Search Results (9,221)

As a key device for precise feeding in aquaculture, feeders directly affect feed utilization efficiency and farming profitability; however, pneumatic pond feeders commonly exhibit poor spreading uniformity and low feed utilization. In this study, a dual-sided air intake structure incorporating a triangular flow-splitter plate was added inside the feed chamber, and the spreading process was simulated using a coupled computational fluid dynamics–discrete element method approach to analyze the motion mechanisms of feed pellets within the feeding device. A rotatable orthogonal composite experimental design was employed for the multiparameter collaborative optimization of the feed chamber height ($h$), the triangular flow-splitter plate width ($d$), and its inlet angle ($\alpha$). The results demonstrated that the triangular flow-splitter plate renders the velocity field within the device chamber more uniform and reduces the coefficient of variation ($CV$) of circumferential pellet distribution to 18.27%, a 22.19% decrease relative to the unmodified design. Experimental validation using the optimal parameter combination confirmed a mean $CV$ of 17.02%, representing a 24.45% reduction compared with the original structure. This study provides a theoretical foundation and reliable technical solution for precise feeding equipment in aquaculture. Full article

Marine plastic pollution has become a critical transboundary environmental issue, particularly affecting coastal regions with insufficient waste management infrastructure. This study applies a modified Lagrangian hydrodynamic model, TrackMPD v.1, to simulate the movement and accumulation of macroplastics in the West Africa Coastal Area. The research investigates three case studies: (1) the Liberia–Gulf of Guinea region, (2) the Mauritania–Gulf of Guinea coastal stretch, (3) the Cape Verde, Mauritania, and Senegal regions. Using both forward and backward simulations, macroplastics’ trajectories were tracked to identify key sources and accumulation hotspots. The findings highlight the cross-border nature of marine litter, with plastic debris transported far from its source due to ocean currents. The Gulf of Guinea emerges as a major accumulation zone, heavily impacted by plastic pollution originating from West African rivers. Interesting connections were found between velocities and directions of the plastic debris and some of the characteristics of the West African Monson climatic system (WAM) that dominates the area. Backward modelling reveals that macroplastics beached in Cape Verde largely originate from the Arguin Basin (Mauritania), an area influenced by fishing activities and offshore oil and gas operations. Results are visualized through point tracking, density, and beaching maps, providing insights into plastic distribution and accumulation patterns. The study underscores the need for regional cooperation and integrated monitoring approaches, including remote sensing and in situ surveys, to enhance mitigation strategies. Future work will explore 3D simulations, incorporating degradation processes, biofouling, and sinking dynamics to improve the representation of plastic behaviour in marine environments. This research is conducted within the Global Development Assistance (GDA) Agile Information Development (AID) Marine Environment and Blue Economy initiative, funded by the European Space Agency (ESA) in collaboration with the Asian. Development Bank and the World Bank. The outcomes provide actionable insights for policymakers, researchers, and environmental managers aiming to combat marine plastic pollution and safeguard marine biodiversity. Full article

Computing the temporal variation in clearwater scour depth around abutments is important for bridge foundation design. To reach the equilibrium scour depth at bridge abutments takes a very long time. However, the corresponding times under prototype conditions can yield values significantly greater than the time to reach the design flood peak. Therefore, estimating the temporal variation in scour depth is necessary. This study evaluates multiple machine learning (ML) models to identify the most accurate method for predicting scour depth (Ds) over time using experimental data. The dataset of 3275 records, including flow depth (Y), abutment length (L), channel width (B), velocity (V), time (t), sediment size (d₅₀), and Ds, was used to train and test Linear Regression (LR), Random Forest Regressor (RFR), Support Vector Regression (SVR), Gradient Boosting (GBR), XGBoost, LightGBM, and KNN models. Results demonstrated the superior performance of AI-based models over conventional regression. The RFR model achieved the highest accuracy (R² = 0.9956, Accuracy = 99.73%), followed by KNN and GBR. In contrast, the conventional LR model performed poorly (R² = 0.4547, Accuracy = 57.39%). This study confirms the significant potential of ML, particularly ensemble methods, to provide highly reliable scour predictions, offering a robust tool for enhancing bridge design and safety. Full article

One of the most interesting applications of crude glycerol (CG) is its use for biogas production via the anaerobic co-digestion (AcoD) process. The main aim of the current study was to provide a comprehensive review on the performance of the AcoD of CG mixed with various substrates. For this purpose, analyses were performed for studies available in the literature wherein one-stage experiments were conducted. To the best of the authors’ knowledge, the present study is the first one which demonstrates an analysis of the main parameters of CG and substrates (e.g., animal manure, sewage sludge, cattle manure and food waste) used for AcoD. Moreover, a detailed analysis of the impact of selected parameters on AcoD performance was carried out. It is demonstrated that the values of key parameters characterizing the CG used for AcoD were within wide ranges. This can be explained by the fact that the composition of CG depends on many factors; for instance, these include the source of oil used for biodiesel production, processing technology, the ratio of reactants, the type of catalyst and the procedure applied. Moreover, performing a literature review allowed us to demonstrate that adding CG to feedstock caused the enhancement of process performance compared to results obtained for mono-digestion. Additionally, it was shown that, in general, increasing the concentration of CG in feedstock led to improvement of the biogas yield; however, a potential inhibitory effect should be considered. Analysis of data available in the literature allowed us to indicate that for most of the experiments performed, a methane (CH₄) content in biogas higher than 60% was obtained for CG content in feedstock up to 8% v/v. In addition, it is demonstrated that in order to evaluate the performance of AcoD performed under thermophilic conditions, more studies are required. Finally, it should be pointed out that the present study provides considerable insight into the management of CG. Full article

Objetives: This study aimed to (1) describe and compare the external physical requirements of international cerebral palsy (CP) football players during training sessions and official matches at the 2024 IFCPF World Cup, and (2) analyze the relationships between standardized field-based physical performance tests and the physical requirements recorded in both contexts. Methods: Twelve international outfield players from the Spanish national CP football team were monitored throughout the tournament. Physical performance was evaluated two weeks prior using 5-m and 30-m sprints, a Modified Agility Test (MAT), a dribbling test, and the 30–15 Intermittent Fitness Test (vIFT). Match and training physical requirements were assessed using inertial devices, including total and relative distances, velocity metrics, and acceleration/deceleration outputs. Results: Matches imposed significantly greater demands than training sessions in terms of peak velocity, total distance per minute, and distance at moderate (>12–18 km/h) and high (>18 km/h) intensities (t = 2.79 to 8.06; p = 0.01; ES(d) = 0.50 to 1.45). Training sessions exhibited greater variability in load while match requirements were consistent across games. Performance in the MAT and dribbling tests correlated with several physical indicators in both training and competition. In contrast, vIFT and sprint tests showed limited associations, especially with match variables. Conclusions: Match play elicits higher and more stable physical requirements than training. The MAT and dribbling tests appear to be ecologically valid tools for assessing functional readiness in CP football. These findings support the integration of specific physical tests and tailored training designs to better replicate the competitive requirements of international CP football. Full article

Porcine enteric coronaviruses (CoVs), including swine acute diarrhea syndrome coronavirus (SADS-CoV), porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), and porcine transmissible gastroenteritis virus (TGEV), are major pathogens causing porcine viral diarrhea syndrome (VDS), which brings significant economic losses to the swine industry; distinguishing between these clinically similar viruses has become a serious challenge. We developed a highly specific and interference-resistant porcine CoV multiplex digital PCR (dPCR) assay. The assay exhibited robust anti-interference capabilities, as the concentrations of the four viruses did not affect their accurate quantification. The coefficients of variation (CV%) of intra-batch and inter-batch repeatability for all target viruses were less than 11%. The limit of quantification (LoQ) of this dPCR assay reached 7.5 copies/reaction for each target, and it was one order of magnitude more sensitive than qPCR. The limits of detection (LoD) for SADS-CoV, PEDV, PDCoV, and TGEV were 2.72, 3.00, 3.56, and 3.19 copies/reaction, respectively. A total of 408 known samples were used for validation tests, and the results were highly consistent with the known conditions, showing a compliance rate of 97–100%. The diagnostic specificity (Dsp) of the method was 99–100%. In conclusion, the developed multiplex dPCR assay is highly suitable for early detection and quarantine in four porcine CoVs. The results indicate that this dPCR method is characterized by high specificity, anti-interference capabilities, repeatability, and high sensitivity. It also demonstrates a high compliance rate and diagnostic specificity in sample detection. This multiplex dPCR will contribute to the control of porcine enteric CoV-caused VDS and provide clues for subsequent research. Full article

Cancer-associated fibroblasts (CAFs) are crucial regulators of the tumor microenvironment (TME), promoting cancer progression, immune suppression, and therapy resistance. Single-cell transcriptomics has identified at least five distinct CAF subtypes: myofibroblastic (myCAFs), inflammatory (iCAFs), antigen-presenting (apCAFs), metabolic (meCAFs), and vascular/developmental (vCAFs/dCAFs), each with unique localization, signaling, and functions. While CAFs are well studied in epithelial cancers, their roles in sarcomas are less understood despite the shared mesenchymal origin of tumor and stromal cells. This overlap blurs the line between malignant and non-malignant fibroblasts, raising fundamental questions about the identity of CAFs in mesenchymal tumors. In this narrative review, we explore the heterogeneity and plasticity of CAFs across solid tumors, focusing on their role in immune evasion, epithelial-to-mesenchymal transition (EMT), and resistance to chemotherapy, targeted therapy, and immunotherapy. We highlight emerging evidence on CAF-like cells in sarcomas and their contribution to tumor invasion, immune exclusion, and metastatic niche formation. We also assess new strategies to target or reprogram CAFs and suggest that CAF profiling may serve as a potential biomarker for patient stratification. Understanding CAF biology across various tumor types, including those with dense stroma and immunologically cold sarcomas, is crucial for developing more effective, personalized cancer treatments. Full article

Pentagonal two-dimensional allotropes—penta-graphene (PG) and penta-SiC₂—are promising but experimentally elusive materials whose identification requires spectroscopic fingerprints that extend beyond ground-state descriptors. Using density functional theory within a core-hole formalism and polarisation-resolved cross sections, we compute element- and site-resolved K-edge spectra for pristine H- and OH-terminated PG, Si-substituted PG, and pristine/H-passivated penta-SiC₂. In PG, the C K-edge shows a ${\pi }^{*}$ onset at 285 eV from three-coordinated C and ${\sigma }^{*}$ bands at 293–303 eV, yielding three plateaus and a strong low-energy z-polarised response. The H/OH functionalisation suppresses the 283–288 eV plateau and weakens the polarisation anisotropy, which can be rationalised by PDOS changes at the two non-equivalent C sites. Si substitution generates a polarisation-dependent Si K-edge doublet (∼1844/1857 eV). In penta-SiC₂, the high-energy Si feature broadens (1850–1860 eV) and the C K-edge becomes strongly anisotropic; H-passivation yields a sharp, almost polarisation-independent C K-edge at 290 eV. The presence of clearly resolved, system-dependent spectral features enables unambiguous experimental discrimination between phases and terminations, facilitating spectroscopic discovery and supporting device development in 2D pentagonal materials. Full article

Excessive osteoclast activity in bone remodeling can lead to an imbalance between bone resorption and formation, a common occurrence in abnormal bone metabolic diseases. This research investigates the effect of Coptidis rhizoma water extract (CRW) on osteoclastogenesis provoked by RANKL in vitro and bone destruction mediated by ovariectomy (OVX) in vivo. CRW, prepared from dried Coptidis rhizoma (CR), was analyzed for its active compounds—coptisine and berberine—using HPLC analysis. CRW markedly decreased the size and number of TRAP-positive multinucleated cells (TRAP⁺ MNCs), suppressed F-actin ring formation, and diminished bone resorption in RANKL-treated cultures. In the early phase of differentiation, CRW suppressed the phosphorylation of MAPKs p38, JNK, and ERK, as well as NF-κB p65, Iκ-Bα, and Akt. CRW also down-regulated RANKL-mediated induction of c-Fos and NFATc1 and attenuated the activation of NFATc1- dependent genes, such as OSCAR, ATP6V0D2, ACP5 (TRAP), OC-STAMP, DC-STAMP, CTSK (cathepsin K), CALCR (calcitonin receptor), and MMP-9. In ovariectomized rats, micro-CT and histological analyses showed that CRW alleviated femoral bone destruction. These findings indicate that CRW restrains osteoclast differentiation and function and may have therapeutic potential for disorders driven by excessive osteoclast activity. Full article

This paper presents the design and implementation of a 6-bit high-precision active vector-sum phase shifter (PS) operating in the E-band, fabricated using a 40 nm CMOS process. To generate high-quality in-phase and quadrature (I/Q) signals, a folded transformer-based quadrature generator circuit (QGC) employing inductive compensation is developed. Additionally, the series peaking enhancement technique is applied to improve overall gain and effectively extend the bandwidth. Measurement results demonstrate that the phase shifter achieves a 3 dB bandwidth from 72.3 GHz to 82.3 GHz. Within this range, the measured RMS phase error is merely 1.78–2.55 degrees without calibration, and the RMS gain error is 0.6–0.75 dB. The core area of the proposed phase shifter is 940 μm × 280 μm, and it consumes 57.2 mW of power with a 1.1 V supply. Full article

Coniferous forests in Canada play a vital role in carbon sequestration, wildlife conservation, climate change mitigation, and long-term sustainability. Traditional methods for classifying and segmenting coniferous trees have primarily relied on the direct use of spectral or LiDAR-based data. In 2024, we introduced a novel data representation method, pseudo tree crown (PTC), which provides a pseudo-3D pixel-value view that enhances the informational richness of images and significantly improves classification performance. While our original implementation was successfully tested on urban and deciduous trees, this study extends the application of PTC to Canadian conifer species, including jack pine, Douglas fir, spruce, and aspen. We address key challenges such as snow-covered backgrounds and evaluate the impact of training dataset size on classification results. Classification was performed using Random Forest, PyTorch (ResNet50), and YOLO versions v10, v11, and v12. The results demonstrate that PTC can substantially improve individual tree classification accuracy by up to 13%, reaching the high 90% range. Full article

To address the challenges of short allowable motion windows and complex motion planning inherent in dual forging manipulator systems, this study proposes a coordinated motion pattern tailored to dual-manipulator operations, focusing on forging deformation behavior and press control characteristics. First, six representative long-shaft forging materials were classified based on typical industrial applications. Using DEFORM-3D (V11.0) software, the deformation process during the elongation operation was analyzed, and the velocity and displacement characteristics at both ends of the forgings were extracted to clarify the compliant motion requirements of the grippers. Next, a segmented computation method for manipulator allowable motion time was developed based on the motion–time curve of the hydraulic press, significantly improving the time utilization efficiency for coordinated control. Furthermore, experimental tests were carried out to verify the dynamic response performance and motion accuracy of the dual-manipulator system. Finally, the dual-manipulator forging cycle was systematically divided into four stages—pre-forging adjustment, inter-pass compliance, execution phase, and forging completion—resulting in a structured and implementable coordination control framework. This research provides both a theoretical foundation and practical pathway for achieving efficient and precise coordinated motion control in dual forging manipulator systems, offering strong potential for engineering application and industrial deployment. Full article

To foster the performance of wireless communication while saving energy, the integration of Intelligent Reflecting Surfaces (IRS) into autonomous vehicle (AV) communication networks is considered a powerful technique. This paper proposes a novel IRS-assisted vehicular communication model that combines Lagrange optimization and Gradient-Based Phase Optimization to determine the optimal transmission power, optimal interference transmission power, and IRS phase shifts. Additionally, the proposed model help increase the Signal-to-Interference-plus-Noise Ratio (SINR) by utilizing IRS, which leads to maximizes energy efficiency and the achievable data rate under a variety of environmental conditions, while guaranteeing that resource limits are satisfied. In order to represent dense vehicular environments, practical constraints for the system model, such as IRS reflection efficiency and interference, have been incorporated from multiple sources, namely, Device-to-Device (D2D), Vehicle-to-Vehicle (V2V), Vehicle-to-Base Station (V2B), and Cellular User Equipment (CUE). A Lagrangian optimization approach has been implemented to determine the required transmission interference power and the best IRS phase designs in order to enhance the system performance. Consequently, a one-dimensional convolutional neural network has been implemented for the optimized data provided by this framework as training input. This deep learning algorithm learns to predict the required optimal IRS settings quickly, allowing for real-time adaptation in dynamic wireless environments. The obtained results from the simulation show that the combined optimization and prediction strategy considerably enhances the system reliability and energy efficiency over baseline techniques. This study lays a solid foundation for implementing IRS-assisted AV networks in real-world settings, hence facilitating the development of next-generation vehicular communication systems that are both performance-driven and energy-efficient. Full article

Robots with parallelogram mechanisms are widely employed in industrial applications due to their mechanical rigidity and precise motion control. However, the analytical definition of feasible workspace regions free from self-collisions remains an open challenge, especially considering the nonlinear and composite nature of such regions. This work introduces a mathematical model grounded in a collision theorem that formalizes boundary functions based on joint variables and geometric constraints. These functions explicitly define the envelope of safe configurations by evaluating relative positions between critical structural components. Using the MinervaBotV3 as a case study, the symbolic joint-space boundaries and their corresponding geometric regions in both 2D and 3D are computed and visualized. The feasible region is refined through centroid-based scaling to introduce safety margins and avoid singularities. The results show that this framework enables analytically continuous workspace representations, improving trajectory planning and reliability in constrained environments. Future work will extend this method to spatial mechanisms and real-time implementations in hybrid robotic systems. Full article

This study aimed to develop synbiotic edible films based on fish gelatin containing Lacticaseibacillus rhamnosus GG, evaluating the impact of different prebiotics (inulin and fructooligosaccharides, FOSs) and structuring polysaccharides (pectin and alginate) on their physical, mechanical, thermal properties, cell viability, and in vitro gastrointestinal behavior. Seven film formulations were prepared from fish gelatin solutions (3%, w/v) containing glycerol (30%, w/w, as plasticizer), with the addition of prebiotics (inulin or FOSs, 1:1 w/w to gelatin), either alone or in combination with pectin (1%, w/v) or alginate (0.5%, w/v). Specifically, F1 contained gelatin, glycerol, and L. rhamnosus GG (control); F2 and F5 included inulin or FOSs, respectively; F3 and F6 combined inulin or FOSs with pectin; and F4 and F7 combined inulin or FOSs with alginate. After incorporation of the probiotic, the solutions were cast and dried at 37 °C for 24 h. The incorporation of prebiotics and polysaccharides significantly influenced probiotic viability after film drying (p < 0.05). The control formulation (F1) showed the highest reduction (26.10%), while F4 (inulin + alginate) and F7 (FOS + alginate) exhibited the lowest losses of 10.41% and 10.98%, respectively. These films also demonstrated better performance during simulated digestion, with F7 showing the smallest reduction after 6 h (0.5 log), maintaining 7.0 colony-forming units per gram (CFU g⁻¹), which is considered adequate for functional effects. Physically, the films varied in solubility (27.50% to 41.37%), thickness (0.085 to 0.095 mm), water vapor permeability (WVP) (8.17 to 11.75 g·mm/m²·d·kPa), and moisture content (13.47% to 17.50%). Mechanically, F4 showed the highest tensile strength (24.5 MPa), while F1 had the highest elongation at break (62%). During storage, F7 and F4 showed the lowest viability losses (29.8% and 29.4%, respectively) under refrigeration. Overall, the results indicate that the association of prebiotics with structuring polysaccharides improves stability, cellular protection, and functional performance of the films. Full article