Prevalence and Risk Factors of Stroke in Inpatients with Type 2 Diabetes Mellitus in China

Objective The prevalence and the cluster characteristics of risk factors of stroke were assessed in a Chinese diabetic population.Methods Clinical data of 30693 inpatients who were diagnosed with type 2 diabetes mellitus(T2DM)and admitted between 2013 and 2018 were retrospectively analyzed.The age-standardized prevalence of stroke was estimated using the 2010 Chinese population census data,and risk factors were analyzed by multiple imputation and regression.Results The crude and standardized prevalence rates of stroke in patients with T2DM were 34.4%and 21.5%,respectively,and 85.2%of the stroke patients had ischemic stroke.Nearly half of the patients who experienced stroke had clusters of more than 4 risk factors.Compared with no-risk-factor clustering,the risk of stroke significantly increased 3-4 times in the presence of more than 4 risk-factor clusters(P<0.001).Hypertension was the most common major risk factor for ischemic stroke[odds ratio(OR),2.34;95%confidence interval(CI),2.18-2.50]and hemorrhagic stroke(OR,3.68;95%CI 2.95-4.59;P<0.001).Moreover,a 1-standard-deviation increase in fasting blood glucose(FBG)was significantly negatively correlated with ischemic stroke risk,and the same change in FBG was significantly associated with an 8%increased risk of hemorrhagic stroke.Conclusion The prevalence of stroke in patients with T2DM is rather high,and the clustering of risk factors is associated with the development of stroke in T2DM patients.Risk factors differ in different stroke subtypes.Identifying risk factors for a specific high-risk group is necessary.

Examining the Use of Scott’s Formula and Link Expiration Time Metric for Vehicular Clustering

Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms.K-clustering algorithms are simplistic,with fast performance and relative accuracy.However,their implementation depends on the initial selection of clusters number(K),the initial clusters’centers,and the clustering metric.This paper investigated using Scott’s histogram formula to estimate the K number and the Link Expiration Time(LET)as a clustering metric.Realistic traffic flows were considered for three maps,namely Highway,Traffic Light junction,and Roundabout junction,to study the effect of road layout on estimating the K number.A fast version of the PAM algorithm was used for clustering with a modification to reduce time complexity.The Affinity propagation algorithm sets the baseline for the estimated K number,and the Medoid Silhouette method is used to quantify the clustering.OMNET++,Veins,and SUMO were used to simulate the traffic,while the related algorithms were implemented in Python.The Scott’s formula estimation of the K number only matched the baseline when the road layout was simple.Moreover,the clustering algorithm required one iteration on average to converge when used with LET.

Health risk assessment of trace metal(loid)s in agricultural soils based on Monte Carlo simulation coupled with positive matrix factorization model in Chongqing, southwest China

This study aimed to investigate the pollution characteristics, source apportionment, and health risks associated with trace metal(loid)s(TMs) in the major agricultural producing areas in Chongqing, China. We analyzed the source apportionment and assessed the health risk of TMs in agricultural soils by using positive matrix factorization(PMF) model and health risk assessment(HRA) model based on Monte Carlo simulation. Meanwhile, we combined PMF and HRA models to explore the health risks of TMs in agricultural soils by different pollution sources to determine the priority control factors. Results showed that the average contents of cadmium(Cd), arsenic (As), lead(Pb), chromium(Cr), copper(Cu), nickel(Ni), and zinc(Zn) in the soil were found to be 0.26, 5.93, 27.14, 61.32, 23.81, 32.45, and 78.65 mg/kg, respectively. Spatial analysis and source apportionment analysis revealed that urban and industrial sources, agricultural sources, and natural sources accounted for 33.0%, 27.7%, and 39.3% of TM accumulation in the soil, respectively. In the HRA model based on Monte Carlo simulation, noncarcinogenic risks were deemed negligible(hazard index <1), the carcinogenic risks were at acceptable level(10^(-6)<total carcinogenic risk ≤ 10^(-4)), with higher risks observed for children compared to adults. The relationship between TMs, their sources, and health risks indicated that urban and industrial sources were primarily associated with As, contributing to 75.1% of carcinogenic risks and 55.7% of non-carcinogenic risks, making them the primary control factors. Meanwhile, agricultural sources were primarily linked to Cd and Pb, contributing to 13.1% of carcinogenic risks and 21.8% of non-carcinogenic risks, designating them as secondary control factors.

Prevalence and risk factors of depression among patients with perianal fistulizing Crohn’s disease

BACKGROUND Psychological distress,especially depression,associated with perianal fistulizing Crohn’s disease(PFCD)is widespread and refractory.However,there is a surprising paucity of studies to date that have sought to identify the prevalence and risk factors of depression associated with PFCD.AIM To estimate the prevalence of depressive symptoms and investigate the depression-related risk factors in patients with PFCD.METHODS The study was conducted in the form of survey and clinical data collection via questionnaire and specialized medical staff.Depressive symptoms,life quality,and fatigue severity of patients with PFCD were assessed by Patient Health Questionnaire-9,Inflammatory Bowel Disease Patient Quality of Life Questionnaire(IBDQ),and Inflammatory Bowel Disease(IBD)Fatigue Patient Self-assessment Scale.The basic demographic information,overall disease features,perianal clinical information,and laboratory inflammation indicators were also gathered.Multivariate regression analysis was ultimately used to ascertain the risk factors of depression associated with PFCD.RESULTS A total of 123 patients with PFCD were involved,and 56.91%were suffering from depression.According to multivariate logistic regression analysis,Perianal Disease Activity Index(PDAI)score[odds ratio(OR)=0.69,95%confidence interval(CI):0.50 to 0.95],IBDQ score(OR=0.93,95%CI:0.88 to 0.97),modified Van Assche index(OR=1.24,95%CI:1.01 to 1.53),and IBD Fatigue score(OR=1.72,95%CI:1.23 to 2.42)were independent risk factors of depression-related prevalence among patients with PFCD(P<0.05).Multiple linear regression analysis revealed that the increasing perianal modified Van Assche index(βvalue=0.166,95%CI:0.02 to 0.31)and decreasing IBDQ score(βvalue=-0.116,95%CI:-0.14 to-0.09)were independently associated with the severity of depression(P<0.05).CONCLUSION Depressive symptoms in PFCD patients have significantly high prevalence.PDAI score,modified Van Assche index,quality of life,and fatigue severity were the main independent risk factors.

Epidemiological Aspects of Obesity, Overweight and Cardiovascular Risk Factors at Associes in Semi-Urban Areas (Case of Sébikotane)

Introduction: Obesity and overweight are a public health problem. The general objective was to determine the epidemiological aspects of obesity, overweight and associated risk factors in a semi-urban environment. Patients and Methods: This was a cross-sectional, descriptive study conducted on November 28 and 29, 2023 in Sébikotane. It focused on volunteers for screening for chronic non-communicable diseases. Epidemiological and clinical data were evaluated. Results: One hundred and twenty-nine cases of obesity were recorded (28%). Two hundred and eighty-two cases were overweight or obese (61.3%). The mean age was 49.55 years, with a standard deviation of 12.41 years. The age group [40 - 49 years] was the most representative, with 85 cases (30.1%), and the majority were female, with 264 cases (93.6%). Primary education was the most common, with 75 cases (46.3%). Grade 1 obesity concerned ninety-seven cases (75.2%), and diabetes was present in thirty cases (23%). Hypertension was present in ninety-five cases (33.7%). Obesity was more marked in the age group [40 - 49 years] with 45 cases (36%). Conclusion: Obesity and overweight are a major cause of morbidity and mortality. The development and implementation of a prevention and management program is essential.

Surgical and non-surgical risk factors affecting the insufficiency of ileocolic anastomosis after first-time surgery in Crohn’s disease patients

BACKGROUND Crohn's disease(CD)often necessitates surgical intervention,particularly when it manifests in the terminal ileum and ileocecal valve.Despite undergoing radical surgery,a subset of patients experiences recurrent inflammation at the anasto-motic site,necessitating further medical attention.AIM To investigate the risk factors associated with anastomotic insufficiency following ileocecal resection in CD patients.METHODS This study enrolled 77 patients who underwent open ileocolic resection with pri-mary stapled anastomosis.Patients were stratified into two groups:Group I co-mprised individuals without anastomotic insufficiency,while Group II included patients exhibiting advanced anastomotic destruction observed endoscopically or those requiring additional surgery during the follow-up period.Surgical and non-surgical factors potentially influencing anastomotic failure were evaluated in both cohorts.RESULTS Anastomotic insufficiency was detected in 12 patients(15.6%),with a mean time interval of 30 months between the initial surgery and recurrence.The predomi-nant reasons for re-intervention included stenosis and excessive perianastomotic lesions.Factors associated with a heightened risk of anastomotic failure encompassed prolonged postoperative obstruction,anastomotic bleeding,and clinically confirmed micro-leakage.Additionally,patients in Group II exhibited preoperative malnutrition and early recurrence of symptoms related to CD.CONCLUSION Successful surgical outcomes hinge on the attainment of a fully functional anastomosis,optimal metabolic status,and clinical remission of the underlying disease.Vigilant endoscopic surveillance following primary resection facilitates the timely identification of anastomotic failure,thereby enabling noninvasive interventions.

Distribution, Mobility, and Health Risks Assessment of Trace Metals in River Sediments from Intense Agricultural Activity Areas in West Africa

The economy of West African countries is mainly based on agriculture. However, the trace metal(loid)s contamination status in rivers is relatively unknown in the region. In this work, 45 surface sediments collected from the Bandama, Comoé, and Bia Rivers in south and south eastern Côte d’Ivoire (West Africa), were analyzed for total metal concentrations and chemical speciation. The results showed that the river sediments were considerably contaminated by Cd and moderately contaminated by As, Cu, Pb, and Zn. Significant spatial variations were observed among the stations but not between the rivers. Metals Cd and Cu were likely to cause more ecological risks. The speciation analysis unravelled that the metal(loid)s partitioned mainly in the residual fraction, with the potential mobile fraction varying from 14% to 28%. The study calls for establishment of strict policies relative to the application of fertilizers and agrochemicals and mining activities to protect the environment and human health risks.

S-100β CysC和NF-κB对急性缺血性脑卒中患者静脉溶栓后出血转化的预测价值

目的 探讨急性缺血性脑卒中(AIS)外周血中S-100β、CysC和NF-κB水平对静脉溶栓后出血转化的影响及预测价值。方法 收集2019-03—2022-03接受溶栓治疗的AIS患者140例,根据溶栓后24 h是否发生出血转化(HT)将患者分为非HT组(n=112)和HT组(n=28)。比较2组一般临床资料,采用多因Logistic回归分析影响HT发生的危险因素,受试者工作特征(ROC)曲线评估S-100β、CysC和NF-κB预测HT发生的价值。结果 HT组与非HT组相比,患者年龄、发病至溶栓时间、房颤、TOAST分型、C反应蛋白、凝血酶原时间、S-100β、CysC、NF-κB、白质高信号和脑微出血等均有统计学差异(P<0.05)。Logistic多因素回归分析显示,房颤、S-100β、CysC和NF-κB为影响HT发生的危险因素。S-100β、CysC和NF-κB预测AIS患者静脉溶栓后出血转化的曲线下面积分别为0.915(0.902~0.923)、0.874(0.856~0.882)和0.789(0.771~0.796),均具有一定的预测价值。结论 S-100β、CysC和NF-κB为AIS患者静脉溶栓后HT发生的危险因素,对HT发生具有一定的预测价值。

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments, but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT) model and the K-means cluster algorithm to produce a regional landslide susceptibility map. Yanchang County, a typical landslide-prone area located in northwestern China, was taken as the area of interest to introduce the proposed application procedure. A landslide inventory containing 82 landslides was prepared and subsequently randomly partitioned into two subsets: training data(70% landslide pixels) and validation data(30% landslide pixels). Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means cluster algorithm. The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC) curve) of the proposed model was the highest, reaching 0.88,compared with traditional models(support vector machine(SVM) = 0.85, Bayesian network(BN) = 0.81,frequency ratio(FR) = 0.75, weight of evidence(WOE) = 0.76). The landslide frequency ratio and frequency density of the high susceptibility zones were 6.76/km^(2) and 0.88/km^(2), respectively, which were much higher than those of the low susceptibility zones. The top 20% interval of landslide occurrence probability contained 89% of the historical landslides but only accounted for 10.3% of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without containing more " stable" pixels. Therefore, the obtained susceptibility map is suitable for application to landslide risk management practices.

Risk Assessment of Unmanned Aerial Vehicle Flight Based on Kmeans Clustering Algorithm

To quantify unmanned aerial vehicle(UAV)flight risks in low-altitude airspace,we analyze the factors of UAV flight risks from three aspects:flight conflict,flight environment,and traffic characteristics.The aerial risk index and ground risk index of the UAV are constructed,the index screening model and the UAV flight risk assessment model are established,and a UAV flight risk assessment model based on K-means clustering has been proposed.Meanwhile,numerical simulations show the proposed method can not only evaluate the UAV flight risks effectively,but also provide technical support for UAV risk management and control.

Multiple assessments, source determination, and health risk apportionment of heavy metal(loid)s in the groundwater of the Shule River Basin in northwestern China

Global ecosystems and public health have been greatly impacted by the accumulation of heavy metal(loid)s in water.Source-specific risk apportionment is needed to prevent and manage potential groundwater contamination with heavy metal(loid)s.The heavy metal(loid)s contamination status,water quality,ecological risk,and health risk apportionment of the Shule River Basin groundwater are poorly understood.Therefore,field sampling was performed to explore the water quality and risk of heavy metal(loid)s in the groundwater of the Shule River Basin in northwestern China.A total of 96 samples were collected from the study area to acquire data for water quality and heavy metal(loid)s risk.There was noticeable accumulation of ferrum in the groundwater of the Shule River Basin.The levels of pollution were considered to be moderately low,as evaluated by the degree of contamination,heavy metal evaluation index,heavy metal pollution index,and Nemerow pollution index.The ecological risks were also low.However,an assessment of the water quality index revealed that only 58.34%of the groundwater samples had good water quality.The absolute principal component scores-multiple linear regression model was more suited for this study area than the positive matrix factorization model.There were no obvious noncarcinogenic or carcinogenic concerns for all types of receptors according to the values of the total hazard index and total carcinogenic risk.The human activities and the initial geological environment factor(65.85%)was the major source of noncarcinogenic risk(residential children:87.56%;residential adults:87.52%;recreational children:86.77%;and recreational adults:85.42%),while the industrial activity factor(16.36%)was the major source of carcinogenic risk(residential receptors:87.96%;and recreational receptors:68.73%).These findings provide fundamental and crucial information for reducing the health issues caused by heavy metal(loid)s contamination of groundwater in arid areas.

Contamination and human health risk assessment of heavy metal(loid)s in topsoil and groundwater around mining and dressing factories in Chifeng,North China

Chifeng is a concentrated mining area for non-ferrous metal minerals,as well as a key prevention and control area for heavyduty enterprises.This situation necessitates an efective ecological and human health risk assessment of heavy metal(loid)s driven by the wide distribution of metal ore processing,mining,and smelting factories in Hexigten Banner and Bairin Left Banner.We conducted surveys to assess the levels of heavy metal(loid)s(Cr,As,Pb,Cd,and Hg)in the topsoil and groundwater of the areas.The results indicated that the concentrations of As,Cd,and Pb in partial soil samples exceeded the environmental quality standards of Grade II.Based on contamination assessments,such as geoaccumulation indices and pollution indices,we inferred that Cd,Pb,and As were primary pollutants in topsoil.Potential ecological risks when considered as part of the average risk indices(RI)are up to 1626.40 and 2818.76,respectively,in the two areas.Comparative analysis revealed that Cd posed a very high potential ecological risk,followed by As.Moreover,the evaluation showed that the three exposure pathways of carcinogenic and non-carcinogenic risk followed a descending order:inhalation>ingestion>dermal contact,except for Pb.Arsenic in topsoil posed a potential non-carcinogenic risk to human health,while there were no adverse efects of As in groundwater.In addition,the average total carcinogenic risk for As in the two areas,as well as the risk of Pb in the topsoil of Bairin Left Banner and all the fve heavy metal(loid)s in groundwater,exceeded human tolerance.Pb–Zn mines caused higher human health risks.In addition,the tandem contamination of heavy metal(loid)s in soil and groundwater was not obvious.This research study provides a basis for pollution remediation to control heavy industry-induced ecological and health risks of heavy metal(loid)s.

Energy-Efficient Clustering Using Optimization with Locust Game Theory

Wireless sensor networks(WSNs)are made up of several sensors located in a specific area and powered by a finite amount of energy to gather environmental data.WSNs use sensor nodes(SNs)to collect and transmit data.However,the power supplied by the sensor network is restricted.Thus,SNs must store energy as often as to extend the lifespan of the network.In the proposed study,effective clustering and longer network lifetimes are achieved using mul-ti-swarm optimization(MSO)and game theory based on locust search(LS-II).In this research,MSO is used to improve the optimum routing,while the LS-II approach is employed to specify the number of cluster heads(CHs)and select the best ones.After the CHs are identified,the other sensor components are allo-cated to the closest CHs to them.A game theory-based energy-efficient clustering approach is applied to WSNs.Here each SN is considered a player in the game.The SN can implement beneficial methods for itself depending on the length of the idle listening time in the active phase and then determine to choose whether or not to rest.The proposed multi-swarm with energy-efficient game theory on locust search(MSGE-LS)efficiently selects CHs,minimizes energy consumption,and improves the lifetime of networks.The findings of this study indicate that the proposed MSGE-LS is an effective method because its result proves that it increases the number of clusters,average energy consumption,lifespan extension,reduction in average packet loss,and end-to-end delay.

[WS_(3)Cu_(2)]簇基超分子框的组装、结构及其三阶非线性光学响应

将二(4-吡啶)硫烷(L_(1))、4,4'-二(4-吡啶)二苯甲酮(L_(2))分别与(Et_(4)N)(Tp*WS_(3))(A)(Tp*=三(3,5-二甲基吡唑)氢合硼酸根)和[Cu(Me CN)_(4)]PF_(6)进行反应,得到2个W/Cu/S簇基超分子化合物[Tp*WS_(3)Cu_(2)(L_(1))]_(2)(PF_(6))_(2)·2Me CN·2CHCl_(3)(1·2Me CN·2CHCl_(3))和[Tp*WS_(3)Cu_(2)(L_(2))(Me CN)]_(2)(PF_(6))_(2)·4Me CN (2·4Me CN)。对配合物1·2Me CN·2CHCl_(3)和2·4Me CN分别进行了单晶X射线衍射、核磁、质谱、红外、紫外可见和元素分析表征。单晶X射线衍射分析表明,它们是由2个L_(1)/L_(2)配体连接2个[Tp*WS_(3)Cu_(2)]~+簇核形成的阳离子型簇基超分子框。核磁氢谱和高分辨电喷雾离子化质谱(HRESI-MS)证明它们在溶液中具有一定的稳定性。并利用Z扫描技术测试了超分子化合物1·2Me CN·2CHCl_(3)和2·4MeCN溶液的三阶非线性光学特性,测试结果表明它们的三阶非线性光学响应强于前驱体A。

Overexpression of proteasome 26S subunit non-ATPase 6 protein and its clinicopathological significance in intrahepatic cholangiocarcinoma

BACKGROUND Currently,intrahepatic cholangiocarcinoma(ICC)poses a continuing,significant health challenge,but the relationship has yet to be established between ICC and the proteasome 26S subunit non-ATPase 6(PSMD6).AIM To investigate the protein expression and clinicopathological significance of PSMD6 in ICC.METHODS The potential impact of the PSMD6 gene on the growth of ICC cell lines was analyzed using clustered regularly interspaced short palindromic repeat knockout screening technology.Forty-two paired specimens of ICC and adjacent noncancerous tissues were collected.PSMD6 protein expression was determined by immunohistochemistry.Receiver operating characteristic curve analysis was performed to validate PSMD6 expression level,and its association with ICC patients’various clinicopathological characteristics was investigated.RESULTS The PSMD6 gene was found to be essential for the growth of ICC cell lines.PSMD6 protein was significantly overexpressed in ICC tissues(P<0.001),but showed no significant association with patient age,gender,pathological grade,or tumor-node-metastasis stage(P>0.05).CONCLUSION PSMD6 can promote the growth of ICC cells,thus playing a pro-oncogenic role.

黄土液化作用及其次生灾害风险评估方法初探——以积石山M_(S)6.2地震为例

2023年12月18日甘肃积石山6.2级地震引发的黄土液化泥石流地质灾害,造成了大量人员伤亡和财产损失。以此为背景,系统梳理了液化调查、风险评估和风险区划的工作思路:选定地区液化的内在和诱发因子,收集并分析资料,拟定调查工作底图,以调查问卷的形式开展液化影响因素摸底工作,开展针对性的外业调查或辅以物探和钻探工作,得到土壤液化发育潜势实际材料图;其后借用常规地质灾害的评估方法,开展调查区域的易发性、易损性评价和风险评价,得到调查区风险区划图。利用此方法对积石山地震诱发的泥石流灾害进行验证,分析其液化灾害的地质环境背景、形成机理和危害特征,并对其发生的风险进行评价。文章首次提出土的液化作用及其次生灾害区域调查因子的选择和风险评估的流程,可为开展土层液化作用及其次生灾害隐患区排查、国土空间规划,特别是高烈度山区集中居住点地质安全评估和选址建议提供参考。

基于K-means聚类和随机森林的电缆风险评估及修复决策

交联聚乙烯电缆是10 kV配电系统中的重要设备,其安全性至关重要。对电缆的修复决策做出科学判断,有助于提高配电系统的安全性并降低经济成本。鉴于此,本文提出了一种基于K-means聚类和随机森林(Random forest,RF)分类模型的电缆风险评估及修复决策方法。该方法首先根据电缆的绝缘状态,定义电缆的风险等级和风险程度;然后利用K-means聚类算法对多个老化指标进行聚类以实现风险等级区间的划分,从而建立多老化指标风险矩阵;基于多老化指标风险矩阵,利用综合权重法确定多维老化指标所对应的分类标签;最后基于RF算法建立并训练电缆的修复决策分类模型,输出电缆的修复决策结果。所提方法的平均正确率达到99.70%,实现了电缆快速且可靠的修复决策。

融合专家领域知识和K-means聚类的三支风险评级方法

金融和医疗等实际环境中的决策关键在于决策风险的权衡考虑,准确预测和分类风险级别非常必要。然而,传统的群体决策关注专家评价意见的一致性和共识,对于获得客观的专家评价意见和决策质量的考虑较少,在风险评级场景中难以量化和评估决策实际效果。因此,引入数据驱动的思想,利用数据和聚类结果辅助发现专家评估意见,在三支决策理论框架下优化群体意见,改进和计算逻辑回归的判别点,并基于UCI和Kaggle的4个信贷风险和疾病诊断公开数据集,完成风险评级分类。通过数据实验的结果可以发现:与经典的机器学习方法相比,文中提出的基于群体决策的三支分类方法更加关注风险的规避,在各个数据集上的分类表现均有稳定且较优的结果,说明通过发现专家领域知识,利用数据的客观信息辅助专家评估风险有助于解决不同背景的决策问题。

滇西南1976年龙陵M_(S)7.3、M_(S)7.4双强震触发滑坡遥感解译及其构造意义

深入研究中国滇西南地区发育的龙陵-澜沧新生地震构造带对于合理划分活动地块边界及未来开展强震危险性评价工作具有重要意义。使用高分辨率卫星影像对已发生的双强震震例开展回溯研究是一种可行的技术手段。文中对震前、震后高分辨率Keyhole卫星影像进行遥感解译,结合野外验证和前人研究结果,获得了1976年M_(S)7.3、M_(S)7.4龙陵双强震触发滑坡较为完整的数据库。结果显示:1)共解译滑坡14448个,总面积为17.2km^(2),70.9%的滑坡分布在花岗岩质的岩体风化层中,单体滑坡面积集中在数百至1000m^(2)区间,多为表层风化层内的浅层滑坡,滑动距离较小;2)同震滑坡密集区与高烈度区不匹配,其空间分布显示破裂区规模约为30km,且均位于活动断裂的一侧,表明其发震构造并非为龙陵-瑞丽断裂或畹町断裂。滇西南地区共轭强震破裂可能局限了单次强震的空间规模,因此在确认未来强震危险区时应重点关注NE向与NW向构造的交会部位。

Wind Power System Risk Assessment Based on Fuzzy Clustering and Copula Function Modeling

According to the characteristics of the correlation of multiple wind farm output, this paper put forwards a modeling method based on fuzzy c-means clustering and the copula function, and correlation wind farms are inserted into IEEE-RTS79 reliability system for risk assessment. By the probabilistic load flow calculated by Monte Carlo simulation method, the probability of the accident is derived, and bus voltage and branch power flow overload risk index are defined in this paper. The results show that this method can realize the modeling of the correlation of wind power output, and the risk index can identify the weakness of the system, which can provide reference for the operation and maintenance personnel.