In the present study,data mining and network pharmacology were utilized to explore the principles and mechanisms of traditional Chinese medicine(TCM)in treating acute appendicitis.The goal was to provide a scientific ...In the present study,data mining and network pharmacology were utilized to explore the principles and mechanisms of traditional Chinese medicine(TCM)in treating acute appendicitis.The goal was to provide a scientific basis for clinical treatment and further research on this disease.First,we searched the National Patent Database for Chinese herbal compound prescriptions used to treat acute appendicitis.We then applied frequency analysis,character and taste meridian analysis,association rule analysis,and hierarchical cluster analysis to identify the patterns of TCM treatment for acute appendicitis,selecting key combinations of Chinese medicines.Next,we screened the main active components of these key TCM based on quality markers.Using databases such as SwissTargetPrediction,SymMap,ETCM,and STRING,we analyzed the pharmacological mechanisms of these key TCM in treating acute appendicitis.Key active components and targets were further verified through molecular docking.We identified a total of 129 patents involving 316 Chinese medicines,with 24 being frequently used.The results indicated that most Chinese herbs used for acute appendicitis were heat-clearing drugs,blood-activating and stasis-removing drugs,and purging drugs.The primary active ingredients of the Rhubarb-cortex moutan-flos lonicerae combination for treating acute appendicitis included Emodin,Paeonol,Physcion,Chlorogenic acid,Chrysophanol,Rhein acid,and Aloe-emodin.These ingredients targeted key proteins such as ALB,TP53,BCL2,STAT3,IL-6,and TNF,and were involved in cellular responses to lipopolysaccharides,cell composition,and various cytokine-mediated biological processes.They also interacted with signaling pathways like AGE-RAGE,TNF,IL-17,and FoxO.Based on patent data,this study analyzed medication patterns in the treatment of acute appendicitis,discussed the possible mechanisms of key TCM combinations,and provided a scientific basis and new perspectives for the diagnosis and treatment of the disease.展开更多
Introduction Neurosurgical emergencies such as spontaneous intracerebral hemorrhage(ICH),traumatic brain injury(TBI),and acute brain herniation are among the most time-sensitive and high-stakes conditions in modern me...Introduction Neurosurgical emergencies such as spontaneous intracerebral hemorrhage(ICH),traumatic brain injury(TBI),and acute brain herniation are among the most time-sensitive and high-stakes conditions in modern medicine.Clinical decisions often must be made within minutes,yet these decisions are traditionally guided by limited information,heuristic reasoning,and past experience.In this context,the rise of medical data mining and real-time analytics offers a transformative opportunity:to extract actionable intelligence from the flood of clinical,imaging,and physiological data already being collected,and to use this intelligence to guide care in real time[1–3](Figure 1).展开更多
With the gradual acceleration of information construction in colleges and universities,digital campus and smart campus have gradually become important means for colleges and universities to scientifically manage the c...With the gradual acceleration of information construction in colleges and universities,digital campus and smart campus have gradually become important means for colleges and universities to scientifically manage the campus.They have been applied to teaching,scientific research,student management,and other fields,improving the quality and efficiency of management.This paper mainly studies the intelligent educational administration management system based on data mining technology.Firstly,this paper introduces the application process of data mining technology,and builds an intelligent educational administration management system based on data mining technology.Then,this paper optimizes the application of the Apriori algorithm in educational administration management through transaction compression and frequent sampling.Compared with the traditional Apriori algorithm,the optimized Apriori algorithm in this paper has a shorter execution time under the same minimum support.展开更多
Objective To explore the optimization and principles of acupoint selection and coordination in the treatment of adult abdominal obesity using acupuncture and moxibustion over the past decade using data mining.Methods ...Objective To explore the optimization and principles of acupoint selection and coordination in the treatment of adult abdominal obesity using acupuncture and moxibustion over the past decade using data mining.Methods Clinical studies of abdominal obesity treated with acupuncture and moxibustion,collected in the past 10 years,were searched from China Biology Medicine disc(CBMdisc),China National knowledge infrastructure(CNKI),Wanfang,China Science and Technology Journal Database(VIP),Pubmed,Embase,Google Scholar,Web of Science,(The Cumulative Index to Nursing and Allied Health Literature)CINAHL,Psyclnfo and Scopus,dated from March 1,2013 to March 31,2023.Using IBM SPSS Modeler 18.0 and other software,the frequency analysis,association-rules analysis and cluster analysis were conducted on interventions,traditional Chinese medicine(TCM)patterns,use frequency of acupoint,meridian attribution of acupoint,acupoint location,etc.Results A total of 55 articles were included,with 102 prescriptions and 71 acupoints involved.The top 3 interventions were acupoint embedding method,simple electroacupuncture and simple filiform needling.Seventeen patterns/syndromes of TCM differentiation were collected,dominated by spleen deficiency and damp blockage,spleen and kidney yang deficiency and heat accumulation in stomach and intestines.The acupoints in clinical practice were mostly at the foot-yangming stomach meridian,the conception vessel and the foot-taiyin spleen meridian,and located at the abdominal region.The top 5 acupoints of high frequency were Tianshu(ST25),Zhongwan(CV12),Daheng(SP15),Zusanli(ST36),Huaroumen(ST24)and Daimai(GB26).The specific points of the high frequency were the crossing points and front-mu points,of which,ST25 and CV12 were the most prominent.After association-rules analysis on the high-frequency acupoints,20 groups of associated acupoints were obtained,in which,the core acupoints included ST25,CV12,SP15 and ST36.Conclusion In recent 10 years,abdominal obesity is treated by the acupoints of foot-yangming stomach meridian,the conception vessel and the foot-taiyin spleen meridian.Compared with the regimen for simple obesity,the acupoints at the abdominal region are specially selected in treatment of abdominal obesity,such as ST25,CV12,SP15 and ST36.Supplementary acupoints are selected based on syndrome differentiation to simultaneously address both the disease manifestations and root causes.展开更多
Objective:To explore the core acupuncture acupoints and pattern-adapted acupoint combination rules for autism spectrum disorder(ASD)complicated with sleep disorder using clinical data mining technology.Methods:A retro...Objective:To explore the core acupuncture acupoints and pattern-adapted acupoint combination rules for autism spectrum disorder(ASD)complicated with sleep disorder using clinical data mining technology.Methods:A retrospective analysis was conducted on the diagnosis and treatment data of 104 children with ASD complicated with sleep disorder admitted to Xi’an Traditional Chinese Medicine(TCM)Encephalopathy Hospital from January 2022 to December 2024.Cross-pattern main acupoints were screened via frequency statistics,chi-square test,and factor analysis;pattern-specific auxiliary acupoints were extracted by combining multiple correspondence analysis,cluster analysis,and association rule mining.Results:Ten cross-pattern main acupoints(Baihui,Sishenzhen,Language Area 1,Language Area 2,Neiguan,Shenmen,Yongquan,Xuanzhong)were identified,and acupoint combination schemes for four major TCM patterns(Hyperactivity of Liver and Heart Fire,Deficiency of Kidney Essence,Deficiency of Both Heart and Spleen,Hyperactivity of Liver with Spleen Deficiency)were established.Conclusion:Acupuncture treatment should follow the principle of“regulating spirit and calming the brain as the root,and dredging collaterals based on pattern differentiation as the branch”.The synergy between main and auxiliary acupoints can accurately regulate the disease,providing a basis for precise clinical treatment.展开更多
In light of the rapid growth and development of social media, it has become the focus of interest in many different scientific fields. They seek to extract useful information from it, and this is called (knowledge), s...In light of the rapid growth and development of social media, it has become the focus of interest in many different scientific fields. They seek to extract useful information from it, and this is called (knowledge), such as extracting information related to people’s behaviors and interactions to analyze feelings or understand the behavior of users or groups, and many others. This extracted knowledge has a very important role in decision-making, creating and improving marketing objectives and competitive advantage, monitoring events, whether political or economic, and development in all fields. Therefore, to extract this knowledge, we need to analyze the vast amount of data found within social media using the most popular data mining techniques and applications related to social media sites.展开更多
Since the impoundment of Three Gorges Reservoir(TGR)in 2003,numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall.One case is the Outang landsli...Since the impoundment of Three Gorges Reservoir(TGR)in 2003,numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall.One case is the Outang landslide,a large-scale and active landslide,on the south bank of the Yangtze River.The latest monitoring data and site investigations available are analyzed to establish spatial and temporal landslide deformation characteristics.Data mining technology,including the two-step clustering and Apriori algorithm,is then used to identify the dominant triggers of landslide movement.In the data mining process,the two-step clustering method clusters the candidate triggers and displacement rate into several groups,and the Apriori algorithm generates correlation criteria for the cause-and-effect.The analysis considers multiple locations of the landslide and incorporates two types of time scales:longterm deformation on a monthly basis and short-term deformation on a daily basis.This analysis shows that the deformations of the Outang landslide are driven by both rainfall and reservoir water while its deformation varies spatiotemporally mainly due to the difference in local responses to hydrological factors.The data mining results reveal different dominant triggering factors depending on the monitoring frequency:the monthly and bi-monthly cumulative rainfall control the monthly deformation,and the 10-d cumulative rainfall and the 5-d cumulative drop of water level in the reservoir dominate the daily deformation of the landslide.It is concluded that the spatiotemporal deformation pattern and data mining rules associated with precipitation and reservoir water level have the potential to be broadly implemented for improving landslide prevention and control in the dam reservoirs and other landslideprone areas.展开更多
Objective To explore the medication rules of traditional Chinese medicine(TCM)and mechanism of action of hub herb pairs for treating insomnia.Methods Totally 104 prescriptions were statistically analyzed.The associati...Objective To explore the medication rules of traditional Chinese medicine(TCM)and mechanism of action of hub herb pairs for treating insomnia.Methods Totally 104 prescriptions were statistically analyzed.The association rule algorithm was applied to mine the hub herb pairs.Network pharmacology was utilized to analyze the mechanism of the hub herb pairs,while molecular docking was applied to simulate the interaction between receptors and herb molecules,thereby predicting their binding affinities.Results The most frequently used herbs in TCM prescriptions for treating insomnia included Semen Ziziphi Spinosae,Radix Glycyrrhizae,Radix et Rhizoma Ginseng,and Poria cum Radix Pini.Among them,the most commonly used were the supplementing herbs,followed by heat-clearing,mind-calming,and exterior-releasing ones,with their properties of warm and cold,flavors of sweet,Pungent,and bitter,and meridian tropisms of liver,lungs,spleen,kidneys,heart,and stomach.The hub herb pairs based on the association rules included Radix Astragali-Radix et Rhizoma Ginseng,Rhizoma Chuanxiong-Radix Glycyrrhizae,Seman Platycladi-Semen Ziziphi Spinosae,Pericarpium Citri Reticulatae-Radix Glycyrrhizae,Radix Polygalae-Semen Ziziphi Spinosae,and Radix Astragali-Semen Ziziphi Spinosae.Network pharmacology revealed that the cAMP signaling pathway might play a key role in treating insomnia synergistically with HIF-1 signaling pathway,prolactin signaling pathway,chemical carcinogenesis receptor activation,and PI3K-Akt signaling pathway.Molecular docking indicated that there was good binding between the active ingredients of the hub herb pairs and the hub targets.Conclusions This study identified six hub herb pairs for treating insomnia in TCM.These hub herb pairs may synergistically treat insomnia with HIF-1 signaling pathway,prolactin signaling pathway,chemical carcinogenesis receptor activation,and PI3K-Akt signaling pathway through the cAMP signaling pathway.展开更多
The correlation between the longitudinal crack occurrence and integrated heat transfer of the mold with data mining methods was investigated.Firstly,three kinds of support vector machine models based on principal comp...The correlation between the longitudinal crack occurrence and integrated heat transfer of the mold with data mining methods was investigated.Firstly,three kinds of support vector machine models based on principal component analysis with different input features were established to explore the effect of integrated heat transfer on the accuracy of the prediction model for the longitudinal crack.The results show that the accuracy was improved while features including mean and standard deviation of integrated heat transfer were added.Then,the difference in integrated heat transfer between defect and normal samples under the same process parameters was quantitatively compared.Compared with normal samples,the temperature difference of cooling water for defect samples decreased by 0.65%,and the temperature difference fluctuation increased by 31.1%.Finally,the literature data were used to provide support for the quantitative correlation according to defect formation mechanism.A new criterion for the prediction of longitudinal crack and a discovering method for correlation between product quality and process parameters in the manufacturing industry have been provided.展开更多
Background:Erzhu Erchen decoction(EZECD),which is based on Erchen decoction and enhanced with Atractylodes lancea and Atractylodes macrocephala,is widely used for the treatment of dampness and heat(The clinical manife...Background:Erzhu Erchen decoction(EZECD),which is based on Erchen decoction and enhanced with Atractylodes lancea and Atractylodes macrocephala,is widely used for the treatment of dampness and heat(The clinical manifestations of Western medicine include thirst,inability to drink more,diarrhea,yellow urine,red tongue,et al.)internalized disease.Nevertheless,the mechanism of EZECD on damp-heat internalized Type 2 diabetes(T2D)remains unknown.We employed data mining,pharmacology databases and experimental verification to study how EZECD treats damp-heat internalized T2D.Methods:The main compounds or genes of EZECD and damp-heat internalized T2D were obtained from the pharmacology databases.Succeeding,the overlapped targets of EZECD and damp-heat internalized T2D were performed by the Gene Ontology,kyoto encyclopedia of genes and genomes analysis.And the compound-disease targets-pathway network were constructed to obtain the hub compound.Moreover,the hub genes and core related pathways were mined with weighted gene co-expression network analysis based on Gene Expression Omnibus database,the capability of hub compound and genes was valid in AutoDock 1.5.7.Furthermore,and violin plot and gene set enrichment analysis were performed to explore the role of hub genes in damp-heat internalized T2D.Finally,the interactions of hub compound and genes were explored using Comparative Toxicogenomics Database and quantitative polymerase chain reaction.Results:First,herb-compounds-genes-disease network illustrated that the hub compound of EZECD for damp-heat internalized T2D could be quercetin.Consistently,the hub genes were CASP8,CCL2,and AHR according to weighted gene co-expression network analysis.Molecular docking showed that quercetin could bind with the hub genes.Further,gene set enrichment analysis and Gene Ontology represented that CASP8,or CCL2,is negatively involved in insulin secretion response to the TNF or lipopolysaccharide process,and AHR or CCL2 positively regulated lipid and atherosclerosis,and/or including NOD-like receptor signaling pathway,and TNF signaling pathway.Ultimately,the quantitative polymerase chain reaction and western blotting analysis showed that quercetin could down-regulated the mRNA and protein experssion of CASP8,CCL2,and AHR.It was consistent with the results in Comparative Toxicogenomics Database databases.Conclusion:These results demonstrated quercetin could inhibit the expression of CASP8,CCL2,AHR in damp-heat internalized T2D,which improves insulin secretion and inhibits lipid and atherosclerosis,as well as/or including NOD-like receptor signaling pathway,and TNF signaling pathway,suggesting that EZECD may be more effective to treat damp-heat internalized T2D.展开更多
[Objectives]To explore the trend of brands towards the design of waist protection products through data mining,and to provide reference for the design concept of the contour of waist protection pillow.[Methods]The str...[Objectives]To explore the trend of brands towards the design of waist protection products through data mining,and to provide reference for the design concept of the contour of waist protection pillow.[Methods]The structural design information of all waist protection equipment was collected from the national Internet platform,and the data were classified and a database was established.IBM SPSS 26.0 and MATLAB 2018a were used to analyze the data and tabulate them in Tableau 2022.4.After the association rules were clarified,the data were imported into Cinema 4D R21 to create the concept contour of waist protection pillow.[Results]The average and standard deviation of the single airbag design were the highest in all groups,with an average of 0.511 and a standard deviation of 0.502.The average and standard deviation of the upper and lower dual airbags were the lowest in all groups,with an average of 0.015 and a standard deviation of 0.120;the correlation coefficient between single airbag and 120°arc stretching was 0.325,which was positively correlated with each other(P<0.01);the correlation coefficient between multiple airbags and 360°encircling fitting was 0.501,which was positively correlated with each other and had the highest correlation degree(P<0.01).[Conclusions]The single airbag design is well recognized by companies,and has received the highest attention among all brand products.While focusing on single airbag design,most brands will consider the need to add 120°arc stretching elements in product design.At the time of focusing on multiple airbag design,some brands believe that 360°encircling fitting elements need to be added to the product,and the correlation between the two is the highest among all groups.展开更多
Background:Diabetic retinopathy(DR)is currently the leading cause of blindness in elderly individuals with diabetes.Traditional Chinese medicine(TCM)prescriptions have shown remarkable effectiveness for treating DR.Th...Background:Diabetic retinopathy(DR)is currently the leading cause of blindness in elderly individuals with diabetes.Traditional Chinese medicine(TCM)prescriptions have shown remarkable effectiveness for treating DR.This study aimed to screen a novel TCM prescription against DR from patents and elucidate its medication rule and molecular mechanism using data mining,network pharmacology,molecular docking and molecular dynamics(MD)simulation.Method:TCM prescriptions for treating DR was collected from patents and a novel TCM prescription was identified using data mining.Subsequently,the mechanism of the novel TCM prescription against DR was explored by constructing a network of core TCMs-core active ingredients-core targets-core pathways.Finally,molecular docking and MD simulation were employed to validate the findings from network pharmacology.Result:The TCMs of the collected prescriptions primarily possessed bitter and cold properties with heat-clearing and supplementing effects,attributed to the liver,lung and kidney channels.Notably,a novel TCM prescription for treating DR was identified,composed of Lycii Fructus,Chrysanthemi Flos,Astragali Radix and Angelicae Sinensis Radix.Twenty core active ingredients and ten core targets of the novel TCM prescription for treating DR were screened.Moreover,the novel TCM prescription played a crucial role for treating DR by inhibiting inflammatory response,oxidative stress,retinal pigment epithelium cell apoptosis and retinal neovascularization through various pathways,such as the AGE-RAGE signaling pathway in diabetic complications and the MAPK signaling pathway.Finally,molecular docking and MD simulation demonstrated that almost all core active ingredients exhibited satisfactory binding energies to core targets.Conclusions:This study identified a novel TCM prescription and unveiled its multi-component,multi-target and multi-pathway characteristics for treating DR.These findings provide a scientific basis and novel insights into the development of drugs for DR prevention and treatment.展开更多
The study aims to recognize how efficiently Educational DataMining(EDM)integrates into Artificial Intelligence(AI)to develop skills for predicting students’performance.The study used a survey questionnaire and collec...The study aims to recognize how efficiently Educational DataMining(EDM)integrates into Artificial Intelligence(AI)to develop skills for predicting students’performance.The study used a survey questionnaire and collected data from 300 undergraduate students of Al Neelain University.The first step’s initial population placements were created using Particle Swarm Optimization(PSO).Then,using adaptive feature space search,Educational Grey Wolf Optimization(EGWO)was employed to choose the optimal attribute combination.The second stage uses the SVMclassifier to forecast classification accuracy.Different classifiers were utilized to evaluate the performance of students.According to the results,it was revealed that AI could forecast the final grades of students with an accuracy rate of 97%on the test dataset.Furthermore,the present study showed that successful students could be selected by the Decision Tree model with an efficiency rate of 87.50%and could be categorized as having equal information ratio gain after the semester.While the random forest provided an accuracy of 28%.These findings indicate the higher accuracy rate in the results when these models were implemented on the data set which provides significantly accurate results as compared to a linear regression model with accuracy(12%).The study concluded that the methodology used in this study can prove to be helpful for students and teachers in upgrading academic performance,reducing chances of failure,and taking appropriate steps at the right time to raise the standards of education.The study also motivates academics to assess and discover EDM at several other universities.展开更多
The aviation industry is a sector that is developing, changing and growing every day in terms of technological and legal framework. There are generally three factors that enable airlines to hold on to the market. Thes...The aviation industry is a sector that is developing, changing and growing every day in terms of technological and legal framework. There are generally three factors that enable airlines to hold on to the market. These factors are safety, service quality and price. Airline companies can analyze the customers in the market with a focus on price and quality and develop a business model according to their expectations. For example, business class and economy class passenger expectations are different from each other, so the service and price to be offered to them will be different. However, all customers have one common expectation and that is safety. No matter how high quality the service is or how cheap the price is, no one wants to fly with an airline or plane that is not safe. From an airline company’s point of view, an accident or breakdown of one of the company’s aircraft can cause irreparable image loss and financial damage. If we look at past examples, we see that there are many airline companies or maintenance organizations that could not recover after an accident and went bankrupt. Safety is an indispensable factor. Therefore, there is a unit in the sector called the safety management system (SMS), which collects data by taking a proactive and reactive approach. The way and purpose of the safety management system is to take a proactive approach to recognize and prevent unsafe situations before they cause accidents or breakdowns, or to take a reactive approach to find the causes of accidents and breakdowns that have occurred as a result of certain factors and to take the necessary measures to prevent the same situations from happening again in the sector. The field of data mining, which is necessary to predict the future behavior of customers in the field of marketing, is an area that marketing also values. In this study, data mining studies to ensure safety in the aviation industry and the security of customer information in marketing will be emphasized, firstly, the concept and importance of data mining will be mentioned.展开更多
Background: The severe visual damage or blindness is usually mainly caused by retinal diseases in all age groups. Traditional Chinese medicine (TCM) prescriptions containing Chrysanthemi Flos are commonly used for bri...Background: The severe visual damage or blindness is usually mainly caused by retinal diseases in all age groups. Traditional Chinese medicine (TCM) prescriptions containing Chrysanthemi Flos are commonly used for brightening eyes and have shown good clinical value for treating retinal diseases. This study aimed to screen a novel TCM prescription against retinal diseases based on patents containing Chrysanthemi Flos and explores its medication rule and mechanism using data mining, network pharmacology, molecular docking and molecular dynamics simulation. Methods: Data mining approach was used to screen a novel TCM prescription against retinal diseases and explore its medication rule. The mechanism of the novel TCM prescription against retinal diseases was revealed by constructing the network of TCMs-core active ingredients-core targets-core pathways using network pharmacology. Molecular docking and molecular dynamics simulation were performed to confirm the binding ability between core active ingredients and core targets. Results: TCM prescriptions with clearing heat and supplementing activities were applied most to treat three types of retinal diseases including glaucoma, diabetic retinopathy and age-related macular degeneration. These TCM prescriptions mainly possessed bitter and cold properties and were associated with the liver and lung meridians. A novel TCM prescription consisting of Chrysanthemi Flos, Cassiae Semen, Lycii Fructus, Angelicae Sinensis Radix and Salviae Miltiorrhizae Radix et Rhizoma was screened for the first time. Eighteen compounds were found to be the core active ingredients, modulating sixteen core targets including STAT3, MAPK3, AKT1, PIK3CA, EGFR and TP53, which may involve fifteen core pathways such as the AGE-RAGE signaling pathway in diabetic complications, MAPK signaling pathway, PI3K-Akt signaling pathway, HIF-1 signaling pathway and EGFR tyrosine kinase inhibitor resistance. Molecular docking and molecular dynamics simulation showed a strong binding affinity between almost all of the core active ingredients and targets. Conclusion: The novel TCM prescription has the potential to treat retinal diseases by inhibiting the inflammatory response, oxidative stress, retinal neovascularization, and apoptosis of retinal ganglion cells and retinal pigment epithelium cells as well as ameliorating retinal structural impairment through core targets and signaling pathways. This is the first study to screen a novel TCM prescription against retinal diseases, and provides reliable evidence and promising directions for new drug development.展开更多
Background:Using network pharmacology to explore the potential molecular mechanism of traditional Chinese medicine in treating polycystic ovary syndrome(PCOS)with kidney deficiency and blood stasis syndrome.Method:Col...Background:Using network pharmacology to explore the potential molecular mechanism of traditional Chinese medicine in treating polycystic ovary syndrome(PCOS)with kidney deficiency and blood stasis syndrome.Method:Collect the related literature materials of PCOS with kidney deficiency and blood stasis syndrome treated by traditional Chinese medicine in four databases in recent ten years,extract the information of prescriptions and complete the frequency analysis.Traditional Chinese Medicine Systems Pharmacology Database was used to screen out the effective components.Use Online Mendelian Inheritance in Man and other databases to screen PCOS disease targets.The intersection targets obtained by clustering prescription and PCOS disease targets were submitted to STRING database for protein-protein interaction network analysis,and Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes pathways were analysed by Metascape.Result:There are 155 kinds of traditional Chinese medicines used in the literature.The most commonly utilized ones are Cuscutae Semen,Angelicae Sinensis Radix,and Rehmanniae Radix Praeparata.The results of the cluster analysis indicated that the plants most commonly found throughout the prescription were Leonuri Herba,Lycopi Herba,Dipsaci Radix,etc.GO results show that biological processes include cell reaction to organic nitrogen compounds and cell reaction to nitrogen compounds.The functional display of GO molecule includes cytokine receptor binding,signal receptor regulator activity and so on.Kyoto Encyclopedia of Genes and Genomes results show that the possible mechanisms of action are cancer pathway,an endocrine resistance signal pathway.Conclusion:Through data mining,the cluster prescription for PCOS with kidney deficiency and blood stasis syndrome is Leonuri Herba,Lycopi Herba,Dipsaci Radix,etc.The network pharmacology research of cluster prescription shows that the main drug components for treating PCOS with kidney deficiency and blood stasis syndrome are quercetin,kaempferol,luteolin,tanshinone IIA,etc.,which act on PTGS2,NCOA2,and other targets,and treat PCOS with kidney deficiency and blood stasis syndrome through cancer and endocrine resistance.展开更多
The teaching quality evaluation system based on data mining technology can accurately and fairly identify the core driving factors to improve teaching quality.This method adopts the analysis of big data correlation ru...The teaching quality evaluation system based on data mining technology can accurately and fairly identify the core driving factors to improve teaching quality.This method adopts the analysis of big data correlation rules,including data collection and processing preparation steps,builds the data warehouse of association rules,and then generates an educational quality evaluation framework using the principle of data mining.Based on this,this paper analyzes the construction design and method of the teaching evaluation system under data mining,hoping to provide help for the improvement of the teaching evaluation system and the improvement of teaching quality.展开更多
Data mining is the process of extracting implicit but potentially useful information from incomplete, noisy, and fuzzy data. Data mining offers excellent nonlinear modeling and self-organized learning, and it can play...Data mining is the process of extracting implicit but potentially useful information from incomplete, noisy, and fuzzy data. Data mining offers excellent nonlinear modeling and self-organized learning, and it can play a vital role in the interpretation of well logging data of complex reservoirs. We used data mining to identify the lithologies in a complex reservoir. The reservoir lithologies served as the classification task target and were identified using feature extraction, feature selection, and modeling of data streams. We used independent component analysis to extract information from well curves. We then used the branch-and- bound algorithm to look for the optimal feature subsets and eliminate redundant information. Finally, we used the C5.0 decision-tree algorithm to set up disaggregated models of the well logging curves. The modeling and actual logging data were in good agreement, showing the usefulness of data mining methods in complex reservoirs.展开更多
Different acupuncture-moxibustion therapies can produce different clinical effects, that is, the effect has specificity, which is significantly important in obtaining acupuncture-moxibustion efficacy. In this study, t...Different acupuncture-moxibustion therapies can produce different clinical effects, that is, the effect has specificity, which is significantly important in obtaining acupuncture-moxibustion efficacy. In this study, the clinical application laws of fire needle, acupoint injection, catgut embedment, acupoint application, moxibustion therapy and filiform needle acupuncture were summarized in the aspects of category of disease, efficacy and related prescriptions （such as medication and acupoint selection） based on the result of data mining, and the general applicable categories of disease of acupuncture-moxibustion treatment methods were further screened, so as to guide the clinical application and give play to the best efficacy.展开更多
Privacy is a critical requirement in distributed data mining. Cryptography-based secure multiparty computation is a main approach for privacy preserving. However, it shows poor performance in large scale distributed s...Privacy is a critical requirement in distributed data mining. Cryptography-based secure multiparty computation is a main approach for privacy preserving. However, it shows poor performance in large scale distributed systems. Meanwhile, data perturbation techniques are comparatively efficient but are mainly used in centralized privacy-preserving data mining (PPDM). In this paper, we propose a light-weight anonymous data perturbation method for efficient privacy preserving in distributed data mining. We first define the privacy constraints for data perturbation based PPDM in a semi-honest distributed environment. Two protocols are proposed to address these constraints and protect data statistics and the randomization process against collusion attacks: the adaptive privacy-preserving summary protocol and the anonymous exchange protocol. Finally, a distributed data perturbation framework based on these protocols is proposed to realize distributed PPDM. Experiment results show that our approach achieves a high security level and is very efficient in a large scale distributed environment.展开更多
基金Henan Province Special Research Project of Tra ditional Chinese Medicine(Grant No.2022ZY1090).
文摘In the present study,data mining and network pharmacology were utilized to explore the principles and mechanisms of traditional Chinese medicine(TCM)in treating acute appendicitis.The goal was to provide a scientific basis for clinical treatment and further research on this disease.First,we searched the National Patent Database for Chinese herbal compound prescriptions used to treat acute appendicitis.We then applied frequency analysis,character and taste meridian analysis,association rule analysis,and hierarchical cluster analysis to identify the patterns of TCM treatment for acute appendicitis,selecting key combinations of Chinese medicines.Next,we screened the main active components of these key TCM based on quality markers.Using databases such as SwissTargetPrediction,SymMap,ETCM,and STRING,we analyzed the pharmacological mechanisms of these key TCM in treating acute appendicitis.Key active components and targets were further verified through molecular docking.We identified a total of 129 patents involving 316 Chinese medicines,with 24 being frequently used.The results indicated that most Chinese herbs used for acute appendicitis were heat-clearing drugs,blood-activating and stasis-removing drugs,and purging drugs.The primary active ingredients of the Rhubarb-cortex moutan-flos lonicerae combination for treating acute appendicitis included Emodin,Paeonol,Physcion,Chlorogenic acid,Chrysophanol,Rhein acid,and Aloe-emodin.These ingredients targeted key proteins such as ALB,TP53,BCL2,STAT3,IL-6,and TNF,and were involved in cellular responses to lipopolysaccharides,cell composition,and various cytokine-mediated biological processes.They also interacted with signaling pathways like AGE-RAGE,TNF,IL-17,and FoxO.Based on patent data,this study analyzed medication patterns in the treatment of acute appendicitis,discussed the possible mechanisms of key TCM combinations,and provided a scientific basis and new perspectives for the diagnosis and treatment of the disease.
文摘Introduction Neurosurgical emergencies such as spontaneous intracerebral hemorrhage(ICH),traumatic brain injury(TBI),and acute brain herniation are among the most time-sensitive and high-stakes conditions in modern medicine.Clinical decisions often must be made within minutes,yet these decisions are traditionally guided by limited information,heuristic reasoning,and past experience.In this context,the rise of medical data mining and real-time analytics offers a transformative opportunity:to extract actionable intelligence from the flood of clinical,imaging,and physiological data already being collected,and to use this intelligence to guide care in real time[1–3](Figure 1).
文摘With the gradual acceleration of information construction in colleges and universities,digital campus and smart campus have gradually become important means for colleges and universities to scientifically manage the campus.They have been applied to teaching,scientific research,student management,and other fields,improving the quality and efficiency of management.This paper mainly studies the intelligent educational administration management system based on data mining technology.Firstly,this paper introduces the application process of data mining technology,and builds an intelligent educational administration management system based on data mining technology.Then,this paper optimizes the application of the Apriori algorithm in educational administration management through transaction compression and frequent sampling.Compared with the traditional Apriori algorithm,the optimized Apriori algorithm in this paper has a shorter execution time under the same minimum support.
基金Supported by Shanghai College Students Innovation and Entrepreneurship Training Program Project:202310268066The 16th Batch of Science And Technology Innovation Projects of Shanghai University of Traditional Chinese Medicine:SHUTCM2023010+1 种基金2024 Shanghai Oriental Talent Program Youth Project2021 High-level Local University Innovation Team Project of Shanghai University of Traditional Chinese Medicine:No.3 Shanghai Education Commission Personnel [2022]。
文摘Objective To explore the optimization and principles of acupoint selection and coordination in the treatment of adult abdominal obesity using acupuncture and moxibustion over the past decade using data mining.Methods Clinical studies of abdominal obesity treated with acupuncture and moxibustion,collected in the past 10 years,were searched from China Biology Medicine disc(CBMdisc),China National knowledge infrastructure(CNKI),Wanfang,China Science and Technology Journal Database(VIP),Pubmed,Embase,Google Scholar,Web of Science,(The Cumulative Index to Nursing and Allied Health Literature)CINAHL,Psyclnfo and Scopus,dated from March 1,2013 to March 31,2023.Using IBM SPSS Modeler 18.0 and other software,the frequency analysis,association-rules analysis and cluster analysis were conducted on interventions,traditional Chinese medicine(TCM)patterns,use frequency of acupoint,meridian attribution of acupoint,acupoint location,etc.Results A total of 55 articles were included,with 102 prescriptions and 71 acupoints involved.The top 3 interventions were acupoint embedding method,simple electroacupuncture and simple filiform needling.Seventeen patterns/syndromes of TCM differentiation were collected,dominated by spleen deficiency and damp blockage,spleen and kidney yang deficiency and heat accumulation in stomach and intestines.The acupoints in clinical practice were mostly at the foot-yangming stomach meridian,the conception vessel and the foot-taiyin spleen meridian,and located at the abdominal region.The top 5 acupoints of high frequency were Tianshu(ST25),Zhongwan(CV12),Daheng(SP15),Zusanli(ST36),Huaroumen(ST24)and Daimai(GB26).The specific points of the high frequency were the crossing points and front-mu points,of which,ST25 and CV12 were the most prominent.After association-rules analysis on the high-frequency acupoints,20 groups of associated acupoints were obtained,in which,the core acupoints included ST25,CV12,SP15 and ST36.Conclusion In recent 10 years,abdominal obesity is treated by the acupoints of foot-yangming stomach meridian,the conception vessel and the foot-taiyin spleen meridian.Compared with the regimen for simple obesity,the acupoints at the abdominal region are specially selected in treatment of abdominal obesity,such as ST25,CV12,SP15 and ST36.Supplementary acupoints are selected based on syndrome differentiation to simultaneously address both the disease manifestations and root causes.
基金Song Hujie’s Inheritance Studio of National Renowned Traditional Chinese Medicine Experts.
文摘Objective:To explore the core acupuncture acupoints and pattern-adapted acupoint combination rules for autism spectrum disorder(ASD)complicated with sleep disorder using clinical data mining technology.Methods:A retrospective analysis was conducted on the diagnosis and treatment data of 104 children with ASD complicated with sleep disorder admitted to Xi’an Traditional Chinese Medicine(TCM)Encephalopathy Hospital from January 2022 to December 2024.Cross-pattern main acupoints were screened via frequency statistics,chi-square test,and factor analysis;pattern-specific auxiliary acupoints were extracted by combining multiple correspondence analysis,cluster analysis,and association rule mining.Results:Ten cross-pattern main acupoints(Baihui,Sishenzhen,Language Area 1,Language Area 2,Neiguan,Shenmen,Yongquan,Xuanzhong)were identified,and acupoint combination schemes for four major TCM patterns(Hyperactivity of Liver and Heart Fire,Deficiency of Kidney Essence,Deficiency of Both Heart and Spleen,Hyperactivity of Liver with Spleen Deficiency)were established.Conclusion:Acupuncture treatment should follow the principle of“regulating spirit and calming the brain as the root,and dredging collaterals based on pattern differentiation as the branch”.The synergy between main and auxiliary acupoints can accurately regulate the disease,providing a basis for precise clinical treatment.
文摘In light of the rapid growth and development of social media, it has become the focus of interest in many different scientific fields. They seek to extract useful information from it, and this is called (knowledge), such as extracting information related to people’s behaviors and interactions to analyze feelings or understand the behavior of users or groups, and many others. This extracted knowledge has a very important role in decision-making, creating and improving marketing objectives and competitive advantage, monitoring events, whether political or economic, and development in all fields. Therefore, to extract this knowledge, we need to analyze the vast amount of data found within social media using the most popular data mining techniques and applications related to social media sites.
基金supported by the Natural Science Foundation of Shandong Province,China(Grant No.ZR2021QD032)。
文摘Since the impoundment of Three Gorges Reservoir(TGR)in 2003,numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall.One case is the Outang landslide,a large-scale and active landslide,on the south bank of the Yangtze River.The latest monitoring data and site investigations available are analyzed to establish spatial and temporal landslide deformation characteristics.Data mining technology,including the two-step clustering and Apriori algorithm,is then used to identify the dominant triggers of landslide movement.In the data mining process,the two-step clustering method clusters the candidate triggers and displacement rate into several groups,and the Apriori algorithm generates correlation criteria for the cause-and-effect.The analysis considers multiple locations of the landslide and incorporates two types of time scales:longterm deformation on a monthly basis and short-term deformation on a daily basis.This analysis shows that the deformations of the Outang landslide are driven by both rainfall and reservoir water while its deformation varies spatiotemporally mainly due to the difference in local responses to hydrological factors.The data mining results reveal different dominant triggering factors depending on the monitoring frequency:the monthly and bi-monthly cumulative rainfall control the monthly deformation,and the 10-d cumulative rainfall and the 5-d cumulative drop of water level in the reservoir dominate the daily deformation of the landslide.It is concluded that the spatiotemporal deformation pattern and data mining rules associated with precipitation and reservoir water level have the potential to be broadly implemented for improving landslide prevention and control in the dam reservoirs and other landslideprone areas.
基金National Natural Science Foundation of China(82360905)Gansu Provincial University Teachers'Innovation Fund Projects(2023A-092 and 2024B-109).
文摘Objective To explore the medication rules of traditional Chinese medicine(TCM)and mechanism of action of hub herb pairs for treating insomnia.Methods Totally 104 prescriptions were statistically analyzed.The association rule algorithm was applied to mine the hub herb pairs.Network pharmacology was utilized to analyze the mechanism of the hub herb pairs,while molecular docking was applied to simulate the interaction between receptors and herb molecules,thereby predicting their binding affinities.Results The most frequently used herbs in TCM prescriptions for treating insomnia included Semen Ziziphi Spinosae,Radix Glycyrrhizae,Radix et Rhizoma Ginseng,and Poria cum Radix Pini.Among them,the most commonly used were the supplementing herbs,followed by heat-clearing,mind-calming,and exterior-releasing ones,with their properties of warm and cold,flavors of sweet,Pungent,and bitter,and meridian tropisms of liver,lungs,spleen,kidneys,heart,and stomach.The hub herb pairs based on the association rules included Radix Astragali-Radix et Rhizoma Ginseng,Rhizoma Chuanxiong-Radix Glycyrrhizae,Seman Platycladi-Semen Ziziphi Spinosae,Pericarpium Citri Reticulatae-Radix Glycyrrhizae,Radix Polygalae-Semen Ziziphi Spinosae,and Radix Astragali-Semen Ziziphi Spinosae.Network pharmacology revealed that the cAMP signaling pathway might play a key role in treating insomnia synergistically with HIF-1 signaling pathway,prolactin signaling pathway,chemical carcinogenesis receptor activation,and PI3K-Akt signaling pathway.Molecular docking indicated that there was good binding between the active ingredients of the hub herb pairs and the hub targets.Conclusions This study identified six hub herb pairs for treating insomnia in TCM.These hub herb pairs may synergistically treat insomnia with HIF-1 signaling pathway,prolactin signaling pathway,chemical carcinogenesis receptor activation,and PI3K-Akt signaling pathway through the cAMP signaling pathway.
基金the support from National Natural Science Foundation of China(52274318).
文摘The correlation between the longitudinal crack occurrence and integrated heat transfer of the mold with data mining methods was investigated.Firstly,three kinds of support vector machine models based on principal component analysis with different input features were established to explore the effect of integrated heat transfer on the accuracy of the prediction model for the longitudinal crack.The results show that the accuracy was improved while features including mean and standard deviation of integrated heat transfer were added.Then,the difference in integrated heat transfer between defect and normal samples under the same process parameters was quantitatively compared.Compared with normal samples,the temperature difference of cooling water for defect samples decreased by 0.65%,and the temperature difference fluctuation increased by 31.1%.Finally,the literature data were used to provide support for the quantitative correlation according to defect formation mechanism.A new criterion for the prediction of longitudinal crack and a discovering method for correlation between product quality and process parameters in the manufacturing industry have been provided.
基金supported by a grant from Hubei Key Laboratory of Diabetes and Angiopathy Program of Hubei University of Science and Technology(2020XZ10)Project of Education Commission of Hubei Province(B2022192).
文摘Background:Erzhu Erchen decoction(EZECD),which is based on Erchen decoction and enhanced with Atractylodes lancea and Atractylodes macrocephala,is widely used for the treatment of dampness and heat(The clinical manifestations of Western medicine include thirst,inability to drink more,diarrhea,yellow urine,red tongue,et al.)internalized disease.Nevertheless,the mechanism of EZECD on damp-heat internalized Type 2 diabetes(T2D)remains unknown.We employed data mining,pharmacology databases and experimental verification to study how EZECD treats damp-heat internalized T2D.Methods:The main compounds or genes of EZECD and damp-heat internalized T2D were obtained from the pharmacology databases.Succeeding,the overlapped targets of EZECD and damp-heat internalized T2D were performed by the Gene Ontology,kyoto encyclopedia of genes and genomes analysis.And the compound-disease targets-pathway network were constructed to obtain the hub compound.Moreover,the hub genes and core related pathways were mined with weighted gene co-expression network analysis based on Gene Expression Omnibus database,the capability of hub compound and genes was valid in AutoDock 1.5.7.Furthermore,and violin plot and gene set enrichment analysis were performed to explore the role of hub genes in damp-heat internalized T2D.Finally,the interactions of hub compound and genes were explored using Comparative Toxicogenomics Database and quantitative polymerase chain reaction.Results:First,herb-compounds-genes-disease network illustrated that the hub compound of EZECD for damp-heat internalized T2D could be quercetin.Consistently,the hub genes were CASP8,CCL2,and AHR according to weighted gene co-expression network analysis.Molecular docking showed that quercetin could bind with the hub genes.Further,gene set enrichment analysis and Gene Ontology represented that CASP8,or CCL2,is negatively involved in insulin secretion response to the TNF or lipopolysaccharide process,and AHR or CCL2 positively regulated lipid and atherosclerosis,and/or including NOD-like receptor signaling pathway,and TNF signaling pathway.Ultimately,the quantitative polymerase chain reaction and western blotting analysis showed that quercetin could down-regulated the mRNA and protein experssion of CASP8,CCL2,and AHR.It was consistent with the results in Comparative Toxicogenomics Database databases.Conclusion:These results demonstrated quercetin could inhibit the expression of CASP8,CCL2,AHR in damp-heat internalized T2D,which improves insulin secretion and inhibits lipid and atherosclerosis,as well as/or including NOD-like receptor signaling pathway,and TNF signaling pathway,suggesting that EZECD may be more effective to treat damp-heat internalized T2D.
基金Supported by Municipal Public Welfare Science and Technology Project of Zhoushan Science and Technology Bureau,Zhejiang Province(2021C31064).
文摘[Objectives]To explore the trend of brands towards the design of waist protection products through data mining,and to provide reference for the design concept of the contour of waist protection pillow.[Methods]The structural design information of all waist protection equipment was collected from the national Internet platform,and the data were classified and a database was established.IBM SPSS 26.0 and MATLAB 2018a were used to analyze the data and tabulate them in Tableau 2022.4.After the association rules were clarified,the data were imported into Cinema 4D R21 to create the concept contour of waist protection pillow.[Results]The average and standard deviation of the single airbag design were the highest in all groups,with an average of 0.511 and a standard deviation of 0.502.The average and standard deviation of the upper and lower dual airbags were the lowest in all groups,with an average of 0.015 and a standard deviation of 0.120;the correlation coefficient between single airbag and 120°arc stretching was 0.325,which was positively correlated with each other(P<0.01);the correlation coefficient between multiple airbags and 360°encircling fitting was 0.501,which was positively correlated with each other and had the highest correlation degree(P<0.01).[Conclusions]The single airbag design is well recognized by companies,and has received the highest attention among all brand products.While focusing on single airbag design,most brands will consider the need to add 120°arc stretching elements in product design.At the time of focusing on multiple airbag design,some brands believe that 360°encircling fitting elements need to be added to the product,and the correlation between the two is the highest among all groups.
基金supported by the National Natural Science Foundation of China(Grant No.82104701)Science Fund Program for Outstanding Young Scholars in Universities of Anhui Province(Grant No.2022AH030064)+3 种基金Key Project at Central Government Level:the Ability Establishment of Sustainable Use for Valuable Chinese Medicine Resources(Grant No.2060302)Foundation of Anhui Province Key Laboratory of Pharmaceutical Preparation Technology and Application(Grant No.2021KFKT10)China Agriculture Research System of MOF and MARA(Grant No.CARS-21)Talent Support Program of Anhui University of Chinese Medicine(Grant No.2020rcyb007).
文摘Background:Diabetic retinopathy(DR)is currently the leading cause of blindness in elderly individuals with diabetes.Traditional Chinese medicine(TCM)prescriptions have shown remarkable effectiveness for treating DR.This study aimed to screen a novel TCM prescription against DR from patents and elucidate its medication rule and molecular mechanism using data mining,network pharmacology,molecular docking and molecular dynamics(MD)simulation.Method:TCM prescriptions for treating DR was collected from patents and a novel TCM prescription was identified using data mining.Subsequently,the mechanism of the novel TCM prescription against DR was explored by constructing a network of core TCMs-core active ingredients-core targets-core pathways.Finally,molecular docking and MD simulation were employed to validate the findings from network pharmacology.Result:The TCMs of the collected prescriptions primarily possessed bitter and cold properties with heat-clearing and supplementing effects,attributed to the liver,lung and kidney channels.Notably,a novel TCM prescription for treating DR was identified,composed of Lycii Fructus,Chrysanthemi Flos,Astragali Radix and Angelicae Sinensis Radix.Twenty core active ingredients and ten core targets of the novel TCM prescription for treating DR were screened.Moreover,the novel TCM prescription played a crucial role for treating DR by inhibiting inflammatory response,oxidative stress,retinal pigment epithelium cell apoptosis and retinal neovascularization through various pathways,such as the AGE-RAGE signaling pathway in diabetic complications and the MAPK signaling pathway.Finally,molecular docking and MD simulation demonstrated that almost all core active ingredients exhibited satisfactory binding energies to core targets.Conclusions:This study identified a novel TCM prescription and unveiled its multi-component,multi-target and multi-pathway characteristics for treating DR.These findings provide a scientific basis and novel insights into the development of drugs for DR prevention and treatment.
基金supported via funding from Prince Sattam bin Abdulaziz University Project Number(PSAU/2024/R/1445).
文摘The study aims to recognize how efficiently Educational DataMining(EDM)integrates into Artificial Intelligence(AI)to develop skills for predicting students’performance.The study used a survey questionnaire and collected data from 300 undergraduate students of Al Neelain University.The first step’s initial population placements were created using Particle Swarm Optimization(PSO).Then,using adaptive feature space search,Educational Grey Wolf Optimization(EGWO)was employed to choose the optimal attribute combination.The second stage uses the SVMclassifier to forecast classification accuracy.Different classifiers were utilized to evaluate the performance of students.According to the results,it was revealed that AI could forecast the final grades of students with an accuracy rate of 97%on the test dataset.Furthermore,the present study showed that successful students could be selected by the Decision Tree model with an efficiency rate of 87.50%and could be categorized as having equal information ratio gain after the semester.While the random forest provided an accuracy of 28%.These findings indicate the higher accuracy rate in the results when these models were implemented on the data set which provides significantly accurate results as compared to a linear regression model with accuracy(12%).The study concluded that the methodology used in this study can prove to be helpful for students and teachers in upgrading academic performance,reducing chances of failure,and taking appropriate steps at the right time to raise the standards of education.The study also motivates academics to assess and discover EDM at several other universities.
文摘The aviation industry is a sector that is developing, changing and growing every day in terms of technological and legal framework. There are generally three factors that enable airlines to hold on to the market. These factors are safety, service quality and price. Airline companies can analyze the customers in the market with a focus on price and quality and develop a business model according to their expectations. For example, business class and economy class passenger expectations are different from each other, so the service and price to be offered to them will be different. However, all customers have one common expectation and that is safety. No matter how high quality the service is or how cheap the price is, no one wants to fly with an airline or plane that is not safe. From an airline company’s point of view, an accident or breakdown of one of the company’s aircraft can cause irreparable image loss and financial damage. If we look at past examples, we see that there are many airline companies or maintenance organizations that could not recover after an accident and went bankrupt. Safety is an indispensable factor. Therefore, there is a unit in the sector called the safety management system (SMS), which collects data by taking a proactive and reactive approach. The way and purpose of the safety management system is to take a proactive approach to recognize and prevent unsafe situations before they cause accidents or breakdowns, or to take a reactive approach to find the causes of accidents and breakdowns that have occurred as a result of certain factors and to take the necessary measures to prevent the same situations from happening again in the sector. The field of data mining, which is necessary to predict the future behavior of customers in the field of marketing, is an area that marketing also values. In this study, data mining studies to ensure safety in the aviation industry and the security of customer information in marketing will be emphasized, firstly, the concept and importance of data mining will be mentioned.
基金supported by the National Natural Science Foundation of China(Grant No.82104701)Science Fund Program for Outstanding Young Scholars in Universities of Anhui Province(Grant No.2022AH030064)+5 种基金Key Project at Central Government Level:the Ability Establishment of Sustainable Use for Valuable Chinese Medicine Resources(Grant No.2060302)Youth Project of Natural Science Foundation of Anhui Province(Grant No.2208085QH268)Key Project of Natural Science Research in Universities of Anhui Province(Grant No.KJ2020A0430,KJ2021A0544)Foundation of Anhui Province Key Laboratory of Pharmaceutical Preparation Technology and Application(Grant No.2021KFKT10)China Agriculture Research System of MOF and MARA(Grant No.CARS-21)Talent Support Program of Anhui University of Chinese Medicine(Grant No.2020rcyb007).
文摘Background: The severe visual damage or blindness is usually mainly caused by retinal diseases in all age groups. Traditional Chinese medicine (TCM) prescriptions containing Chrysanthemi Flos are commonly used for brightening eyes and have shown good clinical value for treating retinal diseases. This study aimed to screen a novel TCM prescription against retinal diseases based on patents containing Chrysanthemi Flos and explores its medication rule and mechanism using data mining, network pharmacology, molecular docking and molecular dynamics simulation. Methods: Data mining approach was used to screen a novel TCM prescription against retinal diseases and explore its medication rule. The mechanism of the novel TCM prescription against retinal diseases was revealed by constructing the network of TCMs-core active ingredients-core targets-core pathways using network pharmacology. Molecular docking and molecular dynamics simulation were performed to confirm the binding ability between core active ingredients and core targets. Results: TCM prescriptions with clearing heat and supplementing activities were applied most to treat three types of retinal diseases including glaucoma, diabetic retinopathy and age-related macular degeneration. These TCM prescriptions mainly possessed bitter and cold properties and were associated with the liver and lung meridians. A novel TCM prescription consisting of Chrysanthemi Flos, Cassiae Semen, Lycii Fructus, Angelicae Sinensis Radix and Salviae Miltiorrhizae Radix et Rhizoma was screened for the first time. Eighteen compounds were found to be the core active ingredients, modulating sixteen core targets including STAT3, MAPK3, AKT1, PIK3CA, EGFR and TP53, which may involve fifteen core pathways such as the AGE-RAGE signaling pathway in diabetic complications, MAPK signaling pathway, PI3K-Akt signaling pathway, HIF-1 signaling pathway and EGFR tyrosine kinase inhibitor resistance. Molecular docking and molecular dynamics simulation showed a strong binding affinity between almost all of the core active ingredients and targets. Conclusion: The novel TCM prescription has the potential to treat retinal diseases by inhibiting the inflammatory response, oxidative stress, retinal neovascularization, and apoptosis of retinal ganglion cells and retinal pigment epithelium cells as well as ameliorating retinal structural impairment through core targets and signaling pathways. This is the first study to screen a novel TCM prescription against retinal diseases, and provides reliable evidence and promising directions for new drug development.
基金supported by Clinical observation on the treatment of diabetic peripheral neuropathy by supplementing qi,promoting blood circulation and tonifying kidney (grant mumber YJ202324).
文摘Background:Using network pharmacology to explore the potential molecular mechanism of traditional Chinese medicine in treating polycystic ovary syndrome(PCOS)with kidney deficiency and blood stasis syndrome.Method:Collect the related literature materials of PCOS with kidney deficiency and blood stasis syndrome treated by traditional Chinese medicine in four databases in recent ten years,extract the information of prescriptions and complete the frequency analysis.Traditional Chinese Medicine Systems Pharmacology Database was used to screen out the effective components.Use Online Mendelian Inheritance in Man and other databases to screen PCOS disease targets.The intersection targets obtained by clustering prescription and PCOS disease targets were submitted to STRING database for protein-protein interaction network analysis,and Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes pathways were analysed by Metascape.Result:There are 155 kinds of traditional Chinese medicines used in the literature.The most commonly utilized ones are Cuscutae Semen,Angelicae Sinensis Radix,and Rehmanniae Radix Praeparata.The results of the cluster analysis indicated that the plants most commonly found throughout the prescription were Leonuri Herba,Lycopi Herba,Dipsaci Radix,etc.GO results show that biological processes include cell reaction to organic nitrogen compounds and cell reaction to nitrogen compounds.The functional display of GO molecule includes cytokine receptor binding,signal receptor regulator activity and so on.Kyoto Encyclopedia of Genes and Genomes results show that the possible mechanisms of action are cancer pathway,an endocrine resistance signal pathway.Conclusion:Through data mining,the cluster prescription for PCOS with kidney deficiency and blood stasis syndrome is Leonuri Herba,Lycopi Herba,Dipsaci Radix,etc.The network pharmacology research of cluster prescription shows that the main drug components for treating PCOS with kidney deficiency and blood stasis syndrome are quercetin,kaempferol,luteolin,tanshinone IIA,etc.,which act on PTGS2,NCOA2,and other targets,and treat PCOS with kidney deficiency and blood stasis syndrome through cancer and endocrine resistance.
文摘The teaching quality evaluation system based on data mining technology can accurately and fairly identify the core driving factors to improve teaching quality.This method adopts the analysis of big data correlation rules,including data collection and processing preparation steps,builds the data warehouse of association rules,and then generates an educational quality evaluation framework using the principle of data mining.Based on this,this paper analyzes the construction design and method of the teaching evaluation system under data mining,hoping to provide help for the improvement of the teaching evaluation system and the improvement of teaching quality.
基金sponsored by the National Science and Technology Major Project(No.2011ZX05023-005-006)
文摘Data mining is the process of extracting implicit but potentially useful information from incomplete, noisy, and fuzzy data. Data mining offers excellent nonlinear modeling and self-organized learning, and it can play a vital role in the interpretation of well logging data of complex reservoirs. We used data mining to identify the lithologies in a complex reservoir. The reservoir lithologies served as the classification task target and were identified using feature extraction, feature selection, and modeling of data streams. We used independent component analysis to extract information from well curves. We then used the branch-and- bound algorithm to look for the optimal feature subsets and eliminate redundant information. Finally, we used the C5.0 decision-tree algorithm to set up disaggregated models of the well logging curves. The modeling and actual logging data were in good agreement, showing the usefulness of data mining methods in complex reservoirs.
基金National Natural Science Foundation of China:81072883,81173342,81473773Scientific Research Project of Hebei Education Department:Z 2014145Planned Project of Young Talents in Colleges and Universities in Hebei Province:BJ 2014047
文摘Different acupuncture-moxibustion therapies can produce different clinical effects, that is, the effect has specificity, which is significantly important in obtaining acupuncture-moxibustion efficacy. In this study, the clinical application laws of fire needle, acupoint injection, catgut embedment, acupoint application, moxibustion therapy and filiform needle acupuncture were summarized in the aspects of category of disease, efficacy and related prescriptions （such as medication and acupoint selection） based on the result of data mining, and the general applicable categories of disease of acupuncture-moxibustion treatment methods were further screened, so as to guide the clinical application and give play to the best efficacy.
基金Project supported by the National Natural Science Foundation of China (Nos. 60772098 and 60672068)the New Century Excel-lent Talents in University of China (No. NCET-06-0393)
文摘Privacy is a critical requirement in distributed data mining. Cryptography-based secure multiparty computation is a main approach for privacy preserving. However, it shows poor performance in large scale distributed systems. Meanwhile, data perturbation techniques are comparatively efficient but are mainly used in centralized privacy-preserving data mining (PPDM). In this paper, we propose a light-weight anonymous data perturbation method for efficient privacy preserving in distributed data mining. We first define the privacy constraints for data perturbation based PPDM in a semi-honest distributed environment. Two protocols are proposed to address these constraints and protect data statistics and the randomization process against collusion attacks: the adaptive privacy-preserving summary protocol and the anonymous exchange protocol. Finally, a distributed data perturbation framework based on these protocols is proposed to realize distributed PPDM. Experiment results show that our approach achieves a high security level and is very efficient in a large scale distributed environment.
