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The purpose of this paper is to examine the relationship between aged care employees’ perceived job quality and intention to stay in current aged care facilities, mediated by work-life interference.

This paper uses the nationally representative employee–employer matched data from the 2012 National Aged Care Workforce Census and Survey in Australia. It applies the theoretical lens of the Job Characteristics Model and a mediation analytical model that controls for a rich set of employee, employer and regional characteristics.

This paper finds that higher perceived job quality positively correlates with greater intention to stay and that work-life interference mediates the relationship between perceived job quality and intention to stay.

This paper cannot make inference about causal relationship. Future studies on the aged care workforce should collect longitudinal data so that time-invariant unobservables can be eliminated in econometric modelling.

Efforts by the aged care sector to design quality jobs are likely to have significant positive correlation with the intention to stay, not only because employees are less likely to leave higher quality jobs per se, but also because higher quality jobs interfere less in the family lives of aged care workers, which itself is associated with greater intention to stay.

The results add to a small literature that has investigated how work-family variables can mediate between interventions that organisations put in place to improve work-life balance, and employee outcomes.

Grounded in the job demands–resources (JD-R) theory, this study investigates how the difficulty in social distancing at work, resulting from the COVID-19 crisis, may lead to intention to quit and career regret and how and when these effects may be attenuated.

Three-wave survey data were collected from 223 frontline service workers in a large restaurant company during the COVID-19 crisis.

The results show that difficulty in social distancing reduced employees' work engagement, and consequently, increased their turnover intention and career regret. These relationships were moderated by external employability, such that the influence of difficulty in social distancing weakened as external employability increased.

Social distancing measures have been applied across the globe to minimize transmission of COVID-19. However, such measures create a new job demand for service workers who find it difficult to practice social distancing due to the high contact intensity of service delivery. This study identified personal resources that help service workers cope with the demand triggered by COVID-19.

Adaptive slicing is a key step in three-dimensional (3D) printing as it is closely related to the building time and the surface quality. This study aims to develop a novel adaptive slicing method based on ameliorative area ratio and accurate cusp height for 3D printing using stereolithography (STL) models.

The proposed method consists of two stages. In the first stage, the STL model is sliced with constant layer thickness, where an improved algorithm for generating active triangular patches, the list is developed to preprocess the model faster. In the second stage, the model is first divided into several blocks according to the number of contours, then an axis-aligned bounding box-based contour matching algorithm and a polygons intersection algorithm are given to compare the geometric information between several successive layers, which will determine whether these layers can be merged to one.

Several benchmarks are applied to verify this new method. Developed method has also been compared with the uniform slicing method and two existing adaptive slicing methods to demonstrate its effectiveness in slicing.

Compared with other methods, the method leads to fewer layers whilst keeping the geometric error within a given threshold. It demonstrates that the proposed slicing method can reach a trade-off between the building time and the surface quality.

The purpose of this study is to reveal the effect of nano-Al₂O₃ particle addition on the nucleation/growth kinetics, microhardness, wear resistance and corrosion resistance of Co–P–xAl₂O₃ nanocomposite plating.

The kinetics and properties of Co–P–xAl₂O₃ nanocomposite plating prepared by electroplating were investigated by electrochemical measurements, scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, Vickers microhardness measurement, SRV5 friction and wear tester and atomic force microscopy.

A 12 g/L nano-Al₂O₃ addition in the plating solution can transform the nucleation/growth kinetics of the plating from the 3D progressive model to the 3D instantaneous model. The microhardness of the plating increased with the increase of nano-Al₂O₃ content in plating. The wear resistance of the plating did not adhere strictly to Archard’s law. An even and denser corrosion product film was generated due to the finer grains, with a high corrosion resistance.

The effect of different nano-Al₂O₃ addition on the nucleation/growth kinetics and properties of Co–P–xAl₂O₃ nanocomposite plating was investigated, and an anticorrosion mechanism of Co–P–xAl₂O₃ nanocomposite plating was proposed.

Frequency diverse array (FDA) radar with uniform frequency offset between antenna elements has been proposed and investigated, which exhibits a range-angle-dependent beampattern. Nevertheless, because of the coupling in range and angle responses, it cannot estimate directly both the range and angle information of a target.The purpose of this paper is to consider a sub-array scheme of range-angle joint estimation of a target for frequency diverse array (FDA) radar.

First, The entire array is divided into two sub-arrays, which employs two different frequency offsets. For aperture extension, each sub-array adopts difference co-array structure . Therefore, the targets range and angle can be estimated directly with the subspace-based multiple signal classification algorithms for the decoupling capability of distance and angle dimensional. The estimation performance is examined by analyzing the Cramer-Rao lower bound (CRLB) versus signal-to-noise ratio (SNR).

Each sub-array adopts difference co-array structure to provide degrees of freedom by only physical sensors when the second-order statistics of the received data is used. And the sub-array is equivalent to two sets of equations to solve two unknown quantities, and the closed solution of the unknown quantity can be directly determined, which cannot be gained by the phase-array radar and basic ULA FDA radar. Finally, numerical simulation results verify the validity of the proposed method.

In this paper, we devise a subarray scheme on FDA radar for range and angle estimation. In order to aperture extension, difference co-array is employed in each subarrays, and more targets can be distinguished than the physical sensors. The range and angle estimation performance is examined by analyzing the CRLB.

Metamodeling is an effective method to approximate the relations between input and output parameters when significant efforts of experiments and simulations are required to collect the data to build the relations. This paper aims to develop a new sequential sampling method for adaptive metamodeling by using the data with highly nonlinear relation between input and output parameters.

In this method, the Latin hypercube sampling method is used to sample the initial data, and kriging method is used to construct the metamodel. In this work, input parameter values for collecting the next output data to update the currently achieved metamodel are determined based on qualities of data in both the input and output parameter spaces. Uniformity is used to evaluate data in the input parameter space. Leave-one-out errors and sensitivities are considered to evaluate data in the output parameter space.

This new method has been compared with the existing methods to demonstrate its effectiveness in approximation. This new method has also been compared with the existing methods in solving global optimization problems. An engineering case is used at last to verify the method further.

This paper provides an effective sequential sampling method for adaptive metamodeling to approximate highly nonlinear relations between input and output parameters.

This paper aims to study the effect of temperature on the process and kinetic parameters of the hydrogen evolution reaction of X80 under cathodic protection (CP) in 3.5% NaCl solution.

Potentiodynamic polarization combined with the hydrogen permeation test is used to analyze the hydrogen evolution reaction (HER) process and the rate-determining step for which is diagnosed through the electrochemical impedance spectrum method. Then, the influence of temperature on kinetic parameters of HER can be known from the results obtained by using the Iver-Pickering-Zamenzadeh model for data analysis.

The results show that the HER proceeds through Volmer–Tafel route with the Volmer reaction acting as the rate-controlling step; Increasing temperature gives a higher activity of the HER on X80, it also accelerates the hydrogen desorption and diffusion of hydrogen into the metal.

There exist few studies on the topic of how temperature affects the HER process. It is imperative to conduct a relevant study to give some instruction in cathodic protection system design and this paper fulfills this need.

The purpose of this paper is to propose an efficient space-time operator-splitting method for the high-dimensional vector-valued Allen–Cahn (AC) equations. The key of the space-time operator-splitting is to devide the complex partial differential equations into simple heat equations and nolinear ordinary differential equations.

Each component of high-dimensional heat equations is split into a series of one-dimensional heat equations in different spatial directions. The nonlinear ordinary differential equations are solved by a stabilized semi-implicit scheme to preserve the upper bound of the solution. The algorithm greatly reduces the computational complexity and storage requirement.

The theoretical analyses of stability in terms of upper bound preservation and mass conservation are shown. The numerical results of phase separation, evolution of the total free energy and total mass conservation show the effectiveness and accuracy of the space-time operator-splitting method.

Extensive 2D/3D numerical tests demonstrated the efficacy and accuracy of the proposed method.

The space-time operator-splitting method reduces the complexity of the problem and reduces the storage space by turning the high-dimensional problem into a series of 1D problems. We give the theoretical analyses of upper bound preservation and mass conservation for the proposed method.

This paper aims to investigate the transformations during aging at 200°C for different periods on microstructure and mechanical properties of high-temperature Zn-4Al-3Mg solders.

The solder was melted in a resistance furnace, and different cooling rates were obtained by changing the cooling medium. Subsequently, all the specimens were aged at 200°C for 20 h and 50 h. A scanning electron microscope equipped with an energy dispersive X-ray detector and X-ray diffraction were used for the observation of microstructures and the determination of phase composition. Tensile tests and Rockwell hardness tests were also performed.

After aging, Zn atoms precipitated from the supersaturated α-Al and the (α-Al + η-Zn)_eutectoid phase with the original fine lamellar structure coarsened and spheroidized to minimize the system energy. Among these solders, the furnace-cooled alloys exhibited the highest thermal stability, largely retaining their original morphology after aging, whereas the collapse and spheroidization of the η-Zn phase and the coarsening of the η-Zn dendrites took place in the air-cooled and water-cooled samples, respectively. Furthermore, a decrease in tensile strength during aging was attributed to the thermal softening effect. The variation of macro-hardness was mainly associated with the microstructural alterations in terms of quantity, morphology and distribution of soft η-Zn phase and hard intermetallic compounds induced by the aging treatment.

The structural stability of eutectic Zn-4Al-3Mg solders solidified at different cooling rates and the effect of aging on mechanical properties were investigated.

The geomagnetic field vector is a function of the satellite’s position. The position and speed of the satellite can be determined by comparing the geomagnetic field vector measured by on board three-axis magnetometer with the standard value of the international geomagnetic field. The geomagnetic model has the disadvantages of uncertainty, low precision and long-term variability. Therefore, accuracy of autonomous navigation using the magnetometer is low. The purpose of this paper is to use the geomagnetic and sunlight information fusion algorithm to improve the orbit accuracy.

In this paper, an autonomous navigation method for low earth orbit satellite is studied by fusing geomagnetic and solar energy information. The algorithm selects the cosine value of the angle between the solar light vector and the geomagnetic vector, and the geomagnetic field intensity as observation. The Adaptive Unscented Kalman Filter (AUKF) filter is used to estimate the speed and position of the satellite, and the simulation research is carried out. This paper also made the same study using the UKF filter for comparison with the AUKF filter.

The algorithm of adding the sun direction vector information improves the positioning accuracy compared with the simple geomagnetic navigation, and the convergence and stability of the filter are better. The navigation error does not accumulate with time and has engineering application value. It also can be seen that AUKF filtering accuracy is better than UKF filtering accuracy.

Geomagnetic navigation is greatly affected by the accuracy of magnetometer. This paper does not consider the spacecraft’s environmental interference with magnetic sensors.

Magnetometers and solar sensors are common sensors for micro-satellites. Near-Earth satellite orbit has abundant geomagnetic field resources. Therefore, the algorithm will have higher engineering significance in the practical application of low orbit micro-satellites orbit determination.

This paper introduces a satellite autonomous navigation algorithm. The AUKF geomagnetic filter algorithm using sunlight information can obviously improve the navigation accuracy and meet the basic requirements of low orbit small satellite orbit determination.