Finding Truth in Cause-Related Advertising: A Lexical Analysis of Brands’ Health, Environment, and Social Justice Communications on Twitter

Consumers increasingly desire to make purchasing decisions based on factors such as health, the environment, and social justice. In response, there has been a commensurate rise in cause-related marketing to appeal to socially-conscious consumers. However, a lack of regulation and standardization makes it difficult for consumers to assess marketing claims; this is further complicated by social media, which firms use to cultivate a personality for their brand through frequent conversational messages. Yet, little empirical research has been done to explore the relationship between cause-related marketing messages on social media and the true cause alignment of brands. In this paper, we explore this by pairing the marketing messages from the Twitter accounts of over 1,000 brands with third-party ratings of each brand with respect to health, the environment, and social justice. Specifically, we perform text regression to predict each brand’s true rating in each dimension based on the lexical content of its tweets, and find significant held-out correlation on each task, suggesting that a brand’s alignment with a social cause can be somewhat reliably signaled through its Twitter communications — though the signal is weak in many cases. To aid in the identification of brands that engage in misleading cause-related communication as well as terms that more likely indicate insincerity, we propose a procedure to rank both brands and terms by their volume of “conflicting” communications (i.e., “greenwashing”). We further explore how cause-related terms are used differently by brands that are strong vs. weak in actual alignment with the cause. The results provide insight into current practices in causerelated marketing in social media, and provide a framework for identifying and monitoring misleading communications. Together, they can be used to promote transparency in causerelated marketing in social media, better enabling brands to communicate authentic valuesbased policy decisions, and consumers to make socially responsible purchase decisions

ExtrudeNet: Unsupervised Inverse Sketch-and-Extrude for Shape Parsing

Sketch-and-extrude is a common and intuitive modeling process in computer aided design. This paper studies the problem of learning the shape given in the form of point clouds by inverse sketch-and-extrude. We present ExtrudeNet, an unsupervised end-to-end network for discovering sketch and extrude from point clouds. Behind ExtrudeNet are two new technical components: 1) an effective representation for sketch and extrude, which can model extrusion with freeform sketches and conventional cylinder and box primitives as well; and 2) a numerical method for computing the signed distance field which is used in the network learning. This is the first attempt that uses machine learning to reverse engineer the sketch-and-extrude modeling process of a shape in an unsupervised fashion. ExtrudeNet not only outputs a compact, editable and interpretable representation of the shape that can be seamlessly integrated into modern CAD software, but also aligns with the standard CAD modeling process facilitating various editing applications, which distinguishes our work from existing shape parsing research. Code is released at https://github.com/kimren227/ExtrudeNet.Comment: Accepted to ECCV 202

Quantitative control of idealized analysis models of thin designs

When preparing a design model for engineering analysis, model idealization is often used, where defeaturing, and/or local dimension reduction of thin regions, are carried out. This simplifies the analysis, but quantitative estimates of the idealization error, the analysis error caused by this idealization, are necessary if the results are to be of practical use. The paper focuses on a posteriori estimation of such idealization error, via both a theoretical analysis and practical algorithms. Our approach can compute bounds for the errors induced by dimension reduction, defeaturing or both in combination. Performance of our error estimate is demonstrated using examples

Primary prevention for risk factors of ischemic stroke with Baduanjin exercise intervention in the community elder population: study protocol for a randomized controlled trial

BACKGROUND: Stroke is a major cause of death and disability in the world, and the prevalence of stroke tends to increase with age. Despite advances in acute care and secondary preventive strategies, primary prevention should play the most significant role in the reduction of the burden of stroke. As an important component of traditional Chinese Qigong, Baduanjin exercise is a simple, safe exercise, especially suitable for older adults. However, current evidence is insufficient to inform the use of Baduanjin exercise in the prevention of stroke. The aim of this trail is to systematically evaluate the prevention effect of Baduanjin exercise on ischemic stroke in the community elder population with high risk factors. METHODS: A total of 170 eligible participants from the community elder population will be randomly allocated into the Baduanjin exercise group and usual physical activity control group in a 1:1 ratio. Besides usual physical activity, participants in the Baduanjin exercise group will accept a 12-week Baduanjin exercise training with a frequency of five days a week and 40 minutes a day. Primary and secondary outcomes will be measured at baseline, 13 weeks (at end of intervention) and 25 weeks (after additional 12-week follow-up period). DISCUSSION: This study will be the randomized trial to evaluate the effectiveness of Baduanjin exercise for primary prevention of stroke in community elder population with high risk factors of stroke. The results of this trial will help to establish the optimal approach for primary prevention of stroke. TRIAL REGISTRATION: Chinese Clinical Trial Registry: ChiCTR-TRC-13003588. Registration date: 24 July, 2013

Everyday-Life Business Deviance Among Chinese SME Owners

Despite its prevalence in emerging economies, everyday-life business deviance (EBD) and its antecedents have received surprisingly little research attention. Drawing on strain theory and the business-ethics literature, we develop a socio-psychological explanation for this deviance. Our analysis of 741 owners of Chinese small- and medium-sized enterprises (SMEs) suggests that materialism and trust in institutional justice affect EBD both directly and indirectly in a relationship mediated by the ethical standards of SME owners. These findings have important implications for researching deviant business behavior within SMEs

MET-Meme : a multimodal meme dataset rich in metaphors

Memes have become the popular means of communication for Internet users worldwide. Understanding the Internet meme is one of the most tricky challenges in natural language processing (NLP) tasks due to its convenient non-standard writing and network vocabulary. Recently, many linguists suggested that memes contain rich metaphorical information. However, the existing researches ignore this key feature. Therefore, to incorporate informative metaphors into the meme analysis, we introduce a novel multimodal meme dataset called MET-Meme, which is rich in metaphorical features. It contains 10045 text-image pairs, with manual annotations of the metaphor occurrence, sentiment categories, intentions, and offensiveness degree. Moreover, we propose a range of strong baselines to demonstrate the importance of combining metaphorical features for meme sentiment analysis and semantic understanding tasks, respectively. MET-Meme, and its code are released publicly for research in \urlhttps: //github.com/liaolianfoka/MET-Meme-A-Multi-modal-Meme-Dataset-Rich-in-Metaphors. © 2022 ACM

Assessing Spatial Accessibility to Medical Resources at the Community Level in Shenzhen, China

Spatial accessibility to medical resources is an integral component of universal health coverage. However, research evaluating the spatial accessibility of healthcare services at the community level in China remains limited. We assessed the community-level spatial access to beds, doctors, and nurses at general hospitals and identified the shortage areas in Shenzhen, one of the fastest growing cities in China. Based on hospital and population data from 2016, spatial accessibility was analyzed using several methods: shortest path analysis, Gini coefficient, and enhanced 2-step floating catchment area (E2SFCA). The study found that 99.9% of the residents in Shenzhen could get to the nearest general hospital within 30 min. Healthcare supply was much more equitable between populations than across communities in the city. E2SFCA scores showed that the communities with the best and worst hospital accessibility were found in the southwest and southeast of the city, respectively. State-owned public hospitals still dominated the medical resources supply market and there was a clear spatial accessibility disparity between private and public healthcare resources. The E2SFCA scores supplement more details about resource disparity over space than do crude provider-to-population ratios (PPR) and can help improve the efficiency of the distribution of medical resources

Study of the Properties of Full Component Recycled Dry-Mixed Masonry Mortar and Concrete Prepared from Construction Solid Waste

Solutions are needed to solve the problem of a large amount of construction solid waste and a shortage of natural aggregate (coarse and fine aggregates). In this paper, simple-crushed coarse aggregate (SCRCA) and simple-crushed fine aggregate (SCRFA) were obtained by simple-crushing of construction solid waste. On this basis, SCRCA and SCRFA were treated with particle-shaping to obtain particle-shaping coarse aggregate (PSRCA) and particle-shaping fine aggregate (PSRFA), and the recycled powder (RP) produced in the process of particle-shaping was collected. Under the condition of a 1:4 cement-sand ratio, RP was used to replace cement with four substitution rates of 0, 10%, 20%, and 30%, and dry-mixed masonry mortar was prepared with 100% SCRFA, PSRFA, and river sand (RS). The basic and mechanical properties and microstructure of hydration products of dry-mixed mortar were analyzed, and the maximum substitution rate of RP was determined. Under the condition that the amount of cementitious material is 400 kg/m3 and the RP is at the maximum replacement rate, three different aggregate combinations to prepare concrete are the 100% use of SCRCA and SCRFA, PSRCA and PSRFA, and RS and natural aggregate (NCA); the workability, mechanical properties, and aggregate interface transition zone of the prepared concrete were analyzed. The results show that when the replacement rate of RP is less than 20%, it has little effect on the properties of products. The performance of PSRCA and PSRFA after treatment is better than that of SCRCA and SCRFA. Under different RP substitution rates, the performance of dry-mixed mortar prepared with PSRFA is very close to that prepared with RS. The performance of recycled concrete prepared with PSRCA and PSRFA is also very close to that of products prepared with NCA and RS. The failure morphology of PSRCA and RSRFA concrete is also similar to that of NCA and RS concrete