Fe3O4/g-C3N4/TiO2 catalyst has been fabricated using a simple ultrasonic method with high photocatalytic activity. The morphology, structure and optical properties of Fe3O4/ g-C3N4/TiO2 were systematically investigated by a variety of characterization techniques. The optimum degradation conditions were investigated by degrading tetracycline (TC) under visible light irradiation. The results showed that the degradation efficiency was the highest when the initial TC concentration was 5.0 mg/L, the pH value was 11 and the catalyst dosage was 1.0 g/L. After 100 min of visible light irradiation, the degradation efficiency of TC achieved at 73.61%, which was 1.64 and 1.19 times that of g-C3N4 and Fe3O4/ g-C3N4, respectively. Moreover, Fe3O4/ g-C3N4/TiO2 had good stability and recyclability. The results of capture experiments showed that ‧O2 − and ‧OH were the main active species during the photocatalytic process, and a possible photocatalytic reaction mechanism of Fe3O4/ g-C3N4/TiO2 catalyst was proposed. This study provides a new way to improve the photocatalytic performance of g-C3N4, which has great potential in degrading pollutants such as antibiotics in wastewater.

The lightweight and high strength characteristics of aluminum alloy materials make them have promising prospects in the field of construction engineering. This paper primarily focuses on aluminum alloy materials. Aluminum alloy was combined with concrete, wood and carbon fiber reinforced plastic (CFRP) cloth to create a composite column. The axial compression test was then conducted to understand the mechanical properties of different composite structures. It was found that the pure aluminum tube exhibited poor performance in the axial compression test, with an ultimate load of only 302.56 kN. However, the performance of the various composite columns showed varying degrees of improvement. With the increase of the load, the displacement and strain of each specimen rapidly increased, and after reaching the ultimate load, both load and strain gradually decreased. In comparison, the aluminum alloy-concrete composite column performed better than the aluminum alloy-wood composite column, while the aluminum alloy-wood-CFRP cloth composite column demonstrated superior performance. These results highlight excellent performance potential for aluminum alloy-wood-CFRP composite columns in practical applications.

Hierarchically porous carbon foam composites with highly dispersed Fe2O3 nanoparticles confined in the foam pores, facilely fabricated by hydrolysis-driven emulsion polymerization strategy. The as-generated acidic conditions of Fe3+ hydrolysis could catalyze the polymerization of phenolic resin, and the carbon-based composite materials containing iron oxides were obtained in situ. The structural characterization results show that HCF@Fe2O3 NPs-2 electrode has the largest specific surface area (549 m2/ g) and pore volume (0.46 cm3/ g). Electrochemical results indicates that typical HCF@Fe2O3 NPs-2 electrode displays good capacitive properties. including high specific capacitance (225 F/g at 0.2 A/g current density). Excellent magnification performance (capacity retention rate 80% as current density increases from 0.2 to 10 A/g). At the same time, HCF@SnO2 NPs was successfully synthesized by replacing hydrolyzed tin tetrachloride with ferric chloride. This study provides a new idea for the preparation of metal oxide–carbon matrix composites, and also highlights the potential of such carbon foams in application of energy storage.

Exploring cheap and efficient oxygen evolution reaction (OER) catalysts is extremely vital for the commercial application of advanced energy storage and conversion systems. Herein, a self-supporting Co3S4/ S-doped reduced graphene oxide ( Co3S4/S-rGO) film catalyst is successfully prepared by a blade coating coupled with high-temperature annealing strategy, and its morphology, structure and composition are measured and analyzed. It is substantiated that the as-synthesized Co3S4/ S-rGO film possesses unique self-supporting structure, and is composed of uniformly dispersed Co3S4 nanoparticles and highly conductive S-rGO, which benefit the exposure of catalytic sites and electron transfer. By reason of the synergistic effect of the two individual components, the self-supporting Co3S4/ S-rGO film catalyst displays outstanding catalytic performance towards OER. As a consequence, the Co3S4/ S-rGO film catalyst delivers an overpotential of 341 mV at 10 mA cm-2, and the current attenuation rate is only 2.6% after continuous operation for 4 h, verifying excellent catalytic activity and durability. Clearly, our results offers a good example for the construction of high-performance self-supporting carbon-based composite film catalysts for critical electrocatalytic reactions.

Seawater evaporation and purification powered by solar energy are considered as a promising approach to alleviate the global freshwater crisis, and the development of photothermal materials with high efficiency is imminent. In this study, cellulose nanofiber (CNF)/MXene/Ni chain (CMN) aerogels were successfully synthesized by electrostatic force and hydrogen bond interaction force. CMN10 achieved a favorable evaporation rate as high as 1.85 kg m− 2 h− 1 in pure water, and the corresponding evaporation efficiency could be up to 96.04%. Even if it is applied to seawater with multiple interference factors, its evaporation rate can still be 1.81 kg m− 2 h− 1. The superior seawater evaporation activity origins from the promoted separation of photoexcited charges and photothermal conversion by the synergy of Ni chain and MXene, as well as the water transport channel supported by the 3D structure frame of CNF. Most importantly, CMN aerogel can maintain water vapor evaporation rates above 1.73 kg m− 2 h− 1 under extreme conditions such as acidic (pH 2) and alkaline (pH 12) conditions. In addition, various major ions, heavy metals and organic pollutants in seawater can be rejected by CMN10 during desalination, and the rejection rates can reach more than 99.69%, ensuring the purity of water resources after treatment. This work shows the great potential of CMN aerogel as a high-efficiency solar evaporator and low-cost photothermal conversion material. Cellulose nanofiber (CNF)/MXene/Ni chain (CMN) aerogels demonstrated high evaporation of water from sea water.

To improve the thermophysical properties of Al alloy for thermal management materials, the Cu-coated carbon fibers (CFs) were used as reinforcement to improve the thermal conductivity (TC) and the coefficient of thermal expansion (CTE) of Al-12Si. The CFs reinforced Al matrix (CFs/Al) composites with different CFs contents were prepared by stir casting. The effects of the CFs volume fraction and Cu coating on the microstructure, component, TC and CTE of CFs/Al composites were investigated by scanning electron microscopy with EDS, X-ray diffraction, thermal dilatometer and thermal dilatometer. The results show that the Cu coating can effectively improve the interface between CFs and the Al-12Si matrix, and the Cu coating becomes Al2Cu with Al matrix after stir casting. The CFs/Al composites have a relative density greater than 95% when the volume fraction of CFs is less than 8% because the CFs uniform dispersion without agglomeration in the matrix can be achieved by stir casting. The TC and CTE of CFs/Al composites are further improved with the increased CFs volume fraction, respectively. When the volume fraction of CFs is 8%, the CFs/Al composite has the best thermophysical properties; the TC is 169.25 W/mK, and the CTE is 15.28 × 10– 6/K. The excellent thermophysical properties of CFs and good interface bonding are the main reasons for improving the thermophysical properties of composites. The research is expected to improve the application of Al matrix composites in heat dissipation neighborhoods and provide certain theoretical foundations.

The primary therapeutic approach for Brucella species infections has mainly been based on antibiotic treatment. However, the development of vaccines for brucellosis control remains controversial. Furthermore, there is currently no licensed vaccine available for human brucellosis. This study aims to evaluate the effect of a combination of recombinant protein vaccines against Brucella (B.) abortus infection using a mouse model. Two B. abortus genes, namely dapB and gpm, were cloned and expressed in competent Escherichia (E.) coli DH5α using the pCold-TF vector. Successfully cloned vectors were subjected to PCR amplification using specific primer pairs. The apparent sizes of dapB and gpm were detected at 807 bp and 621 bp, respectively. Besides, the purified recombinant proteins dapB and gpm were detected using SDS-PAGE electrophoresis with correct sizes of 82.86 kDa and 87.61 kDa, respectively. These recombinant proteins were used to immunize mice as a combined subunit vaccine (CSV) to elicit host immunity against B. abortus infection. Mice immunized with CSV exhibited increased proliferation of CD4+ and/or CD8+ T cells at week 7th and 9th before sacrifice, in comparison to the control group. Notably, CSV immunization showed a significant decrease in bacterial burden in the spleen compared to the control group. Altogether, CSV using dapB and gpm induced host adaptive immune response against Brucella infection, suggesting its potential as an effective new subunit vaccine candidate.

Graphene-based sensors have emerged as significant tools for biosensing applications due to their unique electrical, mechanical, and thermal properties. In this study, we have developed an innovative and sensitive aptasensor based on the surfacemodified graphene for the detection of lung cancer biomarker CA125. The sensor leverages the combination of graphene surface and gold nanoparticles (AuNPs) electrodeposition to achieve a high level of sensitivity and selectivity for the biomarker detection. A noticeable decrease in electron transfer resistance was observed upon the AuNPs deposition, demonstrating the enhancement of electrochemical performance. Our experimental findings showed a strong linear relationship between the sensor response and CA125 concentrations, ranging from 0.2 to 15.0 ng/mL, with a detection limit of 0.085 ng/ mL. This study presents a novel approach to lung cancer detection, surpassing the traditional methods in terms of invasiveness, cost, and accuracy. The results from this work could pave the way for the development of graphene-based sensors in various other biosensing applications.

Extensive research and testing continue to be conducted for the development of vaccines targeting zoonotic diseases such as brucellosis. In this study, the potential of the DapB as a recombinant protein vaccine to effectively combat Brucella abortus 544 infection in BALB/c mice was evaluated. Western blotting assay results showed that recombinant protein DapB reacted with Brucella-positive serum, indicating its potential immunoreactivity. In vivo results showed that the peripheral blood CD4+ and CD8+ T cell population significantly increased in the DapB-immunized mice group after the first, second and third blood collection, compared to the control group that received PBS. Additionally, at the fourth blood collection, an increase in CD4+ T cell activation was observed in three vaccination groups compared to PBS negative control group. These results indicate the potential of DapB in stimulating cellular immunity. Fourteen days after infection, the bacterial load in the spleen was evaluated. The reduction in bacterial replication in the spleen by both DapB and RB51 highlights their protective efficacy against Brucella infection. These findings contribute to the ongoing efforts in developing effective vaccines against brucellosis and provide valuable insights for further research in this field.

The global PC game market is enjoying sustainable growth, and diverse grow types and quantities of games. Among the many, the theme of horror circulates in the market. Ahead of placing orders, the poster initiates the first exchange with the game, players and consumers, and affects buyers' behavior and cognition subject to its color. What is an eye-catching poster? Different games have different styles and philosophies, so it leads to a certain degree of variation in the poster design of each game. In order to study the common points of popular game color design. For the top 10 most acclaimed horror games on STEAM (PC), 5 to 6 color elements were mined from each poster for analysis and offered suggestions on poster design. First, in the color selection, more warm colors are on the list of recommendation, such as yellow, you can also choose cool colors such as blue. Second, high-saturation and high-brightness colors speak for better choice. The design of color is not absolute, and this thesis only analyzes the posters of commercially circulated and well-received horror games. It is hoped to provide insights for user-friendly interface design, support and understanding of user behaviors.

AI recommendation service is adopted in consumption consulting such as high-tech and fashion consumption (Thapliyal & Ahuj, 2021). Now, for high-tech and fashion products, the advance selling strategy is widely adopted. Thus, this study targets to detective the consumers’ preference toward AI agents comparing human agents under advance selling and spot selling. The independent variable of this study is consumption type: Pre-sale Products vs. Spot Products. Pre-sale Products are quite popular currently, especially technological products. Construal-level theory (CLT) offers a valuable framework to explain the mechanisms that trigger evaluations, predictions, and behaviors by linking the degree of mental abstraction (the construal level) to psychological distance (Trope & Liberman, 2000; 2003; 2010). Four dimensions including temporal, special, social, and probability distance are argued to present the psychological distance (Trope et al., 2007). Liberman et al. (2022) discuss the time distance and argue the distant-future events are represented in a more abstract, structured, high-level manner than near-future events. Kim & Duhachek (2020) draw on a dimension of persuasion by AI agents to posit that AI agents are perceived as low-construal agents because of the fact that people hold a lay theory that AI agents do not have superordinate goals and cannot learn from their experiences or possess consciousness like humans do. Consequently, they find that individuals perceive greater appropriateness and are more persuaded when an AI agent’s persuasive messages highlight low-construal as opposed to high-construal features. Moreover, consumers prefer abstract information related to a certain product rather than concrete information when a purchase is to take place in the distant future or when construal levels are high (Hernandez et al., 2015). Thus, this research hypothesizes: When consumers buy pre-sale products (vs. spot products), human agents will be the more favorable service provider than AI agents since the consumer is under a high level of construal. This research proposes to adopt a 2 (Advance Selling vs. Spot Selling) x 2 (Short Psychological Distance vs. Far Psychological Distance) x 2 (AI Agents vs. Human Agents) between groups experimental study to test the main effects and mechanism (H1). Furthermore, this study would identify the key moderating effects to discuss the boundary effects of the mechanism for establishing marketing strategies with AI services for managers.

The Covid-19 pandemic has caused unprecedented crises to societies and economies around the world and has brought drastic changes in the way consumers behave. Fashion business is one of the industries that has been significantly affected by Covid-19 as many consumers reduced their discretionary spending during the pandemic. While the world is entering the post-pandemic era and recovering from the pandemic, it is important to uncover and reflect on the reasons behind varying patterns of consumers’ coping behaviors associated with fashion shopping. However, current research on consumer fashion behavior during the pandemic primarily focuses on a particular type of shopping behavior, without addressing varying patterns of fashion consumption behaviors. In addition, most of these studies attributed such changes in behaviors to motivations toward protection against health-adverse threats based on the Protection Motivation Theory, which mostly focuses on protective behaviors and has limited power in understanding varying internal reasons toward various coping behaviors. Considering the varying adaptive and maladaptive patterns of fashion consumption behaviors observed in the market, it is important to address the psychological mechanism behind varying adaptive and maladaptive patterns of fashion consumption behaviors. Thus, drawing from the Stimulus-Organism-Response (SOR) framework, this study aims to investigate how cognitive appraisal of threats affects the affective/emotional state of consumers and consequently their intention to engage in various coping behaviors in the context of fashion shopping. Specifically, this study aims to investigate how individuals’ cognitive appraisals on risks and uncertainty induce varying emotional feelings (i.e., fear, anxiety, and hope), which further leads to their decisions to engage in problem vs. emotion-focused coping through fashion shopping during the pandemic.

The costs associated with law enforcement have seen a sharp increase, driven by rising personnel costs and the growing demand for policing services (Gascón, 2010; Urban Institute, 2020). Considerable discussion has arisen about how science can potentially help law enforcement “do more with less”, and some scholars have suggested introducing new crime control technologies to address this problem (e.g., Roach, 2022; Weisburd & Neyroud, 2011). With the onset of the COVID-19 pandemic, police departments around the world had additional demand, as they were made responsible for overseeing and ensuring compliance with COVID protocols. As a response, some countries (e.g., Singapore and China; Barrett, 2021) resorted to employing service robots either alongside or in place of police officers to assist with COVID-related compliance tasks.

The use of AI chatbots in frontline customer service is beneficial as it can provide quick service responses, cost-saving on human employees and accelerate customers’ decision-making process. However, implementing chatbots can be a double-edged sword. On the one hand, companies benefit from the use of chatbots. On the other hand, it may hurt customer experience as customers perceive chatbots are less trustworthy and show less social presence. Service failures today have become more unpredictable with the increasing complexity of social environments. Aligning with the trends of online customer service, customers are most likely to encounter a chatbot when seeking online customer service to solve service failures. With most of the previous literature investigating customers’ perceptions of chatbots and chatbot-related service failures, little research has focused on the area where chatbots as service recovery agents and how customers perceive the use of chatbots handling their service requests after service failures.

How to shifting consumer behavior to be more sustainable has been a hot research topic. The COVID-19 Pandemic has ignited this since consumers pay more attention to sustainability issues. Sustainability application (app) has been a promising way to connect individuals and provide information to promote a habit of sustainable consumption. The use of these apps to facilitate sustainable consumption has been a recent research focus. The strategy to encouraging app adoption is a research priority identified in a synthesized literature review of prior studies on mobile app marketing. As such, it is imperative to understand how to design sustainability apps to motivate consumers to facilitate app use intention. Attention, relevance, confidence, and satisfaction (ARCS) model is one commonly used motivational design model, which has been applied to mobile learning systems to examine gamification design. The four factors of ARCS correspond to different strategies to increase users’ motivation to use the app. Thus, the aim of this research is to develop an ARCS motivational model for sustainability apps. A simulated gamified sustainability app was utilized with the aim of reducing carbon footprint. A market research firm was contracted to collect data by using an online questionnaire. Respondents were shown the pictures and functions of the app including the interface of the app, carbon footprint status, the leaderboard of carbon emissions in the community, shop, personal profile and then answered questions. 346 usable questionnaires were obtained. Partial least squares structural equation modeling was used to analyze the data.

The wide application of digital media technology in fashion shows has become the epitome of the development and innovation of today's fashion industry, enabling designers to break through the constraints of time and space, changing the performance of today's fashion shows, and making them present unprecedented new features. With the development of information technology, the integration of emerging digital technology and the fashion industry is accelerating. So far, separate studies have been carried out in various academic fields on the combination of Metaverse and NFT, but the current status and nature of relevant research are still incomplete. Furthermore, the current research on virtual fashion shows and NFT in China's apparel industry is limited. The purpose of this study is to investigate the influence of digital fashion marketing stimulation on consumer brand attitudes using the stimulation-organ-response (SOR) framework model. By analyzing 77 cases of virtual fashion shows in China, this study obtained antecedent variables and designed a research model. An online sample of 300 Chinese Gen Z consumers was collected and analyzed using SPSS and FSQCA. This research hopes to provide valuable information for the sustainable development of China's fashion industry, and to help Chinese fashion brands confirm the future market development direction of Metaverse and NFT.

The purpose of this study is to clarify the concept of mindfulness and examine its effects on climate-friendly food perception and choice, thereby uncovering climate-friendly food by parsing out the different effects of mindfulness vs. mindlessness and exploring the key consumer outcomes. The value of this study lies in clarifying the role of climate-friendly food and mindfulness in perceived food value and food choice. This study provides a framework for examining the effects of climate-friendly food and mindfulness, thereby shedding light on climate-friendly food and discovering perceived climate-friendly food value and food choice as main outcomes. This study contributes to the literature on value by clarifying the concept of mindfulness and the relationships between perceived food value and food choice. The findings also offer practical implications for how marketing strategies for value work more effectively and cater to different types of mindfulness.

People spent around 90% of smartphone usage time on mobile applications (apps). In response to these opportunities, companies have developed branded apps to interact with consumers and facilitate loyalty. However, companies have hard time retaining consumers to their own brand due to the fierce competition in the app market. As such, it is imperative to unveil factors driving continuance intention of branded apps. This is one of a key research themes in a recent literature review of marketing research on mobile apps. Most of prior studies have adopted the utilitarian perspective where perceived usefulness and ease of use are identified as the key drivers. However, the fit perspective has received limited attention. It has gained increasing importance as recent studies have emphasized the role of person-app fit and person-brand fit in driving consumers’ purchase decision performance and as consumers’ lives are highly embedded into branded apps. This study aims to investigate continuance intention of branded apps from the fit perspective. This research selected the target branded apps in Taiwan based on prior studies. A market research firm was contracted to collect data randomly on various social media sites, and its membership database by using online questionnaires. 198 usable questionnaires were obtained. Partial least squares structural equation modeling was used to analyze the data.