Injecting Image Details into CLIP's Feature Space

Although CLIP-like Visual Language Models provide a functional joint feature space for image and text, due to the limitation of the CILP-like model's image input size (e.g., 224), subtle details are lost in the feature representation if we input high-resolution images (e.g., 2240). In this work, we introduce an efficient framework that can produce a single feature representation for a high-resolution image that injects image details and shares the same semantic space as the original CLIP. In the framework, we train a feature fusing model based on CLIP features extracted from a carefully designed image patch method that can cover objects of any scale, weakly supervised by image-agnostic class prompted queries. We validate our framework by retrieving images from class prompted queries on the real world and synthetic datasets, showing significant performance improvement on these tasks. Furthermore, to fully demonstrate our framework's detail retrieval ability, we construct a CLEVR-like synthetic dataset called CLVER-DS, which is fully annotated and has a controllable object scale

Channel Pruning Base on Joint Reconstruction Error for Neural Network

In this paper, we propose a neural network channel pruning method based on the joint reconstruction error (JRE). To preserve the global discrimination ability of a pruned neural network, we propose the global reconstruction error. To ensure the integrity of information in the forward propagation process of a neural network, we propose the local reconstruction error. Finally, through normalization, the two magnitude mismatched losses are combined to obtain the joint error. The baseline network and pruned network are symmetrical structures. The importance of each channel in the pruned network is determined by the joint error between the channel and the corresponding channel in the baseline network. The proposed method prunes the channels in the pruned network according to the importance score and then restores its accuracy. The proposed method reduces the scale of the neural network and speeds up the model inferring speed without losing the accuracy of the neural network. Experimental results show the effectiveness of the method. For example, on the CIFAR-10 dataset, the proposed method prunes 50% of the channels of the VGG16 model, and the accuracy of the pruned model is 0.46% higher than that of the original model

Channel Pruning Base on Joint Reconstruction Error for Neural Network

In this paper, we propose a neural network channel pruning method based on the joint reconstruction error (JRE). To preserve the global discrimination ability of a pruned neural network, we propose the global reconstruction error. To ensure the integrity of information in the forward propagation process of a neural network, we propose the local reconstruction error. Finally, through normalization, the two magnitude mismatched losses are combined to obtain the joint error. The baseline network and pruned network are symmetrical structures. The importance of each channel in the pruned network is determined by the joint error between the channel and the corresponding channel in the baseline network. The proposed method prunes the channels in the pruned network according to the importance score and then restores its accuracy. The proposed method reduces the scale of the neural network and speeds up the model inferring speed without losing the accuracy of the neural network. Experimental results show the effectiveness of the method. For example, on the CIFAR-10 dataset, the proposed method prunes 50% of the channels of the VGG16 model, and the accuracy of the pruned model is 0.46% higher than that of the original model

Chromium(III) adsorption removal from acidic solutions by isomeric and tunnel-structural iron oxyhydroxides

Iron oxyhydroxides for heavy metal treatment have attracted wide attention. In this work, iron oxyhydroxides of isomeric FeOOH (GpI) and tunnel-structural schwertmannite/akaganéite (GpII) were selected to study chromium (Cr(III)) adsorption removal from acidic aqueous solutions by batch experiments, under various reaction time, adsorbate/adsorbent level, pH and anions. Adsorption processes well fitted to pseudo-second-order kinetics (R2 = 0.992–0.999, except for 0.829 for Lep). Isotherm data could be fitted by Langmuir (R2 = 0.901–0.985), Freundlich (R2 = 0.884–0.985) and Temkin (R2 = 0.845–0.961) models at pH 3.7. Langmuir maximum adsorption capacities (mg/g) were 10.4−18.8 (FeOOH, except for 3.08 for Gth2) in GpI, and 20.60/43.40 (Sch-Chem/Sch-Bio) and 12.80/24.70 (Aka-Chem/Aka-Bio) in GpII. Adsorption capacities would gradually increase as Cr(III) concentrations increased within 0−40 mg/L, and could be markedly affected by the SO42- and H2PO4- anions. There were stable adsorption capacities at about pH 3.7, and then increased at pH 3.7–4.1. The Fourier transform infrared (FTIR) and X-ray photoelectron spectroscopy (XPS) results showed that adsorption mechanisms were electrostatic interaction and surface complexation. In addition, three optimal bio-/chem-schwertmannite and lepidocrocite adsorbents had good reusable properties and treating abilities of Cr(III)-polluted waters at pH 4.0. These results could provide a theoretical basis for the application of iron oxyhydroxides in removing Cr(III) from acid wastewaters. HIGHLIGHTS Iron oxyhydroxides were used for Cr(III) adsorption removal.; Cr(III) removal efficiencies were analyzed under various impact factors.; Bioschwertmannite had the highest Cr(III) adsorption capacity.; Schwertmannite and lepidocrocite had good reusability.

Mechanism of Mechanical Analysis on Torsional Buckling of U-Shaped Bellows in FLNG Cryogenic Hoses

Floating liquefied natural gas (FLNG) cryogenic hoses can be employed for the transmission of liquefied natural gas (LNG). Usually, U-shaped metal bellows can be applied as the inner lining of FLNG cryogenic hoses. In installation, positioning and other working conditions, torsion is one of the main loads, and torsional buckling instability is a major failure mode of U-shaped metal bellows of FLNG cryogenic hoses. In the current research, the buckling instability of bellows under torsional loads has been investigated in detail, the mechanical mechanism of deformation in torsional buckling mode of bellows has been analyzed and the influence of the structural design parameters on the stability performance has been summarized. It was seen that the axis of the bellows was presented as a spiral line shape during the torsional buckling stage. At the same time, the torsional buckling properties of toroid and spiral bellows were analyzed. The obtained results showed that the torsional buckling stability of the spiral bellows was weaker than that of the toroid bellows and increase of the spiral angle of the spiral bellows intensified this trend. In addition, the post-buckling analysis of U-shaped bellows under torsional loads was carried out by means of experiments and finite element simulation. It was shown that the results obtained from finite element (FE) analysis in this research presented a relatively accurate critical torque value and a consistent buckling instability mode, compared with the experimental results. On this basis, the effects of common defects such as thickness thinning on the torsional stability of bellows were investigated. Considering the geometric defect of thickness thinning, the error of FE analysis was reduced further, and it was found that the defect could significantly decrease the stability of the bellows. The above analysis results could provide a reference for structural design and post-buckling analysis of bellows

Mechanism of Mechanical Analysis on Torsional Buckling of U-Shaped Bellows in FLNG Cryogenic Hoses

Floating liquefied natural gas (FLNG) cryogenic hoses can be employed for the transmission of liquefied natural gas (LNG). Usually, U-shaped metal bellows can be applied as the inner lining of FLNG cryogenic hoses. In installation, positioning and other working conditions, torsion is one of the main loads, and torsional buckling instability is a major failure mode of U-shaped metal bellows of FLNG cryogenic hoses. In the current research, the buckling instability of bellows under torsional loads has been investigated in detail, the mechanical mechanism of deformation in torsional buckling mode of bellows has been analyzed and the influence of the structural design parameters on the stability performance has been summarized. It was seen that the axis of the bellows was presented as a spiral line shape during the torsional buckling stage. At the same time, the torsional buckling properties of toroid and spiral bellows were analyzed. The obtained results showed that the torsional buckling stability of the spiral bellows was weaker than that of the toroid bellows and increase of the spiral angle of the spiral bellows intensified this trend. In addition, the post-buckling analysis of U-shaped bellows under torsional loads was carried out by means of experiments and finite element simulation. It was shown that the results obtained from finite element (FE) analysis in this research presented a relatively accurate critical torque value and a consistent buckling instability mode, compared with the experimental results. On this basis, the effects of common defects such as thickness thinning on the torsional stability of bellows were investigated. Considering the geometric defect of thickness thinning, the error of FE analysis was reduced further, and it was found that the defect could significantly decrease the stability of the bellows. The above analysis results could provide a reference for structural design and post-buckling analysis of bellows

Yolk@Shell Nanoarchitecture of Au@r-GO/TiO₂ Hybrids as Powerful Visible Light Photocatalysts

Yolk@shell nanostructures of Au@r-GO/TiO₂ with mesoporous shells were prepared by a sol–gel coating process sequentially with GO and TiO₂ on Au/SiO₂ core/shell spheres, followed by calcination and template removal, where the silica interlayer acts as a template not only to produce the void space but also to promote the coating of the r-GO and TiO₂ layer. The evaluation of visible light photocatalytic activities in dye decomposition and water-splitting H₂ production demonstrated their superior photocatalytic performance, which indicates their potential as powerful photocatalysts