Real-time Correlation Research Articles

Simulation methods realized by virtual reality modeling language for 3D animation considering fuzzy model recognition.

The creation of 3D animation increasingly prioritizes the enhancement of character effects, narrative depth, and audience engagement to address the growing demands for visual stimulation, cultural enrichment, and interactive experiences. The advancement of virtual reality (VR) animation is anticipated to require sustained collaboration among researchers, animation experts, and hardware developers over an extended period to achieve full maturity. This article explores the use of Virtual Reality Modeling Language (VRML) in generating 3D stereoscopic forms and environments, applying texture mapping, optimizing lighting effects, and establishing interactive user responses, thereby enriching the 3D animation experience. VRML's functionality is further expanded through the integration of script programs in languages such as Java, JavaScript, and VRML Script via the Script node. The implementation of fuzzy model recognition within 3D animation simulations enhances the identification of textual, musical, and linguistic elements, resulting in improved frame rates. This study also analyzes the real-time correlation between the number of polygons and frame rates in a virtual museum animation scene. The findings demonstrate that the frame rate of the 3D animation within this virtual setting consistently exceeds 40 frames per second, thereby ensuring robust real-time performance, preserving the quality of 3D models, and optimizing rendering speed and visual effects without affecting the system's responsiveness to additional functions.

Emergent spacetime and the ergodic hierarchy

Various diagnostics of the emergence of an arrow of time in the bulk description of a holographic theory have been proposed, including the decay of some real time correlation functions and the appearance of type III1 von Neumann algebras carrying half-sided modular inclusions. This Letter puts forward a close parallel between these diagnostics and a quantum formulation of the ergodic hierarchy of dynamical systems. Theories with an emergent spacetime appear to sit near the top of this hierarchy. Published by the American Physical Society 2024

Trans-Clot MAP gradient: A novel innovative technique during thrombectomy for acute ischemic stroke with potential applications for assessing collateral circulation, determining clot etiology, informing device selection, and predicting first-pass success.

Endovascular mechanical thrombectomy has significantly improved recovery in acute ischemic stroke (AIS). While traditional patient selection has relied on factors such as last known well and penumbra volume, emerging research highlights the importance of collateral circulation in influencing thrombectomy success. However, current methods to assess collateral circulation are often unreliable and lack standardization, limiting their integration into clinical decision-making and prompting the need for innovative approaches. This study introduces trans-clot manometry as a promising approach for quantitatively assessing collateral blood flow before thrombectomy. Two patients were included in this study: a 64-year-old female with a left M1 near-complete occlusion and an 81-year-old male with a left P1 occlusion. After receiving intravenous tenecteplase, each patient underwent emergent thrombectomy where intraoperative trans-clot manometry revealed significant trans-clot mean arterial pressure (MAP) gradients (66.7% for Patient 1 and 96.9% for Patient 2). Both patients had successful first-pass thrombectomy (Patient 1: TICI 3; Patient 2: TICI 3), with substantial clinical improvement (Patient 1: NIHSS 11 to 1; Patient 2: NIHSS 19 to 8). Intraoperative trans-clot manometry offers a simple yet powerful, objective, and generalizable measure of collateral circulation, applicable to a wide range of AIS cases regardless of clot location or vessel size. In addition, real-time correlations with heart-rate variability and radial artery pressures provide an intrinsic quality control, ensuring proper execution of the technique and accuracy of the resulting MAP gradient. Future research will focus on validating this approach, determining its generalizability, and establishing MAP gradient thresholds to enhance device selection and predict first-pass success.

EMG model calibration and trajectory tracking of rehabilitation exoskeleton by asynchronous tele-training

ABSTRACT This study presents a novel kinematic tracking model, designed for a networked exoskeleton system that is asynchronously taught by a remote therapist. The therapist’s rehabilitation exercises are quantitatively assessed using a monocular vision system. The resultant metrics are then transmitted asynchronously over the network to patients equipped with exoskeletons. The exoskeleton utilises these metrics as reference paths for exercises, complemented by electromyography (EMG) feedback. This work introduces a calibration approach aimed at estimating angular positions by utilising EMG observations. The calibration model establishes real-time correlations between polynomial reference positions. We further explore redundant kinematics, incorporating an EMG observer for linear, time-variant rehabilitation tracking control. Our methodology is validated using vision-based metric data and experimental EMG measurements including shoulder flexion, elbow flexion, and rowing-like movements. Computer simulations demonstrate the system’s ability to reliably, robustly, and effectively follow desired trajectories. This research offers a promising approach for remote personalized rehabilitation.

Correlation functions from tensor network influence functionals: The case of the spin-boson model.

We investigate the application of matrix product state (MPS) representations of the influence functionals (IFs) for the calculation of real-time equilibrium correlation functions in open quantum systems. Focusing specifically on the unbiased spin-boson model, we explore the use of IF-MPSs for complex time propagation, as well as IF-MPSs for constructing correlation functions in the steady state. We examine three different IF approaches: one based on the Kadanoff-Baym contour targeting correlation functions at all times, one based on a complex contour targeting the correlation function at a single time, and a steady state formulation, which avoids imaginary or complex times, while providing access to correlation functions at all times. We show that within the IF language, the steady state formulation provides a powerful approach to evaluate equilibrium correlation functions.

Femtosecond Terahertz Pulse Propagation Measurements and Simulations of Dewetting Kinetics in Real Time.

We report a terahertz time-domain study of dewetting kinetics on two time scales: femtoseconds and in real time (on the order of minutes). We recorded full electric field terahertz time domain signals with femtosecond time resolution during dewetting of water in cellulose. The femtosecond time-domain signals were analyzed with respect to the amplitude and signal emission times and how these two quantities changed over the course of dewetting kinetics. The femtosecond time-domain signals were modeled by a combination of finite-difference time-domain electromagnetic simulations of linear terahertz pulse propagation and an effective medium description of the dielectric permittivity. A logistic regression mechanism was incorporated into the electrodynamics simulations to account for the observed kinetics. In addition, analysis of the area-normalized, real-time time-dependent terahertz spectra was used to identify broad regions in the terahertz spectral range that correlated with the kinetic process. Real-time two-dimensional terahertz correlation maps were used to identify the pure rotational spectrum of water vapor, thus characterizing the evaporation part of the dewetting kinetics problem. We conclude with a kinetic model that accounts for our observations through a microscopic mechanism involving the interconversion among bulk water, water clusters, and individual water molecules in the gas phase. Overall, the approach presented here illustrates an application of femtosecond time-resolved experiments in the terahertz spectral range to the study of kinetic processes.

The RNA N6-methyladenosine demethylase FTO regulates ATG5 to inhibit malignant progression of uveal melanoma

PurposeThis research aimed to identify the function of fat mass- and obesity-associated protein (FTO), an eraser of N6-methyladenosine (m6A), and explore its possible mechanisms in uveal melanoma (UVM). MethodsWe performed quantitative real-time PCR (qPCR), Western blotting and gene correlation analysis with GEPIA2 to assess FTO expression and identify its potential targets in UVM. CCK-8, colony formation, cell cycle, cell apoptosis, wound healing and Transwell invasion assays were utilized to assess cell viability, cell cycle distribution, apoptosis, migration and invasion. Western blotting, qPCR and methylated RNA immunoprecipitation–qPCR (MeRIP–qPCR) were carried out to explore the underlying mechanism of FTO in 2 UVM cell lines. ResultsFTO, a key m6A demethylase, was found to be upregulated in human UVM tissues compared with normal choroid tissues. Knockdown of FTO in Mel270 and OMM2.3 cells significantly promoted proliferation and migration and suppressed apoptosis. Mechanistically, knockdown of FTO decreased the expression of ATG5, an autophagy-related gene, leading to attenuation of autophagosome formation, thereby inhibiting autophagy. Upon FTO knockdown, increased levels of methylated ATG5 and decreased ATG5 stability were detected. Furthermore, ATG5 dramatically alleviated FTO downregulation-induced tumor growth and metastasis. ConclusionsOur research highlights the importance of the m6A demethylase FTO in UVM by demonstrating that it direct regulates ATG5-induced autophagy in an m6A-dependent manner. These findings suggest that FTO may serve as a potential therapeutic target for UVM.

Syndromic Surveillance Tracks COVID-19 Cases in University and County Settings: Retrospective Observational Study.

Syndromic surveillance represents a potentially inexpensive supplement to test-based COVID-19 surveillance. By strengthening surveillance of COVID-19-like illness (CLI), targeted and rapid interventions can be facilitated that prevent COVID-19 outbreaks without primary reliance on testing. This study aims to assess the temporal relationship between confirmed SARS-CoV-2 infections and self-reported and health care provider-reported CLI in university and county settings, respectively. We collected aggregated COVID-19 testing and symptom reporting surveillance data from Cornell University (2020-2021) and Tompkins County Health Department (2020-2022). We used negative binomial and linear regression models to correlate confirmed COVID-19 case counts and positive test rates with CLI rate time series, lagged COVID-19 cases or rates, and day of the week as independent variables. Optimal lag periods were identified using Granger causality and likelihood ratio tests. In modeling undergraduate student cases, the CLI rate (P=.003) and rate of exposure to CLI (P<.001) were significantly correlated with the COVID-19 test positivity rate with no lag in the linear models. At the county level, the health care provider-reported CLI rate was significantly correlated with SARS-CoV-2 test positivity with a 3-day lag in both the linear (P<.001) and negative binomial model (P=.005). The real-time correlation between syndromic surveillance and COVID-19 cases on a university campus suggests symptom reporting is a viable alternative or supplement to COVID-19 surveillance testing. At the county level, syndromic surveillance is also a leading indicator of COVID-19 cases, enabling quick action to reduce transmission. Further research should investigate COVID-19 risk using syndromic surveillance in other settings, such as low-resource settings like low- and middle-income countries.

Work statistics for quantum spin chains: Characterizing quantum phase transitions, benchmarking time evolution, and examining passivity of quantum states

We study three aspects of work statistics in the context of the fluctuation theorem for quantum spin chains up to 1024 sites by numerical methods based on matrix-product states (MPSs). First, we use our numerical method to evaluate the moments/cumulants of work done by the sudden quench process on the Ising or Haldane spin chains, and we study their behaviors across the quantum phase transitions. Our results show that, up to the fourth cumulant, the work statistics can indicate the quantum phase transition characterized by the local order parameters but barely for purely topological phase transitions. Second, we propose to use the fluctuation theorem, such as Jarzynski's equality, which relates the real-time correlator to the ratio of the thermal partition functions, as a benchmark indicator for the numerical real-time evolving methods. Third, we study the passivity of ground and thermal states of quantum spin chains under some cyclic impulse processes. We show that the passivity of thermal states and ground states under the Hermitian actions is ensured by the second laws and variational principles, respectively, and we also verify this by numerical calculations. In addition, we also consider the passivity of ground states under non-Hermitian actions, for which the variational principle cannot be applied. Despite that, we find no violation of passivity from our numerical results for all the cases considered in the Ising and Haldane chains. Overall, we demonstrate that the work statistics for the sudden quench and impulse processes can be evaluated precisely by the numerical MPS method to characterize quantum phase transitions and examine the passivity of quantum states. We also propose to exploit the universality of the fluctuation theorem to benchmark the numerical real-time evolutions in an algorithmic and model-independent way. Published by the American Physical Society 2024

The Fracture Evolution Mechanism of Tunnels with Different Cross-Sections under Biaxial Loading

Biaxial compression tests based on an elliptical tunnel were conducted to study the failure characteristics and the meso-crack evolution mechanism of tunnels with different cross-sections constructed in sandstone. The progressive crack propagation process around the elliptical tunnel was investigated using a real-time digital image correlation (DIC) system. Numerical simulations were performed on egg-shaped, U-shaped, and straight-walled arched tunnels based on the mesoscopic parameters of the elliptical tunnel and following the principle of an equal cross-sectional area. The meso-crack evolution and stress conditions of the four types of tunnels were compared. The results show that (1) fractures around an elliptical tunnel were mainly distributed at the end of the long axis and mainly induce slabbing failure, and the failure mode is similar to a V-shaped notch; (2) strain localization is an important characteristic of rock fracturing, which forebodes the initiation, propagation, and coalescence paths of macro-cracks; and (3) the peak loads of tunnels with egg-shaped, U-shaped, and straight-walled arched cross-sections are 98.76%, 97.56%, and 90.57% that of an elliptical cross-section. The elliptical cross-section shows the optimal bearing capacity.

Dual CFT on Nariai limit for Kerr–Sen–dS black holes

In this work, we study the Kerr–Sen–de Sitter black hole (BH) in the Nariai limit where the event and cosmological horizon coincide. We show that the near-horizon Kerr–Sen–de Sitter black hole in Nariai limit is a fiber over AdS2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document} with an appropriate coordinate transformation, instead of fiber over dS2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document}. Hence, we can compute the associated central charge and CFT temperature by using the Kerr/CFT method. It is remarkably exhibited that through Cardy’s growth of states, the Bekenstein–Hawking entropy on cosmological horizon is reproduced. Moreover, we show that the radial equation of the quantum scalar field in J- and Q-pictures on this charged rotating background in Nariai limit can be portrayed in quadratic Casimir operator form with SL(2,R)×SL(2,R)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SL(2,R)\ imes SL(2,R)$$\\end{document} isometry. We also compute the corresponding thermodynamic quantities from CFT to find the absorption cross-section and real-time correlator in J-picture. In Q-picture, we do not find a well-defined CFT description. We then extend the study of quantum scalar field in Nariai limit for Kerr–Newman–dS black hole solution and show that the hidden conformal symmetry on this black hole’s background in J- and Q-pictures is well-defined.

Boundary correlators and the Schwarzian mode

The effective low temperature dynamics of near-extremal black holes is governed by the quantum fluctuations of the Schwarzian mode of JT gravity. Utilizing as a proxy a planar charged black hole in asymptotically Anti-de-Sitter spacetime, we investigate the effects of these fluctuations on a probe scalar field. The corresponding holographic real-time boundary correlators are computed following a holographic renormalization procedure, using the dubbed gravitational Schwinger-Keldysh geometry (grSK) and known exact results of boundary correlators from the near-horizon region. This analysis gives rise to a retarded Green’s function that decays as a power law for late Lorentzian times. Its analytic structure indicates the presence of a branch cut in the complex frequency domain at finite temperature. These features are a non-perturbative hallmark that prevails as long as the planar transverse space is kept compact.

Bioturbation effect of artificial inoculation on the flavor metabolites and bacterial communities in the Chinese Mao-tofu fermentation

A comparison between artificially inoculated Mao-tofu (CC) and naturally fermented Mao-tofu (MM) indicated that artificially adding Mucor plasmaticus to Mao-tofu dramatically enhanced the essential amino acid (EAA) content, as well as umami and sweet amino acids. Gas chromatography-tandem mass spectrometry (GC–MS/MS) analysis revealed that phenol (3.226 μg/g), 1-octen-3-ol (5.031 μg/g), ethyl heptanoate (1.646 μg/g), and indole (3.422 μg/g) were the key flavor components in Mao-tofu. Unlike MM, CC displayed a substantial increase in esters and a considerable decrease in foul odor substances, including sulfur-containing compounds and indole. Lactococcus raffinolactis, Enterobacter sp. 638, and Streptococcus parauberis KCTC 11537 represented the key bacterial species altering the amino acids and flavor of Mao-tofu according to PacBio single-molecule real-time (SMRT) sequencing and correlation analysis. This study presents the technical feasibility of artificially inoculating Mao-tofu to regulate the core bacterial communities and control the quality of fermented soybean products.

Retracted: Deep Learning-Based Real-Time Discriminate Correlation Analysis for Breast Cancer Detection.

[This retracts the article DOI: 10.1155/2022/4609625.].

Real-time correlation of crystallization and segmental order in conjugated polymers.

Modulating the segmental order in the morphology of conjugated polymers is widely recognized as a crucial factor for achieving optimal electronic properties and mechanical deformability. However, it is worth noting that the segmental order is typically associated with the crystallization process, which can result in rigid and brittle long-range ordered crystalline domains. To precisely control the morphology, a comprehensive understanding of how highly anisotropic conjugated polymers form segmentally ordered structures with ongoing crystallization is essential, yet currently elusive. To fill this knowledge gap, we developed a novel approach with a combination of stage-type fast scanning calorimetry and micro-Raman spectroscopy to capture the series of specimens with a continuum in the polymer percent crystallinity and detect the segmental order in real-time. Through the investigation of conjugated polymers with different backbones and side-chain structures, we observed a generally existing phenomenon that the degree of segmental order saturates before the maximum crystallinity is achieved. This disparity allows the conjugated polymers to achieve good charge carrier mobility while retaining good segmental dynamic mobility through the tailored treatment. Moreover, the crystallization temperature to obtain optimal segmental order can be predicted based on Tg and Tm of conjugated polymers. This in-depth characterization study provides fundamental insights into the evolution of segmental order during crystallization, which can aid in designing and controlling the optoelectronic and mechanical properties of conjugated polymers.

(Keynote) Enabling Continuous Molecular Monitoring in vivo via Implantable and Wearable Aptamer-Based Sensors

The ability to continuously monitor fluctuating concentrations of specific molecules in the body can drastically improve precision medicine by allowing the real-time correlation of dynamic molecular processes with health and disease. While this ability has been pursued from multiple directions, electrochemical strategies have been successful and commercializable platforms. For example, continuous glucose monitors have dramatically improved the therapeutic management and quality of life for Type 1 diabetics. Unfortunately, the enzymatic sensing used in glucose monitors is not applicable to a large number of clinically relevant biomarkers. This limitation significantly reduces the scope of dynamic biochemical processes we can probe to study healthy human physiology and disease. In response, my laboratory is developing in vivo electrochemical aptamer-based sensors, a platform that is generalizable to the highly specific sensing of arbitrary molecular targets and supports continuous molecular monitoring in the body. In this presentation I will discuss the current state-of-the-art of these sensors, and the challenges we are addressing to enable preclinical and clinical applications.

Shock waves in holographic EPR pair

We study real-time correlators for N = 4 super Yang Mill fields coupled to a pair of entangled quarks using holography, in the setup that energy quanta sent from one quark perturb the quantum state of the fields and affect the other quark. We make the connection with the ER=EPR conjecture by considering the situation when two quarks are uniformly accelerating opposite to each other. The dynamics of quarks, in the gravity dual, is described by the string worldsheet theory, which in this case has the induced metric describing a two-sided AdS black hole, or a wormhole. Energy quanta sent by one of the quarks produce the shock wave on the worldsheet. We find the effect of shock wave on the boundary field correlators and we discuss the consequence for the ER=EPR conjecture.

Experimental investigation on the shear mechanical behavior and energy evolution of sandstone subjected to pre-peak cyclic loading

The shear mechanical behavior of rock under pre-peak cyclic shear loading is one of the key factors affecting the stability of slopes. A series of pre-peak cyclic shear tests considering the loading parameters including the number of cycles, frequency, and shear amplitude were carried out to explore the shear mechanical characteristics and energy evolution of sandstone. The results illustrated that the fatigue mechanics behavior of sandstone is highly influenced by cyclic amplitude and loading frequency. The peak shear strength is positively correlated with cyclic amplitude, while it decreases firstly and consequently increases as loading frequency rises. With the increase in cycles, the elastic and dissipated energy decrease rapidly at first and then stabilize, and the accumulated dissipated energy law is transformed from exponential to linear increase. Finally, real-time acoustic emission monitoring and digital image correlation were used to obtain the fatigue damage and crack evolution processes of rock.

Real-time diagram technique for instantonic systems

The Schwinger-Keldysh diagram technique is usually involved in the calculation of real-time in-in correlation functions. In the case of a thermal state, one can analytically continue imaginary-time Matsubara correlation functions to real times. Nevertheless, not all real-time correlation functions usually can be obtained by such procedure. Moreover, numerical analytic continuation is an ill-posed problem. Thus, even in the case of a thermal state one may need for the Schwinger-Keldysh formalism. If the potential of a system admits degenerate minima, instantonic effects enter the game, so one should also integrate over the instantonic moduli space, including the one, corresponding to the imaginary time translational invariance. However, the Schwinger-Keldysh closed time contour explicitly breaks such invariance. We argue, that this invariance must be recovered, and show, how it can be done. After that, we construct an extension of the Schwinger-Keldysh diagram technique to instantonic systems and demonstrate it on the example of the first few-point correlation functions.

Automatic Fault Diagnosis Technology of Roller Bearings of High-speed Rail Based on IFD and AE

INTRODUCTION: With the development of technology and policy support, high-speed rail's temporal and spatial layout is gradually expanding, and it becomes essential to ensure high-safety operation.&#x0D; OBJECTIVES: The real-time correlation fault diagnosis technology of critical components of electromechanical systems of high-speed trains is analyzed, and a new method of automatic fault diagnosis based on genetic support vector machine is proposed.&#x0D; METHODS: In this study, the Author combines two techniques, IFD and AE, and introduces an adaptive weighting algorithm to fuse the data of the two and experimentally verify their accuracy.&#x0D; RESULTS: The experimental results show that in the IFD experiment, the 2-point frequency at 1050 speed is 347.6 Hz, and the 3-point frequency is 498.4 Hz, both of which are very close to the 2 and 3 times frequencies of the 1-point frequency, and the multiplicative relationship is much more straightforward.&#x0D; CONCLUSION: Combining IFD and AE can realize automatic and accurate diagnosis of bearing state and pre-diagnosis of bearings by adaptive weighted fusion algorithm, which is effective in the practical mechanical diagnosis of rolling bearing faults in high-speed railroads.