Support Capability Research Articles

Abstract 4134824: Evaluation of ChatGPT-4.0 and Google Bard ‘s Capabilities in Clinical Decision Support in Cardiac Electrophysiology

Background: ChatGPT-4.0 and Bard have shown clinical decision support (CDS) potential in general medicine, but their role in EP is unknown. This study aims to evaluate ChatGPT and Bard’s CDS potential by assessing their accuracy in multiple-choice questions (MCQs), guideline recommendations (GRs) and treatment (Tx) suggestions. Methods: Two chatbots were tested with 15 clinical vignettes (CVs) and 47 case-related MCQs from Heart Rhythm Case Reports, focusing on ablation, arrhythmia and CIEDs management. CVs included narrative diagnostic images results. 3 tasks were performed: 1) Generating GRs, rated 0 for incorrect or correct but irrelevant to the primary problem, 0.5 for correct for the primary problem, 1 for case-specific (CS) if relevant to both the primary problem and concomitant conditions (e.g. afib with HF); 2) Suggesting Tx steps, scored 0 for incorrect, 0.5 for correct and 1 for CS. Tx was deemed correct if referenced in the case or guidelines, and CS if used in the case. For Tx responses not CS, a prompt was provided before reassessment. The prompt included one similar CV and its Tx from PubMed case reports. 3) Answering MCQs, rated 1 for correct and 0 for incorrect. Welch's T-test was used for analysis. Results: Bard outperformed ChatGPT in generating CS-GRs (P = 0.01). However, there was no significant difference in CS-Tx suggestions with a prompt (P value = 0.12, Figure 1C) or without a prompt (P value = 0.59, Figure 1A). When prompted for non-CS-Tx responses, ChatGPT significantly improved from 0.66 to 0.93 (P value = 0.02), suggesting an enhanced ability to provide CS-Tx plans post-prompt. In contrast, Bard showed no notable improvement (0.73 vs. 0.76, P value = 0.79, Figure 1B). Both chatbots demonstrated similar MCQ accuracy, with scores below 70%, indicating EP training gaps or the need for prompts to activate existing knowledge. Conclusion: This study showed Bard's superiority in generating GRs and ChatGPT's remarkable improvement in suggesting Tx when external knowledge is provided, revealing their CDS potential in specialized fields.

Variable droop gain frequency supporting control with maximum rotor kinetic energy utilization for wind-storage system

To address the emerging frequency stability issue brought by the large replacement of synchronous generators with renewable generations, wind turbine generators are required to possess frequency-supporting capability. However, existing frequency-supporting control strategies lack the assessment of the frequency support capability of wind turbine generators, leading to degraded control performance under various situations. Aiming to solve this problem, this paper proposes a variable-droop-gain control for wind turbine generators with maximum rotor kinetic energy utilization. Firstly, an analytical relationship was established between droop gain, disturbance scale, and rotor speed. Subsequently, the released energy of the wind turbine generator is evaluated, which equals the difference in the rotor kinetic energy under the initial and the post-disturbance steady-state rotor speed. It was proved that the released kinetic energy cannot exceed a certain proportion of total rotor kinetic energy. Accordingly, a variable initial gain scheme is proposed, which determines the initial droop gain as per the disturbance scale for maximizing the kinetic energy release of wind turbines. Moreover, an additional real-time droop gain adjustment rule is added to prevent the over-deceleration of wind turbines. The simulation results show that the proposed scheme may provide the maximum KE release and effectively improve the system frequency nadir while ensuring the safe operation of wind turbine generators.

Exploring the impact of social capital on business performance: The role of dynamic capabilities, open innovation and government support

This study examines the relationships between social capital (encompassing structural, cognitive, and relational dimensions), dynamic capabilities, open innovation (both inbound and outbound), government support, and business performance in Vietnam. Using a quantitative approach, data were collected from 289 respondents and analyzed using Partial Least Squares Structural Equation Modeling. The findings show that social capital positively influences both dynamic capabilities and open innovation. While dynamic capabilities have a significant impact on business performance, open innovation enhances government support but does not directly affect business performance. Additionally, dynamic capabilities mediate the relationship between social capital and business performance, and government support partially mediates the relationship between open innovation and business performance. These results underscore the importance of government support and dynamic capabilities in leveraging social capital for enhanced business performance, while also highlighting the need for further investigation into the direct impacts of open innovation on performance.

The study of active support for energy storage system in system frequency regulation

Abstract As the penetration of new energy sources increases, the proportion of traditional energy units continues to decline, reducing the inertia and primary frequency regulation capability of the power system. Therefore, exploring the frequency support capabilities of energy storage systems with low inertia is crucial. Based on this, this paper first proposes an active frequency support method for energy storage system based on a Voltage Source Virtual Synchronous Generator (VSG), aiming to enhance system inertia and reduce response delay. Based on this issue, a parameter tuning optimization selection model based on the Transient Search Optimization (TSO) algorithm is proposed to determine the optimal power output and best frequency regulation parameters for the energy storage system. Finally, the model proposed in this paper is applied to the IEEE 14-bus system to verify its effectiveness.

The Parameterized Oceanic Front-Guided PIX2PIX Model: A Limited Data-Driven Approach to Oceanic Front Sound Speed Reconstruction

In response to the demand for high-precision acoustic support under the condition of limited data, this study utilized high-resolution reanalysis data and in situ observation data to extract the Kuroshio Extension Front (KEF) section through front-line identification methods. By combining the parameterized oceanic front model and the statistical features of big data, the parameterized oceanic front was reconstructed. A proxy dataset was generated using the Latin hypercube sampling method, and the sound speed reconstruction model based on the PIX2PIX model was trained and validated using single sound speed profiles at different positions of the oceanic front, combined with the parameterized oceanic front model. The experimental results show that the proposed sound speed reconstruction model can significantly improve the reconstruction accuracy by introducing the parameterized front model as an additional input, especially in the shallow-water area. The mean absolute error (MAE) of the full-depth sound speed reconstruction for this model is 0.63~0.95 m·s−1, and the structural similarity index (SSIM) is 0.76~0.78. The MAE of the sound speed section within a 1000 m depth is reduced by 6.50~37.62%, reaching 1.95~3.31 m·s−1. In addition, the acoustic support capabilities and generalization of the model were verified through ray tracing models and in situ data. This study contributes to advancing high-precision acoustic support in data-limited oceanic environments, laying a solid groundwork for future innovations in marine acoustics.

Optimal Configuration Model for Large Capacity Synchronous Condenser Considering Transient Voltage Stability in Multiple UHV DC Receiving End Grids

In a multi-fed DC environment, the UHV DC recipient grid faces significant challenges related to DC phase shift failure and voltage instability due to the high AC/DC coupling strength and low system inertia level. While the new large-capacity synchronous condensers (SCs) can provide effective transient reactive power support, the associated investment and operation costs are high. Therefore, it is valuable to investigate the optimization of SC configuration at key nodes in the recipient grid in a scientific and rational manner. This study begins by qualitatively and quantitatively analyzing the dynamic characteristics of DC reactive power and induction motors under AC faults. The sub-transient and transient reactive power output model is established to describe the SC output characteristics, elucidating the coupling relationship between the SC’s reactive power output and the DC reactive power demand at different time scales. Subsequently, a critical stabilized voltage index for dynamic loads is defined, and the SC’s reactive power compensation target is quantitatively calculated across different time scales, revealing the impact of transient changes in DC reactive power on the transient voltage stability of the multi-fed DC environment with dynamic load integration. Finally, an optimal configuration model for the large-capacity SC is proposed under the critical stability constraint of dynamic loads to maximize the SC’s reactive power support capability at the lowest economic cost. The proposed model is validated in a multi-fed DC area, demonstrating that the optimal configuration scheme effectively addresses issues related to DC phase shift failures and voltage instability resulting from AC bus voltage drops.

팀티칭 보육교사의 교육과정운영 자율성과 동료교사의 사회적지지가 놀이지원역량에 미치는 영향

Objectives The purpose of this study is to examine the effect of team teaching childcare teachers' curriculum operation autonomy and fellow teachers' social support on play support competency. Methods To this end, a survey was conducted among 307 childcare teachers currently operating team-teaching classes at childcare centers in the Busan and Gyeongnam regions. The collected data were analyzed using SPSS 24.0, employing descriptive statistics, correlation analysis, and multiple regression analysis. Results First, team teaching childcare teachers' curriculum management autonomy averaged 4.09 on a 5-point scale, the social support from fellow teachers averaged 4.02, and the ability to support play averaged 4.16. Second, it was found that there are significant correlations between team teaching childcare teachers' curriculum operation autonomy, fellow teachers' social support, overall play support competency, and all its sub-factors. Third, the curriculum operation autonomy of team teaching childcare teachers and fellow teachers' social support explained 49.1% of cognitive competency, 44.1% of affective competency, and 57.7% of practical competency, which are sub-factors of play support competency. Common factors affecting these sub-factors included a child-centered play environment and interactions, collaboration and participation with families and the community, flexible daily routines, and evaluative support, with evaluative support being the most explanatory. Conclusions The meaningful play environment and interactions, along with reflective self-assessment by educators and recognition and praise from peers, indicate the potential for enhancing the play support capabilities of childcare teachers. Therefore, efforts to analyze and support the team-teaching environment of childcare teachers implementing revised educational curricula are necessary to enhance their play support capabilities.

Enhancing distribution system stability and efficiency through multi‐power supply startup optimization for new energy integration

AbstractThis paper addresses the challenge of maximizing power capture from new energy sources, including coal, wind, solar, and hydroelectric power, which often lack sufficient inertia support. This deficiency can lead to frequency instability and cascading failures within the power system. A cooperative optimization model for the start‐up of multiple power supplies, designed to enhance the integration of new energy sources while maintaining system stability is proposed. The model incorporates primary frequency modulation and the intrinsic inertia support capabilities of self‐synchronous voltage source field stations, considering dynamic frequency constraints. Additionally, it employs new energy units with primary frequency modulation to provide inertia support during curtailment, particularly when conventional units cannot meet frequency standards due to existing constraints. Extensive simulations and comparative analyses demonstrate that the proposed model improves new energy utilization by up to 37.5% and reduces operational costs by approximately 16%, enhancing overall operational efficiency in high energy consumption scenarios.

A novel frequency constrained unit commitment considering VSC-HVDC's frequency support in asynchronous interconnected system under renewable energy Source's uncertainty

The increasing share of renewable energy source (RES) poses a challenge to the frequency security of the power system. Frequency constrained unit commitment (FCUC) serves as an effective measure to address this challenge at the operational level. This paper introduces a novel FCUC model applicable to the asynchronous interconnected system connected by voltage source converter based HVDC (VSCHVDC), fully taking into account the frequency support capability of VSCHVDC in order to reduce the demand for synchronous generators' inertia and reserve while ensuring frequency security, thereby lowering operating costs. Additionally, the uncertainty of RES is also considered. The constraint expressions for three frequency indicators are derived based on a system frequency response model that includes frequency support from VSCHVDC. The proposed model optimizes unit commitment, generation and reserve dispatch and VSCHVDC transmission power and frequency response parameters, while addressing RES uncertainty using the distributionally robust chance constrained approach. In response to the highly nonlinear characteristics of the maximum frequency derivation (MFD) constraints, we propose an intelligent sampling-based support vector machine to convexify the MFD constraints and introduce a two-stage decomposition algorithm for solving the model. The effectiveness of the proposed model is demonstrated based on a modified IEEE RTS-79 system.

Quercetin-enriched animal-free scaffolds for promoted cell proliferation and differentiation in cultured meat production

To solve the challenges posed by increasing meat consumption, it is imperative to develop polysaccharide composite edible scaffolds for cell-cultured meat production using novel food production technologies. This study developed some non-animal-origin polysaccharide composite scaffolds for cell-cultured meat production, based on chitin‑sodium alginate and crosslinked with quercetin. The results indicated that the chitin‑sodium alginate-quercetin (CH-SA-QR) scaffolds exhibited a porous and loose structure, and excellent mechanical support capability and cell adhesion sites. Meanwhile, QR1 and QR1.5 scaffolds were screened by immunofluorescence staining, RT-qPCR, and SEM imaging results to facilitate the proliferation and differentiation of cells and enhance the generation of myotube fusion and extracellular matrix protein. Importantly, the texture of the fried cultured meat was similar to traditional beef or even more tender, while the color appearance of the cultured meat was different from beef, but more similar to fried meat cutlets. These results suggest that cultured meat produced based on CH-SA-QR scaffolds could provide consumers with more choices.

Enhancing PV Hosting Capacity of Electricity Distribution Networks Using Deep Reinforcement Learning-Based Coordinated Voltage Control

Coordinated voltage control enables the active management of voltage levels throughout electricity distribution networks by leveraging the voltage support capabilities of existing grid-connected PV inverters. The efficient management of power flows and precise voltage regulation through coordinated voltage control schemes facilitate the increased adoption of rooftop PV systems and enhance the hosting capacity of electricity distribution networks. The research work presented in this paper proposes a coordinated voltage control scheme and evaluates the enhanced hosting capacity utilizing a deep reinforcement learning-based approach. A comparative analysis of the proposed algorithm is presented, and the performance is benchmarked against existing local voltage control schemes. The proposed coordinated voltage control scheme in this paper is evaluated using simulations on a real-world low-voltage electricity distribution network. The evaluation involves quasi-static time series power flow simulations for assessing performance. Furthermore, a discussion is presented that reflects on the strengths and limitations of the proposed scheme based on the results observed from the case study.

Pengaruh Kemampuan Adaptasi dan Dukungan Pemerintah terhadap Ketahanan Bisnis yang Dimediasi Kemampuan Teknologi Informasi pada UMKM di Koperasi Konsumen Wanita Pengusaha Indonesia (KOWAPI) Srikandi Daerah Istimewa Yogyakarta

This research aims to examine and analyze the influence of adaptability on business resilience, the influence of government support on business resilience, the influence of adaptability on information technology capabilities, the influence of government support on information technology capabilities, the influence of information technology capabilities on business resilience, the influence of adaptability on business resilience mediated by information technology capabilities and the influence of government support on business resilience mediated by information technology capabilities in MSMEs that are members of the Indonesian Women Entrepreneurs Cooperative (Kowapi) Srikandi DIY. The research method used was quantitative with a sample size of 80 respondents. The data collection technique was carried out using a questionnaire survey via Google Form and analyzed using SEM-PLS modeling analysis. The test results show that adaptability, government support and information technology capabilities have a positive effect on the resilience of MSME businesses in DIY. Information technology capability is a variable that explains the relationship between adaptability and government support on business resilience. This research focuses on confirming previous research regarding factors that influence MSME business resilience. It is hoped that future research will have broader and deeper objects, not only on MSME actors in the Kowapi "Srikandi" Cooperative.

One-Step Cannulation and Distance Measurement during Aortic Branched Endograft Repair: The Neuron Catheter Trick.

This paper aims to describe a straightforward, efficient, and reliable technique to simplify cannulation maneuvers during aortic branched endograft repair. The suggested approach utilizes the Penumbra Neuron Select catheter, which combines diagnostic, sizing, and support capabilities in one. This has the potential to reduce procedural time and minimize the need for serial catheter and guidewire exchanges. The proposed technique offers a simple yet effective tool to mitigate the risk of vessel loss and injury, and to streamline complex aortic repair procedures.

A wind farm control strategy for frequency regulation reserve: Optimize wake loss and frequency support capability

—With a high proportion of renewable energy, the issue of grid frequency fluctuations is becoming increasingly prominent. To tackle this challenge, wind farms can enhance frequency regulation response by increasing rotational kinetic energy through overspeed control. However, this approach may result in energy losses due to the wake effect. This paper proposes an optimized configuration strategy for wind farm frequency regulation reserve (FRR), utilizing pitch angle cooperative control to reduce wake losses. The objective is to explore the optimal configuration for maximizing wind energy utilization under FRR conditions. A genetic algorithm is used to find the optimal control parameters in the established FLORIS-based wind farm power reserve wake model, which involves rotor speed and pitch angle control, to maximize output power and rotational kinetic energy. Based on this, a lookup table is constructed to map wind conditions to the optimal control parameters for different FRR level. According to the reserve power schedule, optimization control is applied to the wind farm. Simulation results show that, compared to the traditional equal distribution strategy for FRR power, the proposed control strategy can enhance the total kinetic energy reserve of the wind farm by optimizing wake loss, thereby improving frequency support capability.

Research on risk management of ship maintenance projects based on multi agent swarm model simulation method

In recent years, the role of naval ship power has become increasingly prominent in regional conflicts and military operations worldwide, and the powerful capabilities demonstrated by naval forces have also been valued by countries around the world. While naval forces are frequently deployed to carry out various tasks, the intensity of equipment wear and tear on ships is also significantly increasing, posing a huge challenge to the maintenance and support capabilities of ship equipment. In the actual process of ship equipment maintenance, a series of risk factors such as cost, schedule, and quality will have a significant impact on the entire ship maintenance project, and even affect the success or failure of the entire project. This article first decomposes the project process of ship maintenance projects, further analyzes the various risk factors of ship maintenance projects based on the project decomposition situation, and then distinguishes the overall project, project process, and project risk factors to establish an intelligent agent group model for simulation analysis. Through the above simulation analysis, we will conduct in-depth research on the specific impact of project risks on ship maintenance projects, and analyze and verify the positive role and practical significance of project risk management in project risk control and project efficiency improvement. In the process of the above research content, methods and measures for risk management of ship maintenance projects are proposed, providing scientific and efficient risk management suggestions for such projects, improving the scientific management efficiency of ship maintenance projects, and contributing to the improvement of the quality and efficiency of project management.

Research on inertia characteristics of two-stage photovoltaic systems under generalized sag control

With the vast majority of photovoltaic (PV) power generation linked to the grid, the mainstream maximum power point tracking control cannot provide effective inertia support capability for the system. This paper examines the inertia source and action rules of three typical grid-tied photovoltaic systems under generalized sag control at the physical mechanism level, using the theory of the static synchronous generator model as a guide. It is found that the PV system under generalized sag is also capable of supporting the system through inertia. The boost converter, direct current bus capacitor, and inverter all contribute to the inertia capability of the PV system, but it is necessary to couple the control of the responding link with the grid frequency. The closer the action link is to the grid, the faster the speed of the corresponding grid frequency, but the weaker the inertia effect is provided to the system. The accuracy of the aforementioned analysis is confirmed by the simulation.

유아교사의 놀이교수효능감과 디지털리터러시 및 디지털놀이 지원역량 간의 관계 분석

Objectives The purpose of this study is to analyze the relationship among early childhood teachers' play teaching efficacy and digital literacy and digital play support capabilities. Methods To this end, a survey was conducted on 252 early childhood teachers working at early childhood education institutions in Seoul and Gyeonggi Province from April 11 to April 25, 2024 on the efficacy of play teaching, digital literacy, and digital play support capabilities of early childhood teachers. For data analysis, descriptive statistics, Pearson's moment correlation analysis, and stepwise multiple regression analysis were performed using the SPSS 29.0 program. Results First, early childhood teachers' play teaching efficacy showed a significant positive correlation with digital literacy and digital play support capabilities. Second, early childhood teachers' digital literacy was found to be the most powerful positive predictor of play teaching efficacy. And knowledge literacy, a sub-factor of digital literacy, was the most influential predictor, followed by digital play response and communication, followed by computer literacy, a sub-factor of digital play support capabilities. Conclusions The results of this study are expected to promote understanding of early childhood teachers' play teaching efficacy in the operation of a play-oriented curriculum and provide basic data to help develop teacher education programs to improve play teaching efficacy.

보육교사의 그릿과 놀이지원역량과의 관계에서 놀이교수효능감의 매개효과

This The purpose of this study is to verify the mediating effect of play teaching efficacy in the relationship between grit recognized by daycare center childcare teachers and play support capabilities. To this end, data were collected from 257 childcare teachers, and the main research results are as follows. First, it was found that the grit of daycare center childcare teachers had a statistically significant positive (+) effect on the play support competency. Second, it was found that the grit of daycare center childcare teachers had a statistically significant positive (+) effect on the play teaching efficacy. Third, the play teaching efficacy of daycare center childcare teachers had a statistically significant positive (+) effect on the play support competency. Finally, it was found that the grit of daycare center teachers had a statistically significant effect on the play support competency through the play teaching efficacy as a medium. Based on the above research results, this study aims to provide basic data to effectively improve the play support capabilities of childcare teachers, and to prepare important guidelines for implementing infant and play-oriented curriculum in childcare sites.

An Integrated Frequency Regulation Method Based on System Frequency Security Posture

As the share of renewable energy in a grid increases, the grid’s frequency support capability weakens, and the spatial distribution of grid frequency becomes more pronounced. As a result, control strategies based on system frequency consistency and traditional frequency regulation dominated by synchronous machines are becoming increasingly inadequate for meeting the frequency regulation requirements of new-type power systems. To enhance the system’s frequency support capability, it is imperative to fully utilize the frequency regulation resources within the power system. To address this issue, this paper first introduces a system frequency security posture assessment method that accounts for the spatial distribution characteristics of the grid. Subsequently, a parameter optimization method for diverse frequency regulation resources is proposed in conjunction with the proposed comprehensive evaluation method for frequency regulation. Next, using a renewable energy feeder regional grid as an example, an integrated frequency regulation method based on the system frequency security posture is presented. Finally, the frequency regulation performance and economic costs of different frequency regulation methods are analyzed under various operating scenarios and disturbances using a model based on actual data from the renewable energy feeder regional grid. The simulation and index calculation results demonstrate that the method proposed in this paper effectively enhances the system’s frequency support capability, reduces the frequency disparity between different nodes within the grid, and maintains high economic performance.

Resilience Assessment of Deep Excavation Engineering Systems Based on Bayesian Network

As a key component of infrastructure, the construction safety of deep excavation is particularly important. In order to improve the safety and stability of Deep excavation construction, research on the risk resistance and rapid recovery capabilities of Deep excavation projects is carried out. By introducing the concept of resilience, we analyze the key factors that affect the safety and resilience of Deep excavation projects, use Bayesian networks to establish a resilience model that expresses the causal relationship between factors, and learn the parameters of the network model through data samples collected through surveys; by adjusting the network Analyze the relationship between each factor and system resilience at each node, and clarify the measures that should be taken and key control objects, thereby improving the system resilience and ensuring that normal construction can be carried out safely and orderly. Research shows that this model can be used to quantify the safety toughness value of deep excavation and reason and analyze the impact of various factors on the toughness value, thereby improving risk management and decision support capabilities.