System Dynamics Research Articles

From challenges to opportunities: navigating the human response to automated agents in the workplace

Workers are increasingly embracing Artificial Intelligence (AI) to optimise various aspects of their operations in the workplace. While AI offers new opportunities, it also presents unintended challenges that they must carefully navigate. This paper aims to develop a deeper understanding of workers’ experiences with interactions with automated agents (AA) in the workplace and provide actionable recommendations for organisational leaders to achieve positive outcomes. We propose and test a simulation model that quantifies and predicts workers’ experiences with AA, shedding light on the interplay of diverse variables, such as workload, effort and trust. Our findings suggest that lower-efficiency AA might outperform higher-efficiency ones due to the constraining influence of trust on adoption rates. Additionally, we find that lower initial trust in AA could lead to increased usage in certain scenarios and that stronger emotional and social responses to the use of AA may foster greater trust but result in decreased AA utilisation. This interdisciplinary research blends a systems dynamics approach with management theories and psychological concepts, aiming to bridge existing gaps and foster the sustainable and effective implementation of AA in the workplace. Ultimately, our research endeavour contributes to advancing the field of human-AI interaction in the workplace.

Factors That Facilitated the Development of Blockchain Technology in the AEC Industry: Study Based on System Dynamics

Factors That Facilitated the Development of Blockchain Technology in the AEC Industry: Study Based on System Dynamics

Slow-fast dynamics in non-linear enzyme cascades gives rise to spatial multiscaling.

Slow-fast dynamics in a well-mixed biological system is known to be associated with functional modularity with temporal hierarchy of processes. Yet, the significance of slow-fast dynamics in spatially distributed reaction-diffusion systems remains to be clarified.We assessed such systems with slow-fast dynamics, such as blood coagulation and predator-prey models to identify spatial patterns with independent parametric regulation, and performed their reaction-rate based sensitivity analysis with the help of computational one-dimensional reaction-diffusion models.In blood coagulation, spatial distribution of fibrin had two scales: a larger region with a high and almost constant fibrin concentration (corresponding to solid blood clot) and a narrow transition zone, where fibrin concentration decayed to zero (semi-liquid clot). Slow variables (e.g., the concentration of the coagulation factor IXa) regulated the clot size (large scale), while fast variables (e.g., concentrations of thrombin and factor Xa) regulated the thickness of the gel-to-liquid transition zone (small scale). Analysis of the simplified model of blood coagulation, composed only of factor X and IX activation, and of the predator-prey model confirmed this finding to be sufficiently general, and revealed that the limitation of fast enzyme production (due to precursor depletion or to kinetics with saturation) was crucial for this multi-scaling. Independent regulation of spatial scales also required species with slow kinetics to be upstream from species with fast kinetics.The shared slow-fast dynamics of the examined systems endow them with the ability to form spatial patterns, representing a new mechanism complementing the Turing-type and the Positional Information type pattern formation.

On Zero Dynamics and Controllable Cyber-Attacks in Cyber-Physical Systems and Dynamic Coding Schemes as Their Countermeasures

On Zero Dynamics and Controllable Cyber-Attacks in Cyber-Physical Systems and Dynamic Coding Schemes as Their Countermeasures

Medium Amplitude Field Susceptometry (MAFS) for magnetic nanoparticles

The linear dynamic susceptibility is arguably the most important property to specify the magnetization dynamics of a given system. Therefore, this quantity has been studied in great detail and the corresponding measurements known as susceptometry are well-established. Notwithstanding its relevance, the linear susceptibility is inherently limited to describe the magnetization response to weak external fields only. Here, we suggest the framework of Medium Amplitude Field Susceptometry (MAFS) to study the non-linear response which complements the linear susceptibility and provides additional information on the magnetic properties of the system and is applicable to magnetic fields of medium amplitudes. In particular, we introduce the general third-order nonlinear susceptibility χˆ3 as a central quantity that completely specifies the lowest-order non-linear response to arbitrary time-dependent magnetic fields. We show that response functions in medium amplitude oscillatory magnetic fields and parallel superposition susceptometry are contained in χˆ3 as special cases. Also included in χˆ3 are interesting intermodulation effects when the system is probed by a superposition of oscillating magnetic fields with different frequencies. We work out the explicit form of χˆ3 for several model systems for the dynamics of magnetic nanoparticles (MNPs). We expect this unifying framework to be not only of theoretical interest, but also useful for a deeper characterization of MNP systems, giving additional information on their suitability for various applications.

On the dynamics of a financial system with the effect financial information

This study aims to investigate a financial system consisting of four ordinary differential equations associated with the rate of interest, investment demand, price index, and the density of financial information gained by the population. The equilibrium and local stability of the system are investigated numerically. The impact of saving amounts and the rate of investment demand increases after getting financial information on the system are discussed. The findings of the study are verified graphically. It is found that the system becomes stable if the rate of investment demand increases after getting financial information kept at a certain level, such that the savings amount is maintained at a higher level. Also, the bifurcation diagrams of the system for various significant parameters that affect the system’s stability have been depicted.

Impaired Incretin Homeostasis in Nondiabetic Moderate-to-Severe CKD.

Key Points Total incretin levels and incretin response during oral glucose tolerance testing were significantly higher among patients with moderate-to-severe nondiabetic patients with CKD compared with healthy people.Unlike in healthy individuals, increased incretin response was not correlated with insulin response and coincided with persistently greater glucagon levels to oral glucose tolerance testing in CKD.Disruption in the incretin system and glucagon dynamics may contribute to metabolic complications in moderate-to-severe CKD. Background Incretins are regulators of insulin secretion and glucose homeostasis metabolized by dipeptidyl peptidase-4 (DPP-4). CKD may modify incretin release, metabolism, or response. Methods We performed 2-hour oral glucose tolerance testing in 59 people with nondiabetic CKD (eGFR <60 ml/min per 1.73 m2) and 39 matched controls. We measured total area under the curve and incremental area under the curve (iAUC) of plasma total glucagon-like peptide-1 (GLP-1) and total glucose-dependent insulinotropic polypeptide (GIP). Fasting DPP-4 levels and activity were measured. Linear regression was used to adjust for demographic, body composition, and lifestyle factors. Results Mean (SD) eGFR was 38±13 and 89±17 ml/min per 1.73 m2 in patients with CKD and controls, respectively. GLP-1 total area under the curve and GIP iAUC were higher in patients with CKD than controls with a mean of 1531±1452 versus 1364±1484 pM×min and 62,370±33,453 versus 42,365±25,061 pg×min/ml, respectively. After adjustment, CKD was associated with 15,271 pM×min/ml greater GIP iAUC (95% confidence intervals [CIs], 387 to 30,154) compared with controls. Adjustment for covariates attenuated associations of CKD with higher GLP-1 iAUC (adjusted difference, 122; 95% CI, −619 to 864). Plasma glucagon levels were higher at 30 minutes (mean difference, 1.6; 95% CI, 0.3 to 2.8 mg/dl) and 120 minutes (mean difference, 0.84; 95% CI, 0.2 to 1.5 mg/dl) in patients with CKD compared with controls. There were no differences in insulin levels or plasma DPP-4 activity or levels between groups. Conclusions Overall, incretin response to oral glucose is preserved or augmented in moderate-to-severe CKD, without apparent differences in circulating DPP-4 concentration or activity. However, neither insulin secretion nor glucagon suppression is enhanced.

Design Formulation of Nanospanlastic Novel Carriers as a Promising Approach to Enhanced Bioavailability in Intranasal Drug Delivery for Sinusitis: Statistical Optimization and In vitro and In vivo Characterization

Background: Most new biologically active chemicals require better water solubility and slower dissolution rates. Cefdinir (CFD) has a very low bioavailability in its crystalline form and is poorly soluble in water. Objective: By preparing cefdinir's spanlastic nanovesicles (SNVs) using the ethanol injection method, the current study has attempted to enhance the drug's solubility and bioavailability using a statistical design approach. Methods: Independent variables, including the nonionic surfactant concentration, edge activator (EA), sonication time, SNVs entrapment efficiency, particle size, zeta potential, PDI, and in vitro release, have been evaluated. The best CFD-SNVs were positioned within in situ gel with muco-adhesive properties made of hydroxypropyl methylcellulose and deacetylated gellan gum. By contrasting intranasal injection of the produced gel with an IV solution, animal models have been used to investigate CFD's systemic and cerebral dynamics. Results: Statistical analysis has suggested an ideal SNVs formulation with nonionic surfactant (65 mg), EA (15 mg), and sonication (3 min). The sol-gel temperature for forming the mucoad-hesive in situ gel containing SNVs has been found to be 34.03°C, and 18.36 minutes has been the extended mucociliary transit time. Following intranasal injection, compared to SNV dispersion, the gelling system has exhibited higher brain bioavailability (2251.9 ± 75 vs. 5281.6 ± 51%, re-spectively). The gel has also demonstrated effective drug targeting of the brain with higher direct transport percentage indices. Conclusion: Mucoadhesive in situ gel with CFD-loaded SNVs can be administered via the in-tranasal route. To enhance bioavailability in the brain and drug targeting from the nose to the brain, nasal in situ gel loaded with CFD-SNVs could be a new carrier to be employed in sinusitis.

Nonlinear second order plus time delay model identification and nonlinear PID controller tuning based on extended linearization method

PID control systems based on the first order plus time delay model (FOPTD), which approximate the full system dynamics, are well-accepted for a wide range of linear processes. While such controllers can be applied to overdamped nonlinear processes, they often experience excessive overshoots and oscillations for general nonlinear processes. To overcome this limitation, we propose a novel method to design a nonlinear PID controller based on the second order plus time delay (SOPTD) model. The system nonlinearity requires parameter adjustments of the linearized model across operational ranges. Hence, in this work, it is handled by the extended linearization method (ELM), ensuring local stability under the assumptions of slow and small changes in operating points. Importantly, the model achieves global input-to-output stability even without the above constraints, provided there are no structural and parametric errors. The resulting nonlinear SOPTD model can describe changes in process gain and two time constants as the operation point varies. We demonstrate the applicability of our approach with a polymerization reactor simulation and liquid-level control experiments.

Dynamic mode decomposition of GRACE satellite data

Advancements in satellite technology yield environmental data with ever improving spatial coverage and temporal resolution. This necessitates the development of techniques to discern actionable information from large amounts of such data. We explore the potential of dynamic mode decomposition (DMD) to discover the dynamics of spatially correlated structures present in global-scale data, specifically in observations of total water storage anomalies provided by GRACE satellite missions. Our results demonstrate that DMD enables data compression and extrapolation from a reduced set of dominant spatiotemporal structures. The accuracy of its predictions of global system dynamics is preserved in its reconstruction of local time series. These findings suggest potential uses of DMD in analysis of remote-sensing data for hydrologic applications.

Unveiling the Dynamic Mechanisms of Generative AI in English Language Learning: A Hybrid Study Based on fsQCA and System Dynamics

Unveiling the Dynamic Mechanisms of Generative AI in English Language Learning: A Hybrid Study Based on fsQCA and System Dynamics

The Impact of White Noise on Chaotic Behavior in a Financial Fractional System with Constant and VariableOrder: A Comparative Study

In this study, we investigated the impact of white noise on the chaotic dynamics of a financial system with Caputo fractional derivatives of constant- and variable-order. We solve thesefractional financial systems numerically. We analyze the chaotic behavior of these fractional-order hyperchaotic systems through simulations, study the effects of white noise on chaotic dynamics, and provide a comparison between fractional hyperchaotic systems of constant and variable orders. The study reveals that white noise can either amplify or suppress chaos, with significant differences observed between the constant- and variable-order cases. We obtained numerous intriguing graphical findings for the model by evaluating various scenarios. The findings provide useful information for better understanding financial market dynamics in the presence of noise.

Notes from the field: Practical considerations for agent‐based and continuous representations of system dynamics

Notes from the field: Practical considerations for agent‐based and continuous representations of system dynamics

Application of Reservoir Computers for Chaos Synchronization and Cracking Chaos-Based Cryptography in Fermionic 2D Thirring and 4D Gursey Models with Spinor Fields

Reservoir computers have recently become one of the most widely exploited model-free approaches to chaos synchronization due to their fast convergence speed and simple yet effective learning rules. In this study, reservoir computing has been utilized to emulate the dynamics of chaotic Thirring and Gursey systems. In the supervised learning of the reservoir, one-step ahead states of the dynamical systems have been employed as the teaching signals. After the training phase, the reservoir was first run autonomously and then weakly driven by chaotic systems. It has been shown that the trained reservoir computers can exhibit the same characteristics as the attractors of the learned chaotic systems, which enable their use in synchronization tasks of chaotic systems with possible application in cracking chaos-based cryptography. To investigate the effect of noise on the performance of reservoir computers, noise signals with different colors and amplitudes have been included in the transmitted signals. The obtained results indicate that the proposed scheme can provide lower error metrics for both models.

The concept of creating a maneuverable power plant based on a small modular reactor

Purpose. To develop a maneuverable power plant (MPP) based on the NuScale small modular reactor (SMR) by selecting a thermal scheme structure for a steam turbine installation using minimal additional equipment and ensuring its operation in both nominal and peak modes with maximum efficiency. This also includes ensuring its maneuverability through the use of hydrogen technologies for generating, storing, and returning energy to the steam turbine cycle. Methodology. The study employed the method of mathematical modeling of thermodynamic cycles of thermal schemes of steam turbine installations (STI) with concentrated parameters, which makes it possible to describe the dynamics of systems consisting of discrete elements that are thermodynamic systems. Findings. Various structural options for the thermal scheme of the MPP based on the NuScale SMR for nominal operation were developed and mathematically modeled, followed by a comparative analysis of their energy efficiency. As a result, a scheme and operational parameters were selected with the highest electrical efficiency (net), which allows increasing the net efficiency of the NuScale SMR-based power plant from the developers’ announced 28 to 32.8 %. A thermal scheme for the MPP based on the SMR with an energy storage system was proposed. Applying this scheme allows increasing the net efficiency of a power plant based on NuScale SMR in peak mode to 34.8 %. Originality. A concept for creation and schematic solution for a prospective MPP based on an SMR capable of accumulating electrical energy was proposed. The main innovative solution regarding the structure of the technological scheme of the MPP based on the SMR is the organization of its operation in nominal and peak modes, which fundamentally differ in the thermodynamic cycle. In the nominal mode, the steam turbine installation operates on a thermodynamic cycle with steam separation, and in the peak mode without it, by increasing the temperature of fresh steam as a result of burning hydrogen and oxygen. Hydrogen and oxygen are produced in an electrolyzer during the power plant’s operation in the nominal mode by using the generated electricity “excess”. Practical value. Small modular reactors are currently mainly in the development stage. Additionally, the non-nuclear part of the SMR-based power plant, namely the STI, has not received sufficient attention, as evidenced by the literature. However, it plays a crucial role in the overall efficiency of the installation. The study focuses on the highly relevant issue of improving the efficiency of an SMR-based power plant by developing the structure of the STI thermal scheme involving hydrogen technologies. This will help reduce dependence on fossil hydrocarbons in the total volume of primary fuel and enable sustainable functioning of the Ukrainian energy system, as well as contribute to the preservation and improvement of the environmental state.

Sustainability assessment with the green retrofitting concept for building: A study case in the Gresik regency, Indonesia

In green construction, sustainable resources are essential. One such material is copper, which is widely utilized in electronics, transportation, manufacturing, and residential buildings. As a very useful material, it has many beneficial impacts on human life. Observed from the recent demand spike is in line with the overall trend and the current growing smelter construction in Indonesia. Researchers intend to adapt the existing Copper Smelting Plant Building into an environmentally friendly building as a part of the production chain, in addition to reducing public and environmental concerns about the consequences of this development. We have identified a disparity in cost, where the high cost of green buildings is an obstacle to its implementation to enhance the cost performance with increased renewable energy of the Smelter Construction Building, this study investigates the application of LEED parameters to evaluate green retrofit approaches through system dynamics. The most relevant features of the participant assessments were identified using the SEM-PLS approach, which is used to build and test statistical models of causal models. We have results for this Green Retrofitting study following significant variables according to the following guidelines: innovation, low-emission materials, renewable energy, daylighting, reducing indoor water usage, rainwater management, and access to quality transit.

Microbial distribution in Mudbank regions off Alappuzha, South-West coast of India.

The coastal waters of Kerala, in the South Eastern Arabian Sea (SEAS), are unique during the Southwest monsoon season due to the concurrent occurrence of two physical processes, the upwelling and Mudbanks. However, little is known about the viral ecology and activity in a system where upwelling and Mudbanks coexist, though it is generally recognized that microbial assemblages play a vital role in the food web dynamics of marine systems, particularly in upwelling. Water samples were taken from monsoon and pre-monsoon period from three locations, (M1, M2, and M3) off Alappuzha, on the southwest coast of India to examine the viral activity and distribution. The dissolved oxygen levels showed the incursion of hypoxic waters in all the stations during the peak upwelling period. Upwelling signals were prominent in all the stations, but Mudbank and upwelling co-occurred at M2 alone during monsoon. The abundance of viruses ranged from 0.86 to 15.68 × 106 Viral-like Particles (VLPs mL-1) and prokaryotic abundance ranged from 2.73-16.26 × 105 cells mL-1. Viral and prokaryotic abundance was significantly higher in the monsoon compared to pre and late-monsoon. Based on Transmission electron microscopy (TEM) results, the non-tailed viruses constituted the major (43%) proportion of the total viruses in this study region. However, the viral production rates and viral-mediated bacterial mortality were high in the pre-monsoon compared to the monsoon and late-monsoon periods. There was no obvious effect of Mudbanks on viral dynamics and the observed variations in virological and hydrological features were governed mainly by coastal upwelling.

An Integrated Review of Pluto-Charon Binary Syatem

The Pluto-Charon binary system is a significant celestial configuration in the Kuiper belt, it is the first Kuiper-belt binary to be discovered. The study of the Pluto-Charon binary system is helpful for the understanding of planetary formation and evolution and Kuipe-belt objects. The surface feature of the binary and the evolution of the system related to the Sun or its satellites and rings have been hot in research on the Pluto-Charon system. For example, most study hold a view that the Pluto-Charon binary was formed by a giant impact. However, the internal structure and formation remain partly unexplored. This review paper compiles literature on the physical properties, formation, and basic dynamics of the Pluto-Charon system. Observational data from the New Horizons mission has advanced the understanding of the system, the review overviewed the characteristics of the Pluto-Charon binary system from the observation and analysis in the current research, such as the surface material of the two bodies. The paper also added a basic introduction to the binary system.

Research Framework of Regional Economic-Ecological System Vulnerability Evolution and Adaptive Leap under the Background of Climate Change

This study focuses on the vulnerability evolution mechanism of regional economic-ecological systems and its adaptive leapfrogging path under the background of climate change. Based on the theory of complex adaptive systems and the framework of social-ecological system coupling, a regional economic-ecological system vulnerability assessment index system was constructed. Using the system dynamics model and scenario simulation method, the impact transmission mechanism of climate change on regional economic-ecological systems was analyzed, and the spatiotemporal evolution law of system vulnerability was revealed. The study found that climate change has aggravated the vulnerability of regional economic-ecological systems by changing resource endowments, disturbing industrial structure, and affecting ecological service functions. In response to this problem, this study proposed a leapfrogging path based on adaptive management: including building a climate-resilient industrial system, optimizing resource allocation efficiency, enhancing ecosystem service functions, and improving regional adaptive governance mechanisms. The research results have important theoretical value and practical significance for promoting regional sustainable development and ecological civilization construction.

Speed control and maximum efficiency operation of three‐phase squirrel cage induction motors supplied by modified Γ−Z$\Gamma - Z$ impedance source inverter

AbstractA three‐phase squirrel cage induction motor (IM) drive system supplied by a new modified structure of impedance source inverter ( ISI) is proposed. The two main goals are speed (torque) control, and efficiency improvement. The modified ISI has the ability to boost the input voltage. This improves the operation range of the system particularly for limited DC‐link voltage conditions. A first order integral‐terminal sliding mode (ITSM) controller is designed incorporating the motor and inverter dynamic model equations. The maximum efficiency strategy based on Lagrange's theorem is achieved by optimizing the motor input power (input energy) as the objective function under the constant load torque. The maximum efficiency strategy using energy saving is suitable for electric drive system applications. Also, the control method is resilient to any change in motor parameters and unmodulated system dynamics. Furthermore, its output control error can be eliminated in a limited interval. Finally, a prototype of the system using a 1.5 kW three‐phase squirrel cage IM is provided and several tests are conducted. The experimental results show the efficacy of the proposed method.