Consumer brand engagement (CBE) signals propensity for brand purchase. A scale proposes three dimensions of CBE (i.e., cognitive, affective and activation dimensions) but the dimensions prominent and driving brand purchase intentions in an Instagram cosmetic purchase context need examination. In this context, this study tests Hollebeek, Glynn and Brodie’s (2014) 10-items/3 dimensions scale and examines an outcome of cosmetics brand purchase intention on Instagram. Data was quantitatively collected from 203 consumers who were students and non-students using convenience and snowballing non- probability sampling method. Confirmatory factor analysis and structural equation modelling were used to analyse the data. The results revealed that although the three CBE dimensions were identified in a Cosmetic Instagram purchase context, it was the affective and activation dimensions that positively predicted consumers’ intentions to purchase cosmetic brands after engaging with the brand on Instagram. Theoretical and practical implications are provided.

Following a series of major breakthroughs in artificial intelligence (AI) technology, it is believed that the use of AI technology can fundamentally subvert many industries and business fields, one of which is marketing. For instance, AI is likely to become a key driver of how advertising and marketing activities are conducted (Qin and Jiang, 2019) and thus dramatically change marketing strategies and customer behaviors (Davenport et al., 2020).

With the development of social media, most people will use social media to watch the videos of digital influencers to get spiritual comfort, and they will think that digital influencers are like friends who are connected with their own lives. However, most of the previous studies focused on the influence of digital influencers on followers’ behavioral intentions (e.g. loyalty, and purchase intention). They rarely discussed the online social well-being obtained by followers after watching digital influencers' posts. Therefore, this study integrates the attributes of followers (loneliness, low self-esteem, empathy) and the characteristics of digital influencers (social attractiveness, expertise, homophily) to explore the influence of the parasocial interaction established between digital influencers and followers on followers’ online social well-being. This study uses the Internet to collect questionnaires and takes users who have watched digital influencers' posts on social media as the research object. A total of 597 valid questionnaires are collected. The research results show that: the characteristics of digital influencers (social attractiveness, expertise, and homophily), and followers' attributes (low self-esteem and empathy) have positively affected parasocial interaction. It is noteworthy that loneliness has no significant effect on parasocial interaction.

The objective of this study is to compare the efficiency of VR and 2D in the tourism industry as marketing tools, using affective forecasting and purchase intention. Accordingly, this study has two primary research aims. The first is to examine if a higher level of mental imagery (resulting from VR) is more effective than a lower level (2D) in a tourism marketing context. To evaluate this, the researchers use experimental method, measuring predicted dominance, predicted pleasure and predicted arousal, as well as purchase intention towards the hotel. Relevant to the tourism industry, tourism products are spatially and temporally distant (vs. near). This study aims to investigate how differently mental imagery, resulting from VR (versus 2D) experience, generates affective forecasting of a tourism product when tourists plan distant (versus near) future trips (temporal distance).

With the development of information technology, online food delivery services have significantly changed people’s food consumption patterns. The outbreak of COVID-19 has further facilitated the development due to restaurant restrictions and social distancing measures. Due to the emergence of online food delivery services, scholars have paid increasing attention to this popular topic, and a large number of studies have examined which factors are related to consumers’ intention to use online food delivery services. However, previous studies showed inconsistent findings, and relationships between variables lack a comprehensive understanding. Therefore, this study aimed to develop a research model and examine the factors influencing consumers’ intention to use online food delivery services. By reviewing and analyzing 52 studies with 53 independent samples (N = 22,937), the meta-analytic structural equation modeling approach was carried out to assess the research model. The findings indicate that two attributes of online food delivery services (i.e., convenience and price-saving orientation) play different roles in the research model. Specifically, convenience significantly impacted perceived ease of use but had no direct impact on perceived usefulness. Price-saving orientation significantly influenced both perceived ease of use and perceived usefulness. Moreover, relationships between perceived ease of use, perceived usefulness, and perceived trust were significant, and these factors ultimately significantly led to the intention to use food delivery services. The findings contribute to theoretical advancement in the extant literature on food delivery services and help firms develop to provide better food delivery services for consumers’ continuous usage.

This study aims to address two important questions: will advertising on mobile short-form video apps jeopardize the value perception of luxury brands (RQ1), and if so, how will self-deprecating online reviews eliminate these negative effects (RQ2). An experimental design approach was employed to investigate the proposed research questions. Three experiments were conducted to test the hypotheses. SPSS was used for data analysis. The study 1 finds that compared with traditional media, advertising on mobile short-form video apps shortened the psychological distance between consumers and luxury, therefore has a more negative impact on consumers’ perception of luxury brands. The study 2 reveals that self-deprecating online reviews can eliminate the negative effects of advertising of luxury brands. On the basis of previous research, this paper proves the negative influence of social media on luxury brands in the scene of new social media-mobile short format video application. In addition, it also studies the moderating effect of online comments, especially self-deprecating comments, on consumers' perception of luxury brands. This study outlines theoretical contributions and practical implications for the luxury marketing management and made suggestions for future research in the field of luxury marketing in Social Media.

The tourism industry specifically experienced distinct failing revenues and was an economic sector among those most rigorously influenced by the pandemic. In the gradual recovery period after the pandemic, the technology implementation in travel has been a great achievement for travel companies. This study is based on a systematic literature review to examine the ability of Virtual Reality (VR) and Geographic information systems (GIS) to serve as a facilitator of sustainable tourism development goals. The potential impact of VR and GIS within tourism will bolster the Sustainable Development Goals (SDGs) and will be conceptualized. The use of these technologies in connection to the SDGs can associate with SDG No. 8, SDG No.9, SDG No.11, and SDG No. 13, which are related to "decent work and economic growth", "industry, innovation, and infrastructure", "sustainable cities and communities", and "climate action."

The hospitality industry is widely using customer data to develop successful personalized marketing communication. However, in the event of information leakage, personalized advertising may escalate customers’ privacy distress. Building on Conservation of Resources theory, this study proposes three dimensions for privacy threats that impact the relationship between personalized hospitality advertising and consumer responses. Findings from six experiments across high and low involvement hospitality products demonstrate diverging effects of personalized advertising depending on the type of privacy threat communicated. Results further indicate that customers’ psychological comfort mediates the relationship between high-personalized advertising and the customer response to the advertising when privacy threat is high. Additionally, when the perceived severity and distance of the announced privacy threat are high and low respectively, rational appeals generate higher levels of psychological comfort, while the same happens for emotional appeals when the perceived scope of the threat is high. The study concludes with value-adding theoretical and managerial implications for the hospitality industry.

The Wide-Angle Polarimetric Camera (PolCam) is installed on the Korea’s lunar orbiter, Danuri, which launched on August 5, 2022. The mission objectives of PolCam are to construct photometric maps at a wavelength of 336 nm and polarization maps at 461 and 748 nm, with a phase angle range of 0◦–135◦ and a spatial resolution of less than 100 m. PolCam is an imager using the push-broom method and has two cameras, Cam 1 and Cam 2, with a viewing angle of 45◦ to the right and left of the spacecraft’s direction of orbit. We conducted performance tests in a laboratory setting before installing PolCam’s flight model on the spacecraft. We analyzed the CCD’s dark current, flat-field frame, spot size, and light flux. The dark current was obtained during thermal / vacuum test with various temperatures and the flat-field frame data was also obtained with an integrating sphere and tungsten light bulb. We describe the calibration method and results in this study.

It is difficult to distinguish the pure signal produced by an orbiting planetary companion around giant stars from other possible sources, such as stellar spots, pulsations, or certain activities. Since 2003, we have obtained radial (RV) data from evolved stars using the high-resolution, fiber-fed Bohyunsan Observatory Echelle Spectrograph (BOES) at the Bohyunsan Optical Astronomy Observatory (BOAO). Here, we report the results of RV variations in the binary star HD 135438. We found two significant periods: 494.98 d with eccentricity of 0.23 and 8494.1 d with eccentricity of 0.83. Considering orbital stability, it is impossible to have two companions in such close orbits with high eccentricity. To determine the nature of the changes in the RV variability, we analyzed indicators of stellar spot and stellar chromospheric activity to find that there are no signals related to the significant period of 494.98 d. However, we calculated the upper limits of rotation period of the rotational velocity and found this to be 478–536 d. One possible interpretation is that this may be closely related to the rotational modulation of an orbital inclination at 67–90 degrees. The other signal corresponding to the period of 8494.1 d is probably associated with a stellar companion orbiting the giant star. A Markov Chain Monte Carlo (MCMC) simulation considering a single companion indicates that HD 135438 system hosts a stellar companion with 0.57+0.017 −0.017 M⊙ with an orbital period of 8498 d.

This paper is written as a follow-up observations to reinterpret the radial velocity (RV) of HD 36384, where the existence of planetary systems is known to be ambiguous. In giants, it is, in general, difficult to distinguish the signals of planetary companions from those of stellar activities. Thus, known exoplanetary giant hosts are relatively rare. We, for many years, have obtained RV data in evolved stars using the high-resolution, fiber-fed Bohyunsan Observatory Echelle Spectrograph (BOES) at the Bohyunsan Optical Astronomy Observatory (BOAO). Here, we report the results of RV variations in the M giant HD 36384. We have found two significant periods of 586 d and 490 d. Considering the orbital stability, it is impossible to have two planets at so close orbits. To determine the nature of the RV variability variations, we analyze the HIPPARCOS photometric data, some indicators of stellar activities, and line profiles. A significant period of 580 d was revealed in the HIPPARCOS photometry. H𝛼 EW variations also show a meaningful period of 582 d. Thus, the period of 586 d may be closely related to the rotational modulations and/or stellar pulsations. On the other hand, the other significant period of 490 d is interpreted as the result of the orbiting companion. Our orbital fit suggests that the companion was a planetary mass of 6.6 𝑀J and is located at 1.3 AU from the host.

Background: Germ cells undergo towards male or female pathways to produce spermatozoa or oocyte respectively which is essential for sexual reproduction. Mesenchymal stem cells (MSCs) have the potential of trans-differentiation to the multiple cell lineages. Methods: Herein, rat MSCs were isolated from bone marrow and characterized by their morphological features, expression of MSC surface markers, and in vitro differentiation capability. Results: Thereafter, we induced these cells only by retinoic acid supplementation in MSC medium and, could able to show that bone marrow derived MSCs are capable to trans-differentiate into male germ cell-like cells in vitro. We characterized these cells by morphological changes, the expressions of germ cell specific markers by immunophenotyping and molecular biology tools. Further, we quantified these differentiated cells. Conclusions: This study suggests that only Retinoic acid in culture medium could induce bone marrow MSCs to differentiate germ cell-like cells in vitro . This basic method of germ cell generation might be helpful in the prospective applications of this technology.

대한민국 교육은 코로나19 팬데믹으로 대면 교육에서 비대면 교육으로 전환되었다. 학생들이 사회에 대해 배 울 수 있는 그룹 활동 교육은 축소되거나 중단되었고, 비대면 서비스기술 발전으로 메타버스라는 새로운 서비 스를 탄생시켰다. 본 논문에서 저자는 한국 초·중·고교에서 요구하는 집단 활동 교육을 비대면으로 체험할 수 있는 'Virtual School'(VS)이라는 플랫폼을 제안한다. 이 플랫폼은 학생들이 사용하기 쉬운 VRChat과 3D 가상 환경 렌더링을 위한 Unity 3D 엔진을 기반으로 한다. VS 플랫폼은 졸업식, 입학식, OX 퀴즈 등 다양한 활동 을 제공한다. 해당 플랫폼은 부산진고등학교에서 시범 운영되었으며, 메타버스 관련 비대면 교육 플랫폼 연구 분야에서 활발히 활용될 것으로 기대한다.

비대면 교육 플랫폼의 필요성은 COVID-19 팬데믹으로 가속을 받게 되었다. 코로나 바이러스의 확산을 막기 위하여 대한민국의 대다수 교육기관들은 등 하교를 최소화 하였으며, 수업 방식은 네트워크를 이용한 화상 회 의 형태로 변하게 되었다. 화상 회의 형태의 비 대면 교육 플랫폼은 교수자 및 학생들에게 정적인 상호작용 (Static Interaction)만을 지원하여 학생들의 적극적인 수업 참여를 유도 하지 못했으며, 교수자의 교육 방식에 큰 제한을 주어 수업의 질을 크게 낮추게 되었다. 본 논문에서는 학생들의 자율적인 수업 참여율을 높이기 위 하여 게임의 특성을 가지는 메타버스 형태의 Web 기반 비 대면 교육 플랫폼”Off-On Class”를 제안한다. ”Off-On Class”는 강남 수학의 힘 학원에서 비 대면 교육 플랫폼의 요구 사항을 분석하여 개발 및 시범 운영 을 하였다.

VR 및 AR은 대중들이 접근하기 어려운 기술이 아닌, 개인용 스마트 폰 하나로 체험 및 활용 할 수 있는 시 대가 되었다. 최근 이런 개인용 스마트 폰의 다양한 센서를 활용한 AR 콘텐츠가 개발되고 서비스 되고 있다. AR 콘텐츠의 수요가 커지면서Software교육의 수요도 커지게 되었다. 하지만, 비전공자들도 배우기 쉬운 Python 언어를 중심으로 SW 교육이 활발해졌음에도, 아직까지 AR 콘텐츠 개발에서는 Python을 적극적으로 사용할 수 없다. AR 콘텐츠는 기술 분야 뿐 아니라 인터렉티브 아트 분야에서도 활발하게 사용되고 있다. 최근 인터 렉티브 아티스트들은 Python을 이용하여 인공지능을 활용한 작품을 개발 및 전시하고 있다. Python을 통한 SW 교육은 SW 분야의 취업에만 필요한 것이 아니라 아트 분야에서도 필요한 교육이 되었다. 본 논문에서는 AR 콘텐츠 개발 교육을 위한 Python과 Unity 3D Engine을 이용한 네트워크 기반 AR 프레임 워크를 제안한다. 제 안한 AR 프레임 워크는 Web 기반 브라우저에서 개인용 스마트 폰의 카메라에 접근하여 카메라 정보를 Main Server에 전송하고 Python에서 Mark를 분석한다. Mark 정보에 맞춰 Unity 3D Engine에서 3D 오브젝트를 렌더 링하고, 카메라 정보화 합성 후, MJPEG 스트리밍으로 개인용 스마트 폰 화면에 렌더링 된다. 본 논문에서 제 안한 AR 프레임 워크는 SW 교육 플랫폼과 비대면 교육 플랫폼의 요구사항을 반영하며, 인터렉티브 아티스트 들의 다양한 도전에 필요한 기술적 제한을 낮춰 줄 것으로 기대한다.

Biomass-derived porous carbon is an excellent scientific and technologically interesting material for supercapacitor applications. In this study, we developed biomass-derived nitrogen-doped porous carbon nanosheets (BDPCNS) from cedar cone biomass using a simple KOH activation and pyrolysis method. The BDPCNS was effectively modified at different temperatures of 600 °C, 700 °C, and 800 ℃ under similar conditions. The as-prepared BDPCNS-700 electrode exhibited a high BET surface area of 2883 m2 g− 1 and a total pore volume of 1.26 cm3 g− 1. Additionally, BDPCNS-700 had the highest electrical conductivity (11.03 cm− 1) and highest N-doped content among the different electrode materials. The BDPCNS-700 electrode attained a specific capacitance of 290 F g− 1 at a current density of 1 A g− 1 in a 3 M KOH electrolyte and an excellent longterm electrochemical cycling stability of 93.4% over 1000 cycles. Moreover, the BDPCNS-700 electrode had an excellent energy density (40.27 Wh kg− 1) vs power density (208.19 W kg− 1). These findings indicate that BDPCNS with large surface areas are promising electrode materials for supercapacitors and energy storage systems.

Graphene oxide/Iron III oxide (GO: Fe2O3) nanocomposites (NCs) have been topical in recent times owing to the enhanced properties they exhibit. GO acting as a graphene derivative has demonstrated superior features as obtainable in a graphene sheet. Furthermore, the attachment of oxygen functional groups at its basal and edge planes of graphene has allowed for easy metal/oxide functionalization for improved properties harvesting. Fe2O3 nanoparticles (NPs) on the other hand have polymorphic property enabling the degeneracy of Fe2O3 in different phases, thereby resulting in different physical and crystalline properties when used to functionalize GO. The properties of GO: Fe2O3 have been applied to supercapacitor energy harvesting, Li-ion batteries, and biomedicine. The enhanced properties are attributed to the adsorption and electronic structure properties of Fe atoms. In this review, the various synthesis used in the preparation of reduced/graphene oxide: Fe2O3 is discussed. As indicated in the considered literature, the XPS analysis suggests electronic bond interactions between C–C, C–O, C–Fe and Fe–C. The available report on UPS measurements further suggests the formation of mixed states emanating from  and  bonds. The discussed reports further suggest that the various applications based on the harvesting of electronic, electrical, and magnetic properties are due to the ionic and exchange interactions between the different orbital states of carbon, oxygen and iron. The challenges and future prospects of the synthesis and application of GO/Fe2O3 are examined. Graphical abstract showing the process of exfoliation, reduction and functionalization of graphite to produce reduced graphene oxide (rGO).

Radioactive waste can be classified according to the concentration level for radionuclides, and the disposal method is different through the level. Gamma analysis is inevitably performed to determine the concentration of radioactive waste, and when a large amount of radioactive waste is generated, such as decommissioning nuclear facilities, it takes a lot of time to analyze samples. The performance of a lot of analysis can cause human errors and workload. In general, gamma analysis is performed using by HPGe detector. Recently, for convenience of analysis, commercial automatic sample changers applicable to the HPGe detectors were developed. The automatic sample changers generate individual analysis reports for each sample. In this study, gamma analysis procedure was improved using the application of the automatic sample changer and the automated data parsing using by Python. The application of automatic sample changers and data parsing technique can solve the problems. The human errors were reduced to 0% compared to the previous method by improving the gamma analysis procedure, and working time were also dramatically reduced. This automation of analysis procedure will contribute to reducing the burden of analysis work and reducing human errors through various improvements.