In this study we examine variations in the structure of perovskite compounds of LaBa2Cu2O9, LaBa2CaCu3O12 and LaBa2Ca2Cu5O15 synthesized using the solid state reaction method. The samples’ compositions were assessed using X-ray fluorescence (XRF) analysis. The La: Ba: Ca: Cu ratios for samples LaBa2Cu2O9, LaBa2CaCu3O12 and LaBa2Ca2Cu5O15 were found by XRF analysis to be around 1:2:0:2, 1:2:1:3, and 1:2:2:5, respectively. The samples’ well-known structures were then analyzed using X-ray diffraction. The three samples largely consist of phases 1202, 1213, and 1225, with a trace quantity of an unknown secondary phase, based on the intensities and locations of the diffraction peaks. According to the measured parameters a, b, and c, every sample has a tetragonal symmetry structure. Each sample’s mass density was observed to alter as the lead oxide content rose. Scanning electron microscope (SEM) images of the three phases revealed that different Ca-O and Cu-O layers can cause different grain sizes, characterized by elongated thin grains, without a preferred orientation.

This study focuses on how the partial substitution of copper by nickel nanoparticles affects the electrical and structural properties of the Bi2Ba2Ca2Cu2.9Ni0.1O10+δ, Bi2Ba2Ca2Cu2.8Ni0.2O10+δ and Bi2Ba2Ca2Cu2.6Ni0.4O10+δ compounds. Approximate values of crystallization size and crystallization percentage for the three compounds were calculated using the Scherer, modified Scherer, and Williamson-Hall methods. A great similarity was observed in the crystal size values from the Scherer method, 243.442 nm, and the Williamson-Hall method, 243.794 nm for the second sample. At the same time this sample exhibited the highest crystal size value for the three methods. In the examination of electrical properties, the sample with 0.1 partial substitution, Bi2Ba2Ca2Cu2.9Ni0.1O10+δ was determined to be the best with a critical temperature of 100 K and an energy gap of 6.57639 × 10-21 MeV. Using the SEM technique to analyze the structural morphology of the three phases, it was discovered that the size of the granular forms exceeds 25 nm. It was determined that the samples’ shapes alter when nickel concentration rises. The patterns that reveal the distribution of the crystal structure also exhibit clear homogeneity.

Decabromodiphenyl ether (BDE209) is a persistent aromatic compound widely associated with environmental pollutants. Given its persistence and possible bioaccumulation, exploring a feasible technique to eradicate BDE209 efficiently is critical for today’s environmentally sustainable societies. Herein, an advanced nanocomposite is elaborately constructed, in which a large number of titanium dioxide ( TiO2) nanoparticles are anchored uniformly on two-dimensional graphene oxide (GO) nanosheets ( TiO2/GO) via a modified Hummer’s method and subsequent solvothermal treatment to achieve efficient photocatalytic degradation BDE209. The obtained TiO2/ GO photocatalyst has excellent photocatalytic due to the intense coupling between conductive GO nanosheets and TiO2 nanoparticles. Under the optimal photocatalytic degradation test conditions, the degradation efficiency of BDE209 is more than 90%. In addition, this study also provides an efficient route for designing highly active catalytic materials.

The synthesis of a novel first stage GIC containing simultaneously lithium, potassium and barium through a solid–liquid reaction by molten salts method is described. Such a route has been largely developed in our laboratory for intercalation of metals into graphite. The interplanar distance of this quaternary compound reaches 950 pm and exhibits poly-layered intercalated sheets defined by X-ray measurements. The Li0.2K0.75Ba0.6C6 chemical formula of the compound is determined by ion beam analysis and this GIC is remarkably homogeneous. This GIC is the first poly-layered one containing barium.

In today's fast-evolving technological environment, the growth of mobile devices has provided businesses with additional knowledge on how to effectively communicate with their targeted audience. As big data generated by mobile users has become a valuable source for improving communication, users’ location data has provided an additional parameter to take into account while trying to enhance the effectiveness of digital marketing campaigns. This paper presents a comparative study of the location-based marketing field and tools. It provides an overview of different exploitation methods of location-based mobile services and data for effective digital marketing campaigns and guidelines for future research.

This study aims to investigate how attitudes towards femvertising affects brand credibility, brand authenticity, and purchase intention. Further, the mediation of femwashing on these relationships was investigated. And lastly, the impact of brand credibility and authenticity on purchase intention was examined. The results show that a favourable attitude towards femvertising positively affects brand credibility and authenticity but is not significant for purchase intention. Likewise, the mediation of femwashing on these relationships was not significant. In addition, brand credibility and brand authenticity had a positive impact on purchase intention.

The application of mindfulness is increasing significantly in different areas of business studies. However, identifying how mindfulness research has evolved and the major research themes, specifically within the business studies domain, remains lacking. This study unveils the intellectual structure of mindfulness research in business studies. Using citation and co-citation analysis, the study identifies the most influential articles, annual growth, and three key research clusters constituting the intellectual foundation.

Gastro-tourism extends beyond what to eat, but also the attractiveness and the environment. It encompasses a tourist experience journey starting from pre, during, until post-travel. Gastro tourism in the new normal engages with traditional vs novel value of experiences. This study aims to answer how Gen Z experiences gastro tourism and the impact of digital technologies using surveys on Tiktok Ads followed by an experiment with an immersive culinary adventure using 3D visual technology.

The Metaverse is a digital space that utilizes the internet and augmented reality to blend real-life and virtual experiences. This emerging environment offers opportunities for individuals to purchase goods and services, enjoy entertainment, and participate in virtual events. By utilizing Direct-to-Avatar (D2A) and Metahuman (D2M) approaches, brands can create more seamless and immersive customer experiences, representing a progression in omnichannel evolution. Despite this growing interest in the Metaverse, there is limited research on how it impacts consumer perceptions. To address this gap, a qualitative study was conducted involving semi-structured interviews with C-level executives in the fashion industry, alongside two experimental studies that examined hypotheses related to the Metaverse experience. The results revealed that customer experiences in the Metaverse enhance perceived seamlessness and customer engagement. These findings can assist managers in identifying innovative ways to improve customer experiences, including developing new paradigms for the phygital world, combining elements of both physical and digital reality, and creating distinctive brand-customer interactions.

This paper aims to examine the effect of AI framing (i.e., Scientific AI vs Magic AI) on consumers' product evaluation. This study shows that magically framed AI technology may be more beneficial to appeal to product innovativeness when subjective product properties (e.g., personal taste) becomes important. On the contrary, when objective product properties (e.g., functionality) becomes important, scientifically framed AI technology is more likely to generate higher perceived product attractiveness and purchase intention.

Sponsored product reviews have emerged as an important tool in influencer marketing. In particular, non-monetary sponsorships, where brands give influencers a product as a gift for a free trial, are widely used in influencer marketing. Yet, there is little understanding of i) the impact of non-monetary sponsorship on consumers’ downstream behaviors, such as social media engagement, ii) the moderating effect of influencer type, and iii) the underlying mechanisms through consumer perceptions of the brand (i.e., brand trust) and product (i.e., perceived product quality). To fill this gap, we first empirically examined the impact of non-monetary sponsorship on customer engagement using an Instagram dataset through regression analyses. In this analysis, the propensity score matching (PSM) method was employed to match non-monetary sponsored posts with other similar posts, which controls unobserved confounding variables and resolves the endogeneity problem. The empirical analysis shows that non-monetary sponsorship increases social media engagement, and the positive impact is stronger when a micro-influencer generates a non-monetary sponsored post. Next, using a lab experiment, we provide evidence for a causal link between non-monetary sponsorship and consumers’ downstream behavior (i.e., social media engagement, purchase intention, and brand attitude) and support the mediation through higher perceived product quality and brand trust. We contribute to the literature on influencer marketing by documenting the positive impact of non-monetary sponsorship on social media engagement, examining the moderating role of influencer type, and providing novel mechanisms underlying the effect of non-monetary sponsorship. The findings also highlight the changes in consumer perception of sponsorship and offer insights into the design of influencer marketing campaigns for marketing practitioners.

Crowdfunding is an increasingly popular fundraising tool where project creators solicit capital from potential backers in return for monetary rewards or presales of products/services. Potential backers in crowdfunding are looking for potential cues to reduce uncertainty and predict new venture success when making their capital contributions. To increase their funding success, project creators strategically use project descriptions as a marketing tool to attract potential backers and funding.

As one of the biggest service-oriented industries worldwide, the hotel industry significantly contributes to environmental degradation in several ways. Service marketers, consumers, and policy makers are increasingly aware of the damage that excessive natural resources depletion in the guise of water and energy consumption and CO2 emissions by hotels might bring about to the planet. As a result of the growing global concern about climate change, there has been an increase in consumer demand for environmentally-responsible hospitality options. One such option is green hotels, which are environmentally-conscious hospitality properties that are gaining popularity worldwide at a rapid pace. Consumers who prioritize eco-friendliness are willing to pay a premium for green hotels. However, unlike tangible products, services such as hotel experiences are subjective, emotional, and therefore, difficult to evaluate before actual usage. One of the prominent ways in which consumers assess green hotels’ credibility is through user generated content in the form of reviews.

With about 80% of the global economy expected to shift to the global market by 2030, exports of reverse direct purchase products, in which foreign consumers purchase products from online shopping malls in Korea, are growing 55% annually. As of 2021, sales of reverse direct purchases in South Korea increased 50.6% from the previous year, surpassing 40 million. In order for domestic SMEs(Small and medium sized enterprises) to enter overseas markets, it is important to come up with export strategies based on various market analysis information, but for domestic small and medium-sized sellers, entry barriers are high, such as lack of information on overseas markets and difficulty in selecting local preferred products and determining competitive sales prices. This study develops an AI-based product recommendation and sales price estimation model to collect and analyze global shopping malls and product trends to provide marketing information that presents promising and appropriate product sales prices to small and medium-sized sellers who have difficulty collecting global market information. The product recommendation model is based on the LTR (Learning To Rank) methodology. As a result of comparing performance with nDCG, the Pair-wise-based XGBoost-LambdaMART Model was measured to be excellent. The sales price estimation model uses a regression algorithm. According to the R-Squared value, the Light Gradient Boosting Machine performs best in this model.

In the era of the 4th Industrial Revolution, Logistic 4.0 using data-based technologies such as IoT, Bigdata, and AI is a keystone to logistics intelligence. In particular, the AI technology such as prognostics and health management for the maintenance of logistics facilities is being in the spotlight. In order to ensure the reliability of the facilities, Time-Based Maintenance (TBM) can be performed in every certain period of time, but this causes excessive maintenance costs and has limitations in preventing sudden failures and accidents. On the other hand, the predictive maintenance using AI fault diagnosis model can do not only overcome the limitation of TBM by automatically detecting abnormalities in logistics facilities, but also offer more advantages by predicting future failures and allowing proactive measures to ensure stable and reliable system management. In order to train and predict with AI machine learning model, data needs to be collected, processed, and analyzed. In this study, we have develop a system that utilizes an AI detection model that can detect abnormalities of logistics rotational equipment and diagnose their fault types. In the discussion, we will explain the entire experimental processes : experimental design, data collection procedure, signal processing methods, feature analysis methods, and the model development.

Aluminum’s exceptional properties, such as its high strength-to-weight ratio, excellent thermal conductivity, corrosion resistance, and low neutron absorption cross-section, make it an ideal material for diverse nuclear industry applications, including aluminum plating for the building envelope of nuclear power plants. However, plating aluminum presents challenges due to its high reactivity with oxygen and moisture, thus, complicating the process in the absence of controlled environments. Plating under an inert atmosphere is often used as an alternative. However, maintaining an inert atmosphere can be expensive and presents an economic challenge. To address these challenges, an innovative approach is introduced by using deep eutectic solvents (DES) as a substitute for traditional aqueous electrolytes due to the high solubility of metal salts, and wide electrochemical window. In addition, DESs offer the benefits of low toxicity, low flammability, and environmentally friendly, which makes DESs candidates for industrial-scale applications. In this study, we employed an AlCl3-Urea DES as the electrolyte and investigated its potential for producing aluminum coatings on copper substrates under controlled conditions, for example, current density, deposition duration, and temperature. A decane protective layer, non-polar molecular, has been used to shield the AlCl3-Urea electrolyte from the air during the electrodeposition process. The electrodeposition was successful after being left in the air for two weeks. This study presents a promising and innovative approach to optimizing aluminum electrodeposition using deep eutectic solvents, with potential applications in various areas of the nuclear industry, including fuel cladding, waste encapsulation, and radiation shielding.

Chemical environments of near-field (Engineered barrier and surrounded host rock) can influence performance of a deep geological repository. The chemical environments of near-field change as time evolves eventually reaching a steady state. During the construction of a deep geological repository, O2 will be introduced to the deep geological repository. The O2 can cause corrosion of Cu canisters, and it is important predicting remaining O2 concentration in the near-field. The remaining O2 concentration in the near field can be governed by the following two reactions: oxidation of Cu(I) from oxidation of Cu and oxidation of pyrite in bentonite and backfill materials. These oxidation reactions (Cu(I) and pyrite oxidation) can influence the performance of the deep geological repository in two ways; the first way is consuming oxidizing agents (O2) and the second way is the changing pH in the near-field and ultimately influencing on the mass transport rate of radionuclides from spent nuclear fuel (failure of canisters) to out of the engineered barrier. Hence, it is very important to know the evolution of chemical environments of near-field by the oxidation of pyrite and Cu. However, the oxidation kinetics of pyrite and Cu are different in the order of 1E7 which means the overall kinetics cannot be fully considered in the deep geological repository. Therefore, it is important to develop a simplified Cu and pyrite oxidation kinetics model based on deep geological repository conditions. Herein, eight oxidation reactions for the chemical species Cu(I) were considered to extract a simplified kinetic equation. Also, a simplified kinetics equation was used for pyrite oxidation. For future analysis, simplified chemical reactions should be combined with a Multiphysics Cu corrosion model to predict the overall lifetime of Cu canisters.

Since the beginning of the seventh century, Islamic law has played an essential role in protecting the personal, economic, judicial, and political rights of civilians during armed conflict. Fourteen centuries before the Universal Declaration of Human Rights was drafted in 1948, it had already initiated a human revolution consisting of a set of human principles. In addition, Islamic law has made a significant contribution to international humanitarian law (IHL). This paper focuses on two specific legal constructs in warfare: the definition of the combatant and the principle of distinction. This article comparatively examines how these two laws deal with different aspects of war that fall under jus ad bellum, jus in bello, and jus post bellum. A comparative analysis of the various elements and aspects of just war theory in Islamic and contemporary international law provides a much deeper understanding of its limitations. We can safely conclude that there is a unique relationship between the Islamic law of war and IHL.