Operational requirements analysis method based on question answering of WEKG

The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering(QA) of weapons and equipment knowledge graph(WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.

Study of Axial Vibration of a Motor-Compressor System Using Operational Modal Analysis

A case study of excessive vibration on a motor-compressor system is presented in this paper.After barely two months of operation,the reciprocating compressor motor’s routine monitoring revealed excessive axial vibration amplitude.For this reason,the Operational Modal Analysis(OMA)was carried out in order to identify the pri-mary cause.According to the investigation,one of the harmonic components which was 18 times the motor’s running speed matched with a resonance frequency of 112 Hz.According to OMA study,the motor was vibrating in torsional motion because the compressor’s load had stimulated the entire motor-compressor unit at this reso-nance frequency.The analysis also demonstrates the bulging effect of the motor shaft’s axial vibration on the motor’s endplate.

Systemic immune-inflammation index combined with pediatric appendicitis score in assessing the severity and prognosis for paediatric appendicitis

BACKGROUND Pediatric appendicitis is a common cause of abdominal pain in children and is recognized as a significant surgical emergency.A prompt and accurate diagnosis is essential to prevent complications such as perforation and peritonitis.AIM To investigate the predictive value of the systemic immune-inflammation index(SII)combined with the pediatric appendicitis score(PAS)for the assessment of disease severity and surgical outcomes in children aged 5 years and older with appendicitis.METHODS Clinical data of 104 children diagnosed with acute appendicitis were analyzed.The participants were categorized into the acute appendicitis group and chronic appendicitis group based on disease presentation and further stratified into the good prognosis group and poor prognosis group based on prognosis.The SII and PAS were measured,and a joint model using the combined SII and PAS was constructed to predict disease severity and surgical outcomes.RESULTS Significant differences were observed in the SII and PAS parameters between the acute appendicitis group and chronic appendicitis group.Correlation analysis showed associations among the SII,PAS,and disease severity,with the combined SII and PAS model demonstrating significant predictive value for assessing disease severity[aera under the curve(AUC)=0.914]and predicting surgical outcomes(AUC=0.857)in children aged 5 years and older with appendicitis.CONCLUSION The study findings support the potential of integrating the SII with the PAS for assessing disease severity and predicting surgical outcomes in pediatric appendicitis,indicating the clinical utility of the combined SII and PAS model in guiding clinical decision-making and optimizing surgical management strategies for pediatric patients with appendicitis.

The combined detection of carcinoembryonic antigen,carcinogenic antigen 125,and carcinogenic antigen 19-9 in colorectal cancer patients

BACKGROUND Hepatic metastases are common and difficult to treat after colorectal cancer(CRC)surgery.The predictive value of carcinoembryonic antigen(CEA),cancer antigen(CA)125 and CA19-9 combined tests for liver metastasis is unclear.AIM To evaluate predictive value of combined tests for CEA,CA125,and CA19-9 levels in patients with liver metastases of CRC.METHODS The retrospective study included patients with CRC alone(50 cases)and patients with CRC combined with liver metastases(50 cases)who were hospitalized between January 2021 and January 2023.Serum CEA,CA125 and CA19-9 levels were compared between the two groups,and binary logistic regression was used to analyze the predictive value of the combination of these tumor markers in liver metastasis.In addition,we performed receiver operating characteristic(ROC)curve analysis to assess its diagnostic accuracy.RESULTS The results showed that the serum CEA,CA125 and CA19-9 levels in the CRC with liver metastasis group were significantly higher than those in the CRC alone group.Specifically,the average serum CEA level in the CRC with liver metastasis group was 162.03±810.01 ng/mL,while that in the CRC alone group was 5.71±9.76 ng/mL;the average serum CA125 levels were 43.47±83.52 U/mL respectively.and 13.5±19.68 U/mL;the average serum CA19-9 levels were 184.46±473.13 U/mL and 26.55±43.96 U/mL respectively.In addition,binary logistic regression analysis showed that CA125 was significant in predicting CRC liver metastasis(P<0.05).ROC curve analysis results showed that the areas under the ROC curves of CEA,CA125 and CA19-9 were 0.607,0.692 and 0.586.CONCLUSION These results suggest that combined detection of these tumor markers may help early detection and intervention of CRC liver metastasis,thereby improving patient prognosis.

An operational modal analysis method in frequency and spatial domain

A frequency and spatial domain decomposition method （FSDD） for operational modal analysis （OMA） is presented in this paper, which is an extension of the complex mode indicator function （CMIF） method for experimental modal analysis （EMA）. The theoretical background of the FSDD method is clarified, Singular value decomposition is adopted to separate the signal space from the noise space. Finally, an enhanced power spectrum density （PSD） is proposed to obtain more accurate modal parameters by curve fitting in the frequency domain. Moreover, a simulation case and an application case are used to validate this method.

HYBRID WAVELET PACKET-TEAGER ENERGY OPERATOR ANALYSIS AND ITS APPLICATION FOR GEARBOX FAULT DIAGNOSIS

Based on wavelet packet decomposition （WPD） algorithm and Teager energy operator （TEO）, a novel gearbox fault detection and diagnosis method is proposed. Its process is expatiated after the principles of WPD and TEO modulation are introduced respectively. The preprocessed sigaaal is interpolated with the cubic spline function, then expanded over the selected basis wavelets. Grouping its wavelet packet components of the signal based on the minimum entropy criterion, the interpolated signal can be decomposed into its dominant components with nearly distinct fault frequency contents. To extract the demodulation information of each dominant component, TEO is used. The performance of the proposed method is assessed by means of several tests on vibration signals collected from the gearbox mounted on a heavy truck. It is proved that hybrid WPD-TEO method is effective and robust for detecting and diagnosing localized gearbox faults.

Comprehensive Evaluation Model of Reservoir Operation Based on Improved Set Pair Analysis

A comprehensive evaluation model based on improved set pair analysis is established. Considering the complexity in decision-making process, the model combines the certainties and uncertainties in the schemes, i.e., identical degree, different degree and opposite degree. The relations among different schemes are studied, and the traditional way of solving uncertainty problem is improved. By using the gray correlation to determine the difference degree, the problem of less evaluation indexes and inapparent linear relationship is solved. The difference between the evaluation parameters is smaller in both the fuzzy comprehensive evaluation model and fuzzy matter-element method, and the dipartite degree of the evaluation result is unobvious. However, the difference between each integrated connection degree is distinct in the improved set pair analysis. Results show that the proposed method is feasible and it obtains better effects than the fuzzy comprehensive evaluation method and fuzzy matter-element method.

ROC analysis of CT hemodynamic in the diagnosis of breast cancer

Objective:The aim of this study was evaluate the diagnostic value of computed tomography(CT) perfusion in breast cancer by the method of receiver operator characteristic curve(ROC) analysis.Methods:Eighty-one cases with breast masses found by health examination or mammography were scanned by multi-slice spiral CT(MSCT) perfusion and hemodynamic parameters of blood flow(BF), mean transit time(MTT) and blood volume(BV) were calculated by deconvolution arithmetic.According to the pathologic results, two groups, benign and malignant were classified and statistical analysis were performed between them.The ROC characteristics of BF, MTT, BV were compared for each and the diagnostic value of the hemodynamic parameters were confirmed.Results:In the malignant group, BF was(0.735 ± 0.440) mL/min/mL, MTT was(22.771 ± 7.647) s and BV was 0.234 ± 0.082.In the benign group, BF was(0.466 ± 0.527) mL/min/mL, MTT was(26.712 ± 12.934) s and BV was 0.179 ± 0.117.There was a significant difference for BF and BV between the benign and malignant groups.When the hemodynamic parameters were used to discriminate the breast lesions, the area under the ROC curve(AUCROC) of BF was 0.832 ± 0.086, the maximum, while AUCROC of BV was 0.695 ± 0.092.There was no significant statistical difference between BF and BV.AUCROC of MTT was 0.473 ± 0.102, which was minimal.Since the threshold of BF was 0.381 mL/min/mL, the sensitivity was 82.3%, the specificity was 73.2%, the positive likelihood ratio(LR) was 3.071 and the negative LR was 0.242.The threshold of BV was 0.190 with sensitivity 73.3%, specificity 56.5%, positive likelihood ratio 1.685 and negative LR 0.473.Conclusion:BF and BV among CT hemodynamic parameters have certain diagnostic value in breast cancer, but BF or BV can not yet be single index to confirm or deny the diagnosis.

Operational Modal Analysis of a Ship Model in the Presence of Harmonic Excitation

A ship is operated under an extremely complex environment, and waves and winds are assumed to be the stochastic excitations. Moreover, the propeller, host and mechanical equipment can also induce the harmonic responses. In order to reduce structural vibration, it is important to obtain the modal parameters information of a ship. However, the traditional modal parameter identification methods are not suitable since the excitation information is difficult to obtain. Natural excitation technique-eigensystem realization algorithm （NExT-ERA） is an operational modal identification method which abstracts modal parameters only from the response signals, and it is based on the assumption that the input to the structure is pure white noise. Hence, it is necessary to study the influence of harmonic excitations while applying the NExT-ERA method to a ship structure. The results of this research paper indicate the practical experiences under ambient excitation, ship model experiments were successfully done in the modal parameters identification only when the harmonic frequencies were not too close to the modal frequencies.

Determination of the diagnostic value of the resazurin reduction assay for evaluating boar semen by receiver operating characteristic analysis

Aim： To assess that metabolic status of spermatozoa could provide a useful tool for evaluation of semen quality. Methods： The accuracy of the spectrophotometric application of the resazurin reduction assay was assessed using receiver operating characteristic （ROC） analysis. Results： Areas under ROC curves （AUC） for motile sperm concentration and sperm index （SI） （sperm concentration multiplied by the square root of percentage sperm motility multiplied by the percentage normal sperm morphology） were 0.922. The best discrimination between poor and good semen samples according to the SI was achieved at a cut-off point of A610 = 0.209, where high sensitivity （94.1%） and specificity （91.7%） were calculated. The assay was less accurate when motile sperm concentration was used as the criterion value, yielding sensitivity of 88.2% and specificity of 87.5%, respectively. Likelihood ratios （LR） indicate that absorbances lower than 0.209 were at least 11.3 times as likely to be found in good semen samples than those in poor according to the SI, whereas in the case of motile sperm concentration, the LR was calculated to be 7.06. Conclusion： These results show that the resazurin reduction assay combined with spectrophotometry is an accurate method of assessing the quality of boar semen.

Operation Analysis on T&D Equipment in Three Gorges LeftBank Hydropower Station

The paper outlines the Yangtze Three Gorges water conservancy complex. It describes the power transmission and distribution equipment in the Three Gorges LeftBank Hydropower Station, especially large high-voltage distribution devices. It elaborates the measures for suppressing GIS over-voltage and the tests on VFTO, besides technical measures to ensure safety and stability of power system in the station. It also makes some analyses and summaries about the problems encountered in operation of the equipment.

Determination of the diagnostic value of the resazurin reduction assay for evaluating boar semen by receiver operating cha-racteristic analysis

Aim:To assess that metabolic status of spermatozoa could provide a useful tool for evaluation of semen quality. Methods:The accuracy of the spectrophotometric application of the resazurm reduction assay was assessed using receiver operating characteristic(ROC)analysis.Results:Areas under ROC curves(AUC)for motile sperm concen- tration and sperm index(SI)(sperm concentration multiplied by the square root of percentage sperm motility multi- plied by the percentage normal sperm morphology)were 0.922.The best discrimination between poor and good semen samples according to the SI was achieved at a cut-off point of A_(610)=0.209,where high sensitivity(94.1%)and specificity(91.7%)were calculated.The assay was less accurate when motile sperm concentration was used as the criterion value,vielding sensitivity of 88.2% and specificity of 87.5%,respectively,Likelihood ratios(LR)indicate that absorbances lower than 0.209 were at least 11.3 times as likely to be found in good semen samples than those in poor according to the SI,whereas in the case of motile sperm concentration,the LR was calculated to be 7.06.Conclusion: These results show that the resazurin reduction assay combined with spectrophotometry is an accurate method of assessing the quality of boar semen.

Modal macro-strain identification from operational macro-strain shape under changing loading conditions

To develop modal macro-strain （ MMS ） identification techniques and improve their applicability in a continuous health monitoring system for civil infrastructures, the concept of operational macro-strain shape （OMSS） and the corresponding identification method are proposed under unknown ever-changing loading conditions, and the MMS is then obtained. The core of the proposed technique is mainly based on the specific property that the macro-strain transmissibility tends to be independent of external excitations at the poles of the system and converges to a unique value. The proposed method is verified using the experimental data from a three-span continuous beam excited by an impact hammer at different locations. The identified results are also compared with the commonly used methods, such as the peak- picking （PP） method, the stochastic subspace identification （SSI） method, and numerical results, in the case of unknown input forces. Results show that the proposed technique has unique merits in accuracy and robustness due to its combining multiple tests under changing loading conditions, which also reveal the promising application of the distributed strain sensing system in identifying MMS of operational structures, as well as in the structural health monitoring （SHM） field.

Serum N-glycan markers for diagnosing liver fibrosis induced by hepatitis B virus

BACKGROUND Hepatitis B virus (HBV) infection is the primary cause of hepatitis with chronic HBV infection,which may develop into liver fibrosis,cirrhosis and hepatocellular carcinoma.Detection of early-stage fibrosis related to HBV infection is of great clinical significance to block the progression of liver lesion.Direct liver biopsy is regarded as the gold standard to detect and assess fibrosis;however,this method is invasive and prone to clinical sampling error.In order to address these issues,we attempted to find more convenient and effective serum markers for detecting HBV-induced early-stage liver fibrosis.AIM To investigate serum N-glycan profiling related to HBV-induced liver fibrosis and verify multiparameter diagnostic models related to serum N-glycan changes.METHODS N-glycan profiles from the sera of 432 HBV-infected patients with liver fibrosis were analyzed.Significant changed N-glycan levels (peaks)(P <0.05) in differentfibrosis stages were selected in the modeling group,and multiparameter diagnostic models were established based on changed N-glycan levels by logistic regression analysis.The receiver operating characteristic (ROC) curve analysis was performed to evaluate diagnostic efficacy of N-glycans models.These models were then compared with the aspartate aminotransferase to platelet ratio index (APRI),fibrosis index based on the four factors (FIB-4),glutamyltranspeptidase platelet albumin index (S index),GlycoCirrho-test,and GlycoFibro-test.Furthermore,we combined multiparameter diagnostic models with alanine aminotransferase (ALT) and platelet (PLT) tests and compared their diagnostic power.In addition,the diagnostic accuracy of N-glycan models was also verified in the validation group of patients.RESULTS Multiparameter diagnostic models constructed based on N-glycan peak 1,3,4and 8 could distinguish between different stages of liver fibrosis.The area under ROC curves (AUROCs) of Model A and Model B were 0.890 and 0.752,respectively differentiating fibrosis F0-F1 from F2-F4,and F0-F2 from F3-F4,and surpassing other serum panels.However,AUROC (0.747) in Model C used for the diagnosis of F4 from F0-F3 was lower than AUROC (0.795) in FIB-4.In combination with ALT and PLT,the multiparameter models showed better diagnostic power (AUROC=0.912,0.829,0.885,respectively) when compared with other models.In the validation group,the AUROCs of the three combined models (0.929,0.858,and 0.867,respectively) were still satisfactory.We also applied the combined models to distinguish adjacent fibrosis stages of 432patients (F0-F1/F2/F3/F4),and the AUROCs were 0.917,0.720 and 0.785.CONCLUSION Multiparameter models based on serum N-glycans are effective supplementary markers to distinguish between adjacent fibrosis stages of patients caused by HBV,especially in combination with ALT and PLT.

Damping Identification of Bridges Under Nonstationary Ambient Vibration

This research focuses on identifying the damping ratio of bridges using nonstationary ambient vibration data. The damping ratios of bridges in service have generally been identified using operational modal analysis （OMA） based on a stationary white noise assumption for input signals. However, most bridges are generally subjected to nonstationary excitations while in service, and this violation of the basic assumption can lead to uncertainties in damping identification. To deal with nonstationarity, an amplitude-modulating function was calculated from measured responses to eliminate global trends caused by nonstationary input. A natural excitation technique （NExT）-eigensystem realization algorithm （ERA） was applied to estimate the damping ratio for a stationarized process. To improve the accuracy of OMA-based damping estimates, a comparative analysis was performed between an extracted stationary process and nonstationary data to assess the effect of eliminating nonstationarity. The mean value and standard deviation of the damping ratio for the first vertical mode decreased after signal stationarization.

High-resolution computed tomography findings independently predict epidermal growth factor receptor mutation status in groundglass nodular lung adenocarcinoma

BACKGROUND For lung adenocarcinoma with epidermal growth factor receptor(EGFR)gene mutation,small molecule tyrosine kinase inhibitors are more effective.Some patients could not obtain enough histological specimens for EGFR gene mutation detection.Specific imaging features can predict EGFR mutation status to a certain extent.AIM To assess the associations of EGFR mutations with high-resolution computerized tomography(HRCT)features in ground-glass nodular lung adenocarcinoma.METHODS This study retrospectively assessed patients with ground-glass nodular lung adenocarcinoma diagnosed between January 2011 and March 2017.EGFR gene mutations in exons 18-21 were detected.The patients were classified into mutant EGFR and wild-type groups,and general data and HRCT image characteristics were assessed.RESULTS Among 98 patients,31(31.6%)and 67(68.4%)had mutated and wild-type EGFR in exons 18-21,respectively.Gender,age,smoking history,location of lesions,morphology,edges,borders,pleural indentations,and associations of nodules with bronchus and blood vessels were comparable in both groups(all P>0.05).Patients with mutant EGFR had larger nodules than those with the wild-type(17.19±6.79 and 14.37±6.30 mm,respectively;P=0.047).Meanwhile,the vacuole/honeycomb sign was more frequent in the mutant EGFR group(P=0.011).The logistic regression prediction model included the combination of nodule size and vacuole/honeycomb sign(OR=1.120,95%CI:1.023-1.227,P=0.014)revealed a sensitivity of 83.9%,a specificity of 52.2%and an AUC of 0.698(95%CI:0.589-0.806;P=0.002).CONCLUSION Nodule size and vacuole/honeycomb features could independently predict EGFR mutation status in ground-glass nodular lung adenocarcinoma.

A refined Frequency Domain Decomposition tool for structural modal monitoring in earthquake engineering

Output-only structural identification is developed by a refined Frequency Domain Decomposition（rFDD） approach, towards assessing current modal properties of heavy-damped buildings（in terms of identification challenge）, under strong ground motions. Structural responses from earthquake excitations are taken as input signals for the identification algorithm. A new dedicated computational procedure, based on coupled Chebyshev Type Ⅱ bandpass filters, is outlined for the effective estimation of natural frequencies, mode shapes and modal damping ratios. The identification technique is also coupled with a Gabor Wavelet Transform, resulting in an effective and self-contained time-frequency analysis framework. Simulated response signals generated by shear-type frames（with variable structural features） are used as a necessary validation condition. In this context use is made of a complete set of seismic records taken from the FEMA P695 database, i.e. all 44 ＂Far-Field＂（22 NS, 22 WE） earthquake signals. The modal estimates are statistically compared to their target values, proving the accuracy of the developed algorithm in providing prompt and accurate estimates of all current strong ground motion modal parameters. At this stage, such analysis tool may be employed for convenient application in the realm of Earthquake Engineering, towards potential Structural Health Monitoring and damage detection purposes.

Fault Diagnosis of Cylindrical Grinding Machine

Based on experiment modal analysis(EMA) and operation modal analysis(OMA), the dynamic characteristics of cylindrical grinding machine were measured and provided a basis for further failure analysis.The influences of grinding parameters on dynamic characteristics were studied by analyzing the diagnostic signals extracted from racing and grinding experiments.The significant frequency of 38 Hz related to grinding wheel spindle speed of 2 307 r/min showed that the wheel spindle system was in a state of imbalan...

Overview of the New OMAH Technique for Scaling OMA Mode Shapes

Methods for scaling mode shapes determined by operational modal analysis(OMA)have been extensively investigated in the last years.A recent addition to the range of methods for scaling OMA mode shapes is the so-called OMAH technique,which is based on exciting the structure by harmonic forces applied by an actuator.By applying harmonic forces in at least one degree-of-freedom(DOF),and measuring the response in at least one response DOF,while using at least as many frequencies as the number of mode shapes to be scaled,the mode shape scaling(modal mass)of all modes of interest may be determined.In previous publications on the method the authors have proven that the technique is easy and robust to apply to both small scale and large scale structures.Also,it has been shown that the technique is capable of scaling highly coupled modes by using an extended multiple reference formulation.The present paper summarizes the theory of the OMAH method and gives recommendations of how to implement the method for best results.It is pointed out,as has been shown in previous papers,that the accuracy of the mode scaling is increased by using more than one response DOF,and by selecting DOFs with high mode shape coefficients.To determine the harmonic force and responses,it is recommended to use the three-parameter sine fit method.It is shown that by using this method,the measurement time can be kept short by using high sampling frequency and bandpass filtering whereas spectrum based methods require long measurement times.This means that even for structures with low natural frequencies,the extra measurement time for scaling the mode shapes can be kept relatively short.

Diagnostic and Prognostic Significance of Keapl mRNA Expression for Lung Cancer Based on Microarray and Clinical Information from Oncomine Database

We performed a bioinformatics analysis with validation by multiple databases,aiming to evaluate the diagnostic and prognostic value of Kelch-like ECH-associated protein 1(Keapl)mRNA for lung cancer,and to explore possible mechanisms.Diagnostic performance of Keapl mRNA was determined by receiver operating characteristic(ROC)curve analysis.Prognostic implication of Keapl mRNA was estimated by Kaplan-Meier survival analysis.Co-expressed genes with both Keapl and Nfe2L2 were identified by LinkedOmics.Mechanisms of Keapl-Nfe2L2-co-expressed genes underlying the pathogenesis of lung cancer were explored by function enrichment and pathway analysis.The ROC curve analysis determined a good diagnostic performance of Keapl mRNA for lung squamous cell carcinoma(LUSC),with an area under the ROC curve(AUC)of 0.833,sensitivity of 72.7%,and specificity of 90.6%(P<0.001).Multivariate Cox regression recognized high Keapl mRNA to be an independent risk factor of mortality for overall lung cancer[hazard ratio(HR):11.034,P=0.044],but an independent antagonistic factor for lung adenocarcinoma(LUAD)(HR:0.404,P<0.001).Validation by UALCAN and GEPIA supported Oncomine findings regarding the diagnostic value of Keapl mRNA for LUSC,but denied its prognostic value.After screening,we identified 17 co-expressed genes with both Keapl and Nfe2L2 for LUAD,and 22 for LUSC,mainly enriched in signaling pathway of oxidative stress-induced gene expression via Nrf2.In conclusion,Keapl mRNA has a good diagnostic performance,but controversial prognostic efficacy for LUSC.The pathogenesis of lung cancer is associated with Keapl-Nfe2L2-co-expressed genes by signaling pathway of oxidative stress-induced gene expression via Nrf2.