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Reservoir dispatching regulations are a crucial basis for reservoir operation, and using information extraction technology to extract entities and relationships from heterogeneous texts to form triples can provide structured knowledge support for professionals in making dispatch decisions and intelligent recommendations. Current information extraction technologies require manual data labeling, consuming a significant amount of time. As the number of dispatch rules increases, this method cannot meet the need for timely generation of dispatch plans during emergency flood control periods. Furthermore, utilizing natural language prompts to guide large language models in completing reservoir dispatch extraction tasks also presents challenges of cognitive load and instability in model output. Therefore, this paper proposes an entity and relationship extraction method for reservoir dispatch based on structured prompt language. Initially, a variety of labels are refined according to the extraction tasks, then organized and defined using the Backus–Naur Form (BNF) to create a structured format, thus better guiding large language models in the extraction work. Moreover, an AI agent based on this method has been developed to facilitate operation by dispatch professionals, allowing for the quick acquisition of structured data. Experimental verification has shown that, in the task of extracting entities and relationships for reservoir dispatch, this AI agent not only effectively reduces cognitive burden and the impact of instability in model output but also demonstrates high extraction performance (with F1 scores for extracting entities and relationships both above 80%), offering a new solution approach for knowledge extraction tasks in other water resource fields. [ABSTRACT FROM AUTHOR]

Automatically generating descriptions for disaster news images could effectively accelerate the spread of disaster message and lighten the burden of news editors from tedious news materials. Image caption algorithms are remarkable for generating captions directly from the content of the image. However, current image caption algorithms trained on existing image caption datasets fail to describe the disaster images with fundamental news elements. In this paper, we developed a large-scale disaster news image Chinese caption dataset (DNICC19k), which collected and annotated enormous news images related to disaster. Furthermore, we proposed a spatial-aware topic driven caption network (STCNet) to encode the interrelationships between these news objects and generate descriptive sentences related to news topics. STCNet firstly constructs a graph representation based on objects feature similarity. The graph reasoning module uses the spatial information to infer the weights of aggregated adjacent nodes according to a learnable Gaussian kernel function. Finally, the generation of news sentences are driven by the spatial-aware graph representations and the news topics distribution. Experimental results demonstrate that STCNet trained on DNICC19k could not only automatically creates descriptive sentences related to news topics for disaster news images, but also outperforms benchmark models such as Bottom-up, NIC, Show attend and AoANet on multiple evaluation metrics, achieving CIDEr/BLEU-4 scores of 60.26 and 17.01, respectively. [ABSTRACT FROM AUTHOR]

The "Golden Triangle" is located on the border between Myanmar, Laos, and Thailand, and slash-and-burn cultivation is an ancient and typical land type in this region. With the development of the "The Belt and Road" strategy of China and the climate change, the vegetation information is bound to change intensively under the combined influence of alternative plantation projects and economic policies. Here we used MOD13Q1-normalized differential vegetation index (NDVI) and meteorological data to analyze the variation of vegetation coverage and its correlation with climatic factors (temperature and precipitation) during the period of 2000–2018 by using trend analysis, stability analysis, and partial correlation analysis. The results showed that the overall vegetation coverage of this region exerted the trend of improvement and became more stable over time. Spatially, the agglomeration degree became weaker as time goes during 2000–2018. The precipitation was more closely correlated with NDVI than temperature, indicating that precipitation could be the main limiting factor influencing vegetation change in this area. The correlation between NDVI and climatic factors exhibited differences among different seasons, with NDVI being less correlated with temperature and precipitation in spring and summer and more correlated with them in autumn and winter. Investigating the long-term vegetation coverage of this region and analyzing the trend of climate change is beneficial to understand the development trend of the ecological environment and resource potential in this region. Simultaneously, it can provide a favorable ecological evaluation for The Belt and Road strategy and provide important scientific suggestions and guidance for the sustainable development of ecosystems and human society under the drastic environmental changes. [ABSTRACT FROM AUTHOR]

Lipid droplet (LD) is a kind of subcellular organelle, which originates from the endoplasmic reticulum (ER). LDs can move flexibly between other organelles and store energy in the cells. In recent years, LDs and lipid droplet–associated proteins have attracted added attention at home and abroad, especially in cardiovascular diseases. Cardiovascular diseases, especially ischemic heart disease (IHD), have always been the focus of attention because of their high morbidity and mortality. Atherosclerosis and myocardial remodeling are two important pathologic processes of IHD, and LDs and other organelles are involved in the development of the disease. The interaction between LDs and ER is involved in the formation of foam cells in atherosclerosis. And LDs, mitochondria, and lysosomes also affect the remodeling of cardiomyocytes by affecting ROS production and regulating PI3K/AKT pathways. In this article, we will review the role of LDs in IHD. [ABSTRACT FROM AUTHOR]

Cardiovascular disease (CVD) is one of the vital causes of morbidity and mortality, and the number of deaths from CVD has increased worldwide. Circular RNAs (circRNAs) is a novel type of endogenous noncoding RNA, which can form covalent closed continuous rings and are highly expressed in the eukaryotic transcriptome. In recent years, research on circRNAs have been increasing and the researchers have also become cumulatively aware of the association between circRNAs and CVD. This review highlights the biogenesis and functions of circRNAs and the role in cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Adding pigments into waterborne barrier coatings improves barrier properties and cost-effectiveness but increases the risk of crack formation during folding. Crack formation is affected by pigment shape, aspect ratio, and concentration; however, the exact mechanism for these effects is still not well understood. In this work, a systematic model was used to understand the influence of the paper and coating thickness, the latex and pigment modulus, the pigment shape and aspect ratio, and pigment concentration on the failure of waterborne barrier coatings during folding. A finite element method-based model was solved with a commercial package to simulate the folding process. These simulations were compared to experimental results to verify the key parameters that affect coating failure. High paper and coating thickness, pigment loadings, pigment aspect ratios, and modulus differences between latex and pigment increased the likelihood of failure. Experiments and models using lower modulus spherical plastic pigments were more difficult to fail than coatings made with higher modulus kaolin. The maximum strain for coatings bent to a set curvature was the smallest when the modulus of latex and pigment were similar. The model agreed closely with experimental results for two pigment types at various pigment loadings. [ABSTRACT FROM AUTHOR]

As a basic property of cloud, accurate identification of cloud type is useful in forecasting the evolution of landfalling typhoons. Millimeter-wave cloud radar is an important means of identifying cloud type. Here, we develop a fuzzy logic algorithm that depends on radar range-height-indicator (RHI) data and takes into account the fundamental physical features of different cloud types. The algorithm is applied to a ground-based Ka-band millimeter-wave cloud radar. The input parameters of the algorithm include average reflectivity factor intensity, ellipse long axis orientation, cloud base height, cloud thickness, presence/absence of precipitation, ratio of horizontal extent to vertical extent, maximum echo intensity, and standard variance of intensities. The identified cloud types are stratus (St), stratocumulus (Sc), cumulus (Cu), cumulonimbus (Cb), nimbostratus (Ns), altostratus (As), altocumulus (Ac) and high cloud. The cloud types identified using the algorithm are in good agreement with those identified by a human observer. As a case study, the algorithm was applied to typhoon Khanun (1720), which made landfall in south-eastern China in October 2017. Sequential identification results from the algorithm clearly reflected changes in cloud type and provided indicative information for forecasting of the typhoon. [ABSTRACT FROM AUTHOR]

In this work, near-infrared (NIR)-responsive core-shell gold nanorods/mesoporous silica/reduced graphene oxide (Au/SiO/rGO) nanoparticles with synergistically enhanced photothermal stability and transition effect had been prepared via electrostatic interaction. Gold nanorods (AuNRs) and rGO were employed as the NIR-responsive components. UV-Vis-NIR extinction spectra revealed that the surface plasmon resonance peak of AuNRs from Au/SiO/rGO nanohybrids remained unchanged after 9 h NIR exposure. UV-Vis-NIR extinction results also showed that thin silica shell was superior to the thick ones in the photothermal stability improvement of Au/SiO/rGO nanoparticles. Moreover, the doxorubicin release of Au/SiO/rGO was more rapid than that of Au/SiO upon NIR irradiation, indicating that synergistically enhanced photothermal effect between rGO and AuNRs endowed Au/SiO/rGO nanoparticles with excellent photothermal transition efficiency. Such novel NIR-responsive core-shell hybrid nanoparticles with enhanced photothermal stability and transition effect are well suited for further biological applications, such as photothermal therapy, bioimaging and drug delivery. [ABSTRACT FROM AUTHOR]

The primary aim of this study was to present the outcomes of percutaneous catheter drainage (PCD) in patients with infected pancreatitis necrosis. A second aim was to focus on disease severity, catheter size, and additional surgical intervention. A literature search of the PubMed/MEDLINE/Cochrane Library (January 1998 to February 2015) databases was conducted. All randomized, non-randomized, and retrospective studies with data on PCD techniques and outcomes in patients with infected pancreatitis necrosis were included. Studies that reported data on PCD along with other interventions without the possibility to discriminate results specific to PCD were excluded. The main outcomes were mortality, major complications, and definitive successful treatment with percutaneous catheter drainage alone. Fifteen studies of 577 patients were included. There was only one randomized, controlled trial, and most others were retrospective case series. Organ failure before PCD occurred in 55.3 % of patients. With PCD alone, definitive successful treatment was 56.2 % of patients. Additional surgical intervention was required after PCD in 38.5 % of patients. The overall mortality rate was 18 % (104 of 577 patients). Complications occurred in 25.1 % of patients, and fistula was the most common complication. PCD is an efficient tool for treatment in the majority of patients with infected pancreatitis necrosis as the only intervention. Multiple organ failures before PCD are negative parameters for the outcome of the disease. Large catheters fail to prove to be more effective for draining necrotic tissue. However, in the extent of multi-morbid patients, to determine one single prognostic factor seems to be difficult. [ABSTRACT FROM AUTHOR]

The common carp, Cyprinus carpio, is one of the most important cyprinid species and globally accounts for 10% of freshwater aquaculture production. Here we present a draft genome of domesticated C. carpio (strain Songpu), whose current assembly contains 52,610 protein-coding genes and approximately 92.3% coverage of its paleotetraploidized genome (2n = 100). The latest round of whole-genome duplication has been estimated to have occurred approximately 8.2 million years ago. Genome resequencing of 33 representative individuals from worldwide populations demonstrates a single origin for C. carpio in 2 subspecies (C. carpio Haematopterus and C. carpio carpio). Integrative genomic and transcriptomic analyses were used to identify loci potentially associated with traits including scaling patterns and skin color. In combination with the high-resolution genetic map, the draft genome paves the way for better molecular studies and improved genome-assisted breeding of C. carpio and other closely related species. [ABSTRACT FROM AUTHOR]

This brief is concerned with the issue of quantized H filtering for singular time-varying delay systems with an unreliable communication channel. The missing data are described by a binary switching sequence satisfying a conditional probability distribution. The purpose is to design a linear H filter such that the filtering error system is regular, causal, stochastically stable, and satisfies the prescribed H performance constraint. First, based on a finite sum inequality, a new delay-dependent stability condition is obtained. Then, the filter parameters are derived by solving a linear matrix inequality (LMI). Finally, numerical examples are given to illustrate that the proposed approach is effective and feasible. [ABSTRACT FROM AUTHOR]

Fluorescence imaging in vivo can non-invasively monitor and reveal the process of the implants. In this work, it has developed a novel Carbon dots/Hydroxyapatite/PVA (CDs/HA/PVA) dual-network (DN) hydrogel scaffold with excellent fluorescence and biocompatible properties, which have significant importance as implant biomaterials with the demands for less invasive procedures. The composite hydrogel was fabricated by two combined procedures, including firstly chemical crosslinking then physical crosslinking techniques. The composite hydrogel was further characterized by HRSEM, TGA and fluorescence spectrum et al. The results showed that the polymer networks of the CDs/HA/PVA DN hydrogel became more compact and their pore sizes decreased to about 1~3 μm after suffered the freezing/thawing cyclic process. When the mass ratios of CDs to PVA increased from 0.0% to 6.0%, they also exhibited a prominent enhancement of the maximum fluorescence emission intensities. What's more, the CDs/HA/PVA DN hydrogels had excellent biocompatibility as MC3T3-E1 cells exhibited highly cell viabilities on their surfaces, the relative cell viability was about 91.24% after the MC3T3-E1 cells were incubated with the hydrogels for 5 days. This fluorescence-related hydrogel has potential to be applied in non-invasive monitoring field for the in vivo evaluation of implant biomaterials. [ABSTRACT FROM AUTHOR]