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This study aims to produce composite pigments, including SHS/ZnAl-LDHs, IDS/ZnAl-LDHs and SNND/ZnAl-LDHs, with improved coloration, enhanced photostability and thermostability and biocompatibility.

The chemical structures of the composite pigments were characterized by X-ray diffraction spectroscopy and Fourier transform infrared spectroscopy. Photostability and thermal stability were assessed using ultraviolet-visible spectroscopy and colorimetry. The coverage of the dyes was determined through black-and-white tile testing, and specific RGB values were used to indicate color expressiveness. Finally, a four-color eyeshadow was formulated, and safety tests were conducted via human patch test and cellular assays to confirm the safety and reliability of the samples.

The experimental results demonstrate an enhancement in the photo and thermal stability of the SHS/ZnAl-LDHs, IDS/ZnAl-LDHs and SNND/ZnAl-LDHs composites, along with their superior performance in terms of covering power and color saturation. These composite pigments also exhibit high safety, making them well-suited for cosmetic applications.

The composite pigments based on hydrotalcite can be used in the cosmetic industry without causing any harm to the environment and human health.

The addition of hydrotalcite enables better application of pigments in cosmetics.

The purpose of this study is to prolong the service life of the Al–Si alloy cylinder and achieve the objective of energy saving and emission reduction by the composite treatments.

Chemical etching + laser texturing + filled MoS₂ composite treatment was applied to the friction surface of aluminum–silicon (Al–Si) alloy cylinder. The friction coefficient and wear loss were measured to characterize the tribology property of cylinders.

The composite-treated Al–Si alloy cylinder had the lowest friction coefficient and weight loss. The friction coefficient and weight loss of the composite treatment were approximately 27.08% and 54.17% lower than those of the untreated sample, respectively. The laser micro-textures control the release of solid lubricant to the interface of friction pairs slowly, which prolongs the service life of cylinders.

The synergistic effect of the chemical etching + laser texturing + filled MoS2 modified the tribology properties of Al–Si alloy cylinder. The chemical etching raised the silicon particles to bear the load, and laser micro-textures control the release of solid lubricant to improve the lubrication property.

The development of prefabricated buildings has become one of the primary solutions to transform the traditional construction industry around the world. Incentive policy is one of the important driving factors for the development of prefabricated building. The policy system in the field of prefabricated buildings needs to be improved urgently. However, there is still a dearth of research on how incentive policies exert impact on the development of prefabricated buildings. This paper aims to reveal the impact mechanisms of different types of policies on the development system of prefabricated buildings.

This study categorizes prefabricated building policies, constructs a system dynamics model of prefabricated building policies and conducts scenario simulations to examine the impact and sensitivity of different types of policies on the development system of prefabricated buildings.

The results show that compulsory policies play a greater role in the early stage of prefabricated building development and need to be withdrawn at the right time. Preferential and encouraging policies play an incentive role in the middle and later stages of prefabricated building development. Encouraging policies predominate in the later stage of prefabricated building development. Based on the research results, policy recommendations for prefabricated building development are put forward respectively from the government, developers and consumers.

The research results are expected to make up for the lack of clear policies paths in existing research and provide theoretical references for the formulation and optimization of future policies.

The purpose of this paper is to propose a DC-port voltage balance strategy realizing it by logic combination modulation (LCM). This voltage balance strategy is brief and high efficient, which can be used in many power electronic devices adopting the cascaded H-bridge rectifier (CHBR) such as power electronic transformer (PET).

The CHBR is typically as a core component in the power electronic devices to implement the voltage or current conversion. The modulation method presented here is aiming to solve the voltage imbalance problem occurred in the CHBR with more stable work station and higher reliability in ordinary operating conditions. In particular, by changing the switch states smoothly and quickly, the DC-port voltage can be controlled as the ideal value even one of the modules in CHBR is facing the load-removed problem.

By using the voltage balance strategy of LCM, the problem of voltage imbalance occurring in three-phase cascaded rectifiers has been solved properly. With the lower modulation depth, the efficiency of the strategy is shown to be better and stronger. The strategy can work reliably and quickly no matter facing the problem as load-removed change or the ordinary operating conditions.

The limitation of the proposed DC-port voltage balance strategy is calculated and proved, in a three-module CHBR, the LCM could balance the DC-port voltage while one module facing the load-removed situation under 0.83 modulation depth.

This paper provides a useful and particular voltage balance strategy which can be used in the topology of three-phase cascaded rectifier. The value of the strategy is that a brief and reliable voltage balance method in the power electronic devices can be achieved. What is more, facing the problem, such as load-removed, in outport, the strategy can response quickly with no switch jump and switch frequency rising.

This paper aims to assess the level of occupants’ satisfaction, comparing older and newer on-campus accommodation buildings in Sydney, Australia, aiming to identify their comfort factors deficiencies in terms of design and construction solutions/strategies (e.g. spatial arrangements, materials, thermal comfort).

A post occupancy evaluation survey was used to assess the occupant satisfaction with three on-campus accommodation buildings in The University of New South Wales (UNSW) Sydney. One of the selected buildings is an older building opened for occupation in 1996, and the other two are more recent on campus accommodations buildings. The survey included 11 post occupancy evaluation elements identified through literature review which were categorised into three dimensions: technical, functional and behavioural.

The results show that the satisfaction levels with thermal and acoustic comfort were below standards for both older and newer buildings. In addition, the older building used in this study was rated low in terms of: indoor air quality, lighting, maintenance and management, vertical transportation facility, room layout and furniture quality, building layout and aesthetics and level of privacy. Such factors related to both functional and behavioural dimensions were of greater satisfaction in newer buildings.

Findings suggest the high priority of strategies that address and improve the thermal and acoustic comfort of older and newer on-campus accommodation buildings if the intention is to enhance students’ satisfaction, especially considering the impact that these facilities have on students’ performance. Thermal performance in different seasons and adaptive thermal comfort activities should be considered in the design of new on-campus accommodation buildings and the retrofit of existing old buildings.

On-campus accommodation is an important facility that supports student learning outcomes and helps students adapt in a new learning environment. A post occupancy evaluation study to assess the adequacy of this facility is still lacking because previous studies have generally focussed on class rooms and work spaces in the education sector. This research compares the user satisfaction of older and newer on-campus accommodation buildings in Australia, to highlight deficiencies and areas for improvement in the design of existing and future buildings.

Artificial intelligence (AI) and big data analysis may further enhance the automated and smart features of tourism and hospitality services. However, it also poses new challenges to human resource management. This study aims to explore the direct and indirect effects of employees’ AI perception on career resilience and informal learning as well as the mediating effect of career resilience.

This paper proposed a theoretical model of AI perception, career resilience and informal learning with perceived AI as the antecedent variable, career resilience as the mediate variable and informal learning as the endogenous variable. Targeting the employees working with AI, a total of 472 valid data were collected. Data were analyzed using structural equation modeling with AMOS software.

Findings indicated that employees’ perception of AI positively contributes to career resilience and informal learning. Apart from the direct effect on informal learning, career resilience also mediates the relationship between AI perception and informal learning.

Research findings provide both theoretical and practical implications by revealing the impact of AI perception on employees’ career development, leaning activities, explaining how AI transforms the nature of work and career development and shedding lights on human resource management in the tourism and hospitality field.

本文提出了人工智能感知为前因变量、职业弹性为中介变量、非正式学习为内生变量的理论模型。以旅游业AI工作环境中的员工为研究对象, 本课题共收集了472份来自中国的有效数据, 并通过结构方程建模（SEM）来进行相关模型检验。

人工智能和大数据分析可能会使旅游和酒店服务更加自动化和智能化, 但这也对人力资源管理提出了新的挑战。本研究旨在探讨员工对人工智能（AI）的感知对职业弹性和非正式学习的直接和间接影响, 以及职业弹性的中介作用。

研究结果显示, 员工对人工智能的感知对职业弹性和非正式学习有积极影响。除了对非正式学习的直接影响外, 职业弹性在人工智能 (A I) 感知和非正式学习之间起中介作用。

本研究在以下几个方面具有重要的理论和实践意义：解释了人工智能感知对员工职业发展和学习行为的影响, 以及它是如何改变工作性质和员工职业发展的; 研究发现对旅游和酒店行业的人力资源管理具有实践指导意义。

La IA y el análisis de big data pueden potenciar aún más las características automatizadas e inteligentes de los servicios de turismo y hostelería. Sin embargo, también plantea nuevos retos a la gestión de los recursos humanos. Este estudio pretende explorar los efectos directos e indirectos de la percepción de la IA por parte de los empleados sobre la resiliencia profesional y el aprendizaje informal, así como el efecto mediador de la resiliencia profesional.

En este trabajo se propone un modelo teórico de percepción de la IA, resiliencia profesional y aprendizaje informal con la IA percibida como variable antecedente, la resiliencia profesional como variable mediadora y el aprendizaje informal como variable endógena. Dirigidos a los empleados que trabajan con IA, se recogieron un total de 472 datos válidos. Los datos se analizaron mediante un modelo de ecuaciones estructurales (SEM) con el software AMOS.

Los Resultados indicaron que la percepción de la IA por parte de los empleados contribuye positivamente a la resiliencia profesional y al aprendizaje informal. Aparte del efecto directo sobre el aprendizaje informal, la resiliencia profesional también media en la relación entre la percepción de la IA y el aprendizaje informal.

Los Resultados de la investigación proporcionan implicaciones tanto teóricas como prácticas al revelar el impacto de la percepción de la IA en el desarrollo profesional de los empleados, las actividades de aprendizaje, explicar cómo la IA transforma la naturaleza del trabajo y el desarrollo profesional, y arrojar luz sobre la gestión de los recursos humanos en el ámbito del turismo y la hostelería.

The purpose of this paper is to introduce an improved system identification method for small unmanned helicopters combining adaptive ant colony optimization algorithm and Levy’s method and to solve the problem of low model prediction accuracy caused by low-frequency domain curve fitting in the small unmanned helicopter frequency domain parameter identification method.

This method uses the Levy method to obtain the initial parameters of the fitting model, uses the global optimization characteristics of the adaptive ant colony algorithm and the advantages of avoiding the “premature” phenomenon to optimize the initial parameters and finally obtains a small unmanned helicopter through computational optimization Kinetic models under lateral channel and longitudinal channel.

The algorithm is verified by flight test data. The verification results show that the established dynamic model has high identification accuracy and can accurately reflect the dynamic characteristics of small unmanned helicopter flight.

This paper presents a novel and improved frequency domain identification method for small unmanned helicopters. Compared with the conventional method, this method improves the identification accuracy and reduces the identification error.

The purpose of this paper is to study the unit train make-up scheme for loaded direction in the heavy haul railway.

A 0-1 nonlinear integer programming model with the aim of minimizing the idling period between actual train arrival time and expected train arrival time for all loaded unit trains are proposed.

The proposed model is applied into a case study based on Daqin heavy haul railway. Results show that the proposed model can offer operators an optimal unit train make-up scheme for loaded direction in heavy haul railway.

The proposed model can offer operators an optimal unit train make-up scheme for loaded direction in heavy haul railway.

Project portfolio risk (PPR) management plays an important role in promoting the smooth implementation of a project portfolio (PP). Accurate PPR prediction helps managers cope with risks timely in complicated PP environments. However, studies on accurate PPR impact degree prediction, which consists of both risk occurrence probabilities and risk impact consequences considering project interactions, are limited. This study aims to model PPR prediction and expand PPR prediction tools.

In this study, the authors build a PPR prediction model based on a genetic algorithm and back-propagation neural network (GA-BPNN) integrated with entropy-trapezoidal fuzzy numbers. Then, the authors verify the proposed model with real data and obtain PPR impact degrees.

The test results indicate that the proposed method achieves an average absolute error of 0.002 and an average prediction accuracy rate of 97.8%. The former is reduced by 0.038, while the latter is improved by 32.1% when compared with the results of the original BPNN model. Finally, the authors conduct an index sensitivity analysis for identifying critical risks to effectively control them.

This study develops a hybrid PPR prediction model that integrates a GA-BPNN with entropy-trapezoidal fuzzy numbers. The authors use this model to predict PPR impact degrees, which consist of both risk occurrence probabilities and risk impact consequences considering project interactions. The results provide insights into PPR management.

This study aims to quantify the underlying feelings of online reviews and discover the role of seasonality in customer dining experiences.

This study applied sentiment analysis to determine the polarity of a given comment. Furthermore, content analysis was conducted based on the core attributes of the customer dining experiences.

Positive feelings towards the food and the service do not show a linear relationship, while the overall dining experiences increase in line with the positive feelings on food quality. Moreover, feelings towards the atmosphere of the restaurants are the most positive in peak season.

This study provides guidelines for restaurateurs regarding the aspects that need more attention in different seasons.

The paper contributes to the knowledge of customer feelings in local restaurants/gastronomy and the role seasonality plays in fostering such feelings. In addition, the novel methodological procedures provide insights for tourism research in discovering new dimensions in theories based on big data.

本论文旨在量化在线评论中的情感导向以及发掘季节性对消费者用餐体验的作用。

本论文采用情感分析法对既定评论做出情感判断。此外, 本文还依据消费者用餐体验中的核心价值采用了内容分析法。

研究发现消费者对食物和服务的正向情感并不是线性关系。然而, 整体用餐体验与对食物质量的正向情感是线性正向的关系。此外, 消费者对饭店氛围的情感在旺季的时节是最为突出的。

本论文对饭店从业者在不同季节的关注点上起到了指导作用。

本论文对地方饭店/美食的消费者情感认知做出了贡献, 此外, 本论文还对季节性如何促进消费情感的作用做出了研究。本论文还采用了新型的研究方法, 这对于旅游研究来说, 做出了基于大数据的新理论研究方向。