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Journal articles on the topic 'Evaluation Coupling Graph (ECG)'

Author: Grafiati

Published: 6 September 2023

Last updated: 31 July 2025

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1

Li, Zhuojian, Guanxing Chen, Guang Tan, and Calvin Yu-Chian Chen. "CoupleMDA: Metapath-Induced Structural-Semantic Coupling Network for miRNA-Disease Association Prediction." International Journal of Molecular Sciences 26, no. 10 (2025): 4948. https://doi.org/10.3390/ijms26104948.

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The prediction of microRNA-disease associations (MDAs) is crucial for understanding disease mechanisms and biomarker discovery. While graph neural networks have emerged as promising tools for MDA prediction, existing methods face critical limitations: (1) data leakage caused by improper use of Gaussian interaction profile (GIP) kernel similarity during feature construction, (2) self-validation loops in calculating miRNA functional similarity using known MDA data, and (3) information bottlenecks in conventional graph neural network (GNN) architectures that flatten heterogeneous relationships an

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Zhao, Zhiyao, Xuanhao Li, Xiaoyu Cui, and Xin Zhang. "Fault Coupling Analysis and Reliability Assessment of Actuation System Based on Bond Graph Model." Applied Sciences 13, no. 13 (2023): 7462. http://dx.doi.org/10.3390/app13137462.

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In this paper, a new degradation model of the more electrical aircraft (MEA) actuation system is proposed. The bond graph model is used to build the dissimilar redundancy actuation system model, taking into account the degradation behavior (wear, fatigue, aging) of components in the system operation and the fault coupling phenomenon caused by the accumulation of dissipated energy in space and time, and a fault coupling degradation model of the actuation system is established with clear mechanism support. Through the fault mechanism analysis, various fault types are injected into the bond graph

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Xu, Xiaolin. "RCA Analysis of Multi-Source Faults in Autonomous Driving." International Journal of Information System Modeling and Design 16, no. 1 (2025): 1–28. https://doi.org/10.4018/ijismd.373424.

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This strategy is proposed to address the safety issues caused by inaccurate fault localization and unclear boundary delineation of fault hazard due to the coupling and correlation of multi-source heterogeneous faults in autonomous driving. Construct a multi-source fault entity model using a knowledge graph, locally interpret the characteristics of each fault attribute, and integrate asynchronous message queues and linked data object encoding to handle nested relationships between fault entities; Further utilize the Analytic Hierarchy Process to establish a fault structure evaluation model and

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Entezari, Amin, Farzad Kamali, Shabnam Madadi, et al. "Investigating the Correlation between Electrocardiographic Parameters and the Occurrence of Clinical Symptoms in Patients with Idiopathic Premature Ventricular Contractions." Research in Cardiovascular Medicine 14, no. 2 (2025): 94–97. https://doi.org/10.4103/rcm.rcm_17_25.

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Abstract Background: This study aimed to investigate the correlation between electrocardiographic (ECG) parameters of premature ventricular contraction (PVC) morphology and clinical outcomes, including symptom burden and health-related quality of life (HRQoL). Materials and Methods: This observational study at Rajaie Cardiovascular Center examined the relationship between PVC ECG parameters and HRQoL in patients undergoing ablation for idiopathic PVCs. Data on demographics, echocardiography, and ECG parameters were collected. The study received ethical approval, and statistical analysis was pe

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Liu, Lihua, Jing Huang, and Huimin Wang. "Visibility Graph Power Geometric Aggregation Operator and Its Application in Water, Energy and Food Efficiency Evaluation." International Journal of Environmental Research and Public Health 17, no. 11 (2020): 3891. http://dx.doi.org/10.3390/ijerph17113891.

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In the real decision-making process, there are so many time series values that need to be aggregated. In this paper, a visibility graph power geometric (VGPG) aggregation operator is developed, which is based on the complex network and power geometric operator. Time series data are converted into a visibility graph. A visibility matrix is developed to denote the links among different time series values. A new support function based on the distance of two values are proposed to measure the support degree of each other when the two time series values have visibility. The VGPG operator considers

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Perpetuini, David, Antonio Maria Chiarelli, Lidia Maddiona, et al. "Multi-Site Photoplethysmographic and Electrocardiographic System for Arterial Stiffness and Cardiovascular Status Assessment." Sensors 19, no. 24 (2019): 5570. http://dx.doi.org/10.3390/s19245570.

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The development and validation of a system for multi-site photoplethysmography (PPG) and electrocardiography (ECG) is presented. The system could acquire signals from 8 PPG probes and 10 ECG leads. Each PPG probe was constituted of a light-emitting diode (LED) source at a wavelength of 940 nm and a silicon photomultiplier (SiPM) detector, located in a back-reflection recording configuration. In order to ensure proper optode-to-skin coupling, the probe was equipped with insufflating cuffs. The high number of PPG probes allowed us to simultaneously acquire signals from multiple body locations. T

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Hua, Xian, Jing Li, Ting Wang, et al. "Evaluation of movement functional rehabilitation after stroke: A study via graph theory and corticomuscular coupling as potential biomarker." Mathematical Biosciences and Engineering 20, no. 6 (2023): 10530–51. http://dx.doi.org/10.3934/mbe.2023465.

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<abstract> <p>Changes in the functional connections between the cerebral cortex and muscles can evaluate motor function in stroke rehabilitation. To quantify changes in functional connections between the cerebral cortex and muscles, we combined corticomuscular coupling and graph theory to propose dynamic time warped (DTW) distances for electroencephalogram (EEG) and electromyography (EMG) signals as well as two new symmetry metrics. EEG and EMG data from 18 stroke patients and 16 healthy individuals, as well as Brunnstrom scores from stroke patients, were recorded in this paper. Fi

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Huang, Meng, Bo Li, Xiaoyun Chen, Qineng Zhuang, and Yanbing Guo. "Study of critical deviation transfer for assembly of complex structural parts of aircraft." Journal of Physics: Conference Series 2746, no. 1 (2024): 012002. http://dx.doi.org/10.1088/1742-6596/2746/1/012002.

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Abstract In current assembly process of the aircraft complex structural parts, there are problems such as nonlinear, multilevel strong coupling and large uncertainty transfer relationship between assembly quality and its deviation sources. In this paper, an assembly deviation transfer method based on transfer entropy network graph is proposed to address the challenges. Firstly, the source of assembly deviation is analysed by constructing a multi-level assembly coordination network with assembly deviation detection data. Secondly, an assembly deviation propagation model is established by combin

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Berselli, Giovanni, Rocco Vertechy, Mitja Babič, and Vincenzo Parenti Castelli. "Dynamic modeling and experimental evaluation of a constant-force dielectric elastomer actuator." Journal of Intelligent Material Systems and Structures 24, no. 6 (2012): 779–91. http://dx.doi.org/10.1177/1045389x12457251.

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Constant-force actuators based on dielectric elastomers can be obtained by coupling a dielectric elastomer film with particular compliant frames whose structural properties must be carefully designed. In any case, the practical achievement of a desired force profile can be quite a challenging task owing to the time-dependent phenomena, which affect the dielectric elastomer’s electromechanical response. Within this scenario, a hyperviscoelastic model of a rectangular constant-force actuator is reported. The model, based on the bond graph formalism, can be used as an engineering tool when design

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Orlova, Е. А., О. S. Tarasova, V. D. Son'kin, and А. S. Borovik. "INFLUENCE OF THE AGE ON BAROREFLEX SYNCHRONIZATION OF ARTERIAL PRESSURE AND HEART RATE DURING THE PASSIVE STANDING TEST." Aerospace and Environmental Medicine 55, no. 1 (2021): 46–50. http://dx.doi.org/10.21687/0233-528x-2021-55-1-46-50.

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Age-related changes in phase synchronization of spontaneous blood pressure (BP) and heart rate (HR) fluctuations within the baroreflex wave range (about 0.1 Hz) were studied in 66 subjects aged 20 to 52 years. Measurements performed during the head-up tilt test included continuous BP monitoring using the volume-compensation method, ECG recording for ensuing HR calculation, and breathing rate recording. The phase synchronization index (PSI) was used for evaluation of BP-HR coupling. In supine position, phase synchronization in the subjects over 40 years was higher as compared with their counter

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Liu, Huimin, Qiu Yang, Xuexi Yang, Jianbo Tang, Min Deng, and Rong Gui. "Coupling Hyperbolic GCN with Graph Generation for Spatial Community Detection and Dynamic Evolution Analysis." ISPRS International Journal of Geo-Information 13, no. 7 (2024): 248. http://dx.doi.org/10.3390/ijgi13070248.

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Spatial community detection is a method that divides geographic spaces into several sub-regions based on spatial interactions, reflecting the regional spatial structure against the background of human mobility. In recent years, spatial community detection has attracted extensive research in the field of geographic information science. However, mining the community structures and their evolutionary patterns from spatial interaction data remains challenging. Most existing methods for spatial community detection rely on representing spatial interaction networks in Euclidean space, which results i

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Huang, Shanshan. "Research hotspots and knowledge graph analysis of the relationship between Urbanization and Ecological Environment in the Yellow River Basin." SHS Web of Conferences 157 (2023): 03007. http://dx.doi.org/10.1051/shsconf/202315703007.

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Based on the literature sample data of the research topics related to urbanization and ecological environment relationship in the Yellow River Basin in CNKI database from 2000 to 2022, this paper uses excle and CiteSpace software to systematically sort out the preface, current hot spots and development trends of the research on the relationship between urbanization and ecological environment in the Yellow River Basin through volume analysis, keyword co-occurrence and cluster analysis, and the results show that the existing research scale tends to be smaller, and pays attention to multi-scale a

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Zeng, Jie, Yue Ren, Kan Wang, Xiong Hu, and Jiufa Li. "Spatio-Temporal-Attention-Based Vehicle Trajectory Prediction Considering Multi-Vehicle Interaction in Mixed Traffic Flow." Applied Sciences 14, no. 1 (2023): 161. http://dx.doi.org/10.3390/app14010161.

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As a link connecting the environmental perception system and the decision-making system, accurate obstacle trajectory prediction provides a reliable guarantee of correct decision-making by autonomous vehicles. Oriented toward a mixed human-driven and machine-driven traffic environment, a vehicle trajectory prediction algorithm based on an encoding–decoding framework composed of a multiple-attention mechanism is proposed. Firstly, a directed graph is used to describe vehicle–vehicle motion dependencies. Then, by calculating the repulsive force between vehicles using a priori edge information ba

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Feng, Ju, and Jens Nørkær Sørensen. "Towards a general tool chain integration platform for multi-disciplinary analysis and optimization in wind energy." Journal of Physics: Conference Series 2767, no. 8 (2024): 082014. http://dx.doi.org/10.1088/1742-6596/2767/8/082014.

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Abstract To enable easier uptake and flexible usage for the wind energy community, a general tool chain integration platform for multi-disciplinary analysis and optimization, TopDesign, is proposed and developed. This work describes its concept and the initial implementation. The platform is written in Python and provided as an open source framework. The design of this platform puts emphasis on flexibility, usability and extensibility. General model classes with standard interfaces, which can wrap custom tools/models in different formats based on different programming languages, will be provid

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Gao, Jinggeng, Yong Yang, Honglei Xu, Yingzhou Xie, Chen Zhou, and Haiying Dong. "The Wideband Oscillatory Localization Method Based on Combining Compressed Sensing and Graph Attention Networks." Energies 17, no. 23 (2024): 6062. https://doi.org/10.3390/en17236062.

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Due to the increasing integration of new energy sources, the power system now exhibits low inertia, in which the broadband oscillation problem is increasingly significant in the face of the strong coupling of complex and variable power systems, and the current lack of uniform and effective mathematical models and analysis methods. To solve this major problem, a broadband oscillation localization method based on the combination of compressed perception and graph attention network (GAT) is proposed. The method firstly uses the principle of compression perception to compress and transmit the osci

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Nakayama, Fernando, Paulo Lenz, Stella Banou, Michele Nogueira, Aldri Santos, and Kaushik R. Chowdhury. "A Continuous User Authentication System Based on Galvanic Coupling Communication for s-Health." Wireless Communications and Mobile Computing 2019 (November 28, 2019): 1–11. http://dx.doi.org/10.1155/2019/9361017.

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Smart health (s-health) is a vital topic and an essential research field today, supporting the real-time monitoring of user’s data by using sensors, either in direct or indirect contact with the human body. Real-time monitoring promotes changes in healthcare from a reactive to a proactive paradigm, contributing to early detection, prevention, and long-term management of health conditions. Under these new conditions, continuous user authentication plays a key role in protecting data and access control, once it focuses on keeping track of a user’s identity throughout the system operation. Tradit

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Nalla, Gopi. "Technology Focus: History Matching and Forecasting (April 2024)." Journal of Petroleum Technology 76, no. 04 (2024): 95–96. http://dx.doi.org/10.2118/0424-0095-jpt.

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This year’s history matching and forecasting selections cover topics that include a deep-learning framework to forecast spatial/temporal dynamics of CO2 mineralization in reactive rocks, productivity decline analysis using coupled full-field and near-wellbore poromechanics modeling, and a reservoir graph network model for multiwell forecasting in unconventional reservoirs. In paper SPE 216998, the authors present a deep-learning methodology to create surrogate models capable of predicting the precipitation of minerals during CO2 injection into deep saline aquifers. The authors state that this

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Rogale, Dubravko, Snježana Firšt Rogale, Željko Knezić, Siniša Fajt, Daniel Časar Veličan, and Nikolina Jukl. "Process Parameters of High Frequency Welding." Materials 17, no. 2 (2024): 517. http://dx.doi.org/10.3390/ma17020517.

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High frequency (HF) welding of polymer materials is increasingly used in modern manufacturing processes. The literature on HF welding process parameters was reviewed and it was found that 3–5 basic welding parameters were considered, which is insufficient for the scientific study of HF welding of polymeric materials. This article presents the mathematical expressions for the evaluation combining 17 influential parameters. For the first time, the specific and latent heat of the welded polymer material were used. The breaking forces of welds made by RF welding are investigated by varying the ano

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Zhou, Wei, Wenqiang Wang, and Xupeng Wang. "Research on Lightning Prediction Based on GCN-LSTM Model Integrating Spatiotemporal Features." Atmosphere 16, no. 4 (2025): 447. https://doi.org/10.3390/atmos16040447.

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To overcome the limitations of spatiotemporal feature extraction that are inherent in conventional lightning warning algorithms relying solely on temporal analysis, we propose a novel prediction framework integrating a Graph Convolutional Network (GCN), Long Short-Term Memory (LSTM) architecture, and a multi-head attention mechanism. The methodology innovatively constructs station adjacency matrices based on geographical distances between meteorological monitoring stations in Qingdao, Shandong Province, China, where GCN layers capture inter-station spatial dependencies while LSTM units extract

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Mežnar, Sebastian, Nada Lavrač, and Blaž Škrlj. "SNoRe: Scalable Unsupervised Learning of Symbolic Node Representations." IEEE Access 8 (December 9, 2020): 212568–88. https://doi.org/10.1109/ACCESS.2020.3039541.

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Learning from complex real-life networks is a lively research area, with recent advances in learning information-rich, low-dimensional network node representations. However, state-of-the-art methods are not necessarily interpretable and are therefore not fully applicable to sensitive settings in biomedical or user profiling tasks, where explicit bias detection is highly relevant. The proposed SNoRe (Symbolic Node Representations) algorithm is capable of learning symbolic, human-understandable representations of individual network nodes, based on the similarity of neighborhood hashes which serv

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Li, He, Quan Liu, Xiaopu Ma, et al. "Cooperative Recharge Scheme Based on a Hamiltonian Path in Mobile Wireless Rechargeable Sensor Networks." Mathematical Problems in Engineering 2022 (May 19, 2022): 1–20. http://dx.doi.org/10.1155/2022/6955713.

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The energy problem and limited capacity of batteries have been fundamental constraints in many wireless sensor network (WSN) applications. For WSN, the wireless energy transmission technology based on magnetic resonance coupling is a promising energy transmission technology. To reduce the cost and energy consumption during charging in mobile wireless rechargeable sensor networks (MWRSNs), a cooperative mobile charging mechanism based on the Hamiltonian path is proposed in this paper. To improve the charging task interval, we study the use of a mobile charger (MC) as a mobile sink node to colle

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Shi, Tongtong, Ping Wang, Xudong Qi, et al. "CPT-DF: Congestion Prediction on Toll-Gates Using Deep Learning and Fuzzy Evaluation for Freeway Network in China." Journal of Advanced Transportation 2023 (April 10, 2023): 1–16. http://dx.doi.org/10.1155/2023/2941035.

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Toll-gates are crucial points of management and key congestion bottleneck for the freeway. In order to avoid traffic deterioration and alleviate traffic congestion in advance, it is necessary to predict and evaluate the congestion in toll-gates scattering in large-scale region of freeway network. In this paper, traffic volume and operational delay time are selected from various traffic indicators to evaluate congestion considering the particular characteristics of the traffic flow within the toll-gate area. The congestion prediction method is designed including two modules: a deep learning (DL

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Izzat Bin Zainuddin, Mohd, and CV Aravind. "Design Analysis of a Dual Rotor Permanent Magnet Machine driven Electric Vehicle." MATEC Web of Conferences 152 (2018): 03004. http://dx.doi.org/10.1051/matecconf/201815203004.

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Electric bike in urban countries such as Europe and China commonly used the brushless direct current machine (BLDC) as it able to produce high torque to transport the user from one place to another. However, BLDC torque density can’t be improving due to limitation magnetic flux generated by the permanent magnet. Therefore, the performance of electric bike can’t be improved. Outer rotor BLDC machine design able to improve the torque density of the motor due to increase radius of the motor which can be explained by simple physics equation (Torque = Force x radius). However, an outer rotor machin

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Chen, Wenxing, Shuyang Dai, and Baojuan Zheng. "Thermal-Mechanical Coupling Model Based on the Hybrid Finite Element Method for Solving Bipolar the Plate Deformation of Hydrogen Fuel Cells." Machines 10, no. 7 (2022): 505. http://dx.doi.org/10.3390/machines10070505.

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New energy is the focus of attention all over the world, and research into new energy can inject new vitality into the industrial system. Hydrogen fuel cells are not only environmentally friendly, but also rich in reserves that can be used as a strategic resource for the entire country. The difficulty lies in the safe design of application equipment and the batch generation and storage of hydrogen. In addition, fuel cells have the disadvantage of a slow start-up. Based on the above problems, this paper proposes a hybrid-element method to solve the thermal-mechanical coupling model of fuel cell

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Diallo, Diaoulé, Jurij Schoenfeld, René Schmieding, Sascha Korf, Martin J. Kühn, and Tobias Hecking. "Integrating Human Mobility Models with Epidemic Modeling: A Framework for Generating Synthetic Temporal Contact Networks." Entropy 27, no. 5 (2025): 507. https://doi.org/10.3390/e27050507.

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High-resolution temporal contact networks are useful ingredients for realistic epidemic simulations. Existing solutions typically rely either on empirical studies that capture fine-grained interactions via Bluetooth or wearable sensors in confined settings or on large-scale simulation frameworks that model entire populations using generalized assumptions. However, for most realistic modeling of epidemic spread and the evaluation of countermeasures, there is a critical need for highly resolved, temporal contact networks that encompass multiple venues without sacrificing the intricate dynamics o

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Zhu, Zhaowei, Jingxuan Zhu, Ji Liu, and Yang Liu. "Federated Bandit." Proceedings of the ACM on Measurement and Analysis of Computing Systems 5, no. 1 (2021): 1–29. http://dx.doi.org/10.1145/3447380.

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In this paper, we study Federated Bandit, a decentralized Multi-Armed Bandit problem with a set of N agents, who can only communicate their local data with neighbors described by a connected graph G. Each agent makes a sequence of decisions on selecting an arm from M candidates, yet they only have access to local and potentially biased feedback/evaluation of the true reward for each action taken. Learning only locally will lead agents to sub-optimal actions while converging to a no-regret strategy requires a collection of distributed data. Motivated by the proposal of federated learning, we ai

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Zhu, Zhaowei, Jingxuan Zhu, Ji Liu, and Yang Liu. "Federated Bandit: A Gossiping Approach." ACM SIGMETRICS Performance Evaluation Review 49, no. 1 (2022): 3–4. http://dx.doi.org/10.1145/3543516.3453919.

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We study Federated Bandit, a decentralized Multi-Armed Bandit (MAB) problem with a set of N agents, who can only communicate their local data with neighbors described by a connected graph G. Each agent makes a sequence of decisions on selecting an arm from M candidates, yet they only have access to local and potentially biased feedback/evaluation of the true reward for each action taken. Learning only locally will lead agents to sub-optimal actions while converging to a no-regret strategy requires a collection of distributed data. Motivated by the proposal of federated learning, we aim for a s

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Feng, Lyuhang, Jiawei Sun, Tongtong Zhai, Mingrui Miao, and Guanchao Yu. "Planning for Cultural Connectivity: Modeling and Strategic Use of Architectural Heritage Corridors in Heilongjiang Province, China." Buildings 15, no. 12 (2025): 1970. https://doi.org/10.3390/buildings15121970.

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This study focuses on the systematic conservation of historical architectural heritage in Heilongjiang Province, particularly addressing the challenges of point-based protection and spatial fragmentation. It explores the construction of a connected and conductive heritage corridor network, using historical building clusters across the province as empirical cases. A comprehensive analytical framework is established by integrating the nearest neighbor index, kernel density estimation, minimum cumulative resistance (MCR) model, entropy weighting, circuit theory, and network structure metrics. Ker

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Verkaik, Jarno, Edwin H. Sutanudjaja, Gualbert H. P. Oude Essink, Hai Xiang Lin, and Marc F. P. Bierkens. "GLOBGM v1.0: a parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model." Geoscientific Model Development 17, no. 1 (2024): 275–300. http://dx.doi.org/10.5194/gmd-17-275-2024.

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Abstract. We discuss the various performance aspects of parallelizing our transient global-scale groundwater model at 30′′ resolution (30 arcsec; ∼ 1 km at the Equator) on large distributed memory parallel clusters. This model, referred to as GLOBGM, is the successor of our 5′ (5 arcmin; ∼ 10 km at the Equator) PCR-GLOBWB 2 (PCRaster Global Water Balance model) groundwater model, based on MODFLOW having two model layers. The current version of GLOBGM (v1.0) used in this study also has two model layers, is uncalibrated, and uses available 30′′ PCR-GLOBWB data. Increasing the model resolution fr

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Nikita Landge, Ajaz Khan, Aasir Awez, Khan M Tarkhan, and Prof. Khwaja Ramizuddin. "ECG Graph Monitoring System using Ad8232 with ECG Sensor and Arduino." International Journal of Advanced Research in Science, Communication and Technology, May 21, 2022, 319–20. http://dx.doi.org/10.48175/ijarsct-3927.

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Patient monitoring is the heart of the fitness care domain in day to day lifestyles both at domestic or at medical institution. This paper affords the layout of a transportable electrocardiograph (ECG) device the use of the AD8232 microchip as the analog front-stop (AFE). Beginning with the producer’s evaluation board of the AFE chip for testing circuit configurations, open-supply hardware and software components had been integrated into a breadboard prototype. In the long run, a custom printed circuit board (PCB) changed into produced. The prototype required to accommodate the microchip on a

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Hadiyoso, Sugondo, Suci Aulia, and Indrarini Dyah Irawati. "Multi-Class Heart Abnormalities Detection Based on ECG Graph Using Transfer Learning Method." Jurnal Rekayasa Elektrika 19, no. 1 (2023). http://dx.doi.org/10.17529/jre.v19i1.28637.

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The heart is one of the vital organs in the circulatory system. Regular checkups are very important to prevent heart disease. The most basic examination is blood pressure then further examination is related to the evaluation of the electrical activity of the heart using an electrocardiogram (ECG). The ECG carries important information regarding various abnormalities of heart function. Several automated classification techniques have been proposed to facilitate diagnosis. However, not all digital ECG devices provide raw data for analysis. ECG classification method based on images can be an alte

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Costa, J., L. Bichon, A. Maouche, P. Durdon, R. Pouy, and A. Robbins. "Evaluation of Perugini score and myocardial mass and voltage abnormalities in transthyretine cardiac amyloidosis." European Heart Journal 42, Supplement_1 (2021). http://dx.doi.org/10.1093/eurheartj/ehab724.1807.

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Abstract Background Transthyretine cardiac amyloidosis (TTR-CA) is an emerging treatable disease in cardiology. Severity of TTR infiltration can be assessed by bone scintigraphy with Perugini score, depending on HPD-Tc99M myocardial intensity uptake. Less is known on how Perugini score interplays with routine cardiac structural parameters, especially cardiac mass and voltage. Aim To evaluate correlation between Perugini score and myocardial mass and voltage abnormalities in patients with TTR-CA. Methods Patients diagnosed with ATTR-CA and addressed to our center for treatment underwent complet

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Riebel, Leto Luana, Zhinuo Jenny Wang, Hector Martinez-Navarro, et al. "In silico evaluation of cell therapy in acute versus chronic infarction: role of automaticity, heterogeneity and Purkinje in human." Scientific Reports 14, no. 1 (2024). http://dx.doi.org/10.1038/s41598-024-67951-5.

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AbstractHuman-based modelling and simulation offer an ideal testbed for novel medical therapies to guide experimental and clinical studies. Myocardial infarction (MI) is a common cause of heart failure and mortality, for which novel therapies are urgently needed. Although cell therapy offers promise, electrophysiological heterogeneity raises pro-arrhythmic safety concerns, where underlying complex spatio-temporal dynamics cannot be investigated experimentally. Here, after demonstrating credibility of the modelling and simulation framework, we investigate cell therapy in acute versus chronic MI

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Alkhodari, Mohanad, Namareq Widatalla, Maisam Wahbah, et al. "Deep learning identifies cardiac coupling between mother and fetus during gestation." Frontiers in Cardiovascular Medicine 9 (July 29, 2022). http://dx.doi.org/10.3389/fcvm.2022.926965.

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In the last two decades, stillbirth has caused around 2 million fetal deaths worldwide. Although current ultrasound tools are reliably used for the assessment of fetal growth during pregnancy, it still raises safety issues on the fetus, requires skilled providers, and has economic concerns in less developed countries. Here, we propose deep coherence, a novel artificial intelligence (AI) approach that relies on 1 min non-invasive electrocardiography (ECG) to explain the association between maternal and fetal heartbeats during pregnancy. We validated the performance of this approach using a trai

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Hellqvist, Henrik, Mikael Karlsson, Johan Hoffman, Thomas Kahan, and Jonas Spaak. "Estimation of aortic stiffness by finger photoplethysmography using enhanced pulse wave analysis and machine learning." Frontiers in Cardiovascular Medicine 11 (March 11, 2024). http://dx.doi.org/10.3389/fcvm.2024.1350726.

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IntroductionAortic stiffness plays a critical role in the evolution of cardiovascular diseases, but the assessment requires specialized equipment. Photoplethysmography (PPG) and single-lead electrocardiogram (ECG) are readily available in healthcare and wearable devices. We studied whether a brief PPG registration, alone or in combination with single-lead ECG, could be used to reliably estimate aortic stiffness.MethodsA proof-of-concept study with simultaneous high-resolution index finger recordings of infrared PPG, single-lead ECG, and finger blood pressure (Finapres) was performed in 33 part

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Rella, V., C. Delcea, A. Clement, et al. "Left atrial function and left atrioventricular coupling indices for atrial fibrillation prediction in hypertrophic cardiomyopathy." European Heart Journal - Cardiovascular Imaging 26, Supplement_1 (2025). https://doi.org/10.1093/ehjci/jeae333.372.

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Abstract Background In hypertrophic cardiomyopathy (HCM), atrial fibrillation (AF) is a marker of disease progression and worse outcome, increasing the risk of thromboembolic events. Identification of HCM patients (pts) at risk of AF is pivotal for their clinical management and follow-up. Purpose We aimed to explore whether a detailed echocardiographic evaluation of the left atrium (LA) remodeling and function in HCM pts might improve the predictive value for new AF compared to standard parameters. Methods In consecutive HCM pts referred to our Cardiomyopathy Clinic between 2020 and 2023, we a

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Fan, Jingjing, Junhua Mei, Yuan Yang, et al. "Sleep‐phasic heart rate variability predicts stress severity: Building a machine learning‐based stress prediction model." Stress and Health, February 27, 2024. http://dx.doi.org/10.1002/smi.3386.

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AbstractWe propose a novel approach for predicting stress severity by measuring sleep phasic heart rate variability (HRV) using a smart device. This device can potentially be applied for stress self‐screening in large populations. Using a Holter electrocardiogram (ECG) and a Huawei smart device, we conducted 24‐h dual recordings of 159 medical workers working regular shifts. Based on photoplethysmography (PPG) and accelerometer signals acquired by the Huawei smart device, we sorted episodes of cyclic alternating pattern (CAP; unstable sleep), non‐cyclic alternating pattern (NCAP; stable sleep)

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Wu, Zhaohong, Matthew I. Campbell, and Benito R. Fernández. "Bond Graph Based Automated Modeling for Computer-Aided Design of Dynamic Systems." Journal of Mechanical Design 130, no. 4 (2008). http://dx.doi.org/10.1115/1.2885180.

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This paper introduces research leading to a computer-aided design tool in which engineering designers can test various design concepts (topologies) in an environment equipped to automatically model the dynamics and conveniently optimize the specified components (given the evaluation criteria defined by human designers). A component repository is developed to store not only the component dynamics models, but also other information such as typical component design constraints and physical constitutive laws. In this paper, automated modeling of design configurations is introduced through a design

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Hoeksema, W. F., M. H. Van Der Ree, E. M. T. Dieleman, et al. "Stereotactic arrhythmia radiotherapy for ventricular tachycardia does not appear to alter QRS duration and QTc interval: a secondary analysis of the prospective STARNL-1 trial." Europace 25, Supplement_1 (2023). http://dx.doi.org/10.1093/europace/euad122.337.

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Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Dutch Heart Foundation grant to dr. P.G. Postema, MD PhD Background Stereotactic arrhythmia radiotherapy (STAR) has evolved as promising bail-out treatment in patients with therapy-refractory ventricular tachycardia (VT). The mechanism of action of STAR in preventing VT has yet to be elucidated and further understanding could improve this technique in the future. Preclinical studies reported an increase in conduction velocity and consequently a decrease in conduction intervals on electrocardiograms (

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Wang, Yong, Yaoyao Han, An Luo, Shenghua Xu, Jian Chen, and Wangwang Liu. "Site selection and prediction of urban emergency shelter based on VGAE-RF model." Scientific Reports 14, no. 1 (2024). http://dx.doi.org/10.1038/s41598-024-64031-6.

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AbstractAs urban development accelerates and natural disasters occur more frequently, the urgency of developing effective emergency shelter planning strategies intensifies. The shelter location selection method under the traditional multi-criteria decision-making framework suffers from issues such as strong subjectivity and insufficient data support. Artificial intelligence offers a robust data-driven approach for site selection; however, many methods neglect the spatial relationships of site selection targets within geographical space. This paper introduces an emergency shelter site selection

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Hazra, Debapriya, Steven Jones, Swati Dey, and Deeptankar DeMazumder. "Abstract 4136938: Autonomous Personalized Dynamic ECG Analysis Predicts 1-hour Incidence of Sudden Cardiac Arrest." Circulation 150, Suppl_1 (2024). http://dx.doi.org/10.1161/circ.150.suppl_1.4136938.

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Background: Sudden cardiac arrest (SCA) is a leading cause of death in the USA. Defibrillators prevent SCA by delivering shocks for sustained ventricular tachyarrhythmias (VT). However, current clinical methods for predicting SCA are limited. We have shown that distinct nonlinear fluctuation patterns “hidden” within normal-appearing ECG waveforms have unique prognostic value. Hypothesis: Autonomous personalized dynamic ECG analysis predicts the 1-hour incidence of SCA. Methods: In an established pressure-overload model that exhibits key features of human VT and SCA (e.g., cardiac restitution p

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Ma, Congsha, and Ming Lei. "Time series prediction for monitoring cardiovascular health in autistic patients." Frontiers in Psychiatry 16 (July 7, 2025). https://doi.org/10.3389/fpsyt.2025.1623986.

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IntroductionMonitoring cardiovascular health in autistic patients presents unique challenges due to atypical sensory profiles, altered autonomic regulation, and communication difficulties. As cardiovascular comorbidities rise in this population, there is an urgent need for tailored computational strategies to enable continuous monitoring and predictive care planning. Traditional time series methods—including statistical autoregressive models and recurrent neural networks—are constrained by opaque decision processes, limited personalization, and insufficient handling of multimodal data, restric

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"Design and Implementation of Hybrid FIR Filters using Vedic Multiplier and Fast Adders." International Journal of Recent Technology and Engineering 8, no. 4 (2019): 11849–53. http://dx.doi.org/10.35940/ijrte.d9569.118419.

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FIR (Finite Impulse Response) filters play a significant role in the field of Digital Signal Processing (DSP) to eliminate noise suppression in Electro Cardio Graph (ECG), Imaging devices and the signal stored in analog media. So filter evaluation is accomplished to reduce the noise level. The Filter passes only the desired frequency to pass thereby reducing distortion in the processed signal during measurement. The FIR filter comprises of basic units like adders, multipliers and the delay element for its operations.FIR and IIR are the two types of digital filters chosen based on the range of

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Lima, Paulo C., Riccardo Mariani, Aldo Procacci, and Benedetto Scoppola. "The Blume–Emery–Griffiths Model on the FAD Point and on the AD Line." Journal of Statistical Physics 190, no. 11 (2023). http://dx.doi.org/10.1007/s10955-023-03181-9.

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AbstractWe analyse the Blume–Emery–Griffiths (BEG) model on the lattice $${\mathbb {Z}}^d$$ Z d on the ferromagnetic-antiquadrupolar-disordered (FAD) point and on the antiquadrupolar-disordered (AD) line. In our analysis on the FAD point, we introduce a Gibbs sampler of the ground states at zero temperature, and we exploit it in two different ways: first, we perform via perfect sampling an empirical evaluation of the spontaneous magnetization at zero temperature, finding a non-zero value in $$d=3$$ d = 3 and a vanishing value in $$d=2$$ d = 2 . Second, using a careful coupling with the Bernoul

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Yuan, Siyu, Hui Huang, Bingyang Cai, Jiwei Li, Miao Zhang, and Jie Luo. "Altered metabolic-functional coupling in the epileptogenic network could predict surgical outcomes of mesial temporal lobe epilepsy." Frontiers in Neuroscience 17 (June 8, 2023). http://dx.doi.org/10.3389/fnins.2023.1165982.

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ObjectiveTo investigate the relationship between glucose metabolism and functional activity in the epileptogenic network of patients with mesial temporal lobe epilepsy (MTLE) and to determine whether this relationship is associated with surgical outcomes.Methods18F-FDG PET and resting-state functional MRI (rs-fMRI) scans were performed on a hybrid PET/MR scanner in 38 MTLE patients with hippocampal sclerosis (MR-HS), 35 MR-negative patients and 34 healthy controls (HC). Glucose metabolism was measured using 18F-FDG PET standardized uptake value ratio (SUVR) relative to cerebellum; Functional a

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Tang, Chuanxi, Ruiao Sun, Ke Xue, et al. "Distinct serum GDNF coupling with brain structural and functional changes underlies cognitive status in Parkinson's disease." CNS Neuroscience & Therapeutics, September 17, 2023. http://dx.doi.org/10.1111/cns.14461.

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AbstractAimAberrations in brain connections are implicated in the pathogenesis of Parkinson's disease (PD). We previously demonstrated that Glial cell‐derived neurotrophic factor (GDNF) reduction is associated with cognition decline. Nonetheless, it is elusive if the pattern of brain topological connectivity differed across PD with divergent serum GDNF levels, and the accompanying profile of cognitive deficits has yet to be determined.MethodsWe collected data on the participants' cognition, demographics, and serum GDNF levels. Participants underwent 3.0T magnetic resonance imaging, and we asse

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Khan, M. Jaleed, Filip Ilievski, John G. Breslin, and Edward Curry. "A survey of neurosymbolic visual reasoning with scene graphs and common sense knowledge." Neurosymbolic Artificial Intelligence, May 13, 2024, 1–24. http://dx.doi.org/10.3233/nai-240719.

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Combining deep learning and common sense knowledge via neurosymbolic integration is essential for semantically rich scene representation and intuitive visual reasoning. This survey paper delves into data- and knowledge-driven scene representation and visual reasoning approaches based on deep learning, common sense knowledge and neurosymbolic integration. It explores how scene graph generation, a process that detects and analyses objects, visual relationships and attributes in scenes, serves as a symbolic scene representation. This representation forms the basis for higher-level visual reasonin

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Qin, Yong, Zeshui Xu, Xinxin Wang, and Marinko Škare. "Fuzzy decision-making in tourism and hospitality: A bibliometric review." Journal of Intelligent & Fuzzy Systems, January 27, 2029, 1–26. http://dx.doi.org/10.3233/jifs-236618.

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Fuzzy decision-making is increasingly becoming a pivotal approach to solving complex and intricate issues in tourism and hospitality management. The primary objective of this study is to unveil the developmental status, key themes and research trends within fuzzy decision-making in tourism and hospitality management (FDMTH) using Bibliometrix, CorText Manager and VOSviewer tools. As such, we conduct a comprehensive bibliometric and content-wise analysis of selected 341 publications concerning FDMTH. For one thing, we use valuable bibliometric indicators to conduct a general feature peek and pe

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Mandea, M. C., C. C. Beladan, B. Cergan, et al. "Correlations between ventricular arterial coupling and myocardial work indices in healthy subjects: a speckle tracking echocardiography study." European Heart Journal - Cardiovascular Imaging 26, Supplement_1 (2025). https://doi.org/10.1093/ehjci/jeae333.312.

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Abstract Background The interaction between left ventricular (LV) function and arterial afterload, defined as ventricular-arterial coupling (VAC), is a key determinant of cardiovascular (CV) performance. The echocardiographic assessment of VAC by the ratio of effective arterial elastance (Ea) to LV end-systolic elastance (Ees) is the most used non-invasive method. Recently, the myocardial work index (MWI) is proposed as a novel VAC non-invasive method. This method, integrating LV pressure (using a brachial cuff), and LV global longitudinal strain (GLS) by speckle tracking echocardiography (STE

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Zippari, Caterina, Rachele Nieri, Zeinab Hamouche, et al. "Substrate-borne vibrations produced during the interaction with natural enemies alter aphids probing behavior." Journal of Pest Science, March 30, 2024. http://dx.doi.org/10.1007/s10340-024-01761-6.

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AbstractThe “ecology of fear”, i.e., physiological and behavioral alterations displayed by pests in response to predation risk, has recently been proposed as a sustainable alternative to chemicals for pest control. However, the development of such a strategy requires a detailed understanding of the signals and cues underlying the pest-antagonist interaction and eliciting the prey behavioral alteration. Here, we characterized the substrate-borne vibrations produced during the interaction between the green peach aphid Myzus persicae and its antagonists, the parasitoid wasp Aphidius colemani and

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