Consideration Of Dynamics Research Articles

Reimagining art therapy for the digitally-mediated world: a Hexagonal Relationship

ABSTRACT Art Therapists have long been aware of the intersubjective complexities that are evoked in art therapy in relation to images, art-making and their attendant processes. These have often been understood with reference to the psychodynamic concepts of transference and countertransference. In this paper we ask, what happens to these processes when art therapy moves online and becomes digitally-mediated? How do the dynamics of ‘the Virtual’ affect the image and art-making, and the therapeutic relationship? Drawing on Schaverien and Jung’s ideas about transference and countertransference, we propose a new model or ‘map’ of Art Therapy which helps to think about these questions, which we call a ‘Hexagonal Relationship’. To date, published literature has tended to foreground the logistics and practicalities of moving art therapy online, with consideration of complex interpersonal dynamics occupying less of a central space in emerging narratives about digitally-mediated art therapy. We suggest that applying our model to practice could potentially support art therapists to access deeper, less conscious and perhaps more symbolic levels of material in online work, in service of the client’s process. We invite art therapists and clients to consider our model with reference to their own experiences of digitally-mediated art therapy, and to test out our questions and hypotheses in their own contexts. Plain-language summary Art Therapists work with the idea that the images made in art therapy are affected by the relationship between the person making the image (often known as ‘the client’), the art therapist, and the environment in which the art therapy session takes place. Making and reflecting on images is a way of understanding and working with whatever is going on for the client, both in their ‘external’ life and also in their ‘internal world’ (for example, their thoughts, feelings, imaginings and beliefs). A lot of art therapy now happens online, particularly since the start of the COVID-19 pandemic, and we are all part of the digital world in terms of how we communicate and relate with others. We think it is helpful to consider how art therapy (including the therapeutic relationship, art-making processes and the images made) might be affected by the digital environment and so we have written this paper to explore these ideas. We show readers a diagram of what we call the ‘Hexagonal Relationship’ to help explain what we mean. We think this will help us to understand more of what happens in art therapy in the digital world, making this kind of therapeutic help more effective and meaningful for clients and their art therapists. We hope that clients and art therapists will test out these ideas for themselves and come into a conversation with us (perhaps through papers like this one, published in art therapy journals) about how well our ideas stand up to actual experience.

From sink to source: changing climate and disturbance regimes could tip the 21st century carbon balance of an unmanaged mountain forest landscape

Abstract Forests are one of the most important components of the global carbon cycle. Consequently, forest protection as a nature-based climate solution has garnered increasing interest. Protected areas instated to safeguard biodiversity provide an opportunity to maximize carbon storage in situ, with important co-benefits between conservation and climate change mitigation. However, changing climate and disturbance regimes put this carbon storage function at risk. Here we investigated carbon sequestration and storage in a protected landscape in the German Alps (Berchtesgaden National Park) throughout the 21st century. We simulated the impacts of climate change as well as increasing wind and bark beetle disturbances on cumulative Net Ecosystem Production using a process-based forest landscape model. Considering a wide range of potential changes in wind frequency and speed under a variety of climate change scenarios, we addressed the question under which future conditions the landscape will turn from a carbon sink to a carbon source. While the landscape was a net carbon sink at the end of the simulation in 76 per cent of the simulation runs, increasing disturbances and climate change greatly reduced its carbon sink capacity. Under RCP2.6, the landscape remained a robust carbon sink even under elevated disturbance (probability of turning from sink to source between 0 per cent and 25 per cent). In contrast, carbon release was likely under RCP8.5 even with little change in the disturbance regime (probability: 30 per cent to 95 per cent). Productive areas in lower elevations that currently have the highest carbon density on the landscape were contributing most strongly to a reduction of the carbon sink strength. Our study reveals that the effect of protected areas acting as nature-based climate solutions might be overestimated if the risks from changing climate and disturbance regimes are neglected. We therefore call for a more explicit consideration of future forest dynamics in the discussion of the potential role of forests in climate change mitigation.

A survey of visual navigation: From geometry to embodied AI

The capacity to extract information and comprehend an unseen environment is critical for mobile robots to navigate. Few surveys has mentioned the combinatorial-non-optimality problem of the traditional visual navigation methods. As computer vision technology has improved in recent years, visual navigation approaches have escalated drastically, particularly after the appearance of the CVPR Embodied AI workshop. However, few studies take these important changes into account. This survey fills this research gap by collecting, analyzing, and summarizing more than 100 recent papers. The majority of them are published within 5 years and are cited over 80 times, which provide more credible results. Based on our thorough comparison, this survey categorizes all visual navigation methods into two styles: geometry style and embodied AI style. This survey examines these two styles from the perspective of input–output. In addition, this survey attempts to provide mathematical formulations for each style. This paper provides a case study to illustrate the methodological paradigm with greatest potential. This methodological paradigm using photo-realistic simulation in the Embodied AI style, which could solve the combinatorial-non-optimality problem. Thereafter, this survey discusses several issues including pros–cons analysis, problem formulation, common framework, task generalization, dynamic environment consideration, sim-to-real, and inspiring approaches, which are all based on the scholars who have cited the method. In the last part, challenges and future trends are summarized. This survey would assist researchers who work on AI-empowered visual navigation systems.

“We are our own worst enemy”: a qualitative exploration of work-related stress in the construction industry

PurposeAround 400,000 working days per year are lost in the construction industry due to stress, depression or anxiety, but a large proportion of the industry – those primarily not based “on-site” – is not included in these statistics. Little research has been conducted in this group about their experiences of occupational stress. The authors explored how stress was experienced and managed by construction professionals and its perceived impact on health.Design/methodology/approachThe authors interviewed 32 construction professionals in a British construction company, with varying levels of seniority and years in the industry. Interviews were transcribed, coded and analysed thematically.FindingsStress was viewed an inevitable and increasing part of the construction industry, exacerbated by recent economic challenges. Participants talked about a culture of stress and overwork but often felt unable to challenge it due to job insecurity. Senior management acknowledged stress was a problem within the industry and something that potentially threatened company productivity. Company-wide initiatives had been implemented to address stress levels (e.g. Mental Health First Aiders), but were criticised for ignoring underlying issues. Informal means of managing stress were identified, such as careful consideration of team dynamics, which allowed employees to form close bonds and using “banter” and camaraderie to relieve stress. However, the persistence of a macho male image meant some participants were reluctant to talk about their feelings at work. Participants described individual coping strategies, such as exercise, but these were hard to prioritise in challenging times.Originality/valueThere is growing recognition that health and well-being must be given greater priority in the construction industry. Industry pressures and competitive practices undermine efforts to improve staff well-being. Action must be taken at senior levels to address this conflict, while building on existing informal mechanisms of support and stress relief.

Fluid mechanics of the zebrafish embryonic heart trabeculation.

Embryonic heart development is a mechanosensitive process, where specific fluid forces are needed for the correct development, and abnormal mechanical stimuli can lead to malformations. It is thus important to understand the nature of embryonic heart fluid forces. However, the fluid dynamical behaviour close to the embryonic endocardial surface is very sensitive to the geometry and motion dynamics of fine-scale cardiac trabecular surface structures. Here, we conducted image-based computational fluid dynamics (CFD) simulations to quantify the fluid mechanics associated with the zebrafish embryonic heart trabeculae. To capture trabecular geometric and motion details, we used a fish line that expresses fluorescence at the endocardial cell membrane, and high resolution 3D confocal microscopy. Our endocardial wall shear stress (WSS) results were found to exceed those reported in existing literature, which were estimated using myocardial rather than endocardial boundaries. By conducting simulations of single intra-trabecular spaces under varied scenarios, where the translational or deformational motions (caused by contraction) were removed, we found that a squeeze flow effect was responsible for most of the WSS magnitude in the intra-trabecular spaces, rather than the shear interaction with the flow in the main ventricular chamber. We found that trabecular structures were responsible for the high spatial variability of the magnitude and oscillatory nature of WSS, and for reducing the endocardial deformational burden. We further found cells attached to the endocardium within the intra-trabecular spaces, which were likely embryonic hemogenic cells, whose presence increased endocardial WSS. Overall, our results suggested that a complex multi-component consideration of both anatomic features and motion dynamics were needed to quantify the trabeculated embryonic heart fluid mechanics.

Optimization-based Model Predictive Tube Control for Autonomous Ground Vehicles with Minimal Tuning Parameters

The trajectory planning and tracking problem are critical points of intelligent vehicles concerning their safety and stability. If these parts are separated, interactions should be made between them, especially when sudden changes and disturbances appear. This paper presents a method that integrates the two parts using a cascade structure. Additionally, the proposed method deals with the interaction between the lateral and the longitudinal trajectory based on dynamical considerations. The whole problem is handled using the model predictive method based on online optimization. This system receives the path borders as input and generates the control requests for the actuators on its output. The configuration space of the system can be maximized to gain stability by handling the lateral-longitudinal parts and the trajectory planning and tracking in one complex system. The main advantage of the proposed approach is that the optimization problem in the predictive method is formulated so that the path and dynamics are considered equality and inequality constraints, and the cost function includes only a physical phenomenon to be minimized without tuning parameters. The evaluation of the proposed algorithm is presented in this paper based on simulation and real-time measurements results.

Poesia na Pesquisa em Administração

Abstract Poetry can contribute to advance management research. Reflecting on poetry as a path to regenerate management research lets us understand the ways of researching and the constitution of the researcher. Poetry is a way to start the construction of meaning and, at the same time, a coping mechanism, a way of re-existing not to de-exist. The poetic representation of lives is not an end in itself. The goal is political: to change the way we think about people and their lives in organizations using the poetic format. The researcher-poet makes the world visible from new perspectives and understandings, evidencing a political-ethical responsibility regarding the poetic. Poetry can move beyond prescribed ways of reading, writing, understanding, and ‘doing’ organizations and management, connecting itself to ethical considerations of voice and power dynamics.

Cold dynamics in cellular automata: a tutorial

This tutorial is about cellular automata that exhibit 'cold dynamics'. By this we mean zero entropy, stabilization of all orbits, trivial asymptotic dynamics, etc. These are purely transient irreversible dynamics, but they capture many examples from the literature. A rich zoo of properties is presented and discussed: nilpotency and asymptotic, generic or mu-variants, unique ergodicity, convergence, bounded-changeness, freezingness. They all correspond to the 'cold dynamics' paradigm in some way, and we study their links and differences by various examples and results from the literature. Besides dynamical considerations, we also focus on computational aspects: we show how such 'cold cellular automata' can still compute under their dynamical constraint, and what are their computational limitation.

On the analysis of open-loop Nash equilibria admitting a feedback synthesis in nonlinear differential games

Open-loop Nash equilibrium strategies for differential games described by nonlinear, input-affine, systems and cost functionals that are quadratic with respect to the control input are studied. First it is shown that the computation of such strategies hinges upon the solution of a system of nonlinear, time-varying, partial differential equations (PDEs) obtained by building on arguments borrowed from Pontryagin’s Minimum Principle and combined with Dynamic Programming considerations. Then, by relying on a state/costate interpretation of the above characterization, a feedback synthesis of the underlying open-loop strategy is obtained by solving linear first-order PDEs that ensure invariance of certain submanifolds in the state–space of the extended state/costate dynamics. These PDEs are the nonlinear counterpart of the well-known asymmetric Algebraic Riccati Equations arising in the study of linear quadratic Nash games.

From island biogeography to landscape and metacommunity ecology: A macroecological perspective of bat communities

The equilibrium theory of island biogeography and its quantitative consideration of origination and extinction dynamics as they relate to island area and distance from source populations have evolved over time and enriched theory related to many disciplines in spatial ecology. Indeed, the island focus was catalytic to the emergence of landscape ecology and macroecology in the late 20th century. We integrate concepts and perspectives of island biogeography, landscape ecology, macroecology, and metacommunity ecology, and show how these disciplines have advanced the understanding of variation in abundance, biodiversity, and composition of bat communities. We leverage the well-studied bat fauna of the islands in the Caribbean to illustrate the complex interplay of ecological, biogeographical, and evolutionary processes in molding local biodiversity and system-wide structure. Thereafter, we highlight the role of habitat loss and fragmentation, which is increasing at an accelerating rate during the Anthropocene, on the structure of local bat communities and regional metacommunities across landscapes. Bat species richness increases with the amount of available habitat, often forming nested subsets along gradients of patch or island area. Similarly, the distance to and identity of sources of colonization influence the richness, composition, and metacommunity structure of islands and landscape networks.

Developing a Ball Screw Drive System of High-Speed Machine Tool Considering Dynamics

In order to provide guidance and reference for developing a ball screw drive system of the high-speed machine tool, this article investigates three basic issues with consideration of dynamics, including mechanical characteristics, inertia matching problem, and driving torque characteristics. The axial stiffness and natural frequency of the system are first calculated to verify the correctness of mechanical parts selection, and the stability of the system is ensured by designing an appropriate gain. vvNext, the inertia matching problem between the servo motor and load is analyzed based on the two-inertia-system, and the range of the inertia ratio is determined as an important principle in developing a ball screw drive system. The speed–torque characteristics are further discussed, and a graphical method is proposed to quickly and accurately determine a suitable servo motor. Finally, a complete flow is described, and the ball screw drive systems of a high-speed machine tool for aeroengine casing manufacturing are developed as an application. The actual test results of speed, accuracy, cutting ability, and machining performance indicate that the developed ball screw drive systems have a satisfactory performance, which validate the effectiveness of the comprehensive study.

Stochastic Hybrid Approximation for Uncertainty Management in Gas-Electric Systems

Gas-fired generators, with their ability to quickly ramp up and down their electricity production, play an important role in managing renewable energy variability. However, these changes in electricity production translate into variability in the consumption of natural gas, and propagation of uncertainty from the electric grid to the natural gas system. To ensure that both systems are operating safely, there is an increasing need for coordination and uncertainty management among the electricity and gas networks. A challenging aspect of this coordination is the consideration of natural gas dynamics, which play an important role in intra-day operation, but give rise to a set of non-linear and non-convex equations that are hard to optimize even in the deterministic case. Ideally, the problem is formulated as a stochastic problem but many conventional methods for stochastic optimization are numerically intractable because they either incorporate a large number of scenarios directly or require the underlying problem to be convex. To address these challenges, we propose using a Stochastic Hybrid Approximation algorithm to more efficiently solve these problems and investigate the efficacy of several different variants of this algorithm. Our case study demonstrates that the proposed technique is able to quickly obtain high quality solutions and outperforms existing benchmarks such as Generalized Benders Decomposition. We demonstrate that coordinated uncertainty management that accounts for the gas system can significantly reduce both electric and gas system load shed in stressed conditions.

Wind field reconstruction using nacelle based lidar measurements for floating wind turbines

In this work we investigate the influence of floater motions on nacelle based lidar wind speed measurements. The analysis is focused on wind field characteristics which are most relevant for performance analysis, namely rotor effective wind speed, shear and turbulence intensity. A numerical approach, coupling the publicly available in-house lidar simulation framework ViConDAR (Virtual Constrained turbulence and liDAR measurements) with an aeroelastic floating offshore wind turbine simulation is employed. Synthetic turbulent wind fields are generated with the open source turbulence generator TurbSim. The dynamics of the floating offshore wind turbine are simulated in the aeroelastic simulation code OpenFAST. Turbine dynamics and the corresponding synthetic wind field are then passed to the lidar simulation module of ViConDAR, which has been adapted for the consideration of turbine dynamics in all six degrees of freedom to simulate the lidar measurements under influence of motion. The simulation framework is demonstrated in a case study, simulating a lidar system on the nacelle of the IEA 15 MW turbine in combination with the WindCrete floater concept. Two different realistic lidar patterns are investigated under different metocean conditions. Different motion cases are examined individually and combined to evaluate the influence of rotational and translational degrees of freedom. Results show an increase of mean absolute error between lidar estimated and full wind field rotor effective wind speed of 0 to 25% depending on the environmental conditions. Observed overestimation of mean rotor effective wind speed was found to be in the region of up to 1%.

Phase and amplitude evolution in the network of triadic interactions of the Hasegawa–Wakatani system

The Hasegawa–Wakatani system, commonly used as a toy model of dissipative drift waves in fusion devices, is revisited with considerations of phase and amplitude dynamics of its triadic interactions. It is observed that a single resonant triad can saturate via three way phase locking, where the phase differences between dominant modes converge to constant values as individual phases increase in time. This allows the system to have approximately constant amplitude solutions. Non-resonant triads show similar behavior only when one of its legs is a zonal wave number. However, when an additional triad, which is a reflection of the original one with respect to the y axis is included, the behavior of the resulting triad pair is shown to be more complex. In particular, it is found that triads involving small radial wave numbers (large scale zonal flows) end up transferring their energy to the subdominant mode which keeps growing exponentially, while those involving larger radial wave numbers (small scale zonal flows) tend to find steady chaotic or limit cycle states (or decay to zero). In order to study the dynamics in a connected network of triads, a network formulation is considered, including a pump mode, and a number of zonal and non-zonal subdominant modes as a dynamical system. It was observed that the zonal modes become clearly dominant only when a large number of triads are connected. When the zonal flow becomes dominant as a “collective mean field,” individual interactions between modes become less important, which is consistent with the inhomogeneous wave-kinetic picture. Finally, the results of direct numerical simulation are discussed for the same parameters, and various forms of the order parameter are computed. It is observed that nonlinear phase dynamics results in a flattening of the large scale phase velocity as a function of scale in direct numerical simulations.

Expanding the Accessible Chemical Space of SIRT2 Inhibitors through Exploration of Binding Pocket Dynamics.

Considerations of binding pocket dynamics are one of the crucial aspects of the rational design of binders. Identification of alternative conformational states or cryptic subpockets could lead to the discovery of completely novel groups of the ligands. However, experimental characterization of pocket dynamics, besides being expensive, may not be able to elucidate all of the conformational states relevant for drug discovery projects. In this study, we propose the protocol for computational simulations of sirtuin 2 (SIRT2) binding pocket dynamics and its integration into the structure-based virtual screening (SBVS) pipeline. Initially, unbiased molecular dynamics simulations of SIRT2:inhibitor complexes were performed using optimized force field parameters of SIRT2 inhibitors. Time-lagged independent component analysis (tICA) was used to design pocket-related collective variables (CVs) for enhanced sampling of SIRT2 pocket dynamics. Metadynamics simulations in the tICA eigenvector space revealed alternative conformational states of the SIRT2 binding pocket and the existence of a cryptic subpocket. Newly identified SIRT2 conformational states outperformed experimentally resolved states in retrospective SBVS validation. After performing prospective SBVS, compounds from the under-represented portions of the SIRT2 inhibitor chemical space were selected for in vitro evaluation. Two compounds, NDJ18 and NDJ85, were identified as potent and selective SIRT2 inhibitors, which validated the in silico protocol and opened up the possibility for generalization and broadening of its application. The anticancer effects of the most potent compound NDJ18 were examined on the triple-negative breast cancer cell line. Results indicated that NDJ18 represents a promising structure suitable for further evaluation.

Lattice Boltzmann investigation of flow boiling in a microchannel

A hybrid multiphase lattice Boltzmann model is adopted to investigate the flow boiling heat transfer process in a horizontal microchannel with consideration of bubble dynamics. The flow pattern transition in a microchannel, involving single-phase flow, bubbly flow, slug flow, and contact-slug flow, is reproduced by varying the heat flux. The influencing parameters, including the liquid mass flux, the heating wall wettability, and the confinement height of channels, on dynamic bubble behaviors and heat transfer performance are discussed. The results indicate that a sequence of single-phase flow, bubbly flow, slug flow, and contact-slug flow occurs in a microchannel with increasing heat flux. Correspondingly, the dominant heat transfer mechanism experiences the liquid convection (single-phase flow), nucleate boiling (bubbly flow), the microlayer evaporation (slug flow), and the hybrid gas convection and microlayer evaporation (contact-slug flow). The increase of mass flux or confinement height extends the range of heat flux for high-efficiency bubbly and slug flow. The hydrophilic heating wall is preferred for better heat transfer performance in a microchannel due to the strengthened microlayer evaporation and less vapor occupation of the effective nucleation area.

Kinetic exchange models of societies and economies.

The statistical nature of collective human behaviour in a society is a topic of broad current interest. From formation of consensus through exchange of ideas, distributing wealth through exchanges of money, traffic flows, growth of cities to spread of infectious diseases, the application range of such collective responses cuts across multiple disciplines. Kinetic models have been an elegant and powerful tool to explain such collective phenomena in a myriad of human interaction-based problems, where an energy consideration for dynamics is generally inaccessible. Nonetheless, in this age of Big Data, seeking empirical regularities emerging out of collective responses is a prominent and essential approach, much like the empirical thermodynamic principles preceding quantitative foundations of statistical mechanics. In this introductory article of the theme issue, we will provide an overview of the field of applications of kinetic theories in different socio-economic contexts and its recent boosting topics. Moreover, we will put the contributions to the theme issue in an appropriate perspective.This article is part of the theme issue ‘Kinetic exchange models of societies and economies’.

Hybrid Hierarchical Learning for Adaptive Persuasion in Human-Robot Interaction

Adaptive learning is critical to helping robots personalize their interactions with people, particularly when considering skills needed by socially assistive robots, such as persuasion. In this letter, we propose a novel, hybrid hierarchical learning architecture for use in social human-robot interaction (HRI) to adapt robot persuasive behaviors to both the static (e.g., need for cognition) and dynamic (e.g., affect) considerations of a user. A learning hierarchy is introduced that uses a contextual bandit approach in the top level to optimize for a static cognition bias and <i>Q</i>-Learning in the lower level to optimize selection of a robot persuasive strategy to deploy that aligns with a user&#x0027;s affect. We compare the performance of our system with a non-hierarchical learning method in simulated experiments for the task of persuading people to do daily exercises. The results show that our hybrid hierarchical architecture outperforms a non-hierarchical benchmark in learning speed and robustness to both longitudinal user change and noisy observations. Our architecture is the first to: 1) persuasively adapt to different users during social HRI considering both static and dynamic user change, and 2) use user state decomposition in persuasive HRI.

CFD–DEM simulations of wet particles fluidization with a new evolution model for liquid bridge

AbstractA new model for liquid‐bridge evolution with consideration of particle dynamics, is proposed to improve Computational Fluid Dynamics‐Discrete Element Method (CFD–DEM) simulations of wet particles fluidization under high liquid loading and viscosity. A liquid bridge is allowed to form and remains stable only when the normal relative velocity of two particles is lower than a critical value vnc. A large vnc leads to an increase of liquid‐bridge or cohesive force. The model can be reduced to the conventional liquid‐bridge model in literature when vnc = 0 or ∞. With the new model, the prediction of bubble properties including bubble center, aspect ratio, and volume agrees well with the experimental data in literature. In particular, under high liquid loading, bubble disintegration due to particle agglomerating is reasonably captured. The simulations demonstrate the advantage of the new model that can extend the liquid‐bridge models and CFD–DEM for high liquid loading and viscosity.

Damping torque coefficient analysis of PMSG‐based WT with VSG control considering wind turbine dynamics

This paper expands the damping torque coefficient analysis (DTCA) for studying the small-signal stability of permanent magnet synchronous generator (PMSG)-based wind turbine (WT) under virtual synchronous generator (VSG) control with consideration of WT dynamics. Firstly, the typical VSG is implemented in the grid-side voltage source converter (GSVSC), which enables selfsynchronization without phase-locked loop (PLL). The maximum power point track (MPPT) algorithms are utilized to give the power reference for VSG. Then, the corresponding inertia and damping support can be provided by the kinetic energy of PMSG. Based on the established model, the DTCA is analytically conducted to not only reveal the key factors that influence the WT stability but also provide guidance for parameter tuning. As a result, it is important to find that the WT dynamics impair the damping and even lead to system instability. Moreover, the minimum value of VSG damping control parameter is analytically given to ensure the system stability under any load below the rated wind speed. Finally, the case studies considering one single PMSG connected to a large grid with and without inclusion of WT dynamics are performed and compared to demonstrate the accuracy of the proposed model and evaluate the applications of DTCA.