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Customization, a marketing strategy through providing personalized products, might be a new solution to motivate consumer feedbacks in electronic commerce (e-commerce) websites. Taking the dual-value of customization (emotional involvement and uniqueness expression) as the theoretical basis, this study aims to investigate the impact of customization on consumer's word-of-mouth (WOM) behaviors and contents by motivating: (1) more, (2) faster, (3) positive at first and then negative, (4) longer and (5) more helpful WOMs.

A field study was conducted with multi-sourced data: customer order data from a Chinese retailer and WOM data from Amazon.com. The two datasets were matched to filter out 463 online reviews among 6,892 customers who placed customized orders. Heckman's two-stage model, logistic regression, Ordinary least squares regression, Tobit regression, analysis of covariance and Lind–Mehlum U Test were used in the data analysis.

This study has found that (1) customization level motivates WOM behaviors including WOM posting and WOM speed, (2) an inverted U-shaped relationship exists between customization level and consumer rating and (3) customization level has a significantly positive impact on WOM helpfulness but not on WOM length.

This study advances theoretical development in the area of WOM motivators by proposing a new product-centric approach, customization, to stimulate voluntary WOMs. Empirical field research that analyzes consumer's real responses to customization is in scarcity. The dual-value of customized products is proposed as the underlying mechanism to explain the impact of customization level on consumer's WOM behaviors/contents. An interesting inverted U-shaped relationship is found between customization level and customer rating. This research provides nuanced practical guidance for websites, companies and consumers.

The main research problem is the relationship between the use motivation (UM) and use behavior (UB) of middle-aged and old short videos users and the difference of the influence of the use motivation of middle-aged and old users, a special group, on the usage behavior is analyzed.

By means of a questionnaire survey and in-depth interview, the middle-aged and old-aged users' short video use motivation and behavior and their influence relationship are discussed.

It is found that information appeal is the main motivation of middle-aged and old-aged users to use short videos and users with different social attributes have differences in motivation and there is a significant relationship between motivation and behavior.

The research objective is middle-aged and elderly short video users. And how to promote the transformation of middle-aged and old-aged users' use mentality and record and create their unique bright spots in the big stage of short videos with a more active and independent attitude, is of unique significance not only to the users themselves but also to the media content of this era and the users' existence in the technological change.

This paper aims to investigate the following questions: What are the types of discussion prompts in a fully online graduate course? What are the key characteristics of students’ discussion initial posts and replies in a fully online graduate course? In what ways, if any, do discussion prompts influence the types of initial posts and replies in discussion threads?

This study adopted a qualitative approach to explore the dynamics of students’ knowledge construction through using asynchronous discussion boards. A total of 20 discussion prompts and 115 discussion threads from nine archival discussion boards in a fully online library science course were collected and analyzed.

The findings identified open-ended, explanatory and reflective prompts in discussion boards. Students engaged in simply stating, paraphrasing, elaborating, extending, reflecting, socializing and sharing emotions in discussion posts. These findings highlighted the interconnectedness of reflection and socio-emotional interactions in a community of inquiry and pointed out their important roles to support richer and deeper online discussions. The study further observed linkages between the types of discussion prompts and the types of discussion posts.

This study addressed an urgent need to understand the use of online discussion boards in an emergency remote teaching condition in a pandemic. The findings of this study offered educators insights into evidence-based design recommendations for prompts to support students’ knowledge construction and deep learning through using discussion boards.

This paper aims to develop sliding mode control (SMC) methods for second-order multi-agent systems (MAS) in the presence of mismatched uncertainties.

Based on the disturbance observer (DOB), discontinuous and continuous sliding mode protocols are designed to achieve finite-time consensus in spite of the disturbances.

Compared with integral SMC, numerical simulation results show that the proposed control methods exhibit better performance with respect to reduction of chattering.

The main contributions are the following: MAS described with mismatched uncertainties are considered; both discontinuous and continuous sliding mode controllers are considered; with the proposed sliding mode controller, the desired sliding surface can be reached in finite time and the DOB is introduced in the controller to alleviate the chattering phenomenon.

The purpose of this paper is to study the variations of composition and properties of the passive film on 316 L stainless steel surface in 80°C, 0.5 mol L-1 H2SO4 + 2 mg L-1 NaF solution, is helpful to understand the mechanisms of corrosion resistancethe of plated Pd on 316 L ss.

The variations of composition and properties of the passive film on 316 L stainless steel surface in 80°C, 0.5 mol L-1 H2SO4 + 2 mg L-1 NaF solution after connected to Pd electrode were studied with methods of potential monitor, X-ray photoelectron spectroscopy analysis and electrochemical impedance spectrum (EIS) measurement.

By connecting to a Pd electrode, the potential of the SS sample increased from the active region to the passive region. By connecting to the Pd electrode, the contents of Cr, Cr(OH)3 and Fe3O4 in passive film increased obviously. With increased Pd/SS area ratio, the Cr(OH)3 content in passive film increased but the Fe3O4 content changed little. The results show that after connecting to Pd the corrosion resistance of the passive film on 316 L stainless steel increases obviously, which may be attributed to the more compact passive film because of higher Cr, Cr(OH)3 and Fe3O4 contents and less point defects in the film.

The effects and mechanism of Pd on passivation of SS was studied.

This paper addresses the limitations of current graph neural network-based recommendation systems, which often neglect the integration of side information and the modeling of complex high-order interactions among nodes. The research motivation stems from the need to enhance recommendation performance by effectively utilizing all available data. We propose a novel method called MSHCN, which leverages hypergraph neural networks to integrate side information and model complex interactions, thereby improving user and item representations.

The MSHCN method employs a hypergraph structure to incorporate various types of side information, including social relationships among users and item attributes, which are essential for enriching user and item representations. The k-means clustering algorithm is utilized to create item-associated hypergraphs, while sentiment analysis on user reviews refines the modeling of user interests. Additionally, hypergraphs are constructed for user-user and item-item interactions based on interaction similarity. MSHCN also incorporates contrastive learning as an auxiliary task to enhance the representation learning process.

Extensive experiments demonstrate that MSHCN significantly outperforms existing recommendation models, particularly in its ability to capture and utilize side information and high-order interactions. This results in superior user and item representations and improved recommendation performance.

The novelty of MSHCN lies in its use of a hypergraph structure to integrate diverse side information and model intricate high-order interactions. The incorporation of contrastive learning as an auxiliary task sets it apart from other hypergraph-based models, providing a significant enhancement in recommendation accuracy.

The purpose of this paper is to improve the robustness of the traditional Bhattacharyya metric for the effect of histogram quantization in the histogram-based visual tracking. However, the traditional Bhattacharyya metric neglects the correlation of crossing-bin and is not robust for the effect of histogram quantization.

In this paper, the authors propose a visual tracking method via crossing-bin histogram Bhattacharyya similarity in the particle filter.

A crossing-bin matrix is introduced into the traditional Bhattacharyya similarity for measuring the reference histogram and the candidate histogram, and the basic tasks of measure such as maximum similarity of self and the triangle inequality are proven. The authors use the proposed measure in the particle filter visual tracking framework and address a model update strategy based on the crossing-bin histogram Bhattacharyya similarity to improve the robustness of visual tracking.

In the experiments using the famous challenging benchmark sequences, precision of the proposed method increases by 12.8 per cent comparing the traditional Bhattacharyya similarity and the cost time decreases by 38 times comparing the incremental Bhattacharyya similarity. The experimental results show that the proposed method can track the object robustly and rapidly under illumination change and occlusion.

In this paper, the C80 special coal gondola car was taken as the subject, and the load test data of the car body at the center plate, side bearing and coupler measured on the dedicated line were broken down to generate the random load component spectrums of the car body under five working conditions, namely expansion, bouncing, rolling, torsion and pitching according to the typical motion attitude of the car body.

On the basis of processing the measured load data, the random load component spectrums were equivalently converted into sinusoidal load component spectrums for bench test based on the principle of pseudo-damage equivalence of load. Relying on the fatigue and vibration test bench of the whole railway wagon, by taking each sinusoidal load component spectrum as the simulation target, the time waveform replication (TWR) iteration technology was adopted to create the drive signal of each loading actuator required for the fatigue test of car body on the bench, and the drive signal was corrected based on the equivalence principle of measured stress fatigue damage to obtain the fatigue test loads of car body under various typical working conditions.

The fatigue test results on the test bench were substantially close to the measured test results on the line. According to the results, the relative error between the fatigue damage of the car body on the test bench and the measured damage on the line was within the range of −16.03%–27.14%.

The bench test results basically reproduced the fatigue damage of the key parts of the car body on the line.

An exact pattern prototype is a prerequisite for female girdle pattern-making. The purpose of this paper is to develop new ways to make girdle pattern prototypes based on 3D technology.

This paper presented two novel methods for creating girdle pattern prototypes. The first one was the girdle's parametric foundation pattern developing method based on 3D geometric modeling. In this method, considering the different characteristics of a female's lower body shape, several models were created to define the relationship between the female's lower body shape and the pattern, such as a side-waist curvature model, an interior-posterior waist-warping model, a buttocks' parametric model and an abdomen parametric model. Then, parameters of drawing the prototype were abstracted to facilitate transforming the 3D geometric model into the 2D pattern. Another method was implemented by 3D virtual modeling and unwrapping. The whole process included surface division, surface reconstruction and surface unwrapping.

The prototypes created by these two methods were tested using the 3D virtual trying-on examination. Trial tests showed that the patterns can be dressed in the right positions on the virtual model with little pressure. This means that the proportions and shapes of the pattern are correct. The prototypes obtained through the methods proposed in this paper have good effects and high precision. Both methods can be used for making the girdle's foundation pattern.

Two pragmatic approaches of girdle's prototype building have been put forward. The parametric prototype designing method has changed the unconstrained state of free modeling. The pattern structure can be controlled by parameter constraints. In the other method, with 3D scanning and surface modeling technology, personalized girdle's pattern is generated, and the segmentation lines of the girdle can be designed flexibly according to the requirements. These findings also can be used in other tight garments' prototype making.

This study aims to analyse the scientific relationship between technological innovation and carbon emissions. Taking the Chinese electric power industry as the empirical research object, this study examined the effect of power technological innovation on carbon emissions and proposed policy recommendations for the development of technological innovation in China.

This study first calculated the energy consumption and carbon emission level of the Chinese electric power industry from 2005 to 2018. Secondly, this study built an evaluation index system for technological innovation of electric power with six indicators: average utilisation hours of power generation equipment; power consumption rate of power plant; line loss rate; standard coal consumption for power generation; standard coal consumption for power supply; and number of patent applications granted for generation, conversion or distribution of electric power in China. Finally, from a practical point of view, the relationship between technological innovation and carbon emissions of the Chinese electric power industry from 2005 to 2018 is evaluated and analysed.

Power technology innovation has been found to have a long-term and relatively large effect on carbon emissions, and carbon emissions have a short-term and insignificant impact on power technology innovation.

This study puts forward relevant suggestions for developing technological innovation and technology transfer, which is essential to establishing a low-carbon or zero-carbon power system in China.

This study provides empirical evidence for clarifying the relationship between technological innovation and carbon emissions in the power industry and further develops research theories on technological innovation and carbon emissions.

Relevant authorities will adopt measures to promote technological innovation and development in the power sector to reduce carbon emissions.

This study built an evaluation index system with six indicators for technological innovation of electric power. The evaluation method was used to measure the technological innovation level of the Chinese electric power industry. The causal link between technological innovation and carbon emissions in China was analysed.