DiffuVST: Narrating Fictional Scenes with Global-History-Guided Denoising Models

Recent advances in image and video creation, especially AI-based image synthesis, have led to the production of numerous visual scenes that exhibit a high level of abstractness and diversity. Consequently, Visual Storytelling (VST), a task that involves generating meaningful and coherent narratives from a collection of images, has become even more challenging and is increasingly desired beyond real-world imagery. While existing VST techniques, which typically use autoregressive decoders, have made significant progress, they suffer from low inference speed and are not well-suited for synthetic scenes. To this end, we propose a novel diffusion-based system DiffuVST, which models the generation of a series of visual descriptions as a single conditional denoising process. The stochastic and non-autoregressive nature of DiffuVST at inference time allows it to generate highly diverse narratives more efficiently. In addition, DiffuVST features a unique design with bi-directional text history guidance and multimodal adapter modules, which effectively improve inter-sentence coherence and image-to-text fidelity. Extensive experiments on the story generation task covering four fictional visual-story datasets demonstrate the superiority of DiffuVST over traditional autoregressive models in terms of both text quality and inference speed.Comment: EMNLP 2023 Finding

Rational design of acid stable oxide catalysts for OER with OC22

The efficiency of $H_2$ production via water electrolysis is typically limited to the sluggish oxygen evolution reaction (OER). As such, significant emphasis has been placed upon improving the rate of OER through the anode catalyst. More recently, the Open Catalyst 2022 (OC22) has provided a large dataset of density functional theory (DFT) calculations for OER intermediates on the surfaces of oxides. When coupled with state-of-the-art graph neural network models, total energy predictions can be achieved with a mean absolute error as low as of 0.22 eV. In this work, we interpolated a database of the total energy predictions for all slabs and OER surface intermediates for 4,119 oxide materialas in the original OC22 dataset using pre-trained models from the OC22 framework. This database includes all terminations of all facets up to a maximum Miller index of 1 with adsorption configurations for $O^*$ and $OH^*$. To demonstrate the full utility of this database, we constructed a flexible screening framework to identify viable candidate anode catalysts under a bulk and nanoscale regime for OER by assessing the price, thermodynamic stability, and resistance to corrosion, surface stability, and overpotential. Finally we verified the overpotentials and reaction energies of the final candidate catalysts using DFT. From our assessment, we were able to identify 48 and 69 viable candidates for OER under the bulk and nanoscale regime respectively

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

Peregrine and saker falcon genome sequences provide insights into evolution of a predatory lifestyle

As top predators, falcons possess unique morphological, physiological and behavioral adaptations that allow them to be successful hunters: for example, the peregrine is renowned as the world's fastest animal. To examine the evolutionary basis of predatory adaptations, we sequenced the genomes of both the peregrine (Falco peregrinus) and saker falcon (Falco cherrug), and we present parallel, genome-wide evidence for evolutionary innovation and selection for a predatory lifestyle. The genomes, assembled using Illumina deep sequencing with greater than 100-fold coverage, are both approximately 1.2 Gb in length, with transcriptome-assisted prediction of approximately 16,200 genes for both species. Analysis of 8,424 orthologs in both falcons, chicken, zebra finch and turkey identified consistent evidence for genome-wide rapid evolution in these raptors. SNP-based inference showed contrasting recent demographic trajectories for the two falcons, and gene-based analysis highlighted falcon-specific evolutionary novelties for beak development and olfaction and specifically for homeostasis-related genes in the arid environment–adapted saker

Serum-Derived Extracellular Vesicles Protect Against Acute Myocardial Infarction by Regulating miR-21/PDCD4 Signaling Pathway

Acute myocardial infarction (AMI) represents a leading cause of morbidity and mortality worldwide. Extracellular vesicles (EVs) are being recognized as a promising therapeutic approach in protecting against MI. Serum is a rich source of EVs, which transports various microRNAs (miRNAs, miRs). EVs from serum have been shown beneficial for protecting against ischemia-reperfusion injury; however, their roles in AMI are unclear. In addition, whether a miRNA might be responsible for the effects of serum EVs on protecting against AMI is undetermined. Here, we demonstrated that serum EVs significantly reduced cardiomyocytes apoptosis in both cellular and mouse models of AMI, and dramatically attenuated the infarct size in mouse hearts after AMI. Inhibition of miR-21 was shown to reduce the protective effects of serum EVs in inhibiting cardiomyocytes apoptosis. miR-21 was decreased in mouse hearts after AMI, while serum EVs increased that. In addition, the programmed cell death 4 (PDCD4) expression was identified as a target gene of miR-21. Therefore, our study showed the protective effects of serum EVs on AMI, and provided a novel strategy for AMI therapy

Silencing of DLGAP5 by siRNA Significantly Inhibits the Proliferation and Invasion of Hepatocellular Carcinoma Cells

<div><p>Background</p><p>The dysregulation of oncogenes and tumor suppressor genes plays an important role in many cancers, including hepatocellular carcinoma (HCC), which is one of the most common cancers in the world. In a previous microarray experiment, we found that DLGAP5 is overexpressed in HCCs. However, whether the up-regulation of DLGAP5 contributes to hepatocarcinogenesis remains unclear. </p> <p>Methodology/Principal Findings</p><p>In this study, we showed that DLGAP5 was significantly up-regulated in 76.4% (168 of 220) of the analyzed HCC specimens when compared with adjacent liver tissue. DLGAP5 overexpression was evident in 25% (22 of 88) of the HCC specimens without AFP expression, suggesting that DLGAP5 may be a novel biomarker for HCC pathogenesis. The silencing of DLGAP5 gene expression by RNA interference significantly suppressed cell growth, migration and colony formation in vitro. The expression level of DLGAP5 was also found to be related to the methylation level of its promoter in the HCC specimens. </p> <p>Conclusions/Significance</p><p>Taken together, these data suggest that the expression of DLGAP5 is regulated by methylation and that the up-regulation of DLGAP5 contributes to HCC tumorigenesis by promoting cell proliferation.</p> </div

RETRACTED ARTICLE: HOXA7 plays a critical role in metastasis of liver cancer associated with activation of Snail

Abstract Background Liver cancer is one of the main causes of cancer-related death in human. HOXA7 has been proved to be related with several cancers. Method The expression levels of HOXA7 were examined by Western blot, qRT-PCR or ICH. MTT was used to detect the proliferative rate of liver cancer cells. The invasive abilities were examined by matrigel and transwell assay. The metastatic abilities of liver cancer cells were revealed in BALB/c nude mice. Results In this report, we revealed that HOXA7 promoted metastasis of HCC patients. First, increased levels of HOXA7 were examined in liver cancer especially in metastatic liver cancer. Moreover, higher expression level of HOXA7 was associated with poorer prognosis of liver cancer patients. Overexpression of HOXA7 significantly enhanced proliferation, migration, invasion in vitro and tumor growth and metastasis in vivo meanwhile silencing HOXA7 significantly inhibited the aboves abilities of liver cancer cells. In this research, we identified that HOXA7 performed its oncogenic characteristics through activating Snail. Conclusion Collectively, we identify the critical role and possible mechanism of HOXA7 in metastasis of liver cancer which suggest that HOXA7 may be a potential therapeutic target of liver cancer patients