Search Results (641)

We investigate the variation in shear-wave velocity (V_S) in the shallow soil of the ARGONET vertical array in Cephalonia, Greece, utilizing an extensive 8–10-year dataset of earthquake records and applying seismic interferometry by deconvolution and Generalized Additive Models (GAMs). We identify and quantify the contributions of seasonal variation, soil anisotropy, soil nonlinearity, and long-term V_S changes. Of the examined factors, nonlinearity produces the strongest V_S changes in the form of reduction of up to several tens of m/s. The azimuthal and seasonal partial effects appear similar in strength. However, V_S also exhibits year-to-year variation, with lower levels likely linked to the slow recovery of the soil following strong earthquakes in the broader region. When this partial effect is also considered, the temporal variation of V_S is more significant than the azimuthal variation. We also observed that strong weather phenomena, such as the unusual hurricane “Ianos” that hit western Greece in 2020, are captured in our model through tensor interaction terms. Our model can identify V_S drops related to nonlinear soil behavior even when masked by other effects. We demonstrate and verify this through seismic interferometry to stepwise increasing parts of earthquake recordings highlighting these within-events or coseismic V_S drops. Full article

The phase shift (PS) between spontaneous slow oscillations of cerebral and systemic hemodynamics reliably reflects the state of cerebral autoregulation (CA). However, CA measurements are performed retrospectively after studying the signals from the analysis sensors. At the same time, CA-oriented therapy is becoming increasingly important with the receipt of data on the state of CA in real time, especially in intensive care units. We offer a hardware and software complex for transcranial Dopplerography, which uses a non-invasive method and allows for continuous measurement of cerebral blood flow to assess the rate of CA in real time. The hardware and software complex uses sensors to measure the PS between spontaneous slow oscillations of blood flow velocity (BFV) in the middle cerebral arteries (MCAs) and systemic arterial pressure (BP) in the Mayer wave range and performs wavelet analysis of sensor signals. An examination of 30 volunteers, with an average age of 28 ± 8 years, and 15 patients, with an average age of 57 ± 16 years, with various neurovascular pathologies confirms the feasibility of using the developed hardware and software complex for continuous monitoring of PS in real time to study the mechanisms of cerebral blood flow regulation. Full article

We propose the Clustered Link-Prediction SEIRS model with Temporal Node Activation (CLP-SEIRS-T), a novel epidemiological framework that integrates community structure, link prediction, and temporal activation schedules to simulate malware propagation in urban communication networks. Unlike traditional static or homogeneous models, our approach captures the heterogeneous community structure of the network (modular connectivity), along with evolving connectivity (emergent links) and periodic device-usage patterns (online/offline cycles), providing a more realistic portrayal of how computer viruses spread. Simulation results demonstrate that strong community modularity and intermittent connectivity significantly slow and localize outbreaks. For instance, when devices operate on staggered duty cycles (asynchronous online schedules), malware transmission is fragmented into multiple smaller waves with lower peaks, often confining infections to isolated communities. In contrast, near-continuous and synchronized connectivity produces rapid, widespread contagion akin to classic epidemic models, overcoming community boundaries and infecting the majority of nodes in a single wave. Furthermore, by incorporating a common-neighbor link-prediction mechanism, CLP-SEIRS-T accounts for future connections that can bridge otherwise disconnected clusters. This inclusion significantly increases the reach and persistence of malware spread, suggesting that ignoring evolving network topology may underestimate outbreak risk. Our findings underscore the importance of considering temporal usage patterns and network evolution in malware epidemiology. The proposed model not only elucidates how timing and community structure can flatten or exacerbate infection curves, but also offers practical insights for enhancing the resilience of urban communication networks—such as staggering device online schedules, limiting inter-community links, and anticipating new connections—to better contain fast-spreading cyber threats. Full article

We study the axial and polar perturbations of slowly rotating Ellis–Bronnikov wormholes in General Relativity, applying a perturbative double expansion. In particular, we derive the equations for $l=2$, $M_z=2$ perturbations of these objects, which are parametrized by an asymmetry parameter. The equations constitute an astrophysically interesting sector of the perturbations that contribute dominantly to the gravitational wave radiation. Moreover, calculation of these modes may exhibit potential instabilities in the quadrupole sector. Full article

Objectives: In this study, our aim is to summarise the available data on the correlation between sarcopenia and sleep disturbances as a consequence of changes in the myokine concentrations. Methods: Our research was conducted by searching through PubMed, Mendeley and Google Scholar. In our analysis, 63 studies are included from the years 2011 to 2025. Among these studies, there are clinical trials, cross-sectional studies, reviews, systematic reviews and meta-analyses. Discussion: There is vast evidence confirming that sleep disturbances are more common among sarcopenic patients. On the other hand, sarcopenia is frequently observed among people with worse quality of sleep. It is also well documented that sarcopenia leads to changes in the myokine serum concentrations, and similar changes are observed among people suffering from sleep disturbances. Sarcopenic patients have lower levels of irisin, BDNF (brain-derived neurotrophic factor), meteorin and IL-15 (interleukin 15) and higher concentrations of FGF-21 (fibroblast growth factor 21) and interleukins 1β, 6 and 10. Lower levels of irisin, BDNF and meteorin, and higher levels of FGF-21 and interleukins 6 and 10, lead to sleep disturbances, like insomnia, reduction of REM (rapid eye movement) sleep time and lower slow-wave activity during the NREM (non-rapid eye movement) sleep phase. These changes are also observed in obstructive sleep apnea (OSA). More severe OSA is correlated with lower levels of irisin and meteorin and higher levels of FGF-21 and interleukins 6 and 8. Conclusions: Taking into account the similarities in the myokine concentration changes in sarcopenia and in sleep disturbances, it may be concluded that alterations in the myokine levels induced by sarcopenia provoke sleep disturbances. However, it is necessary to further investigate these correlations to understand them better. Full article

Background: Obstructive sleep apnea (OSA) is highly prevalent in the early stages of Alzheimer’s disease (AD), and its hallmark, sleep fragmentation, may accelerate cognitive decline. Continuous positive airway pressure (CPAP) improves OSA-related hypoxia during slow-wave sleep, but its cognitive benefits in AD remain unclear. Methods: We performed a 12-month sub-analysis of a prospective, longitudinal pilot study that enrolled 21 adults (median age = 77 yr; 71% women) with Mild Cognitive Impairment (MCI) with AD confirmed biomarkers and polysomnography-diagnosed OSA. All participants underwent baseline overnight polysomnography (PSG) and neuropsychological testing (Clinical Dementia Rating (CDR), Mini-Mental State Examination (MMSE), Repeatable Battery for the Assessment of Neuropsychological Status (RBANS)) that were repeated after 12 months. Twelve participants were CPAP-compliant (moderate/severe OSA) and nine were non-users (mild OSA/intolerance). Cognitive change scores (Δ = 12 months -baseline) were compared with Generalized Linear Models (GLM) adjusted for baseline cognition and Apnea–Hypopnea Index (AHI); associations between baseline sleep parameters and cognitive trajectories were examined. And the association of sleep variables with the use of CPAP was also evaluated. Results: Compared with non-users, CPAP users showed significantly slower global decline (Δ MMSE: p = 0.016) and improvements in overall cognition (Δ RBANS Total: p = 0.028) and RBANS sub-domains (Δ RBANS FC: p = 0.010; Δ RBANS SF: p = 0.045). Longer baseline non-rapid eye movement (NREM) stage 3 and rapid eye movement (REM) sleep, greater total sleep time and sleep efficiency, and right-side sleeping were each linked to better cognitive outcomes, whereas extended NREM stage 2, wakefulness, and supine sleeping were associated with poorer trajectories. Conclusions: Twelve months of CPAP use was associated with attenuated cognitive decline and domain-specific gains in AD-related MCI with OSA. Sleep architecture and body position during sleep predicted cognitive outcomes, underscoring the therapeutic relevance of optimizing breathing and sleep quality. Larger, longer-term trials are warranted to confirm CPAP’s disease-modifying potential and to clarify the mechanistic role of sleep in AD progression. Full article

This paper presents a W-band low-voltage traveling-wave tube (TWT) incorporating a spoof surface plasmon polariton (SSPP) slow-wave structure (SWS) and a dual-sheet beam. The SSPP-based SWS adopts a periodic double-F-groove configuration, which provides strong field localization, increases the interaction impedance, and reduces the phase velocity, thereby enabling a low synchronization voltage. Owing to its symmetric open geometry, the SWS naturally forms a dual-sheet beam tunnel, which enhances the effective beam current without increasing the aperture size. Eigenmode calculations indicate that, within the 92–97 GHz band, the normalized phase velocity is between 0.198 and 0.208, and the interaction impedance exceeds 2.65 Ω. Moreover, an energy-coupling structure was developed to ensure efficient signal transmission. Three-dimensional particle-in-cell (PIC) simulations predict a peak output power of 366.1 W and an electronic efficiency of 6.15% at 95.5 GHz for a 2 × 250 mA dual-sheet beam at 11.9 kV, with stable amplification and without self-oscillation observed. The proposed low-voltage, high-efficiency W-band TWT offers a manufacturable and easily integrable solution for next-generation millimeter-wave systems, supporting high-capacity wireless backhaul, airborne communication, radar imaging, and sensing platforms where compactness and reduced power-supply demands are critical. Full article

Background: Epilepsy and cognitive impairment frequently coexist, yet their relationship remains complex and insufficiently understood. This study aims to explore the clinical and electrophysiological features of patients presenting with both conditions in order to identify patterns that may inform more accurate diagnosis and effective management within a personalized medicine framework. Methods: We retrospectively analyzed 14 patients with late-onset epilepsy and coexisting cognitive impairment, including mild cognitive impairment and Alzheimer’s disease. Clinical history, cognitive assessments, neuroimaging, and electroencephalographic recordings were reviewed. EEG abnormalities, seizure types, and treatment responses were systematically documented. Results: Patients were categorized into two groups: (1) those with established Alzheimer’s disease who later developed epilepsy and (2) those in whom epilepsy preceded cognitive impairment. Temporal lobe involvement was a key feature, with EEG abnormalities frequently localizing to the frontal–temporal electrodes and manifesting as background slowing, focal multiform slow waves, and epileptiform discharges. Levetiracetam was the most commonly used antiseizure medication, and it was effective across both groups. Conclusions: This case series highlights the value of EEG in characterizing patients with subclinical and overt epileptic activity and cognitive impairment comorbidity. The inclusion of a substantial number of cases with documented EEG abnormalities provides valuable insight into the interplay between epilepsy and neurodegenerative diseases. By integrating neurophysiological data with clinical and cognitive trajectories, this work aligns with the principles of precision medicine, facilitating a more comprehensive evaluation and tailored management approach. Further longitudinal studies are required to validate prognostic markers and guide optimal therapeutic strategies. Full article

Cerebrovascular reactivity, cerebral autoregulation (CA), and oxygen delivery can be measured continuously and in a non-invasive fashion using cerebral near-infrared spectroscopy (NIRS). Although the literature is limited surrounding the difference between signals acquired and derived from low (<100 Hz) and high sampling rates (≥100 Hz). As part of a prospective observational study, we preliminarily explored and assessed the difference in the information provided by two NIRS systems using regional cerebral oxygen saturation and cerebral oximetry index signals at low and high sampling rates. The raw data in two frequencies (down-sampled to 1 Hz using the mean and up-sampled to 250 Hz) were decimated to focus on slow-wave vasogenic fluctuations associated with CA. Then, the data were analyzed using various statistical methods such as the absolute signal difference, Pearson correlation, Bland–Altman agreement, Cross-correlation function, optimal time-series autocorrelative structure, time-series impulse response function, and Granger causality relationships. The results of the various statistical analyses indicated that the signals obtained using high-frequency NIRS were different from signals obtained from low-frequency NIRS of the same cerebral region. Hence, high-frequency NIRS systems may possibly contain better signal features compared to NIRS systems with low sampling rates, but further work is required to assess high-frequency NIRS in other healthy and cranial trauma populations. Full article

Wave energy is a highly concentrated energy resource with five times higher energy density than wind and at least ten times the power density of solar energy. It is expected to make a major contribution to addressing climate change and to help end our dependency on fossil fuels. Many ingenious wave energy conversion methods have been put forward, and a large number of wave energy converters (WECs) have been developed. However, to date, wave energy conversion technology is still in the demonstration application stage. Key issues such as survivability, reliability, and efficient conversion still need to be solved. The major hurdle is the fact that ocean waves provide a slow-moving, high-magnitude force, whereas most electric generators operate at high rotary speed and low torque. Coupling the slow-moving, high-magnitude force of ocean waves normally requires conversion to a high-speed, low-magnitude force as an intermediate step before a rotary generator is applied. This, in general, tends to severely limit the overall efficiency and reliability of the converter and drives the capital cost of the converter well above an acceptable commercial target. Magnetohydrodynamic (MHD) wave energy conversion makes use of MHD generators in which a conducting fluid passes through a very strong magnetic field to produce an electric current. In contrast to alternatives, the relatively slow speed at which the fluid traverses the magnetic field makes it possible to directly couple to ocean waves with a high-magnitude, slowly moving force. The MHD generator provides an excellent match to the mechanical impedance of an ocean wave, and therefore, an MHD WEC has no rotating mechanical parts with high speeds, no complex control process, and has good response to low sea states and high efficiency under all working conditions. This review introduces the system composition, working process, and technical features of WECs based on MHD generators first. Then, the research development, key points, and issues of wave energy conversion technology based on MHD generators are presented in detail. Finally, the problems to be solved and the future research directions of wave energy conversion based on MHD generators are pointed out. Full article

With the growing wave of end-of-life new energy vehicles, the recycling of lithium iron phosphate (LFP) batteries has become increasingly imperative. In contrast to conventional pyrometallurgical and hydrometallurgical approaches, recent efforts have shifted toward innovative recycling strategies and emerging applications for spent LFP materials. During battery operation, the irreversible oxidation of Fe²⁺ to Fe³⁺ often leads to lithium loss and performance degradation. To address this, various approaches—such as electrochemical delamination and ultrasonic separation—have been developed to efficiently detach cathode materials from current collectors, followed by thermal or wet-chemical regeneration to restore their electrochemical activity. Beyond conventional regeneration, the upcycling of spent LFP into value-added functional materials offers a sustainable pathway for resource reutilization. Notably, phosphorus extracted from LFP can be converted into slow-release fertilizers, broadening the scope of secondary applications. As the volume of spent LFP batteries continues to rise, there is an urgent need to establish an integrated recycling framework that harmonizes environmental impact, technical efficiency, and economic viability. Henceforth, this review summarizes recent advances in LFP recycling and upcycling, discusses critical challenges, and provides strategic insights for the sustainable and high-value reuse of spent LFP cathodes. Full article

The relationship between sleep and epilepsy involves complex interactions between thalamocortical circuits, circadian mechanisms, and sleep architecture that fundamentally influence seizure susceptibility and cognitive outcomes. Epileptic activity disrupts essential sleep oscillations, particularly sleep spindles generated by thalamic circuits. Thalamic epileptic spikes actively compete with physiological sleep spindles, impairing memory consolidation and contributing to cognitive dysfunction in epileptic encephalopathy. This disruption explains why patients with epilepsy often experience learning difficulties despite adequate seizure control. Sleep stages show differential seizure susceptibility. REM sleep provides robust protection through enhanced GABAergic inhibition and motor neuron suppression, while non-REM sleep, particularly slow-wave sleep, increases seizure risk. These observations reveal fundamental mechanisms of seizure control within normal brain physiology. Circadian clock genes (BMAL1, CLOCK, PER, CRY) play crucial roles in seizure modulation. Dysregulation of these molecular timekeepers creates permissive conditions for seizure generation while being simultaneously disrupted by epileptic activity, establishing a bidirectional relationship. These mechanistic insights are driving chronobiological therapeutic approaches, including precisely timed antiseizure medications, sleep optimization strategies, and orexin/hypocretin system interventions. This understanding enables a paradigm shift from simple seizure suppression toward targeted restoration of physiological brain rhythms, promising transformative epilepsy management through sleep-informed precision medicine. Full article

Borderline Personality Disorder (BPD) is marked by emotional dysregulation, instability in self-image and relationships, and high impulsivity. While functional magnetic resonance imaging (fMRI) studies have provided valuable insights into the disorder’s neural correlates, electroencephalography (EEG) may capture real-time brain activity changes relevant to BPD’s rapid emotional shifts. This review summarizes findings from studies investigating resting state and task-based EEG in individuals with BPD, highlighting common neurophysiological markers and their clinical implications. A targeted literature search (1980–2025) was conducted across databases, including PubMed, Google Scholar, and Cochrane. The search terms combined “EEG” or “electroencephalography” with “borderline personality disorder” or “BPD”. Clinical trials and case reports published in English were included if they recorded and analyzed EEG activity in BPD. A total of 24 studies met the inclusion criteria. Findings indicate that individuals with BPD often show patterns consistent with chronic hyperarousal (e.g., reduced alpha power and increased slow-wave activity) and difficulties shifting between vigilance states. Studies examining frontal EEG asymmetry reported varying results—some linked left-frontal activity to heightened hostility, while others found correlations between right-frontal shifts and dissociation. Childhood trauma, mentalization deficits, and dissociative symptoms were frequently predicted or correlated with EEG anomalies, underscoring the impact of adverse experiences on neural regulation—however, substantial heterogeneity in methods, small sample sizes, and comorbid conditions limited study comparability. Overall, EEG research supports the notion of altered arousal and emotion regulation circuits in BPD. While no single EEG marker uniformly defines the disorder, patterns such as reduced alpha power, increased theta/delta activity, and shifting frontal asymmetries converge with core BPD features of emotional lability and interpersonal hypersensitivity. More extensive, standardized, and multimodal investigations are needed to establish more reliable EEG biomarkers and elucidate how early trauma and dissociation shape BPD’s neurophysiological profile. Full article

Small ruminant production is increasingly affected by heat stress, with recent heat waves highlighting growing economic and welfare-related challenges. Chronic exposure to elevated temperatures disrupts thermoregulation, reduces feed intake, slows growth, compromises meat quality, and increases mortality. This study evaluated the effects of chromium-yeast supplementation at different doses and timepoints on physiological and molecular stress biomarkers in heat-stressed lambs. Forty-eight clinically healthy 6-month-old Katahdin lambs (average weight 20 ± 2.9 kg) were assigned to a 2 × 4 factorial design, with two ambient temperature conditions (heat stress [HS] and thermoneutral [TN]) and four levels of dietary Cr-yeast (0, 0.2, 0.4, and 0.8 mg/kg of dry matter intake). Lambs were housed individually in pens (1.2 × 2.5 m), with ad libitum access to water, and fed a 50:50 corn silage and concentrate diet (excluding mineral premix) twice daily. Blood samples were collected at days 0, 30, and 60 to evaluate plasma cortisol and the expression of hsp60 and hsp70. Chromium bioavailability was assessed by blood levels using absorption chromatography, and glucose clearance was measured at the end of the experiment. Significant reductions in cortisol and hsp70 expression were observed after 30 days of Cr-yeast supplementation under HS conditions (p < 0.05), particularly at the highest dose. For hsp60, a significant reduction was observed at the highest dose on day 30 under HS (p < 0.05). These effects were not sustained on day 60 (p > 0.05). No significant differences were detected under TN conditions (p > 0.05). These findings suggest that Cr-yeast may offer short-term physiological and cellular protection against chronic heat stress in lambs. Full article

Millimeter-wave (mmWave) and terahertz (THz) communications are susceptible to frequent link disruptions and severe performance degradation due to high directionality, significant path loss, and sensitivity to blockages. These challenges are particularly acute in highly dynamic and densely populated user environments. The issues present significant obstacles to ensuring reliability and quality of service (QoS) in future space–air–ground integrated networks. To address these challenges, this paper proposes an adaptive transmission control scheme designed for space–air–ground integrated multi-hop networks operating in the mmWave/THz bands. By analyzing the intermittent connectivity inherent in such networks, the proposed scheme incorporates an incremental factor and a backlog indicator into its congestion control mechanism. This allows for the accurate differentiation between packet losses resulting from network congestion and those caused by channel blockages, such as human body occlusion or beam misalignment. Furthermore, the scheme optimizes the initial congestion window during the slow-start phase and dynamically adapts its transmission strategy during the congestion avoidance phase according to the identified cause of packet loss. Simulation results demonstrate that the proposed method effectively mitigates throughput degradation from link blockages, improves data transmission rates in highly dynamic environments, and sustains more stable end-to-end connectivity. Our proposed scheme achieves a 35% higher throughput than TCP Hybla, 40% lower latency than TCP Veno, and maintains 99.2% link utilization under high mobility. Full article