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Malnutrition has a significant effect on the onset and progression of infective pathology. The malnutrition status in COVID-19 cases are not understood well. Prognostic Nutritional Index (PNI) is a new and detailed assessment of nutrition and inflammation cases. This study aims to investigate the effect of PNI on mortality in COVID-19 patients.

In total, 334 patients (males, 142; females, 192; 64.5 ± 12.3 years of age) with COVID-19 bronchopneumonia were enrolled in this investigation. Cases were divided into two groups with respect to survival (Group 1: survivor patients, Group 2: non-survivor patients). Demographic and laboratory variables of COVID-19 cases were recorded. Laboratory parameters were calculated from blood samples taken following hospital admission. PNI was calculated according to this formula: PNI = 5 * Lymphocyte count (10⁹/L) + Albumin value (g/L).

When the patients were assessed with respect to laboratory values, leukocytes, neutrophils, CRP, ferritin, creatinine and D-Dimer parameters were significantly lower in Group 1 patients than Group 2 patients. Nevertheless, serum potassium value, lymphocyte count, calcium and albumin values were significantly higher in Group 1 cases than in Group 2 cases. PNI value was significantly lower in Group 2 cases than in Group 1 cases (39.4 ± 3.7 vs 53.1 ± 4.6).

In this retrospective study of COVID-19 cases, it can be suggested that PNI may be a significant risk factor for mortality. In conclusion of this research, high-risk patients with COVID-19 can be determined early, and suitable medical therapy can be begun in the early duration.

The integration of e-commerce platforms and artificial intelligence (AI) into the marketing channel ecosystem is challenging the explanatory capacity of traditional channel power theories, indicating a significant yet unaddressed research gap concerning the impact of these digital entities and AI on channel power exercise dynamics. This study adopts a contingency perspective to critically revisit how e-commerce platforms exercise channel power and the ensuing effects on channel conflicts. The purpose of this study is to extend the boundaries of traditional channel power theories, enhancing their relevance in today’s digital marketplace.

Building on channel power theories, the authors developed a framework tested with survey data collected from 262 sellers. This framework incorporates three key contingent variables: inter-platform competition, AI capabilities and platform value co-creation. Regression analysis was used to perform the analyses.

This study finds that intense inter-platform competition mitigates the (positive) negative relationship between platform channel power and the exercise of (non-) coercive power. Moreover, a platform’s AI capabilities and value co-creation activities diminish the potential for channel conflicts induced by the exercise of coercive power. AI capabilities can also strengthen the negative relationship between the exercise of non-coercive power and channel conflicts.

This study contributes to the advancement of traditional channel power theories by integrating contemporary digital elements like AI and platform dynamics. This study provides theoretical and practical insights on navigating channel power in modern marketing environments, offering strategic guidelines for optimizing channel relationships.

This study aims to improve the stability and obstacle surmounting ability of the traditional wall-climbing robot on the surface of the ship, a wheel-track composite magnetic adsorption wall-climbing robot is proposed in this paper.

The robot adopts a front and rear obstacle-crossing mechanism to achieve a smooth crossover. The robot is composed of two passive obstacle-crossing mechanisms and a frame, which is composed of two obstacle-crossing magnetic wheels and a set of tracks. The obstacle-crossing is realized by the telescopic expansion of the obstacle-crossing mechanism. Three static failure models are established to determine the minimum adsorption force for the robot to achieve stable motion. The Halbach array is used to construct the track magnetic circuit, and the influence of gap, contact area and magnet thickness on the adsorption force is analyzed by parameter simulation.

The prototype was designed and manufactured by the authors for static failure and obstacle crossing tests. The prototype test results show that the robot can cross the obstacle of 10 mm height under the condition of 20 kg load.

A new structure of wall-climbing robot is proposed and verified. According to the test results, the wall-climbing robot can stably climb over the obstacle of 10 mm height under the condition of 20 kg load, which provides a new idea for future robot design.

Metro stations have become a crucial aspect of urban rail transportation, integrating facilities, equipment and pedestrians. Impractical physical layout designs and pedestrian psychology impact the effectiveness of an evacuation during a metro fire. Prior research on emergency evacuation has overlooked the complexity of metro stations and failed to adequately consider the physical heterogeneity of stations and pedestrian psychology. Therefore, this study aims to develop a comprehensive evacuation optimization strategy for metro stations by applying the concept of design for safety (DFS) to an emergency evacuation. This approach offers novel insights into the management of complex systems in metro stations during emergencies.

Physical and social factors affecting evacuations are identified. Moreover, the social force model (SFM) is modified by combining the fire dynamics model (FDM) and considering pedestrians' impatience and panic psychology. Based on the Nanjing South Metro Station, a multiagent-based simulation (MABS) model is developed. Finally, based on DFS, optimization strategies for metro stations are suggested.

The most effective evacuation occurs when the width of the stairs is 3 meters and the transfer corridor is 14 meters. Additionally, a luggage disposal area should be set up. The exit strategy of the fewest evacuees is better than the nearest-exit strategy, and the staff in the metro station should guide pedestrians correctly.

Previous studies rarely consider metro stations as sociotechnical systems or apply DFS to proactively reduce evacuation risks. This study provides a new perspective on the evacuation framework of metro stations, which can guide the designers and managers of metro stations.

In the 21st century, libraries are experiencing a significant decline in users due to shifting reading habits and the impact of technology, necessitating library transformation and a heightened emphasis on library marketing. Special libraries, in particular, rely heavily on patrons for survival, often due to their private ownership and limited resources. This paper aims to discuss the aforementioned objectives.

This paper examines the Taste Library, a special library in Hong Kong, and analyzes its current practices based on an interview with its founder, website content, and social media presence. The 7Ps Marketing Mix model is employed to assess the strengths and weaknesses of the library's current market position.

The Taste Library's existing practices exhibit limitations in attracting young patrons. To address this issue, we propose marketing strategies focused on enhancing social network presence, offering digitized content, and engaging in school outreach.

By concentrating on youth marketing, this study offers valuable insights for special libraries in developing strategic plans for transitioning and maintaining sustainability.

Few studies concentrate on marketing small special libraries, particularly in the East, within today's digitized economy.

Sustainable development requires companies to achieve a long-term balance between the economic, environmental and social spheres in their development process, and is not limited to long-term commercial success. Enhancing corporate environmental, social and governance (ESG) performance plays a critical role in achieving sustainable economic and social development. The purpose of this study is to empirically examine the influence of short-selling on corporate ESG performance and unravel the mechanisms involved.

The authors use the data from Chinese A-share listed companies spanning from 2010 to 2021 as the research sample and conduct empirical research using mediating effect model, instrumental variables and difference-in-differences methods.

The findings suggest that short-selling has a positive impact on ESG performance, thus, contributing to the realization of sustainable development goals (SDGs) and achieving a balanced development of economy, environment and society, rather than only promoting corporate longevity. This can be attributed to short-selling’s ability to strengthen supervision constraints on firms, improve firms’ intrinsic capabilities and promote firms’ green technological innovation. Furthermore, the ESG-enhancing effects of short-selling are contingent upon the internal and external governance levels of the firms. That is, short-selling has a more significant effect on ESG performance enhancement for firms with weaker internal and external governance. The extended analysis finds that concerning firms’ market advantage, the positive impact of short-selling on ESG is more pronounced for firms with weak monopoly power and those facing intense industry competition. In addition, when examining firms’ individual characteristics, the ESG-enhancing effect of short-selling is more potent for nonstate-owned firms, those with a shorter listing history and those facing a heightened risk of resource mismatch.

This study provides theoretical support and empirical evidence from the perspective of short-selling to help boost corporate ESG development and improve corporate contributions to sustainable development. ESG is the concrete projection of sustainable development concept at the firm level. Good ESG performance contributes to the realization of the SDGs by influencing the strategy, operation and management of the enterprise, and promoting the enterprise to more actively create the comprehensive value of the economy, society and environment.

The results of this study show that short-selling can significantly enhance corporate ESG performance and strengthen corporate sustainability initiatives, thereby promoting the realization of SDGs at the firm level. These findings carry substantial implications, not only foster the improvement of China’s capital market system but also provide empirical evidence from China for capital market policy-making and sustainable development practices in other emerging markets.

This study not only addresses the gap in studying ESG performance from the perspective of short-selling behavior but also enriches the research on the economic consequences of short-selling and enriches the literature on the determinants of ESG performance.

This chapter explores how the development of football fandom for the Chinese national team and local football clubs is strongly associated with societal changes. Although the performances of Chinese football teams, especially the national team, have failed to impress the world, football remains the most popular because of millions of supporters with loyalty and passion. Most studies related to fans mainly focus on the economic and political implications of spectatorship along with the rise of China. Nevertheless, few articles are available to answer the fundamental questions, such as ‘When did these supporters come out?’ and ‘What were the factors of the development of fandom?’. By going through archival records and published documents over the last decades, this chapter offers a comprehensive and historical analysis of the development of football fandom in the People's Republic of China (PRC) and deals with these unanswered questions. As such, this chapter does not intend to be the most authoritative one but is one of the rare sources to lay down the foundation for research on Chinese football fandom. Furthermore, this chapter also proves that studies on football fandom can be a useful window for observing Chinese society.

During the COVID-19 pandemic, an infodemic erupted on social media, leading to a surge in negative disclosure behaviors such as expressing dissatisfaction and releasing negative emotions. By extending the elaboration likelihood model and the Big Five personality theory to the domain of online self-disclosure, we aimed to identify the factors that influence negative disclosure behavior.

We investigated how the features of negative information content, information sources and recipients’ social perceptions influence how social media users disclose negative information. We also examined the moderating roles of personality traits in this process. To validate the model and test our hypotheses, we collected cross-sectional data from 456 social media users.

Empirical results reveal that (1) information overload, topic relevance, attractiveness of information sources, peer approval of negative disclosure and social influence on negative information strengthen the intention to disclose negative information. (2) The perception of social risk weakens the intention to disclose negative information. (3) Openness to experience, extraversion and neuroticism strengthen the relationship between the intention to disclose negative information and actual disclosure behavior.

Our results not only provide new perspectives on the decision-making mechanisms behind negative disclosure behavior but also extend personality research within the context of the dissemination of negative information. Furthermore, it offers insights into negative information dissemination on social media platforms, with significant implications for various stakeholders.

The purpose of this study is to examine the role of social presence in enhancing positive behaviors in the virtual reality (VR)-based wine tourism context through an innovative approach.

Two sequential experimental studies were conducted to test proposed hypotheses using Web and head-mounted display (HMD) VR formats. Specifically, Study 1 probed the influence of social presence on mental imagery, which subsequently impacted destination visit intention, drinking intent and memorable experience. Study 2 used a field experiment to explore the boundary effects of environmental cues (nature versus social) on social presence and a series of behavioral intentions using an HMD format.

The findings represent one of the first efforts to unravel the influence of social presence on positive behaviors through mental imagery and the moderating role of environmental cues.

This research enhances the understanding of wine tourism, drawing upon social presence theory and stimulus-organism-response framework.

The outcomes provide valuable insights for wine tourism marketers in developing innovative marketing strategies by addressing the usage of social presence and environmental cues in a VR setting.

To the best of the authors’ knowledge, this study is the first to enrich the existing knowledge of wine tourism by exploring the role of social presence and environmental cues in both Web and HMD VR formats.

Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.

A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.

The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.

The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.