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The purpose of this study is to develop resin composite materials composed of polycaprolactone (PCL) acrylates and hydroxyapatite (HA) nanoparticles for ultraviolet digital light projection (DLP) three-dimensional (3D) printing technique.

Two PCL-based triacrylates, namely, glycerol-3 caprolactone-triacrylate (Gly-3CL-TA) and glycerol-6 caprolactone-triacrylate (Gly-6CL-TA) were synthesized from ring-opening polymerization of ε-caprolacton monomer in the presence of glycerol and then acrylation was performed using acryloyl chloride. 3D printing resins made of Gly-3CL-TA or Gly-6CL-TA, 5% HA and 3% of photoinitiator 2,4,6-Trimethylbenzoyl-diphenyl-phosphineoxide were then formulated. The surface topography, surface element composition, flexural strength, flexural modulus, cytotoxicity and degradation of the PCL-based scaffolds were then characterized.

Resin composite composed of Gly-3CL-TA or Gly-6CL-TA and 5% (w/w) of HA can be printed by 405 nm DLP 3D printers. The former has lower viscosity and thus can form a more uniform layer-by-layer structure, while the latter exhibited a higher flexural strength and modulus after being printed. Both composite materials are non-cytotoxic and degradable.

This study provides a direction of the formulation of environment-friendly resin composite for DLP 3D printing. Both resin composites have huge potential in tissue engineering applications.

Support groups are a common feature of the mental health support engaged by carers and consumers. The purpose of this paper is to update and consolidate the knowledge and the evidence for the effectiveness of mental health support groups.

This paper is based on a systematic literature review of relevant databases around support groups for mental health. Support groups are defined as meetings of people with similar experiences, such as those defined as carers of a person living with a mental illness or a person living with a mental illness. These meetings aim to provide support and companionship to one another.

The results show that there is a consistent pattern of evidence, over a long period of time, which confirms the effectiveness of mental health support groups for carers and people living with mental illness. There is strong, scientifically rigorous evidence which shows the effectiveness of professionally facilitated, family-led support groups, psychoeducation carers support groups, and professionally facilitated, program-based support groups for people living with mental illness.

This research implies the use of support groups is an important adjunct to the support of carers and people with mental illness, including severe mental illness.

This research brings together a range of studies indicating the usefulness of support groups as an adjunct to mental health therapy.

The purpose of this paper is to examine how geographic diversification affects the performance of international new ventures.

This study develops hypotheses about the individual and joint effects of geographic diversification and industry life cycle on the performance of international new ventures. This paper also introduces industry technology characteristics as a contingent factor for the above relationships and tests the hypotheses on a large panel data set.

Based on the analyses of the strategies and performance of 699 listed Chinese international new ventures between 1991 and 2014, this study finds that the impact of geographic diversification on performance is contingent on the stage of the industry life cycle and that the moderating effect differs across high-technology and low-technology industries. The results suggest that it is fruitful for international new ventures in high-technology industries to undertake geographic diversification in earlier stages of the industry life cycle, but international new ventures in low-technology industries are better off undertaking geographic diversification during the later stages of the industry life cycle.

The study contributes to the literature on international entrepreneurship by identifying the industry life cycle conditions under which the learning advantages of international new ventures are effective and facilitate the achievement of better performance. This paper also shows that industry technology type matters for geographic diversification strategies of international new ventures.

The aim of this paper is to examine the effects of light controlling system that combined high refractive particles (n-TiO₂ [titanium dioxide – TiO₂]) and tartrazine lake dye (TL dye) on thickness, flexural strength, flexural modulus and surface details of the 3D-printed resin.

Influences of different concentrations of n-TiO₂ and TL dye in light-cured resin formulations for 3D printing (3DP) application were evaluated, including curing thickness, flexural strength and surface details under scanning electron microscopy.

The polymerization thickness of samples containing both n-TiO₂ and TL dye was lower compared to samples with TL dye solely. Samples containing more n-TiO₂ and more TL dye exhibited lower flexural strength and modulus. Ramp models showed that for samples containing 1 per cent TL dye, when their n-TiO₂ content increased from 1 to 5 per cent, surface laminate structures became sharper. However, when the TL dye content doubled to 2 per cent, the surface laminate structures were indefinite compared to 1 per cent TL dye-containing counterparts.

In visible-light 3DP, light controlling system in cooperate dye with high refractive particles provides better energy distribution and scattering control. High refractive particles, dyes and light exposure time had influenced the surface resolution and mechanical properties of the 3DP products.

There are two major strategies for short video advertising which are KOL (key opinion leader) endorsement and in-feed advertising. The authors aim to research the effectiveness of these two strategies for heterogeneous sellers.

The study employed a data set of users from Douyin. Using an endogenous treatment model, the study empirically examines the two strategies' effectiveness in attracting product traffic for online retailors at a short video app Douyin (TikTok).

The results show that the performance of in-feed advertising is higher when the seller's product is of lower price and when the seller has smaller cumulative video exposure. In addition, KOL endorsement is effective regardless of the product price, but performs better when the seller has larger cumulative video exposure.

To the best of the authors’ knowledge, this study is one of the first to explore the interaction effects of two major advertising strategies, KOL endorsement and in-feed advertising on short video platforms. The findings provide important theoretical contributions and practical implications.

Hinged on the transformative service paradigm, this study investigates the relationships among employee acting, customer-perceived service quality, customer emotional well-being, and their value co-creation. Feelings of gratitude among customers may moderate the effect of perceived service quality on their emotional well-being (i.e., positive and negative affects).

A pair study using a structural equation model was conducted to gather data from a financial service organization in a rural area.

The results show how customers perceive service quality positively impacts their emotional well-being immediately after receiving a financial service, which in turn affects their value co-creation. Hence, feelings of gratitude moderate the effect of perceived service quality on customer positive affect.

This study responds to calls for more studies on how service interactions influence customer well-being in the financial services context. This study is among the few that examine moderation effects of customer feelings of gratitude on their emotional well-being to explain why a positive emotion might sway their short-term well-being.

Telecommunication (telecom) fraud is one of the most common crimes and causes the greatest financial losses. To effectively eradicate fraud groups, the key fraudsters must be identified and captured. One strategy is to analyze the fraud interaction network using social network analysis. However, the underlying structures of fraud networks are different from those of common social networks, which makes traditional indicators such as centrality not directly applicable. Recently, a new line of research called deep random walk has emerged. These methods utilize random walks to explore local information and then apply deep learning algorithms to learn the representative feature vectors. Although effective for many types of networks, random walk is used for discovering local structural equivalence and does not consider the global properties of nodes.

The authors proposed a new method to combine the merits of deep random walk and social network analysis, which is called centrality-guided deep random walk. By using the centrality of nodes as edge weights, the authors’ biased random walks implicitly consider the global importance of nodes and can thus find key fraudster roles more accurately. To evaluate the authors’ algorithm, a real telecom fraud data set with around 562 fraudsters was built, which is the largest telecom fraud network to date.

The authors’ proposed method achieved better results than traditional centrality indices and various deep random walk algorithms and successfully identified key roles in a fraud network.

The study used co-offending and flight record to construct a criminal network, more interpersonal relationships of fraudsters, such as friendships and relatives, can be included in the future.

This paper proposed a novel algorithm, centrality-guided deep random walk, and applied it to a new telecom fraud data set. Experimental results show that the authors’ method can successfully identify the key roles in a fraud group and outperform other baseline methods. To the best of the authors’ knowledge, it is the largest analysis of telecom fraud network to date.

This research attempts to evaluate the effects of personal innovativeness and the perceived value of disclosure on the hierarchical nature of privacy concerns under the contingency of self-control when using proximity Bluetooth-beacon technology (PBBT) service in proximity marketing.

The field study takes place in areas where PBBT service is installed in Taipei, Taiwan. A quota sampling approach is used, with 401 qualified respondents participating. The data are analyzed using the partial least square method.

The results confirm the importance of personal innovativeness and perceived value of disclosure as an important determinant to influence privacy concerns about data collection. It is also found that self-control plays a negative moderating role in these two relationships. Moreover, data collection is found to be a fundamental concern leading to other privacy concern facets.

This research represents a pioneer work in proximity marketing regarding how privacy concerns are influenced and how privacy concerns facets are causal-related when using a PBBT platform. More detailed, conditional insight is given as the research is studied under the contingency of self-control. A set of applicable guidelines with empirical evidence is thus provided.

Higher education has seen an unprecedented amount of change in recent decades, with technological advancements impacting on the very essence of teaching and learning. As there are an abundance of digital tools available to educators, it can be a challenge to select the most appropriate online platforms to incorporate into the classroom. This chapter discusses the topic of digital storyboarding by providing a case study of how the author adopted the online platform Storyboard That to enhance student engagement and co-creativity within a UK higher education institution. The chapter debates the benefits and challenges of technology-enhanced learning as part of a blended approach, and concludes with advice for educators wishing to adopt digital storyboarding within their own educational context.

This chapter reviews graphical modeling techniques for estimating large covariance matrices and their inverse. The chapter provides a selective survey of different models and estimators proposed by the graphical modeling literature and offers some practical examples where these methods could be applied in the area of health economics.