Search Results (624)

The Vietnamese Mekong Delta (VMD) is experiencing accelerated coastal erosion, driven by upstream sediment trapping, sea-level rise, and local anthropogenic pressures. This study evaluates the effectiveness of pilot breakwater structures in mitigating erosion and supporting mangrove regeneration along the western coast of Ca Mau Province—one of the delta’s most vulnerable shorelines. An integrated methodology combining field-based wave monitoring, remote sensing analysis of shoreline and mangrove changes (2000–2024), and high-resolution Flow-3D hydrodynamic modeling was employed to assess the performance of four breakwater typologies: semi-circular, pile-rock, Busadco, and floating structures. The results show that semi-circular breakwaters achieved the highest wave attenuation, reducing maximum wave height (H_max) by up to 76%, followed by pile-rock (69%), Busadco (66%), and floating structures (50%). Sediment accretion and mangrove stabilization were most consistent around the semi-circular and pile-rock types. Notably, mangrove loss slowed significantly after breakwater installation, with the annual deforestation rate dropping from 7.67 ha/year (2000–2021) to 1.1 ha/year (2021–2024). Simulations further revealed that mangrove width strongly influences wave dissipation, with belts under 5 m offering minimal protection. The findings highlight the potential of hybrid coastal protection strategies that combine engineered structures with ecological buffers. Modular solutions such as floating breakwaters offer flexibility to adapt with evolving shoreline dynamics. These findings inform scalable coastal protection strategies under sediment-deficit conditions. This study contributes to Vietnam’s Coastal Development Master Plan and broader resilience efforts under Sustainable Development Goals (SDGs) 13 and 14, providing evidence to inform the design and scaling of adaptive, nature-based infrastructure in sediment-challenged deltaic environments. Full article

In the V2X environment, intelligent connected vehicles can obtain multi-dimensional traffic flow data in real time through the vehicle–road collaborative cyber–physical fusion system. Based on this, this study proposes a multi-lane traffic flow lattice model integrating optimal traffic flow difference estimation information to effectively suppress traffic congestion. The linear stability criterion of the system is derived through linear stability analysis, proving that the optimal traffic flow difference estimation can significantly expand the stable region and suppress traffic fluctuations caused by small disturbances. Furthermore, the perturbation method is used to derive the mKdV equation near the critical stability point of the system, revealing the nonlinear characteristics of traffic congestion propagating in the form of kink solitary waves, and indicating that the new consideration effect can effectively slow down the congestion propagation speed by adjusting the parameters of solitary waves (such as wave speed and amplitude). The numerical simulation results show that compared to the traditional model, the improved model exhibits enhanced traffic flow stability and robustness. Meanwhile, it reveals the nonlinear relationship between the increase of the number of lanes and the alleviation of congestion, and there is an optimal lane configuration threshold. The research results not only provide theoretical support for the optimization of traffic flow efficiency in intelligent transportation systems, but also provide a decision-making basis for dynamic lane management strategies in the V2X environment. Full article

Epidemiological studies identified insufficient and poor-quality sleep as independent risk factors for multiple sclerosis (MS). The glymphatic system, active during slow-wave sleep, clears brain waste through perivascular astrocytic aquaporin-4 (AQP4) channels. The presence of antigens induces a transient, physiological lowering of glymphatic flux as a first step of an inflammatory response. A possible hypothesis linking infection with the Epstein–Barr virus, a well identified causal step in MS, and the development of the disease is that mechanisms such as poor sleep or less functional AQP4 polymorphisms may sustain glymphatic flow reduction. Such chronic glymphatic reduction would trigger a vicious circle in which the persistence of antigens and an inflammatory response maintains glymphatic dysfunction. In addition, viral proteins that persist in demyelinated plaques can depolarize AQP4, further restricting waste elimination and sustaining local inflammation. This review examines the epidemiological evidence connecting sleep and MS risk, and the mechanistic findings showing how poor sleep and other glymphatic modulators heighten inflammatory signaling implicated in MS pathogenesis. Deepening knowledge of glymphatic functioning in MS could open new avenues for personalized prevention and therapy. Full article

Introduction: Huntington’s disease (HD) disrupts cortico-striato-thalamocortical circuits decades before clinical onset. Electroencephalography (EEG) offers millisecond temporal resolution, low cost, and broad accessibility, yet its mechanistic and biomarker potential in HD remains underexplored. We conducted a mechanistic review to synthesize half a century of EEG findings, identify reproducible electrophysiological signatures, and outline translational next steps. Methods: Two independent reviewers searched PubMed, Scopus, Google Scholar, ResearchGate, and the Cochrane Library (January 1970–April 2025) using the terms “EEG” OR “electroencephalography” AND “Huntington’s disease”. Clinical trials published in English that reported raw EEG (not ERP-only) in human HD gene carriers were eligible. Abstract/title screening, full-text appraisal, and cross-reference mining yielded 22 studies (~700 HD recordings, ~600 controls). We extracted sample characteristics, acquisition protocols, spectral/connectivity metrics, and neuroclinical correlations. Results: Across diverse platforms, a consistent spectral trajectory emerged: (i) presymptomatic carriers show a focal 7–9 Hz (low-alpha) power loss that scales with CAG repeat length; (ii) early-manifest patients exhibit widespread alpha attenuation, delta–theta excess, and a flattened anterior-posterior gradient; (iii) advanced disease is characterized by global slow-wave dominance and low-voltage tracings. Source-resolved studies reveal early alpha hypocoherence and progressive delta/high-beta hypersynchrony, microstate shifts (A/B ↑, C/D ↓), and rising omega complexity. These electrophysiological changes correlate with motor burden, cognitive slowing, sleep fragmentation, and neurovascular uncoupling, and achieve 80–90% diagnostic accuracy in shallow machine-learning pipelines. Conclusions: EEG offers a coherent, stage-sensitive window on HD pathophysiology—from early thalamocortical disinhibition to late network fragmentation—and fulfills key biomarker criteria. Translation now depends on large, longitudinal, multi-center cohorts with harmonized high-density protocols, rigorous artifact control, and linkage to clinical milestones. Such infrastructure will enable the qualification of alpha-band restoration, delta-band hypersynchrony, and neurovascular coupling as pharmacodynamic readouts, fostering precision monitoring and network-targeted therapy in Huntington’s disease. Full article

We present lightning-induced ionospheric perturbations in narrowband very-low-frequency (VLF) signals from the transmitters NWC (21.82° S, 114.17° E, 19.8 kHz) and VTX (8.4° N, 77.8° E, 18.6 kHz) recorded at the low-latitude station Dehradun (DDN; 30.3° N, 78.0° E) over a 12-month period from September 2020 to October 2021. Early/slow VLF events, VLF LOREs, and step-like VLF LOREs associated with lightning were analyzed for their onset and recovery times. This study utilized data from the World Wide Lightning Location Network (WWLLN), which provides lightning locations and energy estimates. The results show that early/slow VLF events occur most frequently, accounting for approximately 68% of cases, followed by VLF LOREs at 12%, and step-like VLF LOREs at 10%. Furthermore, we observed that 100% of the VLF perturbing events occurred during the nighttime, which is not entirely consistent with previous studies. Moreover, more than 60% of VLF LOREs were associated with lightning energies of approximately 1 kJ, and about 40% were associated with lightning energies of ~10 kJ. Step-like VLF LOREs were linked to WWLLN energies between 1 and 5 kJ. The observed WWLLN energy range is somewhat lower than the energies reported in previous studies. Scattering characteristics revealed that 87.3% of events were associated with wide-angle scattering, while approximately 12.6% were linked to narrow-angle scattering. LWPC version 2.1 was used to simulate these perturbing events and to estimate the reflection height (H′, in km) and the exponential sharpness factor (β, in km⁻¹) corresponding to changes in D-region electron density. The reflection height (H′, in km) and the exponential sharpness factor (β, in km⁻¹) of the D-region varied from 83 to 87 km and from 0.42 to 0.79 km⁻¹ for early/slow VLF events, from 83 to 85 km and from 0.5 to 0.75 km⁻¹ for step-like VLF LOREs, and from 81 to 83 km and from 0.75 to 0.81 km⁻¹ for VLF LOREs, respectively. Full article

We advance a mathematical framework for collective conviction by deriving a continuum theory from the network-based model introduced by us recently. The resulting equation governs the evolution of belief through a degenerate anisotropic logistic–diffusion process, where diffusion slows as conviction saturates. In one spatial dimension, we prove global well-posedness, demonstrate spectral front pinning that arrests the spread of influence at finite depth, and construct explicit traveling-wave solutions. In two dimensions, we uncover a geometric mechanism of curvature–induced quenching, where belief propagation halts along regions of low effective mobility and curvature. Building on this insight, we formulate a variational principle for optimal control under resource constraints. The derived feedback law prescribes how to spatially allocate repression effort to maximize inhibition of front motion, concentrating resources along high-curvature, low-mobility arcs. Numerical simulations validate the theory, illustrating how localized suppression dramatically reduces transverse spread without affecting fast axes. These results bridge analytical modeling with societal phenomena such as protest diffusion, misinformation spread, and institutional resistance, offering a principled foundation for selective intervention policies in structured populations. Full article

As solid-state devices continue to advance, vacuum electron devices maintain critical importance due to their superior high-frequency power handling, long-term reliability, and operational efficiency. Among these, traveling-wave tubes (TWTs) excel in high-power microwave (HPM) applications, offering exceptional bandwidth and gain. However, developing THz-range TWT slow-wave structures (SWSs) presents significant design challenges. This work systematically outlines the SWS design methodology while addressing key obstacles and their solutions. As a demonstration, a staggered double vane (SDV) SWS operating at 1 THz (980–1080 GHz) achieves 650 mW output power, 23.35 dB gain, 0.14% electronic efficiency, and compact 21 mm length. Comparative analysis with deformed quasi-sine waveguide (D-QSWG) SWS confirms the SDV design’s superior performance for THz applications. Full article

This work explores the density-driven overturning circulation of the ocean using a process-oriented three-dimensional hydrodynamic model with a free sea surface. As expected, dense-water formation in polar regions creates a deep western boundary current (DWBC) spreading southward along the continental slope. Near the equator, the DWBC releases its water eastward into the ambient ocean to form a large upwelling zone. This upwelling is coupled with a slow westward surface recirculation feeding into a swift surface return flow along the western boundary that closes the mass budget. This recirculation pattern, which is fundamentally different to the Stommel–Arons model, is a consequence of geostrophic adjustment to anomalies of the surface pressure field that form under the influence of both coastal and equatorial Kelvin waves and Rossby waves. Based on the findings, the author presents a revised model of the ocean’s meridional overturning circulation to supersede earlier, incorrect suggestions. Full article

Accurate and robust trajectory tracking is essential for ensuring the safety and efficiency of underactuated ships operating in complex marine environments. However, conventional sliding mode control (SMC) methods often suffer from issues such as chattering and slow convergence, limiting their practical application. To address these challenges, this paper proposes a novel non-singular fast terminal sliding mode control (NFTSMC) strategy for sustainable trajectory tracking of underactuated ships. The proposed approach first designs a virtual control law based on surge and sway position errors, and then develops a non-singular fast terminal sliding mode control law using an exponential reaching strategy, guaranteeing finite-time convergence and eliminating singularities. The Lyapunov-based stability analysis proves the boundedness and convergence of tracking errors under external disturbances. The simulation results demonstrate that the proposed non-singular fast terminal sliding mode control outperforms traditional sliding mode control in terms of convergence speed, tracking accuracy, and control smoothness, especially under wind, wave, and current disturbances. Full article

To address the limitations of traditional methods in modeling complex nonlinear relationships in horizontal in situ stress prediction for shale reservoirs, this study proposes an integrated framework that combines well logging interpretation with machine learning to accurately predict horizontal in situ stress in shale reservoirs. Based on the logging data from five wells in the Luzhou Block of the Sichuan Basin (16,000 samples), Recursive Feature Elimination (RF-RFE) was used to identify nine key factors, including Stoneley wave slowness and caliper, from 30 feature parameters. Bayesian optimization was employed to fine-tune the hyperparameters of the XGBoost model globally. Results indicate that the XGBoost model performs optimally in predicting maximum horizontal principal stress (SHmax) and minimum horizontal principal stress (SHmin). It achieves R² values of 0.978 and 0.959, respectively, on the test set. The error metrics (MAE, MSE, RMSE) of the XGBoost model are significantly lower than those of SVM and Random Forest, demonstrating its precise capture of the nonlinear relationships between logging parameters and in situ stress. This framework enhances the model’s adaptability to complex geological conditions through multi-well data training and eliminating redundant features, providing a reliable tool for hydraulic fracturing design and wellbore stability assessment in shale gas development. Full article

Electrically charged particles present in this layer of the Earth’s atmosphere can alter radio waves, such as those from GPS, Galileo, or BeiDou, resulting in non-estimated errors with respect to the available navigation models for the end user. For most positioning algorithms based in sequential filters, this effect is translated into a slow convergence towards a solution around the decimeter error level. If we consider that the ionosphere’s effect varies based on the user’s location and solar activity due to the atmosphere particle composition, it becomes clear that a global accurate model, valid across wide areas accounting for different seasons and timespans, is, at the very least, quite challenging. The focus of this paper is the demonstration of a global ionosphere model designed to improve the positioning accuracy of the end user through the estimation of ionospheric corrections to the broadcasted navigation message. Mathematically, this method is based on a spherical harmonic expansion model. This approach has the advantage of reducing the dependency from a highly densified station network where the ionosphere delay must be constantly estimated in dozens of locations, in favor of a simplified model that barely needs to be adjusted with a limited set of real-time data (around 40 stations). In this case, GMV’s global station network was used, which comprises geodetic-grade receivers tracking the signal in open-sky locations around the globe. The global ionospheric model is configured to process signals from GPS and Galileo constellations. To evaluate the performances of this model on the final user position estimation, several precise point positioning (PPP) solutions were computed at different locations. The results were compared with PPP solutions calculated without ionospheric corrections at the same stations. The goal of this paper is to show the significant performance improvement observed with the implementation of the global model. Full article

The neurological basis of consciousness remains unknown despite innumerable theories proposed for over a century. The major obstacle is that empirical studies demonstrate that all sensory information is subdivided and parcellated as it is processed within the brain. A central region where such diverse information combines to form conscious expression has not been identified. A novel hypothesis was introduced over two decades ago that proposed astrocytes, with their ability to interconnect to form a global syncytium within the neocortex, are the locus of consciousness based on their ability to integrate synaptic signals. However, it was criticized because intercellular calcium waves, which are initiated by synaptic activity, are too slow to contribute to consciousness but ideal for memory formation. Although astrocytes are known to exhibit rapid electrical responses in active sensory pathways (e.g., vision), it was technically impossible to determine electrical activity within the astroglia syncytium because of the challenge of separating syncytial electrical responses from simultaneous neuronal electrical activity. Therefore, research on astroglia syncytial electrical activity lagged for over sixty years, until recently, when an ingenuous technique was developed to eliminate neuronal electrical interference. These technical advances have demonstrated that the astroglia syncytium, although massive and occupying the entire neocortex, is isoelectric with minimal impedance. Most importantly, the speed of electrical conductance within the syncytium is as rapid as that of neural networks. Therefore, the astroglia syncytium is theoretically capable of transmitting integrated local synaptic signaling globally throughout the entire neocortex to bind all functional areas of the brain in a timeframe required for consciousness. Full article

Introduction: The monitoring of autonomic nervous balance during childhood remains underexplored. However, heart rate variability (HRV) is widely recognized as a biomarker of health risk across the lifespan. Juvenile idiopathic arthritis (JIA), a group of chronic inflammatory joint disorders, is associated with persistent inflammation and pain, both of which contribute to increased cardiovascular risk, commonly linked to reduced HRV. Among HRV parameters, very-low frequency (VLF) components have been associated with physiological recovery processes. This study aimed to assess HRV during sleep in patients with JIA. Methods: We studied 10 patients with JIA and 10 age-, gender-, and Tanner stage-matched healthy controls. All participants underwent polysomnographic monitoring following an adaptation night in the sleep laboratory. HRV was analyzed using standard time and frequency domain measures over 5 min epochs across all sleep stages. Frequency components were classified into low- and high-frequency bands, and time domain measures included the standard deviation of the beat-to-beat intervals. Group differences in HRV parameters were assessed using nonparametric tests for independent samples, with a significance level set at p < 0.05. Results: JIA exhibited greater sleep disruption than controls, including reduced NREM sleep, longer total sleep time, and increased wake time after sleep onset. HRV analyses in both time and frequency domains revealed significant differences between groups across all stages of sleep. In JIA patients, the standard deviation of the normal-to-normal interval during slow wave sleep (SWS) and total power across all sleep stages (p < 0.05) was reduced. In JIA patients, the standard deviation of the normal-to-normal interval during slow wave sleep and total power across all sleep stages were significantly reduced (p < 0.05). VLF power was also significantly lower in JIA patients across all sleep stages (p = 0.002), with pronounced reductions during N2 and SWS (p = 0.03 and p = 0.02, respectively). A group effect was observed for total power across all stages, mirroring the VLF findings. Additionally, group differences were detected in LF/HF ratio analyses, although values during N2, SWS, and REM sleep did not differ significantly between groups. Notably, the number of affected joints showed a moderate positive correlation with the parasympathetic HRV parameter. Conclusions: Patients with JIA exhibited sleep disruption and alterations in cardiovascular autonomic functioning during sleep. Reduced HRV across all sleep stages in these patients suggests underlying autonomic nervous dysfunction. Addressing sleep disturbances in patients with chronic pain may serve as an effective strategy for managing their cardiovascular risk. Full article

This study presents a novel conceptual model to explain the differential rotation within Earth’s layers, a phenomenon observed through seismic wave studies but not fully understood. While geodynamo theory and electromagnetic coupling models have been proposed to explain this phenomenon, our model offers an alternative perspective focusing on the Moon’s tidal forces. Our model proposes that the Moon’s tidal forces play a crucial role in this process, acting as a braking mechanism on Earth’s rotation. We hypothesize that these tidal forces initially decelerate the Earth’s crust and mantle, with this effect sequentially transmitted to deeper layers. A key aspect of our model is the role of the liquid outer core in mediating this process. We suggest that the liquid state of the outer core delays the transmission of tidal friction, resulting in differential rotation between layers in contact with it. This delay mechanism provides a potential explanation for the observed rotational differences between the mantle and core. Our model demonstrates that about 66,000 years after the Moon’s formation, the tidal force slowed the crust–mantle rotation by approximately 5.5 degrees per year more than the core. Furthermore, we estimate that the frictional heat generated at the boundaries of differential rotation is about 0.3478 TW. At this rate, the outer core temperature would increase by approximately 13.4 K per billion years. This thermal effect may have significant implications for the long-term evolution of Earth’s core, potentially slowing its cooling rate and maintaining its liquid state. Our model thus provides a new perspective on the interplay between lunar tidal forces, Earth’s internal structure, and its thermal evolution, offering insights into the complex dynamics of our planet’s interior. Full article

Sleep is essential for physical and mental health, playing a critical role in memory consolidation, behavioral stability, and the regulation of immune and metabolic functions. The incidence of sleep disorders, particularly sleep deprivation (SD), increases with age and is prevalent in neurodegenerative and psychiatric disorders such as Alzheimer’s disease (AD). Nearly 40% of AD patients experience significant chronic sleep impairments. The clinical distinction between late-life sleep disorders and AD is often challenging due to overlapping symptoms, including cognitive decline and behavioral impairments. Although the exact causal relationship between SD and AD remains complex and multifaceted, strong evidence suggests a bidirectional link, with AD patients frequently exhibiting disrupted sleep architecture, reduced slow-wave activity, and shorter total sleep duration. On a pathophysiological level, SD contributes to neuroinflammation, amyloid-β plaque deposition, and tau tangles, which are key features of AD. Current treatments, such as sedatives and antidepressants, often have limitations, including inconsistent efficacy, dependency risks, and poor long-term outcomes/recurrence, highlighting the need for safer and more effective alternatives. This review examines the interplay between SD and AD and proposes omega (n)-3 fatty acids (FAs) as a potential therapeutic intervention. Preclinical and clinical studies suggest that n-3 supplementation may improve sleep onset/quality, reduce neuroinflammation, support synaptic function, and decrease amyloid-β aggregation, thereby alleviating early AD-related neurological changes. Given their safety profile and neuroprotective effects, n-3 FAs represent a promising strategy for managing the comorbidity of sleep disorders in AD. Full article