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Ultracapacitors find extensive applications in various fields because of their high energy density and long cycling periods. However, due to the movement of ions and the arrangement patterns on rough/irregular electrode surfaces during the charge and discharge process of ultracapacitors, the parameters of ultracapacitors usually change with the variation of operating conditions. The purpose of this study is to accurately and quickly identify the parameters of ultracapacitors.

A variable forgetting factor recursive least square (VFFRLS) algorithm is proposed in this paper for online identifying the equivalent series resistance and capacitance C of ultracapacitors. In this work, a real-time error-based strategy is developed to adaptively regulate the value of the forgetting factor of traditional forgetting factor recursive least square (FFRLS) algorithm. The strategy uses the square of the average time autocorrelation estimation of the prior error and the posterior error between the predicted output and the actual output as the adjustment basis of forgetting factors.

Experiments were conducted using the proposed scheme, and the results were compared with the estimation results obtained by the recursive least squares (RLS) algorithm and the traditional FFRLS algorithm. The maximum root mean square error between the estimated values and actual values for VFFRLS is 3.63%, whereas for FFRLS it is 9.61%, and for RLS it is 19.33%.

By using the proposed VFFRLS algorithm, a relatively high precision can be achieved for the online parameter estimation of ultracapacitors. Besides, the dynamic balance between parameter stability and tracking performance can be validated by dynamically adjusting the forgetting factor.

This chapter presents three Chinese teachers' narrative accounts about how they live in dilemmatic spaces due to excessive entitlement. Still, the teachers move forward with transformative agency. The thick description of the three teacher participants has been reported elsewhere as the narratives of Lee – a math teacher, Ping – a Chinese language teacher and Wang – a school principal. In this chapter, however, ‘excessive teacher entitlement’ is used as a new lens to assist me in revisiting their stories of living in dilemmatic spaces. Narrative inquiry as a method unpacks the three teachers' life experiences. Although Lee, Ping and Wang encounter different entitlements and various dilemmas, their transformative agency in transitioning from a survival mode to thriving human beings brings out the similarities in their experiences. Using Vygotskian philosophy and cultural-historical activity theory (CHAT), this chapter focuses on the teachers' transformative agency as breaking away from given boundaries in their professional lives and taking up initiatives that confront the tacit excessive entitlement in and around them. Furthermore, transformative agency is promising in that it helps develop new practices in teacher education. Finally, the new understanding emanating by viewing the three subjects' experiences from the angle of excessive entitlement has the potential to inspire teachers in other contexts to become conscious of manifestations of excessive entitlement not only in themselves or others they interact with but also in the macro context we live in. This consciousness also increases the likelihood of the urge to find ways to ameliorate excessive entitlement and to move closer to one's cherished professional values.

As after-hours technology-mediated work (ATW) becomes common in organizations, the increased workload and interference to life caused by ATW has induced employee turnover. This research develops a mediated moderation model to explain how employees' intrinsic and extrinsic motivations for ATW affect their turnover intention through work–life conflict.

A survey was conducted to collect data of 484 employees from Chinese companies. Partial Least Square was used to perform data analysis.

The results show that intrinsic motivation for ATW has an indirect negative impact on turnover intention via work–life conflict, whereas extrinsic motivation for ATW has both a positive direct impact and a positive indirect impact (via work–life conflict) on turnover intention. This study also helps find that time spent on ATW can strengthen the positive impact of extrinsic motivation for ATW on turnover intention but has no moderation effect on the impact of intrinsic motivation for ATW. Furthermore, this study reveals that the interaction effect of time spent on ATW and extrinsic motivation on turnover intention is mediated by employees' perceived work–life conflict.

By discovering the distinct impact of employees' intrinsic and extrinsic motivations for ATW on turnover intention, this research provides a contingent view regarding the impact of ATW and offers guidance to managers regarding how to mitigate ATW-induced turnover intention through fostering different motivations.

Traditional grey models are integer order whitening differential models; these models are relatively effective for the prediction of regular raw data, but the prediction error of irregular series or shock series is large, and the prediction effect is not ideal.

The new model realizes the dynamic expansion and optimization of the grey Bernoulli model. Meanwhile, it also enhances the variability and self-adaptability of the model structure. And nonlinear parameters are computed by the particle swarm optimization (PSO) algorithm.

Establishing a prediction model based on the raw data from the last six years, it is verified that the prediction performance of the new model is far superior to other mainstream grey prediction models, especially for irregular sequences and oscillating sequences. Ultimately, forecasting models are constructed to calculate various energy consumption aspects in Chongqing. The findings of this study offer a valuable reference for the government in shaping energy consumption policies and optimizing the energy structure.

It is imperative to recognize its inherent limitations. Firstly, the fractional differential order of the model is restricted to 0 < a < 2, encompassing only a three-parameter model. Future investigations could delve into the development of a multi-parameter model applicable when a = 2. Secondly, this paper exclusively focuses on the model itself, neglecting the consideration of raw data preprocessing, such as smoothing operators, buffer operators and background values. Incorporating these factors could significantly enhance the model’s effectiveness, particularly in the context of medium-term or long-term predictions.

This contribution plays a constructive role in expanding the model repertoire of the grey prediction model. The utilization of the developed model for predicting total energy consumption, coal consumption, natural gas consumption, oil consumption and other energy sources from 2021 to 2022 validates the efficacy and feasibility of the innovative model.

These findings, in turn, provide valuable guidance and decision-making support for both the Chinese Government and the Chongqing Government in optimizing energy structure and formulating effective energy policies.

This research holds significant importance in enriching the theoretical framework of the grey prediction model.

The highlights of the paper are as follows:

1. A novel grey Bernoulli prediction model is proposed to improve the model’s structure.

2. Fractional derivative, fractional accumulating generation operator and Bernoulli equation are added to the new model.

3. The proposed model can achieve full compatibility with the traditional mainstream grey prediction models.

4. Energy consumption in Chongqing verifies that the performance of the new model is much better than that of the traditional grey models.

5. The research provides a reference basis for the government to formulate energy consumption policies and optimize energy structure.

A novel grey Bernoulli prediction model is proposed to improve the model’s structure.

Fractional derivative, fractional accumulating generation operator and Bernoulli equation are added to the new model.

The proposed model can achieve full compatibility with the traditional mainstream grey prediction models.

Energy consumption in Chongqing verifies that the performance of the new model is much better than that of the traditional grey models.

The research provides a reference basis for the government to formulate energy consumption policies and optimize energy structure.

In response to the challenges posed by the conventional manual flange docking method in the LNG (Liquefied Natural Gas) loading process, such as low positioning accuracy, constraints on production efficiency and safety hazards, this study analyzed the LNG five-axis loading arm’s main functions and structural characteristics.

An automated solution for the joints of the LNG loading arm was designed. The forward kinematic model of the LNG loading arm was established using the Denavit–Hartenberg (D-H) parameter method, and its workspace was analyzed. The Newton–Raphson iteration method was employed to solve the inverse kinematics of the LNG loading arm, facilitating trajectory planning. The relationship between the target position and the joint variables was established to verify the stability of the arm’s motion. Flange center identification was achieved using the Hough transform function. Based on the ROS platform, combined with Gazebo and Rviz, an experimental simulation of automatic docking of the LNG loading arm was conducted.

The docking errors in the XYZ directions were all less than 0.8 mm, meeting the required docking accuracy. Moreover, the motion performance of the loading arm during docking was smooth and free of abrupt changes, validating its capability to accomplish the automatic docking task.

The proposed trajectory planning and automatic docking scheme can be used for the rapid filling of LNG filling arms and LNG tankers to improve the efficiency of LNG transportation. In guiding the docking, the proposed automatic docking scheme is an accurate and efficient way to improve safety.

Two friction models of Fe-Fe and Diamond-like carbon (DLC)-Fe were established by molecular dynamics (MD) method to simulate the friction behavior of traditional fracturing pump plunger and new DLC plunger from atomic scale. This paper aims to investigate the effects of temperature and load on the friction behavior between sealed nitrile butadiene rubber (NBR) and DLC films.

In this study, MD method is used to investigate the friction behavior and mechanism of DLC film on plungers and sealing NBR based on Fe-Fe system and DLC-Fe system.

The results show that the friction coefficient of DLC-Fe system exhibits a downward trend with increasing load and temperature. And even achieve a superlubricity state of 0.005 when the load is 1 GPa. Further research revealed that the low interaction energy between DLC and NBR promoted the proportion of atoms with larger shear strain in NBR matrix and the lower Fe layer in DLC-Fe system to be much lower than that in Fe-Fe system. In addition, the application of DLC film can effectively inhibit the temperature rise of friction interface, but will occur relatively large peak velocity.

In this paper, two MD models were established to simulate the friction behavior between fracturing pump plunger and sealing rubber. Through the analysis of mean square displacement, atomic temperature, velocity and Interaction energy, it can be seen that the application of DLC film has a positive effect on reducing the friction of NBR.

This paper aims to analyze how smart city construction affects destination competitiveness and elucidates the potential mechanisms of digital economy. Also, the regional heterogeneity of smart city construction’s influence on destination competitiveness is discussed.

Given the quasi-natural experiment characteristics of China's smart city construction pilot, this study applies a time-varying difference-in-differences approach using a panel dataset of 272 Chinese prefectural-level cities to examine the causal effects of smart city construction on destination competitiveness.

Results indicate substantial enhancement of urban destination competitiveness from smart city construction, with this effect escalating annually. Digital infrastructure and digital finance serve as influence mechanisms. The positive impacts of smart city construction on urban tourism competitiveness do not differ by geographic location, rather there are significant differences between cities of different administrative levels. The impact of smart city construction on destination competitiveness is more significant in low administrative level cities. The improvement of economic development level and innovation ability helps to exert the positive impact of smart cities on tourism competitiveness.

This study constructs a new panel data set for smart city construction and destination competitiveness based on multi-source data and posits a theoretical linkage among smart city construction, digital economy and destination competitiveness. This paper provides invaluable insights on how to boost destination competitiveness by creating smart cities and leveraging the digital economy. Tourism sectors should proactively engage in smart city construction and foster the digital transformation of tourism.

本文旨在分析智慧城市建设如何影响目的地竞争力, 并阐明数字经济的潜在机制。此外, 还讨论了智慧城市建设对目的地竞争力影响的区域异质性。

鉴于中国智慧城市建设试点的准自然实验特征, 本研究基于272个中国地级城市的面板数据集, 采用双重差分方法检验了智慧城市建设对目的地竞争力的因果影响。

研究结果表明, 智慧城市建设显著增强了城市目的地竞争力, 这种影响每年都在增加。数字基础设施和数字金融是影响机制。智慧城市建设对城市旅游竞争力的积极影响不因地理位置而异, 不同行政级别的城市之间存在显著差异。智慧城市建设对低行政级别城市目的地竞争力的影响更为显著。经济发展水平和创新能力的提高有助于发挥智慧城市对旅游竞争力的积极影响。

本研究基于多源数据构建了一个新的智慧城市建设和目的地竞争力面板数据集, 并在智慧城市建设、数字经济和目的地竞争之间建立了理论联系。本文就如何通过创建智慧城市和利用数字经济来提高目的地竞争力提供了宝贵的见解。旅游部门应积极参与智慧城市建设, 促进旅游业的数字化转型。

El objetivo de este artículo es analizar cómo afecta la construcción de ciudades inteligentes a la competitividad de los destinos y dilucidar los posibles mecanismos de la economía digital. Se aborda también la heterogeneidad regional de la influencia de la construcción de ciudades inteligentes en la competitividad de los destinos.

Dadas las características de experimento casi natural del proyecto piloto de construcción de ciudades inteligentes en China, este estudio aplica un enfoque de diferencias en diferencias temporales utilizando un conjunto de datos de panel de 272 ciudades chinas de nivel de prefectura para examinar los efectos causales de la construcción de ciudades inteligentes sobre la competitividad de los destinos.

Los resultados indican una mejora sustancial de la competitividad de los destinos urbanos gracias a la construcción de ciudades inteligentes, efecto que aumenta cada año. La infraestructura digital y las finanzas digitales actúan como mecanismos de influencia. Los efectos positivos de la construcción de ciudades inteligentes sobre la competitividad Del turismo urbano no difieren en función de la ubicación geográfica, sino que las diferencias significativas se producen entre ciudades de diferentes niveles administrativos. El impacto de la construcción de ciudades inteligentes en la competitividad de los destinos es más significativo en las ciudades de bajo nivel administrativo. La mejora del nivel de desarrollo económico y la capacidad de innovación contribuyen al impacto positivo de las ciudades inteligentes en la competitividad turística.

Este estudio construye un nuevo conjunto de datos de panel para la construcción de ciudades inteligentes y la competitividad de los destinos basado en datos de múltiples fuentes y plantea un vínculo teórico entre la construcción de ciudades inteligentes, la economía digital y la competitividad de los destinos. Este artículo ofrece un valioso conocimiento sobre cómo impulsar la competitividad de los destinos mediante la creación de ciudades inteligentes y el aprovechamiento de la economía digital. Los sectores turísticos deberían participar de forma proactiva en la construcción de ciudades inteligentes y fomentar la transformación digital del turismo.

This study aims to investigate the relationship between corporate environmental responsibility (CER) and risk-taking in Chinese A-share listed companies from 2011 to 2020. It seeks to understand the influence of CER on risk-taking behavior and explore potential moderating factors.

A quantitative approach is used, using data from Chinese A-share listed companies over the specified period. Regression analysis is used to examine the relationship between CER and risk-taking, while considering moderating variables such as performance aspiration, environmental enrichment and contextual factors.

The findings indicate that CER positively influences corporate risk-taking, with significant impacts on information asymmetry and corporate reputation. Moreover, positive performance aspiration strengthens the effect of CER on risk-taking, while negative performance aspiration and environmental enrichment weaken this effect. Cross-sectional analysis shows that the positive association between CER and risk-taking is more prominent for firms located in areas with strict environmental regulation, for nonstate-owned firms, and for firms with higher levels of internal control.

This research contributes to the literature by providing insights into the dynamics between CER and risk-taking in the Chinese market context. It expands existing knowledge by considering the influence of performance aspiration on this relationship, offering practical implications for firms seeking to enhance corporate performance through strategic management of environmental responsibilities.

The study aims to provide a detailed definition of Destination Cultural Reputation while also exploring its impact on tourist satisfaction through an investigation of the dynamics between these two elements. Additionally, the potential moderating role of on-site engagement in sustainable activities has been investigated, examining whether satisfaction prompts tourists to exhibit behaviors such as the intention to return and recommend the cultural destination.

To achieve these objectives, a survey and a structural equation model, based on a sample of 647 visitors to an important UNESCO World Heritage site (i.e. Urbino), have been adopted.

Findings confirm tourists’ recognition of the destination’s cultural reputation, supporting its relationship with visitor satisfaction. Additionally, tourist satisfaction is positively associated with destination loyalty. However, on-site sustainable activities negatively moderate the relationship between destination reputation and tourist satisfaction. This suggests that a favorable cultural reputation should align with quality sustainable activities in the destination to prevent tourist dissatisfaction.

The paper offers valuable practical insights for destination managers and policymakers aiming to enhance appeal and sustainability.

The study contributes to enhancing the understanding of the complex relationship between reputation, satisfaction, and loyalty in cultural destinations. In addiction it measures the reputation of tourist destination through the specific cultural dimension.

The purpose of this study is to systematically analyze the wear of cylindrical needle bearings in rotary vector reducers under temperature rise and identify the influencing factors.

Based on the dynamic characteristics of the RV-20E reducer, the time-varying contact force of the cylindrical needle bearing and the entrainment speed of the inner and outer raceways were calculated. A mixed elastohydrodynamic lubrication model of the needle bearing, considering friction and temperature rise, was established using a dynamic rough tooth surface model. The model solved for the oil film thickness, contact stress and wear conditions of the bearing raceway contact area. The effects of the number of rolling needles, the diameter of rolling needles and surface strength on the wear characteristics were analyzed.

The results of this study show that the oil film thickness, oil film pressure and surface scratches of cylindrical needle bearings exhibit an uneven, patchy distribution under the combined effects of friction and temperature rise. When the radius of the rolling needle is less than 1.44 mm, inner ring wear is less than outer ring wear. Conversely, when the radius exceeds 1.44 mm, inner ring wear is greater. The optimal rolling needle radius is 1.6 mm. Increasing the number of rolling needles and enhancing the yield strength of the contact surface significantly extend bearing life.

This study provides valuable recommendations for optimizing bearing structural parameters and material characteristics in the design of rotary vector reducers.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0242/