Search Results (27)

Food-grade titanium dioxide (E171) is widely used in food, feed, and pharmaceuticals for its opacifying and coloring properties. This study investigates the formation of reactive oxygen species (ROS) and the aggregation behavior of E171 using the TNO Gastrointestinal (GI) model, which simulates the stomach and small intestine. E171 was characterized using multiple techniques, including electron spin resonance spectroscopy, single-particle inductively coupled plasma–mass spectrometry, transmission electron microscopy, and dynamic light scattering. In an aqueous dispersion (E171-aq), E171 displayed a median particle size of 79 nm, with 73–75% of particles in the nano-size range (<100 nm), and significantly increased ROS production at concentrations of 0.22 and 20 mg/mL. In contrast, when E171 was mixed with yogurt (E171-yog), the particle size increased to 330 nm, with only 20% of nanoparticles, and ROS production was inhibited entirely. After GI digestion, the size of dE171-aq increased to 330 nm, while dE171-yog decreased to 290 nm, with both conditions showing a strongly reduced nanoparticle fraction. ROS formation was inhibited post-digestion in this cell-free environment, likely due to increased particle aggregation and protein corona formation. These findings highlight the innate potential of E171 to induce ROS and the need to consider GI digestion and food matrices in the hazard identification/characterization and risk assessment of E171. Full article

Integrating infrared and visible-light images facilitates a more comprehensive understanding of scenes by amalgamating dual-sensor data derived from identical environments. Traditional CNN-based fusion techniques are predominantly confined to local feature emphasis due to their inherently limited receptive fields. Conversely, Transformer-based models tend to prioritize global information, which can lead to a deficiency in feature diversity and detail retention. Furthermore, methods reliant on single-scale feature extraction are inadequate for capturing extensive scene information. To address these limitations, this study presents GLMAFuse, an innovative dual-stream encoder–decoder network, which utilizes a multi-scale attention mechanism to harmoniously integrate global and local features. This framework is designed to maximize the extraction of multi-scale features from source images while effectively synthesizing local and global information across all layers. We introduce the global-aware and local embedding (GALE) module to adeptly capture and merge global structural attributes and localized details from infrared and visible imagery via a parallel dual-branch architecture. Additionally, the multi-scale attention fusion (MSAF) module is engineered to optimize attention weights at the channel level, facilitating an enhanced synergy between high-frequency edge details and global backgrounds. This promotes effective interaction and fusion of dual-modal features. Extensive evaluations using standard datasets demonstrate that GLMAFuse surpasses the existing leading methods in both qualitative and quantitative assessments, highlighting its superior capability in infrared and visible image fusion. On the TNO and MSRS datasets, our method achieves outstanding performance across multiple metrics, including EN (7.15, 6.75), SD (46.72, 47.55), SF (12.79, 12.56), MI (2.21, 3.22), SCD (1.75, 1.80), VIF (0.79, 1.08), Qbaf (0.58, 0.71), and SSIM (0.99, 1.00). These results underscore its exceptional proficiency in infrared and visible image fusion. Full article

Accidental leakage from oil–gas storage tanks can lead to the formation of liquid pools. These pools can result in vapor cloud explosions (VCEs) if combustible vapors encounter ignition energy. Conducting accurate and comprehensive consequence analyses of such explosions is crucial for quantitative risk assessments (QRAs) in industrial safety. In this study, a methodology based on the SLAB-TNO model to calculate the overpressure resulting from a VCE is presented. Based on this method, the consequences of the VCE accident considering the gas cloud concentration diffusion are studied. The probit model is employed to evaluate casualty probabilities under varying environmental and operational conditions. The effects of key parameters, including gas diffusion time, wind speed, lower flammability limit (LFL), and environment temperature, on casualty diffusion are systematically investigated. The results indicate that when the diffusion time is less than 100 s, the VCE consequences are significantly more severe due to the rapid spread of the gas cloud. Furthermore, increasing wind speed accelerates gas dispersion, reducing the spatial extent of casualty isopleths. The LFL is shown to have a direct impact on both the mass and diffusion of the flammable gas cloud, with higher LFL values shifting the explosion’s epicenter upward. The environmental temperature promotes gas diffusion in the core area and increases the mass of the combustible gas cloud. These findings provide critical insights for improving the safety protocols in oil and gas storage facilities and can serve as a valuable reference for consequence assessment and emergency response planning in similar industrial scenarios. Full article

Physical properties of the Sun (orientation of rotation axis, oblateness coefficient $J_{2\odot }$, and change rate of the gravitational parameter ${\dot{\mu }}_{\odot }$) are determined using a dynamical model describing the motion of the Sun, planets, the Moon, asteroids, and Trans-Neptunian objects (TNOs). Among the many kinds of observations used to determine the orbits and physical properties of the bodies, the most important for our study are precise interplanetary ranging data: Earth–Mercury ranges from MESSENGER spacecraft and Earth–Mars ranges from Odyssey and MRO. The findings allow us to improve the model of the Sun in modern planetary ephemerides. First, the dynamically determined direction of the Sun’s pole is ≈2° off the visible axis of rotation of the Sun’s surface, which is corroborated by present knowledge of the Sun’s interior. Second, the change rate of the Sun’s gravitational parameter is found to be smaller (in absolute value) than the nominal value derived from the estimate of mass loss through radiation and solar wind. Possible interpretations are discussed. Full article

In order to solve the problem that existing visible and infrared image fusion methods rely only on the original local or global information representation, which has the problem of edge blurring and non-protrusion of salient targets, this paper proposes a layered fusion method based on channel attention mechanism and improved Generative Adversarial Network (HFCA_GAN). Firstly, the infrared image and visible image are decomposed into a base layer and fine layer, respectively, by a guiding filter. Secondly, the visible light base layer is fused with the infrared image base layer by histogram mapping enhancement to improve the contour effect. Thirdly, the improved GAN algorithm is used to fuse the infrared and visible image refinement layer, and the depth transferable module and guided fusion network are added to enrich the detailed information of the fused image. Finally, the multilayer convolutional fusion network with channel attention mechanism is used to correlate the local information of the layered fusion image, and the final fusion image containing contour gradient information and useful details is obtained. TNO and RoadSence datasets are selected for training and testing. The results show that the proposed algorithm retains the global structure features of multilayer images and has obvious advantages in fusion performance, model generalization and computational efficiency. Full article

Sand events continue to occur frequently and affect the North China region. Under unfavorable meteorological conditions, they can easily combine with haze pollution, forming sandy haze events that have a significant impact on human health. Aerosol water content (AWC) is known to have a significant impact on PM_2.5, but its effect is still unclear in sandy haze. In this work, sandy haze and haze periods were observed in Zhengzhou using a series of high-time-resolution instruments. The AWC calculated by the ISORROPIA-II model reached 11 ± 5 μg m⁻³, accounting for 10% of the PM_2.5, in the sandy haze period. Sensitivity tests show that AWC was mainly relative humidity (RH)-dependent. Additionally, elevated SO₄²⁻, TNO_3, and TNH₄ were crucial in the increase in AWC. The increase in Ca²⁺ ions in the sandy haze led to lower AWC than that in the haze periods. Specifically, (NH₄)₂SO₄ was the major contributor to the AWC when the RH was between 30 and 46% in the sandy haze period, and NH₄NO₃ gradually became the main contributor with the increase in RH. In turn, AWC could enhance the formation of sulfate and nitrate, even during the sandy haze period. Therefore, the emergency control of gaseous precursors should also be implemented before the sand events. Full article

The global protein demand is constantly on the increase, requiring sustainable and healthier protein alternatives for animal and human nutrition. Yeast-based proteins (YBPs) represent a non-negligible environmentally friendly fermentation-based solution with high nutritional quality and bioavailability. Although in vitro studies cannot reflect the full complexity of in vivo digestion, they are considered a useful alternative to animal models in assessing protein digestibility. Herein, TIM-1 (TNO gastro-intestinal model) was used to assess the digestibility profile of a proprietary edible YBP according to INFOGEST guidelines. We characterized the YBP’s digestibility and amino acid bio-accessibility and compared the YBP with milk-based references (casein and whey proteins). Each treatment was evaluated in triplicate during 5 h of digestion with hourly collection from jejunum and ileum compartments and final residual stomachal samples. Total nitrogen and free amino acid (FAA) were quantified. Size-exclusion chromatography and SDS-PAGE were also applied to assess the fate of protein hydrolysis over time. This study showed that all proteins were fully hydrolyzed upon one hour of digestion. YBPs were as good as milk-based references in terms of digestibility and small intestine absorption, reaching up to 60% of total bio-accessible protein after 5 h. Noteworthy, total YBP absorption followed a kinetics closer to that of whey protein in jejunum and ileum compartments. Our results are in line with a previous in vivo evaluation of YBPs where fecal N digestibility, PDCAAS, and DIAAS were evaluated. Altogether, our results suggest that YBPs could be a nutritionally relevant animal protein alternative. Full article

This study presents an approach using multiple linear regression to quantify the impact of meteorological parameters and chemical species on aerosol pH variance in an urban setting in the Pearl River Delta, China. Additionally, it assesses the contributions of interactions among these factors to the variance in pH. The analysis successfully explains over 96% of the pH variance, attributing 85.8% to the original variables and 6.7% to bivariate interactions, with further contributions of 2.3% and 1.0% from trivariate and quadrivariate interactions, respectively. Our results highlight that meteorological factors, particularly temperature and humidity, are more influential than chemical components in affecting aerosol pH variance. Temperature alone accounts for 37.3% of the variance, while humidity contributes approximately 20%. On the chemical front, sulfate and ammonium are the most significant contributors, adding 14.3% and 9.1% to the pH variance, respectively. In the realm of bivariate interactions, the interplay between meteorological parameters and chemical components, especially the ${\mathrm{TNO}}_3–\mathrm{RH}$ pair, is exceptionally impactful, constituting 58.1% of the total contribution from interactions. In summary, this study illuminates the factors affecting aerosol pH variance and their interplay, suggesting the integration of statistical methods with thermodynamic models for enhanced understanding of aerosol acidity dynamics in the future. Full article

Whiplash injuries, mainly located in the neck, are one of the most common injuries resulting from road collisions. These injuries can be particularly challenging to detect, compromising the ability to monitor patients adequately. This work presents the development and validation of a computationally efficient model, called Efficient Neck Model—2D (ENM-2D), capable of simulating the whiplash injury mechanism. ENM-2D is a planar multibody model consisting of several bodies that model the head and neck with the same mass and inertia properties of a male occupant model in the 50th percentile. The damping and non-linear spring parameters of the kinematic joints were identified through a multiobjective optimization process, solved sequentially. The TNO-Human Body Model (TNO-HBM), a validated occupant model for rear impact, was simulated, and its responses were used as a reference for validation purposes. The root mean square (RMS) of the deviations of angular positions of the bodies were used as objective functions, starting from the bottom vertebra to the top, and ending in the head. The sequence was repeated until it converged, ending the optimization process. The identified ENM-2D model could simulate the whiplash injury mechanism kinematics and accurately determine the injury criteria associated with head and neck injuries. It had a relative deviation of 8.3% for the head injury criteria and was 12.5 times faster than the reference model. Full article

Guar (Cyamopsis tetragonoloba) is an annual legume tolerant to drought. Guar meal (GM) is a protein- and carbohydrate-rich co-product generated after the mechanical separation of the endosperm from the germ and hull of guar seed. GM has received considerable interest in animal feed as an alternative to soybean meal (SM). In this study, we aimed to assess the nitrogen (N) balance indicators, performance, carcass traits, and main greenhouse gas (GHG) emissions resulting from enteric fermentation (E-CH₄) and manure (M-CH₄ and N₂O). Two tests were performed: (i) a biological trial on 45 pigs (15 animals/group) and (ii) a digestibility test in metabolism cages (N = 15, 5 replicates/group). Three different diets were given to the pigs: one diet was based on 0% GM (SM diet); in the second, GM-50%, GM replaced 50% of the SM; and the third was GM-100%, in which GM fully replaced the SM. The GM and SM diets were analyzed for their proximate composition. A model based on prediction equations was used to estimate the GHGs. GM up to 10% in the diets of finishing pigs did not significantly impact growth performance or carcass traits, although a slight increase in neutral detergent fiber (NDF) was observed. GM up to 10% improved N digestibility (p < 0.0001), net protein utilization (p < 0.0001), the biological value of protein, coefficients of metabolizability, and the coefficient of the total tract’s apparent digestibility. Irrespective of its dietary proportion, GM decreased total nitrogen output (TNO, p = 0.11). A highly significant impact was noted for N₂O and E-CH₄ (for DM, p < 0.0001), as well as a significant impact for E-CH₄, expressed as g CO₂ Eq (p = 0.007), and g CO₂ Eq. LU (livestock unit, p = 0.005), also reported as ADG (p = 0.024). Manure, M-CH₄, was not significantly influenced. In conclusion, GM can replace up to 100% SM and is thus a valuable byproduct that does not alter animal performance and can positively impact N₂O and E-CH₄. Full article

Due to the characteristics of multibody (MB) and finite element (FE) digital human body models (HBMs), the reconstruction of running pedestrians (RPs) remains a major challenge in traffic accidents (TAs) and new innovative methods are needed. This study presents a novel approach for reconstructing moving pedestrian TAs based on a humanoid robot method to improve the accuracy of analyzing dynamic vehicle–pedestrian collision accidents. Firstly, we applied the theory of humanoid robots to the corresponding joints and centroids of the TNO HBM and implemented the pedestrian running process. Secondly, we used rigid–flexible coupling HBMs to build pedestrians, which can not only simulate running but also analyze human injuries. Then, we validated the feasibility of the RP reconstruction method by comparing the simulated dynamics with the pedestrian in the accident. Next, we extracted the velocity and posture of the pedestrian at the moment of collision and further validated the modeling method through a comparison of human injuries and forensic autopsy results. Finally, by comparing two other cases, we can conclude that there are relative errors in both the pedestrian injury results and the rest position. This comparative analysis is helpful for understanding the differences in injury characteristics between the running pedestrian and the other two cases in TAs. Full article

Infrared and visible images of the same scene are fused to produce a fused image with richer information. However, most current image-fusion algorithms suffer from insufficient edge information retention, weak feature representation, and poor contrast, halos, and artifacts, and can only be applied to a single scene. To address these issues, we propose a novel infrared and visual image fusion algorithm based on a bilateral–least-squares hybrid filter (DBLSF) with the least-squares and bilateral filter hybrid model (BLF-LS). The proposed algorithm utilizes the residual network ResNet50 and the adaptive fusion strategy of the structure tensor to fuse the base and detail layers of the filter decomposition, respectively. Experiments on 32 sets of images from the TNO image-fusion dataset show that, although our fusion algorithm sacrifices overall time efficiency, the Combination 1 approach can better preserve image edge information and image integrity; reduce the loss of source image features; suppress artifacts and halos; and compare favorably with other algorithms in terms of structural similarity, feature similarity, multiscale structural similarity, root mean square error, peak signal-to-noise ratio, and correlation coefficient by at least 2.71%, 1.86%, 0.09%, 0.46%, 0.24%, and 0.07%; and the proposed Combination 2 can effectively improve the contrast and edge features of the fused image and enrich the image detail information, with an average improvement of 37.42%, 26.40%, and 26.60% in the three metrics of average gradient, edge intensity, and spatial frequency compared with other algorithms. Full article

In various engineering fields, the fusion of infrared and visible images has important applications. However, in the current process of fusing infrared and visible images, there are problems with unclear texture details in the fused images and unbalanced displays of infrared targets and texture details, resulting in information loss. In this article, we propose an improved generative adversarial network (GAN) fusion model for fusing infrared and visible images. In the generator and discriminator network structure, we introduce densely connected blocks to connect the features between layers, improve network efficiency, enhance the network’s ability to extract source image information, and construct a content loss function using four losses, including an infrared gradient, visible intensity, infrared intensity, and a visible gradient, to maintain a balance between infrared radiation information and visible texture details, enabling the fused image to achieve ideal results. The effectiveness of the fusion method is demonstrated through ablation experiments on the TNO dataset, and compared with four traditional fusion methods and three deep learning fusion methods. The experimental results show that our method achieves five out of ten optimal evaluation indicators, with a significant improvement compared to other methods. Full article

This study established a model of mineral element homeostatic imbalance and examined the respiratory burst function of peripheral blood neutrophils and inflammatory and antioxidant indicators before and after the imbalance in sheep. The results showed that after an EDTA injection, the number of activated neutrophils in the peripheral blood was significantly higher than that in the control group (p < 0.01). In addition, the serum IL-6 level was significantly increased (p < 0.05) and matrix metalloproteinase 7 (MMP7) was inhibited (p < 0.05), but returned to a normal level one week after the injection. Tissue inhibitor of metalloproteinase 1 (TIMP1) levels were consistently higher after the injection and significantly higher than in the control group (p < 0.05). CuZn-SOD, TNOS activity, serum creatinine and urea nitrogen levels were significantly higher than before the injection (p < 0.05). Combining the results of previous studies, the EDTA injection altered the metabolism and transcription of peripheral blood neutrophils. These changes enhance the respiratory burst function of neutrophils and alter the status of inflammatory and antioxidant indicators such as IL-6 and CuZn-SOD. Full article

Existing fusion rules focus on retaining detailed information in the source image, but as the thermal radiation information in infrared images is mainly characterized by pixel intensity, these fusion rules are likely to result in reduced saliency of the target in the fused image. To address this problem, we propose an infrared and visible image fusion model based on significant target enhancement, aiming to inject thermal targets from infrared images into visible images to enhance target saliency while retaining important details in visible images. First, the source image is decomposed with multi-level Gaussian curvature filtering to obtain background information with high spatial resolution. Second, the large-scale layers are fused using ResNet50 and maximizing weights based on the average operator to improve detail retention. Finally, the base layers are fused by incorporating a new salient target detection method. The subjective and objective experimental results on TNO and MSRS datasets demonstrate that our method achieves better results compared to other traditional and deep learning-based methods. Full article