Keyframe Segmentation and Positional Encoding for Video-guided Machine Translation Challenge 2020

Video-guided machine translation as one of multimodal neural machine translation tasks targeting on generating high-quality text translation by tangibly engaging both video and text. In this work, we presented our video-guided machine translation system in approaching the Video-guided Machine Translation Challenge 2020. This system employs keyframe-based video feature extractions along with the video feature positional encoding. In the evaluation phase, our system scored 36.60 corpus-level BLEU-4 and achieved the 1st place on the Video-guided Machine Translation Challenge 2020.Comment: 4 pages; First Workshop on Advances in Language and Vision Research (ALVR 2020

SciCap+: A Knowledge Augmented Dataset to Study the Challenges of Scientific Figure Captioning

In scholarly documents, figures provide a straightforward way of communicating scientific findings to readers. Automating figure caption generation helps move model understandings of scientific documents beyond text and will help authors write informative captions that facilitate communicating scientific findings. Unlike previous studies, we reframe scientific figure captioning as a knowledge-augmented image captioning task that models need to utilize knowledge embedded across modalities for caption generation. To this end, we extended the large-scale SciCap dataset~\cite{hsu-etal-2021-scicap-generating} to SciCap+ which includes mention-paragraphs (paragraphs mentioning figures) and OCR tokens. Then, we conduct experiments with the M4C-Captioner (a multimodal transformer-based model with a pointer network) as a baseline for our study. Our results indicate that mention-paragraphs serves as additional context knowledge, which significantly boosts the automatic standard image caption evaluation scores compared to the figure-only baselines. Human evaluations further reveal the challenges of generating figure captions that are informative to readers. The code and SciCap+ dataset will be publicly available at https://github.com/ZhishenYang/scientific_figure_captioning_datasetComment: Published in SDU workshop at AAAI2

Keyframe Segmentation and Positional Encoding for Video-guided Machine Translation Challenge 2020

Video-guided machine translation as one of multimodal neural machine translation tasks targeting on generating high-quality text translation by tangibly engaging both video and text. In this work, we presented our videoguided machine translation system in approaching the Video-guided Machine Translation Challenge 2020. This system employs keyframe-based video feature extractions along with the video feature positional encoding. In the evaluation phase, our system scored 36.60 corpus-level BLEU-4 and achieved the 1st place on the Video-guided Machine Translation Challenge 2020.First Workshop on Advances in Language and Vision Research (ALVR 2020), July 9th 202

Vitamin C supramolecular hydrogel for enhanced cancer immunotherapy

Vitamin C (VitC) has shown great promise to promote cancer immunotherapy, however, its high hydrophilicity makes it quickly excreted, leading to limited therapeutic efficiency even with frequent high-dose administration. Herein, we provide a pioneering report about the employment of VitC amphiphile self-assembled nanofiber hydrogels for enhanced cancer immunotherapy. Specifically, driven by hydrogen bonding and hydrophobic interactions, the synthesized VitC amphiphile, consisting of a hydrophilic VitC headgroup and a hydrophobic alkyl chain, could self-assemble into an injectable nanofiber hydrogel with self-healing properties. The formed VitC hydrogel not only serves as a reservoir for VitC but also acts as an effective delivery platform for stimulator of interferon genes (STING) agonist-4 (SA). Interestingly, the VitC hydrogel itself exhibits antitumor effects by upregulating genes related to interferon (IFN) signaling, apoptotic signaling and viral recognition and defense. Moreover, the SA-encapsulated VitC hydrogel (SA@VitC hydrogel) synergistically activated the immune system to inhibit the progression of both local and abscopal tumors

Nonlinear relationship between dietary calcium and magnesium intake and peripheral neuropathy in the general population of the United States

BackgroundCalcium and magnesium are essential minerals that have significant roles in nerve function and regulation. There may be a correlation between dietary calcium and magnesium intake and peripheral neuropathy. However, this relationship remains unclear and requires further study.MethodsData from 7,726 participants in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2004 were analyzed in this study. The relationship between total dietary calcium and magnesium intake, as well as each quantile, and peripheral neuropathy was analyzed using a multifactor logistic regression model. To illustrate the dose–response relationship between calcium and magnesium intake and peripheral neuropathy, we utilized a restricted cubic spline (RCS) plot.ResultsOur analysis found a positive correlation between dietary intake of calcium and magnesium and peripheral neuropathy (calcium: OR 1.000, 95% CI 1.000–1.000; magnesium: OR 1.001, 95% CI 1.00–1.002). Participants in the first and third quantiles of dietary calcium intake had a significantly higher incidence of peripheral neuropathy than those in the second quantile (OR 1.333, 95% CI 1.034–1.719, OR 1.497, 95% CI 1.155–1.941). Those in the first and third quantiles of dietary magnesium intake also had a significantly higher incidence of peripheral neuropathy than those in the second quantile (OR 1.275, 95% CI 1.064–1.528, OR 1.525, 95% CI 1.231–1.890). The restricted cubic spline analysis revealed a U-shaped nonlinear relationship between dietary intake of calcium and magnesium and peripheral neuropathy.ConclusionThe study found a U-shaped non-linear relationship between dietary calcium and magnesium intake levels and peripheral neuropathy, indicating that both excessive and insufficient intake of calcium and magnesium can increase the incidence of peripheral neuropathy

Multi-factor coupling analysis of large-energy events in a kilometer deep mine

Based on the research background of Shandong Lilou Coal Mine, this paper used methods such as on-site investigation, engineering comparison, and on-site monitoring to research on the high-energy events that have occurred in Lilou Coal Mine since 2020, and drew the following conclusions: ①Systematically analyzed the relationship between four influencing factors and high-energy microseismic events including the distribution of abutment pressure, working face “square”, crossing faults, and mining speed, and searched the causes of large energy events. The mining influence range of No.1302 (top) working face is about 30 m behind the face to 170 m in front, and the advanced stress peak is about 70 m in front. The lateral microseismic events are mainly distributed along the gob-side entry, and the whole is offset to the side of the goaf. The distribution of microseismic events at No.1303 working face in the advancing direction of the working face ranges from 15 m behind the face to 200 m in front of the face, and the advanced stress peak is about 80 m in front of the face. The microseismic event at the No.1303 working face is bimodal in the lateral distribution pattern, shifting to the belt grooves. Affected by the wide coal pillar, the stress concentration on the belt grooves is higher than that on the track tunnel. The frequency and energy of microseismic events gradually increased before the “square” of the work face, and stabilized after the “square”. Before crossing the fault, the microseismic events gradually increased, decreased sharply during the crossing, and gradually stabilized after crossing the fault. The peak position of the event was about 40 m in front of the “square” or before the fault. When the mining speed of 1302 (top) working face is 50 m/month and the 1303 working face is 60 m/month, the frequency and energy are the largest. ②By analyzing the inducing factors and locations of large-energy events, large-energy events can be divided into three categories: “energy accumulation type” high-energy events, “fault activation type” high-energy events, and “island structure type” high-energy events, and put forward specific prevention and control measures for different types. The research in this article will provide reference for surrounding mines with similar geological factors and mining technical conditions