PCCNet:A Few-Shot Patch-wise Contrastive Colorization Network

Few-shot colorization aims to learn a model to colorize images with little training data. Yet, existing models often fail to keep color consistency due to ignored patch correlations of the images. In this paper, we propose PCCNet, a novel Patch-wise Contrastive Colorization Network to learn color synthesis by measuring the similarities and variations of image patches in two different aspects: inter-image and intra-image. Specifically, for inter-image, we investigate a patch-wise contrastive learning mechanism with positive and negative samples constraint to distinguish color features between patches across images. For intra-image, we explore a new intra-image correlation loss function to measure the similarity distribution which reveals structural relations between patches within an image. Furthermore, we propose a novel color memory loss that improves the accuracy of the memory module to store and retrieve data. Experiments show that our method allows the correctly saturated color to spread naturally over objects and also achieves higher scores in quantitative comparisons with related methods

PCCNet:A Few-Shot Patch-wise Contrastive Colorization Network

Few-shot colorization aims to learn a model to colorize images with little training data. Yet, existing models often fail to keep color consistency due to ignored patch correlations of the images. In this paper, we propose PCCNet, a novel Patch-wise Contrastive Colorization Network to learn color synthesis by measuring the similarities and variations of image patches in two different aspects: inter-image and intra-image. Specifically, for inter-image, we investigate a patch-wise contrastive learning mechanism with positive and negative samples constraint to distinguish color features between patches across images. For intra-image, we explore a new intra-image correlation loss function to measure the similarity distribution which reveals structural relations between patches within an image. Furthermore, we propose a novel color memory loss that improves the accuracy of the memory module to store and retrieve data. Experiments show that our method allows the correctly saturated color to spread naturally over objects and also achieves higher scores in quantitative comparisons with related methods

PCCNet:A Few-Shot Patch-wise Contrastive Colorization Network

Few-shot colorization aims to learn a model to colorize images with little training data. Yet, existing models often fail to keep color consistency due to ignored patch correlations of the images. In this paper, we propose PCCNet, a novel Patch-wise Contrastive Colorization Network to learn color synthesis by measuring the similarities and variations of image patches in two different aspects: inter-image and intra-image. Specifically, for inter-image, we investigate a patch-wise contrastive learning mechanism with positive and negative samples constraint to distinguish color features between patches across images. For intra-image, we explore a new intra-image correlation loss function to measure the similarity distribution which reveals structural relations between patches within an image. Furthermore, we propose a novel color memory loss that improves the accuracy of the memory module to store and retrieve data. Experiments show that our method allows the correctly saturated color to spread naturally over objects and also achieves higher scores in quantitative comparisons with related methods

ENV-607: SURFACTANT-MODIFIED BIOMASS ADSORBENTS FOR ENHANCED REMOVAL OF POLLUTANTS FROM AQUEOUS SOLUTION

From the view of economical efficiency and technology sustainability, considerable attention has been recently given to the use of low-cost biomass residues as adsorbents in pollution control. To achieve a desirable adsorptive efficiency, some efforts have also been made to modify biomass adsorbents through appropriate treatments. There is a particular interest in surfactant-assisted biomass surface modification. Although some findings from previous studies are encouraging, knowledge about the adsorption of pollutants onto surfactant-modified biomass is still limited. A number of issues about the characteristics of involved interface transport are poorly understood. The present study therefore aims to examine the adsorption of anionic azo dyes onto surfactant-modified biomass in the solution. Different surfactants are used for modification. The equilibrium and kinetic studies for the adsorption of anionic azo dyes on modified biomass are conducted and the effects of aqueous chemistry characteristics are also evaluated. The results present the potential of modified biomass as suitable adsorbent for the removal of anionic azo dyes from wastewater. It can help understand the migration patterns of organic pollutants at biomass-water interface

Comparative Metabolomics Revealed Metabolite Differences in Bamboo Shoots (Chimonobambusa tumidissinoda Hsueh & T. P. Yi ex Ohrnberger) at Different Growth Stages

In order to explore the dynamic changes and stage specificity of metabolites in bamboo shoots during its growth, widely targeted metabolomics based on ultra-high performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) was used to analyze fresh bamboo shoots harvested at heights of 10 and 25 cm. The results showed that a total of 875 metabolites belonging to 13 categories were identified from bamboo shoots, including sugars, alcohols and flavonoids, whose relative contents significantly increased in 25 cm-high bamboo shoots. Moreover, the results of multivariate statistical analyses showed that the metabolites in bamboo shoots had an obvious stage specificity. Totally 283 significantly differential metabolites were identified between the two growth stages, of which 102 metabolites were annotated to 82 metabolic pathways. The contents of 20 major nutrients did not significantly differ between the two growth stages; however, the contents of metabolites related to taste, flavor and bioactive function were higher, while the content of bitter compounds was lower in the 25 cm-high bamboo shoots. Therefore, compared with the 10 cm-high bamboo shoots, the 25 cm-high bamboo shoots have a higher comprehensive economic value and are more suitable for harvesting. The results of this study can provide a theoretical reference for the comprehensive development and sustainable utilization of Chimonobambusa tumidissinoda

Yushania tongpeii (Poaceae, Bambusoideae), a new bamboo species from north-eastern Yunnan, China

Yushania tongpeii D.Z.Li, Y.X.Zhang & E.D.Liu, a new species of the temperate bamboo tribe Arundinarieae (Poaceae: Bambusoideae), is described and illustrated from north-eastern Yunnan, China. Yushania tongpeii is characterised by taller branching from nodes 1–2 m above the ground, usually three branches at the node, sparse purple spots and thin white powder on the internode, densely purple-spotted culm sheaths, glabrous margins of culm sheaths and tomentose leaf ligules. Based on the morphological features, this new species is assigned to section Yushania

A Case-control Study on Non-smoking Primary Lung Cancers in Sichuan, China

Background and objective The incidence of lung cancer in non-smokers is increasing in recent years. The aim of this investigation is to explore main risk factors of non-smoking primary lung cancers in Sichuan province in order to provide more accurate data for clinical. Methods One hundred and fourty-five non-smoking pairs of cases and 145 of controls were matched by age and sex. The patients were newly-diagnosed definitely as primary lung cancer at West China Hospital of Sichuan University from March to December 2009. Results Seventeen exposure factors were explored as epidemic agents for non-smoking lung cancer in Sichuan by using univariate analysis; mutivariate conditional Logistic regression analysis showed that passive smoking, moved into newly renovated homes over the past 10 years, family cancer history from second/third-degree relatives, lack of emotion regulation, heavy work pressure and poor quality of sleep were main risk agents for the non-smoking lung cancer incidence with OR 2.267 (95%CI: 1.231-4.177), 5.080 (95%CI: 1.632-15.817), 7.937 (95%CI: 1.815-34.705), 2.491 (95%CI: 1.230-4.738), 5.769 (95%CI: 2.030-16.396), 2.538 (95%CI: 1.277-4.861), respectively. While higher body mass index, eating fruit and vegetable and regular participating in physical exercise might be protective factors with OR 0.419 (95%CI: 0.226-0.779), 0.344 (95%CI: 0.155-0.762), 0.507 (95%CI: 0.274-0.937), respectively. Conclusion The occurrence of non-smoking primary lung cancer associated with a variety of exposure factors including passive smoking, history of exposure to harmful environmental, family cancer history, mental and psychological factors in Sichuan Province

The complete chloroplast genome and phylogenetic position of Thamnocalamus unispiculatus (Poaceae: Bambusoideae: Arundinarieae)

Thamnocalamus unispiculatus T.P.Yi & J.Y.Shi 2007 is an important bamboo species with significant ecological and economic value. This study presents the complete chloroplast genome sequence of T. unispiculatus. The sequence was 139,726 bp in length and exhibited a typical quadripartite structure, containing four regions: large single copy regions (LSC, 83,283 bp), small single copy regions (SSC, 12,851 bp) and a pair of inverted repeats (IRs, 21,726 bp). A total of 130 genes were annotated, including 86 protein-coding genes, 36 transfer RNA genes, and eight ribosomal RNA genes. Phylogenetic analysis indicated that T. unispiculatus and T. spathiflorus are sister species, supporting the conclusion that Thamnocalamus is a monophyletic group. The chloroplast genome of T. unispiculatus promotes the protection and exploration of biodiversity, phylogenetic relationships, and genetic research in Bambusoideae