Theoretical and experimental study of a bi-stable piezoelectric energy harvester under hybrid galloping and band-limited random excitations

In the practical environment,it is very common for the simultaneous occurrence of base excitation and crosswind.Scavenging the combined energy of vibration and wind with a single energy harvesting structure is fascinating.For this purpose,the effects of the wind speed and random excitation level are investigated with the stochastic averaging method(SAM)based on the energy envelope.The results of the analytical prediction are verified with the Monte-Carlo method(MCM).The numerical simulation shows that the introduction of wind can reduce the critical excitation level for triggering an inter-well jump and make a bi-stable energy harvester(BEH)realize the performance enhancement for a weak base excitation.However,as the strength of the wind increases to a particular level,the influence of the random base excitation on the dynamic responses is weakened,and the system exhibits a periodic galloping response.A comparison between a BEH and a linear energy harvester(LEH)indicates that the BEH demonstrates inferior performance for high-speed wind.Relevant experiments are conducted to investigate the validity of the theoretical prediction and numerical simulation.The experimental findings also show that strong random excitation is favorable for the BEH in the range of low wind speeds.However,as the speed of the incoming wind is up to a particular level,the disadvantage of the BEH becomes clear and evident.

Causal associations between gastroesophageal reflux disease and essential hypertension: A bidirectional Mendelian randomization study

BACKGROUND Clinical studies have reported that patients with gastroesophageal reflux disease(GERD)have a higher prevalence of hypertension.AIM To performed a bidirectional Mendelian randomization(MR)analysis to investi-gate the causal link between GERD and essential hypertension.METHODS Eligible single nucleotide polymorphisms(SNPs)were selected,and weighted median,inverse variance weighted(IVW)as well as MR egger(MR-Egger)re-gression were used to examine the potential causal association between GERD and hypertension.The MR-Pleiotropy RESidual Sum and Outlier analysis was used to detect and attempt to reduce horizontal pleiotropy by removing outliers SNPs.The MR-Egger intercept test,Cochran’s Q test and“leave-one-out”sen-sitivity analysis were performed to evaluate the horizontal pleiotropy,heterogen-eities,and stability of single instrumental variable.RESULTS IVW analysis exhibited an increased risk of hypertension(OR=1.46,95%CI:1.33-1.59,P=2.14E-16)in GERD patients.And the same result was obtained in replication practice(OR=1.002,95%CI:1.0008-1.003,P=0.000498).Meanwhile,the IVW analysis showed an increased risk of systolic blood pressure(β=0.78,95%CI:0.11-1.44,P=0.021)and hypertensive heart disease(OR=1.68,95%CI:1.36-2.08,P=0.0000016)in GERD patients.Moreover,we found an decreased risk of Barrett's esophagus(OR=0.91,95%CI:0.83-0.99,P=0.043)in essential hypertension patients.CONCLUSION We found that GERD would increase the risk of essential hypertension,which provided a novel prevent and therapeutic perspectives of essential hypertension.

Genetically predicted fatty liver disease and risk of psychiatric disorders: A mendelian randomization study

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)and alcohol-related liver disease(Ar-LD)constitute the primary forms of chronic liver disease,and their incidence is progressively increasing with changes in lifestyle habits.Earlier studies have do-cumented a correlation between the occurrence and development of prevalent mental disorders and fatty liver.AIM To investigate the correlation between fatty liver and mental disorders,thus ne-cessitating the implementation of a mendelian randomization(MR)study to elu-cidate this association.METHODS Data on NAFLD and ArLD were retrieved from the genome-wide association studies catalog,while information on mental disorders,including Alzheimer's disease,schizophrenia,anxiety disorder,attention deficit hyperactivity disorder(ADHD),bipolar disorder,major depressive disorder,multiple personality dis-order,obsessive-compulsive disorder(OCD),post-traumatic stress disorder(PTSD),and schizophrenia was acquired from the psychiatric genomics consor-tium.A two-sample MR method was applied to investigate mediators in signifi-cant associations.RESULTS After excluding weak instrumental variables,a causal relationship was identified between fatty liver disease and the occurrence and development of some psychia-tric disorders.Specifically,the findings indicated that ArLD was associated with a significantly elevated risk of developing ADHD(OR:5.81,95%CI:5.59-6.03,P<0.01),bipolar disorder(OR:5.73,95%CI:5.42-6.05,P=0.03),OCD(OR:6.42,95%CI:5.60-7.36,P<0.01),and PTSD(OR:5.66,95%CI:5.33-6.01,P<0.01).Meanwhile,NAFLD significantly increased the risk of developing bipolar disorder(OR:55.08,95%CI:3.59-845.51,P<0.01),OCD(OR:61.50,95%CI:6.69-565.45,P<0.01),and PTSD(OR:52.09,95%CI:4.24-639.32,P<0.01).CONCLUSION Associations were found between genetic predisposition to fatty liver disease and an increased risk of a broad range of psychiatric disorders,namely bipolar disorder,OCD,and PTSD,highlighting the significance of preven-tive measures against psychiatric disorders in patients with fatty liver disease.

一种基于KMeans与Random Forest的异常温升捕捉方法

针对线路老化、线路过载的火灾频发问题,分析了线路老化、线路过载与异常温升之间的关联性,以电流值、线缆温度作为输入,利用KMeans聚类算法划分可能存在异常温升的区间,通过Random Forest算法识别线路过载问题,可以提前通知用户整改线路,预防火灾的发生。

Exploring the Impact of Alcohol Consumption and Smoking on Primary Open Angle Glaucoma: A Mendelian Randomization Study

Objective: Utilizing Mendelian Randomization, this study employs Single Nucleotide Polymorphisms (SNPs) as instrumental variables to explore the causal relationships between bibulosity, smoking, and Primary Open Angle Glaucoma (POAG). Methods: GWAS data for bibulosity, smoking, and POAG were obtained from the Social Science Genetic Association Consortium website and the IEU OpenGWAS Project website, respectively. Using a P-value threshold of −8, a linkage disequilibrium coefficient (r2) of 0.001, and a linkage disequilibrium region width of 10,000 kb, the data were aggregated, resulting in 6 SNPs for bibulosity and 253 SNPs for smoking. Three regression models, MR-Egger, Weighted Median Estimator (WME), and Random-Effects Inverse-Variance Weighted (IVW) were applied to analyze the causal impact of bibulosity and smoking on POAG. Results: The GWAS data for alcohol consumption and smoking were derived from European populations, while the GWAS data for Primary Open-Angle Glaucoma (POAG) were sourced from East Asian populations, with no gender restrictions. Analysis using three different regression models revealed that neither excessive alcohol consumption nor smoking significantly increased the risk of developing POAG. Specifically, the odds ratios with 95% confidence intervals for the alcohol consumption group were 0.854 (0.597 - 1.221) in MR-Egger regression, 0.922 (0.691 - 1.231) in WME regression, and 0.944 (0.711 - 1.252) in IVW regression. For the smoking group, the odds ratios were 1.146 (0.546 - 2.406) in MR-Egger regression, 0.850 (0.653 - 1.111) in WME regression, and 0.939 (0.780 - 1.131) in IVW regression. Given the significant heterogeneity in the SNPs associated with smoking, the focus was primarily on the results from the IVW regression model. Conclusion: Alcohol consumption and smoking are not significant risk factors for the development of POAG.

Understanding the educational inequalities in suicide attempts and their mediators:a Mendelian randomisation study

Background Educational inequalities in suicide have become increasingly prominent over the past decade.Elucidating modifiable risk factors that serve as intermediaries in the impact of low educational attainment on suicide has the potential to reduce health disparities.Aims To examine the risk factors that mediate the relationship between educational attainment and suicide attempts and quantify their contributions to the mediation effect.Methods We conducted a two-sample Mendelian randomisation(MR)analysis to estimate the causal effect of educational attainment on suicide attempts,utilising genome-wide association study summary statistics from the Integrative Psychiatric Research(iPSYCH;6024 cases and 44240 controls)and FinnGen(8978 cases and 368299 controls).We systematically evaluated 42 putative mediators within the causal pathway connecting reduced educational attainment to suicide attempts and employed two-step and multivariable MR to quantify the proportion of the mediated effect.Results In the combined analysis of iPSYCH and FinnGen,each standard deviation(SD)decrease in genetically predicted educational attainment(equating to 3.4 years of education)was associated with a 105%higher risk of suicide attempts(odds ratio(OR):2.05;95%confidence interval(Cl):1.81 to 2.31).0f the 42 risk factors analysed,the two-step MR identified five factors that mediated the association between educational attainment and suicide attempts.The respective proportions of mediation were 47%(95%Cl:29%to 66%)for smoking behaviour,36%(95%Cl:0%to 84%)for chronic pain,49%(95%Cl:36%to 61%)for depression,35%(95%Cl:12%to 59%)for anxiety and 26%(95%Cl:18%to 34%)for insomnia.Multivariable MR implicated these five mediators collectively,accounting for 68%(95%Cl:40%to 96%)of the total effect.Conclusions This study identified smoking,chronic pain and mental disorders as primary intervention targets for attenuating suicide risk attributable to lower educational levels in the European population.

Different effects of 24 dietary intakes on gastroesophageal reflux disease: A mendelian randomization

BACKGROUND In observational studies,dietary intakes are associated with gastroesophageal re-flux disease(GERD).AIM To conduct a two-sample mendelian randomization(MR)analysis to determine whether those associations are causal.METHODS To explore the relationship between dietary intake and the risk of GERD,we extracted appropriate single nucleotide polymorphisms from genome-wide asso-ciation study data on 24 dietary intakes.Three methods were adopted for data analysis:Inverse variance weighting,weighted median methods,and MR-Egger's method.The odds ratio(OR)and 95%confidence interval(CI)were used to eva-luate the causal association between dietary intake and GERD.RESULTS Our univariate Mendelian randomization(UVMR)results showed significant evidence that pork intake(OR,2.83;95%CI:1.76-4.55;P=1.84×10–5),beer intake(OR,2.70,95%CI:2.00-3.64;P=6.54×10–11),non-oily fish intake(OR,2.41;95%CI:1.49-3.91;P=3.59×10–4)have a protective effect on GERD.In addition,dried fruit intake(OR,0.37;95%CI:0.27-0.50;6.27×10–11),red wine intake(OR,0.34;95%CI:0.25-0.47;P=1.90×10-11),cheese intake(OR,0.46;95%CI:0.39-0.55;P=3.73×10-19),bread intake(OR,0.72;95%CI:0.56-0.92;P=0.0009)and cereal intake(OR,0.45;95%CI:0.36-0.57;P=2.07×10-11)were negatively associated with the risk of GERD.There was a suggestive asso-ciation for genetically predicted coffee intake(OR per one SD increase,1.22,95%CI:1.03-1.44;P=0.019).Multi-variate Mendelian randomization further confirmed that dried fruit intake,red wine intake,cheese intake,and cereal intake directly affected GERD.In contrast,the impact of pork intake,beer intake,non-oily fish intake,and bread intake on GERD was partly driven by the common risk factors for GERD.However,after adjusting for all four elements,there was no longer a suggestive association between coffee intake and GERD.CONCLUSION This study provides MR evidence to support the causal relationship between a broad range of dietary intake and GERD,providing new insights for the treatment and prevention of GERD.

Strong invariance principle for a counterbalanced random walk

We study a counterbalanced random walkS_(n)=X_(1)+…+X_(n),which is a discrete time non-Markovian process andX_(n) are given recursively as follows.For n≥2,X_(n) is a new independent sample from some fixed law̸=0 with a fixed probability p,andX_(n)=−X_(v(n))with probability 1−p,where v(n)is a uniform random variable on{1;…;n−1}.We apply martingale method to obtain a strong invariance principle forS_(n).

Socioeconomic traits and the risk of Barrett’s esophagus and gastroesophageal reflux disease: A Mendelian randomization study

BACKGROUND Previous observational studies have shown that the prevalence of gastroesophageal reflux disease(GERD)and Barrett’s esophagus(BE)is associated with socioeconomic status.However,due to the methodological limitations of traditional observational studies,it is challenging to definitively establish causality.AIM To explore the causal relationship between the prevalence of these conditions and socioeconomic status using Mendelian randomization(MR).METHODS We initially screened single nucleotide polymorphisms(SNPs)to serve as proxies for eight socioeconomic status phenotypes for univariate MR analysis.The inverse variance weighted(IVW)method was used as the primary analytical method to estimate the causal relationship between the eight socioeconomic status phenotypes and the risk of GERD and BE.We then collected combinations of SNPs as composite proxies for the eight socioeconomic phenotypes to perform multivariate MR(MVMR)analyses based on the IVW MVMR model.Furthermore,a two-step MR mediation analysis was used to examine the potential mediation of the associations by body mass index,major depressive disorder(MDD),smoking,alcohol consumption,and sleep duration.RESULTS The study identified three socioeconomic statuses that had a significant impact on GERD.These included household income[odds ratio(OR):0.46;95% confidence interval(95%CI):0.31-0.70],education attainment(OR:0.23;95%CI:0.18-0.29),and the Townsend Deprivation Index at recruitment(OR:1.57;95%CI:1.04-2.37).These factors were found to independently and predominantly influence the genetic causal effect of GERD.Furthermore,the mediating effect of educational attainment on GERD was found to be mediated by MDD(proportion mediated:10.83%).Similarly,the effect of educational attainment on BE was mediated by MDD(proportion mediated:10.58%)and the number of cigarettes smoked per day(proportion mediated:3.50%).Additionally,the mediating effect of household income on GERD was observed to be mediated by sleep duration(proportion mediated:9.75%)CONCLUSION This MR study shed light on the link between socioeconomic status and GERD or BE,providing insights for the prevention of esophageal cancer and precancerous lesions.

OFDMA-Based Unsourced Random Access in LEO Satellite Internet of Things

This paper investigates the low earth orbit(LEO)satellite-enabled coded compressed sensing(CCS)unsourced random access(URA)in orthogonal frequency division multiple access(OFDMA)framework,where a massive uniform planar array(UPA)is equipped on the satellite.In LEO satellite communications,unavoidable timing and frequency offsets cause phase shifts in the transmitted signals,substantially diminishing the decoding performance of current terrestrial CCS URA receiver.To cope with this issue,we expand the inner codebook with predefined timing and frequency offsets and formulate the inner decoding as a tractable compressed sensing(CS)problem.Additionally,we leverage the inherent sparsity of the UPA-equipped LEO satellite angular domain channels,thereby enabling the outer decoder to support more active devices.Furthermore,the outputs of the outer decoder are used to reduce the search space of the inner decoder,which cuts down the computational complexity and accelerates the convergence of the inner decoding.Simulation results verify the effectiveness of the proposed scheme.

How completely are randomized controlled trials of non-pharmacological interventions following concussion reported? A systematic review

Purpose:The study aimed to examine the reporting completeness of randomized controlled trials(RCTs)of non-pharmacological interventions following concussion.Methods:We searched MEDLINE,Embase,PsycInfo,CINAHL,and Web of Science up to May 2022.Two reviewers independently screened studies and assessed reporting completeness using the Template for Intervention Description and Replication(TIDieR),Consensus on Exercise Reporting Template(CERT),and international Consensus on Therapeutic Exercise aNd Training(i-CONTENT)checklists.Additional information was sought my study authors where reporting was incomplete.Risk of bias(ROB)was assessed with the Cochrane ROB-2 Tool.RCTs examining non-pharmacological interventions following concussion.Results:We included 89 RCTs(n=53 high ROB)examining 11 different interventions for concussion:sub-symptom threshold aerobic exercise,cervicovestibular therapy,physical/cognitive rest,vision therapy,education,psychotherapy,hyperbaric oxygen therapy,transcranial magnetic stimulation,blue light therapy,osteopathic manipulation,and head/neck cooling.Median scores were:TIDieR 9/12(75%;interquartile range(IQR)=5;range:5-12),CERT 17/19(89%;IQR=2;range:10-19),and i-CONTENT 6/7(86%;IQR=1;range:5-7).Percentage of studies completely reporting all items was TIDieR 35%(31/89),CERT 24%(5/21),and i-CONTENT 10%(2/21).Studies were more completely reported after publication of TIDieR(t_(87)=2.08;p=0.04)and CERT(t_(19)=2.72;p=0.01).Reporting completeness was not strongly associated with journal impact factor(TIDieR:rs=0.27;p=0.01;CERT:r_(s)=-0.44;p=0.06;i-CONTENT:r_(s)=-0.17;p=0.48)or ROB(TIDieR:rs=0.11;p=0.31;CERT:rs=0.04;p=0.86;i-CONTENT:rs=0.12;p=0.60).Conclusion:RCTs of non-pharmacological interventions following concussion demonstrate moderate to good reporting completeness,but are often missing key components,particularly modifications,motivational strategies,and qualified supervisor.Reporting completeness improved after TIDieR and CERT publication,but publication in highly cited journals and low ROB do not guarantee reporting completeness.

Efficacy of a Nutritional Cream Intervention to Treat Depression in Rescuers:A Randomized Controlled Trial

Objective To explore the effectiveness of a nutritional intervention in rescuers who screened positive for depression.Methods A randomized controlled trial design was employed.From June to August,2022,4,460 rescuers were screened using the Self-Rating Depression Scale(SDS),and 1,615 positive cases were identified.Thirty-one volunteers were recruited and randomly divided into a nutritional intervention group and a control group.The intervention group received health education and nutritional intervention(a compound paste therapy primarily composed of red roses and Seville orange flowers),while the control group received psychological education.SDS scores were assessed before and after the intervention.Results There was a statistically significant decline in SDS scores in the nutritional intervention group after the intervention(P<0.05).Furthermore,the SDS scores of the intervention group were significantly lower than those of the control group,both before and after the intervention(P<0.05).No severe adverse reactions were observed during safety evaluation.Conclusion The nutritional intervention effectively reduced the depression scores in rescuers.Early nutritional intervention is recommended for rescuers who initially screen positive for depression.

The study of lithographic variation in resistive random access memory

Reducing the process variation is a significant concern for resistive random access memory(RRAM).Due to its ultrahigh integration density,RRAM arrays are prone to lithographic variation during the lithography process,introducing electrical variation among different RRAM devices.In this work,an optical physical verification methodology for the RRAM array is developed,and the effects of different layout parameters on important electrical characteristics are systematically investigated.The results indicate that the RRAM devices can be categorized into three clusters according to their locations and lithography environments.The read resistance is more sensitive to the locations in the array(~30%)than SET/RESET voltage(<10%).The increase in the RRAM device length and the application of the optical proximity correction technique can help to reduce the variation to less than 10%,whereas it reduces RRAM read resistance by 4×,resulting in a higher power and area consumption.As such,we provide design guidelines to minimize the electrical variation of RRAM arrays due to the lithography process.

Detecting XSS with Random Forest and Multi-Channel Feature Extraction

In the era of the Internet,widely used web applications have become the target of hacker attacks because they contain a large amount of personal information.Among these vulnerabilities,stealing private data through crosssite scripting(XSS)attacks is one of the most commonly used attacks by hackers.Currently,deep learning-based XSS attack detection methods have good application prospects;however,they suffer from problems such as being prone to overfitting,a high false alarm rate,and low accuracy.To address these issues,we propose a multi-stage feature extraction and fusion model for XSS detection based on Random Forest feature enhancement.The model utilizes RandomForests to capture the intrinsic structure and patterns of the data by extracting leaf node indices as features,which are subsequentlymergedwith the original data features to forma feature setwith richer information content.Further feature extraction is conducted through three parallel channels.Channel I utilizes parallel onedimensional convolutional layers(1Dconvolutional layers)with different convolutional kernel sizes to extract local features at different scales and performmulti-scale feature fusion;Channel II employsmaximum one-dimensional pooling layers(max 1D pooling layers)of various sizes to extract key features from the data;and Channel III extracts global information bi-directionally using a Bi-Directional Long-Short TermMemory Network(Bi-LSTM)and incorporates a multi-head attention mechanism to enhance global features.Finally,effective classification and prediction of XSS are performed by fusing the features of the three channels.To test the effectiveness of the model,we conduct experiments on six datasets.We achieve an accuracy of 100%on the UNSW-NB15 dataset and 99.99%on the CICIDS2017 dataset,which is higher than that of the existing models.

Causal Relationship between Chronic Obstructive Pulmonary Disease and Abdominal Aortic Aneurysm: A Mendelian Randomization Study

Background: Chronic Obstructive Pulmonary Disease (COPD) is a chronic inflammatory lung condition associated with significant morbidity and mortality. Observational studies indicate a positive correlation between COPD and the risk of abdominal aortic aneurysm (AAA), suggesting individuals with COPD are more likely to develop AAA. However, the causal relationship between COPD and AAA remains unclear. Method: This study employed a bidirectional Mendelian Randomization (MR) approach to assess the causal relationship between COPD and AAA. A two-step MR analysis was conducted to evaluate the mediating effect of 1400 circulating metabolites between COPD and AAA. Expression quantitative trait loci (eQTL) were sourced from the MRC Integrative Epidemiology Unit (MRC-IEU) database, and MR analysis was performed using the TwoSampleMR R package. The results were filtered using the Inverse Variance Weighted (IVW) method to identify genes strongly associated with both COPD and AAA. Furthermore, the Super Exact Test R package was utilized to determine the overlapping genes between COPD and AAA. Enrichment analysis for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was conducted using the clusterProfiler R package. Protein-protein interaction (PPI) analysis was carried out using STRING v12.0. Results: The IVW method indicated a causal relationship between the risk increase of COPD and AAA (OR: 1.47, 95% CI: 1.16 - 1.86, p = 0.001). Among 1400 circulating metabolites, plasma-free proline was identified as mediating the relationship between COPD and AAA, with a mediation effect proportion of −4.6% (95% CI: −9.032%, −0.164%, p = 0.042). Additionally, PPI analysis revealed 20 functionally interrelated genes mediating the linkage between COPD and AAA. KEGG enrichment analysis showed functional enrichment of these genes in the pathway of aldosterone synthesis and secretion. Conclusion: Our study supports a causal relationship between COPD and an increased risk of AAA. Specifically, plasma-free proline and pathways related to aldosterone synthesis and secretion may play key roles in the connection between COPD and AAA.

Mendelian randomization analysis of causal relationship between cheese intake and diabetic retinopathy

AIM:To assess whether there is a possible causal link between the intake of cheese and the risk of diabetic retinopathy(DR)utilizing a two-sample Mendelian randomization(MR)analysis.METHODS:The research data were obtained from summary statistics of genome-wide association studies(GWAS).Genetic loci closely related to cheese intake were extracted as instrumental variables(IVs),and DR was the outcome variable.The data were extracted from individuals of European ethnicity.The data of cheese intake consisted of 451486 samples with 9851867 single nucleotide polymorphisms(SNPs),while the DR data consisted of 206234 samples with 16380446 SNPs.Sixty-one genetic loci closely related to cheese intake were selected as IVs.MR analysis was performed by inverse-variance weighted(IVW)method and MR-Egger regression respectively.The causal relationship between cheese intake and DR was evaluated using odds ratios(ORs)and 95%confidence intervals(CIs).Egger-intercept test was used to test horizontal pleiotropy and sensitivity analysis was performed by leave-one-out test.RESULTS:The P value of the IVW method was less than 0.05,indicating a significant negative correlation between cheese intake and DR.MR-Egger regression showed that the intercept was 0.01 with a standard error of 0.022,and a P-value of 0.634,indicating no evidence of horizontal pleiotropy affecting the IVs related to the exposure factors.Besides,heterogeneity tests confirmed the absence of heterogeneity,and the“leave-one-out”sensitivity analysis demonstrated that the results were stable.CONCLUSION:Cheese intake is causally negatively correlated with the occurrence of DR,and cheese intake could reduce the risk of DR.

An Interpolation Method for Karhunen-Loève Expansion of Random Field Discretization

In the context of global mean square error concerning the number of random variables in the representation,the Karhunen–Loève(KL)expansion is the optimal series expansion method for random field discretization.The computational efficiency and accuracy of the KL expansion are contingent upon the accurate resolution of the Fredholm integral eigenvalue problem(IEVP).The paper proposes an interpolation method based on different interpolation basis functions such as moving least squares(MLS),least squares(LS),and finite element method(FEM)to solve the IEVP.Compared with the Galerkin method based on finite element or Legendre polynomials,the main advantage of the interpolation method is that,in the calculation of eigenvalues and eigenfunctions in one-dimensional random fields,the integral matrix containing covariance function only requires a single integral,which is less than a two-folded integral by the Galerkin method.The effectiveness and computational efficiency of the proposed interpolation method are verified through various one-dimensional examples.Furthermore,based on theKL expansion and polynomial chaos expansion,the stochastic analysis of two-dimensional regular and irregular domains is conducted,and the basis function of the extended finite element method(XFEM)is introduced as the interpolation basis function in two-dimensional irregular domains to solve the IEVP.

Random Forest-Based Fatigue Reliability-Based Design Optimization for Aeroengine Structures

Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function,leading to the traditional direct Monte Claro and surrogate methods prone to unacceptable computing efficiency and accuracy.In this case,by fusing the random subspace strategy and weight allocation technology into bagging ensemble theory,a random forest(RF)model is presented to enhance the computing efficiency of reliability degree;moreover,by embedding the RF model into multilevel optimization model,an efficient RF-assisted fatigue reliability-based design optimization framework is developed.Regarding the low-cycle fatigue reliability-based design optimization of aeroengine turbine disc as a case,the effectiveness of the presented framework is validated.The reliabilitybased design optimization results exhibit that the proposed framework holds high computing accuracy and computing efficiency.The current efforts shed a light on the theory/method development of reliability-based design optimization of complex engineering structures.

A real-time intelligent lithology identification method based on a dynamic felling strategy weighted random forest algorithm

Real-time intelligent lithology identification while drilling is vital to realizing downhole closed-loop drilling. The complex and changeable geological environment in the drilling makes lithology identification face many challenges. This paper studies the problems of difficult feature information extraction,low precision of thin-layer identification and limited applicability of the model in intelligent lithologic identification. The author tries to improve the comprehensive performance of the lithology identification model from three aspects: data feature extraction, class balance, and model design. A new real-time intelligent lithology identification model of dynamic felling strategy weighted random forest algorithm(DFW-RF) is proposed. According to the feature selection results, gamma ray and 2 MHz phase resistivity are the logging while drilling(LWD) parameters that significantly influence lithology identification. The comprehensive performance of the DFW-RF lithology identification model has been verified in the application of 3 wells in different areas. By comparing the prediction results of five typical lithology identification algorithms, the DFW-RF model has a higher lithology identification accuracy rate and F1 score. This model improves the identification accuracy of thin-layer lithology and is effective and feasible in different geological environments. The DFW-RF model plays a truly efficient role in the realtime intelligent identification of lithologic information in closed-loop drilling and has greater applicability, which is worthy of being widely used in logging interpretation.

基于Random Forest和UHPLC-QTOF-MS^(E)对不同来源龟甲基原的鉴定

目的:基于超高效液相色谱串联四极杆飞行时间质谱(UHPLC-QTOF-MS^(E))分析并经数字量化处理,结合随机森林(Random Forest,RF)算法构建数据辨识模型,以实现中华草龟、巴西龟、台湾龟、鳄鱼龟、鳖甲基原的数字化鉴定。方法:经样品预处理后,对不同来源、不同批次的龟甲进行UPLC-QTOF-MS^(E)分析,并以混合样品为基准进行峰位校正、提取并经量化处理,获取反映多肽离子信息的精确质量数-保留时间数据对(Exact Mass Retention Time,EMRT)。然后基于信息增益率的特征筛选获取重要多肽离子信息,结合随机森林(RF)算法进行数据建模,同时基于内部交叉验证中的准确率(Acc)、精确率(P)、曲线下面积(AUC)等参数进行模型评价。最后基于最优模型进行龟甲基原的鉴定验证分析。结果:基于信息增益率的特征筛选,得到71个特征多肽信息,建立的RF模型具有优秀的辨识效果,准确率、精确率以及AUC均大于0.950且外部鉴定验证的正确率为100.0%。结论:基于UHPLC-QTOF-MS^(E)分析,并结合RF算法能够高效准确地实现不同来源龟甲基原的数字化鉴定,可为龟甲的质量控制及基原考证提供参考和帮助。