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The governance of our towns and cities requires an approach that connects people with nature and places. Digital technology can be the glue that does this, if it serves the needs of the various stakeholders, including urban communities. It means identifying the potential connections across people, digital, and place themes, examining successful approaches, and exploring some of the current practice (or lack of it) in spatial planning and smart cities. This can be considered using a range of Internet of Things (IoT) technologies with other methodologies which combine the use of socioeconomic and environmental data about the urban environment. This ambient domain sensing can provide the ecological and other data to show how digital connectivity is addressing the placemaking challenges alongside providing implications for urban governance and communities.

Abnormal behaviors such as rework, backlog, changes and claims generated by project organizations are unavoidable in complex projects. When abnormal behaviors emerge, the previously normal state of interactions between organizations will be altered to some extent. However, previous studies have ignored the associations and interactions between organizations in the context of abnormal organizational behaviors (AOBs), making this challenging to cope with AOBs. As a result, the objective of this paper is to explore how to reduce AOBs in complex projects at the organizational level from a network perspective.

To overcome the inherent limitations of a single case study, this research integrated two data collection methods: questionnaire survey and expert scoring method. The questionnaire survey captured the universal data on the influence possibility of AOBs between complex project organizations and the expert scoring method got the influence probability scores of AOBs between organizations in the case. Using these data, four organizational influence network models of AOBs based on a case were developed to demonstrate how to destroy AOBs networks in complex projects using network attack theory (NAT).

First, the findings show that controlling AOBs generated by key organizations preferentially and improving the ability of key organizations can weaken AOBs network, enabling more effective coping strategies. Second, the owners, government, material suppliers and designers are identified as key organizations across all four influence networks of AOBs. Third, change and claim behaviors are more manageable from the organizational level.

Project managers can target specific organizations for intervention, weaken the AOBs network by applying NAT and achieve better project outcomes through coping strategies. Additionally, by taking a network perspective, this research provides a novel approach to comprehending the associations and interactions between organizations in the context of complex projects.

This paper proposes a new approach to investigating AOBs in complex projects by simultaneously examining rework, backlog, change and claim. Leveraging NAT as a novel tool for managing the harmful effects of influence networks, this study extends the knowledge body in the field of organizational behavior (OB) management and complex project management.

Knowledge loss (KL) is still an unfortunate fact, causing many challenges, including poor organisational performance, despite prior efforts to investigate knowledge retention methods. Therefore, this study identifies early approaches to combat KL and poor organisational performance, shifting focus on employee personality traits.

Grounded on the social exchange theory (SET) cross-section data from 400 Chinese construction knowledge employees were used to investigate the role of internal work locus of control (IWLC) on job rotation (JR), KL and organisational performance. The data were analysed through IBM SPSS Statistics 25 and SmartPLS 4 software.

The results demonstrated that IWLC minimises KL and positively influences JR. Then, JR negatively influences KL and decreases in organisational performance. The negative mediating effect of JR in the relationship between IWLC, KL and decreased organisational performance were also found. Finally, KL proved to positively influence a decrease in organisational performance.

This study contributes to the new understanding of individual behaviour and its influence on organisational outcome variables. Specifically, for ultimate KL prevention and organisational performance improvement, an organisation should understand its employees' behaviours to establish progressive collective learning and knowledge sharing.

This study contributes to the new understanding of individual behaviour and its influence on organisational outcome variables. Specifically, for ultimate KL prevention and organisational performance improvement, an organisation should understand its employees’ behaviours to establish progressive collective learning and knowledge sharing.

This study is the first attempt to explore the influence of personality traits in the early minimisation of KL, particularly the role of IWLC and JR in combating KL and improving organisational performance.

This study examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.

To provide high torques needed to move a robot’s links, electric actuators are followed by a transmission system with a high transmission rate. For instance, gear ratios of 100:1 are often used in the joints of a robotic manipulator. This results into an actuator with large mechanical impedance (also known as nonback-drivable actuator). This in turn generates high contact forces when collision of the robotic mechanism occur and can cause humans’ injury. Another disadvantage of electric actuators is that they can exhibit overheating when constant torques have to be provided. Comparing to electric actuators, pneumatic actuators have promising properties for robotic applications, due to their low weight, simple mechanical design, low cost and good power-to-weight ratio. Electropneumatically actuated robots usually have better friction properties. Moreover, because of low mechanical impedance, pneumatic robots can provide moderate interaction forces which is important for robotic surgery and rehabilitation tasks. Pneumatic actuators are also well suited for exoskeleton robots. Actuation in exoskeletons should have a fast and accurate response. While electric motors come against high mechanical impedance and the risk of causing injuries, pneumatic actuators exhibit forces and torques which stay within moderate variation ranges. Besides, unlike direct current electric motors, pneumatic actuators have an improved weight-to-power ratio and avoid overheating problems.

The aim of this paper is to analyze a nonlinear optimal control method for electropneumatically actuated robots. A two-link robotic exoskeleton with electropneumatic actuators is considered as a case study. The associated nonlinear and multivariable state-space model is formulated and its differential flatness properties are proven. The dynamic model of the electropneumatic robot is linearized at each sampling instance with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. Within each sampling period, the time-varying linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. An H-infinity controller is designed for the linearized model of the robot aiming at solving the related optimal control problem under model uncertainties and external perturbations. An algebraic Riccati equation is solved at each time-step of the control method to obtain the stabilizing feedback gains of the H-infinity controller. Through Lyapunov stability analysis, it is proven that the robot’s control scheme satisfies the H-infinity tracking performance conditions which indicate the robustness properties of the control method. Moreover, global asymptotic stability is proven for the control loop. The method achieves fast convergence of the robot’s state variables to the associated reference trajectories, and despite strong nonlinearities in the robot’s dynamics, it keeps moderate the variations of the control inputs.

In this paper, a novel solution has been proposed for the nonlinear optimal control problem of robotic exoskeletons with electropneumatic actuators. As a case study, the dynamic model of a two-link lower-limb robotic exoskeleton with electropneumatic actuators has been considered. The dynamic model of this robotic system undergoes first approximate linearization at each iteration of the control algorithm around a temporary operating point. Within each sampling period, this linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. The linearization process relies on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. The modeling error which is due to the truncation of higher-order terms from the Taylor series is considered to be a perturbation which is asymptotically compensated by the robustness of the control algorithm. To stabilize the dynamics of the electropneumatically actuated robot and to achieve precise tracking of reference setpoints, an H-infinity (optimal) feedback controller is designed. Actually, the proposed H-infinity controller for the model of the two-link electropneumatically actuated exoskeleton achieves the solution of the associated optimal control problem under model uncertainty and external disturbances. This controller implements a min-max differential game taking place between: (i) the control inputs which try to minimize a cost function which comprises a quadratic term of the state vector’s tracking error and (ii) the model uncertainty and perturbation inputs which try to maximize this cost function. To select the stabilizing feedback gains of this H-infinity controller, an algebraic Riccati equation is being repetitively solved at each time-step of the control method. The global stability properties of the H-infinity control scheme are proven through Lyapunov analysis.

Pneumatic actuators are characterized by high nonlinearities which are due to air compressibility, thermodynamics and valves behavior and thus pneumatic robots require elaborated nonlinear control schemes to ensure their fast and precise positioning. Among the control methods which have been applied to pneumatic robots, one can distinguish differential geometric approaches (Lie algebra-based control, differential flatness theory-based control, nonlinear model predictive control [NMPC], sliding-mode control, backstepping control and multiple models-based fuzzy control). Treating nonlinearities and fault tolerance issues in the control problem of robotic manipulators with electropneumatic actuators has been a nontrivial task.

The novelty of the proposed control method is outlined as follows: preceding results on the use of H-infinity control to nonlinear dynamical systems were limited to the case of affine-in-the-input systems with drift-only dynamics. These results considered that the control inputs gain matrix is not dependent on the values of the system’s state vector. Moreover, in these approaches the linearization was performed around points of the desirable trajectory, whereas in the present paper’s control method the linearization points are related with the value of the state vector at each sampling instance as well as with the last sampled value of the control inputs vector. The Riccati equation which has been proposed for computing the feedback gains of the controller is novel, so is the presented global stability proof through Lyapunov analysis. This paper’s scientific contribution is summarized as follows: (i) the presented nonlinear optimal control method has improved or equally satisfactory performance when compared against other nonlinear control schemes that one can consider for the dynamic model of robots with electropneumatic actuators (such as Lie algebra-based control, differential flatness theory-based control, nonlinear model-based predictive control, sliding-mode control and backstepping control), (ii) it achieves fast and accurate tracking of all reference setpoints, (iii) despite strong nonlinearities in the dynamic model of the robot, it keeps moderate the variations of the control inputs and (iv) unlike the aforementioned alternative control approaches, this paper’s method is the only one that achieves solution of the optimal control problem for electropneumatic robots.

The use of electropneumatic actuation in robots exhibits certain advantages. These can be the improved weight-to-power ratio, the lower mechanical impedance and the avoidance of overheating. At the same time, precise positioning and accurate execution of tasks by electropneumatic robots requires the application of elaborated nonlinear control methods. In this paper, a new nonlinear optimal control method has been developed for electropneumatically actuated robots and has been specifically applied to the dynamic model of a two-link robotic exoskeleton. The benefit from using this paper’s results in industrial and biomedical applications is apparent.

A comparison of the proposed nonlinear optimal (H-infinity) control method against other linear and nonlinear control schemes for electropneumatically actuated robots shows the following: (1) Unlike global linearization-based control approaches, such as Lie algebra-based control and differential flatness theory-based control, the optimal control approach does not rely on complicated transformations (diffeomorphisms) of the system’s state variables. Besides, the computed control inputs are applied directly on the initial nonlinear model of the electropneumatic robot and not on its linearized equivalent. The inverse transformations which are met in global linearization-based control are avoided and consequently one does not come against the related singularity problems. (2) Unlike model predictive control (MPC) and NMPC, the proposed control method is of proven global stability. It is known that MPC is a linear control approach that if applied to the nonlinear dynamics of the electropneumatic robot, the stability of the control loop will be lost. Besides, in NMPC the convergence of its iterative search for an optimum depends on initialization and parameter values selection and consequently the global stability of this control method cannot be always assured. (3) Unlike sliding-mode control and backstepping control, the proposed optimal control method does not require the state-space description of the system to be found in a specific form. About sliding-mode control, it is known that when the controlled system is not found in the input-output linearized form the definition of the sliding surface can be an intuitive procedure. About backstepping control, it is known that it cannot be directly applied to a dynamical system if the related state-space model is not found in the triangular (backstepping integral) form. (4) Unlike PID control, the proposed nonlinear optimal control method is of proven global stability, the selection of the controller’s parameters does not rely on a heuristic tuning procedure, and the stability of the control loop is assured in the case of changes of operating points. (5) Unlike multiple local models-based control, the nonlinear optimal control method uses only one linearization point and needs the solution of only one Riccati equation so as to compute the stabilizing feedback gains of the controller. Consequently, in terms of computation load the proposed control method for the electropneumatic actuator’s dynamics is much more efficient.

The article aims to establish whether the degree of aversion to inflation and the responsiveness to deviations from potential output have changed over time.

This paper assesses time variation in monetary policy rules by applying a time-varying parameter generalised methods of moments (TVP-GMM) framework.

Using monthly data until December 2022 for five inflation targeting countries (the UK, Canada, Australia, New Zealand, Sweden) and five countries with alternative monetary regimes (the US, Japan, Denmark, the Euro Area, Switzerland), we find that monetary policy has become more averse to inflation and more responsive to the output gap in both sets of countries over time. In particular, there has been a clear shift in inflation targeting countries towards a more hawkish stance on inflation since the adoption of this regime and a greater response to both inflation and the output gap in most countries after the global financial crisis, which indicates a stronger reliance on monetary rules to stabilise the economy in recent years. It also appears that inflation targeting countries pay greater attention to the exchange rate pass-through channel when setting interest rates. Finally, monetary surprises do not seem to be an important determinant of the evolution over time of the Taylor rule parameters, which suggests a high degree of monetary policy transparency in the countries under examination.

It provides new evidence on changes over time in monetary policy rules.

This study aims to investigate the formation and characteristics of Taylor bubbles resulting from short-time gas injection in liquid-conveying pipelines. Understanding these characteristics is crucial for optimizing pipeline efficiency and enhancing production safety.

The authors conducted short-time gas injection experiments in a vertical rectangular pipe, focusing on Taylor bubble formation time and stable length. Computational fluid dynamics simulations using large eddy simulation and volume of fluid models were used to complement the experiments.

Results reveal that the stable length of Taylor bubbles is significantly influenced by gas injection velocity and duration. Specifically, high injection velocity and duration lead to increased bubble aggregation and recirculation region capture, extending the stable length. Additionally, a higher injection velocity accelerates reaching the critical local gas volume fraction, thereby reducing formation time. The developed fitting formulas for stable length and formation time show good agreement with experimental data, with average errors of 6.5% and 7.39%, respectively. The predicted values of the formulas in glycerol-water and ethanol solutions are also in good agreement with the simulation results.

This research provides new insights into Taylor bubble dynamics under short-time gas injection, offering predictive formulas for bubble formation time and stable length. These findings are valuable for optimizing industrial pipeline designs and mitigating potential safety issues.

This study explores the immobilisation of enzymes within porous catalysts of various geometries, including spheres, cylinders and flat pellets. The objective is to understand the irreversible Michaelis-Menten kinetic process within immobilised enzymes through advanced mathematical modelling.

Mathematical models were developed based on reaction-diffusion equations incorporating nonlinear variables associated with Michaelis-Menten kinetics. This research introduces fractional derivatives to investigate enzyme reaction kinetics, addressing a significant gap in the existing literature. A novel approximation method, based on the independent polynomials of the complete bipartite graph, is employed to explore solutions for substrate concentration and effectiveness factor across a spectrum of parameter values. The analytical solutions generated through the bipartite polynomial approximation method (BPAM) are rigorously tested against established methods, including the Bernoulli wavelet method (BWM), Taylor series method (TSM), Adomian decomposition method (ADM) and fourth-order Runge-Kutta method (RKM).

The study identifies two main findings. Firstly, the behaviour of dimensionless substrate concentration with distance is analysed for planar, cylindrical and spherical catalysts using both integer and fractional order Michaelis-Menten modelling. Secondly, the research investigates the variability of the dimensionless effectiveness factor with the Thiele modulus.

The study primarily focuses on mathematical modelling and theoretical analysis, with limited experimental validation. Future research should involve more extensive experimental verification to corroborate the findings. Additionally, the study assumes ideal conditions and uniform catalyst properties, which may not fully reflect real-world complexities. Incorporating factors such as mass transfer limitations, non-uniform catalyst structures and enzyme deactivation kinetics could enhance the model’s accuracy and broaden its applicability. Furthermore, extending the analysis to include multi-enzyme systems and complex reaction networks would provide a more comprehensive understanding of biocatalytic processes.

The validated bipartite polynomial approximation method presents a practical tool for optimizing enzyme reactor design and operation in industrial settings. By accurately predicting substrate concentration and effectiveness factor, this approach enables efficient utilization of immobilised enzymes within porous catalysts. Implementation of these findings can lead to enhanced process efficiency, reduced operating costs and improved product yields in various biocatalytic applications such as pharmaceuticals, food processing and biofuel production. Additionally, this research fosters innovation in enzyme immobilisation techniques, offering practical insights for engineers and researchers striving to develop sustainable and economically viable bioprocesses.

The advancement of enzyme immobilisation techniques holds promise for addressing societal challenges such as sustainable production, environmental protection and healthcare. By enabling more efficient biocatalytic processes, this research contributes to reducing industrial waste, minimizing energy consumption and enhancing access to pharmaceuticals and bio-based products. Moreover, the development of eco-friendly manufacturing practices through biocatalysis aligns with global efforts towards sustainability and mitigating climate change. The widespread adoption of these technologies can foster a more environmentally conscious society while stimulating economic growth and innovation in biotechnology and related industries.

This study offers a pioneering approximation method using the independent polynomials of the complete bipartite graph to investigate enzyme reaction kinetics. The comprehensive validation of this method through comparison with established solution techniques ensures its reliability and accuracy. The findings hold promise for advancing the field of biocatalysts and provide valuable insights for designing efficient enzyme reactors.

This manuscript conducts a bibliometric analysis of scholarly literature on sustainable development goal 5 (SDG 5) – gender equality, focusing on Arab countries. The purpose is to comprehensively assess the research landscape, identify trends, contributors and research hotspots and inform evidence-based policies for advancing gender equality in the region.

A descriptive bibliometric analysis was used, using the Scopus database for data collection. The study covers English-language research papers published in peer-reviewed journals between 1993 and 2022, using a comprehensive search strategy focused on gender equality in Arab countries.

The analysis of 634 papers revealed a steep rise in publications post-2015, aligning with the adoption of SDGs. The growth trajectory and citation analysis demonstrated a significant increase in both publications and impact over the last decade. The study identified prolific journals, subject areas, countries, institutions and authors contributing to the literature on gender equality in Arab countries. Notable research hotspots include domestic violence, female genital mutilation, women’s empowerment, microfinance and gender-based violence.

This study contributes to the literature by providing a detailed bibliometric review of SDG 5 research in Arab countries, offering insights into the growth patterns, prolific contributors and research hotspots. The identification of recent research topics, such as child marriage in conflict contexts and female leadership, adds originality to the analysis.