Search Results (2,696)

Consumers are looking for plant-based drinks that provide natural colour and bioactive compounds. Microgreens can be used as a source of pigments and phenolics for such beverages. This study developed a beetroot–tarragon microgreen beverage using hydroalcoholic extracts obtained with a green extraction approach and examined its stability during refrigerated storage. The drink was evaluated for proximate composition, water activity, colour parameters (CIE L*a*b*), microbiological quality and antioxidant activity by the ABTS radical cation decolorization assay (ABTS) over 15 days at 4 ± 2 °C. The beverage showed low fat and energy content and water activity values close to 1.00, so microbiological safety relied on pasteurization and cold storage. Escherichia coli and Staphylococcus aureus were not detected, while total aerobic mesophilic counts reached 10⁴–10⁵ colony-forming units per gram (CFU/g), with slightly lower values in samples containing tarragon. Colour measurements indicated betalain loss and colour fading in the beetroot drink, whereas the reduction in E* was more than 80 percentage points lower in the beetroot–tarragon beverage than in the beetroot-only drink, indicating a strong protective effect of tarragon microgreens on colour stability. For the mixed beetroot–tarragon beverage, mean TEAC increased by about 37% between day 1 and day 10 of refrigerated storage. These results indicate that beetroot and tarragon microgreen extracts can be used to formulate refrigerated plant-based beverages with acceptable colour, microbiological safety and antioxidant capacity. Full article

This paper presents a distributed coordination framework for simultaneous multi-target tracking using a mobile wireless sensor network (MWSN) based on discrete-event-system principles. The proposed framework employs a finite-state-machine architecture, where autonomous mobile sensors sequentially process detection and tracking events. Unlike passive tracking approaches that react to target loss after it occurs, the proposed strategy implements predictive handover through Extended-Kalman-Filter-based uncertainty propagation. This enables sensors to anticipate target loss and to reposition auxiliary sensors in advance, acquiring targets along their predicted trajectories. A bidding-based allocation mechanism coordinates sensor assignments by evaluating four competing objectives: network preservation, spatial proximity to handover points, temporal mission feasibility, and estimation uncertainty. The proposed framework integrates four components: EKF-convergence-triggered proactive handover, multi-objective competitive bidding, distributed min–max conflict resolution, and fusion-driven proportional navigation. Unlike existing methods, auxiliary sensors navigate using confidence-weighted EKF estimates shared by neighboring sensors rather than their own measurements. An ablation study over ten Monte Carlo trials confirms that each component contributes independently, with EKF-based predictive triggering identified as the dominant performance driver. Full article

Compressed sensing (CS) enables signal reconstruction from fewer measurements when the signal is sparse in a transform domain. However, executing ${\ell }_1$-regularized recovery on MCU-class hardware is challenging due to limited compute resources and the cost of repeated forward and adjoint operator evaluations. This paper presents a band-limited proximal variant of FISTA that enforces known spectral support during thresholding, restricting the effective optimization domain without changing the measurement model. We implement a complete CS reconstruction pipeline on an STM32F407 (Cortex-M4) using CMSIS-DSP FFT/IFFT kernels and evaluate it using ECG waveforms acquired through an AD8232 front end as benchmark signals. With $M=340$ measurements (33% of uniform sampling), the embedded implementation achieves a PRDN of 24.38%, closely matching MATLAB references (CVX: 22.64%, FISTA: 22.39%) under identical hyperparameters. Cycle-accurate profiling shows that FFT/IFFT-based forward/adjoint operators dominate the per-iteration runtime. Under a 60 Hz band-limited setting, the required iterations are reduced from 30 to 16 with an acceptable PRDN, demonstrating a practical trade-off between reconstruction accuracy and computational cost on MCU-class devices. Full article

Coastal zones are facing rising exposure to climate-related hazards alongside intensifying human pressures, which highlights the need for robust tools to assess vulnerability. This study uses a GIS-based Coastal Vulnerability Index (CVI) to quantify and map relative vulnerability along ~13 km of shoreline in Al Hoceima Bay (northern Morocco). The proposed CVI integrates eight geological and physical indicators, including geomorphology, shoreline erosion and accretion rates, coastal slope, elevation, natural habitats, relative sea-level rise, significant wave height, and tidal range. Spatial analyses were performed using remote sensing data, historical records, field measurements, and Geographic Information Systems (GIS). The analysis reveals that 37% of the shoreline is categorized as high vulnerability, 44% is moderate, and 19% is low. Highly vulnerable sectors are primarily associated with low elevations, gentle coastal slopes, sandy beach systems, limited natural habitat protection, and proximity to river mouths. These findings demonstrate that the applied CVI provides a rapid and cost-effective framework for identifying priority areas for coastal management and climate adaptation. The proposed approach offers valuable decision-support insights for sustainable coastal planning in Al Hoceima Bay and other Mediterranean coastal environments characterized by limited data availability. Full article

The present contribution provides a systematic review of the international scientific literature on the relationship between contaminated sites and real estate market dynamics. The objective is to investigate whether and to what extent the presence of environmental risk sources—both active or decommissioned—affects the value of surrounding residential properties. In particular, the review is focused on an examination of the methods commonly used in relevant studies to measure, interpret, and represent this impact across different geographical contexts, identifying the main magnitude ranges found in the selected contributions. Several studies consistently confirm a statistically significant negative relationship between proximity to polluting sites and real estate values, although the relevance of this effect varies considerably across case studies. Other records highlight non-notable impacts or even positive effects following remediation and redevelopment interventions. The evidence suggests that this relationship is complex and influenced by factors such as site type, contamination severity, specificities of the local urban context and community perception. Moreover, the findings underscore regional variations in the extent and nature of price impacts, reflecting diverse regulatory frameworks and remediation efforts. The outcomes of the literature review provide a robust foundation for developing more effective evaluation tools able to support decision-making processes, enabling policymakers, planners, and investors to promote sustainable urban regeneration, improve environmental justice, and reduce spatial inequalities. Ultimately, this study highlights the critical need for integrating environmental, social, and economic dimensions to fully capture the multifaceted effects of contaminated sites on property markets, thereby orienting more informed and equitable urban development strategies worldwide. Full article

Abiotic stresses, such as drought, salinity, and aluminum toxicity (Al³⁺), affect the growth and initial establishment of wheat plants, limiting crop yield in restrictive growing environments. Therefore, the early selection of tolerant genotypes adapted to multiple production environments is essential to optimize wheat production. A laboratory experiment was conducted to identify and recommend wheat cultivars that simultaneously combine adaptability and stability for initial morphological responses when subjected to stressful environmental conditions. Plants from 12 wheat cultivars were grown under non-stressful (control) and stressful conditions (drought, salinity and Al³⁺ stress), using a 4 × 12 factorial arrangement with four replicates. On the 28th day, the emergence rate, length, dry matter and vigor of the plants were measured. Abiotic stresses limit the initial growth and vigor of wheat plants, with drought causing the greatest limitation for plant growth and biomass accumulation, while salinity had the greatest impact on plant vigor indices. Aluminum toxicity limits root development and biomass allocation. Principal component analysis explained 67.76% of the total variability and distinguished the plant growing environments. The multi-trait index proved effective in cultivar selection, highlighting the cv. ORS Feroz due to its proximity to the ideotype and adaptability to multiple abiotic stresses. Full article

Bipolar vessel sealing systems are widely used in surgery, yet their effectiveness varies depending on the histological composition of the target vessel. In particular, the influence of elastin on seal stability is not well understood. Porcine carotid arteries, which show a pronounced proximal–distal elastin gradient, provide an ideal model for systematic analysis. In this study, fresh porcine carotid arteries were divided into three segments based on vessel diameter (<5 mm, 5–7 mm, >7 mm). Histological EvG staining was used to quantify elastin and collagen content. All vessels (n = 8 per group) were sealed using a bipolar marSeal^® 5 plus device, followed by burst pressure testing and peel force measurements. Elastin content increased significantly from peripheral to central segments (9% → 25% → 42%; p < 0.001), while collagen content remained constant (22 ± 2%). In parallel, seal stability decreased markedly: burst pressures dropped from 723 mmHg to 240 mmHg and to 31.5 mmHg (p < 0.001). Peel forces showed the same trend (1.75 ± 0.07 N → 0.65 ± 0.03 N → 0.26 ± 0.11 N; p < 0.001). Wall thickness showed no proportional relationship to seal quality. Interestingly, the sealing performance of bipolar systems seems to be greatly influenced by the histological structure of the vessel wall. A high elastin content—rising from 9% to 42% along the carotid artery—was associated with a reduction in burst pressure and peel strength. These findings highlight the need to consider tissue composition when selecting sealing methods and support the development of adaptive energy delivery technologies. Full article

Longnan, located in Gansu Province, China, at the junction of Shaanxi, Gansu, and Sichuan provinces, represents one of the key corridors of the Northern Tea-Horse Ancient Road. This region preserves abundant traditional timber covered bridges with distinct local characteristics. This study employs ArcGIS spatial analysis and documentary research methods to explore the spatial distribution, spatiotemporal evolution, and influencing factors of these bridges. Spatial analyses (nearest neighbor index, kernel density, and standard deviational ellipse) are based on 71 bridges with traceable coordinates, while the temporal evolution analysis incorporates 80 bridges (64 with definite construction periods and 16 with unknown dates; the latter are handled through a sensitivity analysis as described later in this paper The results indicate that the timber covered bridges in Longnan exhibit a significantly clustered distribution, presenting a pattern of “dense in the southwest and sparse in the northeast”, with Wen County and Kang County as the core clustering areas. Temporally, they follow a unimodal evolution pattern: initiation in the Ming Dynasty, peak in the Qing Dynasty, decline in the Republic of China period, and near stagnation in modern times. The location and distribution of the covered bridges show a strong statistical association with natural conditions (e.g., topography, hydrology) and exhibit spatial coincidence with modern vegetation coverage—the latter treated solely as a contemporary context variable rather than a historical driver. Spatial coincidence with the ancient road is quantified (60.56% within a 2000 m buffer), while settlement proximity is only qualitatively noted as background. Socio-economic factors (e.g., population, transportation, and settlements) are examined qualitatively and display spatial coincidence rather than quantitatively measured influence; these factors cannot be directly compared with natural factors. Full article

Background: Optimal phase selection in coronary computed tomography angiography (CCTA) is crucial. While the mid-diastolic slow-filling (SF) phase is typically predicted using a conventional formula based on heart rate and atrioventricular conduction time, its validity in complete left bundle branch block (CLBBB)—where pronounced QRS prolongation induces severe mechanical dyssynchrony—remains unclear. We evaluated the impact of bundle branch block on cardiac-phase selection and validated a QRS-corrected predictive model. Methods: We retrospectively analyzed 94 patients (sinus rhythm, n = 40; complete right bundle branch block [CRBBB], n = 36; CLBBB, n = 18). Measured SF at the proximal right coronary artery was compared against predictions from the conventional formula (SF = −362 + 0.742 × [RR − PQ]) and a proposed QRS-corrected formula incorporating a “−(QRS − 100)” subtraction. To test the necessity of a novel model, regression analyses were reconstructed exclusively for the CLBBB cohort. Results: In CLBBB patients, the conventional formula critically overestimated SF by an average of 37.9 ms (RMSE 42.5 ms). Reconstructing simple and multivariate regression models exclusively for the CLBBB group yielded coefficients remarkably similar to the conventional formula, indicating that the fundamental physiological dependency on RR and PQ intervals remains intact despite the bundle branch block. Crucially, the simple proposed QRS-corrected formula successfully eliminated the overestimation bias (mean error −6.9 ms; p = 0.176) and demonstrated the highest predictive accuracy (RMSE 21.2 ms). Conclusions: A completely new predictive regression model is unnecessary for CLBBB patients. Simply incorporating a theoretical subtraction of pathological QRS prolongation optimally corrects the diastolic resting phase. Full article

Background/Objectives: Evidence on the role of muscle mechanical (myotonic) properties in athletic performance remains limited in young adult and sub-elite populations, particularly in American football, and sex-specific patterns of association are not well understood. This study aimed to investigate the associations between lower extremity myotonic properties and performance outcomes (strength and balance) in American football athletes, with a specific focus on sex-related differences and candidate predictors. Methods: A cross-sectional design was implemented involving 35 American football athletes (17 female, 18 male). Lower extremity muscle tone, stiffness, and elasticity were assessed using MyotonPRO. Strength parameters (lower limb, handgrip, back, and shoulder internal rotation) and balance performance (static and dynamic under eyes-open and eyes-closed conditions) were evaluated using standardized measurement protocols. Pearson correlation analysis was conducted to examine bivariate associations, followed by Least Absolute Shrinkage and Selection Operator (LASSO) regression to determine candidate predictors while addressing multicollinearity. Results: Male athletes exhibited significantly greater height, body mass, and BMI (p < 0.001), alongside elevated myotonic values compared to females. Correlation analyses indicated distinct sex-specific association patterns between myotonic properties and performance metrics. LASSO regression revealed a distinct sex-specific divergence in strength prediction: female strength was predominantly driven by proximal musculature (quadriceps and hamstring elasticity/stiffness), whereas male strength was anchored by distal musculature (gastrocnemius tone/stiffness). Furthermore, rigorous penalization shrunk nearly all balance coefficients to zero in both sexes, indicating that resting myotonic properties do not independently predict dynamic or static postural control. Conclusions: While lower extremity myotonic properties are candidate predictors of multi-regional strength via sex-specific proximal and distal strategies, they do not independently predict balance performance, suggesting postural control relies primarily on active motor recruitment rather than passive resting mechanics. Given the cross-sectional design of this study, causal inferences cannot be drawn, and these findings should be interpreted accordingly. The observed sex-specific differences may support consideration of individualized, sex-informed training strategies in American football athletes. Full article

Decision-making is a critical module for intelligent vehicles to achieve safe and efficient autonomous driving. However, most existing reinforcement learning-based decision-making methods optimize policies by maximizing the expected return, which may inadequately account for low-probability but high-cost safety risks in complex traffic interactions. To address this issue, this paper proposes a Risk-Sensitive Distributional Proximal Policy Optimization (PPO) method, termed Risk-Sensitive Distributional Proximal Policy Optimization (RSDPPO), for highway lane-changing decision-making. Within the PPO framework, a distributional state-value function is introduced to model the return distribution under the current policy, and a Wang distortion-based risk measure is further incorporated to construct a risk-sensitive advantage function. In this way, risk information contained in the return distribution can be propagated into the policy gradient update, guiding the learned policy to avoid high-risk driving behaviors while maintaining training stability. Simulation experiments are conducted in a highway lane-changing scenario with heterogeneous surrounding vehicles. The results show that, under medium-density traffic, the proposed method outperforms representative baseline algorithms in cumulative reward, success rate, and safety reward. Further evaluation under higher-density traffic demonstrates that RSDPPO maintains better overall performance, indicating stronger adaptability to denser traffic conditions. Ablation studies further show that risk-averse distortion improves the balance between safety and efficiency by increasing safety margins during car-following and lane-changing maneuvers. These results indicate that RSDPPO provides an effective risk-sensitive policy optimization framework for safety-oriented highway lane-changing decision-making. Full article

The mineral system model formalizes the critical geological processes and mappable parameters that control ore formation, which can then be translated into spatial predictors used as input features in machine learning (ML)-based mineral prospectivity mapping (MPM). In most MPM studies, exploration evidence features are indeed derived from the mineral system model of the targeted deposit type. However, not all features produced in this way are necessarily informative or favorable for prospectivity analysis. This challenge can be addressed by using feature selection frameworks to identify the most relevant features before applying ML and deep learning (DL) algorithms for mathematical integration. To address this need, this study employs an unsupervised variational autoencoder (VAE) framework to evaluate and rank exploration evidence layers. The VAE quantifies feature importance through a systematic strategy that measures the sensitivity of reconstruction-error components, mean squared error (MSE), mean absolute error (MAE), and Kullback–Leibler (KL) divergence, to individual feature variations. In this way, the VAE ranks the exploration features and helps to identify those that are the most useful for prospectivity mapping. The proposed approach was applied to a real geo-dataset from a porphyry copper district in Iran. Based on the conceptual model of porphyry copper mineralization, 15 evidence layers were generated, including proximity to phyllic, argillic, propylitic, iron oxide, and silicification alteration zones; proximity to intrusive rocks, faults, and fault intersections; and geochemical maps of Cu, Mo, Sb, Pb, Zn, As, and W. The VAE-based ranking indicated that evidence layers related to hydrothermal alterations, intrusive rocks, and faults were the most influential exploration features, whereas geochemical evidence layers showed lower relative importance. Based on this evaluation, two modeling scenarios were considered: in the first, all available features were used, and in the second, only the features selected by the VAE framework were included. In both cases, the final prospectivity model was produced by an autoencoder (AE). For comparison, the prediction-area (P–A) plots of the two prospectivity models were generated using 14 known mineral occurrences as positive ground-truth labels, indicating that the model based on the selected features achieved a higher prediction rate (80%) than the model based on all features (72%). These results demonstrate that the evidence layers derived from the mineral system approach can benefit from unsupervised VAE-based evaluation, leading to improved performance of the prospectivity modeling. Full article

All rotating electrical machines are susceptible to vibrations arising from electromagnetic (EM) forces, electrical faults, mechanical defects, imbalance, and structural resonance. In Doubly Fed Induction Generators (DFIGs), such electromechanical vibrations are especially important because they can degrade reliability, increase noise, and lead to severe damage if resonance-prone operating conditions are not identified in time. Although fault diagnosis in DFIGs has been widely investigated using current, voltage, and flux signatures, comparatively fewer studies have examined fault-specific vibration behaviour under stator and rotor interturn faults (ITTFs), particularly through a coupled EM structural framework. In addition, prior vibration-based studies have not examined the influence of end winding ITTFs, its location, severity, and modal interaction investigating resonance risk. This paper considers vibration characteristics of a variable-speed 2.8 MW DFIG used in a grid-connected Type-3 wind turbine unit (WTU) at no-load operating condition. The DFIG is modelled in ANSYS Academic Research v 2022 R2 Maxwell for EM behaviour assessment for ITTFs in both stator and rotor windings along with modal analysis (MA) in ANSYS Workbench to examine the undamped stator and rotor modes over a range of frequencies. This coupled approach enables identification of vibration signatures associated with different ITTF types. The results show the magnetic flux density near faulty end-winding region increases with fault severity and ranges from 4.19 T to 4.39 T in proximity to faulty windings. A dominant modal frequency band of 60–65 Hz is identified, where stator and rotor modes coincide, creating probable resonance conditions. A severe vibration response is observed for single-phase stator ITTF, showing an amplitude of 2116 mm/s at 480 Hz for a larger number of shorted turns, indicating that asymmetric faults can produce stronger EM excitation than multi-phase faults. The main contribution of this paper is demonstration of a fault-specific, MA and vibration-based Condition monitoring system (CMS) implementation workflow for a DFIG. Unlike prior vibration-based studies that primarily focus on general machine vibration, mechanical faults, bearings, etc., this paper links stator and rotor ITTF induced EM excitation to modal characteristics, resonance behaviour, and measurable vibration signatures, establishing vibration analysis (VA) as a practical complementary technique for CMS of ITTFs in DFIGs. Full article

This paper presents the design of an inverted-F antenna intended for integration into a smartwatch operating in the 2.4 GHz band. The antenna design addresses spatial constraints imposed by the device’s miniaturized form factor and the proximity of electronic components, including the printed circuit board, display, and battery. The influence of the user’s body on the antenna’s performance characteristics was considered during the design phase through numerical simulations employing the Finite-Difference Time-Domain (FDTD) method with a heterogeneous human body model. Simulation results and measurements of a fabricated prototype antenna are presented, demonstrating satisfactory performance in terms of impedance matching with VSWR below 1.5 in the whole band and gain of −1 dBi. Full article

Background and Objectives: To compare the buccal bone thickness of adjacent maxillary incisors between the impacted and contralateral control sides in patients with unilateral palatally impacted canines (PICs) using a split-mouth cone-beam computed tomography (CBCT) design. Materials and Methods: CBCT records of 26 patients with a unilateral PIC (18 females, 8 males; mean age, 17.35 ± 4.58 years) were retrospectively analyzed. Buccal bone thickness was measured at five equally spaced levels from the root apex (Level A) to the buccal alveolar crest (Level E) for the central and lateral incisors. Alveolar crest height, incisor torque and rotation, follicular width, canine localization, canine-to-root proximity, and root resorption were also assessed. Results: The impacted side showed significantly reduced buccal bone thickness at the two most apical levels of the lateral incisor: Level A (−0.81 mm; p < 0.001) and Level B (−0.35 mm; p = 0.004). No side differences were observed at the remaining lateral incisor levels or at any central incisor level. In the orientation-adjusted sensitivity model accounting for incisor torque and rotation, Level A remained significant (−0.75 mm; p < 0.001), whereas Level B was attenuated (p > 0.005). Lateral incisors on the impacted side also showed reduced labial torque (−4.97°; p = 0.001) and greater mesiobuccal rotation (−12.23°; p < 0.001). Conclusions: PICs were associated with localized apical reduction in buccal bone thickness of the adjacent lateral incisor, accompanied by reduced labial torque and greater mesiobuccal rotation. Buccal bone thickness may represent a relevant consideration during CBCT-based treatment planning for PICs. Full article