158 research outputs found

    Study on the thermal property of textile experimentally and numerically

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    Developing Magnetic Material for Remediation of Aquatic Nitrogen Pollution in Water Facilities

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    Natural organic matter affect water environmental security and posed a potential threat to human health, and thus it has long been considered as a key index to evaluate water treatment performance. Dissolved organic nitrogen is one of the NOM, which produces some disinfection byproducts having more toxic than those carbon-based materials. Coagulation is a key unit of drinking water purification and has received wide attention. However, conventional flocculation technology on removal of DON is so poor that we have to seek more effective improving measurement. The combined use of conventional flocculant and organic polymer can improve treatment efficiency to a certain extent, and enhanced coagulation can also improve the DON removal rate, but their DON removal performance is still not dreamful. At present, there is a lack of systematic research on flocculation to remove DON. Although some achievements have been made, there is still a big gap between the preparation technology of flocculant and the goal of efficient removal of DON in water.For treatment of secondary effluent of industrial wastewater, some studies show that the use of Fe3O4 mainly has the effect of accelerating separation, but the adsorption effect is not good. However, with the synergistic flocculation of amino functionalized Fe3O4 it has a good effect on removing water protein, polysaccharide and humic acid, which can meet the water quality discharge standard and reduce the dosage of flocculant. The above results show that functional nanoparticle materials are of great significance to improve the adsorption and flocculation performance. Therefore, the functional modification of magnetic nanoparticles plays an important role

    The optimization of experimental parameters for jet-ring spinning

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    The application of air-jet nozzle in ring spinning system has been turned up in the last decade, and the greatest advantage reported is the reducing of hairiness. In this paper, an attempt has been made to optimize the utility of a single air-jet nozzle in ring spinning system. Some parameters, such as air pressure, the distance between front roller nip line and air-jet nozzle inlet, and the number of orifices were adjusted to get a better quality yarn. In order to confirm the role of these parameters, the properties of ring and jet-ring spun yarns were compared. All the samples were characterized in terms of count, twist, irregularity, hairiness and strength. The results showed that the air pressure and the distance have a significant influence on irregularity; all the experimental parameters have a significant influence on hairiness. By multi-objective programming method, a set of optimal experimental parameters was found, and the properties of jet-ring spun yam were improved significantly

    Exploring Open-Vocabulary Semantic Segmentation without Human Labels

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    Semantic segmentation is a crucial task in computer vision that involves segmenting images into semantically meaningful regions at the pixel level. However, existing approaches often rely on expensive human annotations as supervision for model training, limiting their scalability to large, unlabeled datasets. To address this challenge, we present ZeroSeg, a novel method that leverages the existing pretrained vision-language (VL) model (e.g. CLIP) to train open-vocabulary zero-shot semantic segmentation models. Although acquired extensive knowledge of visual concepts, it is non-trivial to exploit knowledge from these VL models to the task of semantic segmentation, as they are usually trained at an image level. ZeroSeg overcomes this by distilling the visual concepts learned by VL models into a set of segment tokens, each summarizing a localized region of the target image. We evaluate ZeroSeg on multiple popular segmentation benchmarks, including PASCAL VOC 2012, PASCAL Context, and COCO, in a zero-shot manner (i.e., no training or adaption on target segmentation datasets). Our approach achieves state-of-the-art performance when compared to other zero-shot segmentation methods under the same training data, while also performing competitively compared to strongly supervised methods. Finally, we also demonstrated the effectiveness of ZeroSeg on open-vocabulary segmentation, through both human studies and qualitative visualizations

    Variation of Al species during water treatment:correlation with treatment efficiency under varied hydraulic conditions

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    The concentration of hydrolyzed coagulant ion species is a key factor in determining drinking water treatment efficiency. Direct correlation of water treatment efficiency with changes in species during coagulation has not been addressed. We investigated the correlation under different hydraulic conditions and water treatment efficiencies including changes in removal of turbidity, ultraviolet adsorption at 254 nm (UV254) and dissolved organic carbon (DOC). Results highlighted that Al species (monomeric species as Ala, medium polymeric species as Alb and colloidal species as Alc) behaved differently during coagulation and treatment efficiencies were affected. When varying the mixing speed, the removal of Alc species had a strong negative correlation with water treatment efficiency but under other hydraulic conditions positive correlations were found. The removal of Ala species was positively correlated with water treatment efficiency, but under other hydraulic conditions the low abundance of Ala species meant the correlation was difficult to observe. The Alb species were significantly and positively correlated with water treatment efficiency with the highest correlation coefficient (R2) of 0.87. The correlation of metallic species with removal efficiencies of the DOC and the UV254 produced higher R2 values. Correlation of the rate of removal of Alb species with the removal efficiencies of the DOC or the UV254 was better than for Alc. HIGHLIGHTS Hydrolyzed coagulant ion species is considered as one of key factors in determining drinking water treatment efficiency.; Drinking water treatment efficiency is often correlated with the distribution species in coagulant rather than water.; The variation of the species removal was investigated in the coagulation system.; Under varied hydraulic conditions a positive response in correlation was presented.
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