TRNR: Task-Driven Image Rain and Noise Removal with a Few Images Based on Patch Analysis.

The recent success of learning-based image rain and noise removal can be attributed primarily to well-designed neural network architectures and large labeled datasets. However, we discover that current image rain and noise removal methods result in low utilization of images. To alleviate the reliance of deep models on large labeled datasets, we propose the task-driven image rain and noise removal (TRNR) based on a patch analysis strategy. The patch analysis strategy samples image patches with various spatial and statistical properties for training and can increase image utilization. Furthermore, the patch analysis strategy encourages us to introduce the N-frequency-K-shot learning task for the task-driven approach TRNR. TRNR allows neural networks to learn from numerous N-frequency-K-shot learning tasks, rather than from a large amount of data. To verify the effectiveness of TRNR, we build a Multi-Scale Residual Network (MSResNet) for both image rain removal and Gaussian noise removal. Specifically, we train MSResNet for image rain removal and noise removal with a few images (for example, 20.0% train-set of Rain100H). Experimental results demonstrate that TRNR enables MSResNet to learn more effectively when data is scarce. TRNR has also been shown in experiments to improve the performance of existing methods. Furthermore, MSResNet trained with a few images using TRNR outperforms most recent deep learning methods trained data-driven on large labeled datasets. These experimental results have confirmed the effectiveness and superiority of the proposed TRNR. The source code is available on https://github.com/Schizophreni/MSResNet-TRNR.

Functional carbohydrate-based hydrogels for diabetic wound therapy.

Diabetes wound are grave and universal complications of diabetes. Owing to poor treatment course, high amputation rate and mortality, diabetes wound treatment and care have become a global challenge. Wound dressings have received much attention due to their ease of use, good therapeutic effect, and low costs. Among them, carbohydrate-based hydrogels with excellent biocompatibility are considered to be the best candidates for wound dressings. Based on this, we first systematically summarized the problems and healing mechanism of diabetes wounds. Next, common treatment methods and wound dressings were discussed, and the application of various carbohydrate-based hydrogels and their corresponding functionalization (antibacterial, antioxidant, autoxidation and bioactive substance delivery) in the treatment of diabetes wounds were emphatically introduced. Ultimately, the future development of carbohydrate-based hydrogel dressings was proposed. This review aims to provide a deeper understanding of wound treatment and theoretical support for the design of hydrogel dressings.

Current Progress in Natural Deep Eutectic Solvents for the Extraction of Active Components from Plants.

In the last decade, natural deep eutectic solvents (NADESs) have gained more and more attention due to their green, convenient preparation, low toxicity and biodegradability. It is widely used in various fields, especially in the extraction of active components from plants, formed by the combination of hydrogen bond donors (HBDs) and hydrogen bond acceptors (HBAs) at a certain condition. In this article, six preparation methods of NADESs were summarized and the interactions that occur in the eutectic behavior of NADES including hydrogen bonding, electrostatic interaction and van der Waals force were also reviewed. What is more, its significant extraction capacity on flavonoids, phenols, alkaloids and plant pigments endows its extensive applications in the extraction of active components from medicinal plants. Extraction factors including solvents properties (viscosity, carbon chain length, number of hydroxyl groups), extraction condition (water content, extraction temperature, extraction time, solid-liquid ratio), extraction method and recycling method were discussed. In addition, NADESs can also be combined with other technologies, like molecular imprinting, monolithic column, to achieve efficient and specific extraction of active ingredients. Further systematic studies on the biodegradability and biotoxicity are put forward to be urgent.

Optimization of the extraction process of flavonoids from Trollius ledebouri with natural deep eutectic solvents.

In recent years, natural deep eutectic solvents have been favored greatly due to their environment friendly, mild biological toxicity and simple biodegradability. Natural deep eutectic solvents gradually applied for the extracting bioactive compounds from natural products efficiently. In this study, 20 natural deep eutectic solvents were prepared and their physical and chemical properties were tested. The ultrasonic-assisted extraction method was used to extract flavonoids from Trollius ledebouri and high-performance liquid chromatography-ultraviolet was applied to examine two main bioactive flavonoids (orientin and vitexin). Compared with traditional solvents (water and 60% ethanol solution), natural deep eutectic solvents composed of L(-)-proline and levulinic acid (molar ratio 1:2) show a super extraction efficiency. On this basis, the response surface method was used to optimize the extraction temperature, extraction time, water contents, and solid-liquid ratio. As a consequence, the extraction temperature 60℃, extraction time 18 min, water content 14% (v/v), and the solid-liquid ratio 48 mL·g-1 were chosen as the best extraction process. This study shows that natural deep eutectic solvents can effectively extract flavonoids from T. ledebouri, laying a foundation for the further application of natural deep eutectic solvents to extract bioactive compounds from natural products.