Query and Output: Generating Words by Querying Distributed Word Representations for Paraphrase Generation

Most recent approaches use the sequence-to-sequence model for paraphrase generation. The existing sequence-to-sequence model tends to memorize the words and the patterns in the training dataset instead of learning the meaning of the words. Therefore, the generated sentences are often grammatically correct but semantically improper. In this work, we introduce a novel model based on the encoder-decoder framework, called Word Embedding Attention Network (WEAN). Our proposed model generates the words by querying distributed word representations (i.e. neural word embeddings), hoping to capturing the meaning of the according words. Following previous work, we evaluate our model on two paraphrase-oriented tasks, namely text simplification and short text abstractive summarization. Experimental results show that our model outperforms the sequence-to-sequence baseline by the BLEU score of 6.3 and 5.5 on two English text simplification datasets, and the ROUGE-2 F1 score of 5.7 on a Chinese summarization dataset. Moreover, our model achieves state-of-the-art performances on these three benchmark datasets.Comment: arXiv admin note: text overlap with arXiv:1710.0231

Qwen Technical Report

Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to humans. In this work, we introduce Qwen, the first installment of our large language model series. Qwen is a comprehensive language model series that encompasses distinct models with varying parameter counts. It includes Qwen, the base pretrained language models, and Qwen-Chat, the chat models finetuned with human alignment techniques. The base language models consistently demonstrate superior performance across a multitude of downstream tasks, and the chat models, particularly those trained using Reinforcement Learning from Human Feedback (RLHF), are highly competitive. The chat models possess advanced tool-use and planning capabilities for creating agent applications, showcasing impressive performance even when compared to bigger models on complex tasks like utilizing a code interpreter. Furthermore, we have developed coding-specialized models, Code-Qwen and Code-Qwen-Chat, as well as mathematics-focused models, Math-Qwen-Chat, which are built upon base language models. These models demonstrate significantly improved performance in comparison with open-source models, and slightly fall behind the proprietary models.Comment: 59 pages, 5 figure

Nowhere to run: oligo (p-phenylene vinylene) kills oral intracellular bacteria photodynamically

Abstract Bacterial infections pose a severe threat to human health due to the exacerbation of antibiotic resistance and intracellular bacterial infections. Research suggests that oligo(p-phenylene vinylene) (OPV), commonly employed in the manufacture of organic solar batteries, can help address this issue. This study demonstrates the ability of OPV to target and sterilize intracellular Porphyromonas gingivalis and methicillin-resistant Staphylococcus aureus (MRSA) photodynamically. Most notably, OPV specifically targets bacteria without affecting healthy cells under dark conditions. Its chemical composition includes a conjugated backbone and ionic imidazole side chains, which allow OPV to bind to cell membranes. Furthermore, dental blue light curing lamps may excite OPV. Compared with antibiotics and traditional photosensitizers, OPV proves to be a potentially superior solution to eradicate intracellular microbial infections, both in fundamental research and clinical applications

Identification and investigation of the vibrational properties of crystalline and co-amorphous drugs with Raman and terahertz spectroscopy

International audienc

Matrix metalloproteinase 9 facilitates Zika virus invasion of the testis by modulating the integrity of the blood-testis barrier.

Zika virus (ZIKV) is a unique flavivirus with high tropism to the testes. ZIKV can persist in human semen for months and can cause testicular damage in male mice. However, the mechanisms through which ZIKV enters the testes remain unclear. In this study, we revealed that matrix metalloproteinase 9 (MMP9) was upregulated by ZIKV infection in cell culture and in A129 mice. Furthermore, using an in vitro Sertoli cell barrier model and MMP9-/- mice, we found that ZIKV infection directly affected the permeability of the blood-testis barrier (BTB), and knockout or inhibition of MMP9 reduced the effects of ZIKV on the Sertoli cell BTB, highlighting its role in ZIKV-induced disruption of the BTB. Interestingly, the protein levels of MMP9 were elevated by ZIKV nonstructural protein 1 (NS1) in primary mouse Sertoli cells (mSCs) and other cell lines. Moreover, the interaction between NS1 and MMP9 induced the K63-linked polyubiquitination of MMP9, which enhanced the stability of MMP9. The upregulated MMP9 level led to the degradation of essential proteins involved in the maintenance of the BTB, such as tight junction proteins (TJPs) and type Ⅳ collagens. Collectively, we concluded that ZIKV infection promoted the expression of MMP9 which was further stabilized by NS1 induced K63-linked polyubiquitination to affect the TJPs/ type Ⅳ collagen network, thereby disrupting the BTB and facilitating ZIKV entry into the testes