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In high-speed processing, the influence on the machining accuracy of a machine tool is greatly caused by the thermal deformation of the motorized spindle; a further study on the thermal characteristics of the spindle is given in this paper. This study aims to reduce the thermal error and improve the performance of the machine tool by discussing the relationships between the temperature distributions and rotating accuracy caused by the thermal deformations of the spindle.

The paper opted for a method combining the theoretical analysis and the experimental study to study the thermal stability of the high-speed motorized spindle. First of all, a finite element model of the spindle was built with ANSYS, whereby temperature distributions and the thermal deformations were successively obtained at different speeds. And then, both the temperature field and the rotating accuracy of the motorized spindle were measured simultaneously by the thermal stability experiment. Finally, the experimental and theoretical results were compared and validated.

The thermal stability of the motorized spindle was studied in this paper, and some findings from the study were as follows: the spindle’s rotating accuracy maintained good in X direction but bad in Y and Z directions in terms of the deformations; the higher front-end temperature of the spindle which can significantly affect the rotating accuracy is needed to be controlled mainly; the recovery speed of the spindle deformation lagged behind the temperature’s fallback speed; the vibration graph about radial rotating sensitivity synthesized by X1 and X2 presented a trifoliate shape.

Based on a built test-bed which can synchronously measure the motorized spindle’s temperature distribution and rotating accuracy with five-point method, the coupling effects of the thermal deformation and temperature are embodied, and not only the vibration graph but also the thermal tilt angles can be gained. Therefore, considering the influence of the thermal deformation on the heat generated by the bearings, the paper fulfilled a study by which it was obtained that the front-end temperature of the spindle, which was higher and could significantly affect the rotating accuracy, needed to be controlled mainly.

The aim of this study is to understand thermal effects and surface topography of roller bearings with misaligned load under combination of multifactors by an experimental method.

A series of orthogonal experiments would need to be planned and performed. A ranking of impact degree of factors on edge effect and eccentric load effect can be learned with multivariate analysis of variance by Statistical Product and Service Solutions software. Influence rules of each individual factor can also be obtained through more experiments. A roller surface phase diagram both before and after test can be observed with metallographic microscope. An axial profile data of roller can be measured by PGI 3D Profiler, then a roller generatrix contour can be achieved through filtering measured signal with empirical mode decomposition method.

Slip fraction has most impact on edge effect, whereas tilting angle plays a key role in eccentric load effect. For the case of low temperature, skidding damage does not occur. Inversely, because of the high pressure in partial elastohydrodynamic lubrication caused by roller tilt, running-in occurs and micro asperity flattening is observed on a rough surface. And, the larger the tilting angle, the more obvious the micro-flattening and the greater the reduction of roller surface roughness after the test.

A lot of theoretical studies on thermal effect of roller bearings surface morphology have been published. However, there are little on relevant experimental study, especially on thermal effect with an integration of sliding, tilting and unbalance loading.

As the new frontier in online healthcare innovation, mobile health consultation (MHC) is transforming how traditional healthcare is delivered. Despite being known on a large scale for its benefits, MHC still faces consumer resistance. MHC is a technology-enabled service, so an in-depth analysis of consumer resistance from the perspective of technology is crucial to enhance service adoption. This study sought to determine the mechanism by which two information technology (IT)-specific traits – IT affordance and IT identity – influence consumer resistance to MHC during consumer–platform interactions.

We used the Credamo platform to gather data from 786 users with medical consulting experience to validate the resulting relationships.

Based on partial least squares structural equation modeling, three of the six IT affordances (visibility, searching and guidance shopping) exerted a significant positive influence on IT identity, while trigger attending and association affordance had no significant effect on IT identity. Persistence affordance was negatively associated with IT identity, and IT identity negatively influenced consumer resistance to MHC.

Academically, this empirical paper primarily contributes to the MHC literature and the theory of IT affordance and IT identity. Practically, several valuable guidance for MHC platforms is provided.

The mobile medical consultation (MMC) service is growing rapidly, but not all consumers are always willing to actively engage with it. To address this issue, based on IT identity theory, this study explores the underlying mechanism of how two types of platform-related consumer experience influence MMC platform identity, in turn, result in consumer negatively-valenced engagement in MMC.

The data was collected from 400 consumers with the experience of MMC and analyzed by the partial least square (PLS) method.

The findings unfold that these two distinct consumer experience, servicescape experience (i.e. perceived telepresence and perceived platform surveillance) and service search experience (i.e. perceived diagnosticity and perceived serendipity), are associated with MMC platform identity and consumer negatively valenced engagement with MMC.

Research on consumer negatively-valenced engagement in the field of MMC is still in a nascent stage. The study identifies consumer experience in accordance with the unique context of the MMC platform and fills the research gap on the role of IT identity in consumer negatively valenced engagement.

This paper aims to design a novel test device and study the wear properties and the thermal mechanisms of roller pairs in dual-freedom sliding contacts.

On the transition process of lubrication regimes, experiments were conducted with various values of running speed and slip ratio obtained by two motorized spindles. Temperature and surviving time would be obtained of GCr15/GCr15 and DLC/GCr15 friction pairs. Micro photography was obtained with a PGI 3D stylus profiler and a confocal microscopy OLS4000-3D. An empirical mode decomposition method was used to eliminate measure errors.

Results showed that, even with little initial lubricant, rolling/sliding pairs still rotated for a certain time. With the synthetic actions of the dual-freedom sliding, the loss of lubrication and the tilt, interesting helical grooves appeared. Sliding speeds had remarkable effects on survive time, temperatures and surface topographies. In addition, the equilibrium values of the temperature and the surface roughness were obtained in sufficient oil supply. Extreme wear-out conditions were obtained with starved lubrication. Diamond-like carbon coatings showed better heat resistance and better wear resistance.

This work would be critical for the life design and the heat treatment of rolling bearings in the full flood lubrication and the starved lubrication.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0164/

To research involvement of healthcare staff in the UK and identify practical organisational and policy solutions to improve and boost capacity of the existing workforce to conduct research.

A mixed-method study presenting three work packages here: secondary analysis of levels of staff research activity, funding, academic outputs and workforce among healthcare organisations in the United Kingdom; 39 Research and Development lead and funder interviews; an online survey of 11 healthcare organisations across the UK, with 1,016 responses from healthcare staff included for analysis; and 51 interviews of healthcare staff in different roles from six UK healthcare organisations.

Interest in research involvement is strong and widespread but hampered by a lack of systematic organisational support despite national policies and strategies to increase staff engagement in research. While useful, these external strategies have limited universal success due to lack of organisational support. Healthcare organisations should embed research within organisational and human resources policies and increase the visibility of research through strategic organisational goals and governance processes. A systems-based approach is needed.

The research gathered data from a limited number of NHS trusts but these were purposively sampled to provide a range of different acute/community health service organisations in different areas. But data was therefore more detailed and nuanced due to a more in-depth approach.

The findings are relevant for developing policies and practice within healthcare organisations to support research engagement. The findings also set out key policy and strategic recommendations that will support greater research engagement.

Increased research activity and engagement in healthcare providers improves healthcare outcomes for patients.

This is a large scale (UK-wide) study involving a broad range of healthcare staff, with good engagement of nurses, midwives and Allied Healthcare Professionals who have not been previously achieved. This allowed valuable analysis of under-researched groups and comparisons by professional groups. The findings highlight the need for tailored action to embed research reporting, skills, professional development and infrastructure into organisational policies, strategies and systems, along with broader system-wide development.

This paper aims to select an appropriate contact force model and apply it to the interaction model between the balls and the cage in the rolling bearings to describe the elastic–plastic collision phenomena between the two.

Taking the ball–disk collision mode as an example, several main contact force models were compared and analyzed through simulation and experiment. In addition, based on the consideration of yield strength of materials and initial collision velocity, a variable recovery coefficient model was proposed, and its validity and accuracy were verified by the ball–disk collision experiments. Then, respectively, the Flores model and the Hertz model were applied to the interaction between the balls and the cage, and the dynamics simulation results were compared.

The results indicate that the Flores model has good regression of recovery coefficient, indicating good applicability for both elastic and elastic–plastic contacts and can be applied to the contact collision situations of various materials. Under certain working conditions, there are significant differences in the dynamics results of rolling bearings simulated using the Flores model and Hertz model, respectively.

This paper applies the Flores model with variable recovery coefficients to the dynamics simulation analysis of ball bearings to solve the elastic–plastic collision problem between the rolling elements and the cage that cannot be reasonably handled by the Hertz model.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0138/

Three types of PbTe samples, e.g. nanoparticles, nanowires and bulk ingots, have been prepared. The investigation of the Seebeck coefficient of PbTe nanoparticles and nanowires clearly shows the sign change in the temperature range of 575~650 K, which is not observed for bulk ingots. Unfortunately, this temperature range is within the proposed operation temperature range for thermoelectric devices using PbTe and hence, such a change will affect their proper performance. The observed sign change of Seebeck coefficient is not simply caused by the composition variation at high temperature. It is mainly attributed to the extrinsic-to-intrinsic-semiconductor transition for PbTe nanocrystals due to the competing factors between quantum size effect increasing band gap and self-purification process decreasing their charge carrier concentration, which shift the transition point of nanocrystals to lower range as compare to that of bulk samples. Thus, such phenomenon should be considered carefully in the design of thermoelectric devices using semiconductor nanocrystals, which have attracted much attention recently.

Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly wholesale price index of green grams in the Chinese market. The index covers a ten-year period, from January 1, 2010, to January 3, 2020, and has significant economic implications.

In order to address the nonlinear patterns present in the price time series, we investigate the nonlinear auto-regressive neural network as the forecast model. This modeling technique is able to combine a variety of basic nonlinear functions to approximate more complex nonlinear characteristics. Specifically, we examine prediction performance that corresponds to several configurations across data splitting ratios, hidden neuron and delay counts, and model estimation approaches.

Our model turns out to be rather simple and yields forecasts with good stability and accuracy. Relative root mean square errors throughout training, validation and testing are specifically 4.34, 4.71 and 3.98%, respectively. The results of benchmark research show that the neural network produces statistically considerably better performance when compared to other machine learning models and classic time-series econometric methods.

Utilizing our findings as independent technical price forecasts would be one use. Alternatively, policy research and fresh insights into price patterns might be achieved by combining them with other (basic) prediction outputs.

This systematic review aims to comprehensively explore the existing literature on the use of corporate communication within the realm of social media.

A total of 136 peer-reviewed journal articles are explored and analysed using both performance and bibliometric analysis.

This review identifies five main findings: (1) trends in corporate social media research that highlight the growth trajectory of research on social media use for corporate disclosure, (2) geographical coverage of studies indicating the concentration of research in certain regions, such as the USA, followed by China and the UK, with notable gaps in others, such as developing countries, (3) theoretical frameworks employed demonstrate that various theoretical frameworks are utilized, although a significant portion of the studies do not specify any theoretical underpinning, (4) social media platforms studied, confirming Twitter to be the most studied channel followed by Facebook and (5) thematic analysis of articles on disclosure type that categorized the articles using bibliometric analysis into five themes of disclosure: general disclosure, corporate social responsibility-related information, financial information, CEO announcements and strategic news communication. A subsequent cross-theme analysis classifies disclosure determinants and consequences of corporate social media usage.

Through a comprehensive and systematic analysis of existing research, this review offers novel insights into the current state of corporate communication on social media. It consolidates current knowledge, highlights under-explored areas in the existing literature and proposes new directions and potential avenues for future research.