Synthesis and inclusion behavior of a heterotritopic receptor based on hexahomotrioxacalix[3]arene

A heterotritopic hexahomotrioxacalix[3]arene receptor with the capability of binding two alkali metals and a transition metal in a cooperative fashion was synthesized. The binding model was investigated by using ¹H NMR titration experiments in CDCl₃–CD₃CN (10:1, v/v), and the results revealed that the transition metal was bound at the upper rim and the alkali metals at the lower and upper rims. Interestingly, the alkali metal ions Li⁺ and Na⁺ bind at the lower and upper rim respectively depending on the dimensions of the alkali metal ions versus the size of the cavities formed by the calix[3]arene derivative. The hexahomotrioxacalix[3]arene receptor acts as a heterotritopic receptor, binding with the transition metal ion Ag⁺ and the alkali metals ions Li⁺ and Na⁺. These findings were not applicable to other different sized alkali metals, such as K⁺ and Cs⁺

Rapid-INR: Storage Efficient CPU-free DNN Training Using Implicit Neural Representation

Implicit Neural Representation (INR) is an innovative approach for representing complex shapes or objects without explicitly defining their geometry or surface structure. Instead, INR represents objects as continuous functions. Previous research has demonstrated the effectiveness of using neural networks as INR for image compression, showcasing comparable performance to traditional methods such as JPEG. However, INR holds potential for various applications beyond image compression. This paper introduces Rapid-INR, a novel approach that utilizes INR for encoding and compressing images, thereby accelerating neural network training in computer vision tasks. Our methodology involves storing the whole dataset directly in INR format on a GPU, mitigating the significant data communication overhead between the CPU and GPU during training. Additionally, the decoding process from INR to RGB format is highly parallelized and executed on-the-fly. To further enhance compression, we propose iterative and dynamic pruning, as well as layer-wise quantization, building upon previous work. We evaluate our framework on the image classification task, utilizing the ResNet-18 backbone network and three commonly used datasets with varying image sizes. Rapid-INR reduces memory consumption to only 5% of the original dataset size and achieves a maximum 6$\times$ speedup over the PyTorch training pipeline, as well as a maximum 1.2x speedup over the DALI training pipeline, with only a marginal decrease in accuracy. Importantly, Rapid-INR can be readily applied to other computer vision tasks and backbone networks with reasonable engineering efforts. Our implementation code is publicly available at https://anonymous.4open.science/r/INR-4BF7.Comment: Submitted to ICCAD 2023, under revie

Synthesis and structure of the inclusion complex {NdQ[5]K@Q[10](H₂O)4}·4NO₃·20H₂O

Heating a mixture of Nd(NO₃)₃·6H₂O, KCl, Q[10] and Q[5] in HCl for 10 min affords the inclusion complex {NdQ[5]K@Q[10](H₂O)₄}·4NO₃·20H₂O. The structure of the inclusion complex has been investigated by single crystal X-ray diffraction and by X-ray Photoelectron spectroscopy (XPS)

DreamVideo: High-Fidelity Image-to-Video Generation with Image Retention and Text Guidance

Image-to-video generation, which aims to generate a video starting from a given reference image, has drawn great attention. Existing methods try to extend pre-trained text-guided image diffusion models to image-guided video generation models. Nevertheless, these methods often result in either low fidelity or flickering over time due to their limitation to shallow image guidance and poor temporal consistency. To tackle these problems, we propose a high-fidelity image-to-video generation method by devising a frame retention branch based on a pre-trained video diffusion model, named DreamVideo. Instead of integrating the reference image into the diffusion process at a semantic level, our DreamVideo perceives the reference image via convolution layers and concatenates the features with the noisy latents as model input. By this means, the details of the reference image can be preserved to the greatest extent. In addition, by incorporating double-condition classifier-free guidance, a single image can be directed to videos of different actions by providing varying prompt texts. This has significant implications for controllable video generation and holds broad application prospects. We conduct comprehensive experiments on the public dataset, and both quantitative and qualitative results indicate that our method outperforms the state-of-the-art method. Especially for fidelity, our model has a powerful image retention ability and delivers the best results in UCF101 compared to other image-to-video models to our best knowledge. Also, precise control can be achieved by giving different text prompts. Further details and comprehensive results of our model will be presented in https://anonymous0769.github.io/DreamVideo/

Supramolecular Assembly of Tetramethylcucurbit[6]uril and 2-Picolylamine

The supramolecular assembly of symmetrical tetramethylcucurbit[6]uril (TMeQ[6]) and 2-picolylamine (AMPy) has been investigated via various techniques, including ultraviolet-visible (UV-vis) and nuclear magnetic resonance spectroscopy, isothermal titration calorimetry (ITC), and X-ray crystallography. The results indicated that TMeQ[6] could encapsulate the AMPy guest molecule to form a stable inclusion complex. The rotational restriction of the guest in the cavity of TMeQ[6] resulted in a large negative value of entropy. The X-ray crystal structure of the 1:1 inclusion complex between TMeQ[6] and AMPy revealed that AMPy exists in the elliptical cavity of TMeQ[6]

A missed case of intraductal oncocytic papillary neoplasm associated with missed stones in extrahepatic bile duct: a case report

The pathological features of intraductal oncocytic papillary neoplasm (IOPN) of the bile duct include tumor cells that are rich in eosinophilic cytoplasm and arranged in papillary structures. Herein, we report a missed case of IOPN of the bile duct because of concomitant gallstones. A 70-year-old woman was hospitalized with upper abdominal discomfort. The primary diagnosis was choledocholithiasis following imaging examination. However, an unidentified mass was detected after the gallstones were removed. The mass appeared as many papillary protuberances surrounded by fish-egg-like mucosa when viewed by the choledochoscope and was confirmed as IOPN by pathological examination. The patient underwent choledochectomy and no recurrence was observed at the 6-month follow-up examination. In this report, peroral choledochoscopy demonstrated its advantages for the diagnosis of biliary diseases and acquisition of tissue specimens. Therefore, it may solve the challenge related to the lack of preoperative pathological evidence for bile duct tumors

Erratum: Synthesis and structure of the inclusion complex {NDQ[5]K@Q[10](H2O)4}·4NO3·20H2O. (Molecules (2017) 22 (1147)

© 2019 by the authors. The authors wish to make the following correction to their paper [1]: We found that in the Authorship section, below the second address, a mistake exists on the published page. The e-mail, which is stated as “[email protected]”, should be corrected to “[email protected]”. The changes do not affect the scientific results. The manuscript will be updated and the original will remain online on the article webpage, with a reference to this correction