Dynamic correlation is the correlation between two time series across time. Two approaches that currently exist in neuroscience literature for dynamic correlation estimation are the sliding window method and dynamic conditional correlation. In this p...
In previous studies, information dynamics methods such as Von Neumann entropy and Rényi entropy played an important role in many fields, covering both macroscopic and microscopic studies. They have a solid theoretical foundation, but there are...
The urgent need to mitigate climate change has elevated green hydrogen as a sustainable alternative to fossil fuels, while green cryptocurrencies have emerged to address the environmental concerns of traditional cryptocurrency mining. This study inve...
Electrocardiogram waveform delineation is a fundamental task for quantitative cardiac analysis, yet accurate and consistent estimation of waveform boundaries remains challenging due to heart rate variability, inter-subject morphological differences,...
The deformation measurement of a specular surface is of great importance during the quality inspection and installation of optical elements or wafers, especially those with large apertures. We propose a deflectometry method with speckle digital image...
Based on dynamic information collected from different time intervals in some real situations, this paper firstly proposes a dynamic single valued neutrosophic multiset (DSVNM) to express dynamic information and operational relations of DSVNMs. Then,...
The traditional power grid planning lacks consideration of the uncertainty and correlation between wind and solar joint output in the same region, which poses challenges to the stable operation of the power system. Therefore, it is greatly important...
A signal processing technique is presented to improve the angular rate accuracy of Micro-Electro-Mechanical System (MEMS) gyroscope by combining numerous gyroscopes. Based on the conditional correlation between gyroscopes, a dynamic data fusion model...
Accurate traffic flow prediction in road networks is essential for intelligent transportation systems (ITS). Since traffic data are collected from the road network with spatial topological and time series sequences, the traffic flow prediction is reg...
To enhance the safety risk management and control capabilities for TBM (Tunnel Boring Machine) construction in hydraulic tunnels, this study conducts a correlation analysis and dynamic evolution study of safety risks. Data were collected through mult...
A combination of Fringe Projection (FP) and 2D Digital Image Correlation (2D DIC) using a single camera has been employed to simultaneously measure in-plane and out-of-plane displacements during different dynamic events such an impact and a vibration...
Accurate grid frequency prediction is essential for maintaining the stability and reliability of power systems. However, the complex dynamic characteristics of grid frequency and the nonlinear correlations among massive time series data make it chall...
Low Earth orbit (LEO) satellites that can be used as computing nodes are an important part of future communication networks. However, growing user demands, scarce channel resources and unstable satellite–ground links result in the challenge to...
This study presents a dynamic multi-factor correlation analysis method designed to predict provincial carbon dioxide emissions (CDE) within China’s Bohai Rim region, including Tianjin, Hebei, Shandong, and Liaoning. By employing the sliding win...
The dynamic fracture process of rock materials is of importance for several industrial applications, such as drilling for geothermal installation. Numerical simulation can aid in increasing the understanding about rock fracture; however, it requires...
Background: Cryptocurrency allocation tools that use graph learning are often judged on gross performance and rarely stress-tested under realistic trading frictions. Methods: We evaluate a regime-supervised graph-neural tangency pipeline on 33 large-...
Determining the spatial–temporal correlation (STC) between roads can help clarify the operation characteristics of road traffic. Moreover, this correlation affects the utilization quality of traffic data in related research fields. Therefore, it is o...
With the gradual expansion of mining scale in open-pit coal mines, slope safety problems are increasingly diversified and complicated. In order to reduce the potential loss caused by slope sliding and reduce the major threat to the safety of life and...
Understanding the spatiotemporal dynamics of water quality parameters and microbial communities in drinking water distribution systems (DWDS) and their interrelationships is critical for ensuring the safety of tap water supply. This study investigate...
Polylactide foaming as the key stage in laboratory preparation of highly porous biocompatible matrices used as scaffold prototypes was monitored based the effect of dynamic light scattering in expanding polylactide foams. Intensity fluctuations of sc...
To address the issue of traditional static evaluation models being unable to comprehensively analyze the performance of ultra-supercritical coal-fired units under varying loads, we propose a dynamic comprehensive evaluation model based on the improve...
Air pollution is closely associated with human health and the economy. Therefore, it is important to understand variations in the spatiotemporal and sectoral emission distributions of major air pollutants and their drivers. The policies (APAPPC) prom...
The non-Arrhenius behavior of segmental dynamics in glass-forming liquids is one of the most profound mysteries in soft matter physics. In this article, we propose a dynamically correlated network (DCN) model to understand the growing behavior of dyn...
Liquids and gases are distinct in their extent of dynamic atomic correlations; in gases, atoms are almost uncorrelated, whereas they are strongly correlated in liquids. This distinction applies also to electronic systems. Fermi liquids are actually g...
G protein-coupled Receptors (GPCRs) play a central role in many physiological processes and, consequently, constitute important drug targets. In particular, the search for allosteric drugs has recently drawn attention, since they could be more select...
The concept of spontaneous symmetry breaking and off-diagonal long-range order (ODLRO) are associated with Bose–Einstein condensation. However, as in the system of reduced dimension the effect of quantum fluctuation is dominating, the concept o...
The master equation for an open quantum system is derived in the weak-coupling approximation when the additional dynamical variable—the mean interaction energy—is included into the generic relevant statistical operator. This master equati...
Biosynthesis of heme represents a complex process that involves multiple stages controlled by different enzymes. The first of these proteins is a pyridoxal 5′-phosphate (PLP)-dependent homodimeric enzyme, 5-aminolevulinate synthase (ALAS), that...
Based on a logistic map and Feigenbaum map, we proposed a logistic Feigenbaum non-linear cross-coupled hyperchaotic map (LF-NCHM) model. Experimental verification showed that the system is a hyperchaotic system. Compared with the existing cross-coupl...
The purpose of the paper is to discuss ten things potential users should know about the limits of the Dynamic Conditional Correlation (DCC) representation for estimating and forecasting time-varying conditional correlations. The reasons given for cau...
This work is devoted to the procedure for constructing of a cyclically correlated random process of a continuous argument as a mathematical model of cyclic signals in dynamic systems, which makes it possible to consistently describe cyclic stochastic...
Accurately forecasting the dynamic linkages among carbon, energy, and stock markets is essential for effective risk management and the design of energy transition strategies. This study proposes a BOHB-optimized Multivariable Graph Neural Network (BO...
Fatigue crack in rails and cyclic-loaded train parts is a contributory factor in multiple railroad accidents. We address the problem of crack detection and measurement at early stages, when total failure has not yet occurred. We propose to combine ac...
We systematically investigate semiclassical dynamics of the optical field produced by quantum nanoemitters (NEs) embedded in a periodic lattice of conducting nanorings (NRs), in which plasmon polaritons (PPs) are excited. The coupling between PPs and...
The dynamic surface tension (DST) data and biochemical parameters (BCP) of animal blood have been obtained. A strong positive correlation was found for goats between σ1, σ2, σ3 (DST) and sodium levels (BCP), λz (DST)—with the levels of lipid and sodi...
Background: Temporomandibular joint (TMJ) disorders, which affect millions of people worldwide, have multiple etiological factors that make an accurate diagnosis and effective treatments difficult. As a consequence, the gold standard diagnostic crite...
We calculate differential Shannon entropies derived from time-dependent coordinate-space and momentum-space probability densities. This is performed for a prototype system of a coupled electron–nuclear motion. Two situations are considered, whe...
We provide the analytical gradient of the full model likelihood for the Dynamic Conditional Correlation (DCC) specification by Engle (2002), the generalised version by Cappiello et al. (2006), and of the cDCC model by Aielli(2013). We discuss how the...
A method for dynamic finite element (FE) model updating based on correlated mode auto-pairing and adaptive evolution screening (CMPES) is proposed to overcome difficulties in pairing inaccurate analytical modal data and incomplete experimental modal...
We examine non-classical correlations in separable systems through quantum dissonance and one-way quantum deficit. Our study focuses on the generation and dynamics of these correlations in hydrogen atoms influenced by dephasing and dissipative decohe...
In this paper, we consider the estimation of a dynamic panel data model with non-stationary multi-factor error structures. We adopted the common correlated effect (CCE) estimation and established the asymptotic properties of the CCE and common correl...
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Pollutant analysis and pollution source tracing are critical issues in air quality management, in which correlation analysis is important for pollutant relation modeling. A dynamic correlation analysis method was proposed to meet the real-time requir...
With the rapid development of renewable energy, microgrids are becoming more and more essential in distribution networks. However, uncertainties brought by new energy sources have posed great challenges to the energy safety and stability of distribut...
Understanding the relationship between muscle activation and deformation is essential for analyzing arm movement dynamics in both daily activities and clinical settings. Accurate characterization of this relationship impacts rehabilitation strategies...
Asphalt is widely used as a binder in pavement engineering. The temperature-dependent phase transition behavior of asphalt binders critically influences pavement performance. This study comprehensively evaluates phase transition characteristics to es...
Accurate and real-time traffic speed prediction remains challenging due to the irregularity and asymmetry of real-traffic road networks. Existing models based on graph convolutional networks commonly use multi-layer graph convolution to extract an un...
By estimating the changing of industry greenization development and ecological balance in China from 2000 to 2017, this paper aims to study the dynamic correlation between industry and ecology in recent years. We focus on the conservation of resource...
Prognostics and Health Management technologies are useful for early fault detection and optimization of reliability in mechanical systems. Reciprocating compressors units are commonly used in industry for gas pressurization and transportation, and th...
This paper aims to explore the dynamic relationships between the crude oil price (shocks) and investor sentiment. Specifically, this paper utilizes web crawler to construct Chinese investor sentiment index. The structural vector autoregression (SVAR)...
Background: Measurement of the medial longitudinal foot arch in children is a controversial topic, as there are many different methods without a definite standard procedure. The purpose of this study was to 1) investigate intraday and interrater reli...
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