Search Results (5,491)

Cocoa represents a crucial source of income in coastal regions of Ecuador, where the product is exported for the production of high-value chocolates. However, elevated levels of cadmium (Cd) in cocoa beans, attributable to volcanic soils, have the potential to impede international trade, particularly in accordance with European Union regulations. The main objective of this study was to reduce Cd concentrations in cocoa beans of two genotypes, Nacional and CCN-51, by applying different doses of pectin trans-eliminase (PTE) enzyme during the fermentation process in conjunction with mucilage washing techniques, pre-drying resting periods, and various drying methods. To this end, a Taguchi orthogonal design (L9) was employed to evaluate nine treatments per genotype, complemented with two controls. The most efficacious treatment for Nacional was identified as T7, involving a 0.30 mL·kg⁻¹ PTE dose, the absence of mucilage washing, a 48 h resting period, and drying in a marquee. This treatment resulted in a 68.6% reduction in Cd concentration (from 0.28 to 0.09 mg·kg⁻¹). For CCN-51, T3 (0.10 mL·kg⁻¹ PTE, complete washing, 48 h resting, and splint drying) yielded a 26.4% reduction in Cd (from 0.42 to 0.31 mg·kg⁻¹). It is noteworthy that none of the treatments exceeded the EU regulatory threshold of 0.8 mg·kg⁻¹. A physico-chemical analysis was conducted, which revealed significant treatment effects on pH (ranging from 5.63 to 6.85) and acidity (0.02% to 0.03%). Sensory evaluation indicated enhancements in cocoa and nutty flavors, along with a reduction in undesirable astringency and bitterness, particularly in Nacional samples. The findings of this study demonstrate that the combination of enzyme-assisted fermentation and optimized postharvest techniques represents a pragmatic approach to the mitigation of cadmium in cocoa, while simultaneously preserving or enhancing product quality. Full article

Driven by the increasing global population and rapid urbanization, aircraft noise pollution has emerged as a significant environmental challenge, impeding the sustainable development of the aviation industry. Traditional noise prediction methods are limited by incomplete datasets, insufficient spatiotemporal consistency, and poor adaptability to complex meteorological conditions, making it difficult to achieve precise noise management. To address these limitations, this study proposes a novel noise prediction framework based on a hybrid Convolutional Neural Network–Bidirectional Long Short-Term Memory–Attention (CNN–BiLSTM–Attention) model. By integrating multi-source data, including meteorological parameters (e.g., temperature, humidity, wind speed) and aircraft trajectory data (e.g., altitude, longitude, latitude), the framework achieves high-precision prediction of aircraft noise. The Haversine formula and inverse distance weighting (IDW) interpolation are employed to effectively supplement missing data, while spatiotemporal alignment techniques ensure data consistency. The CNN–BiLSTM–Attention model leverages the spatial feature extraction capabilities of CNNs, the bidirectional temporal sequence processing capabilities of BiLSTMs, and the context-enhancing properties of the attention mechanism to capture the spatiotemporal characteristics of noise. The experimental results indicate that the model’s predicted mean value of 68.66 closely approximates the actual value of 68.16, with a minimal difference of 0.5 and a mean absolute error of 0.89%. Notably, the error remained below 2% in 91.4% of the prediction rounds. Furthermore, ablation studies revealed that the complete CNN–BiLSTM–AM model significantly outperformed single-structure models. The incorporation of the attention mechanism was found to markedly enhance both the accuracy and generalization capability of the model. These findings highlight the model’s robust performance and reliability in predicting aviation noise. This study provides a scientific basis for effective aviation noise management and offers an innovative solution for addressing noise prediction problems under data-scarce conditions. Full article

The thermo-hydrological (TH) coupling model constitutes the foundational framework for investigating the temperature distribution of surrounding rock in cold region tunnels. In this study, a fully coupled TH model is proposed that takes into account multiple physical phenomena during the freezing process of surrounding rock. Firstly, the model was established based on thermodynamics, seepage theory, and ice–water phase change theory, which accounted for unfrozen water, latent heat of phase change, ice impedance, and convective heat transfer. The model was successfully verified by comparing its results to field data. Next, the sensitivity of surrounding rock temperature to environmental, thermodynamic, seepage, and coupling parameters in the fully coupled TH model was systematically studied using a numerical analysis method. The results show that the annual temperature amplitude and thermal conductivity represent the main factors affecting the surrounding rock temperature at a radial depth of 0 m, while the initial temperature and porosity are the key factors at a radial depth of 5 m. Permeability has the least influence on the surrounding rock temperature, but the temperature field will experience sudden changes if its value exceeds its value exceeds 1 × 10⁻¹² m². Finally, using the proposed numerical model, the thickness of insulation layer was simulated, and the degree of influence of the parameters on the thickness of insulation layer was analyzed. This study reveals that the annual temperature amplitude has the greatest influence on the calculation of insulation layer thickness, with its normalized sensitivity factor being approximately 50%. These findings not only expand the methodology for exploring the laws of TH coupling but also provide a theoretical foundation for improving the parameter calibration efficiency and calculation accuracy of the fully coupled TH model, and they have significant reference value. Full article

This paper proposes a harmonic source localization method for power systems, combining voltage difference features with a random forest classifier. The method captures harmonic propagation patterns and optimizes network topology handling to ensure accurate and efficient identification across various configurations. Validated on IEEE standard transmission networks, it achieves high accuracy and scalability. While effective in transmission systems, distribution networks pose challenges due to complex topologies and high impedance. Future enhancements will focus on advanced feature engineering, data augmentation, and real-time processing to improve adaptability in diverse power system environments. Full article

Conductive composites are a flexible class of engineered materials that combine conductive fillers with an insulating matrix—usually made of ceramic, polymeric, or a hybrid material—to customize a system’s electrical performance. By providing tunable electrical properties in addition to benefits like low density, mechanical flexibility, and processability, these materials are intended to fill the gap between conventional insulators and conductors. The increasing need for advanced technologies, such as energy storage devices, sensors, flexible electronics, and biomedical interfaces, has significantly accelerated their development. The electrical characteristics of composite materials, including metallic, ceramic, polymeric, and nanostructured systems, are thoroughly examined in this review. The impact of various reinforcement phases—such as ceramic fillers, carbon-based nanomaterials, and metallic nanoparticles—on the electrical conductivity and dielectric behavior of composites is highlighted. In addition to conduction models like correlated barrier hopping and Debye relaxation, the study investigates mechanisms like percolation thresholds, interfacial polarization, and electron/hole mobility. Because of the creation of conductive pathways and improved charge transport, developments in nanocomposite engineering, especially with regard to graphene derivatives and silver nanoparticles, have shown notable improvements in electrical performance. This work covers the theoretical underpinnings and physical principles of conductivity and permittivity in composites, as well as experimental approaches, characterization methods (such as SEM, AFM, and impedance spectroscopy), and real-world applications in fields like biomedical devices, sensors, energy storage, and electronics. This review provides important insights for researchers who want to create and modify multifunctional composite materials with improved electrical properties by bridging basic theory with technological applications. Full article

This paper proposes a method for designing a dual-band low-noise amplifier (DB-LNA) using a new improved complex impedance dual-band transformer (IDBT). This complex IDBT is composed of parallel-coupled lines and two sections of series microstrip lines. The parallel-coupled lines are used to complete the transformation from complex impedances at two different frequencies to a pair of conjugate complex impedances, meanwhile eliminating the need for DC blocking capacitors. The transformation to real impedances is achieved by series microstrip lines at dual frequency points. A single-stage DB-LNA was designed using the BFP840ESD transistor in combination with the proposed IDBT. The fabrication and testing of the Printed Circuit Board (PCB) were then completed. The measured results of the proposed 2.4/5.5 GHz DB-LNA show an S21 parameter of 20.3/14.7 dB, an S11 of −29.8/−20.3 dB, an S22 of −15.2/−16.4 dB, and a noise figure (NF) of 1.6/1.6 dB. The whole DB-LNA has a simple structure, low cost, and excellent performance and is easy to tune. Full article

Background: Obesity is a well-documented risk factor for cardiometabolic diseases associated with insulin resistance. However, research on its relationship with alcohol intake and stress markers, such as cortisol and α-amylase, remains limited, particularly among young adults in the general population. Objective: This study investigated the relationship between adiposity measures, alcohol intake, and biological stress biomarkers among college students. Methods: Participants (n = 189) completed the NIH Diet History Questionnaire II. Body composition was measured via bioelectrical impedance analysis. Salivary α-amylase (sAA) activity and cortisol (sCort) were assessed using the Salimetrics α-amylase kinetic enzyme assay and enzyme immunoassay kits, respectively. Multivariable linear regression models were used to determine the association between alcohol consumption and adiposity on biological stress biomarkers. Results: Among students who were overweight and obese, higher alcohol consumption increased sAA activity (β = 1.52, p = 0.030), with a greater effect in females (β = 2.24, p = 0.012). Body fat percentage showed similar patterns with sAA activity (β = 2.20, p = 0.015), with no significant effect in males. There was no significant interaction between BMI or body fat and alcohol consumption on sCort levels. However, significant main effects were observed for African Americans (β = 0.22, p = 0.020) and overweight and obese status (β = −0.19, p = 0.025) on male students’ sCort levels. African Americans (β = 0.21, p = 0.026) and young male adults within the underfat category (β = 0.35, p = 0.022) also exhibited increased sCort levels. Conclusion: Sex-specific patterns in physiological responses between males and females revealed stronger associations in females for sAA activity and distinct patterns in sCort levels among African American males. Full article

Background/Objectives: The middle-income countries (MICs) in the Middle East and North Africa (MENA) region face multifaceted challenges—including fiscal constraints, conflict, and vaccine hesitancy—that impede the timely introduction of critical vaccines. This study examines the status, barriers, and facilitators to introducing three critical vaccines—human papillomavirus vaccine (HPV), pneumococcal conjugate vaccine (PCV), and rotavirus vaccine (RV)—across seven MENA MICs, to identify actionable solutions to enhance vaccine uptake and immunisation coverage. Methods: Using the READ methodology (ready materials, extract, analyse, and distil data), this review systematically analysed policy documents, reports, and the literature on the introduction of HPV, PCV, and RV vaccines in seven MENA MICs. A data extraction framework was designed to capture the status of vaccine introduction and barriers and facilitators to introduction. Findings and data gaps were validated with stakeholder consultations. Results: Of the seven study countries, progress in introducing PCV and RV has been uneven across the region (five countries have introduced PCV, four have introduced RV, and only a single country has introduced HPV at time of writing), hindered by vaccine hesitancy, fiscal challenges, and insufficient epidemiological data. Morocco is the only country to introduce all three vaccines, while Egypt has yet to introduce any. Other common barriers include the impact of conflict and displacement on healthcare infrastructure, delayed introduction due to the 2020 COVID-19 pandemic, and limited local production facilities and regional cooperation. In addition, not all countries eligible for Gavi MICs support have applied. These findings provide a roadmap for policymakers to accelerate equitable vaccine introduction in the MENA region. Conclusions: Targeted efforts, such as addressing fiscal constraints, improving local manufacturing, tackling gender barriers, and fostering public trust, paired with regional collaboration, can help bridge gaps and ensure no community is left behind in preventing vaccine-preventable diseases. Full article

Background: Multifrequency bioelectrical impedance devices such as the InBody 770 (IB770) offer faster measurements and lower costs compared with other body composition assessments. This study validated measures from IB770 against the deuterium oxide dilution technique (D2O) and DXA and compared a four-compartment (4C) model using total body water (TBW) derived from IB770 compared with D2O. Methods: A total of 55 adult females (mean ± SD, age: 21.1 ± 2.6 years) completed IB770 and DXA scans and the D2O protocol. Lin’s concordance correlation coefficients (CCCs), Bland–Altman analyses, and other equivalence tests evaluated agreement between IB770 and the criterion for measures of fat mass (FM), fat-free mass (FFM), and TBW individually and as part of 4C models. Results: There was substantial agreement between IB770 and D2O for TBW (MD = Mean Difference) (MD = 0.34 L, CCC = 0.98) and between the IB770 and DXA for FM (MD = −0.22 kg, CCC = 0.99). IB770 overestimated FFM compared with DXA (MD = 3.15 kg, CCC = 0.91). Both 4C models had almost perfect agreement for FM (CCC = 0.99), FFM (CCC = 0.99), and body fat percentage (CCC = 0.99). Conclusions: IB770 is valid for assessing TBW and can be used within the context of a 4C model in females. Full article

The voltage source converters convert the DC to AC in order to interface distributed generation units with the utility grid, typically using an LCL filter to smooth the modulated wave. However, the LCL filter can introduce resonance, potentially cause instability, and necessitate the use of damping techniques, such as active damping, which utilizes feedback from the current control loop to suppress resonance. This paper presents a comprehensive performance assessment of four current-feedback-based active damping (AD) techniques—converter current feedback (CCF), CCF with capacitor current feedback (CCFAD), grid current feedback (GCF), and GCF with capacitor current feedback (GCFAD)—under a broad range of realistic grid disturbances and low switching frequency conditions. Unlike prior works that often analyze individual feedback strategies in isolation, this study highlights and compares their dynamic behavior, robustness, and total harmonic distortion (THD) in eight operational scenarios. The results reveal the severe instability of GCF in the absence of damping and the superior inherent damping property of CCF while demonstrating the comparable effectiveness of GCFAD. Moreover, a simplified yet robust design methodology for the LCL filter is proposed, enabling the filter to maintain stability and performance even under significant variations in grid impedance. Additionally, a sensitivity analysis of switching frequency variation is included. The findings offer valuable insights into selecting and implementing robust active damping methods for grid-connected converters operating at constrained switching frequencies. The effectiveness of the proposed methods has been validated through both MATLAB/Simulink simulations and hardware-in-the-loop (HIL) testing. Full article

Background: This study aimed to optimize low-intensity extracorporeal shockwave therapy (Li-ESWT) for the treatment of penile indications through the addition of a secondary reflector. The therapeutic potential of Li-ESWT is well-established, but its efficiency is limited by uncontrolled wave propagation and reflection resulting in regions of increased tensile pressures. The objective is to manage and reduce high tensile pressure and enhance treatment efficacy by reflecting applied shockwaves back into the treatment zone using a novel reflector design. Methods: A comprehensive investigation, including numerical modeling and phantom measurements, exploring a range of improvements to traditional shockwave application by reflecting applied therapeutic shockwaves back into the treatment zone. Computational optimization was employed to identify the most suitable secondary reflector shape for potential future clinical use. Subsequent hydrophone phantom reference measurements were extended to volumetric fields using 3D simulations. Results: Traditional treatment resulted in high tensile pressures in the treatment zone, which was mitigated by introducing an impedance-matched layer (IML) while preserving the initial shockwave’s therapeutic function. The addition of the secondary reflector enabled controlled refocusing of the therapeutic shockwave back into the initial focal zone, thus either increasing the treatment volume or achieving a rapid secondary application. Choice of the reflector’s impedance allowed for the secondary refocusing of either a tensile or positive pressure wave. Conclusions: The combined modifications of employing an IML and secondary reflector eliminate uncontrolled tensile waves and reflections, provide better control over consecutive reflections, and enable repeated shockwave signals with a single applicator shot, potentially reducing the number of required shots per session. Full article

To improve the vibration performance of the giant magnetostrictive transducer, the electromechanical equivalent circuit of the transducer is derived. The finite element method is used to conduct dynamic simulation research on transducers with magnetic blocks of different sizes, and the impedance and output amplitude of the transducers are experimentally tested. The results show that the larger the diameter of the large end of the conical magnetic block, the higher the resonant frequency and output amplitude of the transducer, and the smaller the peak stress and tangential stress of the Terfenol-D rod; the peak stress of the rod is small at both ends and large in the middle, while the tangential stress is large at both ends and small in the middle. The resonant frequency, output amplitude, stress, and mechanical quality factor of the transducer with a conical magnetic block are greater than those of the transducer with a cylindrical magnetic block. The experimental test values of the resonant frequency, output amplitude, and mechanical quality factor of the two transducers are consistent with the calculation values. Full article

The FOT is a non-invasive method for assessing respiratory mechanics. It enables the measurement of respiratory system impedance by applying pressure oscillations through a loudspeaker at the subject mouth and then studying its deformation, which is commensurate to the resistance opposed by the respiratory system. The main parameters which can be determined with the FOT are the impedance (Z) and the components of respiratory resistance (Rrs) and reactance (Xrs). The FOT has been predominantly applied to the study of respiratory mechanics for research purposes; however, preclinical experiments and subsequently observational clinical studies have demonstrated that FOT can effectively assess airway obstruction, bronchodilator response, bronchial hyperresponsiveness, and the presence of small airways disease. More recently, studies on the FOT in restrictive lung diseases have also been reported. Nonetheless, international guidelines on the precise applications of the FOT in lung diseases are still lacking. The aim of the review was to describe the technical aspects related to the FOT methodology in clinical practice and to provide a concise state of the art on the applications of the FOT in obstructive and restrictive lung diseases. Full article

As face forgery techniques, particularly the DeepFake method, progress, the imperative for effective detection of manipulations that enable hyper-realistic facial representations to mitigate security threats is emphasized. Current spatial domain approaches commonly encounter difficulties in generalizing across various forgery methods and compression artifacts, whereas frequency-based analyses exhibit promise in identifying nuanced local cues; however, the absence of global contexts impedes the capacity of detection methods to improve generalization. This study introduces a hybrid architecture that integrates Efficient-ViT and multi-level wavelet transform to dynamically merge spatial and frequency features through a dynamic adaptive multi-branch attention (DAMA) mechanism, thereby improving the deep interaction between the two modalities. We innovatively devise a joint loss function and a training strategy to address the imbalanced data issue and improve the training process. Experimental results on the FaceForensics++ and Celeb-DF (V2) have validated the effectiveness of our approach, attaining 97.07% accuracy in intra-dataset evaluations and a 74.7% AUC score in cross-dataset assessments, surpassing our baseline Efficient-ViT by 14.1% and 7.7%, respectively. The findings indicate that our approach excels in generalization across various datasets and methodologies, while also effectively minimizing feature redundancy through an innovative orthogonal loss that regularizes the feature space, as evidenced by the ablation study and parameter analysis. Full article

Background: Taekwondo (TKD) athletes’ nutritional and health statuses and body composition are critical to their physical performance and overall fitness. In Lebanon, TKD is widely practiced; however, there is a significant gap in the literature regarding the nutritional and health profiles of its athletes. This study aimed to assess the nutritional status, anemia prevalence, body composition, and other health-related characteristics, among Lebanese TKD athletes. Additionally, it explored the determinants of normal hemoglobin (Hb) levels, blood pressure, normal muscle mass, and normal fat mass. Methods: A cross-sectional study was conducted between January and July 2023, involving 110 TKD athletes. Hemoglobin and hematocrit levels were measured to assess anemia, while body composition was evaluated using a bioelectrical impedance analyzer. Blood pressure was also recorded. Household dietary diversity was assessed using the Food Consumption Score, and additional data on sociodemographic factors, training frequency, and supplement or medication use were gathered through a structured questionnaire. Logistic regression models were applied to identify predictors of normal Hb levels, hypertension, and optimal muscle and fat mass. Results: Results showed that male athletes had significantly higher rates of normal Hb (p-value = 0.013) and muscle mass percentages (p-value < 0.001), while females had higher rates of normal blood pressure (p-value = 0.002) and were more likely to use iron supplements (p-value = 0.002) and painkillers (p-value = 0.041). Normal fat mass was positively associated with normal Hb levels (aOR: 11.98, p-value = 0.033). Female gender was linked to a lower likelihood of normal muscle mass (aOR: 0.13, p-value < 0.001) and hypertension (aOR: 0.19, p-value = 0.009). Higher training duration (10 h or more per week) (aOR: 3.46, p-value = 0.04) and normal BMI (aOR: 4.93, p-value = 0.003) were positively associated with normal muscle mass. Normal BMI (aOR: 14.68, p-value < 0.001) was positively associated with normal fat mass. Conclusion: These findings underscore the importance of individualized dietary interventions to enhance athletes’ overall health and performance, through the optimization of athletes’ body composition, and the prevention of deficiencies, especially iron deficiency. Full article