3-Hy­droxy-4-(3-hy­droxy­phen­yl)-2-quinolone monohydrate

In the title compound, also known as viridicatol monohydrate, C15H11NO3·H2O, the dihedral angle between the benzene ring and quinoline ring system is 64.76 (5)°. An intra­molecular O—H⋯O hydrogen bond occurs. The crystal structure is stabilized by classical inter­molecular N—H⋯O and O—H⋯O hydrogen bonds and weak π–π inter­actions with a centroid–centroid distance of 3.8158 (10) Å

3,6,8-Trihy­droxy-3,4,5,7-tetra­methyl-3,4-dihydro­isocoumarin

In the title compound, C13H16O5, one of the three hy­droxy groups is involved in intra­molecular O—H⋯O hydrogen bonds. The other two hy­droxy groups contribute to the three-dimensional hydrogen-bonding network, which consolidates the crystal packing

Iterative Soft Shrinkage Learning for Efficient Image Super-Resolution

Image super-resolution (SR) has witnessed extensive neural network designs from CNN to transformer architectures. However, prevailing SR models suffer from prohibitive memory footprint and intensive computations, which limits further deployment on edge devices. This work investigates the potential of network pruning for super-resolution to take advantage of off-the-shelf network designs and reduce the underlying computational overhead. Two main challenges remain in applying pruning methods for SR. First, the widely-used filter pruning technique reflects limited granularity and restricted adaptability to diverse network structures. Second, existing pruning methods generally operate upon a pre-trained network for the sparse structure determination, hard to get rid of dense model training in the traditional SR paradigm. To address these challenges, we adopt unstructured pruning with sparse models directly trained from scratch. Specifically, we propose a novel Iterative Soft Shrinkage-Percentage (ISS-P) method by optimizing the sparse structure of a randomly initialized network at each iteration and tweaking unimportant weights with a small amount proportional to the magnitude scale on-the-fly. We observe that the proposed ISS-P can dynamically learn sparse structures adapting to the optimization process and preserve the sparse model's trainability by yielding a more regularized gradient throughput. Experiments on benchmark datasets demonstrate the effectiveness of the proposed ISS-P over diverse network architectures. Code is available at https://github.com/Jiamian-Wang/Iterative-Soft-Shrinkage-SRComment: Accepted by ICCV 2023, code released at https://github.com/Jiamian-Wang/Iterative-Soft-Shrinkage-S

A Case of Cutaneous Nocardiosis with Involvement of the Trachea, Anterior Mediastinum and Sternum

Nocardiosis is a rare infectious disease due to Nocardia infections. In this report, we present a rare case of cutaneous nocardiosis with involvement of the trachea, anterior mediastinum and sternum. The strain of Nocardia has been isolated from bacterial culture of infected tissue. 16s rRNA sequencing confirmed that it contained the Nocardia genus. The patient was successfully treated with Co-SMZ