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This conceptual article presents a schematic for use with extended cybernetic recursion in living systems and applies it to the issue of hyper vigilance as a demonstration of its utility.

The test-operate-test-exit (TOTE) schematic of Miller et al. (1960) is critically evaluated along with other schematics, including those of ordered cybernetics, and a new schematic is proposed, a recursive test-operate-test (rTOT), which emphasizes teleological purpose and hierarchical structure. The background psychophysiology of trauma is reviewed and then rTOT is applied to hyper vigilance, a cardinal component of post-traumatic stress disorder (PTSD).

Once the schematic was developed, it was applied to the behavior of hyper vigilance. Other applications are suggested.

As demonstrated, the rTOT schematic has potentially wide application because of its pragmatic and detailed structure.

The rTOT requires careful consideration of teleological purposes for its application and is simple enough, but also complex enough, for relevant utilization. Its compact nature and adjustable hierarchy scope are good mini-max complexity solutions for cybernetic, information modeling schematics.

The revealed teleological purpose of the trauma adaptation of hyper vigilance presents significant alternative formulation options for prevention and intervention.

While the rTOT schematic is derived from previous schematics, it is original in its emphasis on information processing, the teleological aspects of extended recursion and on the provision of a hierarchical structure for those recursions. It is considerably more compact than other schematics associated with the ordered cybernetics literature. The explication of the adaptation model for post-trauma consequences is significantly enhanced by the rTOT application.

As data centres grow in size and complexity, traditional air-cooling methods are becoming less effective and more expensive. Immersion cooling, where servers are submerged in a dielectric fluid, has emerged as a promising alternative. Ensuring reliable operations in data centre applications requires the development of an effective control framework for immersion cooling systems, which necessitates the prediction of server temperature. While deep learning-based temperature prediction models have shown effectiveness, further enhancement is needed to improve their prediction accuracy. This study aims to develop a temperature prediction model using Long Short-Term Memory (LSTM) Networks based on recursive encoder-decoder architecture.

This paper explores the use of deep learning algorithms to predict the temperature of a heater in a two-phase immersion-cooled system using NOVEC 7100. The performance of recursive-long short-term memory-encoder-decoder (R-LSTM-ED), recursive-convolutional neural network-LSTM (R-CNN-LSTM) and R-LSTM approaches are compared using mean absolute error, root mean square error, mean absolute percentage error and coefficient of determination (R²) as performance metrics. The impact of window size, sampling period and noise within training data on the performance of the model is investigated.

The R-LSTM-ED consistently outperforms the R-LSTM model by 6%, 15.8% and 12.5%, and R-CNN-LSTM model by 4%, 11% and 12.3% in all forecast ranges of 10, 30 and 60 s, respectively, averaged across all the workloads considered in the study. The optimum sampling period based on the study is found to be 2 s and the window size to be 60 s. The performance of the model deteriorates significantly as the noise level reaches 10%.

The proposed models are currently trained on data collected from an experimental setup simulating data centre loads. Future research should seek to extend the applicability of the models by incorporating time series data from immersion-cooled servers.

The proposed multivariate-recursive-prediction models are trained and tested by using real Data Centre workload traces applied to the immersion-cooled system developed in the laboratory.

The purpose of this study is to examine the transmission of volatility between business confidence index and stock market indices in Greece. The country remains the riskiest project in European Union (EU) and previous studies fail to reach an accurate conclusion regarding the direction of this transmission.

The study covers the period from January 2013 to August 2022 in monthly basis where important economic events occur. Considering that these economic events derive strong volatility moments, the authors adopt a new methodology that measures the transmission of volatility with higher precision. This is the generalized spillover analysis by Diebold and Yilmaz (2009, 2012).

The results indicate that Business Confidence Index (BCI) is the main receiver of volatility spillovers in Greece under all aspects of the used methodology. The specificity of the results shows that business activity through a green growth model is what drives investor confidence and then their activities.

Although a handful of studies have considered the transmission of volatility between BCI and stock market indices, this study contributes in several ways. This study focuses on one country (Greece), avoiding the dispersion of the results from the examination of the relationship in several countries. The used country remains the riskiest project in EU even nowadays, while other studies fail to confirm the main direction of volatility spillovers from business confidence to stock returns. This study covers a period that is ignored by previous studies and includes important economic events. In addition, considering that these economic events derive strong volatility moments, a new methodology is adopted in this field of research that measures the transmission of volatility with higher accuracy.

Michael Buckland's works have spanned theoretical, historical and practice-oriented foci and genre. This article focuses on some of his theoretical-historical works that span over 20 years, which demonstrate a reading and critique of European Documentation in terms of what has been called “Documentality.” This turn to a philosophy of information called “Documentality” marks the moment of “neo-documentation.” This article surveys this moment in Buckland's works by reading his articles “Information as Thing,” “What is a ‘Document’?”, and “Documentality Beyond Documents.” It shows the transition from Documentation as a philosophy of information as representation to Documentality as a philosophy of information as function and performance. Some concepts and works of Bruno Latour are used to illuminate this transition from Documentation to Documentality. Implications and further research directions are discussed at the end.

Conceptual and historical analyses.

The article follows a neo-documentalist transition in Buckland's works in the thinking of documents from an Otletian representationalist epistemology (“Documentation”) to a functionalist and performative epistemology (“Documentality”) for documents.

This is a conceptual work on a limited corpus in Buckland's oeuvre. It has a limited discussion of Documentality in the works of other writers, namely the works of Bernd Frohmann and Maurizio Ferraris.

The article points to historical shifts in the study of documents in Library and Information Science.

Documentality critically and materially studies documents in sociotechnical information management systems and elsewhere.

This work highlights the importance of the above works and the importance of the neo-documentalist perspective of Documentality.

The purpose of this paper is to improve autonomous flight performance of a fixed-wing unmanned aerial vehicle (UAV) via simultaneous morphing wingtip and control system design conducted with optimization, computational fluid dynamics (CFD) and machine learning approaches.

The main wing of the UAV is redesigned with morphing wingtips capable of dihedral angle alteration by means of folding. Aircraft dynamic model is derived as equations depending only on wingtip dihedral angle via Nonlinear Least Squares regression machine learning algorithm. Data for the regression analyses are obtained by numerical (i.e. CFD) and analytical approaches. Simultaneous perturbation stochastic approximation (SPSA) is incorporated into the design process to determine the optimal wingtip dihedral angle and proportional-integral-derivative (PID) coefficients of the control system that maximizes autonomous flight performance. The performance is defined in terms of trajectory tracking quality parameters of rise time, settling time and overshoot. Obtained optimal design parameters are applied in flight simulations to test both longitudinal and lateral reference trajectory tracking.

Longitudinal and lateral autonomous flight performances of the UAV are improved by redesigning the main wing with morphing wingtips and simultaneous estimation of PID coefficients and wingtip dihedral angle with SPSA optimization.

This paper originally discusses the simultaneous design of innovative morphing wingtip and UAV flight control system for autonomous flight performance improvement. The proposed simultaneous design idea is conducted with the SPSA optimization and a machine learning algorithm as a novel approach.

This paper aims to examine the relationship between the payment of bribes, the access to electricity and the productivity of informal production units (IPUs).

The data used for this study come from the second Survey on Employment and Informal Sector conducted in 2010 by the National Institute of Statistics of Cameroon and representative at the national level. The survey was conducted among 3,560 IPUs. Survey participants reported whether they had been personally affected by corruption in the twelve months preceding the survey. Relying on the data of this survey, the recursive trivariate probit model was used to study the correlation between corruption and access to electricity.

The results reveal that the payment of bribes positively influences IPU access to electricity, and consequently access to this infrastructure has a positive impact on company performance.

A main limitation of this paper is the environment of study in which corruption appeared to be institutionalised. It would therefore be interesting to extend the results obtained by conducting research in other countries and also including other infrastructures such as telecommunications.

The main contribution of this research is to highlight the effectiveness of the fight against corruption and its impact on the access of some basics resources that affect the performance of certain companies. Indeed, the fight against corruption would be easier if economic actors had access to certain resources and fundamental infrastructures for their activities. Thus, improving the supply of resources and infrastructures can be an important lever in the fight against corruption in Africa.

This research addresses a vulnerable sector vis-à-vis the pressure of the actors involved in the provision of a service essential to the activity of companies. It highlights the justification for accepting the use of corruption. Indeed, entrepreneurs are faced with a dilemma between moral standards on the one hand, and economic imperatives on the other. If corruption is a condition of access to electricity which, in turn, improves performance, it is easy to pay bribes to gain access to electricity.

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 consumers want to purchase the target products in the right place, whereas the manufacturers want to allocate their possible products to optimal distribution channels. The manufacturer must know how to handle itself in this business. The study aims to examine the B2B channel decision-making with different product qualities in a non-cooperative supply chain.

The authors develop a B2B Manufacturer-Stackelberg game as an analytical framework, combining asymmetric preference of purchase channels choice by the consumers, a continuous quality setting of the manufacturer and differential channel structure to study the manufacturer’s product strategy and channel optimisation. By horizontal comparisons across four channel structures, product variety can be classified into the differential quality-level zone through exogenous quality intervention, and the preference of manufacturers in each quality-level zone within the structures can be ranked.

Theoretically and practically, the hybrid-channel structure should be completely neglected when the direct channel dominates the retail channel. In contrast, dual-channel structures dominate single channels irrespective of the channel power, and channel preferences between high-quality and low-quality zones are stable, whereas the preference in medium-quality zone is unstable. In addition, the supply chain system cannot achieve global Pareto improvement without any additional coordination mechanism between the manufacturer and the retailer.

The extended results by numerical examples suggest that the bigger the area of the medium-quality zone, the more significant the product variety of the manufacturer.

The purpose of this article is based on the unit patent license fee model in the closed-loop supply chain.

This paper analyzes the impact of the bundling strategy of the retailer selling new products and remanufactured products on the closed-loop supply chain under the condition that the original manufacturer produces new products and the remanufacturer produces remanufacturing products.

The results show that alternative products can be bundled, and in many cases, the bundling of remanufactured products and new products is better than selling alone.

If the retailer chooses bundling, for the remanufacturer, when certain conditions are met, the benefits of bundling are greater than the separate sales at that time; for the original manufacturer, when the recycling price sensitivity coefficient is high, the bundling is better than separate sales.

The purpose of this research is to increase academic understanding of the relationship between systems' political identity and their viability, and to contribute to anarchist-cybernetics by examining the idea of organization proposed by Malatesta using Viable Systems. The research also develops the understanding of the relationship between Viable Systems and the environment.

The author developed a content analysis method that uses dynamic analysis, identifying how some variables affect others, and data is analysed using the Viable Systems Model. The author used Dynamic Causal Diagrams and the Viable System Model to draw conclusions and build theory. The author examined 137 documents produced by Errico Malatesta, studying in detail 39 documents containing the researched concepts.

The article identifies the literature, proposes an organizational theory for society and for cooperatives, strongly grounded in both, self-management and control. It presents a theory of self-management as a balancing effort to the control exercised by the external economic, political and societal forces of the environment. The literature also shows a form of organization that can be interpreted using the VSM framework. The ideas about self-management found in the literature, extend to economics, social theory, ethics, organizations, management and even operations management. The article finishes proposing a set of committees linked to the VSM structure, and successfully bridges anarchism and organizational cybernetics.

The article presents a novel method of systems analysis for the study of literature. It discovers the theory proposed by Malatesta not identified previously. Using the VSM framework, the ideas presented by the author, are translated into the organizational identity, and the operation of cooperatives. It makes an important contribution to anarchist-cybernetics.