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The present study investigates the wetting and corrosion behaviour of slags on dense Al2O3 ceramics, focusing on the influence of varying vanadium- and titanium oxide content. Physicochemical properties of the slag were assessed by measuring wetting angles, heights and diameters of the molten slags on the alumina at different temperatures. Microscopic observations and elemental composition analysis were conducted on the interface between the corroded Al2O3 ceramics and the slags. Our findings demonstrated that the V2O3 addition in the slag leads to its oxidation to V2O5, which further reacts with Fe2O3 and MnO to form low melting point phases such as FeVO4 and MnVO6. Consequently, the melting point of the slag decreases significantly, resulting in a decreased wetting angle with the Al2O3 ceramics. The presence of unsaturated alumina in the slag leads to the dissolution of aluminium ions from the ceramics into the slag, which reacts with Fe2O3 and MnO to form spinel phases, contributing to material loss of the ceramics. Infiltration of the slag into the Al2O3 predominantly occurs through the alumina grain boundaries. Two types of infiltration are identified: one involving reactions with alumina to form low melting point phases like Fe2O3 and the other involving inherent low melting point phases such as MnVO6. In contrast, the penetration of SiO2 into the alumina substrate is limited. Additionally, the dissolution of Al2O3 into the slag creates pathways for further infiltration. This study highlights the significant influence of Ti and V content on the physicochemical properties of the slag and provides insight into the corrosion mechanism of Al2O3 ceramics by Ti and V containing slags.

Restoring campus pedestrian spaces is vital for enhancing college students' mental well-being. This study objectively and thoroughly proposed a reference for the optimization of restorative campus pedestrian spaces that are conducive to the mental health of students. Eye-tracking technology was employed to examine gaze behaviors in these landscapes, while a Semantic Difference questionnaire identified key environmental factors influencing the restorative state. Additionally, this study validated the use of virtual reality (VR) technology for this research domain. Building height difference (HDB), tree height (HT), shrub area (AS), ground hue (HG), and ground texture (TG) correlated significantly with the restorative state (ΔS). VR simulations with various environmental parameters were utilized to elucidate the impact of these five factors on ΔS. Subsequently, machine learning models were developed and assessed using a genetic algorithm to refine the optimal restorative design range of campus pedestrian spaces. The results of this study are intended to help improve students' attentional recovery and to provide methods and references for students to create more restorative campus environments designed to improve their mental health and academic performance. [ABSTRACT FROM AUTHOR]

Background: This study aimed to evaluate the effects of N‐carbamylglutamate (NCG) on piglets' growth performance and immune response, and to unravel the mechanisms of such effects. In a 2 × 2 factorial design including diet (with or without NCG) and immunological challenge (saline or lipopolysaccharide (LPS)), 24 piglets were randomly distributed into four groups. After being fed a basic diet or a NCG‐supplemented diet for 21 days, piglets were administered LPS or saline intraperitoneally. Results: The results showed that NCG increased the average daily gain and average daily feed intake, and the feed conversion ratio of piglets, and alleviated the adverse effects of LPS stimulation on intestinal morphology. At the phylum level, NCG reversed the increase in the abundance of Firmicutes and the reduction in that of Actinomycete caused by LPS stimulation. At the genus level, NCG increased the abundance of Lactobacillus, Blautia, norank_Butyricicoccaceae, Subdoligranulum, and Ruminococcus_gauvreauii_group, and LPS decreased the abundance of Escherichia‐Shigella and Ruminococcus_gauvreauii_group. The short‐chain fatty acid content was increased by NCG, but LPS reduced its content. N‐Carbamylglutamate also inhibited significantly the LPS‐induced increase in the relative expression of signal transducer and activator of transcription (STAT) 3, related orphan receptor (RAR) c, and pro‐inflammatory cytokines, and the decrease in the relative expression of STAT5, forkhead box P3, IL‐10 and transforming growth factor beta 1 mRNA. A significant correlation was found between intestinal microbiota and inflammatory cytokines and short‐chain fatty acids. Conclusion: N‐Carbamylglutamate can improve piglets' growth performance. It can also attenuate LPS‐induced intestinal inflammation by modulating microbiota and Th17/Treg balance‐related immune signaling pathways. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The liver plays crucial roles in material metabolism and immune response. Bacterial endotoxin can cause various liver diseases, thereby causing significant economic losses to pig industry. Tryptophan is an essential amino acid in piglets. However, whether tryptophan can alleviate liver injury and inflammation by regulating necroptosis and pyroptosis has not been clarified. This study aimed to investigate whether dietary tryptophan can alleviate lipopolysaccharide (LPS)-induced liver injury in weaned piglets. 18 weaned piglets were randomly distributed to three treatments, each with 6 replicates: (1) control; (2) LPS-challenged control; (3) LPS + 0.2% tryptophan. After feeding with control or 0.2% tryptophan-supplemented diets for 35 d, pigs were intraperitoneally injected with saline or LPS (100 mg/kg body weight). At 4 h post-injection, blood samples and liver were collected. Results indicated that tryptophan reduced alanine aminotransferase, aspartate aminotransferase, decreased the mRNA expression and protein expression of 70-kDa heat shock proteins. Moreover, tryptophan increased the mRNA expression and protein expression of claudin-1, occludin and zonula occludens and decreased hydrogen peroxide and malondialdehyde contents, and increased catalase, glutathione peroxidase and total superoxide dismutase activities and proinflammatory cytokine levels in the liver. Meanwhile, tryptophan inhibited pyroptosis-related and necroptosis-related protein expression in liver. Collectively, tryptophan could relieve liver damage, increased the antioxidant capacity and reduced inflammation by inhibiting pyroptosis and necroptosis signaling pathways. [ABSTRACT FROM AUTHOR]

Grain filling is essential for wheat yield formation, but is very susceptible to environmental stresses, such as high temperatures, especially in the context of global climate change. Grain RGB images include rich color, shape, and texture information, which can explicitly reveal the dynamics of grain filling. However, it is still challenging to further quantitatively predict the days after anthesis (DAA) from grain RGB images to monitor grain development. Results: The WheatGrain dataset revealed dynamic changes in color, shape, and texture traits during grain development. To predict the DAA from RGB images of wheat grains, we tested the performance of traditional machine learning, deep learning, and few-shot learning on this dataset. The results showed that Random Forest (RF) had the best accuracy of the traditional machine learning algorithms, but it was far less accurate than all deep learning algorithms. The precision and recall of the deep learning classification model using Vision Transformer (ViT) were the highest, 99.03% and 99.00%, respectively. In addition, few-shot learning could realize fine-grained image recognition for wheat grains, and it had a higher accuracy and recall rate in the case of 5-shot, which were 96.86% and 96.67%, respectively. Materials and Methods: In this work, we proposed a complete wheat grain dataset, WheatGrain, which covers thousands of wheat grain images from 6 DAA to 39 DAA, which can characterize the complete dynamics of grain development. At the same time, we built different algorithms to predict the DAA, including traditional machine learning, deep learning, and few-shot learning, in this dataset, and evaluated the performance of all models. Conclusions: To obtain wheat grain filling dynamics promptly, this study proposed an RGB dataset for the whole growth period of grain development. In addition, detailed comparisons were conducted between traditional machine learning, deep learning, and few-shot learning, which provided the possibility of recognizing the DAA of the grain timely. These results revealed that the ViT could improve the performance of deep learning in predicting the DAA, while few-shot learning could reduce the need for a number of datasets. This work provides a new approach to monitoring wheat grain filling dynamics, and it is beneficial for disaster prevention and improvement of wheat production. [ABSTRACT FROM AUTHOR]

Photocatalytic water splitting by semiconductor photocatalysts has attracted considerable attention in the past few decades. In this experiment, nanosized titanium dioxide (nano-TiO[subscript 2]) particles are used to photocatalytically split water, which is then monitored by an oxygen sensor. Sacrificial reagents such as organics (EDTA) and metal ions (Fe[superscript 3+]) are also included in the solutions with powder nano-TiO[subscript 2] as photocatalyst to help elucidate the photocatalytic reactions. In solutions containing nano-TiO[subscript 2] and Fe[superscript 3+], the quantity of dissolved oxygen increases, but the quantity of dissolved oxygen decreases upon addition of EDTA. This experiment provides a simple and convenient methodology to indirectly study the photocatalytic water-splitting process and to assess the effectiveness of scavenging toxic chemicals such as organics and metal ions in water. This work should provide valuable experience for undergraduate students in understanding the role of a photocatalyst in water splitting as well as methods for removing toxic substances in water. The proposed photocatalytic system in conjunction with an oxygen sensor and a data logger shows fast response time and good sensitivity for monitoring the photocatalytic reaction. It is more cost-effective and convenient as compared to other conventional methods. (Contains 3 figures.)