107 research outputs found

    Improving Image Captioning via Predicting Structured Concepts

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    Having the difficulty of solving the semantic gap between images and texts for the image captioning task, conventional studies in this area paid some attention to treating semantic concepts as a bridge between the two modalities and improved captioning performance accordingly. Although promising results on concept prediction were obtained, the aforementioned studies normally ignore the relationship among concepts, which relies on not only objects in the image, but also word dependencies in the text, so that offers a considerable potential for improving the process of generating good descriptions. In this paper, we propose a structured concept predictor (SCP) to predict concepts and their structures, then we integrate them into captioning, so as to enhance the contribution of visual signals in this task via concepts and further use their relations to distinguish cross-modal semantics for better description generation. Particularly, we design weighted graph convolutional networks (W-GCN) to depict concept relations driven by word dependencies, and then learns differentiated contributions from these concepts for following decoding process. Therefore, our approach captures potential relations among concepts and discriminatively learns different concepts, so that effectively facilitates image captioning with inherited information across modalities. Extensive experiments and their results demonstrate the effectiveness of our approach as well as each proposed module in this work.Comment: Accepted by EMNLP 2023 (Main Conference, Oral

    Key problems in in-situ pyrolysis of tar-rich coal drilling for extraction of coal-based oil and gas resources

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    Tar-rich coal is a special coal resource with the property of oil and gas resources. Developing the oil and gas resources contained in the tar-rich coal is of great significance for ensuring energy security and realizing the goal of "dual carbon". In-situ pyrolysis of tar-rich coal is a new coal resource development technology. Through some artificial cracks in coal seams, multiple wells can be connected. The coal seam is then heated using some technologies such as electric heating or fluid heating to generate oil and gas resources from the pyrolysis of tar-rich coal. At present, some problems such as coal seam heating mode, optimal pyrolysis temperature, reservoir reconstruction technology and efficient extraction of pyrolysis oil and gas need to be urgently solved. ① There are some defects in the application of reaction heating, conduction heating, and radiation heating in the underground in-situ heating of tar-rich coal. Convection heating based on injection fluid heating is more suitable for the in-situ heating of tar-rich coal. According to different geological conditions, it is still necessary to carry out targeted research work for optimizing the economical and safe heat carrying fluid and creating an efficient pyrolysis atmosphere. The combination of various heating methods is expected to be the breakthrough direction of the underground in-situ heating method of tar-rich coal. ② At present, 350−450 ℃ is generally recognized as the efficient pyrolysis temperature. With different coal characteristics and different pyrolysis atmospheres, the corresponding dominant pyrolysis temperature range is slightly different. The methods of chemical thermodynamics and kinetics for the pyrolysis of tar-rich coal are effective means to predict pyrolysis temperature scientifically. ③ Hydraulic fracturing, supercritical CO2 fracturing, and liquid nitrogen fracturing have some limitations for the in-situ pyrolysis of tar-rich coal. For different geological conditions, it is necessary to select the appropriate reservoir reconstruction scheme through specific objective evaluation. Controllable shock wave technology has the advantage of high efficiency and control in rock fracturing and is expected to be widely used in the in-situ pyrolysis process in the future. ④ The combustible gases produced by the pyrolysis of tar-rich coal are mainly CH4, H2, and CO, accompanied by a high content of CO2, which is easy to be directly extracted. The oil produced by pyrolysis is coal tar with high density and high viscosity, which will condense in large quantities below 180 ℃. There is a risk of wellbore clogging and the key to improving the extraction efficiency of pyrolysis products is to formulate the temperature and pressure maintenance scheme of the extraction well. In addition, the systematic issues such as integrated geological engineering evaluation, in-situ pyrolysis reaction process monitoring, and the whole-process numerical simulation of tar-rich coal should also be focused on in the future research work

    DNA self-assembly nanoflower reverse P-glycoprotein mediated drug resistance in chronic myelogenous leukemia therapy

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    Introduction: Chronic myelogenous leukemia (CML) is a clonal myeloproliferative disorder caused by the BCR-ABL chimeric tyrosine kinase. Vincristine (VCR) is widely used in leukemia therapy but is hindered by multidrug resistance (MDR).Methods: We prepared DNA nanoflower via self-assembly for the delivery of VCR and P-glycoprotein small interfering RNA (P-gp siRNA).Results and Discussion: The as-prepared nanoflower had a floriform shape with high loading efficiency of VCR (80%). Furthermore, the nanoflower could deliver VCR and P-gp siRNA into MDR CML cells and induce potent cytotoxicity both in vitro and in vivo, thus overcoming MDR of CML. Overall, this nanoflower is a promising tool for resistant CML therapy
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