Incentive-compatible and budget balanced AGV mechanism for peer-to-peer energy trading in smart grids

Peer-to-peer(P2P)energy trading refers to a type of decentralized transaction,where the energy from distributed energy resources is directly traded between peers.A key challenge in peer-to-peer energy trading is designing a safe,efficient,and transparent trading model and operating mechanism.In this study,we consider a P2P trading environment based on blockchain technology,where prosumers can submit bids or offers without knowing the reports of others.We propose an Arrow-d’Aspremont-Gerard-Varet(AGV)-based mechanism to encourage prosumers to submit their real reserve price and determine the P2P transaction price.We demonstrate that the AGV mechanism can achieve Bayesian incentive compatibility and budget balance.Kernel density estimation(KDE)is used to derive the prior distribution from the historical bid/offer information of the agents.Case studies are carried out to analyze and evaluate the proposed mechanism.Simulation results verify the effectiveness of the proposed mechanism in guiding agents to report the true reserve price while maximizing social welfare.Moreover,we discuss the advantages of budget balance for decentralized trading by comparing the Vickrey-Clarke-Groves(VCG)and AGV mechanisms.

Improving Federated Learning through Abnormal Client Detection and Incentive

Data sharing and privacy protection are made possible by federated learning,which allows for continuous model parameter sharing between several clients and a central server.Multiple reliable and high-quality clients must participate in practical applications for the federated learning global model to be accurate,but because the clients are independent,the central server cannot fully control their behavior.The central server has no way of knowing the correctness of the model parameters provided by each client in this round,so clients may purposefully or unwittingly submit anomalous data,leading to abnormal behavior,such as becoming malicious attackers or defective clients.To reduce their negative consequences,it is crucial to quickly detect these abnormalities and incentivize them.In this paper,we propose a Federated Learning framework for Detecting and Incentivizing Abnormal Clients(FL-DIAC)to accomplish efficient and security federated learning.We build a detector that introduces an auto-encoder for anomaly detection and use it to perform anomaly identification and prevent the involvement of abnormal clients,in particular for the anomaly client detection problem.Among them,before the model parameters are input to the detector,we propose a Fourier transform-based anomaly data detectionmethod for dimensionality reduction in order to reduce the computational complexity.Additionally,we create a credit scorebased incentive structure to encourage clients to participate in training in order tomake clients actively participate.Three training models(CNN,MLP,and ResNet-18)and three datasets(MNIST,Fashion MNIST,and CIFAR-10)have been used in experiments.According to theoretical analysis and experimental findings,the FL-DIAC is superior to other federated learning schemes of the same type in terms of effectiveness.

An Incentive Mechanism for Federated Learning:A Continuous Zero-Determinant Strategy Approach

As a representative emerging machine learning technique, federated learning(FL) has gained considerable popularity for its special feature of “making data available but not visible”. However, potential problems remain, including privacy breaches, imbalances in payment, and inequitable distribution.These shortcomings let devices reluctantly contribute relevant data to, or even refuse to participate in FL. Therefore, in the application of FL, an important but also challenging issue is to motivate as many participants as possible to provide high-quality data to FL. In this paper, we propose an incentive mechanism for FL based on the continuous zero-determinant(CZD) strategies from the perspective of game theory. We first model the interaction between the server and the devices during the FL process as a continuous iterative game. We then apply the CZD strategies for two players and then multiple players to optimize the social welfare of FL, for which we prove that the server can keep social welfare at a high and stable level. Subsequently, we design an incentive mechanism based on the CZD strategies to attract devices to contribute all of their high-accuracy data to FL.Finally, we perform simulations to demonstrate that our proposed CZD-based incentive mechanism can indeed generate high and stable social welfare in FL.

Evaluation of Compatibilizers for Improving Compatibility between Waste Vegetable Oil and Aged Asphalt

Modifying agents 2,2-Bis(4-glycidyloxyphenyl)propane(2BPE)and dibutyl phthalate(DBP)were selected to enhance the compatibility.By using molecular simulation software(Materials Studio,MS),nine systems were constructed,including molecular models of aged asphalt and WVO monomers with 2BPE and/or DBP.The solubility parameters,Flory-Huggins parameters,and interaction energies of these systems were calculated to determine the impact of 2BPE and DBP on the compatibility of WVO and aged asphalt.Results showed that the addition of 2BPE and DBP reduced the difference in the solubility parameters between WVO and aged asphalt,thus improving the compatibility between WVO and aged asphalt.Additionally,using a combination of 2BPE and DBP in both aged asphalt and rejuvenator was found to be more effective than using either 2BPE or DBP alone.Finally,it was determined that evaluating the compatibility of WVO and aged asphalt using Van der Waals potential and non-bonding energy as evaluation indicators was more accurate than using electrostatic potential energy.

Hypoglycemic Effect of Radix Et Rhizoma Salviae Miltiorrhizae,Guixi Green Tea and Their Compatibility on Mice

[Objectives]To explore the hypoglycemic effect of Radix Et Rhizoma Salviae Miltiorrhizae,Guixi green tea and their compatibility on mice,so as to provide more options for the adjuvant treatment of diabetes and improve the comprehensive utilization value of Guixi green tea.[Methods]After being fed adaptively for 7 d,60 SPF-grade male mice were intraperitoneally injected with alloxouracil(180 mg/kg)to induce hyperglycemia model,from which 35 mice with a successful model were selected.They were randomly divided into 5 groups(Danshen group,green tea group,compatible group,positive control group and blank control group),with 7 animals in each group.The mice in all groups were administered according to the dose of 200 mg/kg once a day for 15 d.After the last administration,their body weight was measured on the 15 th day after fasting for 12 h,and their fasting blood glucose was measured by tail clipping.[Results]After modeling,the mice in each group showed typical hyperglycemia symptoms,namely obvious polydipsia,polyphagia,polyuria and weight loss.Compared with the blank control group,Danshen group and green tea group had obvious hypoglycemic effect(P<0.05),and compatible group had significant hypoglycemic effect(P<0.01).Compared with the blank control group,the weight loss of diabetic mice could also be inhibited in green tea group and compatible group(P<0.05).[Conclusions]Danshen,Guixi green tea and their compatibility had the effect of lowering blood sugar,among which the compatible group had the most obvious effect.

Carbon Abatement Cost-Sharing Strategy for Electric Power Sector Based on Incentive and Subsidy Mechanisms

The green and low carbon transition and development of the electricity industry is the most crucial task in realizing the“dual-carbon target”,and it is urgent to explore the incentive and subsidy mechanism to promote green electricity consumption and the cost-sharing strategy of carbon reduction,to alleviate the pressure of carbon abatement cost of each subject of the electricity supply chain.Against this background,this paper takes into account the low-carbon subsidies provided by the government and the incentive subsidies for users,and studies the optimal decision-making of each subject in the electricity supply chain,so that each of them can obtain the optimal profit and achieve carbon emission reduction at the same time.Firstly,taking into account the direct power purchase mode of large users and the electricity-selling companies emerging after the reform of the power sales side,we have established a cooperative mechanism for sharing the cost of carbon emission reduction in the electricity supply chain and clarified the relationship between the supply and demand of electricity among the main parties.Subsequently,considering government low-carbon subsidies and user incentive subsidies,the optimal decisionmaking model is established under two scenarios of decentralized and centralized cooperative games in the supply chain,respectively,with the objective of maximizing profits and carbon reduction rates.Solving for the optimal proportion of carbon abatement costs shared by each participant in the electricity supply chain in achieving game equilibrium.Finally,we analyze the role of the government’s low-carbon subsidies,users’incentive subsidies,and other factors on the profit and carbon reduction effect of the electricity industry through the example analysis and further analyze the impact of carbon abatement cost-sharing measures to provide recommendations for the electricity industry to realize low-carbon abatement and make decisions.

Stackelberg Game-Based Optimal Dispatch for PEDF Park and Power Grid Interaction under Multiple Incentive Mechanisms

The integration of photovoltaic,energy storage,direct current,and flexible load(PEDF)technologies in building power systems is an importantmeans to address the energy crisis and promote the development of green buildings.The friendly interaction between the PEDF systems and the power grid can promote the utilization of renewable energy and enhance the stability of the power grid.For this purpose,this work introduces a framework of multiple incentive mechanisms for a PEDF park,a building energy system that implements PEDF technologies.The incentive mechanisms proposed in this paper include both economic and noneconomic aspects,which is the most significant innovation of this paper.By modeling the relationship between a PEDF park and the power grid into a Stackelberg game,we demonstrate the effectiveness of these incentive measures in promoting the friendly interaction between the two entities.In this game model,the power grid determines on the prices of electricity trading and incentive subsidy,aiming to maximize its revenue while reducing the peak load of the PEDF park.On the other hand,the PEDF park make its dispatch plan according to the prices established by the grid,in order to reduce electricity consumption expense,improve electricity utility,and enhance the penetration rate of renewable energy.The results show that the proposed incentive mechanisms for the PEDF park can help to optimize energy consumption and promote sustainable energy practices.

Effects of Radix Puerariae, Radix Rehmanniae and Their Compatibility on Blood Glucose and Blood Lipids in Mice

[Objectives]To explore the effects of the compatibility of Radix Puerariae and Radix Rehmanniae on blood glucose and blood lipids in diabetic mouses.[Methods]Diabetic mouse model was established.The body weight and fasting blood glucose of mice were measured after 7 and 14 d of administration,and the biochemical indicators of blood lipids(TC,HDL-C,and LDL-C)were detected after 14 d of administration.[Results]Compared with the Radix Puerariae group and Radix Rehmanniae group,the compatibility group(1:2)had the best hypoglycemic effect(P<0.05),and TC and LDL-C in the compatibility group(2:1)significantly decreased(P<0.05),while HDL-C in the compatibility group(1:1)significantly increased(P<0.05).[Conclusions]Radix Puerariae,Radix Rehmanniae and their combination can reduce the blood glucose of diabetic mice.The compatibility group(1:2)had a significant hypoglycemic effect(P<0.05),and LDL-C in the compatibility group(2:1)significantly declined,while HDL-C in the compatibility group(1:1)rose significantly.

Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies.For this purpose,a power grid-flexible load bilevel model is constructed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the follower.Initially,an upper-level day-ahead dispatching model for the power grid is established,considering the lowest power grid dispatching cost as the objective function and incorporating the power grid-side constraints.Then,the lower level comprehensively considers the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective function.Finally,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing costs.

Research on the Improvement of Incentive Mechanism for Pharmaceutical Sales Personnel - Taking Company A as an Example

Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensation incentive,performance appraisal,welfare benefit,training incentive,promotion motivation and enterprise cultural inspiration were explored through questionnaires,telephone interviews and in-person interviews.Results and Conclusion This company’s incentive mechanism has problems in two aspects:Material incentives and spiritual incentives.As to the company’s characteristics and strategic development,the optimization countermeasures of incentive mechanism are proposed from the following three aspects:constructing a reasonable incentive system,establishing an efficient spiritual incentive mechanism,and implementing the dynamic incentive and differentiated incentive simultaneously.

Rapid evolution of T2/S-RNase genes in Fragaria linked to multiple transitions from self-incompatibility to self-compatibility

The T2/RNase gene family is widespread in eukaryotes,and particular members of this family play critical roles in the gametophytic self-incompatibility(GSI) system in plants.Wild diploid strawberry(Fragaria)species have diversified their sexual systems via self-incompatible and self-compatible traits,yet how these traits evolved in Fragaria remains elusive.By integrating the published and de novo assembled genomes and the newly generated RNA-seq data,members of the RNase T2 gene family were systematically identified in six Fragaria species,including three self-incompatible species(Fragaria nipponica,Fragaria nubicola,and Fragaria viridis) and three self-compatible species(Fragaria nilgerrensis,Fragaria vesca,and Fragaria iinumae).In total,115 RNase T2 genes were identified in the six Fragaria genomes and can be classified into three classes(Ⅰ-Ⅲ) according to phylogenetic analysis.The identified RNase T2 genes could be divided into 22 homologous gene sets according to amino acid sequence similarity and phylogenetic and syntenic relationships.We found that extensive gene loss and pseudogenization coupled with small-scale duplications mainly accounted for variations in the RNase T2 gene numbers in Fragaria.Multiple copies of homologous genes were mainly generated from tandem and segmental duplication events.Furthermore,we newly identified five S-RNase genes in three self-incompatible Fragaria genomes,including two in F.nipponica,two in F.viridis,and one in F.nubicola,which fit for typical features of a pistil determinant,including highly pistil-specific expression,highly polymorphic proteins and alkaline isoelectric point(pI),while no S-RNase genes were found in all three selfcompatible Fragaria species.Surprisingly,these T2/S-RNase genes contain at least one large intron(>10 kb).This study revealed that the rapid evolution of T2/S-RNase genes within the Fragaria genus could be associated with its sexual mode,and repeated evolution of the self-compatible traits in Fragaria was convergent via losses of S-RNase.

Epidemiological Investigation of Brucellosis Spondylitis and Optimal Selection of Clinical Drug Compatibility, Treatment Course and Treatment Plan

Background: Brucellosis is a zoonotic endemic disease, the main source of infection is infected cattle, sheep, pigs and their products. In recent years, the global incidence of brucellosis spondylitis has increased year by year, and it has spread from pastoral areas to semi-agricultural and semi-pastoral areas, agricultural areas and cities. It has changed from a mainly occupational disease to a mainly food-borne disease, and it is also a zoonotic specific spinal infectious disease that WHO and governments around the world pay great attention to. Due to the low cure rate and high recurrence rate of traditional drug therapy regimen. Therefore, to carry out epidemiological investigation and Related research on clinical drug therapy of brucellosis spondylitis has practical significance for improving diagnosis rate, cure rate and reducing recurrence rate. Objective: To analyze the epidemiological characteristics of Brucellosis spondylitis and explore the choice of drugs and the best drug treatment plan, so as to provide scientific basis for improving the prevention and control of the disease and treatment effect. Methods: Clinical epidemiodogical materials were collected from 113 patients with brucellar spondylitis. All these patients were divided into 5 different groups according to 5 kinds of drugs adopted respectively, and then the patients were given different course of treatment. Results: In the 113 patients, brucellar spondylitis morbility of female patients were higher than that of male ones, and the morbility of Bashang were higher than that of Baxia. These patients were infected mainly through browsing and breeding beasts. Lumbars were the major focus of infection. It was very comnlon that two adjacent lumbars were involved in concurrently. L4 was the most common infection location and its demolishment was most serious. The curative effect of group treated with doxycycline was better than that of group treated without doxycycline. If the course of treatment Was increased, the curative effect Was not increased obviously. Conclusions: There are characteristic features in clinical epidemiology of brucell spondylitis. Doxycycline + Rifampicin + Sulfamethoxazole was used as the preferred antibiotic. Using antibiotics adequately and jointly by two courses of treatment for a long time is the most reasonable way to treat the disease and prevent the disease from recurrence.

An Incentive Mechanism Model for Crowdsensing with Distributed Storage in Smart Cities

Crowdsensing,as a data collection method that uses the mobile sensing ability of many users to help the public collect and extract useful information,has received extensive attention in data collection.Since crowdsensing relies on user equipment to consume resources to obtain information,and the quality and distribution of user equipment are uneven,crowdsensing has problems such as low participation enthusiasm of participants and low quality of collected data,which affects the widespread use of crowdsensing.This paper proposes to apply the blockchain to crowdsensing and solve the above challenges by utilizing the characteristics of the blockchain,such as immutability and openness.An architecture for constructing a crowdsensing incentive mechanism under distributed incentives is proposed.A multi-attribute auction algorithm and a k-nearest neighbor-based sensing data quality determination algorithm are proposed to support the architecture.Participating users upload data,determine data quality according to the algorithm,update user reputation,and realize the selection of perceived data.The process of screening data and updating reputation value is realized by smart contracts,which ensures that the information cannot be tampered with,thereby encouraging more users to participate.Results of the simulation show that using two algorithms can well reflect data quality and screen out malicious data.With the help of blockchain performance,the architecture and algorithm can achieve decentralized storage and tamper-proof information,which helps to motivate more users to participate in perception tasks and improve data quality.

Enhancing the compatibility of the amyloid-dye hybrid nanostructure for improved photo-biocatalysis

Artificial photosynthesis is significant for renewable energy generation,sustainable development,and environmental protection.Dye-protein hybrids are promising for developing photosynthesis mimics(e.g.,photo-biocatalysis),but their performances are far lower than the plant photosystems,partially because of the incompatibility between dye and the protein matrix that limits excited state electron transfer of the included dyes.Here,using ThT-insulin amyloid assembly as a model system,we proposed that increasing the dye-protein compatibility could lead to the improved photo-biocatalytic performance.A ThT derivative,ThTPD,was designed with the same electron acceptor but extended π-conjugated donor structure.When integrated into the insulin amyloid,the extended π-conjugated donor structure allowed increased binding affinity and energy with the amyloid matrix,thus better electron transport to the mediator to drive the photocatalytic reaction.Meanwhile,compared with ThT, ThTPD exhibited improved light absorption and longer excited state lifetime.The photo-biocatalytic performance of ThTPD-insulin amyloid was greatly improved as compared with that of ThT in reduced nicotinamide adenine dinucleotide(NADH) regeneration.When integrating with NADH-dependent L-glutamate reductase,the efficiency of the ThTPD-insulin amyloid hybrid was 2.8-fold higher than that of ThT in glutamate generation,showing promising feature in biocatalytic solar-to-chemical conversion.

Do Research Incentives Promote Researchers’Mental Health?

Background:Researchers have a higher risk of anxiety and depression than the general population,so it is important to promote researchers’mental health.Method:Based on the data from 3210 global researchers surveyed by the journal Nature in 2021,confirmatory factor analysis,OLS regression and other regressions were used to explore the research incentive dimensions and their effects on researchers’mental health.Results:(1)Material incentive factors,work-family life balance factors,good organizational environment and spiritual motivation had significant positive effects on researchers’mental health.(2)The spiritual motivation could better promote researchers’mental health than the other factors.(3)Heterogeneity analysis showed that material incentive factors and spiritual motivation created more significant stimulating effects on the mental health of humanities and social sciences researchers.Work-family life balance factors were more effective in promoting the mental health of the mid-career group and the overtime group.Conclusion:Application of the four research incentives resulted in lower likelihood of anxiety or depression among researchers,and special attention should be paid to the role of the spiritual motivation.In order to promote researchers’mental health,different incentives should be applied to different researcher groups to better improve researchers’mental health.

A dynamic incentive and reputation mechanism for energy-efficient federated learning in 6G

As 5G becomes commercial,researchers have turned attention toward the Sixth-Generation(6G)network with the vision of connecting intelligence in a green energy-efficient manner.Federated learning triggers an upsurge of green intelligent services such as resources orchestration of communication infrastructures while preserving privacy and increasing communication efficiency.However,designing effective incentives in federated learning is challenging due to the dynamic available clients and the correlation between clients'contributions during the learning process.In this paper,we propose a dynamic incentive and reputation mechanism to improve energy efficiency and training performance of federated learning.The proposed incentive based on the Stackelberg game can timely adjust optimal energy consumption with changes in available clients during federated learning.Meanwhile,clients’contributions in reputation management are formulated based on the cooperative game to capture the correlation between tasks,which satisfies availability,fairness,and additivity.The simulation results show that the proposed scheme can significantly motivate high-performance clients to participate in federated learning and improve the accuracy and energy efficiency of the federated learning model.

Improving Interventions on Cardiovascular Disease and Diet: A Policy Incentive Analysis

Various Cardiovascular Diseases (CVDs) can be catastrophic and can lead to irreversible outcomes. Despite improved interventions for CVD prevention awareness, there continues to be discussion and research on diet-related CVD and mortality without addressing the problem. Instead of prioritizing public guidelines and policies, policymakers should understand CVD and address population barriers to adhering to a healthy diet that decreases CVD risk. Therefore, this project aims to analyze federal healthy food incentive policies to promote healthy diet behaviors that reduce CVD risk. The method used was existing data for a comparative policy analysis that included a policy proposal process: phases of progression, measures, and a policy model with data collection and requirements. This analysis compared a current federal food incentive program versus the proposed program. Results of the final analysis derived from the literature review and collected data stated consuming foods from the Mediterranean and other low-fat and low-salt diets reduced CVD risks that also reduced other risks secondary to CVD, such as obesity, diabetes, and Cerebrovascular Accident (CVA). Comparatively, combined healthy food incentives and disincentives were more effective for improving healthy behaviors than, in some cases, even after incentives were removed. Therefore, this policy analysis supports the indication for incentive policy change. However, the lack of federal stakeholders’ response to key policy changes upon proposal submission may require other methods of proposal dissemination. Nonetheless, focusing analysis on various Food Insecurity Nutrition Incentive (FINI) programs instead of one, multi-state program, which may have improved analysis outcomes, was the lesson learned.

Exploring the compatibility theory of traditional Chinese medicine formulae:the disassembled prescriptions study

Traditional Chinese medicine(TCM)has become very popular in the treatment of complex diseases worldwide in recent decades.Despite the promising performance of TCM,how herbs work synergistically in a formula and their therapeutic targets remain ambiguous.This largely limits the correct use and modernization of TCM formulas clinically.The study of disassembled prescriptions is important for investigating the compatibility theory of Chinese medicines.By dissecting the mechanisms of TCM formulae,the compatibility principles of some well-known formulae,such as Realgar-Indigo naturalis,have been elucidated to a certain extent.In this review,several common methods of disassembled prescription studies are summarized,including those of single herb or mineral,sub-prescription,active ingredients or effective parts,large formulae,and systems pharmacology studies,as well as the methods of grouping based on the properties or efficacy of Chinese medicines,in order to provide evidence for formulae study.Moreover,some challenges to be addressed in disassembled prescriptions studies have been identified in this review.

Compatibility Rules of Prescriptions of Tibetan Medicine Polygonatum cirrhifolium Based on Data Mining

[Objectives]To study the prescription compatibility rules of the Tibetan medicine Polygonatum cirrhifolium(Polygonati Rhizoma,Huangjing)based on data mining,so as to provide data support for clinical application and new drug development.[Methods]Prescriptions containing Tibetan medicine Huangjing were collected from Tibetan Medicine Prescriptions Encyclopedia and Tibetan Medicine Classic Literature Collection.The Traditional Chinese Medicine Inheritance Computing System(TCMICS 3.0)and R version 4.1.3 were used to mine and analyze the compatibility rules of prescriptions containing Tibetan medicinal material Huangjing,the rules of medication for high-frequency diseases,and the association rules of various medicinal materials.[Results]A total of 124 prescriptions were collected from the classic literature of Tibetan medicine,and the frequency statistical analysis showed that drugs compatible with Huangjing(≥15)included Tianmendong(Root of Cochinchinese Asparagus)(80),Mirabilis himalaica(Edgew.)Heimerl(Himalayan purple jasmine)(72),Jili(Tribuli Fructus)(70),Tibetan Aoruqin(Vicatia coniifolia)(58),Baidoukou(Round Cardamom Fruit)(47),Hezi(Chebulae Fructus)(45),Shouzhangshen(Rhizome of Conic Gymnadenia)(28),Yuganzi(Phyllanthi Fructus)(26),Pomegranate(25),Maohezi(Terminaliae Belliricae Fructus)(24),Zicaorong(Lacca)(23),Rougui(Cinnamomi Cortex)(15).The main diseases were yellow water disease(20),gynecological diseases(19),kidney cold disease(17),and other Tibetan medicine diseases.Association rule analysis showed that the drug combinations with the highest frequency were Huangjing—Tianmendong,Huangjing—Himalayan purple jasmine,and Huangjing—Jili.[Conclusions]The frequency of combined use of Tibetan medicine Huangjing with dry yellow water,tonifying kidney and diuresis,nourishing health,and treating gynecological diseases is relatively high.

Compatibility Rules of Prescriptions of Tibetan Medicinal Material Mirabilis himalaica(Edgew.)Heimerl Based on Data Mining

[Objectives]To study the prescription compatibility rules of the Tibetan medicinal material Mirabilis himalaica(Edgew.)Heimerl(Himalayan purple jasmine)based on data mining,and to provide reference for clinical application and new drug development.[Methods]The literature data were collected and the prescriptions containing Himalayan purple jasmine were sorted and classified by Microsoft Excel 2019 software.The Traditional Chinese Medicine Inheritance Computing System(TCMICS 3.0)was used to statistically analyze the high-frequency drugs and core drug combinations,the frequency of disease treatment,and the rules of"tastes transforming flavors"of drugs.The FP-tree algorithm was used to analyze the association rules among various Tibetan medicinal materials in the prescriptions,and different supports were set to analyze the compatibility rules of the prescriptions.[Results]There were a total of 129 prescriptions containing Himalayan purple jasmine,297 medicinal materials used in combination with it,and 34 Tibetan medicinal materials with a frequency of≥15.The medicinal flavors were mostly sweet,bitter,and pungent.Among the three flavors,bitterness and sweetness were the majority.At the same time,the medicinal properties were blunt,soft,cool,and warm.A total of 130 kinds of diseases were involved,among which 8 kinds of diseases such as gynecology,kidney cold and yellow water disease had a high frequency.Through association rule analysis,33 commonly used core drug combinations were obtained.The support,confidence,and frequency of the five drug combinations[Jili(Tribuli Fructus),Huangjing(Polygonati Rhizoma),Tianmendong(Root of Cochinchinese Asparagus),and Tibetan Aoruqin(Vicatia coniifolia)]→Himalayan purple jasmine were the basic prescription of Tibetan medicine Wudagen Powder.The drug combinations with higher confidence included Bibo(Piperis Longi Fructus)→Himalayan purple jasmine,Pomegranate(Punica granatum→Himalayan purple jasmine,Baidoukou(Round Cardamom Fruit)→Himalayan purple jasmine,Hezi(Chebulae Fructus)→Himalayan purple jasmine.Jili(Tribuli Fructus)→Himalayan purple jasmine,Huangjing(Polygonati Rhizoma)→Himalayan purple jasmine and Tianmendong(Root of Cochinchinese Asparagus)→Himalayan purple jasmine had highest frequency.[Conclusions]Through the TCMICS,this paper analyzed the compatibility rules of commonly used drugs containing Himalayan purple jasmine and the characteristics of the main diseases.It can be seen that Himalayan purple jasmine is sweet in taste and warm in nature.It assists sovereign drugs in the form of ministerial drugs,which enhances the effect of regulating"long"and nourishing,and plays the role of regulating"long",dispelling cold,and reconciling various drugs,which embodies the compatibility rules of sovereign and ministerial drugs of Tibetan medicines.The main diseases of Himalayan purple jasmine are related to"long"regulation,and it is mostly used in the treatment of gynecological diseases after being combined with other drugs to form a prescription.Most drugs in the prescriptions are sweet,which is the therapeutic principle of regulating"long"and nourishing,and verifies the scientific and rational principle of clinical use of Tibetan medicine.In the prescription,the medicinal properties include both warm and cool,and the medicinal taste is sweet and bitter,which is in line with the compatibility theory of"tastes transforming flavors"in traditional Tibetan medicine prescriptions.