Search results

Tantalum is a kind of metal material with moderate hardness, high ductility, small thermal expansion coefficient, excellent corrosion resistance and outstanding biocompatibility. The purpose of this study is that its tribological performance could be tested and analyzed so as to use it in different fields.

The friction resistance of a-Ta under dry friction conditions was tested at different roads. The relationships between load and friction coefficient, wear rate and two-dimensional shape of wear scars were studied.

The stable Ta₂O₅ film with lubrication effect was generated in the process of friction. And, the larger the test load, the more Ta₂O₅ would be generated.

This work lays a theoretical foundation for tantalum as an excellent wear-resistant material.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2023-0047/

Rhetorical figures are frequently used in English-Chinese advertisement translation, but their impact on consumers is an under-studied issue. This research aims to explore Chinese consumers’ perception of two categories of rhetorical figures in bilingual advertising, namely schemes and tropes, via an eye-tracking experiment.

It takes rhyme and antithesis as representative examples of schemes and takes metaphor as an example of tropes. Eighty-six native Chinese speakers with satisfactory English proficiency participated in the experiment. Thirty English slogans without rhetorical figures were selected for the experiment. Two parallel Chinese versions were prepared, one with rhetorical figures and the other without. Participants were randomly assigned to read the English version and one Chinese version.

Data analyses show that the translations with rhetorical figures generally involve higher fixation duration or count, smaller saccade amplitude and higher subjective ratings. In particular, the impact of metaphor is more prominent than that of rhymes and antitheses. Still, English texts receive higher ratings than Chinese translations except for cases where metaphors are used in translations.

The results suggest that incorporating rhetorical figures particularly tropes into Chinese translations is effective in increasing Chinese consumers’ attention and processing depth and to present English advertisements together with Chinese translations can be helpful for affecting their attitude.

It applies the eye-tracking approach to explore Chinese consumers’ perception of rhetorical figures. It provides empirical evidence for the effectiveness of tropes.

This study aims to present a novel topology optimization method for effectively minimizing the frequency response over a given frequency interval considering anisotropic features and fiber angles simultaneously.

The variable thickness sheet (VTS) method is used to obtain a free material distribution under the specified volume constraint. The anisotropic equivalent stiffness matrix based on the material fiber angles is considered in the orthotropic material properties model, which ensures a sufficiently large design space to minimize the frequency response. To lessen the computational burden, the quasi-static Ritz vector (QSRV) method is integrated to approximate the structural response.

Compared to considering only one element, the optimization process simultaneously considers the spatially-varying fiber angles and the material distribution, allowing for a broader design space to minimize the frequency response of additive manufacturing (AM) structures. The orthotropic properties play an important role in determining optimal material distribution of the structure. Moreover, the QSRV method makes the frequency response analysis more efficient.

The anisotropic stiffness and spatially-varying angles of the fiber materials induced by the layer-by-layer printing process of carbon fiber reinforced plastics (CFRP) are simultaneously considered to further minimize the frequency response of AM structures, which improves the performance of AM-CFRP structures.

Drawing on self-determination theory (Deci and Ryan, 2012) and Hew’s (2016) five-factor model, our study aimed to investigate the impact of two online training design factors (instructor accessibility and active learning) on learner’s self-efficacy and learning outcome amid the COVID-19 pandemic.

A randomized pretest-posttest control group field experiment was designed to assess participants’ self-efficacy and learning outcome of an online training program - territory business management plan, under three conditions: instructor accessibility, active learning, and controlled. Participants (N=87) were medical sales representatives from a Fortune-Global 500 pharmaceutical company’s subsidiary office in China. Data was analyzed with 2 (time) x 3 (group) MANOVA with time (pretest and posttest) as a repeated measure to investigate differences in changes in self-efficacy and learning outcome between three groups.

Overall, participants’ self-efficacy and learning outcome were significantly improved via the online training program for all three groups. Specifically, the impact of the training on learning outcome was the strongest for the active learning group, less strong for the instructor accessibility group, and the least strong for the control group.

Our research contributes towards understandings of the effectiveness of online talent training programs by examining two critical instructional design factors during a time of crisis. Our findings suggest that active learning (interactions with the training materials by purposeful self-reflection) might be a stronger predictor for increasing learning outcome than instructor accessibility (receiving feedback and tutoring sessions from the instructor) for online training programs.

This study quantitatively investigates the impacts of digital and learning orientations on supply chain resilience (SCR) and firm performance (FP), aiming to fill the gaps in understanding their specific impacts in the context of Industry 4.0 developments and supply chain disruptions.

This study utilized survey techniques and structural equation modelling (SEM) to gather and analyse data through a questionnaire based on a seven-point Likert scale. Hypotheses were formulated based on an extensive literature review and tested using Amos software.

The study confirms SCR’s significant impact on FP, aligning with existing research on resilience’s role in organizational competitiveness. This study uncovers the nuanced impacts of digital and learning orientations on SCR and FP. Internal digital orientation (DOI) positively impacts SCR, while external digital orientation (DOE) does not. Specific dimensions of learning orientation – shared vision (LOS), open-mindedness (LOO) and intraorganizational knowledge sharing (LOI) – enhance SCR, while commitment to learning (LOC) does not. SCR mediates the relationship between DOI and FP but not between DOE and FP.

This research focuses on digital and learning orientations, recommending that future studies investigate other strategic orientations and examine the specific contributions of various digital technologies to SCR across diverse contexts.

The empirical findings emphasize the significance of developing internal digital capabilities and specific learning orientations to enhance SCR and FP, aligning these initiatives with resilience strategies.

This study advances knowledge by distinguishing the impacts of internal and external digital orientations and specific learning dimensions on SCR and FP, offering nuanced insights and empirical validation.

Existing literature has elicited the external behaviors of cross-device search but not much is known about users' cognition of cross-device search. The study aims to explore how users perceive the cross-device search by combining with the mental models and how motivations affect the users' understanding of cross-device search.

The research questions are addressed through semi-structured face-to-face interviews with 59 users. Prior to the interview, the user is asked to complete a cross-device search task designed with the simulation of controlled and autonomous motivations to gain a real experience. The concepts of mental models are coded according to the constructivist grounded theory method.

The study finds the users' mental models of cross-device search consist of four dimensions: Element, Quality, Function and Issue. The effect of motivation on the mental models is tested as significant in terms of the Quality and Function aspects. The controlled motivation affects the user's perception of how the device switch influence the search and the autonomous motivation influences the user's opinion of search system functions.

The contribution of this study is found to extend the existing knowledge of cross-device search and update the mental models of information search in the current multi-device environment. The findings inform the future study of cross-device search and practices of search system design.

The purpose of this paper is to present a family of robust metasurface-oriented wireless power transfer systems with improved efficiency and size compactness. The effect of geometric and structural features on the overall efficiency and miniaturisation is elaborately studied, while the presence of substrate losses is, also, considered. Moreover, to further enhance the performance, possible means for reducing the operating frequency, without comprising the unit-cell size, are proposed.

The key element of the design technique is the edge-coupled split-ring resonators patterned in various metasurface configurations and optimally placed to increase the total efficiency. To this goal, a rigorous three-dimensional algorithm, launching a new high-order prism macroelement, is developed in this paper for the fast evaluation of the required quantities. The featured scheme can host diverse approximation orders, while it is drastically more economical than existing methods. Hence, the demanding wireless power transfer systems are precisely modelled via reduced degrees of freedom, without the need to conduct large-scale simulations.

Numerical results, compared with measured data from fabricated prototypes, validate the design methodology and prove its competence to provide enhanced metasurface wireless power transfer systems. An assortment of optimized 3 x 3 and 5 x 5 metamaterial setups is investigated, and interesting deductions, regarding the impact of the inter-element gaps, the distance between the transmitting and receiving components and the substrate losses, are derived. Also, the proposed vector macroelement technique overwhelms typical implementations in terms of computational burden, particularly when combined with the relevant commercial software packages.

Systematic design of advanced real-world wireless power transfer structures through optimally selected metasurfaces with fully controllable electromagnetic properties is presented. The analysis is performed by means of a rapid prism macroelement methodology, which leads to very confined meshes, accurate results and significantly reduced overhead. The selected metamaterial resonators are found to be very flexible and reconfigurable, even in the case of large substrate conductivity losses, whereas their contribution to the system’s total efficiency is decisive.

The impact of COVID-19 has led to a surge in the public’s reliance on the Internet for pandemic information, and the policy of home isolation has exacerbated this. This study aimed to investigate public information needs and ways of accessing and disseminating information during COVID-19 in mainland China.

This study used a qualitative research approach to conduct semi-structured interviews with 15 participants from 9 cities in mainland China about information needs and access behaviors during the COVID-19 outbreak. All interview recordings were converted into text and proofread, then coded and summarised in correspondence with the research questions using the grounded theory.

This study summarized the dynamics of public information needs during the 2.5-year pandemic and identified the difficulties in accessing certain information.

Although information needs of public health emergencies have been a hot topic during COVID-19, scant studies focus on information needs in specific countries in Asia, especially in mainland China, the first country with a major outbreak and stringent lockdown mandates. Therefore, the current study is well enriched by focusing on information demand behavior in the context of COVID-19. Possible measures for improvement were also given to existing and potential problems, taking into account the participants’ views.

The purpose of this paper is to propose a novel target automatic recognition method for unmanned aerial vehicle (UAV), which is based on backpropagation – artificial neural network (BP-ANN) algorithm, with the objective of optimizing the structure of backpropagation network, to increase the efficiency and decrease the recognition time. A hardware-in-the-loop system for UAV target automatic recognition is also developed.

The hybrid model of BP-ANN structure is established for aircraft automatic target recognition. This proposed method identifies controller parameters and reduces the computational complexity. Approaching speed of the network is faster and recognition accuracy is higher. This kind of network combines or better fuses the advantages of backpropagation artificial neural algorithm and Hu moment. with advantages of two networks and improves the speed and accuracy of identification. Finally, a hardware-in-the-loop system for UAV target automatic recognition is also developed.

The double hidden level backpropagation artificial neural can easily increase the speed of recognition process and get a good performance for recognition accuracy.

The proposed backpropagation artificial neural algorithm can be ANN easily applied to practice and can help the design of the aircraft automatic target recognition system. The standard backpropagation algorithm has some obvious drawbacks, namely, converging slowly and falling into the local minimum point easily. In this paper, an improved algorithm based on the standard backpropagation algorithm is constructed to make the aircraft target recognition more practicable.

A double hidden levels backpropagation artificial neural algorithm is presented for automatic target recognition system of UAV.

The purpose of this paper is to study police powers and accountability from a comparative perspective in both China and Hong Kong.

This paper compares and contrasts police powers and accountability.

The implications are many, including different political systems in which China is more authoritarian or paternalistic whereas Hong Kong is more pluralistic; checks and balances mechanisms in Hong Kong are far greater than in China; and the concept of accountability to the public is different in that Hong Kong police are accountable to members of the public but the mainland Chinese police force has a limited and top-down concept of accountability.

An original comparative approach to policing in Hong Kong and China.