COVID-19: potential effects on Chinese citizens’ lifestyle and travel

Purpose: The 2019 novel coronavirus (COVID-19) outbreak is projected to have adverse consequences on the global tourism and hospitality industry. This paper aims to examine how the outbreak may alter Chinese tourists’ lifestyle choices, travel behaviour and tourism preferences in the short and long term. Design/methodology/approach: This paper is based on the synthesis of news broadcasted by several media outlets to be supported by an overview of the related literature on tourism marketing, tourism management and tourist behaviour. The authors’ experiences investigating trends in tourism and hospitality at the local and international level have also contributed to the study. Findings: This paper predicts that COVID-19 will likely affect Chinese travellers’ consumption patterns, such as the growing popularity of free and independent travel, luxury trips and health and wellness tourism. New forms of tourism including slow tourism and smart tourism may also drive future tourism activities. Such changes are likely to force businesses to reconsider their service designs and distribution channels. Research limitations/implications: While Chinese and other potential visitors rethink how they travel, professionals, too, should reflect upon how to bring positive or negative changes to the tourism industry following this pandemic. Subsequent research should also consider how to mitigate the effects of similar public health crises in the future. Practical implications: Recommendations for industry practitioners and policymakers focus on tailoring travel arrangements to tourists’ backgrounds. The suggestions may help to alleviate outbreak-related stress, offer travellers newly enriching experiences and partially mitigate the effects of COVID-19 on the tourism and hospitality industry. These recommendations can also apply more broadly to global tourist markets. Social implications: The COVID-19 outbreak has already brought significant impacts to nearly every society and industry. Tourism scholars and practitioners should carefully consider this tragedy and how it may inform industry and social practices. This and other public health crises represent sterling opportunities to view the industry holistically in terms of its effects on the environment, climate and travellers themselves. Originality/value: This paper presumably represents a frontier study, critically examining the possible impacts of COVID-19 on Chinese travellers’ consumption patterns and how the tourism and hospitality industry may respond to such changes in the future

On the local convergence of the semismooth Newton method for composite optimization

Existing superlinear convergence rate of the semismooth Newton method relies on the nonsingularity of the B-Jacobian. This is a strict condition since it implies that the stationary point to seek is isolated. In this paper, we consider a large class of nonlinear equations derived from first-order type methods for solving composite optimization problems. We first present some equivalent characterizations of the invertibility of the associated B-Jacobian, providing easy-to-check criteria for the traditional condition. Secondly, we prove that the strict complementarity and local error bound condition guarantee a local superlinear convergence rate. The analysis consists of two steps: showing local smoothness based on partial smoothness or closedness of the set of nondifferentiable points of the proximal map, and applying the local error bound condition to the locally smooth nonlinear equations. Concrete examples satisfying the required assumptions are presented. The main novelty of the proposed condition is that it also applies to nonisolated stationary points.Comment: 25 page

A Semipersistent Plant Virus Differentially Manipulates Feeding Behaviors of Different Sexes and Biotypes of Its Whitefly Vector.

It is known that plant viruses can change the performance of their vectors. However, there have been no reports on whether or how a semipersistent plant virus manipulates the feeding behaviors of its whitefly vectors. Cucurbit chlorotic yellows virus (CCYV) (genus Crinivirus, family Closteroviridae) is an emergent plant virus in many Asian countries and is transmitted specifically by B and Q biotypes of tobacco whitefly, Bemisia tabaci (Gennadius), in a semipersistent manner. In the present study, we used electrical penetration graph (EPG) technique to investigate the effect of CCYV on the feeding behaviors of B. tabaci. The results showed that CCYV altered feeding behaviors of both biotypes and sexes of B. tabaci with different degrees. CCYV had stronger effects on feeding behaviors of Q biotype than those of B biotype, by increasing duration of phloem salivation and sap ingestion, and could differentially manipulate feeding behaviors of males and females in both biotype whiteflies, with more phloem ingestion in Q biotype males and more non-phloem probing in B biotype males than their respective females. With regard to feeding behaviors related to virus transmission, these results indicated that, when carrying CCYV, B. tabaci Q biotype plays more roles than B biotype, and males make greater contribution than females

When Less is Enough: Positive and Unlabeled Learning Model for Vulnerability Detection

Automated code vulnerability detection has gained increasing attention in recent years. The deep learning (DL)-based methods, which implicitly learn vulnerable code patterns, have proven effective in vulnerability detection. The performance of DL-based methods usually relies on the quantity and quality of labeled data. However, the current labeled data are generally automatically collected, such as crawled from human-generated commits, making it hard to ensure the quality of the labels. Prior studies have demonstrated that the non-vulnerable code (i.e., negative labels) tends to be unreliable in commonly-used datasets, while vulnerable code (i.e., positive labels) is more determined. Considering the large numbers of unlabeled data in practice, it is necessary and worth exploring to leverage the positive data and large numbers of unlabeled data for more accurate vulnerability detection. In this paper, we focus on the Positive and Unlabeled (PU) learning problem for vulnerability detection and propose a novel model named PILOT, i.e., PositIve and unlabeled Learning mOdel for vulnerability deTection. PILOT only learns from positive and unlabeled data for vulnerability detection. It mainly contains two modules: (1) A distance-aware label selection module, aiming at generating pseudo-labels for selected unlabeled data, which involves the inter-class distance prototype and progressive fine-tuning; (2) A mixed-supervision representation learning module to further alleviate the influence of noise and enhance the discrimination of representations.Comment: This paper is accepted by ASE 202

Viewpoint of suicide travel: An exploratory study on YouTube comments

Tourism is often associated with recreation, leisure, or business; suicide travel—visiting a destination for the explicit purpose of ending one's life under a physician's guidance—starkly opposes traditional tourism definitions. Although physician-assisted suicide has been a focus of ethical debate, perceptions of suicide travel have not yet been addressed in the literature. This study presents a thematic content analysis of online comments to uncover people's reactions to physician-assisted suicide in a tourism context. Findings suggest that human rights, religion, legal issues, and fear of the dying process shape people's stances. Suicide travel can also include preliminary (i.e., informational) journeys. This study enhances knowledge about suicide travel, provides insight for tourism operators, and identifies relevant benefits

BIM supported collaborative design and application for waterway infrastructure

Collaborative design is the core element for BIM implementation, this paper introduces an Autodesk based cloud platform, which integrates different technologies, software, component library and functions extension, to conduct complex design collaboratively with high efficiency. An extension project in Chongqing harbour is used as a case study to demonstrate the easy use and practicability of the developed platform, including 3D terrain modelling / geology modelling, collaboration, pipeline layout, clash detection, structural analysis and so on

BIM supported collaborative design and application for waterway infrastructure

Collaborative design is the core element for BIM implementation, this paper introduces an Autodesk based cloud platform, which integrates different technologies, software, component library and functions extension, to conduct complex design collaboratively with high efficiency. An extension project in Chongqing harbour is used as a case study to demonstrate the easy use and practicability of the developed platform, including 3D terrain modelling / geology modelling, collaboration, pipeline layout, clash detection, structural analysis and so on