Dynamic Feedback Research Articles

Revolutionizing eLearning Assessments: The Role of GPT in Crafting Dynamic Content and Feedback

Revolutionizing eLearning Assessments: The Role of GPT in Crafting Dynamic Content and Feedback

Safety risk perception and control of water inrush during tunnel excavation in karst areas: An improved uncertain information fusion method

Water inrush disasters seriously endanger the construction safety of karst tunnels. To accurately assess the water inrush risk level of karst tunnels, actively prevent and control water inrush disasters. A risk evaluation method based on an improved cloud model (CM) and evidence reasoning (ER) combined with Monte Carlo simulation is proposed, which is applied in a water inrush risk evaluation of the Yaguan tunnel. The results are as follows. (1) This method considers the uncertainty and reliability of the water inrush risk information for karst tunnels. (2) Through an iterative evaluation with Monte Carlo simulation, the dynamic feedback mechanism of the risk state of the karst tunnel construction system is established. (3) Local sensitivity analysis is performed to identify risk factors and related measures are proposed. Hence, the research method can be used to effectively evaluate the water inrush risk level and provide references for similar project risk evaluations.

SiC MOSFET Active Gate Drive Circuit Based on Switching Transient Feedback

Due to the influence of parasitic internal parameters and junction capacitance, the silicon carbide (SiC) power devices are frequently marred by significant overshoots in current and voltage, as well as high-frequency oscillations during the switching process. These phenomena can severely compromise the reliability of SiC-based power electronic converters during operation. This study delves into the switching transient of the SiC MOSFET with the goal of establishing a quantitative correlation between the gate driving current and the overshoot in both the drain-source voltage and the drain current. In light of these findings, the innovative active gate drive (AGD) circuit, which features an adjustable gate current, is introduced. Throughout the switching process, the AGD circuit employs a dynamic monitoring and feedback mechanism that is responsive to the gate voltage and rate of change in the drain-source voltage and drain current of the SiC MOSFET. This adjustment enables gate driving current to be actively modified, thereby effectively mitigating the occurrence of overshoots and oscillations. To empirically validate the efficacy of the proposed AGD circuit in curbing voltage and current overshoots and oscillations, a double-pulse experimental setup was meticulously constructed and tested.

The Role of Cloud Radiative Effects in the Propagating Southern Annular Mode

AbstractThe Southern Annular Mode (SAM) is the most dominant natural mode of variability in the mid‐latitudes of the Southern Hemisphere (SH). However, both the sign and magnitude of the feedbacks from the diabatic processes, especially those associated with clouds, onto the SAM remain elusive. By applying the cloud locking technique to the Energy Exascale Earth System Model (E3SM) atmosphere model, this study isolates the positive feedback from the cloud radiative effect (CRE) to the SAM. Feedback analysis based on a wave activity‐zonal momentum interaction framework corroborates this weak but positive feedback. While the magnitude of the CRE feedback appears to be secondary compared to the feedbacks from the dry and other diabatic processes, the indirect CRE effects through the interaction with other dynamical and thermodynamical processes appear to play as important a role as the direct CRE in the life cycle of the SAM. The cross‐EOF analysis further reveals the obstructive effect of the interactive CRE on the propagation mode of the SH zonal wind directly through the CRE wave source and/or indirectly through modulating other diabatic processes. As a result, the propagation mode becomes more persistent and the SAM it represents becomes more predictable when the interactive CRE is disabled by cloud locking. Future efforts on inter‐model comparisons of CRE‐denial experiments are important to build consensus on the dynamical feedback of CRE.

Shannon entropy of transport self-organization due to dissolution–precipitation reaction at varying Peclet numbers in initially homogeneous porous media

Abstract. Dissolution and precipitation processes in reactive transport in porous media are ubiquitous in a multitude of contexts within the field of Earth sciences. In particular, the dynamic interaction between the reactive dissolution and precipitation processes and the solute transport is of interest as it is capable of giving rise to the emergence of preferential flow paths in the porous host matrix. It has been shown that the emergence of preferential flow paths can be considered to be a manifestation of transport self-organization in porous media as these create spatial gradients that distance the system from the state of perfect mixing and allow for a faster and more efficient fluid transport through the host matrix. To investigate the dynamic feedback between the transport and the reactive processes in the field and its influence on the emergence of transport self-organization, we consider a two-dimensional Darcy-scale formulation of a reactive-transport setup, where the precipitation and dissolution of the host matrix are driven by the injection of an acid compound, establishing local equilibrium with the resident fluid and an initially homogeneous porous matrix, composed of a calcite mineral. The coupled reactive process is simulated in a series of computational analyses employing the Lagrangian particle-tracking (LPT) approach, capable of capturing the subtleties of the multiple-scale heterogeneity phenomena. We employ the Shannon entropy to quantify the emergence of self-organization in the field, which we define as a relative reduction in entropy compared to its maximum value. Scalability of the parameters, which characterize the evolution of the reactive process, with the Peclet number in an initially homogeneous field is derived using a simple one-dimensional ADRE model with a linear adsorption reaction term and is then confirmed through numerical simulations, with the global reaction rate, the mean value, and the variance of the hydraulic-conductivity distribution in the field all exhibiting dependency on the reciprocal of the Peclet number. Our findings show that transport self-organization in an initially homogeneous field increases with time, along with the emergence of the field heterogeneity due to the interaction between the transport and reactive processes. By studying the influence of the Peclet number on the reactive process, we arrive at a conclusion that self-organization is more pronounced in diffusion-dominated flows, characterized by small Peclet values. The self-organization of the breakthrough curve exhibits the opposite tendencies, which are observed from the perspective of a thermodynamic analogy. The hydraulic power, required to maintain the driving head pressure difference between the inlet and outlet of the field, was shown to increase with the increasing variance, as well as with the increasing mean value of the hydraulic-conductivity distribution in the field, using a simple analytic model. This was confirmed by numerical experiments. This increase in power, supplied to the flow in the field, results in an increase in the level of transport self-organization. Employing a thermodynamic framework to investigate the dynamic reaction–transport interaction in porous media may prove to be beneficial whenever the need exists to establish relations between the intensification of the preferential flow path phenomenon, represented by a decline in the Shannon entropy of the transport, with the amount of reaction that occurred in the porous medium and the change in its heterogeneity.

How constant is constant elasticity of substitution? Endogenous substitution between clean and dirty energy

The degree of substitutability between clean and dirty energy plays a central role in leading economic analyses of optimal environmental policy. Despite the importance, assuming a constant and exogenous elasticity of substitution has been a dominant theoretical approach. We challenge this assumption by developing a dynamic general equilibrium model with an endogenous elasticity of substitution that interacts with the relative share of clean inputs in the economy. We find strong dynamic feedback effects arising from endogenous substitution capacity that amplifies the impact of directed technical change and accelerates the transition to a green economy.

Anti-control of Hopf bifurcation for a chaotic system

Abstract The anti-control of Hopf bifurcation is a method used for bifurcation control. It can be used to realize the occurrence or delay of bifurcation at the specified position to meet the needs of engineering applications. In this study, a 4D chaotic system is studied, and a dynamic state feedback control method is proposed to realize the anti-control of Hopf bifurcation for the system. By adjusting the control parameters of the controller, the system Hopf bifurcation can be generated or delayed at the specified position to realize the anti-control of Hopf bifurcation. This control method avoids complicated calculation processes and has remarkable control effects. Through numerical simulation analysis, the correctness of this control method is verified.

Adaptive potential of Russian economic growth in the context of decline in foreign direct investment

This study analyses the adaptive potential of Russia’s economic growth in the context of decline in foreign direct investment (hereinafter referred to as FDI). In light of today’s geopolitical environment, marked by increased trade tension and protectionist measures, understanding the impact of FDI on Russia’s gross domestic product (hereinafter referred to as GDP) becomes critical for policy-making and economic planning. The study employs a vector autoregression modeling approach (hereinafter referred to as VAR) to analyse the dynamics of Russia’s GDP and FDI inflows with consideration to various economic and geopolitical factors. Besides, an extensive dataset is used covering the period from 1996 to 2021 which includes relevant macroeconomic indicators and geopolitical events. The VAR model allows to study short- and long-term correlations between variables reflecting dynamic interaction and feedback effects. In addition, impulse response analysis is used to estimate the magnitude and sustainability of economic growth under conditions of economic instability. The results of the study contribute to understanding the adaptative potential of Russia’s economic growth in the context of FDI restrictions from Western countries. The analysis provides insight into the significance of FDI inflows for the Russian GDP with consideration to the impact of various economic and geopolitical factors.

Developing feedback literacy, scaffolded writing, and resilience through intervention on feedback processes for L2 writing students

Recent research on feedback processes posits that furthering students’ feedback literacy leads to scaffolded learning by effectively engaging them in seeking, understanding, and using feedback information. This study examined effects of a social-constructionist approach to feedback literacy on students’ development of feedback literacy, scaffolded learning, and resilience. Accordingly, we raised students’ awareness of feedback dynamics within the Zone of Proximal Development (ZPD), while engaged in collaborative writing with co-writers. A mixed-methods design was adopted comprising measures of feedback literacy, writing, and resilience before and after the intervention. Semi-structured interviews were also held to probe students’ post-intervention attitudes. Posttest scores and ratings showed significant improvement in the experimental group’s feedback literacy, writing proficiency, and resilience. Further, interviews revealed that feedback literate students developed positive perceptions of feedback processes arising from scaffolded writing and that their enhanced awareness brought them opportunities for engagement, collaboration, graduated scaffolding in the ZPD, and sustained motivation for writing.

Patient-centered perspectives on perioperative care

IntroductionThe collection and evaluation of patient-reported outcomes is essential to the development of patient and family centered care. Current patient surveying techniques are limited by delayed response times and restriction to specific health systems. The use of random-domain intercept technology (RDIT), by Real-Time Interactive World-Wide Intelligence (RIWI, Toronto, ON, Canada) mitigates current barriers by creating a dynamic real-time feedback environment and providing a mass sampling technique.MethodsRDIT was employed to survey a wide sample of respondents across the United States (US). Respondents who self-identified as having had a surgical procedure or cared for someone having a surgical procedure were included in the analysis.Results1,004 participants completed the survey and answered questions regarding demographics, perioperative details, sentiments on postoperative recovery, postoperative clinical endpoints, sentiments on healthcare professionals, and opinions on future surgical care.DiscussionThe results of this cross-sectional study identified areas with potential for improvement in the patient perioperative experience that could improve the patient experience. This novel use of RDIT provided a valuable tool for real-time feedback and mass sampling allowing the creation of a dynamic healthcare environment that fosters timely and targeted improvements to patient experiences and outcomes.

Analysis of multi-scale failure behavior of SiCf/SiC composite clad tube under flexible clamping damage

The intricate spatial fiber winding structure of SiCf/SiC ceramic matrix composite (CMC) cladding tubes makes it difficult to investigate in depth the inherent evolutionary mechanism of damage failure under specific operating conditions. Therefore, in this study, based on X-ray computed tomography (X-CT) reconstruction and cross scale numerical simulation methods, combined with clamping failure experiments under specific conditions for the cladding tubes, we conduct an in-depth analysis of the material's damage, failure, and mechanical behavior in different clamped regions. The research indicates that variations in the clamped regions have a minimal impact on the overall mechanical feedback of the material, and the maximum clamping load remains essentially around 500 N. The tube damage exhibits a unique " regional progressive damage evolution mechanism," where stress differentials of 108.49–115.33% appear between the inner and outer surfaces in different regions, leading to variations in the initiation and propagation of cracks within these areas. Furthermore, based on the minimum potential energy principle and semi-geodesic line theory, the intricate macroscopic tube structure formed by the spatial stacking and winding of SiCf/SiC cladding tube fibers is accurately reconstructed, which is combined with macroscale and microscale local feature models to capture the fibre/matrix morphology of the material with dynamic mechanical feedbacks, and experimentally validated in this work. The results indicate that the numerical model can effectively characterize the complex mechanical damage morphology and progressive failure lows of SiCf/SiC CMC at multiscale. Simultaneously, it is observed that stress concentrations in the fiber crossover region result in a load-bearing capacity 112–283% higher than in other areas. This phenomenon often leads to the first occurrence of failure in this region after clamping overload, exhibiting more pronounced damage characteristics.

A Scalable Deep Learning Framework for Dynamic CSI Feedback With Variable Antenna Port Numbers

A Scalable Deep Learning Framework for Dynamic CSI Feedback With Variable Antenna Port Numbers

Piezoelectric dual network dressing with adaptive electrical stimulation for diabetic infected wound repair via antibacterial, antioxidant, anti-inflammation, and angiogenesis

Electrical stimulation therapy plays a crucial role in the healing of wounds. However, electrical stimulation based on piezoelectric materials faces limitations in dynamically matching cell activity and lacks anti-infection properties, thereby restricting its broader clinical application. Herein, a piezoelectric dual network nanofiber dressing (CuEG/PVDF) was prepared using copper/ epigallocatechin 3-gallate (Cu2+/EGCG) and polyvinylidene fluoride (PVDF). This dressing constructs dynamic force-electrical closed-loop feedback signals through cell adhesion and adaptive electrical stimulation to accelerate the healing of infectious diabetic wounds. Benefiting for the Cu2+-EGCG metal polyphenol network, it enhances the electromechanical coupling properties, hydrophilicity, and cell adhesion of the piezoelectric double network dressing. Cell proliferation and migration were promoted by increased adhesion area, enhanced adaptive electrical stimulation, and active calcium influx. Moreover, CuEG/PVDF demonstrate significant antibacterial, antioxidant, anti-inflammatory, and angiogenic activities. In vivo experiments demonstrate that this dual-network piezoelectric dressing reduces the inflammatory response in rats, eliminates Methicillin-resistant Staphylococcus aureus (MRSA), and accelerates wound repair. Overall, this study presents a promising strategy for implementing electrical stimulation in the treatment of infected wounds.

Model-Free Adaptive State Feedback Control for a Class of Nonlinear Systems

This paper investigates state feedback control for a class of discrete-time multiple input and multiple output nonlinear systems from the perspective of model-free adaptive control and state observation. The design of a dynamic state feedback control can be efficiently carried out using dynamic linearization and state observation. The stability of the proposed method is guaranteed by theoretical analysis. Numerical simulation tests and experimentation on a continuous stirred tank reactor are carried out to validate the effectiveness of the proposed approach. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The growth in the scale of factories and the complexity of associated production processes increases the complexity and time involved in associated mathematical modelling. Data driven approaches to control remove the need to model processes. To the best of the authors’ knowledge, existing approaches to model-free adaptive control (MFAC) of general systems are all based on an input-output control paradigm. These methods thus cannot guarantee the stability of the system state. The purpose of this study is to develop a novel Model-Free Adaptive Control (MFAC) approach to achieve control of the system state. In this paper, the assumptions required to achieve model-free adaptive control by state feedback are presented mathematically. A controller design and the associated stability proof are then presented. Numerical simulation and experimentation is conducted to validate the effectiveness of the proposed approach. In future research, state feedback data control in the presence of random disturbances will be investigated.

Folic Acid Functionalized AQ4N/Gd@PDA Nanoplatform with Real-Time Monitoring of Hypoxia Relief and Enhanced Synergistic Chemo/Photothermal Therapy in Glioma.

Hypoxia is often associated with glioma chemoresistance, and alleviating hypoxia is also crucial for improving treatment efficacy. However, although there are already some methods that can improve efficacy by alleviating hypoxia, real-time monitoring that can truly achieve hypoxia relief and efficacy feedback still needs to be explored. AQ4N/Gd@PDA-FA nanoparticles (AGPF NPs) were synthesized using a one-pot method and were characterized. The effects of AGPF NPs on cell viability, cellular uptake, and apoptosis were investigated using the U87 cell line. Moreover, the effectiveness of AGPF NPs in alleviating hypoxia was explored in tumor-bearing mice through photoacoustic imaging. In addition, the diagnosis and treatment effect of AGPF NPs were evaluated by magnetic resonance imaging (MRI) and bioluminescent imaging (BLI) on orthotopic glioma mice respectively. In vitro experiments showed that AGPF NPs had good dispersion, stability, and controlled release. AGPF NPs were internalized by cells through endocytosis, and could significantly reduce the survival rate of U87 cells and increase apoptosis under irradiation. In addition, we monitored blood oxygen saturation at the tumor site in real-time through photoacoustic imaging (PAI), and the results showed that synergistic mild-photothermal therapy/chemotherapy effectively alleviated tumor hypoxia. Finally, in vivo anti-tumor experiments have shown that synergistic therapy can effectively alleviate hypoxia and inhibit the growth of orthotopic gliomas. This work not only provides an effective means for real-time monitoring of the dynamic feedback between tumor hypoxia relief and therapeutic efficacy, but also offers a potential approach for the clinical treatment of gliomas.

Research on Feedback and improvement Mechanism Innovation of Accounting Talent Training under the Background of New Business

The rapid evolution of the business environment, propelled by technological advancements and globalization, has necessitated a paradigm shift in accounting talent training. This study investigates the feedback and improvement mechanisms crucial for innovating accounting education to meet contemporary business demands. It underscores the importance of integrating real-time business scenarios, technological tools, and global accounting standards into the curriculum. The research adopts a mixed-methods approach, combining quantitative data from surveys of accounting professionals and qualitative insights from interviews with educators. The findings reveal significant gaps in current accounting education, including outdated curricula, insufficient exposure to cutting-edge technologies, and a lack of global perspective. The study proposes a dynamic feedback mechanism involving all stakeholders—students, educators, professionals, and industry bodies—to continually update the curriculum. Furthermore, it suggests incorporating experiential learning and digital tools to enhance practical skills. The conclusion posits that a responsive and innovative training mechanism can better prepare accounting graduates for the challenges of new business landscapes, thereby contributing to the profession's advancement and the broader economy.

Quantifying soil microbial effects on plant species coexistence: A conceptual synthesis.

Soil microorganisms play a critical role in shaping the biodiversity dynamics of plant communities. These microbial effects can arise through direct mediation of plant fitness by pathogens and mutualists, and over the past two decades, numerous studies have shined a spotlight on the role of dynamic feedbacks between plants and soil microorganisms as key determinants of plant species coexistence. Such feedbacks occur when plants modify the composition of the soil community, which in turn affects plant performance. Stimulated by a theoretical model developed in the 1990s, a bulk of the empirical evidence for microbial controls over plant coexistence comes from experiments that quantify plant growth in soil communities that were previously conditioned by conspecific or heterospecific plants. These studies have revealed that soil microbes can generate strong negative to positive frequency-dependent dynamics among plants. Even as soil microbes have become recognized as a key player in determining plant coexistence outcomes, the past few years have seen a renewed interest in expanding the conceptual foundations of this field. New results include re-interpretations of key metrics from classic two-species models, extensions of plant-soil feedback theory to multispecies communities, and frameworks to integrate plant-soil feedbacks with processes like intra- and interspecific competition. Here, I review the implications of theoretical developments for interpreting existing empirical results and highlight proposed analyses and designs for future experiments that can enable a more complete understanding of microbial regulation of plant community dynamics.

Design and implementation of the Beijing Road Traffic Environmental Monitoring Information Platform: A stakeholder’s perspective

The process of urbanization continues to accelerate, placing an increasing burden on the urban environment through the transportation sector. To address this challenge, the Beijing Municipal Transportation Bureau has introduced the Traffic Transport Environment Monitoring Information Platform, which aims to strengthen the monitoring and management of the transportation environment by facilitating flexible management and control of the transportation planning and implementation process through timely diagnostics and dynamic feedback. It represents a technologically innovative measure designed toward establishing and improving the dynamic predictive power of transport planning and monitoring in Beijing. This study thoroughly examines the design and implementation of the platform, providing detailed insights into its overall framework, data collection, and processing mechanisms, as well as strategies for data sharing and utilization. Through an analysis grounded in stakeholder theory, the study demonstrates the effectiveness and practicability of the platform. By prioritizing stakeholder demands, the study not only contributes to transportation planning technology theory but also holds pioneering significance for the practical implementation of transport environment monitoring information platforms in cities across China.

Dynamical Constraint on Precipitation Biases Over the Indo‐Pacific Region During Boreal Summer in AMIP6 Models

AbstractClimate models suffer from longstanding precipitation biases, much of which has been attributed to their atmospheric component owing to unrealistic parameterizations. Here we investigate precipitation biases in 37 Atmospheric Model Intercomparison Project Phase 6 (AMIP6) models, focusing on the Indo‐Pacific region during boreal summer. These models remain plagued by considerable precipitation biases, especially over regions of strong precipitation. In particular, 22 models overestimate the Asian‐Pacific monsoon precipitation, while 28 models underestimate the southern Indian Ocean Intertropical Convergence Zone precipitation. The inter‐model spread in summer precipitation is decomposed into Empirical Orthogonal Functions (EOFs). The leading EOF mode features an anomalous anticyclone circulation spanning the Indo‐northwest Pacific oceans, which we show is energized by barotropic conversion from the confluence of the background monsoonal westerlies and trade‐wind easterlies. Our results suggest precipitation biases in atmospheric models, though caused by unrealistic parameterizations, are organized by dynamical feedbacks of the mean flow.

Artificial intelligence powered glucose monitoring and controlling system: Pumping module.

Diabetes, a globally escalating health concern, necessitates innovative solutions for efficient detection and management. Blood glucose control is an essential aspect of managing diabetes and finding the most effective ways to control it. The latest findings suggest that a basal insulin administration rate and a single, high-concentration injection before a meal may not be sufficient to maintain healthy blood glucose levels. While the basal insulin rate treatment can stabilize blood glucose levels over the long term, it may not be enough to bring the levels below the post-meal limit after 60 min. The short-term impacts of meals can be greatly reduced by high-concentration injections, which can help stabilize blood glucose levels. Unfortunately, they cannot provide long-term stability to satisfy the post-meal or pre-meal restrictions. However, proportional-integral-derivative (PID) control with basal dose maintains the blood glucose levels within the range for a longer period. To develop a closed-loop electronic system to pump required insulin into the patient's body automatically in synchronization with glucose sensor readings. The proposed system integrates a glucose sensor, decision unit, and pumping module to specifically address the pumping of insulin and enhance system effectiveness. Serving as the intelligence hub, the decision unit analyzes data from the glucose sensor to determine the optimal insulin dosage, guided by a pre-existing glucose and insulin level table. The artificial intelligence detection block processes this information, providing decision instructions to the pumping module. Equipped with communication antennas, the glucose sensor and micropump operate in a feedback loop, creating a closed-loop system that eliminates the need for manual intervention. The incorporation of a PID controller to assess and regulate blood glucose and insulin levels in individuals with diabetes introduces a sophisticated and dynamic element to diabetes management. The simulation not only allows visualization of how the body responds to different inputs but also offers a valuable tool for predicting and testing the effects of various interventions over time. The PID controller's role in adjusting insulin dosage based on the discrepancy between desired setpoints and actual measurements showcases a proactive strategy for maintaining blood glucose levels within a healthy range. This dynamic feedback loop not only delays the onset of steady-state conditions but also effectively counteracts post-meal spikes in blood glucose. The WiFi-controlled voltage controller and the PID controller simulation collectively underscore the ongoing efforts to enhance efficiency, safety, and personalized care within the realm of diabetes management. These technological advancements not only contribute to the optimization of insulin delivery systems but also have the potential to reshape our understanding of glucose and insulin dynamics, fostering a new era of precision medicine in the treatment of diabetes.