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Interpreting ocean remote sensing images is still a challenge that is worth studying because they can carry valuable information for various important applications. Due to the absence of labeled datasets, unsupervised object-based image analysis (OBIA) methods provide an effective solution to understand remote sensing images with the advantage of grouping local similar pixels into a homogeneous area. However, ocean remote sensing images usually have the characteristics of large size, large background, and coexisting of large and small objects, which results in previous OBIA methods easily falling into the difficulty of accurately segmenting the large and small objects at the same time and the dilemma of time-consuming computation. To solve this problem, a novel multiscale and multisubgraph (MSMSG)-based image segmentation method is presented in this article. First, a coarse-to-fine superpixel generation method is designed to generate optimal superpixels, which can not only solve the problem of coexisting large objects and small objects but also the problem of manually setting the initial segmentation number. Second, the proposed background removal strategy helps to eliminate the trouble of large background areas in ocean remote sensing images. Third, a multisubgraph is constructed with the help of background removal. Finally, the MSMSG merging strategy is addressed to group all similar superpixels into the same cluster, which not only reduces the useless computation of nonadjacent superpixels but also avoids segmentation errors with the same scale. Experiments conducted on three different datasets show that the proposed segmentation method is high-performance and high-efficiency.

Objective To investigate the longitudinal influence of alveolar bone grafting on the oral microbiota of children with cleft lip and palate (CLP).Materials and methods Twenty-eight children with nonsyndromic CLP were recruited and underwent secondary alveolar bone grafting at the first time. Unstimulated saliva and plaque samples were collected from the subjects preoperatively and at 2 days, 1 month, and 3 months postoperatively. The v3–v4 hypervariable regions of the 16S rRNAgene from bacterial DNA were sequenced using the Illumina MiSeq sequencing platform.Results The alpha diversity of the saliva and plaque microbiota was significantly decreased at 2 days postoperatively and then increased at 1 and 3 months postoperatively. The saliva and plaque microbiota compositions at 2 days postoperatively differed from those at the other time points, and the microbiota compositions at 1 and 3 months postoperatively showed a gradual shift toward the preoperative composition. The saliva, but not plaque, microbiota composition 3 months postoperatively was similar to that preoperatively.Conclusion The effect of secondary alveolar bone grafting on the plaque microbiota in children with CLP lasted longer than the saliva microbiota. Alveolar bone grafting altered the saliva microbiota in children with CLP within 3 months postoperatively.

With the rapid development of the Ethereum ecosystem and the increasing applications of decentralized finance (DeFi), the security research of smart contracts and blockchain transactions has attracted more and more attention. In particular, front-running attacks on the Ethereum platform have become a major security concern. These attack strategies exploit the transparency and certainty of the blockchain, enabling attackers to gain unfair economic benefits by manipulating the transaction order. This study proposes a sandwich attack detection system integrated into the go-Ethereum client (Geth). This system, by analyzing transaction data streams, effectively detects and defends against front-running and sandwich attacks. It achieves real-time analysis of transactions within blocks, quickly and effectively identifying abnormal patterns and potential attack behaviors. The system has been optimized for performance, with an average processing time of 0.442 s per block and an accuracy rate of 83%. Response time for real-time detection new blocks is within 5 s, with the majority occurring between 1 and 2 s, which is considered acceptable. Research findings indicate that as a part of the go-Ethereum client, this detection system helps enhance the security of the Ethereum blockchain, contributing to the protection of DeFi users’ private funds and the safety of smart contracts. The primary contribution of this study lies in offering an efficient blockchain transaction monitoring system, capable of accurately detecting sandwich attack transactions within blocks while maintaining normal operation speeds as a full node.

The oil concentration is a key parameter of great significance to evaluate the oilfield re-injection water (it generally shortened to re-injection water). However, the detection of the oil concentration for the re-injection water is limited due to the lack of the rapid and efficient detection technology for the evaluation of the organics concentration. The present study proposed a rapid analytical method for oil concentration of the re-injection water based on its optical properties, which has been similarly used in rapid detection of materials content, such as gas mixture and water steam quality. The transmittance spectra of the re-injection water were measured by the ultraviolet and visible (UV–Vis) spectrometer, and the effect on the spectra by the oil concentration was also investigated. A fitting relationship between the optical properties and the oil concentration was established. The results showed that the oil concentration has a great impact on the transmittance spectra of the re-injection water. The accuracy of fitting relationship between the optical properties and the oil concentration developed by the double-thickness inversion model and spectroscopy method is good, in which the minimum fitting error is 1.57% and the best fitting accuracy is 99.96%. The oil concentration also plays an important role in the optical properties of re-injection water, which greatly influence on the fitting accuracy.

Aiming at the problem that it is difficult to flexibly realize, the sharing and efficient search of encrypted data in large data-bases, this paper proposes a deterministic threshold proxy re-encryption scheme under the auxiliary input model. This scheme uses Shamir's secret sharing technology to achieve threshold control, uses homomorphic signature technology to verify the legitimacy of ciphertext, and applies deterministic algorithms to solve the search problem in large databases, while ensuring the user's control over their own data, and proves its security can reach indistinguishable semantic security (PRIV1-INDr) under the standard model. Compared with other schemes, this scheme not only shortens the length of the ciphertext and improves the decryption efficiency, but it also has anti-auxiliary input, robustness, and multi-hop characteristics and can better meet actual needs.

Due to the use of Cu(II) ions as catalysts, the production of polyacrylamide generates Cu-containing wastewater, constituting an environmental safety hazard and a waste of resources. This study proposes symmetric Ti3C2TxMXene-based electrodes for capacitive deionization to remove Cu(II) ions from chemical wastewater as a clean, low-energy, and resource-recyclable method and investigates their performances and mechanisms. Results showed that the adsorption capacity and removal efficiency of Cu(II) ions could reach 49.4 mg·g−1and 98.6% under the optimal experimental conditions (the initial Cu(II) ions concentration was 100.0 mg·L−1, imposed voltage of 1.0 V, circulation velocity of 25.0 mL·min−1, and the initial pH of 4.0). At the same time, the adsorption capacity and removal efficiency of Cu(II) ions in real copper-containing wastewater were 47.4 mg·g−1and 97.7%. In addition, by analyzing the changes of the electrode, the mechanism of electroadsorption was determined to include capacitive electroadsorption (double layer with pseudo-capacitance synergy) and cathodic electrodeposition. Ultimately, by applying a reverse voltage, Ti3C2TxMXene-based electrodes can be rapidly regenerated and recycled for continued use as catalysts. This simple operation has the advantage of potential economic benefits. Therefore, the Ti3C2TxMXene-based electrodes can be used potentially to remove Cu(II) ions in practical applications for environmental remediation.

Tachycardia, bradycardia, ventricular flutter and ventricular tachycardia are the four life-threatening arrhythmias, which are seriously harmful to the cardiovascular system. Therefore, a method for identifying these arrhythmias by pulse-to-pulse intervals analysis is proposed in this study. First, the noise and interference are wiped out from the raw pulse signal, and the clear pulse signal is spilt into pulse waves by pulse troughs whose first-order difference is the pulse-to-pulse intervals. Then, 15 features are extracted from the pulse-to-pulse intervals, and the two-samples Kolmogorov-Smirnov test is utilised to select the markedly changed features. Finally, we design the classifiers for arrhythmias recognition by the Probabilistic Neural Network (PNN), feedback neural network (BPNN) and Random Forest (RF). The pulse signal from the international physiological database (PhysioNET) is utilised as the experimental data. The experimental results show that RF classifier has the best average classification performance with the Kappa Coefficient (KC) of 98.86 ± 0.13% which is higher than that of BPNN with KC of 70.70 ± 1.61% and PNN with KC of 62.07 ± 0.75%. Compared with the existing methods, the proposed method has a higher performance in recognition of the four arrhythmias and has great potential to monitor the life-threatening arrhythmia in m-health.

A simultaneous analytical method was proposed for the determination of 13 kinds of free amino acids (FAAs) in the aqueous environment by high performance liquid chromatography (HPLC) combined with pre-column derivatization and solid-phase extraction technology. The recoveries for FAAs were between 8.9% and 87.6%, the detection limits of FAAs were in the range of 0.4– 2.09 mg/L without enrichment pretreatment, the relative standard deviations were less than 0.6%. The method has been successfully applied to determine low concentrations of FAAs in real water samples. The occurrence of total FAAs in the source water of Hangzhou City ranged from 17.4 to 39.0 μg/L. Tyr, Lys, and Asp were the dominant species and found with the highest concentrations of 13.4, 13.3, and 6.9 μg/L, respectively. The conventional water treatment and advanced water treatment with ozonation and activated carbon were not ideal for the removal of FAAs, thus harmful disinfection byproducts might originated in the subsequent chlorination process, including regulated carbonaceous disinfection by-products (C-DBPs) and nitrogenous disinfection by-products (N-DBPs).

Chlorine is the most commonly used disinfectant in drinking water treatment plants in China. It reacts with natural and anthropogenic organic pollutants in the water distribution system, resulting in the formation of carcinogenic disinfection by-products (DBPs). In this study, the influences of residence time, pH, chlorine dosage, water temperature, bromide concentration, and pipe material on the formation of DBPs in the water distribution system were investigated. Studies and observations showed that the formation of trihalomethanes (THMs) and haloacetic acids (HAAs) was positively correlated with residence time, chlorine dosage, water temperature, and bromide concentration during the chlorine disinfection, and the main generated DBPs were determined to be dichloroacetic acid, trichloroacetic acid, and trichloromethane. With the increase of bromide concentration, the generation of Br-DBPs substantially increased. Elevating solution pH posed a promoting effect on THMs production, while exerted an inhibitory effect on HAAs formation. The generation of THMs and HAAs in the water supply network was also affected by pipe material, and the production level followed the order of plastic steel pipe > ductile iron pipe > PE pipe. Through exploring different influencing factors, it provides a reference for the control strategy of DBPs in the water supply network and achieves the purpose of realizing the residents’ drinking water safety.

Coalition-structure's generation methods are usually employed to solve team allocation optimization problems or cooperative computing scheduling problems in the case of multitasking concurrency. In edge computing environments, affected by such factors as a large number of edge nodes, weak computing power, multiple optimization objectives and multiple constraints, the traditional methods can hardly guarantee the optimization speed and the optimal solution's quality when solving similar problems. Based on the advantages of cooperative game algorithms and heuristic algorithms, we propose a coalition-structure's generation method suitable for edge computing environments in this paper. Firstly, we introduce the concept of bargaining set and remove the impossible coalition-structures by judging the no-bargain coalition to narrow the strategic space. Secondly, for increasing the optimization speed and the optimal solution's quality, we improve the inertia weight computing method and the particle state determination method of the primary discrete particle swarm, propose M-ary discrete particle swarm optimization (MDPSO). Finally, we design a series of contrast experiments and verify that this method boasts obvious advantages in optimization speed, the optimal solution's quality, stability, and other aspects. [ABSTRACT FROM AUTHOR]

Long noncoding RNAs (lncRNAs) have been shown to execute key roles in spermatogenesis. However, little is known about how lncRNAs gene expression is itself regulated in the germ cells of testis. We previously demonstrated that high expression of lncRNA-Gm2044 exists in spermatocytes and can regulate male germ cell proliferation. Here, the transcriptional regulation of lnRNA-Gm2044 expression in spermatocytes and the downstream signaling were further explored. A bioinformatics assessment predicted two potential binding-sites for the spermatocyte-specific transcription factor A-MYB in the promoter region of lncRNA-Gm2044. Our results proved that the transcription factor A-MYB promotes the expression of lncRNA-Gm2044 in mouse spermatocyte-derived GC-2spd(ts) cells. ChIP and luciferase assays verified that A-MYB mainly binds to the distal promoter region (-819 bp relative to the transcription start site) of lncRNA-Gm2044 and regulates lncRNA-Gm2044 expression through the -819 bp binding-site. In addition, we confirmed that lncRNA-Gm2044 functions as a miR-335–3p sponge to enhance the levels of miR-335–3p′s direct target protein, Sycp1. Furthermore, A-MYB can up-regulate Sycp1 expression and down-regulate GC-2spd(ts) cell proliferation by activating its target, lncRNA-Gm2044. Overexpression of lncRNA-Gm2044 or knockdown of miR-335–3p can, at least partially, rescue the effects of A-MYB on Sycp1 expression and GC-2spd(ts) cell proliferation.Taken together, our results provide new information on the mechanistic roles of lncRNA-miRNA in transcription factor A-MYB regulation of spermatocyte function.

Phosphate inhibitors added is a method to control iron release from the pipes. This paper studied the effect of different phosphates on controlling iron release in different pipes and different water bodies. A multi-factor fitting method was used to fit a series of models of the iron release rate constant K and the main influencing factors after adding five kinds of phosphates to two different types of iron pipes and two kinds of water, respectively. The inhibition effects of phosphates on iron release were compared according to the predicted values of K under conventional water quality and fluctuating water quality. The results show that Na2HPO4can inhibit the release of iron with the most extensive application. In a gray iron pipe, turbidity has the greatest impact on K and negative correlation with K. However, in a ductile iron pipe, dissolved oxygen has the same effect on K comparing with turbidity.

Nitrogenous disinfection by-products (N-DBPs) are more genotoxic and cytotoxic than the currently regulated carbonaceous DBPs (i.e., C-DBPs), and it has become a frontier issue of drinking water safety research. In this paper, the effect of granular activated carbon (GAC) on adsorption and its influencing factors was investigated for a typical N-DBP phenylacetonitrile, which is produced during chlorination of phenylalanine precursor during water treatment. The results showed that GAC had a high adsorption capacity (qmax= 22.92 mg/g) for phenylacetonitrile, and the adsorption isotherm was fitted to the Langmuir isotherm model. Pseudo-second-order equation can well describe the behavior of phenylacetonitrile adsorption on activated carbon (R2> 0.990), and the adsorption rate constant k2= 0.7780–14.12 g/(mg h). Analysis of the influencing factors showed that higher phenylacetonitrile concentration improved the adsorption equilibrium capacity and the adsorption rate. Water temperature and pH had little effect on the capacity or rate of adsorption.

Implanted materials that enter the body first interact with proteins in body fluids, and cells then perceive and respond to the foreign implant through this layer of adsorbed proteins. Thus, spatially specific regulation of protein adsorption on an implant surface is pivotal for mediating subsequent cellular behaviors. Unlike the surface modulation strategy for traditional biomaterials, in this research, materials with a nonuniform spatial distribution of surface charges were designed to achieve site-selective protein adsorption and further influence cell behavior by charge regulation. Spatially varying microdomains with different levels of piezoelectricity were generated viaa focus laser beam-induced phase transition. In addition, after polarization, the zones with different levels of piezoelectricity showed significant differences in surface charge density. The results of scanning Kelvin probe force microscopy (SKPM) showed that the surface charge on the material exhibits a nonuniform spatial distribution after laser irradiation and polarization. Site-specific charge-mediated selective protein adsorption was demonstrated through a protein adsorption experiment. Cell behavior analysis showed that the increase in charge density was conducive to promoting cell adhesion and the formation of filopodia while the nonuniform spatial distribution of charge promoted an oriented arrangement of cells; both features accelerated cell migration. This study provides a new method for spatially regulating protein adsorption through surface charges to further influence cell behaviors.

Pipe breaks have significant impacts on the hydraulic and water quality performance of water distribution systems (WDSs). Therefore, it is important to evaluate these impacts for developing effective strategies to ultimately minimize the consequences of these events. However, there has been surprisingly limited research focusing on impact evaluation for pipe breaks so far. To address this gap, this paper proposes a framework to comprehensively evaluate hydraulic and water quality impacts of pipe breaks on a WDS using six quantitative metrics. These metrics primarily focus on identifying (i) break outflow volume, (ii) water shortage, (iii) nodes with reduced service quality, (iv) pipes with affected pressures, (v) pipes with reversed flow directions, and (vi) pipes with significantly increased velocities, for each breaking event within a WDS. Statistical behaviors, spatial properties, and pipe rankings of metric results are analyzed to reveal the underlying characteristics of impacts induced by pipe breaks. We illustrate the proposed framework using three WDSs with different properties. Results show that impacts of pipe breaks not only vary with pipe diameters but are also significantly influenced by pipe locations, when the break occurs, and the specific metric considered. The proposed framework greatly enhances the fundamental understanding of the underlying properties of breaking impacts on the hydraulic and water quality of WDSs, as well as the ranking of pipes based on the consequences of breaks. Such understanding offers important guidance to develop effective pipe management, resource planning, and break restoration strategies to minimize the impacts of breaking events on WDSs. The proposed framework is effective to comprehensively evaluate impacts of pipe breaksBoth hydraulic and water quality impacts are influenced by diameters, locations, and occurring time of the breaking pipesPipes are ranked based on consequence levels of their breaks, which offers important guidance for effective management of pipe breaks

The objective of this study was to evaluate the performance of the UV disinfection combined with chlorination in the inactivation of microorganisms and the formation of trihalomethanes (THMs). Experimental results showed that UV irradiation had obvious advantages in reducing the number of microbial species and community complexity. Under the same initial chlorine concentration, the amount of THMs increased with the UV radiation dose increasing. THMs will be reduced in the UV-chlorine disinfection process compared with the pure chlorine disinfection. In terms of number of surviving microorganisms in water, compared with a single chlorine disinfection, UV irradiation showed a very good disinfection effect. With an average 52.5% decline, the data reflected the sample after UV irradiation in microbial diversity and abundance significantly decreased. the physical and chemical properties of organic matter could be qualitatively and quantitatively described by 3DEEM.

In this paper, we propose a method named region mosaicking on Laplacian pyramids (RMLP) to fuse multi-focus images that are captured by microscope. First, we apply the sum-modified Laplacian to measure the focus of multi-focus images. Then the density-based region growing algorithm is utilized to segment the focused region mask of each image. Finally, the mask is decomposed into a mask pyramid to supervise region mosaicking on a Laplacian pyramid. The region level pyramid keeps more original information than the pixel level. The experiment results show that RMLP has the best performance in quantitative comparison with other methods. In addition, RMLP is insensitive to noise and can reduce the color distortion of the fused images on two datasets.

Currently, lithofacies are automatically classified in petroleum reservoirs based on different algorithm models using well-logging vector datasets. However, well-logging vector datasets are challenging for old oil fields where there are only well-logging images dataset present. Nevertheless, tight sandstone reservoirs, which have been neglected, are becoming exploration targets in old oil fields. This has made it necessary to redefine lithofacies characteristics. Thus, this paper describes a novel, widely applicable method for using a convolutional neural network (CNN) to identify tight sandstone reservoir lithofacies, which can handle well-logging image datasets rather than well-logging vector datasets. We applied this method to the Sanzhao Sag in the Northern Songliao Basin of China using the following steps: (1) dividing typical lithofacies based on core and well-logging characteristics; (2) preparing different lithofacies’ well-logging image datasets; and (3) establishing a CNN model with training, testing, and verification. For lithofacies recognition in a tight sandstone reservoir, compared with the recognized result of a model based on a well-logging vector datasets, such as decision tree analysis (DTA; 83%), support vector machine (SVM; 81%), K-nearest neighbor (KNN; 86%), and random forest (RF; 92%), the CNN model has a better prediction accuracy (92%). It also performs well when recognizing new wells in the Sanzhao Sag (92.16%). This result shows that the CNN model can effectively identify tight sandstone reservoir lithofacies based on a well-logging image dataset. Additionally, the sample intervals, lithofacies, geologic characteristics, and sample numbers affecting the prediction accuracy of the CNN model were also analyzed.

In this paper, we propose certain different design ideas on a novel topic in quantum cryptography — quantum operation sharing (QOS). Following these unique ideas, three QOS schemes, the “HIEC” (The scheme whose messages are hidden in the entanglement correlation), “HIAO” (The scheme whose messages are hidden with the assistant operations) and “HIMB” (The scheme whose messages are hidden in the selected measurement basis), have been presented to share the single-qubit operations determinately on target states in a remote node. These schemes only require Bell states as quantum resources. Therefore, they can be directly applied in quantum networks, since Bell states are considered the basic quantum channels in quantum networks. Furthermore, after analyse on the security and resource consumptions, the task of QOS can be achieved securely and effectively in these schemes.

As a globally important artificial sweetener, sucralose (SUC) is a persistent emerging contaminant in global aquatic environments. This research comprehensively track the fate and transport of SUC throughout an urban water cycle; to perform laboratory experiments to determine chlorinated disinfection by-products (DBPs) of SUC sebsequent to advanced oxidation with ozone; and to perform a risk evaluation of SUC related DBPs.; The results demonstrated that SUC was consistently present throughout the urban water cycle, including consumer's tap water. The inluent to the municipal wastewater treatment plant contained 1033.4-2626.3 ng/L SUC, and as expected for this non-biodegradable artificial sweetener, the concentration in the effluent was slightly reduced to 917.6-2031.2 ng/L. The concentration of SUC varied in surface waters with a peak value of 2070.0 ng/L. In finished drinking water 288.1–505.3 ng/L SUC was found, and values of 177.7–409.7 ng/L were present in the distribution system. Up to 16.3% of SUC concentration discharged as municipal wastewater was delivered to residents in their drinking water. While conventional treatment little removed SUC, the mean removal efficiency of SUC with ozonation followed by activated carbon filtration was 39.6% at a full-scale drinking water treatment plant. The fate and transformation of SUC in drinking water treated by ozonation and chlorination were investigated in laboratory experiments. Ozonation partially degraded SUC; however, intermediates reacted with chlorine to generate DBPs, including trichloromethane (TCM), dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA). Peak 7-days potential formation of TCM, DCAA and TCAA were 0.016, 0.51 and 23.34 μg/mg SUC, respectively. DBP yields increased with increasing chlorine dosage, chlorination time, temperature, and solution pH. The presence of ammonia nitrogen in water facilitated dichloroacetonitrile (DCAN) production up to 0.78 μg/mg SUC, while simultaneously reducing the yield of TCM, DCAA and TCAA. Human exposure analysis revealed that carcinogenic risks of DBPs caused only by SUC ozonation were in the range of 1.86 × 10−12-6.12 × 10−9, while non-carcinogenic risks were in the range of 6.0 × 10−9-4.37 × 10−6. The pervasive occurrence of SUC in an urban water cycle, couple to its resistance to biological and chemical treatment, confirms that SUC is a persistent contaminant in the aquatic system, including tap water.

Background and purpose:Detection of atrial fibrillation (AF) after acute ischemic stroke is pivotal for the timely initiation of anticoagulation to prevent recurrence. Besides heart rhythm monitoring, various blood biomarkers have been suggested as complimentary diagnostic tools for AF. We aimed to summarize data on the performance of cardiac natriuretic peptides for the diagnosis of covert AF after acute ischemic stroke and to assess their potential clinical utility.Methods:We searched PubMed and Embase for prospective studies reporting the performance of B-type natriuretic peptide (BNP) or N-terminal pro-B-type natriuretic peptide (NT-proBNP) for the diagnosis of covert AF after acute ischemic stroke. Summary diagnostic performance measures were pooled using bivariate meta-analysis with random-effects model.Results:We included six studies focusing on BNP (n = 1930) and three studies focusing on NT-proBNP (n = 623). BNP had a sensitivity of 0.83 (95% CI: 0.64-0.93), a specificity of 0.74 (0.67-0.81), a positive likelihood ratio of 3.2 (2.6-4.0), and a negative likelihood ratio of 0.23 (0.11-0.49). NT-proBNP had a sensitivity of 0.91 (0.65-0.98), a specificity of 0.77 (0.52-0.91), a positive likelihood ratio of 3.9 (1.8-8.7), and a negative likelihood ratio of 0.12 (0.03-0.48). Considering a pre-test probability of 20%, BNP and NT-proBNP had post-test probabilities of 45% and 50%.Conclusions:NT-proBNP has a better performance than BNP for the diagnosis of covert AF after acute ischemic stroke. Both biomarkers have low post-test probabilities and may not be used as a stand-alone decision-making tool for the diagnosis of covert AF in patients with acute ischemic stroke. However, they may be useful for a screening strategy aiming to select patients for long-term monitoring of the heart rhythm.

: The McDonald criteria are designed for predicting the second event in multiple sclerosis. With several revisions made to the McDonald criteria, the criteria get much easier to use, but what about the diagnostic validity? This research is conducted for evaluating the diagnostic validity of the McDonald criteria in multiple sclerosis.

To create cultural brand is the internal need of enhancing the development of national cultural industry. We collected total of 1526 articles relevant to cultural band from the China National Knowledge Infrastructure (CNKI) to analyse the data with bibliometrics, social network analysis. We divided the cultural brand research into three stages basing on the changes in the number of papers published each year which has been increasing recently and compared each stage according to their characteristics. The results indicate that the overall cultural brand research, characterized by diversification, shows more decentralization in the content. There are more researches focusing on Chinese traditional culture and innovation development of cultural industry due to the urgent need of the development of Chinese cultural brand. In addition, some traditional fields, such as cultural industry and regional culture, always attract more attention in all stages, while the topics that reflect the development of the time can also be popular in certain stage.