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This study aims to investigate and compare the characteristics of three topologies of moving-magnet linear oscillating actuator (LOA) based on their mover position. Positive aspects and consequences of every topology are demonstrated. Three topologies of axially magnetized moving-magnet LOA; outer mover, inner mover (IM) and dual stator (DS) are designed and examined. Due to its characteristically high thrust density and more mechanical strength, axially magnetized tubular permanent magnets (PMs) are used in these topologies.

LOAs are designed and optimized using parametric sweep, in term of design parameters and output parameters like thrust force, stroke and operating resonance frequency of the LOA. All the pros and cons of each topology are investigated and compared. Output parameters of the LOAs are compared using same size of the investigated LOAs. Mover mass, which plays a vital role in resonant operation, is analyzed for IM and DS designs. Investigated LOAs are compared with conventional designs of LOA for compressor in refrigeration system with regards of motor constant, stroke and thrust per PM mass.

This paper analyzes three topologies of moving-magnet LOAs. The basic difference between investigated LOAs is the radius of tubular-shaped mover from its central axis. All the design parameters are compared and concluded that thrust per PM mass of IMLOA is maximum. OMLOA provides maximum motor constant of value 180 N/A. DSLOA provides thrust force with motor constant 120 N/A and required intermediate materials of PMs. All the three designs give the best results in terms of motor constant and thrust per PM mass, compared to conventional designs of LOA.

This paper determines the impact of mover position from its central axis in a tubular-shaped moving-magnet LOA. This work is carried out in correspondence of latest papers of LOA.

In recent years, the convolutional neural network (CNN) based deep learning approach has succeeded in data-mining the relationship between microstructures and macroscopic properties of materials. However, such CNN models usually rely heavily on a large set of labeled images to ensure the accuracy and generalization ability of the predictive models. Unfortunately, in many fields, acquiring image data is expensive and inconvenient. This study aims to propose a data augmentation technique to enhance the performance of the CNN models for linking microstructural images to the macroscopic properties of composites.

Microstructures of composites are synthesized using discrete element simulations and Potts kinetic Monte Carlo simulations. Macroscopic properties such as the elastic modulus, Poisson's ratio, shear modulus, coefficient of thermal expansion, and triple-phase boundary length density are extracted on representative volume elements. The CNN model is trained using the 3D microstructural images as inputs and corresponding macroscopic properties as the labels. The comparison of the predictive performance of the CNN models with and without data augmentation treatment are compared.

The comparison between the prediction performance of CNN models with and without data augmentation showed that the former reduced the weighted mean absolute percentage error (WMAPE) for the prediction from 5.1627% to 1.7014%. This significant reduction signifies that the proposed data augmentation method can effectively enhance the generalization ability and robustness of CNN models.

This study demonstrates that data augmentation is beneficial for solving the problems of model overfitting, data scarcity, and sample imbalance for CNN-based deep learning tasks at a low cost. By developing more and advanced data augmentation techniques, deep learning accelerated homogenization will boost the multi-scale computational mechanics and materials.

This paper aims to provide an overview of the recent developments and new topologies of single-phase moving magnet linear oscillating actuators (MMLOAs). The key advantage of the MMLOA when compared with conventional LOA is the absence of screws, gears and crankshaft mechanism, which results in fewer mechanical parts, simple structure, easy fabrication, lower noise levels and negligible frictional losses.

The review included papers up to August 2021. The structural designs of alternative topologies are deliberated in detail, and their relative merits and demerits are evaluated. Specific design issues, including pole and tooth number combinations, stroke length, magnet pole ratio and split ratio, are investigated. The imperative phenomena of the resonance, as well as the adjustable stroke, are also discussed in detail.

The electromagnetic performance in terms of thrust force of selected MMLOA topologies is compared. It is observed that the MMLOA with flux bridge topology has the highest thrust force of 365 N because of the large volume of the permanent magnets (PMs) used, which consequently increased the mass of the mover but based on overall performance analysis, single-phase end ferromagnetic Halbach surface-mounted PM LOA has the highest efficiency around 92%.

This review provides a comparative analysis for different tubular MMLOA topologies based on design construction and their electromagnetic performances.

Promoting clean heating in rural areas is crucial for achieving a low-carbon transition of energy consumption and China's dual-carbon target. The study aims to consider the energy stacking behavior in heating energy use, reveals the determinants that affect household cleaner heating choices under the winter clean heating plan (WCHP), and proposes policy recommendations for the sustainable promotion of clean heating.

With unique rural household survey data covering the clean heating pilot regions in northern China in 2020, this study estimates the relationship between driving factors and heating energy choices through binary and multivariate probit models.

The regression estimates show that the main drivers of heating energy choices include household income per capita, education level of household head, knowledge of the WCHP, access to heating subsidies and perception of indoor air pollution. There is energy stacking behavior in rural household heating energy use. Household decisions to adopt electricity or clean coal heating are correlated with firewood or soft coal use.

This study is one of the few to investigate the heating energy use of rural households by allowing for the adoption of multiple energy types. Combined with a unique microsurvey dataset, it could provide rich information for formulating proper energy transition planning. The findings also shed light on the importance of heating subsidies, households' knowledge of WCHP and awareness of environmental health in choosing clean heating energy, which has not been fully valued in related research.

Library science and information science, two subdisciplines of library and information science (LIS), are developed independently but interconnectedly. In this information age, LIS is in a special period of transformation and development, which has caused some changes in both library science and information science. By accurately capturing these changes and analyzing them, the authors can effectively map the development of LIS in the new century, thus providing a reference for the evolution and development of the field. The purposes of this paper are to explore the mainstream research fields and frontiers of library science and information science, respectively, since the new century, and to make a comparative analysis of the two subdisciplines.

By using CiteSpace to visualize LIS journals, this study draws knowledge maps of the two subdisciplines of LIS through the co-occurrence descriptors network. Using burst detection algorithm, this study detects words of high frequency variation by investigating the time frequency distribution.

The results show that the research focus of library science has experienced a change from traditional to digital library while information science has moved from information to data focus. This study also finds the similarities and differences between mainstream areas of library science and information science.

This study focuses on the evolution of library science and information science, and explores their mainstream research fields and frontiers in the 21st century. These findings will promote the transformation and development of LIS as well as provide research directions for scholars in the field.

The present study is intended to develop an effective approach to the real-time modeling of general dynamic nonlinear systems based on the multidimensional Taylor network (MTN).

The authors present a detailed explanation for modeling the general discrete nonlinear dynamic system by the MTN. The weight coefficients of the network can be obtained by sampling data learning. Specifically, the least square (LS) method is adopted herein due to its desirable real-time performance and robustness.

Compared with the existing mainstream nonlinear time series analysis methods, the least square method-based multidimensional Taylor network (LSMTN) features its more desirable prediction accuracy and real-time performance. Model metric results confirm the satisfaction of modeling and identification for the generalized nonlinear system. In addition, the MTN is of simpler structure and lower computational complexity than neural networks.

Once models of general nonlinear dynamical systems are formulated based on MTNs and their weight coefficients are identified using the data from the systems of ecosystems, society, organizations, businesses or human behavior, the forecasting, optimizing and controlling of the systems can be further studied by means of the MTN analytical models.

MTNs can be used as controllers, identifiers, filters, predictors, compensators and equation solvers (solving nonlinear differential equations or approximating nonlinear functions) of the systems of ecosystems, society, organizations, businesses or human behavior.

The operating efficiency and benefits of social systems can be prominently enhanced, and their operating costs can be significantly reduced.

Nonlinear systems are typically impacted by a variety of factors, which makes it a challenge to build correct mathematical models for various tasks. As a result, existing modeling approaches necessitate a large number of limitations as preconditions, severely limiting their applicability. The proposed MTN methodology is believed to contribute much to the data-based modeling and identification of the general nonlinear dynamical system with no need for its prior knowledge.

This study aims to investigate the impact of job burnout on job satisfaction and the intention to change occupation within the accounting profession. It also examines the mediating role of psychological well-being.

A descriptive research design was used in this study. Survey data were physically collected from 230 accounting employees in the private sector. Structural equation modeling was used to test the theoretical model.

The results showed that job burnout significantly affects psychological well-being and that psychological well-being significantly mediates the relationship between job burnout and job satisfaction, as well as between job burnout and the intention to change occupation.

This study has significant implications for accounting organizations, suggesting the adoption of strategies to promote psychological well-being. These initiatives have the potential to enhance job satisfaction and reduce accountants’ intention to change their profession.

This study contributes to the existing literature by highlighting the mediating role of psychological well-being in linking job burnout with job satisfaction and the intention to change occupation among accounting professionals.

Intumescent coatings are nowadays a dominant passive system used to protect structural materials in case of fire. Due to their reactive swelling behaviour, intumescent coatings are particularly complex materials to be modelled and predicted, which can be extremely useful especially for performance-based fire safety designs. In addition, many parameters influence their performance, and this challenges the definition and quantification of their material properties. Several approaches and models of various complexities are proposed in the literature, and they are reviewed and analysed in a critical literature review.

Analytical, finite-difference and finite-element methods for modelling intumescent coatings are compared, followed by the definition and quantification of the main physical, thermal, and optical properties of intumescent coatings: swelled thickness, thermal conductivity and resistance, density, specific heat capacity, and emissivity/absorptivity.

The study highlights the scarce consideration of key influencing factors on the material properties, and the tendency to simplify the problem into effective thermo-physical properties, such as effective thermal conductivity. As a conclusion, the literature review underlines the lack of homogenisation of modelling approaches and material properties, as well as the need for a universal modelling method that can generally simulate the performance of intumescent coatings, combine the large amount of published experimental data, and reliably produce fire-safe performance-based designs.

Due to their limited applicability, high complexity and little comparability, the presented literature review does not focus on analysing and comparing different multi-component models, constituted of many model-specific input parameters. On the contrary, the presented literature review compares various approaches, models and thermo-physical properties which primarily focusses on solving the heat transfer problem through swelling intumescent systems.

The presented literature review analyses and discusses the various modelling approaches to describe and predict the behaviour of swelling intumescent coatings as fire protection for structural materials. Due to the vast variety of available commercial products and potential testing conditions, these data are rarely compared and combined to achieve an overall understanding on the response of intumescent coatings as fire protection measure. The study highlights the lack of information and homogenisation of various modelling approaches, and it underlines the research needs about several aspects related to the intumescent coating behaviour modelling, also providing some useful suggestions for future studies.

In practical engineering, oil filters often work under asymmetric cyclic loading. In order to improve the prediction accuracy of fatigue life of the oil filters under asymmetric cyclic loading, the effect of strain ratio and low cycle fatigue plastic deformation on fatigue life need to be considered. This paper aims to discuss the aforementioned objective.

First, strain-controlled fatigue tests with strain ratios of 0, 0.5 and −1 were carried out on the oil filter material 2A70-T6 aluminum alloy, and the test data were used to obtain strain fatigue life curves at three strain ratios. Then, based on the idea of the constant life curve method, the average value of the ratio of the strain amplitude corresponding to different strain ratios under the same partial life was defined as the strain ratio factor. Finally, the elastic-plastic factor was modified by the strain ratio factor, and a new fatigue life prediction model considering the effect of strain ratio was proposed.

The proposed model was validated, respectively, by fatigue test data of 2A70-T6 aluminum alloy, 2124-T851 aluminum alloy and oil filter and the results of the proposed model were compared with the Coffin–Manson equation, Morrow model and Smith–Watson–Topper (SWT) model, showing that the proposed model had higher applicability and accuracy.

In this work, a strain ratio factor is established based on the idea of the constant life curve method, and the strain ratio factor is used to modify the introduced elastic-plastic factor, and then a new fatigue life prediction model considering the influence of strain ratio and low cycle fatigue plastic deformation on material fatigue damage accumulation is proposed. The results show that the prediction results of the proposed model are in good agreement with the experimental data, and the proposed model has good fatigue life prediction ability considering the influence of strain ratio and lays a foundation for the fatigue life prediction of the oil filter.

The purpose of this study was to test the moderating effects of positive thinking (PT) on the relationship between job stress (JS) and turnover intention (TI).

The study was based on a questionnaire distributed among 275 employees at a convenience store business. The validity and reliability of the questionnaire were tested before the data were collected, and hierarchical regression analysis was used to test the moderating effects.

JS had negative effects on employee TI with statistical significance, while PT functioned to moderate the relationship between JS and employee TI with statistical significance.

The moderating effects of PT among employees in the convenience store business were explained clearly. This research supports and expands the broaden-and-build theory in explaining the effects of PT or attitudes to help employees cope with problems and obstacles, create new things and perceive problems as challenges to be overcome.

Managers with an awareness of PT can help employees lower JS, increase organizational commitment and improve employees' PT to reduce the turnover rate.

This study contributes to the literature about organizational behavior and human resource management in dealing with job turnover by clarifying the moderating effects of PT on the relationship between JS and TI.