Objective: To systematically review the domestic research literature on Su Xiao Jiu Xin Wan, construct a knowledge map using the CiteSpace visualization analysis tool, and analyze its research hotspots, development trajectory, and research trends. Methods: A comprehensive search of Chinese journal articles in the China National Knowledge Infrastructure (CNKI) database up to August 30, 2024, was conducted. Bibliometric methods were employed, and CiteSpace 6.2.R4 software was used to visually present and multidimensionally analyze core elements such as author collaboration networks, institutional distribution characteristics, and keyword cooccurrence relationships. Results: A total of 320 articles were included. At the author level, scholars such as Xie Yanming and Wang Xiaolong formed the core research force and established a stable collaborative network. The institutional distribution showed that medical colleges and their affiliated hospitals formed a closely-knit research community, with significant synergistic effects between traditional Chinese medicine research institutions and comprehensive universities. However, crossregional cooperation still needs to be further expanded. Keyword co-occurrence analysis identified nine cluster groups and extracted ten high-burst terms, among which endothelin-1, metabolomics, and emergency care have shown significant research interest in the past five years. Conclusion: The clinical application of Su Xiao Jiu Xin Wan in acute cardiovascular diseases remains the core research direction. The in-depth exploration of its multi-target mechanism of action may become a key breakthrough in future academic research.

Objective: By comparing the medical cases of the renowned traditional Chinese medicine (TCM) practitioner Yu Ying-ao with the original patterns of primary epilepsy in ancient medical records, this study aims to explore reference pathways for the inheritance and innovation of the experiences of renowned TCM practitioners. Method: The Jaccard similarity comparison method is utilized for multi-dimensional comparison and analysis. This involves comparing the associations between syndromes and medications, treatment principles, collections of Chinese medicines, categorization of Chinese medicine effects, and similarities and differences in meridian tropisms in the medical cases of Yu Ying-ao with those of ancient primary epilepsy treatments. Result: In terms of treatment, Yu Ying-ao inherited the basic principle of “resolving phlegm and calming” in ancient medical records, the overall approach to treatment should focus on suppressing seizures and stopping epilepsy, as well as transforming phlegm and unblocking collaterals. The specific treatment varies depending on the condition, with options such as calming the spirit, strengthening the spleen, adjusting the liver, moisturizing the intestines, nvigorating spleen- stomach, and replenishing qi. In terms of core TCM formulas, a comparison with ancient medical records reveals that the essential TCM combinations for the syndrome of phlegm- heat disturbing the spirit, as identified by Yu Ying-ao, are more refined. Both formulas include (Dannanxing), (Baifu), (Yujin), (Danshen), And (Zhuru). In terms of the scope of medication, the frequently used drugs in ancient medical records are mostly those that are highly used in clinical practice by Yu Ying-ao. In terms of efficacy, there has been a high degree of continuity, with both ancient and modern times valuing the use of phlegm- eliminating, heat- clearing, calming, qi regulating, and tonifying vacuity medications. However, Yu Ying-ao tends to emphasize the use of Activating blood stasis and suppressing liver- yang medications in his clinical practice. From the perspective of TCM meridian tropism, ancient medical records most frequently mentioned lung meridian as the primary meridian for TCM prescriptions, followed by spleen, heart, and liver meridians. In the medical cases of Yu Ying-ao, liver meridian was the most frequently mentioned as the meridian for TCM prescriptions, followed by lung, heart, and spleen meridians. Conclusion: Through multidimensional comparative analysis of the composition of core TCM medicines, treatment principles and methods, collections of TCM medicines, categorization of TCM medicine effects, and meridian tropism, reference pathways can be provided for the inheritance and innovation of experienced TCM practitioners.

Objective To provide theoretical basis and data support for the treatment of Xiongbi by analyzing the compatibility and application rules of treating Xiongbi in traditional Chinese medicines (TCMs) based on data mining. Methods Chinese herbal formulas for Xiongbi were searched in the "Chinese formula database" and collected. The usage frequency, efficacy category, and nature and flavour attribution of each medicine in the prescriptions were statistically analyzed. The association rules and clustering analysis were conducted for those Chinese medicines with a usage frequency above 10% by using the IBM SPSS Modeler 18.0 and SPSS Statistics 27 data-processing software. Results A total of 455 prescriptions for Xiongbi in TCM classics were obtained in this study, involving 324 flavors of Chinese medicines, 15 of them had a frequency of use above 10%. The top three medicine ranked according to the frequency were Rougui (170 times), Gancao (128 times), and Danggui (121 times).The efficacy of the drug is based on dispersing cold and relieving pain, tonifying fire to help Yang, and moistening the bowels to relieve constipation;In addition, our results indicated that the main medicine treating Xiongbi belongs to the mild on medicinal property, which were pungent taste and entering the spleen meridian. Association rule analysis showed that Rougui was the core medicine, and the compatibility of "Ganjiang, Rougui" was the core drug pair of medicines for the treatment of Xiongbi. Three potential new prescriptions were obtained from the cluster analysis, each reflecting a different therapeutic idea. Conclusion Rougui was the core medicine in the Xiongbi treatment, the core drug pair of medicines was "Ganjiang, Rougui". Accordingly, Tongyang Sanjie, Zaoshihuatan and Xinpitongzhi are the core ideas of Chinese medicine in treating Xiongbi.

Objective: By comparing the medical records of the famous doctor Yan Xiaocheng with the diagnosis and treatment patterns of ancient epilepsy medical records, this paper explores the discovery model in the process of collating the experience of the famous traditional Chinese medicine doctor. Method: The Jaccard similarity comparison method was used for multi-dimensional comparative analysis to compare the medical records of Yan Xiaocheng with the ancient medical records in terms of syndrome-drug association, treatment principles and methods, Chinese medicine collections, drug efficacy classification, and drug meridians.Result: In terms of treatment, Yan Xiaocheng inherited the basic principle of "resolving phlegm, calming the liver and calming the wind" in ancient medical records, and paid more attention to calming the mind and tranquilizing the nerves in clinical practice. In terms of the range of medication, the high-frequency medications in ancient medical records are also the high-frequency medications used in Yan Xiaocheng's clinical practice. In terms of the meridians of medicine, the most frequent meridian of medicine in ancient medical records is the lung meridian. The highest meridian for Yan Xiaocheng's medicine is the liver meridian. In terms of efficacy, both ancient and modern times have emphasized the use of expectorant medicine, heat-clearing medicine and tranquilizers, but Yan Xiaocheng clinical more emphasis on the use of wind-stopping and spasmodic medicine, diaphoretic medicine and resuscitation-inducing medicine. Conclusion: By conducting multi-dimensional comparative analysis of syndrome-medicine associations, treatment principles and methods, Chinese medicine collections, medicine efficacy classifications, and drug meridians, we can provide an effective path for the inheritance and innovation of the experience of famous traditional Chinese medicine practitioners.

Objective Using literature data mining methods, we analyzed the frequency of medication, combinations of drugs, and so on in the treatment of goiter disease with ancient classic prescriptions. We aimed to uncover the core combinations and new prescriptions for treating goiter; s We searched the "Ancient Classic Prescription Database" for literature related to the treatment of goiter, selected the prescriptions for treating goiter, entered them into the medical case cloud platform of ancient and modern times, and used rule analysis, cluster analysis, and other data mining methods to analyze the rules of prescription combination. Results The study finally included 145 prescriptions. The results of drug frequency statistics showed that the use frequency of kelp, seaweed, and Pinellia was relatively high. The analysis of Chinese medicine properties revealed that cold and warm medicines were used frequently, as were bitter, pungent, and salty medicines. Medicines entering the stomach, liver, and kidney meridians were used the most. The results of association rule analysis and cluster analysis revealed the combination relationship and classification of Chinese medicines. Complex network analysis identified the core prescription composition for treating goiter in ancient classic prescriptions, including kelp, seaweed, and Pinellia. Conclusion: This study analyzed the treatment of goiter with ancient classic prescriptions through data mining and found that kelp, seaweed, and Pinellia might be the core combination for treating goiter. The research results can provide a reference for the clinical practice of traditional Chinese medicine in treating goiter.

Objective:To explore and analyze the medication rule of diagnosis and treatment of primary epilepsy in ancient medical cases, hoping to provide reference for the clinical treatment of primary epilepsy. Methods: To excavate and analyze the ancient medical cases of primary epilepsy, extracted the traditional Chinese medicine(TCM) diagnosis and treatment data in the medical cases, standardized the obtained TCM diagnosis and treatment data, and used the data mining function integrated by the ancient and modern medical case cloud platform V2.3.5 to carry out frequency statistics, cluster analysis, association analysis and complex network analysis on the diagnosis and treatment data, the common medicines used by ancient medical cases of primary epilepsy, properties and classifications of commonly used medicines, therapeutic principle and method and coreprescriptions were obtained. Results: A total of 129 cases, 145 medical records and 132 prescriptions data of TCM were included. A total of 235 Chinese medicines were involved, and the total frequency of medication was 1729. The core prescription groups discovered through complex network methods are: Angelica sinensis, Paeonia lactiflora, Poria cocos, Ginseng, Atractylodes macrocephala, Glycyrrhiza uralensis, Uncaria, Dannan star, Orange red, Poria god, Pinellia ternata, Cinnabar, Alum, Polygala tenuifolia, and Acorus calamus. The highest ranked high-frequency traditional Chinese medicine is Dannanxing, followed by Poria cocos and Pinellia ternata. The drug properties are mainly warm (403 times) and cold (398 times). The distribution of the five flavors of traditional Chinese medicine is mainly composed of sweet herbs (796 times), followed by bitter herbs (675 times) and spicy herbs (529 times). According to the frequency of meridian tropism, the descending order is lung (760 times), spleen (744 times), heart (732 times), and liver (718 times). The overall efficacy of 236 traditional Chinese medicines is mainly focused on resolving phlegm, clearing heat, calming the wind, and calming the heart. Conclusion: The main causes of primary epilepsy were "phlegm" and "wind", with more excess syndrome than deficiency syndrome. The disease mainly occurred in the liver and was closely related to the heart, stomach, and gallbladder; The main location of deficiency syndrome is in the spleen, which is closely related to the heart, liver, and kidney. The principle of treatment is always to dissipate phlegm and regulate nourishment, calm the liver and calm the wind. Specific prescriptions vary depending on the syndrome, including clearing heat, suppressing liver, regulating qi, and promoting blood circulation. The ancient doctors in treating primary epilepsy, which emphasized the combination of cold and warm, and the gentle nature of the drug.

Mobile crowdsensing (MCS) is an effective perception paradigm for large-scale tasks, driven by the proliferation of mobile devices with more powerful sensing and computing capabilities. An effective incentive mechanism is critical to the operation of an MCS system in promoting public engagement. However, the great majority of works discuss fixed task pricing, while the inherent inequality of the supply–demand relationship of the tasks exists. Therefore, it is essential to study the dynamic task pricing problem in the peer-to-peer data sharing MCS system. In this article, we formulate the interactions between the requester and the sensors as a two-stage Stackelberg differential game model, while considering the average behavior of sensors to solve the dynamic task pricing problem. Specifically, in the game model, the requester is the leader who first announces the issued task rate and provides decisive state-changing task pricing dynamics to the sensors. Then, the sensors are the followers who decide the rate of tasks completed noncooperatively based on requesters’ observed strategy, using the level of effort as the state dynamics. The requester and the sensors interact through a mean-field term included in the dynamic state functions, which catches the average behavior of all users. By solving the model, the optimal strategies for the users and the optimal tasks pricing trends in the dynamic environment are obtained. Furthermore, the effectiveness and feasibility of the scheme are verified by a series of numerical simulation experiments.

The ubiquitous mobile portable devices have accelerated the rise of mobile crowdsensing (MCS), a distributed perception paradigm. In MCS, multiple requesters issue their sensing tasks on a server platform, and then the platform distributes the tasks to multiple workers. In this process, requesters typically specify the tasks and requirements; meanwhile, the needed task pricing to workers is also specified, which is used to offsetting worker’s efforts by completing the tasks. However, for different application scenarios, the task requirements, the time periods, and the resource consumptions for completing the tasks are varied, which results in a challenge to raise an appropriate task pricing to diverse workers. Therefore, we study the dynamic task pricing problem in the MCS network system with diverse factors (e.g., multiple requester queueing competitions, dynamic task requirements, and distinct waiting time costs). To solve the problem, we resort to the theory of Age of Information (AoI). Specifically, we leverage the AoI timeliness metric in modeling the requester’s waiting time costs, and then we use queueing game theory to build the dynamic task pricing model. The model analysis has shown the existence of the optimal pricing strategies under the first-come–first-served (FCFS) queueing rule and the last-come–first-served with preemptive in waiting (LCFSW) queueing rule. Finally, numerical simulations are conducted to validate the existence of the optimal task pricing.

Objective The prescription rules of traditional Chinese medicine (TCM) for knee osteoarthritis (KOA) in ancient medical classics were explored based on Traditional Chinese Medicine Inheritance Computer System (TCMICS) to provide reference and evidence for modern clinical treatment. Methods The contents of TCM treatment for KOA in ancient medical classics were comprehensively collected and then logged in TCMICS after screening, where frequency of formulae, medicinals and medicinal combination, as well as properties, flavors and channel tropism of frequently-used medicinals, etc. were counted. Results A total of 510 items were selected from ancient medical classics, including 221 formulae with specific names, and 25 medicinals with a frequency of more than 40. The top three formulae which were most frequently used included Da Fangfeng Tang (Major Ledebouriella Decoction), Wutou Tang (Aconite Decoction), and Duhuo Jisheng Tang (Pubescent Angelica and Mistletoe Decoction). The top five medicinals which were most frequently used included Danggui (Angelicae Sinensis Radix), Niuxi (Achyranthis Bidentatae Radix), Fangfeng (Saposhnikoviae Radix), Chuanxiong (Chuanxiong Rhizoma), and Gancao (Glycyrrhizae Radix et Rhizoma). It was also found through analysis that the core formula was modification of Da Fangfeng Tang. Conclusion The main formulae used for KOA are Da Fangfeng Tang, Wutou Tang, and Duhuo Jisheng Tang, while the selection of medicinals highlights the actions of nourishing the liver and kidney, boosting qi and blood, or activating blood and removing blood stasis, and warming the channels and dissipating cold, which can provide reference for clinical treatment.

Industrial Internet of Things (IIoT) is a new stage for traditional industry to achieve intelligent development. However, the problems of limited resource, communication congestion, and capacity-constrained batteries have emerged due to massive wireless sensing devices (WSDs). With the recent advent of the wireless power transfer (WPT) technique and the development of edge computing technology, the IIoT pays much attention to the interconnected, instant, and high-intelligent system. In this article, we first consider a three-layer architecture to describe the IIoT environment and we propose a resource allocation strategy aiming at maximizing the residual energy of WSDs. The optimization of residual energy is formulated as a mixed-integer nonconvex programming NP hard problem, by constraining the offloading decision, power allocation, computing resource allocation, and time allocation. In addition, an improved hybrid whale optimization algorithm (IHWOA) is proposed to search for the approximate optimal solution. Rapid convergent and stable efficient solution is obtained through simulation experiments. Finally, numerical results prove that the proposed solution achieves good performance.

Objective: Based on the integrated pharmacology platform of Chinese medicine V2.0 (TCMIP V2.0), this paper explores the molecular mechanism and quality markers of Tanyu Tongzhi Recipe against myocardial ischemia reperfusion injury (MIRI). Methods: Use TCMIP V2.0 to collect the drug components, targets, and MIRI disease targets of the recipe for phlegm and blood stasis, construct a drug-disease-target interaction network, screen drugs and disease common targets, analyze the biological process of the common targets, and finally establish a “component-target-pathway-pharmacological action” multi-dimensional network analysis and analysis of the core components in the network. Results: A total of 157 medicinal chemical components, such as Pinellia, Red Peony, Chuanxiong, Licorice, etc. were collected from the prescription of phlegm and blood stasis, with 272 corresponding targets. A total of 290 MIRI disease targets were collected. Through "Traditional Chinese Medicine Association Network Mining," the first 100 targets in the core targets were analyzed and 31 targets shared by drugs and diseases. Analysis of these shared targets revealed that the shared targets are mainly involved in the positive regulation of tube formation, angiogenesis, positive regulation of autophagy, inflammation, and negative regulation of apoptosis. KEGG enrichment analysis shows that these common targets are mainly enriched in the FoxO signaling pathway, HIF-1 signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway, VEGF signaling pathways and other signal pathways. Further analysis of the multi-dimensional network revealed that 46 components of Tanyu Tongzhi Prescription affect the above five signal pathways to exert anti-MIRI effects by interacting with 19 shared targets. Among them, quercetin, kaempferol, naringenin, and baicalein are intervened. AKT affects five signal pathways involved in the occurrence and development of MIRI. Conclusion: Quercetin, kaempferol, naringenin, and baicalein in Tanyu Tongzhi Recipe can resist MIRI by regulating inflammation, autophagy and apoptosis, oxidative stress, angiogenesis, and other processes.

Objective: To analyze medication rule of the treatment for spring warm disease in case records of Qing Dynasty (1636-1912) based on data mining. Methods: Ancient case records of warm disease were selected as the data source and the standard principle of data extraction was established. TCM Miner was used for collecting data and analyzing association rules. Results: A total of 225 case records of spring warm disease are recorded in 20 ancient medical classics, including 37 formulas and 219 Chinese medicines. The main formulas include Baihu Tang (White Tiger Decoction), Fumai Tang (Pulse-Restorative Decoction) and Liuyi San (Six-to-One Powder), which fall into the category of heat-clearing formula, tonifying formula and phlegm-expelling formula respectively. The main Chinese medicines include Lianqiao (Fructus Forsythiae), Fuling (Poria) and Shichangpu (Rhizoma Acori Tatarinowii), which are capable of relieving cough and panting and resolving phlegm, promoting urination and eliminating dampness, as well as tonifying. The properties are mainly warm, cold and neutral; the flavors are mainly sweet, bitter and acrid; and the medicines mainly enter meridians of the lung, stomach and liver respectively. The frequently-used medicinal combinations include Xingren ((Armeniacae Amarum)) -Beimu (Bulbus Fritillariae), Jupi (Citri Exocarpium)-Xingren, Lianqiao-Jinyinhua (Flos Lonicerae Japonicae) -Xuanshen (Radix Scrophulariae), and Lianqiao-Xuanshen-Shichangpu. Conclusion: The formulas and medications in the treatment of spring warm disease in ancient case records focus on clearing heat that is assisted by eliminating exterior pathogen and protecting yin fluid.

During the last few years, automatic modulation classification (AMC) has attracted widespread attention in both civilian and military applications. Conventional AMC schemes are primarily developed under Gaussian noise assumptions. However, recent empirical studies show that non-Gaussian noise has emerged in a variety of wireless networked systems. The bursty nature of non-Gaussian noise fundamentally challenges the applicability of the conventional AMC schemes. In order to improve the classification performance under non-Gaussian noise, in this paper, a novel modulation classification method is proposed by using cyclic correntropy spectrum (CCES) and deep residual neural network (ResNet). First, CCES is introduced to effectively suppress non-Gaussian noise through the designated Gaussian kernel. CCES also provides significantly different CCES graphs with respect to different modulation schemes, enabling AMC to directly operate with the graphs without further feature extraction. Next, based on the CCES graphs, an end-to-end deep ResNet-based AMC is developed to recognize the correct modulation by iteratively evaluating the residual information in a cascade of multiple learning layers. Experimental results confirm that the proposed algorithm outperforms existing designs with much higher classification accuracy, i.e., 3 dB less in the required generalized signal to noise ratio for 100% accuracy, in non-Gaussian noise environments.