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In order to solve the problem of multiplexing gain loss in Alamouti space-time block coding, this paper proposed a two-group Alamouti transmission scheme. On this basis, in order to improve the bit error ratio (13ER) with lower computational complexity at the receiver, this paper proposed a two-group Alamouti transmission scheme by combining GMD algorithm and non-linear precoding technique. The design method of the proposed solution consists of three main operations. Firstly, it obtained the effective channel matrix of two-group Alamouti transmission systems. Secondly, it jointly designed the transceiver with the obtained effective channel matrix by exploiting the GMD algorithm. Finally, it mitigated the inter-channel interference by utilizing non-linear precoding techniques of DPC and Tomlinson-Harashima Precoding (THP). The simulation results demonstrate that the proposed scheme is capable of significantly improving the achievable 13ER performance. [ABSTRACT FROM AUTHOR]

Based on Taoist immortality thought,the ancients' conception of ideal living environment, and the integration of the unique social political and ideological and cultural environment,"Taoism Nature Sanctuary（" TNS） has formed a unique landscape. Through traditional literature consultation, foreign related literature were reviewed. And used Citespace platform to analyze the relevant CNKI researches in the field of TNS. Then combined with the Taiwan academic literature database and main conference papers, reports, analyze the research status from four main perspectives: history and culture, temple architecture and affiliated Taoist gardens, the influence of TNS thought on the landscape design and living environment, and the development of tourism resources. On this basis, summarized the characteristics of the present researches in terms of research methods, areas and research contents, and looks forward to the future, so as to help the realization of the concept of the world heritage. [ABSTRACT FROM AUTHOR]

In order to obtain the new cellulose-degrading bacteria at normal temperature, a bacterial strain named as 18B with cellulosedegrading ability was isolated and purified from garden compost in this study. Congo red staining experiment and filter paper degradation experiment were conducted to verify its cellulose-degradation ability. 16S rRNA sequence alignment and whole genome alignment confirmed that it belonged to the genus Olivibacter, and was the closest to Olivibacter jilunii 14-2AT . Further comparative physiological and biochemical characterization revealed differences with O. jilunii 14-2AT in terms of growth temperature, oxidase and glycolysis. The strain 18B grew in the range of 12-48℃, and the optimal growth temperature was 30-37℃ . O. jilunii 14-2AT grew at 4-42℃ . Strain 18B was positive for oxidase and negative for glycolysis, while O. jilunii 14-2AT had no oxidase activity and was positive for glycolysis. Combined with the results of the genomewide covariance alignment, it was known that strain 18B had a certain evolutionary relationship with O. jilunii 14-2AT . The cellulose-degradation ability was found that the cellulase activity of 18B was up to 82.14+0.99 -9.90 U/L at 37℃, 200 r/min until the 5th d. Meanwhile, the enzyme activity could be maintained without degradation under the incubation conditions with sodium carboxymethyl cellulose as the only carbon source and only inorganic nitrogen source added. O. jilunii 14-2AT had no cellulose degrading ability and could not survive in a culture environment where sodium carboxymethylcellulose was the only organic carbon source. The results of whole genome sequencing showed that there were cellulase genes in the genome of strain 18B. The cellulase genes were heterologous expressed in Escherichia coli, and the degradation ability of the expressed products was tested. The results showed that the cellulase genes were active. The above results finally identified strain 18B as a new physiological strain of O. jilunii with cellulase activity. [ABSTRACT FROM AUTHOR]

Objective To compare the paper method and national standard method for food mould inspection. Methods Took 416 samples of pastries, drinks and others from the center quality management division in Wangjiang County Center for Disease Prevention and Control of Anhui province. inlcuding 317 pastries and 99 drinks, all of which were sent to conduct mould inspection by paper method and national standard methods. It should be compared their results. Results Among them, the qualification rate of pastries and drinks by the national standard method was 75.5%and 63.% respectively while those by paper method 78.9%, 65.7%, which showed the two methods had no statistcal significane in difference (x2=0.899, 0.088, P>0.05). Conclusion The two method is avaliable for mould inspection while the paper method is quicker, simpler, more effective and more practical, who may replace the national standard method. [ABSTRACT FROM AUTHOR]

The experiment was to study the stability of feed additive lysozyme dimer in influencing factors and accelerated test, determined the validity period of the product through long-term test. Three batches of lysozyme dimer samples were taken for influencing factor test (high temperature test, high humidity test and light test), accelerated test and long-term test, the moisture, dimer content and enzyme activity of lysozyme dimer were detected as inspection indicators. The results showed that the lysozyme dimer was relatively stable in the influence factor test, accelerated test and long-term test. The validity period of the product was preliminarily determined to be 12 months after the validity period prediction analysis. The experiment indicates that lysozyme dimer is relatively stable. The product can be packed in compound paper bags and stored in dry and ventilated places. [ABSTRACT FROM AUTHOR]

Normal and slim cigarettes with different filter ventilation and cigarette paper air permeability were rolled. The effects of filter ventilation, cigarette paper ventilation and ventilation distribution on nine phenolic aroma components release from mainstream cigarette smoke were investigated. The results showed the filter ventilation rate, paper ventilation rate negatively correlated to the releases of nine phenolic aroma components in cigarette smoke, and with the increase of ventilation rate, the decrease rate of maltol with caramel flavour and smaller molecular weight was higher, while the decrease rate of eugenol with smoky flavor and larger molecular weight was lower. No matter normal or small cigarettes, the paper and filter ventilation rate have different effects on the decrease of smoke composition, and the paper ventilation rate has greater influence than the filter ventilation rate. The effects of filter ventilation rate, paper ventilation rate and ventilation distribution on the release of nine phenolic aroma components in conventional cigarette smoke were greater than those in slim cigarette smoke. When the total ventilation rate was the same, the release of 9 phenolic aroma components in cigarette smoke with high filter ventilation rate and low paper ventilation rate was higher than that with low filter ventilation rate and high paper ventilation rate. [ABSTRACT FROM AUTHOR]

BACKGROUND: With the continuous improvement and progress of the magnetically controlled growing rod technology in the field of the treatment of spinal deformities, numerous studies have been put into this field, but the main research status, hot spots, and development trends are not clear enough. OBJECTIVE: Based on bibliometrics, this paper discusses the quality and quantity of articles in the field of using magnetically controlled growing rods to treat spinal deformities from different countries, aiming to clarify the global development trend of magnetically controlled growing rods and evaluate the research productivity, research trends, and research hotspots in the world. METHODS: The articles published from 1998 to 2023 were retrieved mainly based on the Web of Science database. CiteSpace 5.8 and VOSviewer 1.6.19 software were used to analyze the data and generate a visual knowledge map. The following parameters were evaluated for all studies: the total number of published papers, centrality, h index, the contribution of countries, authors, and journals, and the trend and hot spots were explored through the analysis of co-citation, highly cited literature, and literature keyword explosion. RESULTS AND CONCLUSION: (1) Finally, 138 articles were included. From 2009 to 2020, the number of published articles in this field gradually increased. The United States has the largest number of articles (53, 37.32%), and the United States has the highest h index and centrality of articles. (2) The results of keyword analysis showed that: the top ten keywords, such as early-onset scoliosis, surgery, complications, and so on, objectively and truly reflected the current situation and hot spots of magnetically controlled growing rod in the field of spinal deformity treatment. In recent years, the research focus in this field is the treatment failure caused by risk factors such as the pull-out of the magnetically controlled growing rod, implantation failure, and rod fracture, the accurate use of the corresponding medical classification, the monitoring and treatment of complications such as quality of life and cerebral palsy. (3) The co-citation results showed that: combined with the innovative and effective research of the magnetically controlled growing rod technology, the classification application of spinal deformity and the monitoring and treatment of related complications may be the research trend in this field. (4) Many highly cited articles further emphasized the therapeutic effect of magnetically controlled growing rod technology, providing an effective new idea and technical support for the field of spinal deformity correction. (5) The results of literature keyword explosion analysis demonstrate that the risk factors, medical classification, quality of life, and cerebral palsy of the application of magnetically controlled growing rods may become the research frontier in this field. (6) It can be seen that the application of magnetically controlled growing rod technology in the classification of spinal deformities and the in-depth study of related complications are the development trend in this field, but to further understand the effectiveness and safety of magnetically controlled growing rod technology in the treatment of spinal deformities, we still need long-term follow-up evidence. The overall research level of this field has steadily improved in recent years, but there are also problems such as the small number of high-quality articles and the unbalanced development of research in various regions. [ABSTRACT FROM AUTHOR]

BACKGROUND: In recent years, numerous studies have shown that long non-coding RNAs (lncRNAs) have an important role in the pathogenesis of periodontitis, including the immune response process and the biological activity and function of cells (periodontal stem cells and osteoblasts). Researchers attempt to regulate periodontal inflammation and periodontal regeneration by regulating lncRNA expression levels. OBJECTIVE: To review the progress of research on lncRNAs in periodontitis, thereby advancing the research of lncRNAs in periodontitis. METHODS: The first author searched PubMed, China National Knowledge Infrastructure (CNKI), Web of Science database, and WanFang Database for relevant literature published up to March 2023. “Long non-coding RNA, lncRNA, periodontitis, periodontium, immunity, inflammation, periodontal ligament stem cells, osteoclasts, osteogenic differentiation, bone resorption, bone formation, recurrence, hypoxia, oxidative stress, static mechanical strain”were used as the Chinese search terms. “lncRNA, periodontitis, periodontal, immunity, inflammation, periodontal membrane stem cells, osteoclasts, osteogenic differentiation, bone resorption, bone formation, recurrence, hypoxia, oxidative stress, static mechanical strain” were used as the English search terms. The title and abstract of each paper were read for initial screening, and 87 papers were finally selected for inductive analysis. RESULTS AND CONCLUSION: Periodontal pathogens stimulate the body, leading to immune imbalance that triggers inflammatory response and destroy periodontal tissue, and lncRNAs are involved in its regulatory mechanism. LncRNAs are involved in the pro-inflammatory regulation of periodontal ligament cells in an inflammatory environment, and their effects on osteoclast differentiation are regulated through ceRNA mechanism, which provides new clues for exploring the pathogenesis of periodontitis. For B cells and macrophages, lncRNAs can regulate the infiltration, cell activity and function of their subsets in periodontitis. LncRNAs participate in the immune response related to periodontitis mainly through two pattern recognition receptors, Toll-like receptors and NOD-like receptors, and nuclear factor-κB signaling pathway. To investigate whether lncRNAs can be used as a biomarker of periodontitis has great value in the diagnosis and prognosis of periodontitis. Animal experiments have demonstrated that the role of lncRNAs in periodontitis can be reversed by modulating the expression level of lncRNAs and thus lncRNAs act as an anti-inflammatory agent, which is of great value for the study of immunotherapy in periodontitis. The regulation of lncRNAs on periodontal ligament stem cells is mainly realized through endogenous competition mechanism and various signaling pathways, and its effects are influenced by various factors, such as inflammatory environment, mechanical strain, hypoxia and oxidative stress. Research on related mechanisms through these related factors provides new ideas for the treatment of periodontitis. [ABSTRACT FROM AUTHOR]

In order to explore the hotspots and research trends of domestic research on biochar in tobacco agriculture in recent years, bibliometric methods were used to analyze papers about biochar application in tobacco planting research included in the China National Knowledge Infrastructure (CNKI). The numbers, annual distribution, author information, publications and research content were statistically analyzed, and the CiteSpace V visualization software was used to predict and analyze research hotspots. The results showed that a total of 114 journal papers and 81 dissertations on the application of biochar to tobacco planting were retrieved, including 8 doctoral dissertations and 73 master’ s dissertations. The institution with the most research in China was Henan Agricultural University, and Liu Guoshun was the scholar with the most published papers. Domestic research on tobacco biochar still lacked a stable core author group, and the number of core authors was small. Tobacco biochar application hotspots focused on tobacco quality, chemical composition and tobacco-growing soil. In recent years, research hotspots tended to be on the effects of biochar on soil microbial communities and heavy metals in tobacco leaves. [ABSTRACT FROM AUTHOR]

Accurately identifying the spatial characteristics of “non-grain” cultivated land and proposing control measures have positive significance for accurate control of “non-grain” cultivated land. Taking Youjiang District as the research area, this paper identified the spatial characteristics of “non-grain” cultivated land in Youjiang District from the aspects of land type composition, slope distribution, landscape pattern, spatial adjacency, farming distance and transportation convenience. This paper proposed optimization and control measures for different types of “ non-grain” cultivated land to in order to guide cultivated land to grow food. The results show that: The total amount of “non-grain” cultivated land in Youjiang District has reached 308. 38 km², mainly dry land, followed by garden land and forest land. The slope of “non-grain” cultivated land is mainly greater than 6°, and when the terrain slope is less than 25°, the area of “non-grain” cultivated land increases with the increase of slope grade. “Non-grain” cultivated land is fragmented, with high spatial proximity to gardens and woodlands, and strong interaction. The closer to rural settlements (less than 800 m) and roads ( less than 1 200 m), the larger the proportion of “ non-grain” cultivated land, and the spatial distribution of “non-grain”cultivated land is affected by cultivation distance and transportation convenience. [ABSTRACT FROM AUTHOR]

Accelerating the citizenization of agricultural migrant population is an important task to realize urbanization, and the fundamental reason for the slow progress of citizens is the excessively high cost of urbanization of agricultural migrant population. At present, there are a considerable number of research findings concerning the cost of agricultural transfer of population urbanization. This paper adopts literature analysis method to review and sort the relevant research results of domestic scholars on the cost-sharing of urbanization for agricultural transfer populations. It elaborates on aspects such as the composition of cost-sharing for urbanization of migrant agricultural populations, precise calculation and quantitative methods of cost-sharing, and the construction of cost-sharing mechanisms. By combing and summarizing the existing research literature, the paper continuously promotes the in-depth study on the cost sharing of citizenization of the migrant agricultural population, so as to promote the development of new urbanization and rural revitalization. [ABSTRACT FROM AUTHOR]

At present, the pollution of nitrogen and phosphorus in rural domestic sewage and farmland drainage has not been effectively controlled. The development of“ecological purification technology”, a representative measure to solve such pollution, has attracted wide attention. This paper analyzes the ecological purification technology of nitrogen and phosphorus pollution in rural domestic sewage and farmland drainage from three perspectives of technology development, technical standards and technical system. The development of technology starts with the analysis and introduction of the current research progress of popular ecological purification technologies. Through the investigation and collation of the promotion and application of these technologies in China, the development characteristics of these technologies in different regions of China are sorted out, and the difficulties faced by the application of current ecological purification technologies are summarized. At present, the relevant departments only pay attention to the compliance rate of effluent quality in the supervision of ecological purification projects, and lack effective post-maintenance and opinion survey feedback. In terms of technical standards, this paper sorts out a series of standards on ecological purification projects that have been issued and implemented, and believes that comprehensive benefit evaluation methods should be introduced to improve the evaluation system of ecological purification projects in China. In terms of technical system, the single technology is classified according to the interception and repairability of ecological purification technology, and the corresponding technical combination system is summarized for rural domestic sewage and farmland drainage. [ABSTRACT FROM AUTHOR]

TOPCon cell substrates are dominated by N-type silicon wafers, and the oxygen content of N-type silicon wafers affects the conversion efficiency of TOPCon cells to a certain extent. In this paper, the Czochralski method was used to grow monocrystalline silicon, and the influence of crystal growth process parameters on the oxygen content of N-type monocrystalline silicon were studied by adjusting the crucible rotation rates, argon flow rates and furnace pressure. The numerical simulation analysis and experimental results show that: the accretion of crucible rotation rates can suppress buoyancy-thermal capillary vortices, reduce the volatilization of SiO at the melt interface, and increase the oxygen content in the silicon melt and in the monocrystalline silicon rods; increasing the argon flow rates and decreasing the furnace pressure can enlarge the mass flow rates of SiO at the melt interface, effectively promote SiO volatilization, reduce the oxygen content at the solid-liquid interface, and thus lessen the oxygen content in the monocrystalline silicon rods. The monocrystalline silicon oxygen content test and EL detection results show that, with the 5 r/min of crucible rotation rate, 100 L/min of argon flow rate, and 1 200 Pa of furnace pressure, the oxygen content in N-type monocrystalline silicon is the lowest, and the concentric circle ratio is also the lowest in the production of photovoltaic cells. The research in this paper can provide some ideas for reducing oxygen content in N-type monocrystalline silicon rods. [ABSTRACT FROM AUTHOR]

Aiming at the problems of inaccurate semantic segmentation results and rough saliency maps of indoor scene images, this paper proposed a network architecture (feature regulator and dual-path guidance, FG-Net) based on multi-modal feature optimization extraction and dual-path guided decoding. Specifically, the feature regulator sequentially performed noise filtering, re-weighted representation, differential complementation and interactive fusion on the multi-modal features at each stage, and optimized multi-modal feature representation in the feature extraction process by strengthening RGB and depth feature aggregation. Then, the dual-path guidance component introduced rich cross-modal cues after feature interactive fusion in the decoding stage to further take advantage of multi-modal features. The dual-path cooperative guidance structure outputted a more detailed saliency map by integrating multi-scale and multi-level feature information in the decoding stage. This paper conducted experiments on the public datasets NYUD-v2 and SUN RGB-D, and achieved 48.5% in the main evaluation metric mIoU, which is better than other state-of-the-art algorithms. The results show that the algorithm achieves more refined semantic segmentation of indoor scene images, and has good generalization and robustness. [ABSTRACT FROM AUTHOR]

Emerging network architectures and technical service requirements for B5G and 6G will enable MEC with CF-mMIMO, helping to handle compute-intensive and latency-sensitive tasks in distributed IoT. For CF-mMIMO-assisted MEC systems, this paper aimed to minimize the delay in completing computational tasks of different task types under energy constraint. In order to solve the above goals, this paper designed a task offloading strategy based on UEs, multiple APs and CPU (central processing unit) for cloud-edge-end collaboration. Specifically, according to the different data types of each UE and AP service, this paper firstly used the convex optimization and graph matching methods to alternately iterate to optimize the offload association and task ratio. Then, under the limitation of the backhaul link, this paper used an improved binary whale optimization algorithm to further offload the tasks of unallocated terminals and associated access points to the cloud with efficient processing. Compared with other meta-heuristics such as ant colony optimization algorithm and hybrid gray wolf optimization algorithm, the proposed algorithm has better performance on discrete offload optimization problems, which can provide a good offload optimization strategy for distributed systems and greatly reduce the average delay of the whole network. [ABSTRACT FROM AUTHOR]

To address the issues of low efficiency and frequent security vulnerabilities in smart contract development, this paper proposed a smart contract auto-generation method based on code comment optimization. Firstly, it constructed a smart contract clustering analysis model based on the semantic information of smart contract code associated annotations to achieve fast and accurate clustering of functions similar to smart contracts. Then, it divided the smart contract knowledge base into different levels such as the contract layer, function layer, and interface layer associated with the annotation. And based on the clustered code and annotation information, it constructed a diversified Prompt feature prompt statement dataset. Finally, it achieved automatic generation of smart contracts with specific needs based on the large language model ChatGLM2-6B and with the help of P-Tuning v2 fine-tuning technology. In order to test the effectiveness of this method, this paper conducted comparative experiments with existing methods using the bilingual translation quality assessment assistant tool BLEU and the code security detection tools Mythril and VaaS. Experimental results show that the average BLEU of the code generated by this method is increased by about 13%, and the code security is improved by about 6%. This method integrates code annotation information into the automatic generation of smart contracts, effectively improves the quality of smart contracts, and provides a new method for the efficient development of safe and reliable smart contracts. [ABSTRACT FROM AUTHOR]

Currently, researchers are focusing on efficient applications and resource scheduling strategies in vehicular edge computing (VEC) environments, however, the real-world validation of these applications and strategies is often limited by cost and time and cannot be performed quickly and efficiently. The emergence of edge/fog computing simulators such as iFogSim2 reduces the cost of experiments. However, the connection switching and resource allocation requirements of high-speed moving vehicles pose challenges to the application of edge/fog computing simulators under VEC. Therefore, this paper improved iFogSim2 by designing VECSim, a VEC environment simulator that supported high-speed mobility. It integrated open-source base station data and constructed vehicle trajectory datasets so that researchers can focus on resource allocation strategies. Firstly, to simplify the experimental steps, this paper improved the mobile trajectory data parsing module and adapted the vehicle trajectory data generated by Simulation of Urban Mobility (SUMO), a microscopic transportation simulation software. Secondly, this paper modeled distributed applications under VEC based on the distributed data flow model and provided a service migration benchmark policy algorithm. In addition, VECSim introduced a time-performance optimization method to accelerate the simulation event processing by parallelizing the operation, which improved the time performance of the simulation tool. Experiments show that compared with similar service migration algorithms in iFogSim2, the proposed service migration algorithm exhibits good stability under the validation of large-scale motor vehicle trajectory dataset, and the time-performance optimization method achieves a 5.3% performance improvement in execution time. [ABSTRACT FROM AUTHOR]

In order to further optimize the overlapping community detection algorithm, this paper proposed a new definition of node importance based on degree and node clustering coefficient, and the nodes were updated in descending order of node importance, and the node update strategy was fixed to improve the stability of community detection. On this basis, this paper proposed an OCD-GEMPA. The algorithm combined the node2vec model to represent the nodes in a low-dimensional vector, constructed a matrix of weight values between nodes, calculated the label attribution coefficient according to the weight values, and selected labels accordingly, avoiding the problem of random selection. Experimental verification of the algorithm on real data sets and synthetic data sets shows that compared to other overlapping community detection algorithms, the OCD-GEMPA algorithm has significant improvements in both EQ and NMI indicators, with better accuracy and stability. [ABSTRACT FROM AUTHOR]

Knowledge tracing aims to model the state of knowledge and ultimately predict the future performance of learners by describing exercises through the representation of concepts. However, in terms of the representation of concepts, the current research doesn’t model the influence of historical knowledge concepts on the temporal relationship of the current concepts, nor does it describe the role of the spatial relationship between various concepts in the exercise. In order to solve these problems, this paper proposed a knowledge tracing model characterized by temporal and spatial correlation fusion. First of all, based on the degree of temporal correlation between concepts, it modelled the temporal effect of historical concepts from current concepts. Secondly, it modelled the spatial interaction between several concepts contained in the exercise to obtain the representation of knowledge points containing temporal and spatial information through the graph attention network. Finally, it used the above representation of concepts to derive the representation of the exercises, and generated the current state of knowledge through the self-attention mechanism. In the experimental stage, this paper compared the performance of the proposed model with the five relevant knowledge tracing models on four real datasets. The results show that the proposed model has better performance. In particular, compared to the five comparative models on the ASSISTments2017 dataset, the AUC and ACC are improved by 1.7%～7.7% and 7.3%～12.1%, respectively. At the same time, the ablation experiment proves the effectiveness of modeling the temporal and spatial correlation between concepts, and the training process experiment shows that the proposed model has certain advantages in the representation of concepts and the modeling of their interaction relationships. The application examples can also show that the model has better practical results than other knowledge tracing models. [ABSTRACT FROM AUTHOR]

Spatial co-location pattern mining aims to discover the association between spatial features and has been an important research direction in spatial data mining. Spatial co-location pattern mining method based on column calculation (CPM-Col algorithm) avoids the most time-consuming operation of generating table instances and directly searches for participating instances. This method has become one of the most efficient approaches. However, backtracking search for participating instances remains a bottleneck, especially in dense datasets and long pattern mining. To accelerate the search for participating instances, this paper proposed two improvements to the CPM-Col algorithm with less extra computations. Firstly, the row instances found by CPM-Col algorithm were stored as partial table instances, for avoiding backtracking calculations of many instances. Secondly, after successfully finding a row instance, some instances of the first feature were obtained by the sub-clique reaction of the row instance. Based on these improvements, this paper proposed a co-location pattern mining method based on improved column calculation (CPM-iCol algorithm) and discussed complexity, correctness, and completeness. Experiments were conducted on synthetic and real datasets. Comparing to a classical algorithm join-less and CPM-Col, the CPM-iCol algorithm significantly reduces mining time and backtracking times. The results show that the proposed algorithm has better performance and scalability than CPM-Col algorithm, especially in dense datasets. [ABSTRACT FROM AUTHOR]

In order to solve the problem that it is difficult for the model to perceive implicit information due to the lack of external knowledge in rumor detection, which limits the ability of the model to mine deep information, this paper proposed knowledge graph based multi-feature fusion rumor detection (KGMRD) method. Firstly, for each event, it constructed posts and comments together into a text sequence and used a classifier to extract the emotional features. This paper constructed a knowledge graph based on text using ConceptNet and aggregated the entity representation in the knowledge graph with the semantic features of text using the attention mechanism, so as to obtain the enhanced semantic feature representation. Secondly, in terms of communication structure, for each event, this paper built its communication structure diagram based on the propagation and forwarding relationship of the post, and used DropEdge to prune the communication structure diagram, so as to obtain more effective communication structure characteristics. Finally, it fused the obtained features to get a new representation and compared seven models including SVM-RBF on three real datasets of Weibo, Twitter15 and Twitter16. The experimental results show that compared with the current baseline with the best effect, the KGMRD method has the best ACC on the Weibo dataset and improves the ACC by 1.1%, and there is a 2.2% improvement on Twitter15 and Twitter16 dataset in ACC. The experiment proves that the KGMRD method is reasonable and effective. [ABSTRACT FROM AUTHOR]

Floating car GPS data serves as the foundation for processing traffic information, with the rapid increase in the number of monitored vehicles, a massive amount of GPS data is generated, posing great challenges to map matching. To address the shortcomings of traditional matching methods in terms of matching efficiency and accuracy, this paper proposed a real time parallel map matching algorithm for massive GPS data that ensured both high matching accuracy and computational efficiency. This paper firstly reconstructed an efficient and accurate real-time map matching algorithm for streaming data by introducing a comprehensive weight factor that considered velocity and direction to enhance the offline map matching algorithm that relied on historical trajectories. Then, it introduced the Spark Streaming distributed computing framework to achieve real-time and parallel computation of the map matching algorithm, significantly improving the efficiency of real-time map matching. Experimental results demonstrate that the proposed algorithm achieves more than a 10% increase in matching accuracy compared to conventional topological matching algorithms on complex road sections, with an overall matching accuracy of over 95%. In terms of matching efficiency, it achieves approximately a fourfold improvement compared to an equivalent number of standalone servers. The experimental results show that the proposed algorithm achieves real-time map matching of 80 million GPS data points on a computing cluster composed of 11 machines, proving that the proposed algorithm can achieve real-time vehicle matching in urban areas. [ABSTRACT FROM AUTHOR]

Blockchain technology has great potentiality in the secure sharing of electronic health records. However, current solutions face issues such as large storage space and low consensus efficiency. This paper proposed a novel scheme based on blockchain and friend and relative nodes. Firstly, this paper adopted a distributed file system to store users’ complete electronic health records on offline servers, and constructed a set of user’s friend and relative nodes. Each user’s data was stored redundantly by its friend and relative nodes, and only the block’s header information was stored on the chain, reducing storage space. Then, this paper designed a data access mechanism based on multi-signature technology, using Shamir secret sharing mechanism to distribute user’s private keys to their relatives and friends. More than half of the relatives and friends could use their own private keys to reconstruct users’ private keys, solving data access problems in emergency situations. Finally, this paper proposed a credit based Byzantine fault-tolerant consensus mechanism, which used the top 10% nodes with credit values as the leader node set and utilized a random algorithm to generate the master node in the leader node set. And it improved consensus security. The experimental results show that compared with existing methods, the proposed scheme reduces the on-chain storage space by 1/7, improves data access efficiency by 15 times, and has higher consensus security while ensuring good latency and throughput. The proposed scheme can achieve secure and efficient sharing of electronic health records, providing a case for the application of blockchain in the medical field. [ABSTRACT FROM AUTHOR]

This paper investigated the issue of covert network attacks on video surveillance systems in light of their networking and intelligent development, which brought about new risks. The primary objective of this research was to explore numerous cases of covert network attacks and summarize the specific characteristics of such attacks targeting video surveillance systems. Additionally, this paper examined the unique advantages of honeypot technology in detecting network attack behaviors and identifying attack clues, and outlined the honeypot defense methods against covert attacks on video surveillance systems. Furthermore, considering the shortcomings in the visual scene deployment of video surveillance honeypots, this paper introduced a deep scene fabrication defense framework that combined generative Al models with video surveillance honeypots. Finally, it proposed the development direction of honeypot defense technology for video surveillance systems. [ABSTRACT FROM AUTHOR]

The wide application of deep learning techniques has strongly promoted the development of the medical image analysis field. Most deep learning methods usually assume that the training and test sets are independent and identically distributed. However, the assumption is problematic to guarantee when the model. Resulting in the dilemma of model performance degradation and poor scene generalization ability. Deep learning-based domain adaptation techniques are the mainstream methods for improving model migration ability, which aims to enable the model trained on one dataset to obtain better results on another dataset with no or only a small amount of labels. Due to the difficulties in sample acquisition and labelling, unique image properties and modal differences in medical images, it brings many practical challenges to domain adaptive technology. This paper firstly introduced the definition and primary challenges of the domain adaptation and then classified and summarized related algorithms in recent years from a technical point of view, compared and analyzed their advantages and disadvantages, and then introduced the medical image datasets commonly used in domain adaptation and related algorithm results in detail. Finally, this paper prospected the future research direction of domain adaptation for medical image analysis regarding development bottlenecks, technical means, and cross-cutting areas. [ABSTRACT FROM AUTHOR]

In the field of deep learning, solving problems often requires combining multiple modal information for reasoning and decision-making, among which visual and language information are two important modalities in the interaction process. In many application scenarios, processing multi-modal tasks often faces problems such as complex model architecture organization and inefficient training methods. Based on the above problems, this paper reviewed the representative achievements in the field of multimodal image text in the past five years. This paper first started from the mainstream multi-modal tasks and introduced related text and image multi-modal datasets and pre-training targets. Secondly, considering the visual language model based on Transformer and the feature extraction method, this paper analyzed from the perspectives of multi-modal organization architecture and cross-modal fusion methods, and summarized and compared the commonalities and differences of different processing strategies. Then it introduced the lightweight method of the model from data input, structural components and other aspects. Finally, it prospected the future research direction of multimodal methods based on image text. [ABSTRACT FROM AUTHOR]

The Badayun pattern composed of circular square and other symmetrical geometric figures originated the ancient concept of "round sky and square earth". The structure of "rice (米 )" in this pattern represents geographical orientation and the pattern contains the "nine palaces and eight diagrams" in traditional Chinese philosophy and culture and it is further developed under the influence of Neo-Confucianism in the Song Dynasty. As a model of the geometric patterns of Song brocade the Badayun pattern is deeply loved by the court and nobles because of its colorful pattern images rigorous and clear composition form complex but not chaotic color style and auspicious and healthy meaning and is widely used in painting and calligraphy mounting and brocade dress pattern design. Based on ancient fabric images and ancient literature records this paper sorted out and summarized the changing rules of the artistic characteristics of the Song brocade Badayun pattern analyzed the historical causes of the changes explored its deeper cultural implications and drew the three major conclusions. First from the Song Dynasty to the Qing Dynasty the evolution law of the artistic characteristics of the Song brocade Badayun pattern was mainly reflected in the skeletal framework from being simple to being complex the color conbination from being simple to being gorgeous and the decorative pattern from being single to being multiple. Second from the Song Dynasty to the Qing Dynasty the changes in the artistic characteristics of the Song brocade Badayun pattern were mainly influenced by a variety of factors such as the awareness of political rights the growth of economic development the development of cultural exchanges and the improvement of brocade skills. The consciousness of political power provided the necessary prerequisite for the spread of patterns the economic development provided the objective conditions for the spread of patterns the cultural exchange phenomenon provided the inspiration for the evolution of patterns and the improvement of brocade skills provided technical support for the performance of patterns. Third from the Song Dynasty to the Qing Dynasty the Song brocade Badayun pattern also expressed the ancient people's recognition of rational aesthetic order their desire for the auspiciousness and health and their pursuit of moral cultivation in both explicit and implicit ways. This paper systematically and deeply collects collates and analyzes the evolution law of the Song brocade Badayun pattern analyzes the cause of its evolution and cultural implication which is helpful to the inheritance and development of Song brocade patterns and provides reference for the innovative design of the Badayun pattern. With the change of dynasties and the development of the times the Badayun pattern no longer has the function of highlighting the user's status and conveying the value of honor but its meaning of auspiciousness and beauty and the significance of highlighting moral cultivation continue to this day and it has been loved by people and widely used in modern textile pattern design. [ABSTRACT FROM AUTHOR]

The human body dissipates heat rapidly at low temperatures and it faces the risk of freezing frostbite and even death if it fails to maintain the physiological thermal balance. It is an efficient way of promoting the thermal insulation of the garment to achieve the thermal balance of the human body by changing its opening design. Although many studies have been conducted on the impact of clothing including the style and pattern or the external temperature on heat transfer of clothing most of them focus on one single factor with the combined factors being rarely discussed in depth. This paper discussed the impact of different arrangements and combinations of three main opening designs of clothing including the front flap the cuff and the collar on thermal insulation performance of cold-proof through thermal manikin at various temperatures. The findings of this study are expected to provide significant instructions for consumers and quantitative reference for the opening design of cold-proof clothing. In the experiment the study selected a one-piece suit as the original garment to carry out different opening designs and obtained three types of single-opening clothing namely 2# clothing with a widened and thickened front fly 2 cm wider and 0. 4 cm thicker 3# clothing with tightened cuffs with a binding size of 16 cm and 4# clothing with a tightened collar with a binding size of 30 cm . Such designs are the three main opening designs of cold-proof clothing. The three single-opening designs of 2# - 4# were arranged and combined in order to accurately quantify the influence of each opening and combination design on the overall and local thermal resistance of clothing. Four kinds of multi-opening optimization designs were obtained 5# front fly widening and thickening + cuff tightening 6# front fly widening and thickening + collar tightening 7# cuff tightening + collar tightening and 8# front fly widening and thickening + cuff tightening + collar tightening. The study used a Newton thermal manikin to measure the thermal insulation of 34 separate segments including the total thermal insulation and the local thermal insulation of hand upper arm forearm upper chest lower chest abdomen shoulder upper back mid back and hip. On this basis in order to explore the influence of the temperature on the thermal performance of clothing from the perspective of thermal insulation mechanism four levels of temperatures were selected including 5 ℃ 0 ℃ - 5 ℃ and - 10 ℃. At the same time the software SPSS was used to statistically compare the total thermal resistance of 1# - 4# clothing and 5# - 8# clothing at 5 ℃. The local thermal resistance changes of single-opening and multi-opening garments were shown in bar graphs. Finally the change rates of the overall and local thermal resistance values of at different temperatures were analyzed. The results showed that both the opening design and the temperature have an impact on clothing insulation performance and the former serves as the most important factor followed by the second. Compared with single-opening design the multi-opening design of clothing plays a more important role in promoting the thermal insulation performance of clothing. The thermal resistance increase rate of 8# clothing can reach 7. 20% but the effect of opening design on the thermal insulation performance of clothing is weakened at lower temperatures. In contrast the 8# multi-opening design has a more obvious promoting effect on the improvement of clothing due to the formation of an enclosed environment at 5 ℃. The findings in this paper can provide objective data for the opening design of cold-proof clothing. In order to achieve the thermal function of winter clothing it is necessary to consider factors such as materials and the environment. At the same time the research results can also provide ideas for further analysis of the opening tightening quantity of cold-proof clothing. [ABSTRACT FROM AUTHOR]

Garment fit evaluation is one of the main bottlenecks in current fashion design and manufacturing. In the process of remote customization and online shopping the size of the clothes that does not fit has become the primary reason for users to return or exchange them which has seriously affected the intelligent upgrade of the clothing industry. Therefore how to judge the fit degree of a garment without actually trying it on is one of the main problems that needs to be solved urgently in the clothing industry. In previous studies garment fit was usually evaluated by some characteristic indexes such as ease allowance clothing wrinkle the spatial relationship between clothing and the human body and clothing pressure. However most of them have some problems such as the need to try on clothes and the complicated evaluation process which are not suitable for remote customization of clothing and online shopping. With the development of computer vision and machine learning technology a small number of scholars use 2D images to judge garment fit based on clothing wrinkle but only for specific garments and the generalization ability is weak. To solve the problem that garment fit cannot be discriminated in advance in the process of remote customization and online shopping this study took women' s suits as an example and put forward a method to discriminate the fitness of women's suits based on 2D human images. Firstly 2D images and 3D human body size of 462 young women aged 18 - 25 in northeast China were collected and a human body data set was established. Twenty-two samples were selected from this data set and virtual models were established for virtual try-on by using CLO3D software. According to the national clothing size standard of China 10 virtual women's suits with the same style and different sizes were made to establish the garment data set. Based on the principle of Kansei engineering the fitting evaluation labels of women' s suits namely tight fit and loose types were given by expert evaluation method combined with virtual fitting. Then a method to discriminate the fit of women' s suits by using garment features and 2D human image features was proposed. As for the garment features GFs the bust girth and length characteristics of women's suits the features of 2D human body image including the key point distance features DFs and overall features OFs were extracted. The specific extraction method is as follows. Firstly the 2D human body image was preprocessed and normalized and the human body contour was extracted by Canny edge detector and the five DFs in the 2D human body image were obtained namely the distance of chest thickness key points distance waist thickness key points distance hip thickness key points distance waist width key points distance and hip breadth key points distance. Then three OFs of the 2D human body image were extracted namely the body height pixel value feature H the feature of the projected unit area ρ and the feature of the projected area ratio of the front and side of the human body C. Finally the Bayesian classifier was used to establish the garment fit prediction model and the Fisher linear discriminant function was used to establish the women' s suit fit discriminant equation. In this paper computer vision technology was used to extract the feature indexes of garment fit evaluation and a machine learning algorithm was combined to realize the women's suit fit discrimination based on 2D human body images. Experimental results indicate that the garment features proposed in this paper and the 2D human body image features based on computer vision technology can be used to predict the fit of women' s suits and the discriminant model of women' s suits based on the Bayesian algorithm has achieved good discriminant accuracy and the cross-validation discriminant accuracy rate can reach 84. 8% so the model is valid. The women' s suit fit discrimination model based on 2D human image feature learning provides an effective and feasible method for garment fit in fashion design production manufacturing and online shopping. This method provides a theoretical basis for the quantitative evaluation of garment fit and is beneficial to the recommendation of clothing size and the improvement of patterns in clothing customization enterprises and online shopping. [ABSTRACT FROM AUTHOR]

Traditional Chinese clothing patterns are an important part of excellent cultural heritage of China with unique visual effects and artistic charm providing abundant materials for modern design. They are widely used in the field of modern design and decoration and are an important symbol of the nationalization of Chinese design. Over the past 20 years scholars have conducted increasing research on traditional clothing patterns and explored the integration of traditional clothing patterns with modern design languages from different perspectives and different disciplinary backgrounds as well as the digital simulation and reconstruction of traditional clothing patterns. At present there is a lack of comprehensive quantitative analysis to objectively evaluate relevant research literature on traditional clothing pattern design transformation and there is an urgent need to grasp the theoretical trends in this field as a whole. This paper selected 425 journal articles on traditional clothing pattern design transformation research from CNKI in the past 20 years. Based on the CiteSpace software and content analysis method the research laws of traditional clothing pattern design transformation in China were sorted and analyzed from the dimensions of knowledge production context knowledge production subject knowledge foundation keyword co-occurrence and timeline. This paper adopted a dual perspective of bibliometrics and content analysis to clarify the research laws of traditional clothing pattern design transformation from the dimensions of time and space in order to provide reference for theoretical deepening application exploration and sustainable development in this field. Three major conclusions were drawn. First from the basic characteristics of the literature the number of publications on traditional clothing pattern design transformation has increased rapidly since 2001. Scholars have paid increasing attention to related research in the field of traditional clothing pattern design transformation. More scholars and research institutions have explored the traditional clothing pattern design transformation to varying degrees from different disciplinary backgrounds and accumulated a certain number of research results. However most of the scholars conduct independent research indicating a lack of collaborative research on the traditional clothing pattern design transformation. Therefore it is necessary to form more academic research teams and core research scholar groups. Second from the perspective of hot research topics the research on traditional clothing pattern design transformation has formed three research hotspots materialized expression of auspicious culture in traditional clothing pattern design transformation innovation of methods for extracting traditional clothing patterns and interdisciplinary integration driving the innovative development of traditional clothing pattern design transformation. Third from the perspective of research evolution the evolution of traditional clothing pattern design transformation can be roughly divided into three stages 2001 - 2008 2009 - 2016 and 2017 - 2022. The integration of multiple disciplines drives the continuous innovation of modern design and forms new development trends. For example the interactive design of traditional clothing patterns provides users with a better user experience traditional clothing pattern service design based on user emotional experience has become an emerging research direction the extraction and innovation of "Chinese elements" in traditional clothing patterns reflect cultural confidence in design transformation the traditional clothing pattern design transformation has gone through a change from commonality to individual psychological needs with design shifting from practicality to spirituality. [ABSTRACT FROM AUTHOR]

Taking Four Girls Mountain Town in Aba Tibetan and Qiang Autonomous Prefecture, Sichuan Province as an example, this paper explored the impacts of mountain sports tourism's development and exploitation from the perspective of local residents'perception, combining related research indicators of domestic and foreign scholars. SPSS26.0 and SmartPLS were used to analyze the reliability and validity of data samples. Through the construction of a structural variance model, the paper analyzed the perception difference of residents on the impact of mountain sports tourism and found out that the development and exploitation of mountain sports tourism in Four Girls Mountain has certain positive and negative effects on the economy, social culture and ecological environment of the residents in the area. The final part of the paper suggests establishing a reasonable distribution mechanism of interest among residents of outdoor tourist attractions, developing a green ecological environment of mountain sports tourism under the goal of carbon neutrality, and updating the talent training and management mode of mountain sports tourism. [ABSTRACT FROM AUTHOR]

Faced with rapid changes in the external environment, the operation of physical bookstores is facing crises. Metaverse is the product of virtual reality integration and it provides a new idea for the transformation and upgrading of bookstores. Based on the analysis of the current situation of bookstore operation, this paper proposes to build the new scenario, a Metaverse bookstore, from the perspective theory of media scene. The concept of establishing a Metaverse bookstore in this paper explores the dynamics between individuals, individuals and their surroundings, as well as individuals and objects. The Metaverse bookstore is in line with the trend of people's experience consumption and visual consumption. The immersive reading experience brought by Metaverse technology enables the bookstore to transcend time and space boundaries and meet the needs of users for personalized reading scenes. In the final part of the paper, the development strategy is proposed to provide a reference for future application research on Metaverse Bookstore. [ABSTRACT FROM AUTHOR]

Objectives: Individual driving destination prediction has important value in location-based services such as personalized services recommendation and intelligent transportation. However, most of the existing deep learning methods construct travel features on the basis of densely-sampled trajectory points, which generate data redundancy but only achieve limited information gain, and in turn introduce negative impacts on model training. Road intersection sequence can simplify the expression of driving trajectories restricted on the roads, and reduce the model training cost. Meanwhile, transfer preference between intersections and current movement mode imply the spatiotemporal correlation between road intersections and destinations, and are capable to represent individual travel intention to some extent, but few researches have applied them to destination prediction. Methods: This paper proposes a novel individual driving destination prediction method that takes intersection transfer preference (ITP) and current movement mode (CMM) into account, named ITPCMM. First, it constructs input features in units of each intersection, and adopts graph attention network to learn the individual-level transfer coefficients between intersections in different time slots. Then, it uses long short-term memory (LSTM) to capture the long-term dependence of transfer preferences. Second, ITP-CMM constructs time cyclic encoding features and driving features to learn current move mode by using two-layered LSTM. Third, intersection transfer preferences and current move mode are fused and weighted through feature intersection and attention mechanisms respectively. And the stacked residual networks are introduced to output prediction results. Results and Conclusions: Based on the trajectory data of twelve private car drivers in Shenzhen City, China for the whole year of 2019, this paper has conducted a group of experiments to verify the feasibility of the proposed method ITP-CMM. We verify the effectiveness of the proposed method by carrying out ablation experiments and comparing the prediction accuracy and stability of ITP-CMM with four baselines, including hidden Markov model, LSTM, distance neighboring dependencies model and attentionaware LSTM for real-time driving destination prediction by considering location semantics and location importance trajectory points. Besides, we demonstrate the value of transfer preference in capturing the spatial correlation between intersections through visual analytics, and explore the impact of the number of transfer intersections on the prediction accuracy. [ABSTRACT FROM AUTHOR]

[Objective This study reflects certain ecological development concept in the field of scientific journals, so as to promote the quality and influence of tropical agricultural scientific journals in China with ecological ideas. Method Based on the niche theory, we analyzed the present situation of Chinese journal of tropical agricultural science and technology from three aspects of column setting, authors' units and fund paper ratio based on niche overlapping theory. Some ecological strategies were put forward from three aspects of space niche, nutrition niche and reality niche. Result] The authors' units were mainly colleges and scientific research institutions. National funding funds accounted for a large number of papers; there was great competition in the resources of authors and readers. Conclusion People should build suitable space niche, strengthen nutrition niche and explore reality niche in order to avoid homogenization of tropical journals and to form a development idea of scientific journals in China. [ABSTRACT FROM AUTHOR]

We searched the literature on the Chinese literature and domestic institutions, and visualized 670 Chinese and English literature articles on the Hermetia illucens published from 2000 to 2023 using CiteSpace. According to the analysis of the number of papers published, publication time, authors, research institutions and keywords, the results showed that the publication time of the papers related to the Hermetia illucens was concentrated in the period of 2016—2022. There are many groups of domestic institutions cooperating, mainly concentrated in the northwest region, the analysis of key words mainly focused on eight aspects: antibacterial peptides, resource utilization, serum biochemical index, larva of A. melanopteris, pteropteris SPP., larva, wavelength and industrial breeding. Based on the above analysis results, the research direction of the Hermetia illucens in the future will focus on three aspects: the promotion and application of antibacterial peptides, the industrialization of the resources of the Hermetia illucens and the development and application of the larval feed of the Hermetia illucens. [ABSTRACT FROM AUTHOR]

Objective To analyze the situatiion of talents and scientific research in 39 CDCs in Chongqing, and to provide reference for cultivating scientific research talents, improving scientific research capacity and management level. Methods From 2018 to 2022, the data of the staff of 39 district and county Centers for Disease Control and Prevention in Chongqing were collected, including the basic situation, statistics of published papers, research topics in progress, scientific research management system and ethics construction, and so on. Results From 2018 to 2022, the number of professional and technical personnel for Centers for Disease Control and Prevention in urban and county areas of Chongqing increased from 1 821 to 2 602, an increase of 42.89%, the proportion of undergraduate students increased from 64.03% to 68.49%, and the number of master students increased from 6.81% to 12.53%. Specialty and below decreased from 29.10% to 18.79% (χ²=111.022, P <0.001). There were 888 papers in Chinese, 23.76% in core journals, 14 in English, 85.71% in SCI, and 0.09 papers published per capita per year. A total of 14 provincial and ministerial projects have been established as the leading unit, 10 of which will be in 2020, and 172 of which will be at the bureau level, with an annual average of 34.4. Only 10 districts and counties have established a relatively complete scientific research management system, of which only seven districts and counties have carried out ethical review projects. Conclusion The proportion of people with bachelor degree or above district and county CDC in Chongqing increased, and the number of papers published increased, but the quantity and quality of papers still need to be improved, and there are few independent projects. The development of disease control should pay attention to the introduction and training of talents, create a scientific research atmosphere, improve the scientific research management system and incentive measures. [ABSTRACT FROM AUTHOR]

The cultivation of innovative talents in agriculture and forestry universities is related to the realization of the national innovation driven development strategy and the service of the strategy of rural vitalization. Therefore, agriculture and forestry universities should carry out the education of innovation and entrepreneurship for students. The paper analyzes the current situation of the innovation and entrepreneurship education of agriculture and forestry universities based on the components of innovation and entrepreneurship education. This paper puts forward some policies and suggestions to promote the innovation and entrepreneurship education of students in agricultural and forestry colleges and universities, including of guiding students to set up innovative and entrepreneurial consciousness, building a mechanism of integrating professional education with innovative and entrepreneurial education, paying attention to the construction of the campus cultural atmosphere of innovative and entrepreneurial education, and establishing the cooperative education mode mechanism of a university with the government, industry and enterprise, etc. [ABSTRACT FROM AUTHOR]

Macrophages have strong plasticity and heterogeneity, and can undergo functional transformation in response to different signal stimuli, such as classical activation of M1 type (M1 type polarization) and selective activation of M2 type (M2 type polarization). The pathways of macrophage M1/M2 polarization are quite extensive, involving nuclear factor-κB (NF-κB)/mitogenactivated protein kinase (MAPK) signaling pathway, interleukin-4 (IL-4)/signal transduction and activator of transcription 6 (STAT6) signaling pathway, Notch signaling pathway, Wnt/β-catenin signaling pathway, etc. At the same time, M1/M2 polarization of macrophages is also regulated by exosomes, metabolites, non-coding RNA, electrical stimulation, probiotics, etc., and its imbalance is closely related to the occurrence and development of different types of liver disease. In this paper, the mechanism of its polarization was reviewed, and it was found that M1 polarization of macrophages played a promoting role in the process of liver tissue injury, inflammation and fibrosis, while M2 polarization of macrophages played the opposite role. Among them, hepatocellular carcinoma, as the advanced stage of chronic liver disease, was characterized by increased M2 polarization and impaired M1 polarization of macrophages. Therefore, this paper pays attention to the role of M1/M2 polarization of macrophages in different types of liver diseases, in order to better establish the targeted therapy of macrophage subsets. [ABSTRACT FROM AUTHOR]

[Objective]. The aims of this article are to intuitively grasp the progress and hotspots in the field of research of gully erosion in the northeast of China black soil region, advance the development of research in gully erosion in the black soil region of northeast China. [Methods] 245 papers in CNKI and Web of Science databases were used to create a knowledge map of gully erosion in the black soil region of northeast using the bibliometric method and CiteSpace software. [Results] (1) Research on gully erosion in black soil area started late, and the number of published papers has increased significantly in the past 10 years, but the results published in international journals are few, accounting for only 26%. (2) The research institutions in this field mainly distribute in northeastern China, of which several institutions include Songliao Basin Committee of Ministry of Water Resources, Beijing Normal University, Northeast Institute of Geography and Agroecology of Chinese Academy of Sciences, Northeast Agricultural University, and Shenyang Agricultural University have made the outstanding contributions and shown the great influence in the field; Prof. Zhang Shuwen is the scholar with the most publications in Chinese, and Prof. Liu Baoyuan and Wu Yongqiu are the scholars with the most publications in English in this field. (3) The co-occurrence of keywords between the published literatures indicates that the current focus of attention on gully erosion in the black soil area of northeast China is mainly on the development characteristics, influencing factors and prevention and control measures of gully erosion. [Conclusion] The comprehensive research framework and a full understanding on gully erosion in the black soil region of northeastern China have not yet been established. In future research, there is a need to further emphasize the study of the formation and development processes and mechanisms of gully erosion in the black soil region of Northeastern China, and to conduct in-depth analyses of the influences of geological, topographical, hydrological, and human activities, among other factors. [ABSTRACT FROM AUTHOR]

[Objective] This paper reveals the spatiotemporal changes of vegetation in different ecosystems in Shaanxi Province, clarifies the influence mechanisms of different climatic factors and their interactions on the changes of vegetation, and provides a theoretical basis for regional ecological environmental protection. [Methods] Based on MODIS NDVI and annual average high temperature, annual average low temperature, annual average temperature, and annual total precipitation data, this paper analyzed the spatiotemporal variation characteristics of vegetation NDVI in each landscape partition from 2000 to 2020 by Theil-Sen Median trend, partial correlation, and geodetector, and the internal correlations and response mechanisms of vegetation NDVI changes with precipitation and temperature were investigated by combining variable separation. [Results] Vegetation NDVI in Shaanxi fluctuated and increased from 2000 to 2020 at a rate of 5.9%/per decade, among which the rate of vegetation NDVI decreased in the different landscape in the order: Northern Shaanxi＞Guanzhong＞Southern Shaanxi.The multi-year vegetation NDVI value of the province was 0.71, with high level in the south and low level in the north. Vegetation NDVI in 67% of the regions showed a significantly improved trend during the study period, and the proportion in different landscape decreased in the order: Northern Shaanxi＞Southern Shaanxi＞Guanzhong. The climate factors fluctuated over time in Shaanxi from 2000 to 2020, the change rates in different landscape decreased in the order: Shaanxi South＞Guanzhong ＞Shaanbei. The spatial trends of temperature factors showed the decrease in annual average high temperature, the increase in annual average low temperature, and the decrease in annual average temperature, and the increase in precipitation. The overall vegetation NDVI of Shaanxi and each sub-district from 2000 to 2020 was negatively correlated with annual average high temperature and positively correlated with annual average low temperature, annual average temperature, and annual total precipitation. The contribution of annual total precipitation was greatest in the province and northern Shaanxi, and the contribution of annual average high temperature was greatest in Guanzhong and southern Shaanxi. The interaction of annual average high temperature and total annual precipitation had the strongest influence on vegetation NDVI in the province, northern Shaanxi and southern Shaanxi, and the interaction between annual mean temperature and total annual precipitation had the strongest effect on vegetation NDVI in Guanzhong. The interaction of of precipitation with maximum and annual average temperatures significantly influenced the vegetation NDVI changes. [Conclusion] The vegetation in Shaanxi and the sub-regions had became better overall during the study period. The vegetation in each sub-region responded differently to climate, and the contribution of each factor and its interactions also differed. [ABSTRACT FROM AUTHOR]

Aiming at the problems of small chaotic space and weak chaotic ability of existing chaotic mapping models, a new three-dimensional chaotic mapping model is designed by coupling two-dimensional Henon chaotic mapping model and Sine chaotic mapping model. Aiming at the problem that the security of encryption system will be reduced if the key is reused, this paper designs a new key generation method using Chebyshev mapping and plaintext image. Using the 3D chaotic mapping and key generation method designed in this paper, a color image encryption method is proposed. The results show that the method can encrypt images safely and effectively and protect the security of image information. [ABSTRACT FROM AUTHOR]

In recent years, there has been rapid development in intelligent aquaculture and fisheries resource conservation, leading to an increased demand for fish tracking technologies. Traditional fish tracking methods rely heavily on visual observation and tag tracking, which suffer from low efficiency, limited applicability, and low accuracy, hindering their widespread adoption. With the rapid advancement of deep learning in computer vision, deep learning-based fish-tracking technologies can provide accurate, objective, scalable, and automated tracking methods. Firstly, this paper introduces the tracking objects and four deep learning-based fish tracking methods:semantic segmentation, instance segmentation, object detection, and object classification. Secondly, it describes how fish tracking technologies capture fish trajectories, postures, fish quantities, and fish lengths, which are important tracking information for fish targets. Furthermore, the application of deep learning-based fish tracking technologies in fish diseases, fish feeding behavior, and fish health status is discussed. The paper also explores the main challenges of current deep learning-based fish tracking technologies, including low contrast and texture blurring, image color distortion, occlusion, and deformation, along with some corresponding solutions. Finally, the paper concludes and provides an outlook on the future development of deep learningbased fish-tracking technologies. It suggests that deep learning-based fish tracking technologies offer higher accuracy and objectivity, providing more solutions for practical applications in different scenarios. This technology is expected to play a more significant role in aquaculture management, fish scientific research, and marine environment conservation, offering more data and support to relevant fields. [ABSTRACT FROM AUTHOR]

Seedling emergence is a crucial stage in plant production as it greatly impacts or even determines the final yield. For dicotyledonous plants, the growth of the hypocotyl and the development of the apical hook play a significant role in seedling emergence. Hypocotyl growth and apical hook development are a continuously dynamic process and are important guarantees for seedling emergence. The elongation of the hypocotyls provides the necessary force for seedlings to penetrate the soil, while the apical hook protects the delicate apical meristems and cotyledons from the damages during the soil topping process. Focusing on the development of the hypocotyl and apical hook, this paper summarized the molecular mechanisms regulating hypocotyl elongation and thickening by arranging themselves through the cytoskeleton in dicotyledonous plants, as well as the growth mechanisms of cellular differentiation involved in apical hook formation, maintenance, and unfolding. This paper examined the synergistic effects and mechanisms of major environmental factors such as light and temperature, as well as plant endogenous hormones, on hypocotyl and apical hook development. Furthermore, the paper explored agricultural practices, including optimizing environmental factors through sowing methods and seedling thinning to enhance hypocotyl growth and apical hook development, which in turn improves seedling emergence rate and stand establishment rate. Lastly, the paper provided suggestions for further research on the molecular mechanisms regulating hypocotyl and apical hook development, along with insights into the adaptation mechanism of apical hook and hypocotyl development to adversity, as well as for achieving effective control of seedling emergence and stand establishment in dicotyledonous plants. This paper serves as a valuable reference for a deeper understanding of the seedling emergence mechanism in dicotyledonous plants and innovative plant seeding and seedling preservation techniques. [ABSTRACT FROM AUTHOR]

When man⁃made or natural disasters occur suddenly, the rapid deployment of search and rescue (SAR) robots is crucial for saving lives. To accomplish rescue tasks, SAR robots need to autonomously plan paths in continuously dynamic and unknown environments to reach the rescue target locations. This paper proposes a sensor configuration scheme for SAR robots, applying a Q-learning algorithm based on Q-table and neural networks to achieve autonomous control of SAR robots. It addresses the challenge of path planning in unknown environments, specifically how to avoid static and dynamic obstacles. Balancing the exploration and exploitation during the training process is one of the challenges in reinforcement learning. This paper introduces a mixed optimization method for dynamically selecting search strategies, building upon greedy search and Boltzmann search. Simulations are conducted using MATLAB, and the results indicate that the proposed method is feasible and effective. SAR robots equipped with the sensor configuration can effectively respond to environmental changes, reaching target locations while successfully avoiding both static and dynamic obstacles. [ABSTRACT FROM AUTHOR]

In response to the broadband stealth challenges faced by armed helicopters, this paper proposes a method that utilizes ray-tracing and inverse synthetic aperture radar (ISAR) imaging to pinpoint the locations of strong scattering sources of the helicopter. The paper introduces a conceptual design that integrates electromagnetic metamaterials and magnetic materials into the strong scattering source regions of the helicopter. The stealth effects are calculated and analyzed after incorporating two types of stealth materials onto the helicopter. The paper firstly analyzes the principles of equivalent medium theory, ray-tracing and ISAR imaging. Subsequently, through the calculations of ray-tracing and ISAR imaging, the locations of strong scattering source can be captured accurately and intuitively. Finally, the reflection coefficients of the two types of stealth materials are presented and mono-station radar cross section (RCS) changes are analyzed after materials are loaded on the helicopter. The calculation results show that the two different types of stealth materials can achieve the RCS reduction in the special angular domain after covering part of the helicopter’s strong scattering source, providing a reference for the integration design of stealth materials, helicopter skins and main-rotors. [ABSTRACT FROM AUTHOR]

This paper explores the political ecology of death and emotion through the secularized funeral rituals reform in Singapore. Although scholars have recently acknowledged the roles of emotion in shaping environmental politics, religion and death as socio-affective forces have not been substantively engaged with by political ecologists. In this paper, we argue that death is inherently both a spiritual and ecological phenomenon, as it addresses not only the spiritual landscape of how people see the natural world, but also the affective tensions and struggles over what counts as a "proper" form of burial in relation to religion and nature. We first investigate the way that the Singapore state utilizes ecological discourses to secularize Chinese death rituals, such that the death can be separated from the transcendent spheres and incorporated into the environmental biopolitics. Second, we examine how Chinese Singaporeans negotiate the emotional tensions in relation to the secularized rituals and especially the sea burials. This paper brings the issue of death into dialogue with political ecology and reflects on its emotional capacity in shaping environmental politics. [ABSTRACT FROM AUTHOR]

Specific path dependence occurs in the research of cross-border economic cooperation. Most of the existing studies are based on the current situation of collaboration and a certain period, while the studies on medium and long periods are relatively few. This paper took the process of international cooperation and development of the Tumen River sub-region as an example, constructed an analysis framework of the evolution mechanism of cross-border economic regional cooperation based on geography multi-scale thought, and discussed the essential characteristics and changing factors for international collaboration of Tumen River sub-region in each historical stage. The results show that: The international cooperation of the Tumen River sub-region has gone through four stages in the past 30 years: the development stage (1984-1992), the development boom period (1993-1996), the slowdown period (1997-2004) and the development restart period (2005-present). Besides, the cross-border economic cooperation in each stage of Tumen River sub-regional international cooperation begins based on the last round of material practice space, which has apparent historical inheritance and policy innovation in different stages. The impact is on cross-border regional infrastructure construction and urbanization development. The role of the United Nations Development Programme (UNDP) in sub-regional development is weakening, the leading role at the national level beefs up, the participation of provinces and local governments is increasing, and their integration with the regional development strategy is becoming increasingly close in the whole process under the general trend that political consultation and economic cooperation have become the global geopolitical environment changes. This paper helps in solvig the dilemma of international cooperation in the Tumen River subregion and enriching the theoretical research on cross-border cooperation of human geography. [ABSTRACT FROM AUTHOR]

摘要 识别关键蛋白质对疾病治疗、药物设计等领域有重要作用。本文首先采用5种节点重要性排序算法,对4种酵母菌PPI网络进行关键蛋白质识别,并通过分析不同网络之间共有的关键蛋白质,构建了关键蛋白质子网。再通过杰卡德相似度指标,筛选出子网中拓扑特征相似的关键蛋白质对,发现4种网络中存在Gavin-EPG 1、Gavin-EPG 2、Babu-EPG 1、Babu-EPG 2、LCMS-EPG、MALDI-EPG共6个核心蛋白质组。尽管它们大都是核糖体蛋白质,然而不同的酵母菌PPI网络中核心蛋白质组中蛋白质的组成差异很大。本文所发现的关键蛋白质以及核心蛋白质组对进一步研究核糖体上蛋白质如何相互作用影响肽链的合成以及折叠提供了重要的理论参考。 Abstract Identifying essential proteins plays a significant role in fields such as disease treatment and drug design. In this paper, we initially employed five node importance ranking algorithms to identify essential proteins in four yeast protein-protein interaction (PPI) networks. By analyzing the common essential proteins among different networks, we constructed a subnetwork of essential proteins. Subsequently, using the Jaccard index, we filtered out pairs of essential proteins within the subnetwork that exhibited similar topological characteristics. This analysis revealed the presence of six core protein groups, namely Gavin-EPG 1, Gavin-EPG 2, Babu-EPG 1, Babu-EPG 2, LCMS-EPG, and MALDI-EPG, across the four networks. Although they are predominantly ribosomal proteins, the composition of proteins within the core protein groups varies significantly among the different yeast PPI networks. The essential proteins and core protein groups identified in this paper provide important theoretical references for further research on how protein interactions on the ribosome affect peptide chain synthesis and folding. [ABSTRACT FROM AUTHOR]

This paper delves into the synthesis strategies of molybdenum disulfide (MoS2) nanomaterials and their prospective applications in the fields of energy conversion and storage. Through a comprehensive analysis of various synthesis methods, including solvothermal and sol-gel processes, the specific impacts of these methods on the morphology and properties of MoS2 nanostructures are revealed. The study indicates that MoS2 nanomaterials with optimized electronic properties and surface activity can be fabricated by precisely controlling the synthesis conditions. These materials demonstrate exceptional performance in applications such as lithium-ion batteries and photodetectors, especially in enhancing battery charge-discharge cycle stability and improving photoelectric conversion efficiency. The paper further discusses the challenges faced in the development of MoS2 applications, particularly in terms of the scalability of material synthesis and consistency of performance. Lastly, the article presents a vision for future research directions, emphasizing the potential to broaden the application of MoS2 in high-performance energy devices through innovative synthesis strategies and material structure optimization. [ABSTRACT FROM AUTHOR]