Search Results (533)

Phytolacca americana L. fruits represent a promising invasive plant matrix for obtaining antioxidant-rich extracts and natural pigments, but extraction efficiency depends strongly on processing conditions. This study reports a comparative assessment and optimization of four extraction methods: maceration (ME), ultrasound-assisted extraction (UAE), bead-beating extraction (BBE), and turbo-extraction (TE), for the recovery of total phenolic content (TPC), total flavonoid content (TFC), total condensed tannins (TTC), betalains, and antioxidant activity assessed by FRAP, DPPH, and ABTS assays from P. americana fruits. A 2³ full factorial design was applied for each method, evaluating the effects of solvent/solid ratio, extraction time, and method-specific parameters. The results of optimization using response surface methodology showed that no single extraction condition maximized all responses simultaneously. Phenolic-related responses and FRAP/ABTS activity were generally favored by a longer extraction time, higher solvent/solid ratio, and accelerated mechanical or acoustic input. In contrast, betalain recovery was consistently improved at a lower solvent/solid ratio, indicating a different optimization pattern for pigment-rich extracts. UAE provided a favorable balance between TFC yield and reproducibility, while TE and BBE were effective for TPC and TTC-related profiles. Overall, the study demonstrates that optimal extraction conditions for P. americana fruits vary according to the target application, such as maximizing pigment recovery, enhancing phenolic content, or improving antioxidant activity. Full article

Molybdenum-doped xerogel composites were prepared and applied in the electro-degradation of tetracycline (TTC), an antibiotic commonly prescribed for the treatment of bacterial infections. Xerogels containing 1, 6, and 14 wt% Mo were synthesized using an RF sol–gel polymerization method in cylindrical molds and were subsequently characterized in terms of their textural, chemical, and electrochemical properties, focusing on the oxygen reduction reaction (ORR). Textural characterization revealed well-developed surface areas and mesoporosity. Electrochemical analysis showed that Mo loading plays a vital role in the ORR mechanism: lower metal content favors the four-electron pathway with lower hydrogen peroxide selectivity, whereas higher Mo loadings promote bifunctional behavior, enabling both in situ H₂O₂ generation and hydroxyl radical production. Undoped and doped xerogels were very active for TTC degradation via the electro-Fenton process, but the presence of MoO₃ and Mo₂C phases improved up to 12% in removal efficiency after 480 min of treatment. Full article

This study investigated lactic fermentation of green buckwheat beverages formulated at 8% (A, AA) and 10% (B, BB) solids using single- and multiple-strain cultures of Lactiplantibacillus plantarum, Lactobacillus acidophilus, Lacticaseibacillus paracasei and Lacticaseibacillus rhamnosus. Fermentation at 37 °C rapidly reduced pH from slightly alkaline values (7.44–7.57) to approximately 4.2–4.5 within 3–8 h, while viable counts increased from near-zero to 8–9 log₁₀CFU mL⁻¹, confirming efficient lactic acid bacteria (LAB) proliferation in all substrates. A general trend was observed in the sugar consumption strategy of studied LAB: sucrose (after hydrolysis) and glucose were almost completely depleted within 6–8 h, fructose was consumed more slowly, and raffinose remained largely unchanged, with the 10% substrate mainly accelerating early sugar turnover without altering final cell densities or the qualitative utilisation pattern. Dry matter changed little during fermentation, whereas total phenolic content (TPC) and total tannin content (TTC) were strongly affected in a matrix- and strain-dependent manner. At 8% solids, fermentation promoted substantial TTC reduction and, for several cultures, a net decrease in extractable phenolics. In contrast, 10% formulations, particularly those inoculated with L. acidophilus and L. paracasei (alone or in combination), partially preserved or increased TPC while achieving more moderate tannin losses. Overall, green buckwheat proved to be a promising substrate for developing fermented beverages in which solids level and starter composition can be tuned to combine rapid acidification and high LAB viability with tailored sugar depletion and favourable modulation of phenolic and tannin fractions. Full article

Rare and safety-critical traffic situations remain challenging for autonomous driving (AD) because they are underrepresented in common training data and may include objects outside standard detector classes. This paper presents a real-time RGB-LiDAR fusion framework for detecting and reacting to rare traffic situations in CARLA (Car Learning to Act), a reproducible simulator for AD research. The approach combines YOLOv8n-based RGB perception, bird’s-eye-view (BEV) LiDAR clustering, decision-level fusion, an interpretable rule-based safety agent with hysteresis, Time-to-Collision (TTC)-aware escalation, and an automatic emergency braking (AEB) override above the CARLA autopilot. Fused observations are classified as semantic–geometric detections, semantic-only detections, or geometric-only obstacle candidates, where unmatched LiDAR clusters are treated conservatively as candidate-level physical evidence rather than confirmed rare objects. The framework was evaluated on three CARLA maps and 3CSim-inspired corner-case scenarios comprising 19,253 frames, with additional weather/lighting stress tests and a public nuScenes mini cross-platform check. On a manually annotated subset of 4800 CARLA frames, corresponding to approximately $24.9\%$ of the recorded CARLA log, the full framework achieved $96.2\%$ precision, $97.3\%$ recall, and a $96.7\%$ F1-score for safety-relevant threat detection. The control experiments show that the fusion-based safety agent reduced unnecessary braking to $1.7\%$ compared with $8.6\%$ for the LiDAR-only baseline and achieved event-level success on the annotated critical intervals. The proposed CPU-only implementation maintained real-time performance, with an average processing time of $34.7\mathrm{ms}$. Full article

This study presents a denominator-conditioned functional-coverage framework for rear-end automated emergency braking (AEB). The framework estimates what share of a declared modeled rear-end hazard denominator is controllable at a given intervention lead time. Ego–lead episodes come from NGSIM US-101 and I-80; the default D0 denominator is a modeled no-action counterfactual from episode-entry states, not a replay of observed future motion or a crash-rate estimator. A longitudinal brake-only replay model estimates policy-specific required lead times for transparent reference policies: a brake-only upper envelope, TTC-family references, a stopping-distance reference, and an RSS-style baseline. Under the default pipeline, the upper envelope saturates near 99%, the weak TTC anchor covers roughly half of the denominator, and stronger references reach about 95–96% frequency-weighted saturation. Duration filters change the saturation by at most 4.00 percentage points, and increasing physical-uncertainty realizations from R = 3 to R = 30 changes the saturation by at most 0.33 percentage points. An extended TTC-family audit shows that a coverage-only candidate reaches 99.00% saturation but 30.70% nuisance intervention, whereas a burden-constrained candidate reaches 97.88% saturation with 9.23% nuisance. The reported values are conditional controllability measures, not certification evidence or deployment-level crash-rate estimates. Full article

Sustaining rice productivity under the dual constraints of freshwater scarcity and low-temperature stress represents a pressing challenge for high-latitude japonica rice systems worldwide. There is an urgent need to develop coupled irrigation–agronomic management strategies that jointly safeguard yield stability and water use efficiency (WUE) in cold-region rice production. In this study, a two-year field experiment was conducted in 2024–2025 on albic soil (Albic Luvisols, WRB; θfc 38.2% v/v, pH 5.80, clayey texture with poor permeability and a propensity for subsurface waterlogging) in the Sanjiang Plain, Heilongjiang Province, China (47°15′ N, 133°28′ E), with nine coupled “irrigation regime × auxiliary practice” treatments, comprising conventional continuous flooding, four-level controlled irrigation (CI) at lower thresholds of 60%, 70%, 75%, and 80% θfc, and their combinations with film mulching (FM) or a humic-acid-based soil amendment (SA). An interpretable machine-learning diagnostic framework was developed, with elastic net (EN) as the primary analytical model and random forest (RF) as a nonlinear control, to simultaneously identify core yield predictors and outlier treatments. The principal findings were: (i) The soil-amendment-coupled 75% θfc CI treatment (SACI) increased grain yield by 12.3% and reduced water input by 17.0% relative to conventional continuous flooding, with WUE reaching 1.801 kg m⁻³, a 35.3% gain over the control (p < 0.05); these improvements were consistent across both individual years (year × treatment interaction: p = 0.601; inter-year rank correlation ρ = 0.967). Lowering the CI threshold below 75% θfc significantly reduced grain yield through diminished effective-panicle retention. (ii) Multi-method consensus analysis (Kendall’s W = 0.871, p < 0.01) identified root volume at the milk stage as the most strongly and consistently associated statistical predictor of yield formation, with convergent mechanistic support from independent rhizosphere evidence (Eh, TTC reductive activity). Definitive causal validation awaits isotope-tracing experiments. (iii) The film-mulching × continuous-flooding treatment (FMCG) was diagnosed as a yield-response outlier (permutation test p = 0.003), three in situ rhizosphere measurements (redox potential, root TTC-reducing activity, and rhizosphere temperature) supported the proposed mechanism of hot–anoxic rhizospheric inhibition. Methodologically, this study develops a four-level evidence convergence framework that integrates intra-model self-consistency, cross-model (EN vs. RF) consensus, independent rhizosphere evidence, and distribution-free permutation testing, with Jackknife+ conformal prediction and companion Monte Carlo simulations (1000 replicates) used to quantify the reliability boundaries under small-sample conditions (n = 27). These findings provide an evidence-based irrigation–soil co-management strategy for cold-region rice production in Northeast China, and the proposed diagnostic paradigm offers a generalizable, reliability-quantified methodological template for interpretable small-sample modeling in multifactorial coupled field experiments. Full article

Real-time traffic safety analysis is necessary to determine proactive risks associated with traffic conflicts. This study presents a driving-risk detection framework based on high-precision naturalistic vehicle trajectory data to support host vehicle driver-warning systems. A rear-end conflict identification approach based on time-to-collision (TTC) is employed to detect vehicle interactions as safe or unsafe. To capture temporal driving patterns, frame-level observations are transformed into sequential samples using a sliding-window strategy while preserving the natural class imbalance of real-world traffic data. Several conventional machine learning models, including CatBoost, LightGBM, XGBoost, Random Forest, Extra Trees, Decision Tree, and SVM, as well as recurrent deep learning models such as Simple RNN, LSTM, and GRU, are evaluated using leave-one-subject-out cross-validation across seven expressways. Among the evaluated models, the Simple RNN achieves a recall of 99.12% and an F1-score of 98.48%, outperforming the conventional machine learning models. Its predictive performance is comparable to that of LSTM and GRU while offering lower inference latency, making it suitable for real-time deployment. A SHAP-based Explainable AI analysis is conducted to identify the most influential factors in conflict detection and to provide insight into model predictions. The analysis supports that host vehicle speed, preceding vehicle speed, and inter-vehicle gap are the primary determinants of rear-end conflict risk. This proactive and interpretable framework, evaluated offline on naturalistic trajectory data, demonstrates strong potential for integration into real-time driver-warning systems. Full article

To address the strong constraints, multiple objectives, and high dynamism of space telemetry, tracking, and command (TT&C) resource scheduling in flight-type launch scenarios, this study proposes a dynamic scheduling approach that integrates priority rules with adaptive multi-task evolution. First, a mixed-integer programming model is developed to capture fixed and mobile equipment, diverse mission requirements, and spatiotemporal coupling constraints, with the optimization objectives of minimizing the total mobile distance, the total number of deployed devices, and the number of mobile devices deployed. Second, a priority-based dynamic rescheduling mechanism is designed to support rolling insertion of emergency tasks and, when necessary, adjust conflicting tasks according to priority rules. Third, an improved NSGA-II algorithm is introduced, incorporating adaptive population adjustment, early stopping, and decoding caching to enhance multi-task search efficiency and convergence stability. Finally, a simulation experiment is constructed based on a typical commercial launch scenario, targeting three types of static task scenarios of different scales; the proposed Adaptive-NSGA-II consistently yields feasible schedules, while reducing the solution time by 70.4%, 62.7%, and 61.0%, respectively, compared with standard NSGA-II. In the dynamic emergency task insertion scenarios, the proposed priority-rule-based rolling rescheduling strategy successfully completes insertion in all three cases, achieves zero additional mobile distance in low-conflict scenarios, and remains significantly superior to the fixed-time direct insertion strategy even under high-conflict conditions. The experimental results demonstrate the effectiveness, robustness, and engineering applicability of the proposed method for TT&C resource scheduling in flight-type launch operations. Full article

Monitoring ultraviolet (UV) radiation dose distribution is crucial in many fields, like medicine and materials science, but traditional point-of-care methods limit the ability to fully assess the spatial extent of the irradiated surface. This paper presents the characterisation of a two-dimensional (2D) dosimetry system based on Pluronic F-127 hydrogel matrix doped with 2,3,5-triphenyltetrazolium chloride (TTC) with respect to exposition to UVA radiation. The hydrogel matrix (25% w/w) provides both high transparency and mechanical stability, while TTC (0.1% w/w) functions as a colour precursor that undergoes irreversible reduction to form water-insoluble red formazan upon UVA exposure. The insolubility of TTC formazan ensures that the resulting colour changes remain spatially stable within the dosimeter. The study included sample preparation in flat PMMA containers and analysis of the effect of radiation field uniformity in a UVP CL-1000 exposure chamber. It was supported by application of Kodak X-Omat 100 NIF UV Film dosimetry. The actual dose distribution in the chamber was shown to be significantly heterogeneous (CV coefficient of variation of approximately 18%), which emphasises the need for 2D dosimeters for precise validation of irradiation devices. The use of flatbed scanning and dedicated image analysis software allowed obtaining precise 2D dose distribution maps. The dosimeter was characterised in the dose range of 0–5000 mJ/cm², showing a reproducible response (R² = 0.9967). A resolution test was conducted to assess the precision of geometric representation. In the final stage of the study, the suitability of the developed dosimetry system was verified under conditions simulating heterogeneous UV radiation dose distribution using patterns printed with Computer-to-Film (CtF) technology. The results showed that optical effects in printed films significantly affect UV transmission, limiting accurate dose recording for black coverage above approximately 40–50%. The results obtained confirm that the TTC-Pluronic F-127 system is an effective, simple and low-cost tool for 2D monitoring of UVA radiation, with potential applications in cosmetology, dermatology, and material ageing tests. Full article

Four-wheel independent steering (4WIS) vehicles can improve low-speed maneuverability and high-speed stability by independently regulating the steering angles of all four wheels. However, under large-curvature trajectories, parameter perturbations, and external disturbances, inconsistent coordination among the four-wheel steering angles may increase tire lateral slip, yaw response deviation, and trajectory tracking errors. To address the difficulty of conventional trajectory tracking methods in simultaneously ensuring geometric consistency, tracking accuracy, and robustness, this paper proposes an adaptive sliding mode trajectory tracking control method based on instantaneous center of rotation (ICR) constraints. First, the tire instantaneous turning center (TTC) of each wheel is derived using rigid-body spatial kinematics, and the TTCs are mapped onto a unified vehicle-body reference plane based on the SAE J670 coordinate system to obtain a real-time vehicle-level ICR estimation. Second, a lateral–yaw dynamic model and a trajectory tracking error model are established. The yaw rate and sideslip angle are corrected using ICR geometric information, and an adaptive sliding mode controller is designed with an equivalent control term, adaptive switching gain, adaptive boundary layer, and sideslip suppression term. The uniform ultimate boundedness of the sliding variable and closed-loop tracking errors is proven using Lyapunov theory. Finally, MATLAB (2023a)2024/CarSim (2019) co-simulations are conducted under small-curvature sinusoidal, double-lane-change, large-curvature sinusoidal, low-adhesion, and mass-perturbation conditions. The results show that the proposed ICR-SMC method significantly reduces lateral and heading errors compared with U-LQR and U-SMC, especially under large-curvature and low-adhesion conditions, demonstrating improved tracking accuracy and robustness for 4WIS vehicles. Full article

Background: Scutellaria baicalensis (Scu) extract has been traditionally used in the treatment of stroke-related syndromes, yet its underlying molecular mechanisms, particularly those involving ferroptosis, remain to be fully elucidated. Purpose: This study aims to validate the hypothesis that Scu extract improves cerebral ischemia-reperfusion injury (CIRI) by inhibiting ferroptosis through the PI3K/AKT signaling pathway. Methods: This study employed middle cerebral artery occlusion (MCAO) in male Sprague-Dawley (SD) rats and oxygen–glucose deprivation/reoxygenation (OGD/R) models to evaluate the protective effects of Scu extract against CIRI. Multiple approaches were integrated to elucidate the underlying mechanisms. Furthermore, a range of experimental techniques, including neurological function assessment, TTC staining, histopathological analysis, biochemical assays, qPCR, transmission electron microscopy (TEM), reactive oxygen species (ROS) detection, Western blotting, and immunofluorescence, were used to comprehensively validate its neuroprotective effects. Results: Scu extract significantly improved neurological outcomes and attenuated brain injury in MCAO rats. Proteomic analysis revealed significant enrichment of ferroptosis-related pathways, which was supported by reduced mitochondrial damage, decreased iron accumulation, and restoration of the SLC7A11/GPX4 axis. Subsequently, UPLC/Q-TOF-MS analysis revealed that four major bioactive components were absorbed in MCAO rats. KEGG pathway analysis based on network pharmacology further indicated that the PI3K/AKT signaling pathway is a key regulatory target. Notably, pharmacological inhibition of PI3K with LY294002 markedly abolished the anti-ferroptotic effects of Scu extract, which was further confirmed in vitro. Conclusions: This study demonstrates that Scu extract confers neuroprotection against CIRI in MCAO rats potentially through inhibiting ferroptosis via activation of the PI3K/AKT pathway. Full article

Background: Systemic arterial hypertension (SAH) induced by Nω-nitro-L-arginine methyl ester (L-NAME) is a well-established model characterized by nitric oxide (NO^●) synthase inhibition and vascular dysfunction. The transient receptor potential vanilloid 1 (TRPV1) regulates Ca²⁺ flux and may contribute to mitochondrial homeostasis. We hypothesized that TRPV1 activation modulates mitochondria function and attenuates cardiac damage during SAH. Methods: Hypertension was induced in Wistar rats by administration of L-NAME (200 mg/L) for 40 days. During the last four days, hypertensive animals received capsaicin (5 mg/kg/day), capsazepine (6 mg/kg/day), or their combination. Cardiac function was evaluated in isolated hearts using the Langendorff perfusion system. Myocardial tissue viability was assessed by triphenyltetrazolium chloride (TTC) staining, and mitochondrial function was evaluated by measuring respiratory control and apoptosis-related proteins. Results: Capsaicin treatment was associated with significant cardioprotective effects in hypertensive rats. Although the findings are consistent with a role of TRPV1 activation in mediating these effects, the partial protection observed with capsazepine suggests that TRPV1-independent mechanisms may also contribute. Conclusions: TRPV1 activation contributes to cardioprotection in SAH, likely through preservation of mitochondrial function and redox balance. However, additional mechanisms beyond TRPV1 modulation may also participate in the observed protective effects. Further studies—including direct assessment of mitochondrial Ca²⁺ flux and the use of more selective or genetic approaches—are currently underway to clarify the underlying mechanisms. Full article

Pollen viability is a crucial determinant of reproductive success in plants. Given the enormous threat posed to the common ash (Fraxinus excelsior L.) by ash dieback, it is important to investigate the potential disease’s effects on pollen viability and germination. Thus, we conducted an analysis of these pollen characteristics across three distinct forest stands in southern Bavaria, with up to 23 ash trees per study site. These ash trees exhibited varying degrees of ash dieback-related damage symptoms, enabling us to assess differences between mildly and severely affected trees (via Mann–Whitney-U/Wilcoxon tests, complemented by linear mixed-effects modelling). Pollen viability was assessed using the TTC test, while pollen germination capacity was evaluated on a sucrose–agar medium. Our findings revealed no statistically significant differences in pollen viability between mildly affected and severely diseased trees, as indicated by both the TTC test and pollen germination assay when applying non-parametric analyses (Mann–Whitney U and Kruskal–Wallis tests). Nevertheless, a consistent tendency towards higher pollen viability was observed in healthier ash trees. When accounting for the hierarchical structure of the data using linear mixed-effects modes, tree vitality showed a significant effect on pollen viability, whereas a substantial proportion of the observed variation was explained by interannual differences. These results indicate that ash trees generally retain the capacity to produce viable pollen across different levels of disease severity, but vitality-related effects are subtle and context-dependent. However, severely diseased trees produced few or no flowers, substantially reducing the likelihood that their pollen contributes to fertilization. We therefore conclude that ash dieback primarily limits reproductive success in common ash mainly by reducing flower and pollen production, whereas pollen viability itself is strongly driven by interannual differences. Consequently, no consistent pattern of declining pollen viability with increasing disease severity emerged. Full article

Pedestrian safety at signalized intersections is a key component of sustainable urban mobility, as safer walking environments support active transportation, reduce crash risk, and improve the inclusiveness of urban transport systems. This study presents a structured review of pedestrian–vehicle conflicts based on a systematic PRISMA-guided literature search, synthesizing 60 studies with emphasis on operational conditions, behavioral factors, infrastructural characteristics, and surrogate safety measures. The review examines the application of surrogate safety measures (SSMs), including Time-to-Collision (TTC), Post-Encroachment Time (PET), Pedestrian Path Deviation (PPD), and Deceleration-to-Safety Time (DST). The findings reveal significant variability in threshold definitions and methodological approaches, which limits the comparability and transferability of results across different traffic contexts. Building on this synthesis, the paper proposes an integrated conceptual framework linking behavioral, operational, and infrastructural determinants to conflict occurrence and severity. The analysis shows that existing studies often treat these factors in isolation, reducing the generalizability of current models. Overall, this review identifies key methodological inconsistencies in surrogate safety indicators and emphasizes the need for standardized yet context-sensitive thresholds and locally validated conflict models to improve the comparability and transferability of pedestrian–vehicle conflict assessments. Full article

Autonomous driving technology is widely recognized as a key solution for enhancing future road safety by preventing traffic accidents caused by human error. However, the widespread adoption of autonomous vehicles (AVs) has not yet been achieved, and traffic accidents involving autonomous vehicles in mixed traffic conditions continue to be reported. This study analyzed conflict events using real-world autonomous driving data and identified AV conflict hotspots. A two-dimensional Time to Collision was employed as a surrogate safety indicator to comprehensively capture various types of conflicts in urban interrupted traffic flow. Analysis of approximately 1000 h of driving data revealed 958,011 conflict events, which were distributed along major AV trajectories. The Network Kernel Density Estimation was applied to identify AV conflict hotspots based on conflict events. The optimal hotspot identification model was determined by evaluating various parameter combinations using the Predictive Accuracy Index validated against real-world accident data. Several hotspots were identified on arterial roads with signalized intersections, nearby bus stops, and frequent access points to roadside facilities such as restaurants, stores, gas stations, and residential complexes. Differences in hotspot patterns by conflict type reveal distinct risk characteristics across road sections, emphasizing the necessity of customized safety countermeasures for each conflict type. The findings of this study are expected to accelerate the deployment and wider adoption of autonomous driving technology, promoting the sustainable operation of AVs. Full article