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During the joint extraction of entity and relationship from the operational management data of hydraulic engineering, complex sentences containing multiple triplets and overlapping entity relations often arise. However, traditional joint extraction models suffer from a single-feature representation approach, which hampers the effectiveness of entity relation extraction in complex sentences within hydraulic engineering datasets. To address this issue, this study proposes a multi-feature joint entity relation extraction method based on global context mechanism and graph convolutional neural networks. This method builds upon the Bidirectional Encoder Representations from Transformers (BERT) pre-trained model and utilizes a bidirectional gated recurrent unit (BiGRU) and global context mechanism (GCM) to supplement the contextual and global features of sentences. Subsequently, a graph convolutional network (GCN) based on syntactic dependencies is employed to learn inter-word dependency features, enhancing the model's knowledge representation capabilities for complex sentences. Experimental results demonstrate the effectiveness of the proposed model in the joint extraction task on hydraulic engineering datasets. The precision, recall, and F1-score are 86.5%, 84.1%, and 85.3%, respectively, all outperforming the baseline model. [ABSTRACT FROM AUTHOR]

Due to the frequent occurrence of extreme weather in recent years, accurate runoff prediction is crucial for the rational planning and management of water resources. Addressing the high uncertainty and multiple influencing factors in runoff prediction, this paper proposes a runoff prediction method driven by multi-source data. Based on multivariate observed data of runoff, water level, temperature, and precipitation, a Time2Vec-TCN-Transformer model is proposed for runoff prediction research and compared with LSTM, TCN, and TCN-Transformer models. The results show that the Time2Vec-TCN-Transformer model outperforms other models in metrics including MAE, RRMSE, MAPE, and NSE, demonstrating higher prediction accuracy and reliability. By effectively combining Time2Vec, TCN, and Transformer, the proposed model improves the MAPE for forecasting 1–4 days in the future by approximately 7% compared to the traditional LSTM model and 4% compared to the standalone TCN model, while maintaining NSE consistently between 0.9 and 1. This model can better capture the periodicity, long-term scale information, and relationships among multiple variables of runoff data, providing reliable predictive support for flood forecasting and water resources management. [ABSTRACT FROM AUTHOR]

Tight sandstone and shale oil and gas are the key targets of unconventional oil and gas exploration in the lake-delta sedimentary systems of China. Understanding the coevolutionary diagenesis of sandstone and shale reservoirs is crucial for the prediction of reservoir quality, ahead of drilling, in such systems. Thin-section description, scanning electron microscopy (SEM), X-ray diffraction (XRD), fluid inclusion analysis, porosity and permeability tests, high-pressure mercury intrusion (HPMI) measurements and nuclear magnetic resonance tests (NMR) were used to reveal the coevolutionary diagenetic mechanisms of a sandstone and shale reservoir in the Lianggaoshan Formation of the Eastern Sichuan Basin, China. The thermally mature, organic-matter-rich, dark shale of layer3 is the most important source rock within the Lianggaoshan Formation. It started to generate abundant organic acids at the early stage of mesodiagenesis and produced abundant hydrocarbons in the early Cretaceous. Porewater with high concentrations of Ca2+ and CO32− entered the sandstone reservoir from dark shale as the shale was compacted during burial. Potassium feldspar dissolution at the boundary of the sandstone was more pervasive than at the center of the sandstone. The K+ released by potassium feldspar dissolution migrated from the sandstone into mudstone. Grain-rimming chlorite coats occurred mainly in the center of the sandstone. Some silica exported from the shale was imported by the sandstone boundary and precipitated close to the shale/sandstone boundary. Some intergranular dissolution pores and intercrystal pores were formed in the shale due to dissolution during the early stages of mesodiagenesis. Chlorite coats, which precipitated during eodiagenesis, were beneficial to the protection of primary pore space in the sandstone. Calcite cement, which preferentially precipitated at the boundary of sandstone, was not conducive to reservoir development. Dissolution mainly occurred at the early stage of mesodiagenesis due to organic acids derived from the dark shale. Calcite cement could also protect some primary pores from compaction and release pore space following dissolution. The porosity of sandstone and shale was mainly controlled by the thickness of sandstone and dark shale. [ABSTRACT FROM AUTHOR]

Local chemotherapy is an alternative therapeutic strategy that involves direct delivery of drugs to the tumor site. This approach avoids adverse reactions caused by the systemic distribution of drugs and enhances the tumor-suppressing effect by concentrating the drugs at the tumor site. Drug-loaded microspheres are injectable sustained-release drug carriers that are highly suitable for local chemotherapy. However, a complex preparation process is one of the main technical difficulties limiting the development of microsphere formulations. In this study, core-shell structured microspheres loaded with paclitaxel (PTX; with a core-shell structure, calcium alginate outer layer, and a poly (lactic acid-co-glycolic acid) copolymer inner layer, denoted as PTX-CA/PLGA-MS) were prepared using coaxial electrostatic spray technology and evaluated in vitro and in vivo. PTX-CA/PLGA-MS exhibited a two-stage drug release profile and enhanced anti-tumor effect in animal tumor models. Importantly, the preparation method reported in this study is simple and reduces the amount of organic solvent(s) used substantially. [ABSTRACT FROM AUTHOR]

In response to the shortcomings of existing knowledge graph embedding strategies, such as weak feature interaction and latent knowledge representation, a unique hydraulic knowledge graph embedding method is suggested. The proposed method incorporates spatial position features into the entity-relation embedding process, thereby enhancing the representation capability of latent knowledge. Furthermore, it utilizes a multi-layer convolutional neural network to fuse features at different levels, effectively capturing more abundant semantic information. Additionally, the method employs multi-scale dilated convolution kernels to capture rich explicit interaction features across different scales of space. In this study, the effectiveness of the proposed model was validated on the link prediction task. Experimental results demonstrated that, compared to the ConvE model, the proposed model achieved a significant improvement of 14.8% in terms of mean reciprocal rank (MRR) on public datasets. Additionally, the suggested model outperformed the ConvR model on the hydraulic dataset, leading to a 10.1% increase in MRR. The results indicate that the proposed approach exhibits good applicability and performance in the task of hydraulic knowledge graph complementation. This suggests that the method has the potential to offer significant assistance for knowledge discovery and application research in the field of hydraulics. [ABSTRACT FROM AUTHOR]

The study of extraordinarily high organic matter content (EHOMC) is beneficial to promote the fine evaluation of shale oil and gas, but so far, there have been few studies on its mechanism. This paper carried out a comprehensive lithological and geochemical analysis of the black shales of the Wujiaping Formation in the Kaijiang-Liangping Trough. The results showed that the black shales of the Wujiaping Formation can be divided into two units (the upper and lower parts), and EHOMC occurs in its upper part. The redox-sensitive trace elements (RSTEs), MoEF-UEF covariation, and Ni/Co correlation showed that the lower part of Wujiaping Formation was a weakly restricted oxidation environment, while the upper part evolved into a sulfidation reducing environment. The productivity indicator elements (BaXS, NiXS, CuXS, P, and Mo) indicated that the upper Wujiaping Formation had higher primary productivity than the lower part. However, rare earth elements ((La/Yb)N) indicated that the deposition rate in the lower part of the Wujiaping Formation was higher than that in the upper part. In general, although the oxygenated water in the lower part of the Wujiaping Formation is not conducive to the preservation of organic matter, the high input of nutrients from land sources and the high deposition rate inhibit the decomposition of organic matter, so the lower part has a certain degree of organic matter accumulation. The sulfidation reducing environment and high paleoproductivity are the main reasons for the enrichment of organic matter in the upper part of the Wujiaping Formation. In addition, the sulfidation reducing environment and high paleoproductivity occurred during the violent upwelling at the end of Guadeloupe, a period of high sea level, these factors have jointly contributed to the enrichment of OM in the upper the Wujiaping Formation. [ABSTRACT FROM AUTHOR]

The performance of all learning-based group emotion recognition (GER) methods depends on the number of labeled samples. Although there are lots of group emotion images available on the Internet, labeling them manually is a labor-intensive and cost-expensive process. For this reason, datasets for GER are usually small in size, which limits the performance of GER. Considering labeling manually is challenging, using limited labeled images and a large number of unlabeled images in the network training is a potential way to improve the performance of GER. In this work, we propose a semi-supervised group emotion recognition framework based on contrastive learning to learn efficient features from both labeled and unlabeled images. In the proposed method, the unlabeled images are used to pretrain the backbone by a contrastive learning method, and the labeled images are used to fine-tune the network. The unlabeled images are then given pseudo-labels by the fine-tuned network and used for further training. In order to alleviate the uncertainty of the given pseudo-labels, we propose a Weight Cross-Entropy Loss (WCE-Loss) to suppress the influence of the samples with unreliable pseudo-labels in the training process. Experiment results on three prominent benchmark datasets for GER show the effectiveness of the proposed framework and its superiority compared with other competitive state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Sodium fluoride (NaF) is widely used in clinical dentistry. However, the administration of high or low concentrations of NaF has various functions in different tissues. Understanding the mechanisms of the different effects of NaF will help to optimize its use in clinical applications. Studies of NaF and epithelial cells, osteoblasts, osteoclasts, and periodontal cells have suggested the significant roles of fluoride treatment. In this review, we summarize recent studies on the biphasic functions of NaF that are related to both soft and hard periodontal tissues, multiple diseases, and clinical dentistry. [ABSTRACT FROM AUTHOR]

The characteristics of laminae in lamellar shale oil reservoirs have important influences on reservoir parameters, especially permeability. In order to explore the influence of lamina density and occurrence on the permeability of lamellar shale after hydration, we studied the lamellar shale in the Chang 7 member of the Yanchang Formation of Triassic in Ordos Basin. By comparing the permeability of bedding shale and lamellar shale with different densities of laminae, it was found that the permeability anisotropy of lamellar shale was stronger. In the direction parallel to the lamina, the permeability increased approximately linearly with an increase in lamina density. The effect of hydration on rock micropore structure and permeability was studied by soaking shale in different fluids. Most of the microfracture in the lamellar shale was parallel to the lamina direction, and hydration led to a widening of the microfracture, which led to the most obvious increase in permeability parallel to the lamina. Collectively, the research results proved that lamina density, occurrence, and hydration have a significant influence on the permeability anisotropy of lamellar shale. [ABSTRACT FROM AUTHOR]

Periodontal inflammation is a common inflammatory disease associated with chronic inflammation that can ultimately lead to alveolar attachment loss and bone destruction. Understanding autophagy and pyroptosis has suggested their significant roles in inflammation. In recent years, studies of differentiated embryo-chondrocyte expressed genes 1 and 2 (Dec1 and Dec2) have shown that they play important functions in autophagy and in pyroptosis, which contribute to the onset of periodontal inflammation. In this review, we summarize recent studies on the roles of clock genes, including Dec1 and Dec2, that are related to periodontal inflammation and other diseases. [ABSTRACT FROM AUTHOR]

The origin of the organic-rich shale in the Upper Ordovician Wufeng Formation and Lower Silurian Longmaxi Formation is complex and controversial. This paper reports the geochemical data of Wufeng-Longmaxi Formations in the Upper Yangtze region to restore the paleoenvironment and explore the accumulation mechanism of organic matter. The total organic carbon (TOC) content of the Wufeng Formation was relatively high, with an average of 2.86%. The Lower Longmaxi Formation showed the highest TOC content, with an average of 3.99%, and the upper part was a continuously low value with an average of 1.22%. The paleoproductivity proxies (Babio, Cu/Al, Ni/Al, Siexcess) showed that in the Katian and Rhuddanian-Aeronian Stages, the Upper Yangtze Sea had high primary productivity, indicating that organic matter accumulation was more affected by terrigenous influx and redox conditions. Al, Zr, and Zr/Al indicated that terrigenous influx was relatively high in the Kaitian-Hirnantian Stages, it was at a constant low in the Rhuddanian Stage, and increased again in the Aeronian Stage. The correlations between redox-sensitive trace elements (Mo, U, V) and TOC indicate that the organic-rich shale of the Wufeng Formation was deposited in the anoxic–euxinic environment. In the Longmaxi Formation, organic-rich shales formed in a more hypoxic environment, and overlying organic-lean shales formed in a suboxic environment. Therefore, the anoxic–euxinic conditions of the Late Ordovician Yangtze Sea were the main reason for the organic matter accumulation, but the high terrigenous influx caused by regression and/or structural controls diluted the organic matter to some extent. For the Early Silurian, a complete transgression–regression cycle changed terrigenous influx and redox conditions, resulting in significant differences in organic matter accumulation. [ABSTRACT FROM AUTHOR]

In order to effectively evaluate shale gas reservoirs with low porosity, extra-low permeability, and no natural productivity, dipole array acoustic logging, which can provide various types of information including P-wave slowness (DTC) and S-wave slowness (DTS), is widely used. As the dipole array acoustic logging tool has a larger investigation depth and is suitable for complex borehole environments, such as those with a high wellbore temperature, high drilling fluid column pressure, or irregular borehole wall, it has been mainly applied to the evaluation of lithology, gas potential, fractures, and stimulation potential in shale gas reservoirs. The findings from a case study of the Sichuan Basin in China reveal that the acoustic slowness, S-P wave slowness ratio (RMSC), and S-wave anisotropy of the dipole array acoustic logging can be used to qualitatively identify reservoir lithology, gas potential, and fractures. Using the relationship between DTC and the total porosity of shale gas reservoirs, and combined with the compensated neutron (CNL) and shale content (Vsh) of the reservoir, a mathematical model for accurately calculating the total porosity of the shale gas reservoir can be established. By using the relationship between the RMSC and gas saturation in shale gas reservoirs and tied with density log (DEN), a mathematical model of gas saturation can be established, and the determination of gas saturation by the non-resistivity method can be achieved, delivering a solution to the issue that the electric model is not applicable under low resistivity conditions. The DTS, DTC, and DEN of shale can be used to calculate rock mechanic parameters such as the Poisson's ratio (POIS) and Young's modulus (YMOD), which can be used to evaluate the shale stimulation potential. [ABSTRACT FROM AUTHOR]

Local chemotherapy is an alternative therapeutic strategy that involves direct delivery of drugs to the tumor site. This approach avoids adverse reactions caused by the systemic distribution of drugs and enhances the tumor-suppressing effect by concentrating the drugs at the tumor site. Drug-loaded microspheres are injectable sustained-release drug carriers that are highly suitable for local chemotherapy. However, a complex preparation process is one of the main technical difficulties limiting the development of microsphere formulations. In this study, core-shell structured microspheres loaded with paclitaxel (PTX; with a core-shell structure, calcium alginate outer layer, and a poly (lactic acid-co-glycolic acid) copolymer inner layer, denoted as PTX-CA/PLGA-MS) were prepared using coaxial electrostatic spray technology and evaluated in vitro and in vivo. PTX-CA/PLGA-MS exhibited a two-stage drug release profile and enhanced anti-tumor effect in animal tumor models. Importantly, the preparation method reported in this study is simple and reduces the amount of organic solvent(s) used substantially.