Search Results (3,325)

Wildfires are part of terrestrial ecosystem processes; however, their frequency and intensity have recently increased due to both natural and anthropogenic factors. Geospatial data are essential for analyzing land cover changes at high spatial resolution, making the development of tools that use this information to detect burned areas particularly important, especially in regions of high ecological value. This study aimed to detect burned areas within the Iztaccíhuatl–Popocatépetl Protected Natural Area in central Mexico using a logistic regression model based on spectral variables such as NDVI, RBRc, and SWIR2 derived from Sentinel-2 imagery. The agreement between observed and classified data yielded Kappa coefficients and overall accuracy values of 0.79. Model performance varied with probability threshold: low thresholds achieved higher metrics, while high thresholds produced a more conservative delineation that was spatially more coherent with the reference polygons, prioritizing pixels with higher probability of being affected and generating maps more consistent with actual burned areas. Overall, the model performed well in detecting burned areas, providing a useful tool for fire monitoring. However, it is recommended to conduct analyses by vegetation type to increase model accuracy, as phenological variability associated with vegetation types can influence spectral responses and reduce precision. Full article

Orchard wind-assisted spraying technology relies on auxiliary airflow to disturb the canopy and improve droplet deposition uniformity. However, there are few effective means of quantitatively assessing the dynamic response of fruit tree leaves to airflow or the changes in airflow patterns within the canopy in real time. To address this, this study proposed an online monitoring method for the aerodynamic characteristics of fruit tree leaves using strain gauge sensors. The flexible strain gauge was affixed to the midribs of leaves from peach, pear and apple trees. Leaf deformations were captured with high-speed video recording (100 fps) alongside electrical signals in controlled wind fields. Bartlett low-pass filtering and Fourier transform were used to extract frequency-domain features spanning between 0 and 50 Hz. The AdaBoost decision tree model was used to evaluate classification performance across frequency bands. The results demonstrated high accuracy in identifying wind exposure (98%) for pear leaf and classifying the three leaf types (κ = 0.98) within the 4–6 Hz band. A comparison with the frame analysis of high-speed video recordings revealed a time error of 2 s in model predictions. This study confirms that strain gauge sensors combined with machine learning could efficiently monitor fruit tree leaf responses to external airflow in real time. It provides novel insights for optimizing wind-assisted spray parameters, reconstructing internal canopy wind field distributions and achieving precise pesticide application. Full article

During liquid drainage from intermediate vessels in various industrial processes such as continuous steel casting, aircraft fuel supply, and chemical separation, free-surface vortices commonly occur. The formation and evolution of these vortices not only entrain surface slag and gas, but also lead to deterioration of downstream product quality and abnormal equipment operation. The vortex evolution process exhibits notable three-dimensional unsteadiness, multi-scale turbulence, and dynamic gas–liquid interfacial changes, accompanied by strong coupling effects between temperature gradients and flow field structures. Traditional macroscopic numerical models show clear limitations in accurately capturing these complex physical mechanisms. To address these challenges, this study developed a mesoscopic numerical model for gas-liquid two-phase vortex flow based on the lattice Boltzmann method. The model systematically reveals the dynamic behavior during vortex evolution and the multi-field coupling mechanism with the temperature field while providing an in-depth analysis of how initial perturbation velocity regulates vortex intensity and stability. The results indicate that vortex evolution begins near the bottom drain outlet, with the tangential velocity distribution conforming to the theoretical Rankine vortex model. The vortex core velocity during the critical penetration stage is significantly higher than that during the initial depression stage. An increase in the initial perturbation velocity not only enhances vortex intensity and induces low-frequency oscillations of the vortex core but also markedly promotes the global convective heat transfer process. With regard to the temperature field, an increase in fluid temperature reduces the viscosity coefficient, thereby weakening viscous dissipation effects, which accelerates vortex development and prolongs drainage time. Meanwhile, the vortex structure—through the induction of Taylor vortices and a spiral pumping effect—drives shear mixing and radial thermal diffusion between fluid regions at different temperatures, leading to dynamic reconstruction and homogenization of the temperature field. The outcomes of this study not only provide a solid theoretical foundation for understanding the generation, evolution, and heat transfer mechanisms of vortices under industrial thermal conditions, but also offer clear engineering guidance for practical production-enabling optimized operational parameters to suppress vortices and enhance drainage efficiency. Full article

Background/Objectives: Limited information exists on how dietary patterns change in adults who experience weight regain vs. those who maintain weight loss after lifestyle interventions. Methods: Five hundred fifty-two adults (60 ± 1.0 years, 33.8 ± 0.4 kg/m²) with type 2 diabetes mellitus from the Look AHEAD Trial achieved ≥ 7% weight loss after Year 1, completed follow-up visits through Year 4, and provided three 134-item food frequency questionnaires. Weight “regain” (WLR) was defined as regaining ≥ 50% of the initial weight lost. Dietary patterns were determined using established DASH diet scores (scale: 0–9) and principal component analysis (PCA; higher scores = more adherent). Repeated measures linear mixed models assessed group and sex differences in dietary patterns. Results: Dietary patterns were similar between groups during weight loss (baseline to Year 1). WLR DASH scores decreased more from Year 1 to Year 4 compared to “maintain” (WLM) (WLR: Y1: 5.66 ± 0.14, Y4: 4.60 ± 0.14; WLM: Y1: 5.49 ± 0.13, Y4: 4.92 ± 0.13; difference-p < 0.01). Of the two PCA-derived dietary patterns, Pattern 1 (vegetable, fruit, and fish) decreased more in WLR (WLR: Y1: 0.12 ± 0.16, Y4: −0.14 ± 0.16, WLM: Y1: 0.06 ± 0.14, Y4: 0.25 ± 0.15; difference-p < 0.01), while Pattern 2 (low-fiber grains and high-fat animal proteins) increased in WLR (WLR: Y1: 0.40 ± 0.11, Y4: 0.61 ± 0.11, WLM: Y1: 0.34 ± 0.10, Y4: 0.21 ± 0.10, difference-p < 0.01). Sex differences showed that only WLR women and WLM men increased sweets from Y1 to Y4 (WLR women Y1: 0.26 ± 0.04, Y4: 0.41 ± 0.04; p < 0.01; WLM men: Y1: 0.23 ± 0.04, Y4: 0.38 ± 0.04; p < 0.01). Conclusions: These data demonstrate that differences in dietary patterns between WLR and WLM emerge after the initial weight loss intervention with some sex differences. This suggests that longer-term shifts in dietary patterns after lifestyle interventions may influence weight loss maintenance. Full article

Variable switching frequency modulation (VSFM) is an easy-to-implement and low-cost method to reduce electromagnetic interference (EMI) of power electronics, yet changes in loss and harmonic behavior make it hard to decide the parameters of the filter and the switching frequency (SF) variation range. In this article, a new VSFM method characterized by evenly distributed SF is proposed, and it is easy to implement. In order to handle the induced variation in loss and current total harmonic distortion (THD) behavior, current dynamics of a full-bridge grid-tied inverter under constant SF modulation (CSFM) are analyzed through multidimensional Fourier decomposition (MFD), and then the results are extended to VSFM. Based on these dynamics, loss of MOSFETs and THD of grid-connected current are estimated through the trapezoidal integral rule, and the analytical expressions of these indexes can be derived. After this, parameters needed for VSFM can be determined while meeting the minimum MOSFET loss and fixed current THD constraint. The performance of EMI, loss, and current harmonic is revealed through simulations and experiments and compared with the CSFM and classical VSFM methods. Full article

Background: Repetitive peripheral magnetic stimulation (rPMS) has emerged as a promising non-invasive treatment modality for reducing muscle hypertonus and spasticity. However, standardized protocols regarding stimulation parameters, particularly the number of stimuli required to achieve therapeutic effects, remain largely undefined. Methods: In an exploratory study, seventeen healthy participants (15 male, 2 female) underwent progressive rPMS treatments at 5 Hz frequency with incrementally increasing stimulus counts (105, 210, 315, 420, and 840 stimuli). Seventeen participants served as controls (11 male, 6 female) receiving sham stimulation. Achilles tendon reflexes were elicited using a computer-controlled reflex hammer, and compound muscle action potential (CMAP) peak-to-peak amplitudes were recorded via surface electromyography before and immediately after each stimulation session. Results: The overall repeated-measures ANOVA indicated a significant main effect (F(5, 80) = 4.98, p = 0.001, η²_p = 0.237). All rPMS treatments produced significant reductions in CMAP amplitudes compared to baseline (p < 0.05). No progressive dose-dependent relationship was observed between stimulus count and response magnitude, suggesting a threshold effect rather than progressive inhibition. Control group showed no significant changes (p ≤ 0.56). Conclusions: Low-frequency (5 Hz) rPMS produces rapid inhibitory effects on spinal reflex circuits with onset after as few as 105 stimuli. These findings indicate that treatment effects can be achieved with substantially fewer stimuli than previously assumed. Further research is needed to identify parameters capable of achieving greater reflex suppression. Full article

Resting-state functional connectivity (rsFC) provides insight into the intrinsic organization of brain networks and is increasingly recognized as a sensitive marker of age-related neural changes. Functional near-infrared spectroscopy (fNIRS) offers a portable and cost-effective approach to measuring rsFC, including in naturalistic settings. However, its sensitivity to age-related alterations in network topology remains poorly characterized. Here, we applied graph-based analysis to resting-state fNIRS data from 57 healthy participants, including 26 young adults (YA, 18–30 years) and 31 older adults (OA, 50–77 years). We observed that older adults exhibited a marked attenuation of low-frequency oscillation (LFO) power across all hemoglobin contrasts, corresponding to a 5–6-fold reduction in spectral power. In addition, network analysis revealed altered topological organization under matched sparsity conditions, characterized by reduced degree heterogeneity and increased segregation in older adults, with the strongest differences observed in the default mode (DMN), auditory, and frontoparietal control (FPC) networks. Network visualizations further indicated a shift toward more right-lateralized and posterior hub organization in older adults. Together, the coexistence of reduced oscillatory power and increased connectivity suggests that fNIRS-derived rsFC reflects combined neural and non-neural hemodynamic influences, including increased coherence arising from age-related vascular and systemic physiological processes. Overall, our findings demonstrate that fNIRS is sensitive to age-related changes in large-scale hemodynamic network organization. At the same time, sensitivity to non-neural hemodynamics highlights the need for cautious interpretation, but it may provide complementary, clinically relevant signatures of aging-related changes. Full article

Background/Objectives: Antepartum computerized cardiotocography (cCTG) represents an essential tool for assessing fetal well-being. This study aimed to comparatively evaluate antepartum cCTG-derived indices across high-risk pregnancies to identify distinctive fetal autonomic and reactivity profiles. Methods: A comparative analysis of antepartum cCTG parameters was conducted. The cohort included pregnancies beyond 28 weeks of pregnancy, 169 cases of hypertensive disorders of pregnancy (HDP), 146 of gestational diabetes mellitus (GDM), 86 of intrahepatic cholestasis (ICP), and 87 low-risk pregnancies as controls. Results: Baseline FHR remained within the physiological range across all groups (110–160 bpm; p > 0.05). Dynamic cCTG parameters exhibited clear pathology-dependent alterations. Short-term variability (STV) showed a stepwise decline from controls to ICP and GDM, reaching its lowest values in HDP (mean 1.08 bpm; p < 0.00001), accompanied by an increased proportion of epochs with STV < 1 bpm. Long-term variability suppression (LTV < 5 bpm) was significantly higher in GDM and HDP (p = 0.0077). Acceleration frequency decreased across all pathological groups, with the most pronounced reduction observed in HDP, whereas fetal movements were paradoxically elevated in both GDM and HDP. Total decelerations were more frequent in ICP and HDP; however, repetitive, late, prolonged, and >5 min decelerations remained rare and did not differ significantly between groups. Conclusions: HDP showed the most unfavorable cCTG profiles, consistent with impaired fetal autonomic regulation and chronic subclinical hypoxemia. GDM and ICP had moderate changes, suggesting milder adaptive responses. These findings emphasize the value of quantitative cCTG in differentiating fetal autonomic patterns in high-risk pregnancies and the importance of tailored surveillance strategies. Full article

This paper proposes a regional inertia estimation method in power systems using ambient data measured by phasor measurement units (PMUs). The proposed method employs band-pass filtering to suppress the low-frequency influence of mechanical power and to attenuate high-frequency noise and discrepancies between rotor speed and electrical frequency. By utilizing a simple first-order AutoRegressive Moving Average with eXogenous input (ARMAX) model, this process allows the inertia constant to be directly identified. This method requires no prior model order selection, rotor speed estimation, or computation of the rate of change of frequency (RoCoF). The proposed method was validated through simulation on three benchmark systems: the Kundur two-area system, the IEEE Australian simplified 14-generator system, and the IEEE 39-bus system. The method achieved area-level inertia estimates within approximately ±5% error across all test cases, exhibiting consistent performance despite variations in disturbance models and system configurations. The estimation also maintained stable performance with short data windows of a few minutes, demonstrating its suitability for near real-time monitoring applications. Full article

Background: Autism Spectrum Disorder (ASD) is a type of neurodevelopmental disorder, and its exact causes are currently unknown. Neuroimaging research suggests that its clinical features are closely linked to alterations in brain functional network connectivity, yet the specific patterns and mechanisms underlying these abnormalities require further clarification. Methods: We recruited 36 children with ASD and 36 age- and sex-matched typically developing (TD) controls. Resting-state EEG data were used to construct static and dynamic low- and high-order functional networks across four frequency bands (δ, θ, α, β). Graph-theoretical metrics (clustering coefficient, characteristic path length, global efficiency, local efficiency) and state entropy were applied to characterize network topology and dynamic transitions between integration and segregation. Additionally, between-frequency networks were built for six band pairs (δ-θ, δ-α, δ-β, θ-α, θ-β, α-β), and network global measures quantified cross-frequency interactions. Results: Low-order networks in ASD showed increased δ and β connectivity but decreased θ and α connectivity. High-order networks demonstrated increased δ connectivity, reduced α connectivity, and mixed alterations in θ and β. Graph-theoretical analysis revealed pronounced α-band topological disruptions in ASD, reflected by a lower clustering coefficient and efficiency and higher characteristic path length in both low- and high-order networks. Dynamic analysis showed no significant entropy changes in low-order networks, while high-order networks exhibited time- and frequency-specific abnormalities, particularly in δ and α (0.5 s window) and δ (6 s window). Between-frequency analysis showed enhanced β-related coupling in low-order networks but widespread reductions across all band pairs in high-order networks. Conclusions: Young children with ASD exhibit coexisting hypo- and hyper-connectivity, disrupted network topology, and abnormal temporal dynamics. Integrating hierarchical, dynamic, and cross-frequency analyses offers new insights into ASD neurophysiology and potential biomarkers. Full article

As space systems evolve towards cis-lunar missions and beyond, the demand for precise yet low-size, -weight, and -power (SWaP) clocks and synchronization methods becomes increasingly critical. We introduce a novel clock synchronization approach based on the Kuramoto oscillator model that facilitates the creation of an ensemble timescale for satellite constellations. Unlike traditional ensembling algorithms, the proposed Kuramoto method leverages nearest-neighbor interactions to achieve collective synchronization. This method simplifies the communication architecture and data-sharing requirements, making it well suited for dynamically connected networks such as proliferated low Earth orbit (pLEO) and lunar or Martian constellations, where intersatellite links may frequently change. Through simulations incorporating realistic noise models for small-scale atomic clocks, we demonstrate that the Kuramoto ensemble can yield an improvement in stability on the order of 1/√N, while mitigating the impact of constellation fragmentation and defragmentation. The results indicate that the Kuramoto oscillator-based algorithm can potentially deliver performance comparable to established techniques like Equal Weights Frequency Averaging (EWFA), yet with enhanced scalability and resource efficiency critical for future spaceborne PNT and communication systems. Full article

Background/Objectives: The vestibular labyrinth is classically viewed as a sensor of low-frequency head motion—linear acceleration for the otoliths and angular velocity/acceleration for the semicircular canals. However, there is now substantial evidence that air-conducted sound (ACS) can also activate vestibular receptors and afferents in mammals and other vertebrates. This sound sensitivity underlies sound-evoked vestibular-evoked myogenic potentials (VEMPs), sound-induced eye movements, and several clinical phenomena in third-window pathologies. The cellular and biophysical mechanisms by which a pressure wave in the cochlear fluids is transformed into a vestibular neural signal remain incompletely integrated into a single framework. This study aimed to provide a narrative synthesis of how ACS activates the vestibular labyrinth, with emphasis on (1) the anatomical and biophysical specializations of the maculae and cristae, (2) the dual-channel organization of vestibular hair cells and afferents, and (3) the encoding of fast, jerk-rich acoustic transients by irregular, striolar/central afferents. Methods: We integrate experimental evidence from single-unit recordings in animals, in vitro hair cell and calyx physiology, anatomical studies of macular structure, and human clinical data on sound-evoked VEMPs and sound-induced eye movements. Key concepts from vestibular cellular neurophysiology and from the physics of sinusoidal motion (displacement, velocity, acceleration, jerk) are combined into a unified interpretative scheme. Results: ACS transmitted through the middle ear generates pressure waves in the perilymph and endolymph not only in the cochlea but also in vestibular compartments. These waves produce local fluid particle motions and pressure gradients that can deflect hair bundles in selected regions of the otolith maculae and canal cristae. Irregular afferents innervating type I hair cells in the striola (maculae) and central zones (cristae) exhibit phase locking to ACS up to at least 1–2 kHz, with much lower thresholds than regular afferents. Cellular and synaptic specializations—transducer adaptation, low-voltage-activated K⁺ conductances (K_LV), fast quantal and non-quantal transmission, and afferent spike-generator properties—implement effective high-pass filtering and phase lead, making these pathways particularly sensitive to rapid changes in acceleration, i.e., mechanical jerk, rather than to slowly varying displacement or acceleration. Clinically, short-rise-time ACS stimuli (clicks and brief tone bursts) elicit robust cervical and ocular VEMPs with clear thresholds and input–output relationships, reflecting the recruitment of these jerk-sensitive utricular and saccular pathways. Sound-induced eye movements and nystagmus in third-window syndromes similarly reflect abnormally enhanced access of ACS-generated pressure waves to canal and otolith receptors. Conclusions: The vestibular labyrinth does not merely “tolerate” air-conducted sound as a spill-over from cochlear mechanics; it contains a dedicated high-frequency, transient-sensitive channel—dominated by type I hair cells and irregular afferents—that is well suited to encoding jerk-rich acoustic events. We propose that ACS-evoked vestibular responses, including VEMPs, are best interpreted within a dual-channel framework in which (1) regular, extrastriolar/peripheral pathways encode sustained head motion and low-frequency acceleration, while (2) irregular, striolar/central pathways encode fast, sound-driven transients distinguished by high jerk, steep onset, and precise spike timing. Full article

Far-infrared (FIR)-emitting textiles are increasingly used in sleepwear; however, their influence on sleep physiology has not been comprehensively evaluated with multi-modal wearable sensing. This randomized, double-blind, placebo-controlled crossover study examined whether FIR-emitting garments modulate nocturnal thermoregulation, autonomic activity, and sleep architecture. Fifteen healthy young men completed two overnight laboratory sleep sessions wearing either FIR-emitting garments or visually matched polyester controls. Tympanic membrane temperature (TMT), sweating rate, skin temperature, and humidity were continuously monitored using wearable sensors, and sleep stages and heart rate variability (HRV) were assessed using validated portable systems. Compared with control garments, FIR garments produced consistently lower TMT across the night (p = 0.004) and reduced mid-sleep sweating (condition × time interaction: p = 0.026). The proportion of rapid eye movement (REM) sleep was higher in the FIR condition (22.2% ± 6.5% vs. 18.6% ± 6.5%, p = 0.027), despite no changes in total sleep time or sleep efficiency. A transient increase in low-frequency power during early sleep (p = 0.027) suggested baroreflex-related thermal adjustments without sympathetic activation. These findings indicate that FIR-emitting garments facilitate mild nocturnal heat dissipation and support REM expression, demonstrating their potential as a passive intervention to improve sleep-related thermal environments. Full article

Brake squeal is an undesirable high-frequency noise caused by vibrations induced by friction in disc brake systems. The noise is strongly affected by temperature, as this influences the material properties of the friction pair and the dynamic behaviour of the brake components. This study investigates the effect of temperature changes on the squeal characteristics of a disc brake system under different operating conditions. Experiments are carried out using a laboratory-scale test setup comprising a rotating disc, pneumatically actuated callipers, and precise measurement equipment. A series of test combinations is performed by systematically varying three parameters: disc surface temperature (40, 55, 70, 85, 100 °C), brake pressure (4.0 bar), and disc rotational speed (50, 100, 150, 200 rpm). Acceleration data are acquired using an accelerometer mounted directly on the calliper, while sound pressure data are measured with a fixed-position microphone located 0.5 m from the disc surface. The collected data are analyzed in the time and frequency domain to identify squeal events and their dominant frequencies. The effect of temperature on brake squeal noise and vibration varies with operating conditions, showing different patterns at low and high disc speed at constant brake pressure. This highlights the importance of considering both thermal and mechanical factors together when addressing brake squeal. Full article

Background: In nuclear medicine, numerous cancer types are treated via internal irradiation with radiopharmaceuticals, including low-LET (linear energy transfer) beta-emitting radionuclides like Lu-177. In most cases, such treatments lead to low-dose exposure of organ systems with β-irradiation, which induces only few isolated DSBs (double-strand breaks) in the nuclei of hit cells, the most threatening DNA damage type. That damaging effect contrasts with the clustering of DNA damage and DSBs in nuclei traversed by high-LET particles (α particles, ions, etc.). Methods: After in-solution β-irradiation for 1 h with Lu-177 leading to an absorbed dose of about 100 mGy, we investigated the spatial nano-organization of chromatin at DSB damage sites, of repair proteins and of heterochromatin marks via single-molecule localization microscopy (SMLM) in PBMCs. For evaluation, mathematical approaches were used (Ripley distance frequency statistics, DBScan clustering, persistent homology and similarity measurements). Results: We analyzed, at the nanoscale, the distribution of the DNA damage response (DDR) proteins γH2AX, 53BP1, MRE11 and pATM in the chromatin regions surrounding a DSB. Furthermore, local changes in spatial H3K9me3 heterochromatin organization were analyzed relative to γH2AX distribution. SMLM measurements of the different fluorescent molecule tags revealed characteristic clustering of the DDR markers around one or two damage foci per PBMC cell nucleus. Ripley distance histograms suggested the concentration of MRE11 molecules inside γH2AX-clusters, while 53BP1 was present throughout the entire γH2AX clusters. Persistent homology comparisons for 53BP1, MRE11 and γH2AX by Jaccard index calculation revealed significant topological similarities for each of these markers. Since the heterochromatin organization of cell nuclei determines the identity of cell nuclei and correlates to genome activity, it also influences DNA repair. Therefore, the histone H3 tri methyl mark H3K9me3 was analyzed for its topology. In contrast to typical results obtained through photon irradiation, where γH2AX and H3K9me3 markers were well separated, the results obtained here also showed a close spatial proximity (“co-localization”) in many cases (minimum distance of markers = marker size), even with the strictest co-localization distance threshold (20 nm) for γH2AX and H3K9me3. The data support the results from the literature where only one DSB induced by low-dose low LET irradiation (<100 mGy) can remain without heterochromatin relaxation for subsequent repair. Full article