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In the post-Enron era around the world, the role of auditor is widely debated. There is an increasing concern that an auditor’s continuous involvement with clients could impair audit quality – the negative view. There is also a positive view that a long auditor tenure leads to accumulation of client-specific knowledge over time, which could lead to high-quality audits. The empirical result with regards to impact of mandatory auditor rotation (MAR) is mixed world-wide. This study aims to examine whether MAR rules implemented in 2017 impact audit quality in India.

Using a unique setting in which MAR was required from 2017 to 2018 onwards in India, this study provides empirical evidence of the impact of MAR regulation on audit quality (modified audit opinion). The study uses data for 714 firms (4,284 firms) for six years (three years before MAR and three years after MAR regulation in India).

The study found that auditor tenure and MAR had significant negative impacts on audit quality, validating the “positive” view of audit tenure and audit quality. In addition, concentrated ownership had a negative impact on audit quality, implying the control and influence by concentrated ownership on auditors and audit opinion. The analysis shows that MAR regulation has not yielded the intended objective of improving audit quality in India. MAR is not a good template for improving audit quality.

The findings of the study are useful to policymakers, regulators, managers, investors and users of financial reports. The study calls for public policy on auditor rotation based on objective scientific evidence. In light of the evidence in India that MAR does not lead to better audit quality, the study calls for reset of regulatory policy in India.

The study provides valuable insights to analysts, regulators and other users of financial accounts about the implications of MAR in India.

The study is one of the few to report on the impact of MAR, particularly in the context of an emerging market economy such as India.

This paper aims to study the effect of concentric hot circular cylinder inside egg-cavity porous-copper nanofluid on natural convection phenomena.

The finite element method–based Galerkin approach is applied to solve numerically the set of governing equations with appropriate boundary conditions.

The effects of different range parameters, such as Darcy number (10–3 = Da = 10–1), Rayleigh number (103 = Ra = 106), nanoparticle volume fraction (0 = ϑ = 0.06) and eccentricity (−0.3 = e = 0.1) on the fluid flow represent by stream function and heat transfer represent by temperature distribution, local and average Nusselt numbers.

A comparison between oval shape and concentric circular concentric cylinder was investigated.

In the current numerical study, heat transfer by natural convection was identified inside the new design of egg-shaped cavity as a result of the presence of a circular inside it supported by a porous medium filled with a nanofluid. After reviewing previous studies and considering the importance of heat transfer by free convection inside tubes for many applications, to the best of the authors’ knowledge, the current work is the first study that deals with a study and comparison between the common shape (concentric circular tubes) and the new shape (egg-shaped cavity).

The authors examine the association between two important audit partner characteristics and the readability of key audit matters (KAMs) disclosed in the audit reports. Specifically, the authors examine how the readability of KAMs is associated with audit partner tenure and workload.

The authors conduct the study in the audit context of Norway and applied the Flesch reading ease scale to measure the readability levels of reported KAMs in the audit reports of companies listed on the Oslo Stock Exchange. Panel data estimation techniques are applied in estimating how partner tenure and workload are associated with the readability of KAMs. In addition, several robustness tests including different measures of KAMs readability and subsample analyses are performed.

The authors find that audit partner tenure and workload have significant associations with the level of KAMs readability. Specifically, the results show that the reported KAMs become more readable as the audit partner tenure increases but are less readable for partners with more workload. These results appear stronger in subsamples of KAMs typically noted to be more complex and associated with higher risks.

As KAMs represent the most significant issues in financial statements audit, these results provide important insights to stakeholders on the potential impact of audit partner tenure and workload on KAMs readability. Less readable KAMs could derail stakeholders' desire to bridge the information gap between auditors and users of the audit report. The uniqueness of this study lies in its focus on audit partner characteristics as opposed to the audit firm.

Excessive audit partner workload impairs KAMs readability.

As KAMs represent the most significant issues in financial statements audit, these results provide important insights to stakeholders on the potential impact of audit partner tenure and workload on KAMs readability. Less readable KAMs could derail stakeholders' desire to bridge the information gap between auditors and users of the audit report. The uniqueness of this study lies in its focus on audit partner characteristics as opposed to the audit firm.

This paper aims to investigate magnetic impacts on bioconvection flow within a porous annulus between an outer cylinder and five inner cylinders. The annulus is filled by oxytactic microorganisms and nano-encapsulated phase change materials.

The modified ISPH method based on the time-fractional derivative is applied to solve the regulating equations in Lagrangian dimensionless forms. The pertinent factors are bioconvection Rayleigh number Ra_b (1–100), circular cylinder’s radius R_c (0.1–0.3), fractional time derivative α (0.95–1), Darcy parameter Da (10⁻⁵–10⁻²), nanoparticle parameter ϕ (0–0.1), Hartmann number Ha (0–50), Lewis number Le (1–20), Peclet number Pe (0.1–0.75), s (0.1–0.9), number of cylinders N_Cylinders (1–4), Rayleigh number Ra (10³–10⁶) and fusion temperature θ_f (0.005–0.9).

The simulations revealed that there is a strong enhancement in the velocity field according to an increase in Ra_b. The intensity and location of the phase zone change in response to changes in θ_f. The time-fractional derivative a acting on a nanofluid velocity and flow characteristics in an annulus. The number of embedded cylinders N_Cylinders is playing a significant role in the cooling processes and as N_Cylinders increases from 1 to 4, the velocity field’s maximum reduces by almost 33.3%.

The novelty of this study is examining the impacts of the magnetic field and the presence of several numbers of embedded cylinders on bioconvection flow within a porous annulus between an outer cylinder and five inner cylinders.

This paper aims to investigate the conformable fractal approaches of unsteady natural convection in a partial layer porous H-shaped cavity suspended by nano-encapsulated phase change material (NEPCM) by the incompressible smoothed particle hydrodynamics method.

The partial hot sources with variable height L_Hot are in the H-cavity’s sides and center. The performed numerical simulations are obtained at the variations of the following parameters: source of hot length L_Hot = (0.4–1.6), conformable fractal parameter α (0.97–1), fusion temperature θ_f (0.05–0.9), thermal radiation parameter Rd (0–7), Rayleigh number Ra (10³–10⁶), Darcy parameter Da (10⁻² to 10⁻⁵) and Hartmann number Ha (0–80).

The main outcomes showed the implication of hot source length L_Hot, Rayleigh number and fusion temperature in controlling the contours of a heat capacity within H-shaped cavity. The presence of a porous layer in the right zone of H-shaped cavity prevents the nanofluid flow within this area at lower Darcy parameter. An increment in the thermal radiation parameter declines the heat transfer and changes the heat capacity contours within H-shaped cavity. The velocity field is strongly enhanced by an augmentation on Rayleigh number. Increasing the Hartmann number shrinks the velocity field within H-shaped cavity.

The novelty of this work is solving the conformable fractal approaches of unsteady natural convection in a partial layer porous H-shaped cavity suspended by NEPCM.

The structural adaptive ability of the soft robot is fully demonstrated in the grasping task of the soft hand. A soft hand can easily realize the envelope operation of the object without planning. With the continuous development of robot applications, researchers are no longer satisfied with the ability of the soft hand to grasp. The purpose of this paper is to perceive the object’s shape while grasping to provide a decision-making basis for more intelligent robot applications.

This paper proposes a dual-signal comparison method to obtain the fingertip position. The dual signal includes the displacement calculated by the static model without considering the external load change and the displacement calculated by the bending sensor. The dual-signal comparison method can use the obvious change trend difference between the above two signals in the hover and contact states to identify the touch position. The authors make the soft hand scan around the object through touch operation to detect the object’s shape, and the tracks of every touch fingertip position can envelop the object’s shape.

The experimental results show that the dual-signal comparison method can accurately identify the contact moment of soft fingers. This detection method makes the soft hand develop the shape detection ability. The soft hand in the experiment can perceive squares, circles and a few other complex shapes.

The dual-signal comparison method proposed in this paper can detect a touch action by using the signal change trend when the working condition suddenly changes with the rough robotic model and sensing, thus improving the utilization value of the measured signal. The problems of large model errors and inaccurate sensors also negatively impact the use of other soft robots. It is generally difficult to achieve good results by directly using these models and sensors with the thinking of rigid robot analysis. The dual-signal comparison method in this paper can provide some reference for this aspect.

The purpose of this study is to propose a fast method for predicting flow fields with periodic behavior with verification in the context of a radial turbine to meet the urgent requirement to effectively capture the unsteady flow characteristics in turbomachinery. Aiming at meeting the urgent requirement to effectively capture the unsteady flow characteristics in turbomachinery, a fast method for predicting flow fields with periodic behavior is proposed here, with verification in the context of a radial turbine (RT).

Sparsity-promoting dynamic mode decomposition is used to determine the dominant coherent structures of the unsteady flow for mode selection, and for flow-field prediction, the characteristic parameters including amplitude and frequency are predicted using one-dimensional Gaussian fitting with flow rate and two-dimensional triangulation-based cubic interpolation with both flow rate and rotation speed. The flow field can be rebuilt using the predicted characteristic parameters and the chosen model.

Under single flow-rate variation conditions, the turbine flow field can be recovered using the first seven modes and fitted amplitude modulus and frequency with less than 5% error in the pressure field and less than 9.7% error in the velocity field. For the operating conditions with concurrent flow-rate and rotation-speed fluctuations, the relative error in the anticipated pressure field is likewise within an acceptable range. Compared to traditional numerical simulations, the method requires a lot less time while maintaining the accuracy of the prediction.

It would be challenging and interesting work to extend the current method to nonlinear problems.

The method presented herein provides an effective solution for the fast prediction of unsteady flow fields in the design of turbomachinery.

A flow prediction method based on sparsity-promoting dynamic mode decomposition was proposed and applied into a RT to predict the flow field under various operating conditions (both rotation speed and flow rate change) with reasonable prediction accuracy. Compared with numerical calculations or experiments, the proposed method can greatly reduce time and resource consumption for flow field visualization at design stage. Most of the physics information of the unsteady flow was maintained by reconstructing the flow modes in the prediction method, which may contribute to a deeper understanding of physical mechanisms.

The purpose of this paper aims to investigate the adaptive impedance control and its optimized PSO algorithm for force tracking of a dual-arm cooperative robot. Because the dual-arm robot is directly in contact with external environment, controlling the mutual force between robot and external environment is of great importance. Besides, a high compliance of the robot should be guaranteed.

An impedance control based on Particle Swarm Optimization (PSO) algorithm is designed to track the mutual force and achieve compliance control of the robot end.

The experimental results show that the impedance control coefficients can be automatically tuned converged by PSO algorithm.

The system can reach a steady state within 0.03 s with overshoot convergence, and the force fluctuation range at the steady state decreases to about ±0.08 N even under the force mutation condition.

The “chiralisation” of Euclidean polygonal tessellations is a novel, recent method which has been used to design new auxetic metamaterials with complex topologies and improved geometric versatility over traditional chiral honeycombs. This paper aims to design and manufacture chiral honeycombs representative of four distinct classes of 2D Euclidean tessellations with hexagonal rotational symmetry using fused-deposition additive manufacturing and experimentally analysed the mechanical properties and failure modes of these metamaterials.

Finite Element simulations were also used to study the high-strain compressive performance of these systems under both periodic boundary conditions and realistic, finite conditions. Experimental uniaxial compressive loading tests were applied to additively manufactured prototypes and digital image correlation was used to measure the Poisson’s ratio and analyse the deformation behaviour of these systems.

The results obtained demonstrate that these systems have the ability to exhibit a wide range of Poisson’s ratios (positive, quasi-zero and negative values) and stiffnesses as well as unusual failure modes characterised by a sequential layer-by-layer collapse of specific, non-adjacent ligaments. These findings provide useful insights on the mechanical properties and deformation behaviours of this new class of metamaterials and indicate that these chiral honeycombs could potentially possess anomalous characteristics which are not commonly found in traditional chiral metamaterials based on regular monohedral tilings.

To the best of the authors’ knowledge, the authors have analysed for the first time the high strain behaviour and failure modes of chiral metamaterials based on Euclidean multi-polygonal tessellations.

Presently, 6 Degree of Freedom (6DOF) visual pose measurement methods enjoy popularity in the industrial sector. However, challenges persist in accurately measuring the visual pose of blank and rough metal casts. Therefore, this paper introduces a 6DOF pose measurement method utilizing stereo vision, and aims to the 6DOF pose measurement of blank and rough metal casts.

This paper studies the 6DOF pose measurement of metal casts from three aspects: sample enhancement of industrial objects, optimization of detector and attention mechanism. Virtual reality technology is used for sample enhancement of metal casts, which solves the problem of large-scale sample sampling in industrial application. The method also includes a novel deep learning detector that uses multiple key points on the object surface as regression objects to detect industrial objects with rotation characteristics. By introducing a mixed paths attention module, the detection accuracy of the detector and the convergence speed of the training are improved.

The experimental results show that the proposed method has a better detection effect for metal casts with smaller size scaling and rotation characteristics.

A method for 6DOF pose measurement of industrial objects is proposed, which realizes the pose measurement and grasping of metal blanks and rough machined casts by industrial robots.