Search Results (25,463)

Laser beams are excellent projection sources due to their high brightness and color purity; however, their high coherence produces speckle noise, which reduces the clarity of images cast by compact projection systems. Existing suppression methods often require complex designs. Here, we propose a simple miniaturized speckle suppression structure (SSS) that consists of a low-absorption particle surface and a micro-vibrating unit. By generating and superimposing different speckle patterns over time, the structure simultaneously reduces both temporal and spatial coherence. A time-varying functional model was developed using a simulation to optimize its dynamic operation. The results of the experimental validation show that at 50 Hz vibration, the speckle contrast decreases from 30.23% to 6.98%, closely matching the simulated prediction of 7.12% and outperforming static configurations by 24%. The results indicate that the SSS is a straightforward, effective solution for enhancing the image quality of compact laser projection displays. Full article

Large-eddy simulation (LES) within a weather research and forecasting (WRF) model coupled with an active scalar transport equation was used to simulate Atmospheric Boundary Layer conditions during the Mosquito fire, the largest wildland fire in California during September 2022. The simulations were conducted with realistic boundary conditions derived from the National Oceanic and Atmospheric Administration (NOAA) High Resolution Rapid Refresh (HRRR) model, with the aim of better understanding the two-way coupling between the ABL and plume dynamics. The terrain was extremely inhomogeneous, and the topography varied significantly within the numerical domain. Initially, LES of the smoke-free ABL was conducted on nested domains, and detailed ABL data were gathered from 8 to 9 September 2022. LES simulations were validated using four Automated Surface Observing System (ASOS) stations and NOAA meteorological (MET) observations, as well as NOAA met Twin Otter measurements, and the desired accuracy was established. The smoke plume was then released into the ABL at noon on 9 September 2022, and the plume simulations were conducted for a period of one hour following the release. During this period, the ABL transitioned from convective to buoyancy-shear-driven regimes. Late-night and early-morning conditions are influenced by the complex topography and low-level jet, whereas buoyancy and shear control the ABL dynamics during the morning and afternoon hours. The plume vertical transport is influenced by the ABL depth and the size of the vertical turbulence structures during that time, whereas the wind conditions and turbulent kinetic energy within the ABL dictate the horizontal transport scales of the plume. In addition, the results demonstrate that the plume modifies the microclimate along its path. Full article

The removal of toxic trace metals such as cadmium (Cd²⁺) and lead (Pb²⁺) from wastewater is critical due to their persistence, bioaccumulation, and adverse health effects. In this study, a novel composite adsorbent was synthesized by integrating activated carbon with nickel–iron-layered double hydroxides (NiFe-LDH) and immobilizing the resulting nanocomposite within Polyether sulfone (PES) beads to improve stability, handling, and recyclability. The material was evaluated under varying pH, initial metal concentration, and contact time conditions. The adsorption behavior was investigated using four isotherm models and two kinetic models. The composite beads exhibited maximum adsorption capacities of 1.784 mg g⁻¹ for Cd²⁺ and 5.882 mg g⁻¹ for Pb²⁺. The Cd²⁺ adsorption followed the Langmuir isotherm model (R² = 0.995), indicating a homogeneous monolayer adsorption, whereas Pb²⁺ adsorption was best described by the Freundlich model (R² = 0.955), suggesting heterogeneous surface interactions and multiple binding sites. The kinetic analysis showed that the adsorption of both metals followed a pseudo-second-order model, supporting chemisorption as the dominant rate-controlling mechanism. The AC@NiFe-LDH/PES beads demonstrated high efficiency, structural integrity, and ease of recovery over multiple cycles, highlighting their potential as a sustainable and environmentally friendly adsorbent for trace metal removal from contaminated water. Full article

Tweeks are ELF/VLF radio signals originating from lightning discharges that exhibit dispersion due to their propagation in the Earth-ionosphere waveguide. Examples of the waveforms of tweeks and their dynamic frequency-time spectra are presented and interpreted. Tweeks observed in the daytime and night-time are compared and contrasted. Tweeks observed during a solar eclipse are also discussed, as are those due to volcanic lightning and those claimed to be recorded some hours or days before a strong earthquake. The variations of tweek occurrence with season and geomagnetic activity, and with variations of solar radiation over the 11-year solar cycle, are reviewed. Wherever possible, geophysical interpretations are discussed. Theoretical models of tweek waveforms and spectra are considered; they vary according to the lightning current model used, the distance from the source (≥1 Mm), the vertical profile of ionospheric D-region ionisation and the specific mode theory used. The simplest interpretation shows that the first-order tweek cut- off frequency ~1.8 kHz is explained as reflection by the ionosphere at a height of ~83 km where the electron density is ~27 × 10⁶ m⁻³. More complex interpretations are also reviewed and compared with electron density observations made by rockets and with profiles given by lower ionospheric models such as the International Reference Ionosphere or the Faraday International Reference Ionosphere. Full article

This paper addresses the finite-horizon state estimation problem for multiplex networks (MNs) subject to random delays and sensor saturations under the constraint of only partial node measurements. The random time-varying delays are modeled via Bernoulli-distributed variables, while a Markovian random access protocol dynamically governs the data transmission at each time step. To tackle this problem, we design a set of robust state estimators based on partial measurements, ensuring the prescribed finite-horizon $H_{\infty }$ performance. Sufficient conditions for the existence of these estimators are established. Subsequently, the estimator gains are derived by solving the matrix inequalities inherent in these conditions. Finally, convincing numerical simulations demonstrate the effectiveness and practical applicability of the proposed algorithm. Full article

In response to the deterioration of path-tracking accuracy and driving stability encountered by intelligent vehicles under dynamically varying operating conditions, a multi-objective optimization strategy integrating soft actor-critic (SAC) reinforcement learning with variable-parameter Model Predictive Control (MPC) is proposed in this paper to achieve online adaptive adjustment of path-tracking controller parameters. Based on a three-degree-of-freedom vehicle dynamics model, a linear time-varying (LTV) MPC controller is constructed to jointly optimize the front wheel steering angle. An SAC agent is developed utilizing the actor-critic framework, with a comprehensive reward function designed around tracking accuracy and control smoothness to enable online tuning of the MPC weighting matrices (lateral error weight, heading error weight, and steering control weight) as well as the prediction horizon parameter, thereby realizing adaptive balance between tracking accuracy and stability under different operating conditions. Based on the simulation results, it can be concluded that under normal operating conditions, the proposed integrated SAC-MPC control scheme demonstrates superior tracking performance, with the maximum absolute lateral error and mean lateral error reduced by 44.9% and 67.2%, respectively, and the maximum absolute heading error reduced by 23.5%. When the system operates under nonlinear conditions during the transitional phase, the proposed control scheme not only enhances tracking accuracy—evidenced by reductions of 43.4% and 23.8% in the maximum absolute lateral error and maximum absolute heading error, respectively—but also significantly improves system stability, as indicated by a 20.7% reduction in the sideslip angle at the center of gravity. Experimental validation further confirms these findings. The experimental results reveal that, compared with the fixed-parameter MPC, the maximum absolute value and mean value of the lateral error are reduced by approximately 36.2% and 78.1%, respectively; the maximum absolute heading angle error is decreased by 24.3%; the maximum absolute yaw rate is diminished by 19.6%; and the maximum absolute sideslip angle at the center of gravity is reduced by 30.8%. Full article

Virtual acoustics enables the creation and simulation of realistic and ecologically valid indoor environments vital for hearing research and audiology. For real-time applications, room acoustics simulation requires simplifications. However, the acoustic level of detail (ALOD) necessary to capture all perceptually relevant effects remains unclear. This study examines the impact of varying ALOD in simulations of three real environments: a living room with a coupled kitchen, a pub, and an underground station. ALOD was varied by generating different numbers of image sources for early reflections, or by excluding geometrical room details specific for each environment. Simulations were perceptually evaluated using headphones in comparison to measured, real binaural room impulse responses, or by using loudspeakers. The perceived overall difference, spatial audio quality differences, plausibility, speech intelligibility, and externalization were assessed. A transient pulse, an electric bass, and a speech token were used as stimuli. The results demonstrate that considerable reductions in acoustic level of detail are perceptually acceptable for communication-oriented scenarios. Speech intelligibility was robust across ALOD levels, whereas broadband transient stimuli revealed increased sensitivity to simplifications. High-ALOD simulations yielded plausibility and externalization ratings comparable to real-room recordings under both headphone and loudspeaker reproduction. Full article

High Mobility Group ^{Box 1} (HMGB1) and S100 proteins are major ligands of Receptor for Advanced Glycation End-products (RAGE) and have causal roles in endometriosis lesions. Yet the AGE–RAGE pathway that unifies Advanced Glycation End-products (AGEs) with these ligands has not been assessed in endometriosis. In diabetes, atherosclerosis, and chronic kidney disease, AGE–RAGE links insulin resistance and oxidative stress to inflammation, fibrosis, and organ harm. Endometriosis shares key drivers of AGE accumulation, including insulin resistance, oxidative stress, and chronic inflammation. Endometriosis is also linked to higher vascular risk and arterial stiffness. We asked whether AGE–RAGE could bridge metabolic stress to pelvic lesions and systemic risk. We did a focused review of mechanisms and an evidence map of studies on AGEs, RAGE, or known RAGE ligands in endometriosis. We grouped findings as most consistent with a driver, amplifier, consequence, or parallel role. We included 29 studies across human samples, cell systems, and animal models. Few studies measured AGE adducts directly. Most work tracked RAGE ligands (mainly HMGB1 and S100 proteins) and downstream immune and angiogenic programs. Across models, this pattern fits best with a self-reinforcing loop after lesions form. RAGE expression often aligned with lesion remodeling, especially fibrosis. Blood and skin readouts of AGE burden were mixed and varied by cohort and sample type. A central gap is receptor proof. Many models point to shared Toll-like receptor 4 (TLR4)/ nuclear factor kappa B (NF-κB) signaling, but few test RAGE dependence. Overall, current evidence supports AGE–RAGE as a disease-amplifying loop involved in chronic inflammation and fibrosis rather than an initiating trigger. Its effects likely vary by stage and site. Priorities now include direct lesion AGE measurement, paired systemic–pelvic sampling over time, receptor-level studies, and trials testing diet or drug interventions against clear endpoints. Outcomes could include fibrosis, angiogenesis, immune state, pain, and oocyte and follicle function. Full article

This study evaluates a time-lagged ensemble averaging strategy to improve the accuracy and robustness of short-range streamflow point forecasts when hydrological simulations are driven by deterministic numerical weather prediction (NWP) forcing. We implemented WRF-Hydro in standalone mode for the Geumho River basin, South Korea, using Local Data Assimilation and Prediction System (LDAPS) forecasts initialized every 6 h with lead times up to 48 h. Time-lagged ensembles were constructed by averaging overlapping WRF-Hydro predictions from successive LDAPS initializations. Across two contrasting flood-producing storms, ensemble-mean forecasts consistently reduced lead-time-dependent skill degradation relative to single-initialization forecasts; the event-wise median Nash–Sutcliffe efficiency at the downstream gauge improved from 0.39 to 0.81 at 48 h (Event 2020) and from 0.48 to 0.85 at 24 h (Event 2022), while RMSE decreased by up to 48%. The most effective ensemble window varied with storm evolution and forecast horizon, indicating additional gains from adaptive time-lag selection. Overall, time-lagged ensemble averaging provides a practical, low-cost post-processing approach to enhance operational short-range streamflow prediction with NWP forcings. Full article

Sugar beet (root) is primarily used by industry as a raw material for sugar production, and its large-scale cultivation is closely linked to the sugar industry. Currently, sugar beet leaf (SBL) is not processed and is typically left on the field as green fertilizer after mechanical harvesting. This represents an underutilized biomass stream with potential bioactive compounds. The aim of this study was to evaluate the distribution of polyphenol and proteins in the leaf blade and petioles of different sugar beet cultivars harvested at various time points. Total polyphenols were quantified using vitexin as a reference standard, and the phenolic profile of methanolic extracts was characterized using complementary HPLC-DAD and LC-MS methods. The protein content in leaf blades ranged from 19% to 29% (dry weight) and was significantly influenced by cultivar and harvest date. Petioles contained significantly lower protein content, ranging from 4.9% to 9.5% (dry weight). The total polyphenol content (TPC) varied with cultivar and harvest time, ranging from 7.8 to 11.0 mg/g DW in leaf blades and from 0.8 to 2.7 mg/g DW in petioles. Leaf blades also contained substantially higher concentrations of vitexin derivatives (mean 7.4 ± 2.3 mg/g DW) than petioles (1.1 ± 0.6 mg/g DW). The percentage contribution of vitexin derivatives to TPC was high in both tissues (>70%) and decreased with later harvest dates. The results provide a detailed characterization of polyphenolic and protein distribution in blades and petioles of sugar beet leaves and can support further evaluation of their potential use in value-added applications. Full article

The rapid development of viticulture in subtropical regions represents a significant achievement in China’s table grape industry over the last two decades. However, insufficient winter chilling in these areas often leads to inadequate dormancy, which compromises nutrient translocation and storage in grapevines. Insufficient chilling accumulation results in asynchronous budbreak and reduced cane quality. In this study, ‘Shine Muscat’ grapevines were used to systematically evaluate how different defoliant agents affect budbreak characteristics from the perspective of nutrient translocation and storage. The results indicated that applications of ethephon or urea alone, as well as their combinations with boric acid, yielded unstable effects, often causing primary bud necrosis, decreased flower formation rates, and phytotoxicity. In contrast, the combination of lime sulfur and boric acid exhibited a remarkable synergistic effect, significantly promoting dry matter and starch accumulation in canes while enhancing the budbreak speed, uniformity, and flower cluster formation rate. Further experiments with varying concentrations of lime sulfur combined with 0.2% boric acid revealed that utilizing 2% lime sulfur in this combination produced the most pronounced effects, achieving the highest dormancy-breaking efficacy under conventional cultivation conditions. This treatment was used for the first time to produce a second crop during off-season cultivation. The dual effects of dormancy release and bud promotion achieved via this approach represent a reliable solution in high-quality and efficient grape production in subtropical regions. Full article

The rapid integration of photovoltaic (PV) generation into modern power networks introduces significant operational challenges, including intermittent power production, uneven charge distribution, and reduced system reliability in multi-battery energy storage systems. Addressing these challenges requires intelligent, adaptive, and physically consistent control strategies capable of operating under uncertain environmental and load conditions. This study proposes a Physics-Informed Neural Network (PINN)-based charge allocation framework that explicitly embeds physical constraints—namely charge conservation and State-of-Charge (SoC) equalization—directly into the learning process, enabling real-time adaptive control under varying irradiance and load conditions. The proposed controller exploits real-time measurements of PV voltage, current, and irradiance to achieve optimal charge distribution while ensuring converter stability and balanced battery operation. The framework is implemented and validated in MATLAB/Simulink under Standard Test Conditions of 1000 W·m⁻² irradiance and 25 °C ambient temperature. Simulation results demonstrate stable PV voltage regulation within the 230–250 V range, an average PV power output of approximately 95 kW, and effective duty-cycle control within the range of 0.35–0.45. The system maintains balanced three-phase grid voltages and currents with stable sinusoidal waveforms, indicating high power quality during steady-state operation. Compared with conventional Proportional–Integral–Derivative (PID) and Model Predictive Control (MPC) methods, the PINN-based approach achieves faster SoC equalization, reduced transient fluctuations, and more than 6% improvement in overall system efficiency. These results confirm the strong potential of physics-informed intelligent control as a scalable and reliable solution for smart PV–battery energy systems, with direct relevance to renewable microgrids and electric vehicle charging infrastructures. Full article

Background: Early and accurate diagnosis remains crucial to improving outcomes in oral cancer. Optical coherence tomography (OCT) offers real-time, high-resolution imaging that may support diagnosis and treatment planning in oral squamous cell carcinoma (OSCC). Methods: In this prospective study, preoperative OCT scans were obtained from 68 histologically confirmed OSCC lesions, with 30 paired adjacent mucosa samples from the same patients as histologically negative comparators (diagnostic dataset: 98 lesions). OCT findings were compared with histopathology for diagnostic performance, OCT biomarker patterns by tumour grade, tumour depth measurement, margin assessment, and subsite-specific performance. Results: OCT demonstrated 98.5% sensitivity, 96.7% specificity, and an AUC of 0.98 for detection of invasive OSCC. OCT biomarkers—including abnormal epithelial architecture with variable epithelial thickness, stratification loss, basement membrane disruption, and increased subepithelial reflectivity—varied systematically with tumour differentiation grade. Tumour depth measurements showed acceptable agreement with histology, while margin definition was correct in 80% of cases. Performance was highest in the tongue and the floor of the mouth, with reduced performance in posterior/keratinised subsites. Image artefacts occurred in 5.1% of scans. Conclusions: OCT provides a reproducible, real-time adjunct for diagnosis, margin planning, and lesion stratification in OSCC, with recognised limitations related to light attenuation and operator-dependent factors. Multicentre validation and integration with digital interpretation platforms are warranted. Full article

Monitoring microplastic pollution relies increasingly on bioindicators that integrate environmental exposure across habitats. This review presents animals explicitly proposed as microplastic bioindicators in recent literature and qualitatively evaluates their appropriateness using established biomonitoring criteria encompassing ecological, physiological, and methodological dimensions. In aquatic systems, bivalves (clams and mussels) demonstrate high suitability due to wide distribution, habitat-specific feeding, effective microplastic retention, and well-established analytical protocols. Fish exhibit intermediate suitability, as ecological representativeness and retention vary among species, and standardized methods often require multi-species approaches. Sessile organisms, including barnacles and sea anemones, align strongly with all three dimensions through spatial fidelity, effective retention, and methodological ease. Crustaceans and sponges also exhibit robust ecological relevance and high retention, with sponges uniquely integrating fine particles over time. Terrestrial and aerial indicators, such as carabid beetles and insectivorous birds, provide complementary coverage with moderate physiological integration and feasible ethical sampling. Sea turtles demonstrate exceptional physiological integration and methodological robustness at regional scales, despite non-sedentary behavior. Overall, taxa combining sedentary or spatially faithful ecology, effective microplastic retention, and standardized laboratory applicability, particularly bivalves, sponges, barnacles, sea anemones, and sediment-associated crustaceans, emerge as the most suitable bioindicators. Future research should prioritize harmonized, multi-taxa frameworks to improve standardization, cross-ecosystem comparability, and long-term microplastic monitoring. Full article

Sustainable management of indoor and outdoor air quality is essential for protecting public health, enhancing well-being, and supporting resilient urban environments. Low-cost air quality sensors enable continuous, real-time monitoring of key pollutants and, when combined with data analytics, provide scalable and cost-effective insights for smart building operation and environmental decision-making. This pilot study evaluates an indoor–outdoor air quality monitoring system deployed at the Faculty of Electrical Engineering and Information Technologies in Skopje, with a focus on: (i) PM2.5 and PM10 concentrations and their relationship with meteorological conditions and human occupancy; (ii) sensor responsiveness and reliability in an educational setting; and (iii) implications for sustainable building operation. From January to March 2025, two indoor sensors (a classroom and a faculty hall) and two outdoor rooftop sensors continuously measured PM2.5 and PM10 at one-minute intervals. All sensors were calibrated against a reference instrument prior to deployment, while meteorological data were obtained from a nearby station. Time-series analysis, Pearson correlation, and multiple regression were applied. Indoor particulate levels varied strongly with occupancy and ventilation status, whereas outdoor concentrations showed weak to moderate correlations with meteorological variables, particularly atmospheric pressure. Moderate correlations between indoor and outdoor PM suggest partial pollutant infiltration. Overall, this pilot study demonstrates the feasibility of low-cost sensors for long-term monitoring in educational buildings and highlights the need for adaptive, context-aware ventilation strategies to reduce indoor exposure. Full article