Accuracy Relative Error Research Articles

Research on health monitoring and damage recognition algorithm of building structures based on image processing

With the continuous deepening of the urbanization process and the progress of science and technology, people transform nature and develop nature on a larger and larger scale, among which the most iconic transformation is a variety of building structures built by people. And with the passage of time, the building structure in the perennial wind and sun, there will be signs of “illness”, if not timely treatment, it will have a huge impact on the stability and safety of the building structure. Based on this, in this paper, according to the characteristics of crack identification on the surface of concrete structure, background subtraction algorithm is selected for image noise reduction processing. Through three steps of digital image noise reduction, crack extraction and crack parameter identification, the quantitative recognition of cracks is completed and a complete system of crack parameter identification is formed. The experimental results show that the machine learning model of building structure health monitoring and damage recognition algorithm proposed in this paper has excellent statistical performance, and the relative error accuracy of recognition can be controlled within 10%.

Refined Urban Grid Simulation Planning Based on Low Carbon Goal Achievement

Abstract In this paper, a new grid planning combined with low-carbon operation simulation is proposed, a new grid planning and low-carbon operation simulation model is proposed, and the new grid planning model is investigated and illustrated from the four dimensions of constraints. For the new grid simulation planning model, the solution efficiency of the new grid planning model combined with low-carbon operation simulation is improved by the time series clustering method and the extreme scenario identification method based on the amount of lost load. Starting from the low-carbon benefit dynamics of the generation side and the consumption side, a refined urban new grid low-carbon benefit dynamic evaluation model is constructed, while the model parameters and table functions are set, and the low-carbon urban grid simulation planning based on low-carbon simulation is empirically analyzed by means of simulation analysis. The results show that in grid planning, when the carbon emission intensity is 1000gCO2/kWh, the S4 scenario only needs to add an extreme scenario in the iterative process to achieve a relative error accuracy of 0.1%, and the method of using the new grid planning and the low-carbon operation simulation model is sufficient to achieve the target of the loss of load rate and carbon emission intensity. In the evaluation of the low-carbon effect, with the increase in investment amount, the installed capacity of clean energy and the total CO2 emission reduction of the refined urban grid will show two relatively obvious upward trends.

Modeling Method of Multiplexed Sampling Electrical Parameter Characteristics Based on AIOT Sensing Module

Abstract In order to further reduce the errors arising in synchronous sampling, this paper designs a multi-channel hybrid sampling electrical parametric feature modeling method based on an AIOT sensing module in the process of design. The AIOT sensing module is used to process the received RF signals using a transconductance amplifier to improve the digitization and reconfigurability of the RF front-end circuit. The signal is transformed and calculated using the Fast Fourier Transform to obtain electrical parameters such as the amplitude of each harmonic and the power factor. The results show that the variation amplitude of the window function of the design method in this paper is generally maintained between -1.5 and 1.5, the amplitude accuracy of the active power rate is within 3.17555%, and the relative error accuracy is within 0.000951%. It can be seen that the AIOT-based sensing module can significantly improve the calculation accuracy of electrical parameters and can be applied to the process of sampling digital measurements of other power signal characteristics.

Reliability analysis of flap deflection angle based on collaborative intelligent moving Kriging model

To effectively monitor the reliability of civil aircraft flap deflection angle, combined with the quick access recorder(QAR), the collaborative intelligent moving Kriging(CIMK) method is proposed by absorbing the Kriging model, decomposition and co-ordination strategy, equilibrium optimizer(EO), and moving least square(MLS). Among them, the decomposition coordination strategy is used to deal with the relationship between the flaps left and right deflection angles. MLS is employed to select effective modeling samples and solve the undetermined coefficients of Kriging model. EO method is applied to determine optimizing the local compact support region radius of MLS. Firstly, the fault reason for flap left-right asymmetry is analyzed to clarify the main characteristic parameters in QAR data. Secondly, combined with the QAR data of relevant influencing parameters, the civil aircraft flap deflection model(limit state function) is constructed by using CIMK. Then, the reliability and influence of civil aircraft flap deflection angle are analyzed by Monte Carlo(MC) sampling method. The results show that when the flap deflection angle is 3°, the reliability is 0.450 2, and the important factors affecting the flap deflection angle are Mach number, left angle of attack, right angle of attack, etc. Compared with the response surface method(RSM), Kriging, support vector machine(SVM), and back-propagation-artificial neural network(BP-ANN), the average absolute error accuracy of the proposed method is relative improved by 53.02%, 51.43%, 49.03%, and 44.04%, the average relative error accuracy is relative improved by 68.36%, 66.76%, 64.41%, and 62.64%, and the modeling efficiency is relative improved by 50.62%, 26.35%, and 43.01% respectively compared with Kriging, SVM and BP-ANN. When the number of simulations is 103, the analysis accuracy is relative improved by 8.82%, 7.25%, 6.22%, and 3.98% respectively.

Optimization and validation of the liquid chromatography coupled to tandem mass spectrometry method for assessing octreotide release from microspheres during inflammation in rabbit models

To study the effect of acute-phase reaction (APR) of inflammation on the release of octreotide acetate microsphere (Sandostatin®, SLAR) at a clinical dose, a more sensitive liquid chromatography coupled to tandem mass spectrometry analysis method needs to be developed because of the low plasma concentrations of octreotide. Solid-phase microextraction with an Oasis® HLB μElution plate was adopted for sample preparation. Extraction recovery ranged from 65.7 % to 73.2 %, and the matrix effect was negligible. High sensitivity and an intense chromatographic peak were acquired by optimizing the chromatography and mass spectrometry conditions. The lower limit of quantitation (LLOQ) was 0.01 ng/mL based on 100 μL of plasma, and linearity ranged from 0.01 to 5.0 ng/mL. The coefficients of variations for intraday and interday precision were less than 4.4 %, and the relative error of accuracy was within 5.7 %. The validated method was successfully applied to pharmacokinetics studies of SLAR in a seven-day inflammation model of rabbits, indicating that the APR did not affected the release and pharmacokinetics of the octreotide microspheres.

The oscillating pulse arrival time as a physiological explanation regarding the difference between ECG- and Photoplethysmogram-derived heart rate variability parameters

Background and ObjectiveECG-based heart rate variability (HRV), and more recently, optical pulse rate variability (PRV) analysis used in wearables are non-invasive tools of neurocardiac investigation. Pulse arrival time (PAT) is derived from their simultaneous recording. We examined the beat-to-beat PAT in greater detail, while analyzed the PRV to HRV relationship. MethodsWe acquired 300sec ECG, photoplethysmogram (PPG), and respiratory-signals from 35 young, healthy volunteers while in a supine position including different breathing patterns. PAT at eight reference points on the PPG-side was assessed by the mean, relative precision (RP%) and spectral analysis. PRV and HRV parameters were compared by relative accuracy error (RAE) and the Bland-Altman-Ratio (BAR). ResultsPAT showed the minimum RP% at the 1/2-amplitude point whereas RP% reached the maximum at the base point; its observed fine oscillation was associated to breathing as confirmed through spectral analysis. The instantaneous slope of PPG rise is inversely proportional to the corresponding PAT. RAE and BAR showed excellent agreement in 15 of 16 analysis at time-domain, mostly excellent or moderate on frequency-domain and nonlinear analysis. The inherent difference between HRV and PRV is formally due to the difference among two consecutive PATs. Conclusion and SignificanceThe present study supported the interchangeability of HRV- and PRV-analysis. Our formalistic explanation linking successive PAT-pairs and the inborn difference between HRV and PRV may bear further implications in selecting the appropriate fiducial points, approximating PRV to HRV measures, and in creating innovative neurocardiac parameters or complex PPG models/simulators.

Quantification of Polyethylene Glycol 400 Excreted in the Urine by MALDI-TOF Mass Spectrometry.

Polyethylene glycol 400 (PEG 400) was used as a permeability probe to examine the gastrointestinal tract which can be involved in the pathogenesis of some inflammatory and autoimmune diseases. A novel methodology was developed and validated for the quantitation of PEG 400 excreted in human urine after oral administration using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). The excretion ratios were determined for the most intense ions corresponding to nine PEG 400 oligomers. The relative error of accuracy was between –6.0% and 8.5%, and the relative standard deviation (RSD) of the precision was below 15%. Our method was successfully applied in a large-scale experimental study involving nearly two hundred volunteers. Due to the large number of measurements, detailed and reliable statistical analysis was performed. No significant difference was found between the male and female group of volunteers at 0.05 significance level, except the two largest PEG oligomers. However, the average excretion ratios of the male volunteers are greater than that of the women for all the nine PEG oligomers, suggesting a difference in the intestinal permeability between men and women.

Quantitation of mycophenolic acid and metabolites by UPLC-MS/MS in renal transplant patients

Mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), specific inhibitors of lymphocyte proliferation, are commonly used as adjuvant therapy with calcineurin inhibitor agents after kidney transplantation. After administration, MMF and EC-MPS are hydrolyzed to mycophenolic acid (MPA), the active form of the drug, which must be monitored due to its narrow therapeutic window, drug–drug interactions, and large intra-and inter-individual pharmacokinetic variability despite a fixed dose. Monitoring plasma MPA level is recommended to maintain the drug within the therapeutic window, optimize its efficacy, and minimize side effects. This study aims to develop a method for quantifying MPA and its major metabolites (mycophenolic acid glucuronide [MPAG]) using on-line solid phase extraction (SPE) coupled with an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) in kidney transplant patients. The linearity of MPA and MPAG were 0.3–13.6 μg/mL and 2.6–232.9 μg/mL, respectively (r2 > 0.999). The relative error of accuracy was < 15%. The within-run and between-run imprecision was < 5.8%. No carryover, ion suppression, or ion enhancement were observed. This method was used to analysis of 351 plasma samples from renal transplant patients after MMF or EC-MPS using this method showed large pharmacokinetic variability between patients. Analysis of the same samples by

A Rapid and Sensitive UHPLC-MS/MS Method for Determination of 2, 3, 8-Trimethylellagic, a Potent Active Compound from Sanguisorba officinalis L., and Its Application in the Pharmacokinetic Study within Thrombocytopenia Rats

To investigate the pharmacokinetics of 2, 3, 8-trimethylellagic (TMEA) in rats in vivo and determine the possible effects of the pathological conditions and compatibility, a rapid and sensitive ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for quantitative determination was developed. TMEA and Artemetin (internal standard, IS) were separated on an Acquity Shim-pack GIST column with a total running time of 7 min using gradient elution at a flow rate of 0.3 mL/min. The intraday and interday relative standard deviations were &lt;9.50%, and the relative error of accuracy was between −5.70% and 2.96%. The calibration curve of TMEA demonstrated good linearity with r2 = 0.9996, with the average recovery changing from 94.77% to 102.47% and the matrix effect from 93.16% to 100.15%. Compared with the normal group, the area under the plasma concentration-time curve from time 0 to the last time of quantifiable concentration (AUC(0 − t)), area under the plasma concentration-time curve from time 0 extrapolated to infinite time (AUC(0 − ∞)), and the maximum concentration (Cmax) of TMEA increased, whereas the time of maximum concentration (Tmax) and apparent clearance (CL/F) remarkably decreased in the TMEA group. With significantly reduced CL/F, AUC(0 − t), AUC(0 − ∞), and Cmax for TMEA were increased approximately one time after combining with 3, 7-Di-O-methylducheside A (DOMA). AUC(0 − t) and Cmax for TMEA in the 2, 3, 8-trimethylellagic-3, 8-dimethoxyellagic acid-2-oxyglucoside (TMEA-DMAG) group were significantly lower than that in the TMEA group with clearly prolonged Tmax and increased CL/F. These findings indicate that the changes in the pharmacokinetic parameters of TMEA may be caused by pathological and combination conditions.

The minimal sampling frequency of the photoplethysmogram for accurate pulse rate variability parameters in healthy volunteers

ObjectiveToday mobile health-monitoring devices calculate heart rate and its variability mostly from the photoplethysmogram (PPG). Minimizing the power consumption is crucial, one option is optimizing the signal sampling rate. Present study aimed to determine the minimal sampling frequency of the PPG signal, which is sufficient for accurate heart rate variability (HRV) analysis. Methods57 high-quality, 5-minute PPG signals from healthy volunteers sampled at 1 kHz (master) were decimated by a factor of 2, 5, 10, 20, 50, 100, 200, 500, then cubic spline and parabola interpolated back to 1 ms resolution. The mean pulse rate, its standard deviation (SDNN), root mean square of successive RR-differences (RMSSD), Porta and Guzik indices (PI, GI) were calculated. Their relative accuracy error (RAE) was determined, RAE<5% was acceptable. Also, the processing times were measured. Results200ms sampling interval without interpolation is sufficient to calculate mean pulse rate with RAE<0.05%. SDNN and RMSSD require at least 20 ms sampling interval without interpolation (RAE: 1.28±0.96% and 4.25±3.59%, respectively). By both interpolations, these sampling intervals can be increased to 100 ms and 50 ms, respectively. Also, the accuracy of GI and PI can be improved by interpolation, here parabola approximation was better (GI: 20 ms versus 100 ms, PI: 50 ms versus 100 ms). Parabola approximation needs significantly less computation than cubic spline interpolation. ConclusionsFor monitoring the average heart rate, 5 Hz sampling frequency can be sufficient without interpolation in healthy subjects. Correct HRV analysis requires higher sampling rates depending on the parameter. Interpolation can improve HRV accuracy from lower temporal resolution PPGs.

On the Minimal Adequate Sampling Frequency of the Photoplethysmogram for Pulse Rate Monitoring and Heart Rate Variability Analysis in Mobile and Wearable Technology

Abstract Recently there has been great interest in photoplethysmogram signal processing. However, its minimally necessary sampling frequency for accurate heart rate variability parameters is ambiguous. In the present paper frequency-modulated 1.067 Hz cosine wave modelled the variable PPG in silico. The five-minute-long, 1 ms resolution master-signals were decimated (D) at 2-500 ms, then cubic spline interpolated (I) back to 1 ms resolution. The mean pulse rate, standard deviation, root mean square of successive pulse rate differences (RMSSD), and spectral components were computed by Varian 2.3 and compared to the master-series via relative accuracy error. Also Poincaré-plot morphology was assessed. Mean pulse rate is accurate down to 303 ms (D) and 400 ms (I). In low-variability series standard deviation required at least 5 ms (D) and 100 ms (I). RMSSD needed 10 ms (D), and 303 ms (I) in normal, whereas 2 ms (D) and 100 ms (I) in low- variability series. In the frequency domain 5 ms (D) and 100 ms (I) are required. 2 ms (D) and 100 ms (I) preserved the Poincaré-plot morphology. The minimal sampling frequency of PPG for accurate HRV analysis is higher than expected from the signal bandwidth and sampling theorem. Interpolation improves accuracy. The ratio of sampling error and expected variability should be considered besides the inherent sensitivity of the given parameter, the interpolation technique, and the pulse rate detection method.

The Optimization the Latching Mechanism Design Based on Progressive Damage Analysis

The rocket latching force is an important parameter, prevent the rocket from falling off and affect the launch of the rocket. In order to obtain the optimal engineering design of the latching bar, this paper predicts the damage failure of two kinds of latching bar, based on the continuous damage theory and the Johnson-Cook constitutive model. Compared with the experimental data, the relative error accuracy of the ultimate strength simulation for rocket latching force is reached 5%.

Development of a UHPLC-MS/MS method for the quantification of ilaprazole enantiomers in rat plasma and its pharmacokinetic application

In Korea and China, ilaprazole is a widely used proton pump inhibitor in the treatment of gastric ulcers. In this study, a specific and sensitive LC-MS/MS method has been developed and validated for the quantification of ilaprazole enantiomers in the rat plasma, using R-lansoprazole as the internal standard. The enantioseparation was achieved on a CHIRALPAK AS-RH column (4.6 mm × 150 mm, i.d. 5 μm), with a mobile phase composed of 10 mM ammonium acetate aqueous solution and acetonitrile (60:40, V/V), at a flow-rate of 0.5 mL/min. The method was validated over the concentration range of 0.5–300 ng/mL for both, R- and S -ilaprazole. The lower limit of quantification was 0.5 ng/mL for both enantiomers. The relative standard deviation (RSD) of intra- and inter-day precision of R-ilaprazole and S-ilaprazole was less than 10.9%, and the relative error accuracy (RE) ranged from −0.5%–2.0%. Finally, the method was successfully evaluated in rats in a stereoselective pharmacokinetic study of the ilaprazole racemate.

Direct Time-Domain TAN Model of 3D Multilayer Hybrid PCB: Experimental Validation

The multilayer technology constitutes the ultimate solution for the design of high-density printed circuit board (PCB). Challenging modeling method is required to predict the signal integrity (SI) of the multilayer PCB. This paper addresses an unfamiliar direct time-domain model of a 3-D multilayer hybrid PCB. The subnetwork primitive elements of the equivalent graph are constituted by lumped components, interconnect lines, vias, pads, and anti-pads. The tensorial analysis of networks (TANs) is used to solve the problem related to the graph topology in the function of the PCB design parameters. The TAN concept is based on the interaction between the primitive elements. The mesh currents constitute the proposed computational unknowns. The unfamiliar model is validated with a three-port network prototype constituted by the six-layer PCB, including passive SMD components. In the frequency domain, S-parameter validation from 100 kHz to 5 GHz is presented. By using 80-Mb/s and 0.5-Gb/s rate data patterns, the proposed TAN model is validated by both simulations and measurements in the time domain. The transient results present vector magnitude relative error accuracy lower than 15%. Thanks to the computation speed and adaptability to multilayer hybrid structures, the TAN model is a prominent approach for the SI and power integrity analyses of 3-D multilayer structures.

Simultaneous Determination and Comparative Pharmacokinetics of Fuzi Water-Soluble Alkaloids between Normal and Acute Heart Failure Rats by Ultra Performance Liquid Chromatography Method.

In order to compare the pharmacokinetics of Fuzi water-soluble alkaloids between normal and acute heart failure rats, an ultra performance liquid chromatography (UPLC) method for simultaneous determination of it in rat plasma was developed. Plasma samples were treated by protein precipitation method. Seven water-soluble alkaloids were separated on a CAPCELL column and detected under the optimized chromatography condition. The calibration curves of seven targeted components showed good linearity with r2 > 0.9990 with average recoveries from 82.72 to 103.33% and matrix effect ranged from 90.02 to 104.03%. The intra- and inter-batch relative standard deviations were <10.72%, and the relative error of accuracy was within the range of -12.79-4.44%, respectively. After oral administration, the pharmacokinetic characteristics of it were investigated. Compared with the normal group, the Cmax and AUClast (area under the plasma concentration-time curve from the time of dosing to the time of last quantifiable concentration) of seven components except 3-Methoxy-p-tyramine Hydrochloride were obviously increased with remarkable prolonged t1/2 in acute heart failure group. In conclusion, a rapid, simple and sensitive UPLC method for the simultaneous quantification of seven water-soluble alkaloids in rat plasma was developed and validated for the first time. And the study showed that the disease condition had an impact on pharmacokinetics of Fuzi water-soluble alkaloids in rats in vivo.

Optimization and validation of high performance liquid chromatography-ultra violet method for quantitation of metoprolol in rabbit plasma: application to pharmacokinetic studies

Purpose: To develop a sensitive, simple and validated high performance liquid chromatography (HPLC) analytical method for the determination of metoprolol tartrate in rabbit plasma. Methods: Mobile phase of methanol and 50 mM ammonium dihydrogen phosphate solution (50:50) at pH 3.05 was used for separation of metoprolol on BDS hypersil C18 column at a wavelength of 223 nm. Flow rate and retention time were 0.6 mL/min and 7.4 min, respectively. For pharmacokinetic study, rabbits were given an oral dose of 8 mg/kg of metoprolol in solution form. Blood samples were taken from jugular vein of the rabbits after drug administration and analysed by HPLC. Results: Separation of metoprolol was not interfered with other components in plasma. The calibration curve was linear in the range of 25 - 1000 ng/mL (r 2 = 0.997). Lower limits of detection (LLOD) and quantitation (LLOQ) were 8.87 and 25 ng/mL, respectively. Relative standard deviation (RSD) of intraday and inter-day precision was < 14.27 and 7.61 %, respectively. Relative error of accuracy was between 4.85 and 14.37 %. Maximum plasma concentration (C max ), time to maximum plasma concentration (T max ) and half-life (t½) after metoprolol oral administration in rabbits were 186.29 ng/mL, 0.50 h and 2.27 h, respectively. Conclusion: A simple, accurate and precise HPLC-UV method for metoprolol determination in rabbit plasma has been successfully developed and applied to a pharmacokinetic study. Keywords: HPLC-UV, Metoprolol, Pharmacokinetics, Rabbit plasma, Liquid-liquid extraction, Validation

Simultaneous analysis of gemfibrozil, morphine, and its two active metabolites in different mouse brain structures using solid-phase extraction with ultra-high performance liquid chromatography and tandem mass spectrometry with a deuterated internal standard.

A rapid and sensitive bioassay was established and validated to simultaneously determine gemfibrozil, morphine, morphine-3β-glucuronide, and morphine-6β-glucuronide in mouse cerebrum, epencephalon, and hippocampus based on ultra-high performance liquid chromatography and tandem mass spectrometry. The deuterated internal standard, M6G-d3, was mixed with the prepared samples at 10 ng/mL as the final concentration. The samples were transferred into the C18 solid-phase extraction columns with gradient elution for solid-phase extraction. The mobile phase consisted of methanol and 0.05% formic acid (pH 3.2). Multiple reaction monitoring has been applied to analyze gemfibrozil (m/z 249.0 → 121.0) in anion mode, and M6G-d3 (m/z 465.1 → 289.1), morphine (m/z 286.0 → 200.9), and M3G and M6G (m/z 462.1 → 286.1) in the positive ion mode. The method has a linear calibration range from 0.05 to 10 ng for gemfibrozil, morphine, and M3G and M6G with correlation coefficients >0.993. The lower limit of quantitation for all four analytes was 0.05 ng/mL, relative standard deviation of intra- and interday precision was less than 10.5%, and the relative error of accuracy was from -8.2 to 8.3% at low, medium, and high concentrations for all the analytes. In conclusion, gemfibrozil can influence the morphine antinociception after coronary heart disease induced chronic angina by the change in one of morphine metabolites', M3G, distribution in mouse brain.

A validated LC-MS/MS assay for the quantitative determination of curdione in rabbit plasma and its application to a pharmacokinetic study after administration of zedoary turmeric oil and bioavailability of the oil.

A selective and sensitive liquid chromatography tandem mass spectrometry method was developed for the first time for the identification and quantification of curdione in rabbit plasma after vaginal drug administration and intravenous administration of zedoary turmeric oil (ZTO) solution (10 mg/kg). The analysis was performed on a triple-quadrupole tandem mass spectrometer with multiple reaction monitoring mode via electrospray ionization source in positive ionization mode. After mixing with internal standard diazepam, plasma samples were extracted with ethyl ether-acetic ether (1:1, v/v). Chromatographic separation was carried out on a C18 column with gradient elution using a mixture of water and acetonitrile (both containing 0.1% formic acid) as mobile phases. Linearity ranged over 1.06-106 and 10.6-530 ng/mL (r ≥ 0.995) with the lower limit of quantfication 1.06 ng/mL. The intra- and inter-day precision relative standard deviation values were <12% and the accuracy relative error was from -10.6 to -6.1% at all quality control sample levels. The method was applied to a study of the pharmacokinetics of curdione after vaginal drug administration and intravenous administration of ZTO.

Survey of ERETIC2 NMR for quantification

The ERETIC (Electronic REference To access In vivo Concentrations)2 method is a new qNMR experimental technique to measure analytes based on the signal of the reference compound without additional hardware equipment. In this study, ERETIC2 method was validated, and we sought to identify whether it would be possible to apply this method to a specific compound analysis of metabolites in plant. The <TEX>$90^{\circ}$</TEX> pulse value (P1) and spin-lattice relaxation time (<TEX>$T_1$</TEX>) of each compound were measured for ERETIC2. The <TEX>$9^1H$</TEX> of 3-(trimethylsilyl) propionic-2,2,3,3-<TEX>$d_4$</TEX> acid (TSP) was used as a reference peak for ERETIC 2, and then, a suitable solvent and pulse sequence for each compound were selected. Under the NOESY-presat sequence, the relative accuracy error for quantitative analyses of primary metabolites was within the range of 5%, with the exception of glucose, which showed <TEX>${\geq}$</TEX> 55% error due to saturation. It showed excellent results for the quantification of glucose by using a <TEX>$30^{\circ}$</TEX> pulse sequence, which did not suppress the water peak. In addition, the quantitative accuracy for secondary metabolites was extremely accurate, with an error <TEX>${\leq}$</TEX>5% when considering the purity of the standard sample. The ERETIC2 method showed outstanding linearity, precision, and accuracy.

Parallel solving model for quantified boolean formula based on machine learning

A new parallel architecture for quantified boolean formula (QBF) solving was proposed, and the prediction model based on machine learning technology was proposed for how sharing knowledge affects the solving performance in QBF parallel solving system, and the experimental evaluation scheme was also designed. It shows that the characterization factor of clause and cube influence the solving performance markedly in our experiment. At the same time, the heuristic machine learning algorithm was applied, support vector machine was chosen to predict the performance of QBF parallel solving system based on clause sharing and cube sharing. The relative error of accuracy for prediction can be controlled in a reasonable range of 20%–30%. The results show the important and complex role that knowledge sharing plays in any modern parallel solver. It shows that the parallel solver with machine learning reduces the quantity of knowledge sharing about 30% and saving computational resource but does not reduce the performance of solving system.