alleviation.

Intense interest has been shown in creating new and effective biocide agents as a result of changes in bacterial isolates, bacterial susceptibility to antibiotics, an increase in patients with burns and wounds and the difficulty of treating infections and antimicrobial resistance. Woven, nonwoven and knitted materials are used to make dressings; however, nonwoven dressings are becoming more popular because of their softness and high absorption capacity. Additionally, textiles have excellent geometrical, physical and mechanical features including three-dimensional structure availability, air, vapor and liquid permeability, strength, extensibility, flexibility and diversity of fiber length, fineness and cross-sectional shapes. It is necessary to treat every burn according to international protocol and along with it has to focus on particular problems of patients and the best possible results.

The objective of this paper is to conduct a thorough examination of research pertaining to the utilization of textiles, as well as alternative materials and innovative techniques, in the context of burn wound dressings. Through a critical analysis of the findings, this study intends to provide valuable insights that can inform and guide future research endeavors in this field.

In the past years, there have been several dressings such as xeroform petrolatum gauze, silver-impregnated dressings, biological dressings, hydrocolloid dressings, polyurethane film dressings, silicon-coated nylon dressings, dressings for biosynthetic skin substitutes, hydrogel dressings, newly developed dressings, scaffold bandages, Sorbalgon wound dressing, negative pressure therapy, enzymatic debridement and high-pressure water irrigation developed for the fast healing of burn wounds.

This research conducts a thorough analysis of the role of textiles in modern burn wound dressings.

This study examines the non-linear effect of board independence on the investment efficiency of listed firms worldwide. This study further tests whether the COVID-19 pandemic, industry competition and economic development influence the relationship between board independence and investment efficiency.

The data are retrieved from the Thomson Reuters (Refinitiv) database and include international data from 33 countries, comprising 21,363 firm-year observations. The authors' regression analyses include firm-specific variables as controls that may impact investment efficiency. The authors also perform various robustness tests including, alternative measures of investment efficiency, weighted least squares regression, quantile regression and endogeneity issues.

The results reveal a non-linear relationship between board independence and investment efficiency. Specifically, the relationship follows a U-shaped pattern, indicating that the negative impact of board independence on investment efficiency becomes positive after it reaches its optimal point, thus supporting optimal board structure theory. Interestingly, the authors find no significant evidence of board independence’s effect on investment efficiency during the pandemic. In contrast, the relationship between board independence and investment efficiency is significant only during the non-pandemic period. Furthermore, the authors discover evidence of a U-shaped relationship in both emerging and developed markets, as well as in industries with high and low competition.

The authors' study discovers new evidence on the non-linear impact of board independence on investment efficiency, which has not been explored previously in existing research.

This study has practical implications for investors by emphasising the importance of corporate governance and the appointment of independent directors. Investors should consider the findings of this study when making decisions related to corporate governance, as they can impact a firm's investment efficiency.

Despite a considerable body of literature exploring the link between corporate governance and investment effectiveness, there is a dearth of research on the non-linear effects of board independence. Furthermore, the effects of the COVID-19 pandemic, industry competition and economic development remain unexplored.

This paper aims to understand the scholarly contributions to mobile advertising by analyzing the publishing trend from 2001 to 2022 from the documents indexed in the Scopus database.

A total of 348 documents were selected for analysis published between 2001 and 2022. The garnered data was examined using a bibliometric domain mapping analysis technique using computer-aided software R and VOSviewer and manually exploring the articles.

The results of this study discover the most prolific authors in the mobile advertising domain and other seminal works carried out by productive researchers in the field of mobile advertising. The journals in which most instrumental research studies have been published are also identified. Moreover, the co-citation, bibliometric coupling and co-occurrence analysis of literature are also carried out to draw themes concerning mobile advertising research that have been identified and categorized.

This research analyzed a singular, exclusive database, “Scopus,” which limited the sectoral scope of publications. Since the present research uses bibliometric analysis, these studies cannot conduct sentiment analysis of the chosen studies.

Marketing professionals looking after technological advancements may use this study to understand the broad scope of mobile advertising applicability across diverse domains and discuss the trade-offs that may address significant bottlenecks in mobile advertising applications.

To the best of the authors’ knowledge, this paper is one of the latest attempts in recent times to understand the research work in mobile advertising using a bibliometric domain analysis approach.

Devices for step estimation are body-worn devices used to compute steps taken and/or distance covered by the user. Even though textiles or clothing are foremost to come to mind in terms of articles meant to be worn, their prominence among devices and systems meant for cadence is overshadowed by electronic products such as accelerometers, wristbands and smart phones. Athletes and sports enthusiasts using knee sleeves should be able to track their performances and monitor workout progress without the need to carry other devices with no direct sport utility, such as wristbands and wearable accelerometers. The purpose of this study thus is to contribute to the broad area of wearable devices for cadence application by developing a cheap but effective and efficient stride measurement system based on a knee sleeve.

A textile strain sensor is designed by weft knitting silver-plated nylon yarn together with nylon DTY and covered elastic yarn using a 1 × 1 rib structure. The area occupied by the silver-plated yarn within the structure served as the strain sensor. It worked such that, upon being subjected to stress, the electrical resistance of the sensor increases and in turn, is restored when the stress is removed. The strip with the sensor is knitted separately and subsequently sewn to the knee sleeve. The knee sleeve is then connected to a custom-made signal acquisition and processing system. A volunteer was employed for a wearer trial.

Experimental results establish that the number of strides taken by the wearer can easily be correlated to the knee flexion and extension cycles of the wearer. The number of peaks computed by the signal acquisition and processing system is therefore counted to represent stride per minute. Therefore, the sensor is able to effectively count the number of strides taken by the user per minute. The coefficient of variation of over-ground test results yielded 0.03%, and stair climbing also obtained 0.14%, an indication of very high sensor repeatability.

The study was conducted using limited number of volunteers for the wearer trials.

By embedding textile piezoresistive sensors in some specific garments and or accessories, physical activity such as gait and its related data can be effectively measured.

To the best of our knowledge, this is the first application of piezoresistive sensing in the knee sleeve for stride estimation. Also, this study establishes that it is possible to attach (sew) already-knit textile strain sensors to apparel to effectuate smart functionality.

This study aims to propose that the corrosion resistance of the neat epoxy coating can be further enhanced by incorporating reinforcing agents.

Chitosan, silica and their hybrid compound were used to study the subject of corrosion resistance of epoxy coating systems. This work used 3.5 Wt.% NaCl solution as the electrolyte, and electrochemical impedance spectroscopy (EIS) was used to investigate the electrochemical behaviour of the studied coating systems. Standard and accelerated states were used without and with scratch on the coating layer.

It was found that the impedance value of composite coating incorporated with the hybrid compound was significantly higher at 10¹⁰ Ω after 14 days of exposure in both testing states. The breakpoint frequency (f_b) determination also proves with large capacitive region at low-to-high frequency of impedance plots corresponding to the high corrosion resistance.

The hybrid compound consisting of chitosan as organic biopolymer and silica as inorganic material, respectively, served as a promising reinforcing agent for composite coating as a promising corrosion inhibitor. Different states of EIS measurement were used which are standard (without scratch) and accelerated (with scratch) states associated with the f_b values.