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Stiffness adjusting ability is essential for soft robotic arms to perform complex tasks. A soft state enables dexterous operation and safe interaction, while a rigid state enables large force output or heavy weight carrying. However, making a compact integration of soft actuators with powerful stiffness adjusting mechanisms is challenging. This study aims to develop a piston-like particle jamming mechanism for enhanced stiffness adjustment of a soft robotic arm.

The arm has two pairs of differential tendons for spatial bending, and a jamming core consists of four jamming units with particles sealed inside braided tubes for stiffness adjustment. The jamming core is pushed and pulled smoothly along the tendons by a piston, which is then driven by a motor and a ball screw mechanism.

The tip displacement of the arm under 150 N jamming force and no more than 0.3 kg load is minimal. The maximum stiffening ratio measured in the experiment under 150 N jamming force is up to 6–25 depends on the bending direction and added load of the arm, which is superior to most of the vacuum powered jamming method.

The proposed robotic arm makes an innovative compact integration of tendon-driven robotic arm and motor-driven piston-like particle jamming mechanism. The jamming force is much larger compared to conventional vacuum-powered systems and results in a superior stiffening ability.

A direct and unified approach is proposed toward simultaneously simulating large strain elastic behaviors of gellan gels with different gellan polymer concentrations. The purpose of this paper is to construct an elastic potential with certain parameters of direct physical meanings, based on well-designed invariants of Hencky’s logarithmic strain.

For each given value of the concentration, the values of the parameters incorporated may be determined in the sense of achieving accurate agreement with large strain uniaxial extension and compression data. By means of a new interpolating technique, each parameter as a function of the concentration is then obtained from a given set of parameter values for certain concentration values.

Then, the effects of gellan polymer concentrations on large strain elastic behaviors of gellan gels are studied in demonstrating how each parameter relies on the concentration. Plane-strain (simple shear) responses are also presented for gellan gels with different polymer concentrations.

A direct, unified approach was proposed toward achieving a simultaneous simulation of large elastic strain behaviors of gellan gels for different gellan polymer concentrations. Each parameter incorporated in the proposed elastic potential will be derived as a function of the polymer concentration in an explicit form, in the very sense of simultaneously simulating large strain data for different concentrations.

The purpose of this paper is to improve the performance of sensorless vector control of induction motor drives by developing a new sliding mode observer for rotor speed and fluxes estimation from measured stator currents and voltages and estimated stator currents.

In the present paper, the discontinuity in the sliding mode observer is smoothed inside a thin boundary layer using fuzzy logic techniques instead of sign function to reduce efficiently the chattering phenomenon that affects the rotor speed.

The feasibility of the proposed fuzzy sliding mode observer has been verified by experimentation. The experimental results are obtained with a 1 kW induction motor using a dSPACE system with DS1104 controller board showing clearly the effectiveness of the proposed approach in terms of dynamic performance compared to the classical sliding mode observer.

The experimental results of the whole control structure highlights that this kind of sensorless induction motor drive can be used for variable speed drive in industrial applications such as oil drilling, electric vehicles, high speed trains (HSTs) and conveyers. Such drives may work properly at zero and low speed in both directions of rotation.

Both the proposed speed observer and the classical sliding mode observer have been developed and implemented experimentally with other adaptive observers for detailed comparison under different operating conditions, such as parameter variation, no-load/load disturbances and speed variations in different speed operation regions.

The purpose of this paper is to present a model that can be used to simulate the photopolymerization process in micro‐stereolithography (SL) in order to predict the shape of the cured parts. SL is an additive manufacturing process in which liquid photopolymer resin is cross‐linked and converted to solid with a UV laser light source. Traditional models of SL processes do not consider the complex chemical reactions and species transport occurring during photopolymerization and, hence, are incapable of accurately predicting resin curing behavior. The model presented in this paper attempts to bridge this knowledge gap.

The chemical reactions involved in the photopolymerization of acrylate‐based monomers were modeled as ordinary differential equations (ODE). This model incorporated the effect of oxygen inhibition and diffusion on the polymerization reaction. The model was simulated in COMSOL and verified with experiments conducted on a mask‐based micro‐SL system. Parametric studies were conducted to investigate the possibilities to improve the accuracy of the model for predicting the edge curvature.

The proposed model predicts well the effect of oxygen inhibition and diffusion on photopolymerization, and the model accurately predicts the cured part height when compared to experiments conducted on a mask‐based SL system. The simulated results also show the characteristic edge curvature as seen in experiments.

A triacrylate monomer was used in the experiments conducted, so results may be limited to acrylate monomers. Shrinkage was not considered when comparing cured part shapes to those predicted using COMSOL.

This paper presents a unique and a pioneering approach towards modeling of the photopolymerization reaction in micro‐SL process. This research furthers the development of patent pending film micro‐SL process which can be used for fabrication of custom micro‐optical components.

In the vast majority of published papers, the optimal allocation of photovoltaic distributed generation (PVDG) units and reconfiguration problems are proposed along with the number of PVDG used in the simulation. However, optimisation without selecting the number of PVDG units installed in the distribution grid is insufficient to achieve a better operational performance of power systems. Moreover, multi-objective installation of PVDG units and reconfiguration aims to simultaneously relieve congestion problems, improve voltage profile and minimise the active and reactive power losses. Therefore, this paper aims to propose a new modified camel algorithm (NMCA) to solve multi-objective problems considering radial distribution system to achieve secure and stable operation of electric power system with good performance.

In this paper, the decision variables include the location and size of PVDG units with specific rang to determine the number of PVDG units needed to install and open network lines determined using NMCA based on the L_∞ technique. This also satisfies the operating and radial constraints. Furthermore, a benchmark comparison with different well known optimisation algorithms has been made to confirm the solutions. Finally, an analysis of the findings was conducted, and the feasibility of solutions was fully verified and discussed.

Two test systems – the institute of electrical and electronics engineers (IEEE) 33-bus and IEEE 69-bus, were used to examine the accuracy and effectiveness of the proposed algorithm. The findings obtained amply proved the efficiency and superiority of the NMCA algorithm over the other different optimisation algorithms.

The proposed approach is applied to solve the installation PVDG unit’s problem and reconfiguration problem in the radial distribution system, satisfying the operating and radial constraints. Also, it minimises active and reactive power losses and improves voltage profile.

High-ductility cementitious composites (HDCC) have an excellent crack controlled capacity and corrosion resistance capacity, which has a promising application in structure engineering under harsh environment. The purpose of this study is to explore the corrosion mechanism of steel bar in HDCC.

Intact and the pre-cracked HDCC specimens under the coupled action of different dry–wet cycles and chloride attack were designed, and intact normal concrete (NC) was also considered for comparison. Corrosion behavior of a steel bar embedded in HDCC was analyzed by an electrochemical method, a chloride permeability test and X-ray computed tomography.

Steel corrosion probability is related to the chloride permeability of the HDCC cover, and the chloride permeability resistance of HDCC is better than that of NC. Besides, crack is the key factor affecting the corrosion of steel bars, and the HDCC with narrower cracks have a lower corrosion rate. Slight pitting occurs at the crack tips. In addition, the self-healing products and corrosion products fill up the cracks in HDCC, preventing the external aggressive ions from entering and thereby decreasing the steel corrosion rate.

HDCC has a superior corrosion resistance than that of NC, effects of variable crack width on corrosion behavior of steel bar in HDCC under the coupled actions of different dry–wet cycles and chloride attack are investigated, which can provide the guide for the design application of HDCC material in structure engineering exposed to marine environment.

This study aims to investigate the effect of social media use on healthcare workers’ psychological safety and task performance and the moderating role of perceived respect from patients during public health crises.

To test the proposed moderated mediation model, a survey was conducted in 12 Chinese medical institutions. A total of 637 valid questionnaires were collected for data analysis.

The results revealed that psychological safety mediated the relationships between task-related social media (TSM) use and social-related social media (SSM) use and task performance. In addition, perceived respect from patients moderated the relationship between TSM use and psychological safety, as well as the indirect relationship between TSM use and task performance through psychological safety.

This study sheds new light on understanding how different types of social media use influence task performance in the context of public health crises. Furthermore, this study considers the interactions of healthcare workers with colleagues and patients and examines the potential synergistic effects of these interactions on healthcare workers’ psychological state and task performance.

There is an increasing demand for higher-accuracy dimensional measurements of nano- and micro-structures. Recently, the authors presented a fiber Bragg grating (FBG) sensor-based dynamic nano-coordinate-measuring machine (CMM) probe for true three-dimensional coordinate measurement, in which a specific mechanical structure with several FBG sensors was developed to provide the probe with sensitivity to loading in all directions.

The study presents a three-dimensional sensing and demodulation system based on an improved matched filter design and the time division multiplexing technique that helps solve the problem of multiplex FBG-signals conflicts. In addition, the application of the dynamic mode of the probe system effectively solves the problem presented by the surface interaction forces.

Consequently, this FBG-based vibrating probe system has increased sensitivity to strain, while maintaining smaller contact force. The experiments for testing probe performance show that the prototype yielded a measurement resolution of 13 nm, a repeatability of 50 nm and a vertical measurement force of less than1.5 mN.

The force tests in the horizontal directions are difficult to conduct because both the probe and the dynamometer are only adaptable to vertical use.

Development of the FBG-based dynamic nano-coordinate-measuring machine probe will achieve a new and inexpensive method for higher-accuracy dimensional measurements of nano- and micro-structures, such as micro-electromechanical systems, micro-fluidic chips, inkjet and diesel engine injector nozzles that are in overall dimensions within the micrometer scale.

The study presents a three-dimensional sensing and demodulation system for the vibrating nano-coordinate-measuring machine probe based on FBG sensors. The prototype yielded a measurement resolution of 13 nm, a repeatability of 50 nm and a vertical measurement force of less than1.5 mN.

The purpose of this paper is to study correlations between the national real estate investment trusts (REIT) markets in the USA and the four Asia‐Pacific countries of Australia, Hong Kong, Japan and Singapore, and document the extent to which the time variation present in these correlations can be explained from a set of 11 economic and financial factors. Both US dollar and local currency returns are used.

Time‐varying correlations are estimated using a DCC‐GARCH model that allows for asymmetries in both the correlations and volatilities. The correlations are then regressed on a set of four economic and seven financial factors, and tests of statistical significance are conducted in order to discriminate between relevant and irrelevant explanatory variables. The authors estimate a fixed‐effects panel regression as well as individual regressions for each dynamic correlation.

Significant time variation is found in the four REIT correlation series. Panel regressions suggest that REIT correlations rise with increases in the interaction of national inflation rates and with higher global equity market uncertainty. It is also found that REIT correlations fall with increases in the US default risk premium and global equity market volume. Relaxing the structure imposed by the panel data model, individual regressions confirm most of the results, although there are some exceptions. It is also found that there are no substantial differences in the dynamics of the correlation coefficients when switching from the US dollar to local currency denominated returns.

Investors in real estate securities across national markets should take into account information about the credit spread, the volatility and volume of global equity markets, and inflation rates when modeling correlations. These variables may alert the investors to the possibility that, under a set of circumstances, investing in real estate across different markets may not provide the expected diversification benefits. Another implication relates to the impact of currency hedging. It appears that the impact of switching from US dollar to local currency denominated returns does not substantially change the time dynamics of the correlations, or the importance of explanatory variables.

Although considerable progress has been made in modelling time‐varying correlations between various REIT markets, to the authors' knowledge, this is one of the first papers to investigate the underlying causes of the co‐movement, especially between the US and Asia‐Pacific markets. The paper's results will help investors and risk managers make better choices by identifying those factors that have more systematic effects on the change in the REIT correlations, rather than more transient forces.

This research aims to identify the factors that influence the investment intention of retail investors in Indian REITs. The study incorporates the theory of planned behavior and innovation diffusion theory as the research framework, with perceived risk and mass media influence as additional constructs.

Primary data were collected using self-administered questionnaires from 534 potential investors in India. The data were analyzed using partial least square structural equation modeling.

The study showed that factors such as relative advantage, compatibility, attitude, subjective norms, perceived behavioral control and mass media significantly and positively influence investment intention in Indian REITs. However, perceived risk was found to have a negative and significant influence, while complexity did not affect investment intention.

This is the first quantitative investigation into determining the factors influencing the investment intention of Indian retail investors on Indian REITs.