In this paper, we consider a predator-prey model incorporating fear and refuge. Our results show that the predator-free equilibrium is globally asymptotically stable if the ratio between the death rate of predators and the conversion rate of prey into predator is greater than the value of prey in refuge at equilibrium. We also show that the co-existence equilibrium points are locally asymptotically stable if the value of the prey outside refuge is greater than half of the carrying capacity. Numerical simulations show that when the intensity of fear increases, the fraction of the prey inside refuge increases; however, it has no effect on the fraction of the prey outside refuge, in the long run. It is shown that the intensity of fear harms predator population size. Numerical simulations show that the application of Z-control will force the system to reach any desired state within a limited time, whether the desired state is a constant state or a periodic state. Our results show that when the refuge size is taken to be a non-constant function of the prey outside refuge, the systems change their dynamics. Namely, when it is a linear function or an exponential function, the system always reaches the predator-free equilibrium. However, when it is taken as a logistic equation, the system reaches the co-existence equilibrium after long term oscillations.

Estimates of agents in a distributed consensus control are aligned with a particular value through interacting on communication graphs, which are of particular interest for researchers in the field of multi-agent coordination. Following this pattern, a discrete-time constrained consensus issue with generalized time delays is first established in this article, which is manipulated into an optimization problem via a quadratic performance index introduced as a global objective function. Then, a novel consensus scheme is investigated and proposed for handling this problem, enabling the consensus to approach the desired state globally and rapidly with optimal system property ensured. Besides, to advance the convergence speed and stability in resisting constant bias or oscillation, an adjustment control method is explored to construct a modified consensus scheme; further, to enhance the scene adaptability, fix topologies are extended to switching ones, and the latter is involved to develop another scheme on this basis. Moreover, the convergence and robustness of these three proposed consensus schemes are substantiated by theoretical analysis and numerical simulations. To highlight the practical implementations, the proposed consensus schemes are incorporated with a winner-take-all operation to accomplish multi-agent competitive coordination in a distributed way, and the results embody their effectiveness and superior consensus control ability, along with strong plasticity. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is dedicated to investigating and optimizing distributed consensus schemes with time delays and output saturation with application to the competitive coordination of multi-agent systems. On the one hand, the consensus problem with output saturation receives limited attention, and few consensus algorithms consider both saturation limitation and channel gain. On the other hand, most existing studies on consensus with saturation consider simply the dynamic behaviour of agents without employing optimization, thus limiting further improvement of system performance. In this paper, a consensus algorithm is built from an optimization perspective that guarantees the state consensus of a multi-agent system with output constraints and generalized time delays. In addition, a consensus scheme is designed in a discrete-time framework and further modified and perfected along with the idea of considering time delays and expanding diverse topologies. Finally, experiments are conducted by applying the consensus scheme to a winner-take-all operation, with contributions of this paper verified.

This technical paper utilizes the Lyapunov theory to characterize the event-triggered set stabilizability of Markovian jump logical control networks (MJLCNs). Whereas the existing result for checking the set stabilizability of MJLCNs is only sufficient, this technical paper further establishes its necessary and sufficient condition. First, the Lyapunov function is established to describe the set stabilizability of MJLCNs necessarily and sufficiently by combining recurrent switching modes and desired state set. Then, the triggering condition and the input updating mechanism are designed regarding the value change of the Lyapunov function. Finally, the effectiveness of theoretical results is demonstrated by a biological example concerning the lac operon in Escherichia coli.

Modern humans are failing to attain their existential potential, expressed as flourishing. Simultaneously, megaproblems like climate change have arisen as unintended consequences of normal societal behaviors. Both failings lie at the deepest root of modern culture, the way we think we think, and consequently choose our norms and design our cultural institutions. The paper explicates a transformative model of cognition, recently developed by Iain McGilchrist, that raises the possibility of flourishing. According to the model, each brain hemisphere attends to the world differently and, thus, produces two distinctive actors. When the right is master, actions reflect the immediate external world, that is, they care for it. When the left controls, actions reflect a virtual world of facts and theories that have been abstracted from experience and stored in the left hemisphere. Its actions are instrumental and treat the real world as a resource. The ills and failings of modernity spring from an excess of left-brain domination. Flourishing, as the desired state of human and natural affairs, requires rejuvenating the right side as master. Some practical approaches, for example, mindfulness exercises, are offered. Pragmatic inquiry, importantly, should become the primary method for dealing with such large, complex problems.

A nonlinear system, exhibiting a unique asymptotic behaviour, while being continuously subject to a stimulus from a certain class, is said to suffer from fading memory. This interesting phenomenon was first uncovered in a non-volatile tantalum oxide-based memristor from Hewlett Packard Labs back in 2016 out of a deep numerical investigation of a predictive mathematical description, known as the Strachan model, later corroborated by experimental validation. It was then found out that fading memory is ubiquitous in non-volatile resistance switching memories. A nonlinear system may however also exhibit a local form of fading memory, in case, under an excitation from a given family, it may approach one of a number of distinct attractors, depending upon the initial condition. A recent bifurcation study of the Strachan model revealed how, under specific train stimuli, composed of two square pulses of opposite polarity per cycle, the simplest form of local fading memory affects the transient dynamics of the aforementioned Resistive Random Access Memory cell, which, would asymptotically act as a bistable oscillator. In this manuscript we propose an analytical methodology, based on the application of analysis tools from Nonlinear System Theory to the Strachan model, to craft the properties of a generalised pulse train stimulus in such a way to induce the emergence of complex local fading memory effects in the nano-device, which would consequently display an interesting tuneable multistable oscillatory response, around desired resistance states. The last part of the manuscript discusses a case study, shedding light on a potential application of the local history erase effects, induced in the device via pulse train stimulation, for compensating the unwanted yet unavoidable drifts in its resistance state under power off conditions.

Consumers’ personality traits significantly influence their perceptions regarding social media advertising. While prior research on consumers’ purchasing intentions in social networking sites advertising has mainly focused on advertising valence antecedents, it is crucial to recognize that consumers’ susceptibility to advertising persuasion, particularly in terms of empathic expression, varies based on a key criterion: whether consumers are driven to attain a specific desired state or are more inclined to avoid an undesirable state. Regulatory Focus Theory (RFT) posits that individuals operate under distinct motivational mechanisms that govern their determination to achieve desired goals, influencing how they process and evaluate advertising messages. In light of RFT, we conducted an online survey with 524 valid responses, utilizing partial least squares (PLS) for research model analysis. The findings revealed that promotion-focused individuals have positively influenced perceptions of social media ad effectiveness (informativeness, ad creativity, perceived relevance, and emotional appeal). In contrast, prevention-focused individuals negatively perceived social media ad effectiveness. Furthermore, this study highlighted that perceived relevance and emotional appeal have a more significant impact on attitudes toward expressing empathy than informativeness and ad creativity.

A stable power system is a desirable state for the optimal performance and delivery of electricity to the end-users. This study evaluates the effectiveness of grid contingency support devices in power system stability enhancement. The new voltage stability pointer (NVSP) was employed to optimally infer the flexible alternating current transmission systems devices through N − 1 contingency ranking. In this research, the static synchronous compensator (STATCOM) was considered as a grid support device. The effectiveness of this technique was validated in R2018a MATLAB with the IEEE 30-bus system using different combinable contingency cases to ascertain the critical lines and vulnerable buses to outages. Based on the results obtained through the NVSP, buses 30, 26, and 29 were cited as STATCOM candidate buses for overall optimal grid performance. The results obtained from the simulation revealed that the total real power loss was reduced by 90.21%. Similarly, the voltage magnitude of the buses was significantly improved to a minimum of 1.00 p.u. after placement of STATCOMs. Further investigation on single STATCOM placement in the IEEE 30-bus system revealed that the highest level of voltage improvement, minimum level of voltage deviation and maximum active power loss reduction was achieved when the STATCOM was placed at bus 30. The overall assessment of the proposed technique yielded better results compared with other methods on the same test system.

This study was conducted to clearly diagnose social conflicts and confusion that our society is experiencing in the form of governance called popular democracy and to seek solutions for them. To this end, in order to utilize the insights of the state presented by John Dewey in the era of the industrial revolution, Dewey's theory of the state was analyzed, focusing on his book The Public and Its Problems, and educational implications were presented based on this.&#x0D; The research question is as follows. ① What is the state? ② What is the desirable state in Dewey's opinion? What are the educational ways to achieve this? The research results are as follows. ① According to Dewey, the state is not a fixed entity but a evolving process. It appears in various forms in time and space, the boundaries between private and public things change fluidly in it, it tries to maintain traditions and customs, and it intervenes in important public matters. ② The net of interdependence has become wide and complex, but solidarity has weakened, and we should change ‘a giant society’ into ‘the great community’. To this end, signs and symbols can be utilized and freedom of social inquiry and sharing the results of it should be guaranteed. ③ In order to realize this educationally, it is necessary to foster ‘the great public’ by strengthening discussion classes. Through discussion classes, students can strengthen their ability to analyze complex social phenomena, have an opportunity to acquire democratic attitudes, and gain experience in creating and implementing the common good.&#x0D; To resolve the constant conflict in modern society, the great community is needed. The great community needs the great public, and the great public needs the great education. We should establish a vision of the great community and realize it through the method of the great education.

In recent years, there has been a growing emphasis on the efficient utilization of natural resources across various facets of life. One such area of focus is transportation, particularly electric mobility in conjunction with the deployment of renewable energy sources. To fully realize this objective, it is crucial to quantify the probability of achieving the desired state—production exceeding consumption. This article deals with the computation of the probability that the energy required to charge an electric vehicle will originate from a renewable source at a specific time and for a predetermined charging duration. The base of the model lies in artificial neural networks, which serve as an ancillary tool for the actual probability assessment. Neural networks are used to forecast the values of energy production and consumption. Following the processing of these data, the probability of energy availability for a given day and month is determined. A total of seven scenarios are calculated, representing individual days of the week. These findings can help users in their decision-making process regarding when and for how long to connect their electric vehicle to a charging station to receive assured clean energy from a local photovoltaic source.

Human impacts are dramatically changing ecological communities, motivating research on resilience. Tropical reefs are increasingly undergoing transitions to short algal turf, a successional community that mediates either recovery to coral by allowing recruitment or transitions to longer turf/macroalgae. Intense herbivory limits turf height; subsequently, overfishing erodes resilience of the desirable coral-dominated reef state. Increased sedimentation also erodes resilience through smothering and herbivory suppression. In spite of this critical role, most herbivory studies on tropical reefs focus on fishes, and the contribution of urchins remains under-studied. To test how different herbivory and sedimentation scenarios impact turf resilience, we experimentally simulated, in situ, four future overfishing scenarios derived from patterns of fish and urchin loss in other reef systems and two future sedimentation regimes. We found urchins were critical to short turf resilience, maintaining this state even with reduced fish herbivory and increased sediment. Further, urchins cleared sediment, facilitating fish herbivory. This study articulates the likelihood of increased reliance on urchins on impacted reefs in the Anthropocene.

Layered zeolitic silicates and corresponding interlayer-expanded porous materials exhibit attractive application potential in wide fields. Nonetheless, designable synthesis and structure analysis of layered silicates remain challenging. Herein, two kinds of layered silicates are synthesized using different di-quaternary ammonium-type organic structure-directing agents (OSDAs). Their crystal structures are analyzed and verified by 3D electron diffraction (3D ED) and high-resolution TEM imaging. The suitable configurations of OSDA can lead to desirable interlayer states. Additionally, two new zeolite structures both with 12-membered ring (MR) channels intersected by 8 MR channels and larger interlayer spaces are constructed from layered silicate precursors by interlayer silylation. The new zeolitic material exhibits potential application in adsorption of organic pollution and catalytic reaction. This study is expected to develop versatile ways for the design and synthesis of layered silicates even zeolites and provide references in characterizing layered materials and zeolites as well.

We analyze the finite element discretization of distributed elliptic optimal control problems with variable energy regularization, where the usual L2(Ω) norm regularization term with a constant regularization parameter ϱ is replaced by a suitable representation of the energy norm in H−1(Ω) involving a variable, mesh-dependent regularization parameter ϱ(x). It turns out that the error between the computed finite element state u˜ϱh and the desired state u‾ (target) is optimal in the L2(Ω) norm provided that ϱ(x) behaves like the local mesh size squared. This is especially important when adaptive meshes are used in order to approximate discontinuous target functions. The adaptive scheme can be driven by the computable and localizable error norm ‖u˜ϱh−u‾‖L2(Ω) between the finite element state u˜ϱh and the target u‾. The numerical results not only illustrate our theoretical findings, but also show that the iterative solvers for the discretized reduced optimality system are very efficient and robust.

Volatile electrical energy prices are a challenge and an opportunity for small and medium-sized companies in energy-intensive industries. By using electrical energy storage and/or an adaptation of production processes, companies can significantly profit from time-depending energy prices and reduce their energy costs.We consider a time-discrete optimal control problem to reach a desired final state of the energy storage at a certain time step. Thereby, the energy input is discrete since only multiples of 100 kWh can be purchased at the EPEX SPOT market. We use available price estimates to minimize the total energy cost by a rounding based dynamic programming approach. With our model non-linear energy loss functions of the storage can be considered and we obtain a significant speed-up compared to the integer (linear) programming formulation.

IntroductionThe present study aimed to assess the status of workplace mental health from the viewpoints of educators, and explore their experiences concerning influential factors on occupational mental health at Shahid Sadoughi University of Medical Sciences.MethodsThe study was a sequential mixed-method study that was conducted in quantitative and qualitative phases. In the quantitative phase, the perception of educators (n = 205) was assessed by a Workplace Mental Health Questionnaire, including 37 items in 9 categories (including an opportunity to control, an opportunity to use skills, external goals created, environmental diversity, environmental clarity, access to money, physical security, opportunity to contact others, and valuable social status and position). In the qualitative phase, data were collected using semi-structured interviews (n = 21) and were analyzed based on the conventional content analysis approach.ResultsThe results showed that the status of workplace mental health of educators was at a moderate level (mean (± SD) = 115.87 (±3.21). The highest and lowest scores of the median were reported in the domains of “opportunity for control” (median = 4) and “opportunity to contact others” (median = 2.75), respectively. The theme of “contrast between preferences and disappointments in the development path” with two categories including “induced demotivation of system elements” and “tendencies of promotion” was explored from the educators’ perspective.ConclusionThe results indicated the moderate level of mental health of educators was influenced by the contrast between preferences and disappointments in the development path. The tendency of educators for promotion was explored as a positive factor in the mental health of educators in the academic environment. A growing desire for creative advancement among educators as a personal factor and a demand to stay updated with all developments as a system factor explained the positive experiences of educators in the university. The results showed the gap between the current situation and the desired state of occupational mental health may result from cultural challenges, lack of adherence to professionalism at the personal level (non-compliance with the principles of well-being and excellence), and interpersonal level (non-compliance with respect, justice, etc.). Moreover, factors disrupting occupational mental health at the system level explored in job stress, a resilient culture, lack of managerial support, ingratitude, lack of reward-effort matching mechanism, and lack of resources.

Abstract Human‐wildlife coexistence as a concept and management objective has received increasing attention from researchers and decision makers. The coexistence approach will benefit from the recognition that, at broader scales, human‐wildlife interactions (HWI) are best understood and managed collaboratively and as complex systems, that is, dynamic, non‐linear, emergent, adaptive and, therefore, unpredictable. We present a planning process for human‐wildlife coexistence that provides a platform for collaboration between researchers and decision‐makers—and other stakeholders as well—and recognizes the complex nature of HWI. The three elements that define the process are: coexistence instead of conservation or conflict mitigation as a goal, systems thinking as the approach, and an emphasis on verifiable results rather than actions. As a way of illustration, we describe a 3‐day planning workshop for human‐jaguar coexistence in the Pantanal, Brazil. The 15 participants representing the academic, governmental, and non‐profit sectors identified 12 interactions directly involving 27 stakeholders and indirectly another 55. A theory of change was produced, connecting 20 actions—to be performed by 22 actors—with the 57 factors that directly and indirectly drive the interactions. How these results complement other approaches such as Action Plans is discussed. The proposed approach favors the pragmatism of adaptive co‐management over the often unrealistic expectation of a linear path to solution, or in other words, a shift from the notion of human‐wildlife coexistence as a quantifiable target to that of coexistence as a desired system state.

Rapid smartphone replacement contributes significantly to electronic waste issues. This paper investigates determinants of premature smartphone obsolescence amongst young adults and proposes psychology-based solutions to reduce associated sustainability impacts. Activity Theory maps replacement journeys to focus interventions on problem recognition. Grounded in contemporary Installation Theory, obsolescence drivers are analysed across physical affordances, embodied competencies and social regulations. Smartphone replacement journeys are mapped through Activity Theory to focus on problem recognition as an intervention point. Expert interviews and a user survey supplement literature in investigating obsolescence factors. Solutions are then structured along Installation Theory dimensions for a systemic approach targeting underlying barriers. Solutions address the three layers of behavioural determination. Smartphone modularity addresses physical issues, like repairability and upgrade. Consumer education campaigns improve competencies and perceptions, hereby fostering longer use. A “Slow Smartphone Movement” is proposed, leveraging social strategies, including pledges and online communities, to redefine cultural obsolescence narratives and address the positional aspects of having the latest generation smartphone. Together these multilayered interventions provide actionable pathways to prolonging lifespan by fundamentally reshaping psychological ownership patterns underlying premature smartphone disposal. Rather than isolated initiatives, these synergistic solutions provide specific, evidence-based pathways to fundamentally transforming entrenched obsolescence mindsets and behaviours amongst younger demographics. The paper concludes by outlining study limitations and stating that future research must empirically evaluate the proposed solutions.The current paper investigates the determinants and consequences of premature smartphone obsolescence amongst young adults and proposes psychology-based solutions to reduce its detrimental environmental and societal impact. Activity Theory was used to define the research scope, ultimately focusing on the first stage in the buyer behaviour model, reflecting a prototypical customer journey along five consecutive decision stages. Problem recognition, essentially the perceived difference between the current and desired state of being, was subsequently analysed through the three interrelated layers of Installation Theory, physical affordances, embodied competencies, and social regulations. Eventually, potential solutions, grounded in academic literature, expert interviews, and a consumer survey, were organised along the three dimensions of installation theory, creating a holistic and effective strategy for tackling smartphone obsolescence. Smartphone modularity represents a promising starting point to address the problems associated with physical affordances, such as broken parts, worn batteries, and planned obsolescence more generally.Additionally, extensive consumer education coupled with awareness campaigns highlighting the alternatives to purchasing new products and awareness campaigns highlighting the alternatives to purchasing new products could tackle issues associated with embodied competencies. Lastly, social regulations manifested partly in the universal need for belonging and social inclusion, represent the last driver of smartphone obsolescence. Virtual communities and reward schemes could further foster lasting normative change, eventually helping redefine the detrimental consumerism culture.

The article substantiates directions for improving the competencies of public officials in managing local development on the basis of process management. It is noted that improving the competences of public officials in managing local development on the basis of process management is an urgent need today. The need to systematize public officials ideas about the essential features and features of process management is proven, namely: basic types of activities in process management; models and measurements of process maturity; process efficiency index calculations; process management success factors; optimization of processes (rules and principles of reengineering). For effective management of local development on the basis of process management, the development of professional competencies of public servants should be carried out through the formation of a holistic vision of the desired state of the municipal entity as a system with detailed outcomes. This will require skills and abilities to align strategic processes with a holistic vision, digitize processes, and further optimize them. Key in this context are the marketing competence of public officials and their mastery of techniques for activating behavioral insights, including community members.

In this work, we combine nonlinear system control techniques with next-generation reservoir computing, a best-in-class machine learning approach for predicting the behavior of dynamical systems. We demonstrate the performance of the controller in a series of control tasks for the chaotic Hénon map, including controlling the system between unstable fixed points, stabilizing the system to higher order periodic orbits, and to an arbitrary desired state. We show that our controller succeeds in these tasks, requires only ten data points for training, can control the system to a desired trajectory in a single iteration, and is robust to noise and modeling error.

Urban and regional systems often face the difficulty and necessity of structural transitions. These transitions, which can be imposed by external circumstances or initiated by a city itself, include energy transitions, transitions to a circular economy, transitions following a pandemic or natural disaster, or intentional policies meant to “move” an urban economy toward a desired state. However, what does economic structure mean in these cases? Traditional notions of economic structure are ambiguous and simplistic and typically consist of simple distributions, such as number of workers per industry. Yet to better understand, guide, or respond to system transitions, planners must move beyond these nebulous notions toward a theoretically grounded, quantifiable definition of economic structure. A recent trend emerging from the nexus of complexity science and urban science has been to operationalize urban economic structures as networks of interacting economic components. Typically based on colocation patterns of some type of entity, these networks have previously been constructed using economic entities such as products, occupations, or labor skills. Yet different types of entities also exhibit colocation patterns with each other, such as patent technology classes and industries. Here, those cross-entity colocation patterns are used to merge multiple types of entities into a single network representation of urban economies, offering a granularity not possible using a single node type. Occupations, industries, college degrees, and patent technology codes are merged into one multidimensional or multinodal network. As in previous studies, a dense core of highly connected entities emerges in this network. The network locations of individual cities are contrasted, and community detection algorithms are used to identify clusters of highly connected economic entities, showing that the densely connected network core is associated with science, technology, and business-related economic entities. Proximities between individual cities within the network are also measured revealing that many cities that are close to each other in the network are also close to each other in physical space. This framework offers potential applications including the ability to quantify structural change over time in response to a shock or to assess the relative difficulty of future desirable trajectories. More broadly, this framework might be applied to the study of structural change in other complex adaptive systems from human institutions to ecosystems.

Analyzing the effects of helical flow in blood vessels using acoustofluidic-based dynamic flow generator