Search Results (140,428)

Background and Objectives: Lie detection is crucial in domains such as security, law enforcement, and clinical assessments. Traditional methods suffer from reliability issues and susceptibility to countermeasures. In recent years, electroencephalography (EEG) and particularly the Event-Related Potential (ERP) P300 component have gained prominence for identifying concealed information. This systematic review aims to evaluate recent studies (2017–2024) on EEG-based lie detection using ERP P300 responses, especially in relation to recognized and unrecognized face stimuli. The goal is to summarize commonly used EEG signal processing techniques, feature extraction methods, and classification algorithms, identifying those that yield the highest accuracy in lie detection tasks. Methods: This review followed PRISMA guidelines for systematic reviews. A comprehensive literature search was conducted using IEEE Xplore, Web of Science, Scopus, and Google Scholar, restricted to English-language articles from 2017 to 2024. Studies were included if they focused on EEG-based lie detection, utilized experimental protocols like Concealed Information Test (CIT), Guilty Knowledge Test (GKT), or Deceit Identification Test (DIT), and evaluated classification accuracy using ERP P300 components. Results: CIT with ERP P300 was the most frequently employed protocol. The most used preprocessing method was Bandpass Filtering (BPF), and the Discrete Wavelet Transform (DWT) emerged as the preferred feature extraction technique due to its suitability for non-stationary EEG signals. Among classification algorithms, Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Convolutional Neural Networks (CNN) were frequently utilized. These findings demonstrate the effectiveness of hybrid and deep learning-based models in enhancing classification performance. Conclusions: EEG-based lie detection, particularly using the ERP P300 response to face recognition tasks, shows promising accuracy and robustness compared to traditional polygraph methods. Combining advanced signal processing methods with machine learning and deep learning classifiers significantly improves performance. This review identifies the most effective methodologies and suggests that future research should focus on real-time applications, cross-individual generalization, and reducing system complexity to facilitate broader adoption. Full article

Torsional vibration dampers effectively mitigate torsional oscillations and additional stresses in diesel engine crankshaft systems, ensuring operational safety and reliability. Traditional damper selection principles, grounded in dual-pendulum dynamic models, focus on minimizing maximum torsional angles but fail to accurately characterize vibration behaviors in multi-cylinder engines. This study addresses this limitation by investigating dynamic modeling and numerical methods for an eight-cylinder diesel crankshaft system. A torsional vibration model was developed using Cholesky decomposition and the Jacobi sweep method for free vibration analysis, followed by dynamic response calculations through model decoupling and modal superposition. Parameter optimization of the damper was achieved via the NSGA-II multi-objective algorithm combined with a Bayesian-hyperparameter-optimized BP neural network. The results show that high-inertia-ratio dampers effectively suppress vibration and stress, while low-inertia-ratio configurations require approximately 20% elevated tuning ratios beyond theoretical parameters to achieve an additional 5% stress reduction, albeit with amplified torsional oscillations. Additionally, the study critically evaluates the numerical reliability of conventional dual-pendulum-based tuning ratio selection methods. This integrated approach enhances the precision of damper parameter matching for multi-cylinder engine applications. Full article

Extreme precipitation events are one of the common hazards in eastern Texas, generating a large amount of storm water. Water running off urban areas may carry non-point source (NPS) pollution to natural resources such as rivers and lakes. Urbanization exacerbates this issue by increasing impervious surfaces that prevent natural infiltration. This study evaluated the efficacy of rain gardens, a nature-based best management practice (BMP), in mitigating NPS pollution from urban stormwater runoff. Stormwater samples were collected at inflow and outflow points of three rain gardens and analyzed for various water quality parameters, including pH, electrical conductivity, fluoride, chloride, nitrate, nitrite, phosphate, sulfate, salts, carbonates, bicarbonates, sodium, potassium, aluminum, boron, calcium, mercury, arsenic, copper iron lead magnesium, manganese and zinc. Removal efficiencies for nitrate, phosphate, and zinc exceeded 70%, while heavy metals such as lead achieved reductions up to 80%. However, certain parameters, such as calcium, magnesium and conductivity, showed increased outflow concentrations, attributed to substrate leaching. These increases resulted in a higher outflow pH. Overall, the pollutants were removed with an efficiency exceeding 50%. These findings demonstrate that rain gardens are an effective and sustainable solution for managing urban stormwater runoff and mitigating NPS pollution in eastern Texas, particularly in regions vulnerable to extreme precipitation events. Full article

Circulating fluidized bed combustion flue gas desulfurization generates large volumes of dry desulfurization ash requiring sustainable management. This study evaluated the impacts of substituting desulfurization ash for mineral powder filler in asphalt mastic on low-temperature rheological properties. Asphalt mastics were produced with 0–100% ash replacing mineral powder at 0.8–1.2 powder-binder mass ratios. Ductility and bending beam rheometer testing assessed flexibility and crack resistance. Burgers’ model fitted bending creep compliance to derive relaxation time, m(t)/S(t) index, and low-temperature compliance parameter for analytical insight. Scanning electron microscopy and Fourier transform infrared spectroscopy probed microstructural development and interaction mechanisms. Results showed that the inclusion of desulfurization ash reduced the low-temperature performance of the asphalt mastic compared to the mineral powder asphalt mastic. Additionally, as the temperature decreased further, the effect of the powder-to-gum ratio on the slurry’s crack resistance became less pronounced. Desulfurization ash primarily interacted with the base bitumen through physical means, and the performance of desulfurization ash asphalt slurry mainly depended on the degree of swelling between the desulfurization ash and the base asphalt. Full article

Recent advancements in deep-learning and computer vision technologies, coupled with the availability of large-scale remote-sensing image datasets, have accelerated the progress of remote-sensing object detection. However, large-scale remote-sensing images typically feature extensive and complex backgrounds with small and sparsely distributed objects, which pose significant challenges to detection performance. To address this, we propose a novel framework for accurate object detection, termed transparent mask background optimization for accurate object detection (TMBO-AOD), which incorporates a clear focus module and an adaptive filtering framework. The clear focus module constructs an empirical background pool using a Gaussian distribution and introduces transparent masks to prepare for subsequent optimization stages. The adaptive filtering framework can be applied to anchor-based or anchor-free models. It dynamically adjusts the number of candidates generated based on background flags, thereby optimizing the label assignment process. This approach not only alleviates the imbalance between positive and negative samples but also enhances the efficiency of candidate generation. Furthermore, we introduce a novel separated loss function that strengthens both foreground and background consistencies. Specifically, it focuses the model’s attention on foreground objects while enabling it to learn the consistency of background features, thus improving its ability to distinguish objects from the background. We employ YOLOv8 combined with our proposed optimizations to evaluate our model in many datasets, demonstrating improvements in both accuracy and efficiency. Additionally, we validate the effectiveness of our adaptive filtering framework in both anchor-based and anchor-free methods. When implemented with YOLOv5 (anchor based), the framework reduces the candidate generation time by 48.36%, while the YOLOv8 (anchor-free) implementation achieves a 46.81% reduction, both with maintained detection accuracy. Full article

The application and promotion of grouted sleeve connectors in prefabricated structures are closely related to their high efficiency and intensive advantages. Numerous scholars have conducted experimental studies on the performance of sleeves, but there has been no systematic consolidation of these efforts. In this study, the latest developments in grouted sleeve connection technology are systematically reviewed and analysed, focusing on its applications and characteristics, performance testing, influencing factors, load-transfer mechanisms, and performance evaluation. First, the differences in sleeve code formulation across various countries are compared, the advantages and disadvantages of different sleeve types and grouting techniques are reviewed, and the application scenarios of sleeves are summarized. Second, an overview of the performance of grouted sleeves in tensile, fatigue, and seismic tests is provided, highlighting key factors affecting structural performance and experimental results. Furthermore, the effects of various factors (the anchorage length, diameter and strength of reinforcing bars; types and defects of grout materials; sleeve tube design; and temperature) on the performance of sleeves are investigated, and some beneficial conclusions are drawn. The load-transfer mechanisms of different sleeve types are subsequently compared, and the common features of the sleeves that meet the performance evaluation criteria are analysed. Finally, potential future research directions and innovations in sleeve technology are suggested to provide researchers and scholars with innovative ideas and research perspectives for developing new sleeves and advancing the application of grouted sleeve connectors. Full article

Background: Inhibition of intestinal α-glucosidase is a key strategy for controlling postprandial hyperglycemia in diabetes. Astragali Radix (AR), a traditional medicinal and dietary herb widely consumed in China, is rich in flavonoids that are believed to exhibit hypoglycemic properties. Methods: A total of 29 AR-related flavonoids, including both original constituents and metabolites, were screened for α-glucosidase inhibitory activity using in vitro enzymatic assays. Mechanistic investigations were conducted through enzyme kinetics, circular dichroism (CD) spectroscopy, surface plasmon resonance (SPR), and molecular docking. The in vivo hypoglycemic effects were assessed using a postprandial hyperglycemic mouse model. Additionally, potential mixture effects of flavonoid combinations were evaluated. Results: Of the 29 flavonoids, 16 demonstrated significant α-glucosidase inhibitory activity, with five (C3, C17, C19, C28, and C29) identified as novel inhibitors. Structure–activity relationship (SAR) analysis revealed that hydroxylation, particularly at the C-3 position, enhanced activity, while glycosylation and methoxylation reduced it. Mechanistic studies demonstrated that these compounds bind to distinct amino acid residues within the active site of α-glucosidase, inducing conformational changes and exerting different types of inhibition, leading to varying inhibitory mechanisms. Additionally, 15 compounds reduced postprandial blood glucose levels, with C3, C16, C17, C19, and C28 confirmed as novel in vivo inhibitors. Notably, two compositions of flavonoids combined at their individually ineffective concentrations exhibited significant inhibitory effects. Conclusions: This study provides a comprehensive evaluation of AR-related flavonoids as α-glucosidase inhibitors and offers valuable insights for the development of highly effective, low-toxicity, flavonoid-based, antidiabetic therapeutics and functional foods. Full article

This paper addresses the challenge of small-object detection in traffic surveillance by proposing a hybrid network architecture that combines attention mechanisms with convolutional layers. The network introduces an innovative attention mechanism into the YOLOv8 backbone, which effectively enhances the detection accuracy and robustness of small objects through fine-grained and coarse-grained attention routing on feature maps. During the feature fusion stage, we employ adaptive dilated convolution, which dynamically adjusts the dilation rate spatially based on frequency components. This adaptive convolution kernel helps preserve the details of small objects while strengthening their feature representation. It also expands the receptive field, which is beneficial for capturing contextual information and the overall features of small objects. Our method demonstrates an improvement in Average Precision (AP) by $1\%$ on the UA-DETRAC-test dataset and $3\%$ on the VisDrone-test dataset when compared to state-of-the-art methods. The experiments indicate that the new architecture achieves significant performance improvements across various evaluation metrics. To fully leverage the potential of our approach, we conducted extended research on radar–camera systems. Full article

Chronic lower limb ischemia is a debilitating condition, particularly prevalent among elderly patients and individuals ineligible for revascularization procedures. Gene therapy aimed at promoting therapeutic angiogenesis presents a promising alternative treatment strategy. Objectives: This study evaluated the preclinical safety of a gene therapy drug composed of the plasmids pBudK-coVEGF-coANG and pBudK-coGDNF in laboratory animals. Safety assessment followed a single intramuscular injection at a dose 30 times higher than the proposed therapeutic level. Methods: Acute toxicity was monitored over a 24-h period. Genotoxicity was assessed using the micronucleus test at doses of 200, 1000, and 5000 μg/kg. Bone marrow cytology was analyzed to detect hematopoietic toxicity. Delayed toxicity was evaluated over a two-week recovery period. Results: No signs of acute toxicity were observed, even at the highest dose. The micronucleus test revealed no genotoxic effects, with no significant increase in micronucleated polychromatic erythrocytes compared to control groups. Bone marrow erythroblast parameters remained within normal physiological ranges. Additionally, no delayed adverse effects were detected during the recovery period. Conclusions: The gene therapy drug demonstrated a favorable preclinical safety profile, exhibiting no evidence of toxicity or genotoxicity, even at substantially elevated doses. These findings support the continued development of this therapy as a potential treatment for chronic lower limb ischemia in patients who are not candidates for surgical intervention. Full article

: To address lower limb fatigue in workers engaged in prolonged standing, this study proposes a structural design for a medial-support passive exoskeleton seat. The design incorporates support rods positioned along the medial aspect of the user’s lower limbs and features an adaptive telescopic rod system, enhancing sitting stability and reducing collision risks in workplace environments. Human motion capture technology was used to collect kinematic data of the lower limbs, and a mathematical model of center-of-gravity variation was developed to calculate and optimize the exoskeleton’s structural parameters. Static analysis was performed using ANSYS software to evaluate the structural integrity of the design. The effectiveness of the exoskeleton seat was validated through surface electromyography (sEMG) experiments, with results showing that the exoskeleton significantly reduces lower limb muscle load by 49.2% to 72.9%. Additionally, force plate experiments demonstrated that the exoskeleton seat improves stability, with a 39.2% reduction in the average displacement of the center of pressure (CoP), confirming its superior postural alignment and balance. The design was also compared with existing exoskeleton chairs, showing comparable or better performance in terms of muscle load reduction, stability, and overall effectiveness. Full article

Climate change and extreme rainfall events pose great pressures on a city’s resilience to flooding and waterlogging. Designed as a kind of green infrastructure to manage stormwater, urban sponge parks (USPs) in China have been demonstrated to have ecological and societal benefits, while their landscape economic values lack evaluation. Taking the real-estate choices surrounding six USPs in China as an example, an evaluation framework integrating text mining with housing introduction documents and hedonic price model (HPM) regression with housing prices was constructed to combine the stated preferences and revealed preferences of citizens when purchasing properties. The main findings include the following: (1) USPs do contribute to property appreciation, especially in newer urban areas, although they are not as strong as location and property characteristic factors; (2) the extent of the influence of USPs on houses decreases as the distance increases, with a maximum radius of 3 km; (3) a USP’s effects vary according to the urban and environmental context, as HPM with GWR (R² ranges from 0.203 to 0.679) outperforms the OLS method (R² ranges from 0.149 to 0.491), which evokes the need for more affluent and detailed analyses in the future. This study demonstrates the economic benefits of USPs and provides an evaluation approach based on citizen science data, which could contribute to the policy-making of USPs in China and promote the implementation of Nature-based Solutions. Full article

Introduction: The anatomy of the distal tibiofibular joint (DTFJ) has been demonstrated to influence the radiological outcome of reduction with syndesmotic screw fixation in the course of ankle fracture treatment. The objective of this study was to describe the anatomy of the DTFJ and to analyze the effect of incisura anatomy on syndesmotic stabilization with suture button systems (SBS), also in the context of their flexible nature of fixation. Materials and Methods: Forty-four (21 females, 23 males) consecutive postoperative bilateral computed tomography scans after stabilization of the DTFJ by SBS in the course of operative treatment of unstable ankle fractures were retrospectively analyzed. The anatomy of the DTFJ was evaluated by examining the following parameters: depth of the tibial incisura (DI), rotation of the incisura (ROI), Nault talar dome angle (NTDA), Leporjärvi clear space (LCS), anterior tibiofibular distance (antTFD), and fibula engagement (FE). The side-to-side (Δ) of LCS, NTDA, and antTFD, which analyzed the reduction result, were correlated with DI, FE, ROI, and NTDA, as well as the transverse offset (TO), reflecting the flexible nature of fixation. Results: Patients with slight overtightening (ΔLCS > −1 mm) showed a fibula that protruded less into the incisura on the native side (smaller FE) compared to symmetrical reduced patients and to patients with slight diastasis (p < 0.05). There was no relationship between the parameters describing the anatomy of the incisura and parameters assessing the parameter of the “flexible nature of fixation” (rs < 0.300). Regarding the anatomical parameters, it was observed that there were inter-individual differences of more than 4 mm (p > 0.05). Conclusions: The considerable inter-individual anatomical variability of the DTFJ was confirmed. The morphological configuration of the incisura has no impact on the immediate radiological reduction result after SBS stabilization of the DTFG, as determined by CT. The extent of the flexible nature of fixation is also not affected by the morphology of the incisura. Stabilization of the DTFJ can be performed regardless of the anatomical configuration. Full article

This study investigated the effects of electron beam radiation on the room-temperature and high-temperature mechanical properties of two ethylene-vinyl acetate (EVA) copolymers, designated EVA 206 and EVA 212. These copolymers had varying vinyl acetate (VA) contents (6 wt.% and 12 wt.%), with the same melt flow index of 2.0 g/10 min. Samples were irradiated at doses ranging from 60 to 180 kGy. The impact of electron beam irradiation on the creep, frequency sweep, and stress–strain behaviors of the ethylene-vinyl acetate copolymers was evaluated using a dynamical mechanical analyzer (DMA). Crystallinity was measured using differential scanning calorimetry (DSC) and wide-angle X-ray diffraction (WAXD). Creep compliance was quantitatively analyzed using four-parameter and six-parameter models. While crosslinking had minimal influence on the room-temperature properties, it significantly affected the behavior at 150 °C. With increasing irradiation dose, creep compliance decreased, while the shear modulus, viscosity, and shear stress at a strain of 0.03 increased, indicating enhanced resistance to deformation. Crosslink density also increased with irradiation dose. EVA 212 with a higher vinyl acetate content exhibited a higher resistance to creep and better high-temperature mechanical properties across all measurements. Full article

Background/Objectives: This systematic review describes a largely descriptive synthesis of studies investigating the diagnostic performance of quantitative contrast-enhanced ultrasound (CEUS) in differentiating benign from malignant peripheral pulmonary lesions. Methods: Formal quantitative pooling of effect sizes was not feasible due to variability in outcome measurements and reporting. Results: Combining CEUS parameters with real-time on-site evaluation (ROSE) substantially improved percutaneous biopsy success rates. In one comparative study, biopsy yield reached 97.62% with CEUS, versus 84% using conventional ultrasound, while complications remained minimal. Other investigations focused on the discriminatory value of specific time-based indices (e.g., AT ≥ 10 s, lesion-lung AT difference ≥ 2.5 s) or complex multi-parameter models. A notable large study demonstrated that a six-parameter logistic regression model achieved near-excellent discrimination, with C-statistics exceeding 0.97 for both development and validation cohorts, outperforming single-threshold approaches. Nevertheless, certain findings emphasize that no single indicator—particularly arrival time alone—reliably distinguishes benign from malignant lesions, given the diverse vascular patterns and histological subtypes involved. TDOA-based analyses proved more promising, as malignant lesions generally exhibit a delayed but robust bronchial arterial supply and rapid washout. Heterogeneity in ultrasound systems, operator experience, and patient populations further underscores the need for standardized protocols. Conclusions: Overall, these data suggest that CEUS, particularly when combined with additional sonographic or cytological tools, significantly enhances diagnostic precision for peripheral pulmonary lesions. Full article

Early crop planting area estimation is crucial for achieving effective government resource allocation, optimizing resource distribution planning, and preparation related to food security. Utilizing remote sensing images during the crop growth period for crop planting area estimation has garnered increasing attention. However, area estimation from remote sensing often lags in obtaining image data. Moreover, this method is also influenced by the quality of remote sensing image data and segmentation accuracy. This paper proposes a new method for early area estimation based on multi-year land cover data using a three-dimensional convolutional end-to-end network. This method eliminates the impact of the intermediate process of image segmentation accuracy on area estimation. Additionally, multi-subimage technology is employed to solve the issue of inconsistent input sample size, and label distribution smoothing technology is used to tackle the problem of unbalanced sample distribution. The proposed method was evaluated on U.S. corn and soybean datasets. In comparison to baseline methods, the method achieved relative errors of 0.67% for corn and 3.72% for soybeans at the national level in the United States in 2021. This demonstrates the effectiveness of the proposed method and the potential for early decision-making support. This approach offers a new perspective for area estimation, significantly advancing the timing of planting area prediction and enhancing the accuracy of early area estimation, providing actionable insights for decision-making and resource management. Full article