Search Results (488)

In this work, redox-responsive chitosan derivatives were prepared by crosslinking with disulfide-bridged dicarboxylic acids. Taking into account that structural variations in diacids can lead to significant differences in properties, especially swelling capacity, this study aimed to evaluate the impact of increasing alkyl chain length and hydrophobicity. Two dicarboxylic acids of different hydrophobic character and chain length were used: dithiodiglycolic acid (DTGA) and dithiopropionic acid (DTPA). The resulting materials were fully characterized. Despite their structural similarity, the derivatives exhibited distinct behaviors: DTGA derivatives formed stable hydrogels, whereas DTPA ones remained compact upon contact with water. These results were confirmed by swelling measurements and oscillatory rheology. The EDC:COOH molar ratio was also evaluated, revealing a strong effect on the degree of crosslinking. Moreover, DTGA systems prepared at a 1:1 ratio showed significantly higher swelling than those synthesized at 3:1. Regarding redox responsiveness, it was assessed by quantifying thiol content before and after reduction with sodium borohydride, and reversibility was assessed through reduction–oxidation cycles. Finally, preliminary experiments evaluated the materials’ ability to incorporate benzalkonium chloride as a model biocide, and their release was tested in the presence of thiosulfate-reducing bacteria, providing initial insight into their behavior in redox-responsive delivery systems. Full article

γ-aminobutyric acid (GABA), the primary inhibitory neurotransmitter in the central nervous system (CNS), regulates neuronal excitability, synaptic plasticity, and oscillatory activity essential for cognition, emotion, and behavior. Disruptions in GABAergic signaling are increasingly recognized as key contributors to a range of neurodevelopmental disorders (NDDs), including schizophrenia (SZ), autism spectrum disorder (ASD), major depressive disorder (MDD), bipolar disorder (BD), and intellectual disability (ID). In this review, we analyze the data available from the literature concerning the components of the GABA pathway. We describe the main steps of GABA metabolism, including GABA synthesis and release, GABA receptors neurotransmission, GABA reuptake and catabolism, and evaluate their involvement in the pathogenesis of neurodevelopmental disorders. We suggest the possibility of existence of so far undescribed mechanisms which maintain the concentrations of GABA at a relatively physiological level when the function of glutamic acid decarboxylases is compromised by mutations. Searching for these mechanisms could be important for better understanding neurodevelopment and could give a clue for future searches for new therapeutic approaches for treating or alleviating the symptoms of BD and SZ. We also argue that the metabolic stage of the GABA pathway has only a minor direct effect on GABA signaling and rather causes clinical effects due to accumulation of neurotoxic byproducts. Full article

The common iliac artery supplies blood to the lower extremities, and stenosis in this region severely impacts hemodynamics. This study investigates the effects of 25%, 50%, and 75% iliac artery stenosis on key hemodynamic parameters using a fluid–structure interaction (FSI) approach. Semi-idealized geometries reconstructed from patient-specific data modeled realistic arterial behavior. Parameters such as wall displacement, time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), high oscillatory low shear magnitude (HOLMES) index, and endothelial cell activation potential (ECAP) were evaluated. Results showed peak wall displacement of 2.85 mm in the bifurcation zone under 75% stenosis. TAWSS increased with stenosis severity, peaking in stenotic regions and decreasing significantly downstream. OSI was highest in non-stenosed right branches and bifurcation areas, indicating multidirectional shear forces. HOLMES values were lowest downstream of stenoses, indicating disturbed flow. ECAP exceeded the thrombosis risk threshold (1.4 Pa⁻¹) in post-stenotic zones under 75% stenosis, suggesting a higher risk of clot formation. These results demonstrate that stenosis disrupts local flow and causes hemodynamic changes downstream, emphasizing the need for comprehensive clinical assessment beyond the stenotic site. Regions with elevated ECAP and low HOLMES downstream may be prone to thrombosis, highlighting the importance of careful hemodynamic monitoring for treatment strategies. Full article

Gene expression measurements of tissues, tumors, or cell lines taken over multiple time points are valuable for describing dynamic biological phenomena such as the response to growth factors. However, such phenomena typically involve multiple biological processes occurring in parallel, making it difficult to identify and discern their respective contributions at any time point. Here, we demonstrate the use of unsupervised machine learning to deconvolve a series of time-dependent gene expression measurements into its underlying temporal components. We first downloaded publicly available RNAseq data obtained from synchronized HeLa cells at consecutive time points following release from cell cycle arrest. Then, we used Fourier analysis and Topic modeling to reveal three underlying components and their relative contributions at each time point. We identified two temporal components with oscillatory behavior, corresponding to the G1-S and G2-M phases of the cell cycle, and a third component with a transient expression pattern, associated with the immediate early response gene program, regulation of cell proliferation, and cervical cancer. This study demonstrates the use of unsupervised machine learning to identify hidden temporal components in biological systems, with potential applications to early detection and monitoring of diseases and recovery processes. Full article

Ice cream is a frozen aerated dessert composed of milk solids, sugars, stabilizers, and fat—with the latter being a key component in defining its structural and sensory properties. This study evaluated the influence of four fat sources—low-trans vegetable fat (T1), butter (T2), UHT cream (T3), and fresh cream (T4)—on the physical and structural characteristics of ice cream, including overrun, melting resistance, texture, color, and rheology, at different stages of processing (before and after maturation). Oscillatory rheological analysis revealed predominantly elastic behavior (G′ > G″) after maturation in all samples, indicating a stable viscoelastic solid structure. Formulations containing T3 and T1 showed the highest overrun values, indicating greater air incorporation, whereas the butter-based formulation (T2) showed the lowest overrun values. Melting resistance followed the following order: T3 > T4 > T2 > T1; therein, the UHT cream formulation exhibited the greatest thermal stability, which was likely due to protein denaturation and aggregation induced by high-temperature processing. Texture analysis showed that the T1 formulation required the lowest maximum extrusion force, while T2 required the highest, reflecting an inverse correlation with overrun values. T1 also displayed the most distinct rheological profile, which was likely due to its specific crystallization behavior and reduced destabilization of the fat globule membrane—which favored the development of a more structured internal network. These findings demonstrate that both the source and processing of fat have a significant impact on the formation of the structural matrix and the final functional properties of ice cream. The results offer technical insights for the development of formulations tailored to specific physical characteristics, optimizing texture, stability, and performance throughout the production process. Full article

This study presents a comparative analysis of horizontal-axis wind turbines (HAWTs) equipped with and without bio-inspired active oscillating vortex generators (VGs). The experimental investigation examines key aspects of mechanical integration and the resulting variations in aerodynamic behavior, demonstrating measurable improvements in electrical power output. The VGs were designed and implemented using servomechanisms and embedded control systems to enable oscillatory motion during operation. Experimental findings were validated against CFD simulations, indicating that the use of VGs increases annual energy production efficiency by 16.7%, primarily due to the stabilization of wake turbulence. While a reduction in output voltage was observed at wind speeds below 5 m/s, the VGs exhibited enhanced performance under variable wind conditions. These results highlight the potential of combining biomimetic design principles with electronically actuated flow-control devices to advance HAWT technology, improving energy efficiency and contributing to operational sustainability. Full article

The greater cane rat algorithm (GCRA) is a swarm intelligence algorithm inspired by the discerning and intelligent foraging behavior of the greater cane rats, which facilitates mating during the rainy season and non-mating during the dry season. However, the basic GCRA exhibits serious drawbacks of high parameter sensitivity, insufficient solution accuracy, high computational complexity, susceptibility to local optima and overfitting, poor dynamic adaptability, and a severe curse of dimensionality. In this paper, a hybrid nonlinear greater cane rat algorithm with sine–cosine algorithm named (SCGCRA) is proposed for resolving the benchmark functions and constrained engineering designs; the objective is to balance exploration and exploitation to identify the globally optimal precise solution. The SCGCRA utilizes the periodic oscillatory fluctuation characteristics of the sine–cosine algorithm and the dynamic regulation and decision-making of nonlinear control strategy to improve search efficiency and flexibility, enhance convergence speed and solution accuracy, increase population diversity and quality, avoid premature convergence and search stagnation, remedy the disequilibrium between exploration and exploitation, achieve synergistic complementarity and reduce sensitivity, and realize repeated expansion and contraction. Twenty-three benchmark functions and six real-world engineering designs are utilized to verify the reliability and practicality of the SCGCRA. The experimental results demonstrate that the SCGCRA exhibits certain superiority and adaptability in achieving a faster convergence speed, higher solution accuracy, and stronger stability and robustness. Full article

Recent studies on semi-dilute Calf-Thymus DNA (CT-DNA) solutions have revealed the presence of birefringence and small-scale textures influenced by shear and ionic strength. In this study, we investigate these phenomena on the same solutions to elucidate the underlying shear-induced supramolecular organization and relaxation dynamics using rheo-birefringence, rheology, and rheo-SAXS (small-angle X-ray scattering). Static SAXS confirmed concentration-dependent inter-chain correlations in the 15–25 nm range, while rheology revealed a slipping yield-stress behavior. Oscillatory strain sweep and steady state rheo-birefringence experiments correlated the appearance of textures with the onset of flow and a stress plateau observed over a shear rate range from approximately 1 to 1000 s⁻¹. Transient rheo-birefringence and rheo-SAXS revealed two distinct relaxation mechanisms on well-separated time scales: a fast process lasting a few seconds, inversely proportional to the shear rate, consistent with the orientational relaxation of DNA segments on a ~20 nm scale; and a slower relaxation over tens of seconds, independent of the shear rate, associated with the disappearance of textures, and attributed to a diffusive process. These findings provide significant insights into the mechanisms governing DNA organization and dynamics in semi-dilute solutions under flow and highlight the need for temporally resolved start-up rheo-SAXS and rheo-birefringence measurements, as well as theoretical models describing these processes across various spatial and temporal scales. Full article

Previous studies have suggested that the back-reaction of super-Hubble cosmological fluctuations on a symmetric background space-time, with respect to being homogeneous and isotropic, could behave like a dynamical relaxation of the cosmological constant. Moreover, this mechanism appears to be self-regulatory, potentially leading to oscillatory behavior in the effective DE. Such an effect would occur in any cosmological model with super-Hubble matter fluctuations, including the standard $\mathrm{\Lambda }$CDM model. Apart from that, recent DESI data, which indicate that DE may be dynamical, have renewed interest in exploring scenarios leading to such an oscillatory behavior. In this study, we propose a parameterization to account for the impact of super-Hubble fluctuations on the background energy density of the Universe. We model the total effective cosmological constant as the sum of a constant and an oscillating contribution. We performed a preliminary comparison of the background dynamics of this model with recent radial BAO data from DESI. We also discuss the status of the $H_0$ tension problem in this model. Full article

Background: Intuitive inquiry meditation (Can-Hua-Tou) is a unique mental practice which differs from relaxation-based practices by continuously demanding intuitive inquiry. It emphasizes the doubt-driven self-interrogation, also referred to as Chan/Zen meditation. Nonetheless, its electrophysiological signature remains poorly characterized. Methods: We recorded 128-channel EEG from 20 male Buddhist monks (5–28 years Can-Hua-Tou experience) and 18 male novice lay practitioners (<0.5 year) during three counter-balanced eyes-closed blocks: Zen inquiry meditation (ZEN), a phonological control task silently murmuring “A-B-C-D” (ABCD), and passive resting state (REST). Power spectral density was computed for alpha (8–12 Hz), beta (12–30 Hz) and gamma (30–45 Hz) bands and mapped across the scalp. Mixed-design ANOVAs and electrode-wise tests were corrected with false discovery rate (p < 0.05). Results: Alpha power increased globally with eyes closed, but condition- or group-specific effects did not survive FDR correction, indicating comparable relaxation in both cohorts. In contrast, monks displayed a robust beta augmentation, showing significantly higher beta over parietal-occipital leads than novices across all conditions. The most pronounced difference lay in the gamma band: monks exhibited trait-like fronto-parietal gamma elevations in all three conditions, with additional, though sub-threshold, increases during ZEN. Novices showed negligible beta or gamma modulation across tasks. No significant group × condition interaction emerged after correction, yet only experts expressed concurrent beta/gamma amplification during meditative inquiry. Conclusions: Long-term Can-Hua-Tou practice is associated with frequency-specific neural adaptations—stable high-frequency synchrony and state-dependent beta enhancement—consistent with Buddhist constructs of citta-ekāgratā (one-pointed concentration) and vigilance during self-inquiry. Unlike mindfulness styles that accentuate alpha/theta, Chan inquiry manifests an oscillatory profile dominated by beta–gamma dynamics, underscoring that different contemplative strategies sculpt distinct neurophysiological phenotypes. These findings advance contemplative neuroscience by linking intensive cognitive meditation to enduring high-frequency cortical synchrony. Future research integrating cross-frequency coupling analyses, source localization, and behavioral correlates of insight will further fully delineate the mechanisms underpinning this advanced contemplative expertise. Full article

This study investigated the aerodynamic structures generated by transverse jet injection in supersonic flows around high-speed vehicles. The unsteady evolution of these structures was analyzed using an improved delayed detached Eddy simulation (IDDES) approach based on the Reynolds stress model (RSM). The simulations successfully reproduced experimentally observed shock systems and vortical structures. The time-averaged flow characteristics were compared with the experimental results, and good agreement was observed. The flow characteristics were analyzed, with particular emphasis on the formation of counter-rotating vortex pairs in the downstream region, as well as complex near-field phenomena, such as flow separation and shock wave/boundary layer interactions. Time-resolved spectral analysis at multiple monitoring locations revealed the presence of a global oscillation within the flow dynamics. Within these regions, pressure fluctuations in the recirculation zone lead to periodic oscillations of the upstream bow shock. This dynamic interaction modulates the instability of the windward shear layer and generates large-scale vortex structures. As these shed vortices convect downstream, they interact with the barrel shock, triggering significant oscillatory motion. To further characterize this behavior, dynamic mode decomposition (DMD) was applied to the pressure fluctuations. The analysis confirmed the presence of a coherent global oscillation mode, which was found to simultaneously govern the periodic motions of both the upstream bow shock and the barrel shock. Full article

This study presents a comprehensive analysis of climate evolution in the Porto region (Northern Portugal) using 148 years (1863–2010) of continuous meteorological data from the Serra do Pilar weather station (WMO station 08546). The research employs both traditional linear statistical methods and advanced non-linear analysis techniques, including polynomial trend fitting and multidecadal oscillation analysis, to accurately characterize long-term climate patterns. Results reveal that linear trend analysis is misleading for this dataset, as both temperature and precipitation follow parabolic (U-shaped) distributions with minima around 1910–1970. The early period (1863–1900) exhibited higher values than the recent period, contradicting linear trend interpretations. Advanced analysis shows that the mean temperature follows a parabolic pattern (R² = 0.353) with the minimum around 1935, while precipitation exhibits similar behavior (R² = 0.053) with the minimum around 1936. Multidecadal oscillations are detected with dominant periods of 46.7, 15.6, and 10.0 years for temperature, and 35.0, 17.5, and 4.5 years for precipitation. Maximum temperatures show complex oscillatory behavior with a severe drop around 1890. Seasonal analysis reveals distinct patterns across all seasons: winter (+0.065 °C/decade) and autumn (+0.059 °C/decade) show warming trends in maximum temperatures, while spring (−0.080 °C/decade) and summer (−0.079 °C/decade) demonstrate cooling trends in minimum temperatures, with no significant trends in spring (+0.012 °C/decade) and summer (+0.003 °C/decade) maximum temperatures or winter (−0.021 °C/decade) and autumn (−0.035 °C/decade) minimum temperatures. The study identifies a significant change point in mean temperature around 1980, which occurs approximately one decade earlier than the global warming acceleration typically observed in the 1990s, suggesting regional Atlantic influences may precede global patterns. Extreme event analysis indicates stable frequencies of hot days (averaging 3.6 days/year above 25.0 °C) and heavy precipitation events (averaging 1.2 days/year above 234.6 mm) throughout the study period. These findings demonstrate that the Porto region’s climate is characterized by natural multidecadal variability rather than monotonic trends, with the climate system showing oscillatory behavior typical of Atlantic-influenced coastal regions. The results contribute to understanding regional climate variability and provide essential baseline data for climate change adaptation strategies in Northern Portugal. The results align with broader patterns of natural climate variability in the Iberian Peninsula while highlighting the importance of non-linear analysis for comprehensive climate assessment. Full article

This paper presents some oscillation criteria for second-order half-linear dynamic equations defined on unbounded above arbitrary time scales. These criteria offer sufficient conditions for all solutions of the equations to display oscillatory behavior. We investigate both delay and advanced cases of these equations, and our approach encompasses a broader class of dynamic equations than previously considered in the literature. The results of this study not only generalize well-known oscillation criteria used in differential equations but also significantly broaden their applicability to arbitrary time scales. Additionally, we provide illustrative examples to demonstrate the relevance and accuracy of our findings. Full article

The concept of fuzzy modeling and fuzzy system design has opened new horizons of research in functional analysis, having a significant impact on major fields such as data science, machine learning, and so on. In this research, we use fuzzy set theory to analyze the global dynamics and oscillatory behavior of nonlinear fuzzy difference equations with exponential decay. We discuss the stability, oscillatory patterns, and convergence of solutions under different initial conditions. The exponential structure simplifies the analysis while providing a clear understanding of the system’s behavior over time. The study reveals how fuzzy parameters influence growth or decay trends, emphasizing the method’s effectiveness in handling uncertainty. Our findings advance the understanding of higher-order fuzzy difference equations and their potential applications in modeling systems with imprecise data. Using the characterization theorem, we convert a fuzzy difference equation into two crisp difference equations. The g-division technique was used to investigate local and global stability and boundedness in dynamics. We validate our theoretical results using numerical simulations. Full article

In multimodal collaborative learning, the gradient dynamics of heterogeneous modalities face significant challenges due to the curvature heterogeneity of parameter manifolds and mismatches in phase evolution. Traditional Euclidean optimization methods struggle to capture the complex interdependencies between heterogeneous modalities on non-Euclidean or geometrically inconsistent parameter manifolds. Furthermore, static alignment strategies often fail to suppress bifurcations and oscillatory behaviors in high-dimensional gradient flows, leading to unstable optimization trajectories across modalities. To address these issues, inspired by hyperbolic geometry and symplectic structures, this paper proposes the Hyperbolic Cosine-Based Symplectic Phase Alignment (HC-SPA) fusion optimization framework. The proposed approach leverages the geometric properties of hyperbolic space to coordinate gradient flows between modalities, aligns gradient update directions through a phase synchronization mechanism, and dynamically adjusts the optimization step size to adapt to manifold curvature. Experimental results on public fusion and semantic segmentation datasets demonstrate that HC-SPA significantly improves multimodal fusion performance and optimization stability, providing a new optimization perspective for complex multimodal tasks. Full article