Hierarchical Residual Learning for Image Denoising

In recent years, residual learning based convolutional neural networks have been applied to image restoration and achieved some success. To avoid network degradation, deep layers in these methods are identity mappings, which are not easy to be learned as observed in recent image recognition work. In this paper, we propose a novel residual learning based CNN framework for image denoising, which does not need to learn identify mappings while avoiding network degradation. The proposed CNN network contains three kinds of sub-networks: feature extraction sub-network, inference sub-network and fusion sub-network. The feature extraction sub-network is first used to densely extract patches and represent them as high dimensional feature maps. Multiple inference sub-networks are then cascaded to learn noise maps by exploiting multi-scale information in a hierarchical fashion, which makes our method have a strong ability of toleraing errors in noise estimation. Finally, the fusion sub-network fuses the noise maps to obtain the final noise estimation. The proposed hierarchical residual learning network can tackle with multiple general image denoising tasks such as Gaussian denoising and single image super-resolution. Experimental results on several datasets show that our hierarchical residual learning based image denoising method outperforms many state-of-the-art ones

Activity and mechanism of vanadium sulfide for organic contaminants oxidation with peroxymonosulfate

Transition metal sulfides have been demonstrated to be effective for peroxymonosulfate (PMS) activation towards wastewater treatment. However, the activity of vanadium sulfide (VS4) and the role of the chemical state of V have not been revealed. Here, three types of VS4 with various morphologies and chemical states of V were synthesized by using methanol (M−VS4, nanosphere composed of nanosheets), ethanol (E-VS4, sea urchin like nanosphere) and ultrapure water (U-VS4, compact nanosphere) as hydrothermal solvent, respectively, and used as heterogeneous catalysts to activate PMS for the degradation of refractory organic pollutants. The effects of PMS concentration, temperature, pH, inorganic ions, and humic acid (HA) on the degradation efficiency of VS4/PMS system were investigated systematically. The results indicated that the highest specific surface area and lowest ratio of V5+ enable E-VS4/PMS system possessed the highest performance in degrading tetracycline hydrochloride (TCH), in which 100% TCH was removed after operating 10 min (0.805 min−1) under a relatively low concentration of PMS (1 mM) and catalyst (100 mg/L). It also revealed that the system exhibited a typical radical process in TCH degradation, which could be attributed to the redox cycles between V5+, V4+ and V3+ in the presence of PMS to generate various radicals. This radical process enabled the E-VS4/PMS system with a high activity in wide reaction conditions and high mineralization ratios in degrading various refractory organic pollutants within 10 min. In addition, the E-VS4/PMS system exhibited favorable reusability and stability with very less V and S ions leaching, and showed excellent performance in real water purification

Data Caching Optimization With Fairness in Mobile Edge Computing

Data Caching Optimization With Fairness in Mobile Edge Computin

Phenoxy-imine/-amide aluminum complexes with pendant or coordinated pyridine moieties: Solvent effects on structural type and catalytic capability for the ROP of cyclic esters

Depending on the solvent employed, the dimeric aluminum phenoxyamide complexes [2-O,4-R4C6H3CHMeN(3′-R1,4′-R2,5′-R3C5HN)]2Al2Me2 (R1 = Me, R2 = R3 = R4 = H Al1; R2 = Me, R1 = R3 = R4 = H Al2; R3 = Me, R1 = R2 = R4 = H Al3; R1 = R2 = R3 = R4 = H Al4; R1 = Me, R4 = OMe, R2 = R3 = H Al5) or their monoaluminum phenoxyimine counterparts, [2-O-C6H4CH = N(3′-R1,4′-R2,5′-R3C5HN)]AlMe2 (R1 = Me, R2 = R3 = H Al6; R2 = Me, R1 = R3 = H Al7; R3 = Me, R1 = R2 = H Al8; R1 = R2 = R3 = H Al9), were obtainable by the treatment of the corresponding 2-pyridyl substituted salicylaldimine pro-ligand with AlMe3. Structural characterization of Al1 – Al4 highlights the Npy,N,O-chelation and bridging capacity of the dianionic pyridyl substituted phenoxyamide ligand. By contrast, the monoanionic phenoxyimine ligand in Al8 serves as an N,O-bidentate ligand with the Npy unit pendant. In the presence of benzyl alcohol (BnOH), all nine complexes exhibited high efficiency for the ring-opening polymerization (ROP) of ϵ-caprolactone (ϵ-CL), in which the activity displayed by dinuclear Al1 – Al5 in general exceeding that seen by mononuclear Al6 – Al9. Analysis of the polycaprolactone (PCL) generated using Al1/BnOH by 1H NMR spectroscopy and MALDI-TOF mass spectrometry showed the polymer to adopt mainly a linear structure with BnO groups constituting the end groups. By contrast, when Al1 was used in the absence of BnOH, the PCL was mainly cyclic in nature. For the ROP of L-LA or rac-LA good efficiency was again achieved albeit at a lower level than that seen for ϵ-CL. In common with that seen with ϵ-CL, the amount of BnOH employed proved crucial in determining both the linearity and end group composition of the polylactide (PLA)

Image Synthesis with Adversarial Networks: a Comprehensive Survey and Case Studies

Generative Adversarial Networks (GANs) have been extremely successful in various application domains such as computer vision, medicine, and natural language processing. Moreover, transforming an object or person to a desired shape become a well-studied research in the GANs. GANs are powerful models for learning complex distributions to synthesize semantically meaningful samples. However, there is a lack of comprehensive review in this field, especially lack of a collection of GANs loss-variant, evaluation metrics, remedies for diverse image generation, and stable training. Given the current fast GANs development, in this survey, we provide a comprehensive review of adversarial models for image synthesis. We summarize the synthetic image generation methods, and discuss the categories including image-to-image translation, fusion image generation, label-to-image mapping, and text-to-image translation. We organize the literature based on their base models, developed ideas related to architectures, constraints, loss functions, evaluation metrics, and training datasets. We present milestones of adversarial models, review an extensive selection of previous works in various categories, and present insights on the development route from the model-based to data-driven methods. Further, we highlight a range of potential future research directions. One of the unique features of this review is that all software implementations of these GAN methods and datasets have been collected and made available in one place at https://github.com/pshams55/GAN-Case-Study

How perceived corporate social responsibility and public knowledge affect public participation intention: evidence from Chinese waste incineration power projects

Purpose: Public participation is essential for mitigating local resistance faced by the environmentally stigmatized facilities. The purpose of this study is to investigate public participation intention in the decision-making of waste incineration power (WIP) projects by examining the role of perceived corporate social responsibility (PCSR) and public knowledge (PK) based on the theory of planned behavior (TPB).  Design/methodology/approach: A theoretical model correlating PCSR with public participation intention was developed by using the constructs of TPB as the mediators and PK as the moderator. Drawing on structural equation modeling (SEM), the data collected from 485 local residents of the WIP projects in Jiangsu, China were analyzed to test the model.  Findings: Companies' CSR practice went through public attitude, subjective norm and personal norm as mediating steps towards promoting participation intention. PK positively moderated the indirect relationships between PCSR and participation intention. Moreover, attitude, subjective norm and personal norm were found to have a positive effect on participation intention.  Originality/value: This study advances the understanding of public participation intention and enriches the literature relating to CSR and TPB involved in infrastructure development. In order to improve public participation intention, companies should take strategic social responsibility actions and present the benefits and moral values of the activities to the public, and as well make effort to diffuse WIP-related knowledge through interactive activities with the public. Authorities should establish social and personal value systems that praise public participation and improve their expectations of participation outcomes.</p

Nucleic acid isothermal amplification-based soft nanoarchitectonics as an emerging electrochemical biosensing platform

The emergence of nucleic acid isothermal amplification strategies based on soft nanoarchitectonics offers a new dimension to the traditional electrochemical technique, particularly because of its flexibility, high efficiency, and increased sensitivity for analytical applications. Various DNA/RNA isothermal amplification strategies have been developed for the design and fabrication of new electrochemical biosensors for efficient and important biomolecular detection. Herein, we provide an overview of recent efforts in this research field and the strategies for signal-amplified sensing systems, with their biological applications, current challenges and prospects in this promising new area

Citrate esterification of debranched waxy maize starch: Structural, physicochemical and amylolysis properties

Considering that the content of resistant starch (RS) in original starch is very low, chemical modification is one of choices to increase RS level for enhancing its application. The current study applied debranched waxy maize starch (DBS) to produce a citrate-esterified debranched starch (CADS) and investigated impact of the modification on RS formation. Native starch was also citrate esterified without debranching treatment as the control (CANS). Physicochemical and digestion properties of each sample were characterized, and the results indicated an absorption at 1724 cm −1 in FTIR spectrum was determined in either CADS or CANS, indicating the occurrence of the esterification. Debranching of starch molecules led to a higher degree of substitution (DS) of 0.793 for CADS than CANS. Furthermore, re-association of debranched starch achieved a B type crystalline pattern rather than an A type from its native starch granules. Esterification greatly destroyed crystalline regions until completely disappeared in CADS. The loss of crystalline region was highly consistent with the absence of endothermic peak both in CADS and CANS as revealed by DSC. Hydrolysis rate and digestibility of each sample followed the order: native starch > DBS > CANS > CADS, which may indicate that the introduction of the citric anhydride onto the starch molecules led to an increased space steric hindrance that delayed the enzyme contacting within glucosidic bonds. It could be the first report to prepare a citrate-esterified debranched starch with a higher resistance to amylolysis, and the current investigation may highlight a potent to produce a starch derivative with a higher RS content. © 2020 Elsevier Lt