Search Results (104)

SARS-CoV-2 infection is associated with not only acute respiratory symptoms but is also characterized by strong neurotropism which may contribute to the development of the multisystem post-COVID syndrome (PASC). Patients frequently report chronic neurocognitive disorders such as brain fog, significant attention deficits and increased susceptibility to epileptiform discharges. The aim of this review is to systematize the knowledge regarding deviations in quantitative electroencephalography (QEEG) recordings in convalescents and to evaluate the utility of this method as an objective biomarker. This work constitutes a comprehensive literature review integrating the latest data on neuroinflammation, blood-brain barrier damage and changes in cortical oscillatory dynamics induced by the infection. The literature analysis indicates that the virus may induce a pathological excitation and inhibition imbalance (E/I imbalance) in neuronal networks. In QEEG studies this manifests as excessive activity of slow bands (Theta, Delta), a deficit of rhythms responsible for attention and sensorimotor integration (SMR) and a pathologically elevated Theta to Beta ratio (TBR). In conclusion, QEEG can serve as an objective and highly sensitive tool supporting the diagnosis and stratification of patients with neurocognitive complications of Long COVID. The integration of precise electrophysiological phenotyping with targeted behavioral neuromodulation (e.g., EEG-Biofeedback) fits into the paradigm of personalized medicine and offers a prospective strategy for mitigating long-term neurological burdens. Full article

Tartrazine (E102), a synthetic azo dye, is extensively utilized across diverse industrial sectors. Understanding the mechanisms of tartrazine degradation and identifying its breakdown products are essential for assessing its environmental fate and potential health risks. Tartrazine is studied in this work in terms of: (i) determining its concentration in a commercial food dye by use the Briggs–Rauscher (BR) oscillatory (clock) reaction as seldom-employed analytical method, (ii) examining its degradation in a highly oxidative system, such as the BR oscillatory reaction, using Raman and FTIR spectroscopy, and (iii) monitoring the degradation process in the BR system at different magnifications using optical and scanning electron microscopy (SEM). The limits of detection (LOD) and quantification (LOQ) obtained for the BR reaction were higher than those determined by UV-Vis spectroscopy. Both methods determined comparable concentrations of tartrazine in the food dye. Based on the results obtained, the reaction mechanism for tartrazine degradation in the clock reaction was proposed. The findings strongly support the BR reaction as an easily available method for determining unknown concentrations of tartrazine in commercial food dyes. Furthermore, this study highlights the potential of the BR reaction for determining microconcentrations and for the rapid degradation of commercial food dyes. Full article

In order to evade interception, advanced aircraft often adopt jump-gliding trajectories to efficiently utilize aerodynamics and achieve complex maneuvers. Precise guidance of UAVs for intercepting such targets is critically challenged due to their high speed and uncertain maneuvers. For terminal guidance scenarios, the extremely short engagement window necessitates strict convergence within the predefined finite time. While PPC offers a promising framework to ensure such convergence with guaranteed transient performance, it suffers from singularity when target uncertainties drive tracking errors beyond performance bounds. To address these challenges, this paper proposes an adaptive prescribed-performance guidance law with predefined-time convergence for UAVs. Built upon the analysis that jump-gliding targets exhibit predominantly longitudinal oscillatory maneuvers, we first establish a velocity model to characterize their motion uncertainties. Using the derived uncertainty bounds and estimated parameters, a predefined-time performance function (PPF) is then developed and robustly modified to eliminate the singularity risk. By integrating this modified PPC with an adaptive law, the proposed framework achieves robust predefined-time convergence of the line-of-sight angle while simultaneously compensating for unknown target maneuvers. Theoretical analysis verifies the framework’s stability, and simulation results demonstrate its effectiveness in intercepting highly maneuverable targets. Full article

Cerebral aneurysms and arteriovenous malformations are life-threatening hemodynamic pathologies of the brain. While surgical intervention is often essential to prevent fatal outcomes, it carries significant risks both during the procedure and in the postoperative period, making the management of these conditions highly challenging. Parameters of cerebral blood flow, routinely monitored during medical interventions or with modern noninvasive high-resolution imaging methods, could potentially be utilized in machine-learning-assisted protocols for risk assessment and therapeutic prognosis. To this end, we developed a linear oscillatory model of blood velocity and pressure for clinical data acquired from neurosurgical operations. Using the method of Sparse Identification of Nonlinear Dynamics (SINDy), the parameters of our model can be reconstructed online within milliseconds from a short time series of the hemodynamic variables. The identified parameter values enable automated classification of the blood-flow pathologies by means of logistic regression, achieving a balanced accuracy of 74%. Our results demonstrate the potential of this model for both diagnostic and prognostic applications, providing a robust and interpretable framework for assessing cerebral blood vessel conditions. Full article

Triple-negative breast cancer (TNBC) is an aggressive subtype with limited treatment options. Emerging evidence shows that mechanotransduction, driven by matrix stiffness and mechanical signaling, promotes TNBC invasion and metastasis. As breast cancer progresses, expansion of fibroblasts and tumor-reactive stroma increases extracellular matrix deposition, generating matrix tension and enhancing mechanotransduction, which promotes cell proliferation, invasion, and metastatic potential through altered gene expression patterns. To investigate the molecular mechanisms underlying these changes, human TNBC cells were subjected to constant or oscillatory strain, followed by comprehensive transcriptomic analysis. Results revealed pronounced differential expression of genes involved in cell migration, adhesion, and transforming growth factor-β (TGFβ) signaling, with RT-PCR validation confirming SKI Like Proto Oncogene (SKIL) as the most strongly upregulated gene. Analysis of The Cancer Genome Atlas (TCGA) datasets indicated that SKIL is highly expressed in multiple breast cancer subtypes. Cross-sectional comparison of oscillatory strain-induced genes with TCGA data revealed coordinated upregulation of TGFβ, SKIL, and other genes associated with invasive phenotypes, immune suppression, and drug resistance, highlighting the vital role of TGFβ signaling. Transcription factor enrichment analysis further identified regulators linked to oncogenic pathways, including TGFβ effectors and Hippo signaling, supporting a mechanotransduction-driven transcriptional program in breast cancer. Full article

Stochastically forced nonlinear wave systems are commonly associated with complex dynamical behavior, although little is known about the general interaction of nonlinear dispersion, irrational forcing frequencies, and multiplicative noise. To fill this gap, we consider a generalized stochastic SIdV equation and examine the effects of deterministic and stochastic influences on the long-term behavior of the equation. The PDE was modeled using a stochastic traveling-wave transformation that simplifies it into a planar system, which was studied using Darboux-seeded constructions, Poincaré maps, bifurcation patterns, Lyapunov exponents, recurrence plots, and sensitivity diagnostics. We discovered that natural, implicit, and unique seeds produce highly diverse transformed wave fields exhibiting both irrational and golden-ratio forcing, controlling the transition from quasi-periodicity to chaos. Stochastic perturbation is demonstrated to suppress as well as to amplify chaotic states, based on noise levels, altering attractor geometry, predictability, and multistability. Meanwhile, OGY control is demonstrated to be able to stabilize chosen unstable periodic orbits of the double-well regime. A stochastic bifurcation analysis was performed with respect to noise strength $\sigma$, revealing that the attractor structure of the system remains robust under stochastic excitation, with noise inducing only bounded fluctuations rather than qualitative dynamical transitions within the investigated parameter regime. These findings demonstrate that the emergence, deformation, and controllability of complex oscillatory patterns of stochastic nonlinear wave models are jointly controlled by nonlinear structure, external forcing, and noise. Full article

Conventional polymer-based plugging materials often fail in deep-well environments due to passive thermal softening and network relaxation, which significantly compromise mechanical integrity and interfacial retention. To address this challenge, a novel smart Upper Critical Solution Temperature (UCST)-responsive hybrid microgel (SUPA) was synthesized for adaptive plugging in complex formations. The distinctive UCST responsiveness was conferred by incorporating N-(2-amino-2-oxoethyl)acrylamide (NAGA) and N-(2-hydroxypropyl) methacrylamide (HPMA) functional units into a robust dual-crosslinked network. Particle size analysis and oscillatory rheology in saline solution revealed the thermal activation mechanism: surpassing the critical temperature triggers the dissociation of intramolecular hydrogen bonds, driving polymer chain extension and volumetric expansion. This conformational transition induces dynamic network reinforcement, quantified by a significant ~7.5-fold increase in the storage modulus (G′). Consequently, the SUPA-enhanced fluid exhibited superior rheological performance, including a 4.4-fold increase in low-shear viscosity and rapid thixotropic recovery (ratio of 1.06). Crucially, lost circulation tests confirmed reliable and highly efficient sealing performance under harsh conditions of 150 °C and 5 MPa, even in fractured models. This study validates a design strategy centered on UCST-activated network reinforcement, offering a robust, mechanism-driven solution for severe lost circulation control in deep-well drilling. Full article

The transient dynamics of electromagnetically induced transparency (EIT) are fundamental to understanding coherent light–atom interactions and the advancement of quantum technologies such as optical switching and quantum memory. However, in room-temperature atomic vapors, Doppler broadening significantly alters these dynamics, yet a comprehensive understanding of its impact on the transient EIT response remains lacking. In this study, we combine analytical and numerical methods to investigate the absorption dynamics of a weak probe field in a three-level Λ-type system driven by a strong coupling field, based on the optical Bloch equations and Laplace transform techniques. Our results show that the transient response is highly sensitive to both the atomic spontaneous emission rate and the Rabi frequency of the coupling field. Increasing the coupling field intensity not only accelerates the approach to steady state but also induces oscillatory dynamics and negative absorption. Under Doppler broadening, the time required to reach steady state increases by approximately three orders of magnitude compared to the Doppler-free case—an effect that is surprisingly insensitive to temperature variations across the 100–400 K range. Moreover, restoring a short steady-state time under broadened conditions necessitates increasing the coupling laser intensity by two orders of magnitude. These findings provide key insights into the influence of Doppler broadening on coherent transient processes and offer practical guidelines for the design of room-temperature atomic devices, including quantum memories and optical modulators. Full article

Pipelines and power cables are critical infrastructures in coastal areas for transporting energy resources from offshore renewable installations to onshore grids. It is important to investigate the hydrodynamic forces on pipelines and cables and their surrounding flow fields, which are highly related to their on-bottom stability. The time-varying hydrodynamic forces coefficients and unsteady surrounding flows of a near-seabed pipeline subjected to a wave-induced oscillatory boundary layer flow are studied through numerical simulations. The Keulegan–Carpenter numbers of the oscillatory flow are up to 400, which are defined based on the maximum undisturbed near-bed orbital velocity, the pipeline diameter and the period of the oscillatory flow. The investigated Reynolds number is set to $1\times {10}^4$, defined based on $U_w$ and $D$. The influences of different seabed roughness ratios $k_s/D$ (where $k_s$ is the Nikuradse equivalent sand roughness) up to 0.1 on the hydrodynamic forces and the flow fields are considered. Both a wall-mounted pipeline with no gap ratio to the bottom wall and a pipeline with different gap ratios to the wall are investigated. The correlations between the hydrodynamic forces and the surrounding flow patterns at different time steps during one wave cylinder are analyzed by using the force partitioning method and are discussed in detail. It is found that there are influences of the increasing $k_s/D$ on the force coefficients at large $\mathrm{K}\mathrm{C},$ while for the small $\mathrm{K}\mathrm{C}$, the inertial effect from the oscillatory flow dominates the force coefficients with small influences from different $k_s/D$. The FPM analysis shows that the elongated shear layers from the top of the cylinder contribute to the peak values of the drag force coefficients. Full article

Myanmar blue jadeite jade is a rare and highly prized gemstone, yet its coloration and formative mechanisms remain poorly understood. In this study, petrographic analysis, ultraviolet–visible (UV–Vis) spectroscopy, electron probe microanalysis (EPMA), and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) were performed on a sample of Myanmar blue jadeite with small white blocks to investigate its mineral composition, trace element distribution, and coloration mechanisms. Most of the sample was found to be blue, with surrounding white areas occurring in small ball-shaped blocks. The main mineral component in both the blue and white domains was jadeite. Although both areas underwent recrystallization, their textures differed significantly. The blue areas retained primary structural features within a medium- to fine-grained texture, reflecting relatively weaker recrystallization. The white areas, however, were recrystallized into a micro-grained texture, reflecting relatively stronger recrystallization, with the superimposed effects of external stress producing a fragmented appearance. The blue jadeite had relatively higher contents of Ti, Fe, Ca, and Mg, while the white jadeite contained compositions close to those of near-end-member jadeite. It was noted that, while white jadeite may have a high Ti content, its Fe content is low. UV–Vis spectra showed a broad absorption band at 610 nm associated with Fe²⁺-Ti⁴⁺ charge transfer and a gradually increasing absorption band starting at 480 nm related to V⁴⁺. Combining the chemical composition and the characteristics of the UV–Vis spectra, we infer that the blue coloration of jadeite is attributed to Fe²⁺-Ti⁴⁺ charge transfer; i.e., the presence of both Ti and Fe in blue jadeite plays a key role in its color formation. V⁴⁺ exhibited no significant linear correlation with the development of blue coloration. Prominent oscillatory zoning was observed in the jadeite, transitioning from NaAlSi₂O₆-dominant cores to Ca-Mg-Fe-Ti-enriched rims, reflecting the trend of fluid evolution during blue jadeite crystallization. Petrographic analysis indicated that the formation of the Myanmar blue jadeite occurred in two or three stages, with the blue regions forming earlier than the white regions. The blue jadeite also underwent significant recrystallization. Our findings contribute to the understanding of the formation of blue jadeite and the diversity of colors in jadeite jade. Full article

This study presents the Fourier–Gegenbauer integral Galerkin (FGIG) method, a new numerical framework that uniquely integrates Fourier series and Gegenbauer polynomials to solve the one-dimensional advection–diffusion (AD) equation with spatially symmetric periodic boundary conditions, achieving exponential convergence and reduced computational cost compared to traditional methods. The FGIG method uniquely combines Fourier series for spatial periodicity and Gegenbauer polynomials for temporal integration within a Galerkin framework, resulting in highly accurate numerical and semi-analytical solutions. Unlike traditional approaches, this method eliminates the need for time-stepping procedures by reformulating the problem as a system of integral equations, reducing error accumulation over long-time simulations and improving computational efficiency. Key contributions include exponential convergence rates for smooth solutions, robustness under oscillatory conditions, and an inherently parallelizable structure, enabling scalable computation for large-scale problems. Additionally, the method introduces a barycentric formulation of the shifted Gegenbauer–Gauss (SGG) quadrature to ensure high accuracy and stability for relatively low Péclet numbers. This approach simplifies calculations of integrals, making the method faster and more reliable for diverse problems. Numerical experiments presented validate the method’s superior performance over traditional techniques, such as finite difference, finite element, and spline-based methods, achieving near-machine precision with significantly fewer mesh points. These results demonstrate its potential for extending to higher-dimensional problems and diverse applications in computational mathematics and engineering. The method’s fusion of spectral precision and integral reformulation marks a significant advancement in numerical PDE solvers, offering a scalable, high-fidelity alternative to conventional time-stepping techniques. Full article

This paper addresses the numerical evaluation of highly oscillatory integrals by developing a spectral Galerkin–Levin approach that efficiently solves Levin’s differential equation formulation for such integrals. The method employs Legendre polynomials as basis functions to approximate the solution, leveraging their orthogonality and favorable numerical properties. A key finding is that the Galerkin–Levin formulation is invariant with respect to the choice of polynomial basis—be it monomials or classical orthogonal polynomials—although the use of Legendre polynomials leads to a more straightforward derivation of practical quadrature rules. Building on this, this paper derives a simple and efficient numerical quadrature for both scalar and matrix-valued highly oscillatory integrals. The proposed approach is computationally stable and well-conditioned, overcoming the limitations of collocation-based methods. Several numerical examples validate the method’s high accuracy, stability, and computational efficiency. Full article

The recent identification of early-onset mutational signatures with geographic variations by Diaz-Gay et al. is a significant finding, since early-onset colorectal cancer has emerged as an alarming public health challenge in the past two decades, and the pathomechanism remains unclear. Environmental risk factors, including lifestyle and diet, are highly suspected. The identification of colibactin from Escherichia coli as a potential pathogenic source is a major step forward in addressing this public health challenge. Therefore, the following opinion manuscript aims to outline the likely onset of the pathomechanism and the critical role of acquired Piezo2 channelopathy in early-onset colorectal cancer, which skews proton availability and proton motive force regulation toward E. coli within the microbiota–host symbiotic relationship. In addition, the colibactin produced by the pks island of E. coli induces host DNA damage, which likely interacts at the level of Wnt signaling with Piezo2 channelopathy-induced pathological remodeling. This transcriptional dysregulation eventually leads to tumorigenesis of colorectal cancer. Mechanotransduction converts external physical cues to inner chemical and biological ones. Correspondingly, the proposed quantum mechanical free-energy-stimulated ultrafast proton-coupled tunneling, initiated by Piezo2, seems to be the principal and essential underlying novel oscillatory signaling that could be lost in colorectal cancer onset. Hence, Piezo2 channelopathy not only contributes to cancer initiation and impaired circadian regulation, including the proposed hippocampal ultradian clock, but also to proliferation and metastasis. Full article

Accurate online identification of abnormal sudden change observations is crucial for ensuring data reliability and has been a key challenge in dam safety monitoring. Traditional methods, such as those based on the Pauta criterion, often fail to effectively identify anomalies in complex data sequences like step-type and oscillatory-type data, primarily due to unreasonable early warning threshold settings. To address this issue, this paper introduces a novel method for setting early warning thresholds by combining the scale estimator ST based on the location M-estimator with the confidence interval radius D derived from predicted values, thereby constructing the MZ criterion with a threshold of 3ST+D. The proposed model demonstrates strong resistance to outliers and good robustness, effectively improving the accuracy of online anomaly identification for various data sequences. The MZ standard achieves a false alarm and missed detection rate of less than 10% in the monitoring data of the XB hydropower plant, which is a significant improvement in detection accuracy compared to the traditional Pauta standard. Engineering applications have shown that the MZ criterion-based identification method achieves a low misjudgment and omission rate, high recognition accuracy, and is highly reliable for online dam safety monitoring. This method holds significant value for both theoretical research and practical engineering applications. Full article

In this paper, we investigate efficient numerical methods for highly oscillatory integrals with Bessel function kernels over finite and infinite domains. Initially, we decompose the two types of integrals into the sum of two integrals. For one of these integrals, we reformulate the Bessel function $J_{\nu }(z)$ as a linear combination of the modified Bessel function of the second kind $K_{\nu }(z)$, subsequently transforming it into a line integral over an infinite interval on the complex plane. This transformation allows for efficient approximation using the Cauchy residue theorem and appropriate Gaussian quadrature rules. For the other integral, we achieve efficient computation by integrating special functions with Gaussian quadrature rules. Furthermore, we conduct an error analysis of the proposed methods and validate their effectiveness through numerical experiments. The proposed methods are applicable for any real number $\nu$ and require only the first $\lfloor \nu \rfloor$ derivatives of f at 0, rendering them more efficient than existing methods that typically necessitate higher-order derivatives. Full article