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As a mature and reliable method, this study is based on the flow function method for mathematical modeling and establishes a class of mathematical models that are approximately realistic, flexible, and easy to calculate. According to the characteristics of fractional order calculus, the initial boundary conditions are modified and optimized to reduce the model error of this class of equations. According to the minimum energy principle and linearized integral calculation method, the multi-field multi-parameter non-linear coupling problem in the calculation process is solved, and the rapid calculation of the initial boundary model is realized. The accuracy of the model is tested by numerical simulation and simulation validation of different processes. A reliable theoretical and technical support is provided for the calculation of this type of equations. [ABSTRACT FROM AUTHOR]

In this paper, a new split iterative compact difference scheme for a class of system is constructed. Then, the conservation properties of the scheme are discussed, and the convergence of the split iterative difference scheme is analyzed by using the discrete energy method on the basis of the prior estimation. Finally, numerical experiments verify these properties of the new scheme. In addition, the numerical results also show the influence of fractional derivative on the variation of the transport equation. [ABSTRACT FROM AUTHOR]

IntroductionUnder the background of digitalization of traditional Chinese medicine (TCM), this study aimed to realize the digital identification and adulteration analysis of Codonopsis Radix (CR) and Stellariae Radix (SR) based on chemical analysis.MethodsThis study combined digitalization concepts and chemical analysis and conducted a chemical analysis of CR and SR from different batches based on UHPLC-QTOF-MSE. Furthermore, the shared ions were extracted from different batches of CR and SR as their “ion characterization” after digital quantization. Then, the data matrices of unique ions of CR relative to SR and SR relative to CR were screened out, and the top-N ions were outputted as the “digital identities” of CR and SR, sorted by ionic strength. Finally, the above “digital identities” of CR and SR were used as benchmarks for matching positive samples and market samples to provide feedback on the matching credibility (MC) for identification and adulteration analysis.ResultsThe results showed that based on the “digital identities” of CR and SR, the digital identification of CR, SR, and positive samples can be realized at the individual level of TCM efficiently and accurately, even if 3% of SR in the mixed samples can still be identified efficiently and accurately. Moreover, 1 of the 12 batches of market samples was identified as an adulterated sample.ConclusionIt proved that the identification and adulteration analysis of two herbs can be realized efficiently and quickly through the “digital identities” of chemical compositions. It has important reference significance for developing the digital identification of CR and SR at the individual level of Chinese medicine based on the “digital identity” of chemical compositions, which was beneficial to the construction of digital quality control of CR and SR.

The combination of volatile compounds endows wines with unique aromatic characteristics and is closely related to their geographical origins. In the pursuit of origin identification and the subdivision of homogeneous production areas, clarifying the characteristics of production areas is of great significance for improving wine quality and commercial value. In this study, GC×GC-TOFMS technology was used to analyze the aroma characteristics of “Cabernet Sauvignon” wines from 26 wineries in the Helan (HL), Yinchuan (YC), Yongning (YN), Qingtongxia (QTX), and Hongsibu (HSP) sub-producing areas in the eastern foothills of Helan Mountain in Ningxia, China. The results indicate a gradual increase in relative humidity from the southern part of Ningxia, with the YN sub-region showing optimal fruit development and the QTX region having the highest maturity. A total of 184 volatile compounds were identified, with 36 compounds with an OAV > 1, crucial for the aroma profiles of primarily fermentation-derived alcohols and esters. An aromatic vector analysis revealed that “floral” and “fruity” notes are the primary characteristics of Cabernet Sauvignon wines from the Helan Mountain East region, with lower maturity aiding in the retention of these aromas. By constructing a reliable OPLS-DA model, it was determined that 15 substances (VIP > 1) played a crucial role in identifying production areas, among which phenylethyl alcohol and isoamyl alcohol were the main contributors. In addition, a Pearson correlation analysis showed a negative correlation between sunlight duration during the growing season and benzyl alcohol accumulation, while a significant positive correlation was observed during the ripening period. Due to the critical role of phenyl ethanol in identifying producing areas, this further demonstrates that sunshine conditions may be a key factor contributing to the differences in wine flavor across regions. This study offers a theoretical foundation for understanding the relationship between climatic factors and flavor characteristics, addressing the issue of wine homogenization in small production areas, clarifying typical style characteristics, and establishing a traceability technology system based on characteristic aroma.

Abstract Background Mahuang Fuzi decoction (MGF) is composed of three herb medicines that has been clinically used to treat inflammatory diseases for a long history. At present, more and more active phytochemicals’ aggregations have been found during the thermodynamic process of herb medicine decoction, and revealing the clinical efficacy of herb medicine through supramolecular strategies is the focus of current research. However, it is not clear whether decoction induced supermolecules’ morphological changes to modify activity. Methods Dynamic light scattering (DLS) and field emission scanning electron microscopy (FESEM) were used to analyze the micromorphology of MGF, MGF SA (MGF supermolecules), and MIX (physical mixture of MGF single decoction). The interaction and thermodynamic parameters of single herbs in a decoction were investigated by Isothermal titration calorimetry (ITC). The phytochemicals were systematically analyzed by ultra high performance liquid chromatography-Q Exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry (UHPLC-Q-Orbitrap HRMS). Under the safe dose on RAW264.7 cells, NO, IL-6 and TNF-α were determined by Enzyme-Linked ImmunoSorbent Assay (ELISA) method. NF-κB p65 translocation from the cytoplasm into the nucleus was examined using the immunofluorescence assay and the western blot, respectively. Furthermore, Metabolomics was used to discover potential biomarkers and the associated metabolic pathways of MGF SA treatment. Results There were nanoscale aggregations in MGF, and the micromorphology of the extracted MGF SA consisted of uniform particles; while the MIX micromorphology had no uniformity. ITC showed that the interaction MH-GC and FZ-GC were a spontaneous exothermic reaction, indicating that their phytochemicals had the property of self-assembly. Though the micromorphology between MGF, MGF SA, and MIX was obviously different, UHPLC-Q-Orbitrap HRMS results displayed that the main phytochemicals of MGF and MIX had nearly the same components. Interestingly, MGF and MGF SA could significantly inhibit the production of NO, and had better inhibition effect on the expression of nuclear protein NF-κB p65 than MIX, among which MGF SA had the best effect. Further investigation indicated that the perturbance of metabolic profiling in RAW264.7 inflammatory cells was obviously reversed by MGF SA. Conclusions The decoction enriched the key active phytochemicals and regulated the formation of homogeneous nanoparticles in MGF SA. The supermolecules in MGF SA significantly enhanced its anti-inflammatory activity, primarily affecting the NF-κB signaling pathway and the biosynthesis and metabolism of arginine in RAW264.7 inflammatory cells. Current study displayed that co-decocting herbal medicine were beneficial to the treatment of diseases than the mixture of the single herbs’ extraction. Graphical Abstract

Ginseng Radix et Rhizoma (GRR), Panacis Quinquefolii Radix (PQR), Notoginseng radix et rhizoma (NRR) and Platycodonis Radix (PR) are often confused in the material market because of similar appearances and characteristics. Moreover, chemical identification methods tend to characterize the whole herb with regard to a single or a few components, which is an inaccurate representation and does not demonstrate the effective utilization of unknown components, and the result is unconvincing. In order to strengthen quality control, improve identification efficiency, and realize digital identification at the individual level of traditional Chinese medicine (TCM), we have put forward the “matrix characteristics” of TCM, combined with a UHPLC-QTOF-MS analysis to explore and realize the digital identification of GRR, PQR, NRR, and PR. The mass spectrometry was quantized to extract common data from different batches of the same TCMs as their matrix characteristics, and the matching credibility (M) was given by matching the “matrix characteristics” with unknown Chinese medicines. The results show that within a reasonable parameter threshold range, the M of four TCMs was higher than 92.00% compared with their own “matrix characteristics”, which was significantly higher than the M ranked second. Furthermore, the digital identification of four TCMs can be successfully realized based on the UHPLC-QTOF-MS analysis and “matrix characteristics”. This has important reference significance for developing the digital identification of GRR at an individual level based on UPLC-QTOF-MS and “matrix characteristics”.

Background: Periplocae Cortex (PC), Acanthopanacis Cortex (AC), and Lycii Cortex (LC), as traditional Chinese medicines, are all dried root bark, presented in a roll, light and brittle, easy to break, have a fragrant scent, etc. Due to their similar appearances, it is tough to distinguish them, and they are often confused and adulterated in markets and clinical applications. To realize the identification and quality control of three herbs, in this paper, Ultra Performance Liquid Chromatography-Quadrupole Time of Flight Mass Spectrometry Expression (UHPLC-QTOF-MSE) combined with chemometric analysis was used to explore the different chemical compositions. Methods: LC, AC, and PC were analyzed by UHPLC-QTOF-MSE, and the quantized MS data combined with Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were used to explore the different chemical compositions with Variable Importance Projection (VIP) > 1.0. Further, the different chemical compositions were identified according to the chemical standard substances, related literature, and databases. Results: AC, PC, and LC can be obviously distinguished in PCA and PLS-DA analysis with the VIP of 2661 ions > 1.0. We preliminarily identified 17 differential chemical constituents in AC, PC, and LC with significant differences (p < 0.01) and VIP > 1.0; for example, Lycium B and Periploside H2 are LC and PC’s proprietary ingredients, respectively, and 2-Hydroxy-4-methoxybenzaldehyde, Periplocoside C, and 3,5-Di-O-caffeoylquinic acid are the shared components of the three herbs. Conclusions: UHPLC-QTOF-MSE combined with chemometric analysis is conducive to exploring the differential chemical compositions of three herbs. Moreover, the proprietary ingredients, Lycium B (LC) and Periploside H2 (PC), are beneficial in strengthening the quality control of AC, PC, and LC. In addition, limits on the content of shared components can be set to enhance the quality control of LC, PC, and AC.

Abstract Over the years, people paid more attention to using renewable energy such as geothermal energy to decrease the dependency on fossil fuel energy. Organic Rankine cycle (ORC) can generate electricity by using low‐temperature heat sources, and geothermal energy is an ideal pollution‐free heat source that can provide continuous and stable energy. Meanwhile, the turbo expander, one of the essential components in ORC, has the advantages of high speed and single‐stage expansion ratio. In this work, we simulated and analyzed the flow field characteristics of the turbo expander under the assigned working conditions using CFX software. The results showed that the working fluid distributed uniformly in the volute, and there was no apparent whirlpool flow or secondary flow. The pressure near the leading edge of the impeller blade was sparse but became dense at the vicinity of the trailing edge. When the speed of the expander was 15000rad min−1 and the inlet pressure was 0.59 MPa, the isentropic efficiency reached the maximum value, and the change of the inlet temperature had little effect on the isentropic efficiency, which can be ignored in actual operation. The results guide in improving the practical application of geothermal energy.

Background: As one of the four most valuable animal medicines, Fel Ursi, named Xiong Dan (XD) in China, has the effect of clearing heat, calming the liver, and brightening the eyes. However, due to the special source of XD and its high price, other animals’ bile is often sold as XD or mixed with XD on the market, seriously affecting its clinical efficacy and consumers’ rights and interests. In order to realize identification and adulteration analysis of XD, UHPLC-QTOF-MSE and multivariate statistical analysis were used to explore the differences in XD and six other animals’ bile. Methods: XD, pig gall (Zhu Dan, ZD), cow gall (Niu Dan, ND), rabbit gallbladder (Tu Dan, TD), duck gall (Yan Dan, YD), sheep gall (Yang Dan, YND), and chicken gall (Ji Dan, JD) were analyzed by UHPLC-QTOF-MSE, and the MS data, combined with multivariate analysis methods, were used to distinguish between them. Meanwhile, the potential chemical composition markers that contribute to their differences were further explored. Results: The results showed that XD and six other animals’ bile can be distinguished from each other obviously, with 27 ions with VIP > 1.0. We preliminarily identified 10 different bile acid-like components in XD and the other animals’ bile with significant differences (p < 0.01) and VIP > 1.0, such as tauroursodeoxycholic acid, Glycohyodeoxycholic acid, and Glycodeoxycholic acid. Conclusions: The developed method was efficient and rapid in accurately distinguishing between XD and six other animals’ bile. Based on the obtained chemical composition markers, it is beneficial to strengthen quality control for bile medicines.

Accurately predicting the drilling efficiency of rotary drilling is the key to achieving intelligent construction. The current types of principle analysis (based on traditional interactive experimental methods) and efficiency prediction (based on simulation models) cannot meet the requirements needed for the efficient, real-time, and accurate drilling efficiency predictions of rotary drilling rigs. Therefore, we adopted a method based on machine learning to predict drilling efficiency. The extremely complex rock fragmentation process in drilling conditions also brings challenges to predicting drilling efficiency. Therefore, this article went through a combination of mechanism and data analysis to conduct correlation analysis and to clarify the drilling characteristic parameters that are highly correlated with drilling efficiency, and it then used them as inputs for machine learning models. We propose a rotary drilling rig drilling efficiency prediction model based on the GA-BP neural network to construct an accurate and efficient drilling efficiency prediction model. Compared with traditional BP neural networks, it utilizes the global optimization ability of a genetic algorithm to obtain the initial weights and thresholds of a BP neural network in order to avoid the defect of ordinary BP neural networks, i.e., that they easily fall into local optimal solutions during the training process. The average prediction accuracy of the GA-BP neural network is 93.6%, which is 3.1% higher than the traditional BP neural network.

Multi-way spool valves (MWSVs) with K-shape notches (KSNs) provide advantages such as improvement of the actuator speed control, micro-action, and response performance. However, the pressure drop (PD) associated with the energy consumption is larger of MWSVs under the high-pressure and large-flow condition. Meanwhile, extremely complex flow coefficient and multi-parameter, highly coupled KSNs are the chief factors restricting the flow-pressure characteristics exploration and optimisation design of MWSVs. To address these problems, complete numerical research and experiment are performed in this study, especially concerning the method of MWSV flow-pressure characteristics modelling, and surrogated model-based optimal design of KSN structures. First, the relationships between KSN structure parameters and flow-pressure properties of MWSV are modelled on the innovative discharge area parameter model (DAPM) and response surface methodology (RSM) (RSM-DPAM) using the CFD dataset. Second, to reduce the PD combining the flow control performance, surrogate model-based optimisation design is addressed. During optimisation, six KSN structure parameters are chosen as design variables, PD and flow area relative deviation (FARD) are selected as objective functions, and the RSM is employed as the projected model. Depended on the created surrogate model, the non-dominated sorting genetic algorithm (NSGA-II) is established to search for the optimal KSN structure. To certify the performance of the optimisation, flow field characteristics are analysed. The results demonstrate that the proposed RSM-DAPM-RSM model achieves reliable prediction for PD and FARD with a great correlation coefficient (0.9757 and 0.9946). The average PD reduces as much as 7.23% while the FARD is only 1.28%. Moreover, the region of low-pressure, high-velocity, and high-turbulent kinetic energy in the flow field are reduced. The proposed framework enhances the performance in KSN spool optimisation and could be applied to other kinds of notches.Abbreviations: BOI: Body of influence; BSV: Bucket spool valve; CFD: Computational fluid dynamics; CM: Construction machinery; DAPM: Discharge area parameter model; FARD: Flow area relative deviation; FCC: Flow control characteristic; GSA: Global sensitivity analysis; KSN: K-shape notch; MHAs: Meta-heuristic algorithms; MODE: Multi-objective differential evolution; MOGA: Multi-objective genetic algorithm; MOO: Multi-objective optimisation; MOPSO: Multi-objective particle swarm optimisation; MWSV: Multi-way spool valve; NRMS: Non-road mobile source; NSGA-II: Non-dominated sorting genetic algorithm; OLHD: Optimal Latin hypercube design; PD: Pressure drop; PDCs: Pressure drop characteristics; RSM: Response surface methodology; SA: Sensitivity analysis; TKE: Turbulent kinetic energy; TOPSIS: Technique for order preference by similarity to ideal solution; VFR: Volume flow rate

In this study, three commercial non-Saccharomyces yeasts, i.e., Torulaspora delbrueckii, Metschnikowia pulcherrima and Lachancea thermotolerans were tested in combination with Saccharomyces cerevisiae to produce Italian Riesling white wines, with the fermentation progress, physical and chemical indexes of white wine, volatile profile and aromatic property of resulting white wines determined and compared, in order to elucidate their influences on the aroma quality of white wines. Results showed that, all fermentations were completed successfully, but the growth of M. pulcherrima was more easily inhibited by the proliferation of S. cerevisiae. Moreover, the ethanol concentrations of white wines from mixed fermentations were lower than that of S. cerevisiae single inoculation. Volatile compounds were detected by HS-GC-IMS, and a total of 34 volatiles were obtained. Wines inoculated with M. pulcherrima contained the highest signal intensities of ethyl caproate, ethyl isovalerate, ethyl 2-methylbutyrate, hexyl acetate, γ-nonolactone, δ-octanolactone, hexanol, 2,3-butanedione and linalool, the overall aromatic property was greatly enhanced. Wines conducted by mixed fermentation using T. delbrueckii/S. cerevisiae and L. thermotolerans/S. cerevisiae contained higher intensities of ethyl octanoate, propyl acetate, ethyl propionate and α-terpinene, and the aroma and sensory characteristics of these two pairs were similar, both better than the wine fermented singly by S. cerevisiae. Moreover, principal component analysis could better distinguish the wines produced by different mixed fermentation processes. In conclusion, this study showed that the mixed fermentation using non-Saccharomyces yeasts/S. cerevisiae pairs played an important role in the improvement of the aroma of white wine.

BackgroundThe high prevalence of β-thalassemia indicates the severe medical burden in Guangxi province in China. Millions of thousands of prenatal women with healthy or thalassemia-carrying fetuses received an unnecessary prenatal diagnosis. We designed a prospective single-center proof-of-concept study to evaluate the utility of a noninvasive prenatal screening method in the stratification of beta-thalassemia patients before invasive procedures.MethodsNext-generation and optimized pseudo-tetraploid genotyping-based methods were utilized in preceding invasive diagnosis stratification to predict the mater-fetus genotype combinations in cell-free DNA, which is from maternal peripheral blood. Populational linkage disequilibrium information with additional neighboring loci to infer the possible fetal genotype. The concordance of the pseudo-tetraploid genotyping with the gold standard invasive molecular diagnosis was used to evaluate the effectiveness of this method.Results127 β-thalassemia carrier parents were consecutively recruited. The total genotype concordance rate is 95.71%. The Kappa value was 0.8248 for genotype combinations and 0.9118 for individual alleles.ConclusionThis study offers a new approach to picking out the health or carrier fetus before invasive procedures. It provides valuable novel insight into patient stratification management on β-thalassemia prenatal diagnosis.

Before use as medicines, most traditional Chinese medicine (TCM) plants are processed and decocted. During processing, there may be some changes in pesticide residues in TCM. In recent years, reports have studied the changes of pesticides during the processes of boiling, drying and peeling of TCM materials but have rarely involved special processing methods for TCM, such as ethanol extraction and volatile oil extraction. The changes of carbendazim, carbofuran, pyridaben and tebuconazole residues in common processing methods for P. cablin products were systemically assessed in this study. After each processing step, the pesticides were quantitated by UPLC-MS/MS. The results showed amount decreases in various pesticides to different extents after each processing procedure. Processing factor (PF) values for the four pesticides after decoction, 75% ethanol extraction and volatile oil extraction were 0.02~0.75, 0.40~0.98 and 0~0.02, respectively, which indicated that residual pesticide concentrations may depend on the processing technique. A risk assessment according to the hazard quotient with PF values showed that residual pesticide amounts in P. cablin were substantially lower than levels potentially posing a health risk. Overall, these findings provide insights into the safety assessment of P. cablin.

Abstract Background American ginseng (AG) is a valuable medicine widely consumed as a herbal remedy throughout the world. Huge price difference among AG with different growth years leads to intentional adulteration for higher profits. Thus, developing reliable approaches to authenticate the cultivation ages of AG products is of great use in preventing age falsification. Methods A total of 106 batches of AG samples along with their 9 physicochemical features were collected and measured from experiments, which was then split into a training set and two test sets (test set 1 and 2) according to the cultivation regions. Principle component analysis (PCA) was carried out to examine the distribution of the three data sets. Four machine learning (ML) algorithms, namely elastic net, k-nearest neighbors, support vector machine and multi-layer perception (MLP) were employed to construct predictive models using the features as inputs and their growth years as outputs. In addition, a similarity-based applicability domain (AD) was defined for these models to ensure the reliability of the predictive results for AG samples produced in different regions. Results A positive correlation was observed between the several features and the growth years. PCA revealed diverse distributions among different cultivation regions. The most accurate model derived from MLP shows good prediction power for the fivefold cross validation and the test set 1 with mean square error (MSE) of 0.017 and 0.016 respectively, but a higher MSE value of 1.260 for the test set 2. After applying the AD, all models showed much lower prediction errors for the test samples within AD (IDs) than those outside the AD (ODs). MLP remains the best predictive model with an MSE value of 0.030 for the IDs. Conclusion Cultivation years have a close relationship with bioactive components of AG. The constructed models and AD are also able to predict the cultivation years and discriminate samples that have inaccurate prediction results. The AD-equipped models used in this study provide useful tools for determining the age of AG in the market and are freely available at https://github.com/dreadlesss/Panax_age_predictor .

Gas–liquid intermittent flow is a kind of flow pattern that distinguishes itself from the conventional flow by the apparent non-steady feature, which causes serious corrosion issues, including localized corrosion. Although it widely exists in wet gas pipelines, how the gas–liquid intermittent flow influences CO2 corrosion of pipeline steels remains a problem to be clarified. In this work, a testing device that enables good simulation of gas–liquid intermittent flow in wet gas pipelines under various conditions was developed and used to perform experimental studies, combining electrochemical tests and corrosion morphology observations. The result shows that flow velocity and gas–liquid ratio act together to affect the CO2 corrosion behavior of X70 steel in typical intermittent flow conditions. The flow velocity has a more profound effect on the corrosion rate, while the gas–liquid ratio is associated with the occurrence of localized corrosion. The effect of the gas–liquid ratio on corrosion behavior was discussed.

Abstract Background Diabetes is a complex metabolic disease characterized by hyperglycemia, plaguing the whole world. However, the action mode of multi-component and multi-target for traditional Chinese medicine (TCM) could be a promising treatment of diabetes mellitus. According to the previous research, the TCM of Polygonum multiflorum (PM) showed noteworthy hypoglycemic effect. Up to now, its hypoglycemic active ingredients and mechanism of action are not yet clear. In this study, network pharmacology was employed to elucidate the potential bioactive compounds and hypoglycemic mechanism of PM. Methods First, the compounds with good pharmacokinetic properties were screened from the self-established library of PM, and the targets of these compounds were predicted and collected through database. Relevant targets of diabetes were summarized by searching database. The intersection targets of compound-targets and disease-targets were obtained soon. Secondly, the interaction net between the compounds and the filtered targets was established. These key targets were enriched and analyzed by protein–protein interactions (PPI) analysis, molecular docking verification. Thirdly, the key genes were used to find the biologic pathway and explain the therapeutic mechanism by genome ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analysis. Lastly, the part of potential bioactive compounds were under enzyme activity inhibition tests. Results In this study, 29 hypoglycemic components and 63 hypoglycemic targets of PM were filtrated based on online network database. Then the component-target interaction network was constructed and five key components resveratrol, apigenin, kaempferol, quercetin and luteolin were further obtained. Sequential studies turned out, AKT1, EGFR, ESR1, PTGS2, MMP9, MAPK14, and KDR were the common key targets. Docking studies indicated that the bioactive compounds could stably bind the pockets of target proteins. There were 38 metabolic pathways, including regulation of lipolysis in adipocytes, prolactin signaling pathway, TNF signaling pathway, VEGF signaling pathway, FoxO signaling pathway, estrogen signaling pathway, linoleic acid metabolism, Rap1 signaling pathway, arachidonic acid metabolism, and osteoclast differentiation closely connected with the hypoglycemic mechanism of PM. And the enzyme activity inhibition tests showed the bioactive ingredients have great hypoglycemic activity. Conclusion In summary, the study used systems pharmacology to elucidate the main hypoglycemic components and mechanism of PM. The work provided a scientific basis for the further hypoglycemic effect research of PM and its monomer components, but also provided a reference for the secondary development of PM.

Saikosaponins comprise a large group of chemical components present in the Bupleurum species that have attracted attention in the field of medicine because of their significant biological activities. Due to the high polarity, structural similarity, and the presence of several isomers of this class of components, their structural identification is extremely challenging. In this study, the mass spectrometric fragmentation pathways, UV spectral features, and chromatographic behavior of different types of saikosaponins were investigated using 24 standard substances. Saikosaponins containing carbonyl groups (C=O) in the aglycone produced fragment ions by loss of 30 Da, and in addition, type IV saikosaponins could produce [aglycone−CH2OH−OH−H]− and [aglycone−H2O−H]− fragment ions through neutral losses at positions C16 and C17. The above characteristic ions can be used to identify saikosaponins. More notably, the identification process of saikosaponins was systematically summarized, and using this method, 109 saikosaponins were identified or tentatively characterized from the saikosaponins extract of Bupleurum marginatum var. stenophyllum (BMS) using UPLC-PDA-Q/TOF-MS with both data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes, of which 25 were new compounds and 60 were first discovered from BMS. Further studies revealed that the saikosaponins profiles of BMS, Bupleurum chinense DC (BC), and Bupleurum marginatum Wall. ex DC (BMW) were very similar. This work is of great significance for the basic research of the Bupleurum species and provides strong technical support to solve the resource problems associated with Radix Bupleuri.

Abstract In the face of the current energy shortage, organic Rankine cycle (ORC) technology is a way to make efficient use of energy, especially geothermal energy. As the core component of an ORC system, a turbo expander can achieve a high conversion efficiency for geothermal energy and has good development prospects. For low temperature geothermal energy such as 95°C water, R245fa could be chosen as the working fluid. Through preliminary thermal calculations and the MATLAB programming method, the main thermal performance parameters and the aerodynamic parameters, structural parameters, and three‐dimensional modeling of the guide vane and impeller were obtained. The design of the turbo expander was modeled and meshed by the Workbench module using the ANSYS software, and the internal flow path of the expander was numerically simulated by the CFX module. The results showed that there was a small range of wake loss at the trailing edge of the vane flow; impact loss and wake loss occurred at the leading and trailing edges of the impeller blades. At the 30% relative chord strength of the impeller, there was excessive expansion, resulting in a local low‐pressure area and a secondary flow from the hub to the rim.

Abstract The optimization of a turboexpander can significantly improve the performance of the organic Rankine cycle (ORC) system, which can use in low‐temperature geothermal energy for high‐efficiency power generation. Therefore, this paper studies and optimizes the expander in the ORC of low‐temperature geothermal energy around 90°C. Firstly, the influence of impeller parameters on the performance of the expander is analyzed. Then, the grid is divided by the turbine mesh, and numerical simulation is performed by CFX. The gas state equation selects the Peng–Robinson equation, and the turbulence equation selects the SST model. Finally, the effect of tip clearance on the performance of the expander was studied. Research on impeller blade parameters shows that with the increase in the outer diameter of the impeller blade outlet, the isentropic efficiency of the expander decreases, and the output power increases. As the increase in the angle between the direction of the impeller blade and the meridian plane, the outlet velocity of the blade increases, the temperature decreases, and the efficiency and control of the turboexpander will decrease. The meridional section width has few effects on the performance of the expander. The study of the tip clearance by numerical simulation shows that the existence of tip clearance will cause clearance flow between pressure surface and suction surface that interferes with the mainstream direction. When the tip clearance increases from 0 mm to 1.2 mm, the efficiency of the expander is reduced by 8.9%.

Abstract Associated petroleum gas produced by CO2‐enhanced oil recovery (CO2‐EOR) has a complex composition, high CO2 content, and is unstable. To date, no integrated process simulation for CO2 capture of the EOR associated petroleum gas has been developed. Based on the analysis of the associated petroleum gas obtained from the Shengli oilfield, a new full‐simulation model of CO2 capture from 100 000 Nm3/d of the associated petroleum gas was developed for the process design of chemical absorption of blended amine solvents and an analysis of the relationship between different process parameters and the targeted result—low circulation flow and energy consumption—was performed using Aspen Plus (Version 8.6). A 90% CO2 removal rate was achieved using 0.2 mol CO2/mol of a blended amine as solvent, with an energy consumption of 3.16 GJ/tCO2. By analyzing the influence of absorption pressure, temperature, and packing height on the circulation flow, the influence of absorption and desorption pressure on the energy consumption of the system was determined. It can be concluded that the optimal parameters are as follows: packing height of absorption column, 10 m; absorption temperature, 308.15 K; desorption pressure, 0.12 MPa; and CO2 loading, 0.2 mol/mol of lean solvent, with an absorption pressure of 0.3‐0.6 MPa.

Magnolia officinalis Rehd. et Wils. and Magnolia officinalis Rehd. et Wils. var. biloba Rehd. et Wils, as the legal botanical origins of Magnoliae Officinalis Cortex, are almost impossible to distinguish according to their appearance traits with respect to medicinal bark. The application of AFLP molecular markers for differentiating the two origins has not yet been successful. In this study, a combination of e-nose measurements, e-tongue measurements, and chemical analyses coupled with multiple-source data fusion was used to differentiate the two origins. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were applied to compare the discrimination results. It was shown that the e-nose system presented a good discriminant ability with a low classification error for both LDA and QDA compared with e-tongue measurements and chemical analyses. In addition, the discriminating capacity of LDA for low-level fusion with original data, similar to a combined system, was superior or equal to that acquired individually with the three approaches. For mid-level fusion, the combination of different principals extracted by PCA and variables obtained on the basis of PLS-VIP exhibited an analogous discrimination ability for LDA (classification error 0.0%) and was significantly superior to QDA (classification error 1.67–3.33%). As a result, the combined e-nose, e-tongue, and chemical analysis approach proved to be a powerful tool for differentiating the two origins of Magnoliae Officinalis Cortex.

A novel and effective chromatographic approach to the separation and purification of isoflavone compounds from Pueraria lobata is described. The method is based on flash chromatography (FC), coupled to preparative high performance liquid chromatography (prep-HPLC) via a six-way valve. The FC step comprised tandem reversed phase columns, pre-packed with MCI gel (Mitsubishi Chemical Corp., Tokyo, Japan) and C18 (Fuji Silysia Chemical Ltd, Osaka, Japan) resin, respectively, and was designed to separate a crude Pueraria lobata extract into several preliminary fractions. Fractions containing the target compounds were then directly injected via the six-way valve into prep-HPLC columns, without further treatment, for final isolation and purification. Nine isoflavonoids were successfully isolated, three through an online mode and the other six through an offline mode. The purities of all compounds exceeded 95.0%, as determined by HPLC with an UV-vis photodiode array detector. The convenience, low solvent consumption, and time-saving advantages of this method offer an attractive and promising approach to the isolation of natural products.

This work investigates the effects of pressure pulsations on reciprocating natural gas compressor performance thermodynamically. A nonlinear hybrid numerical model is thus developed to consider the interaction between the compressor and the pipeline system. The suction chamber, compressor cylinder and discharge chamber are modelled integrally based on the first law of thermodynamics and mass balance, and the pipeline flow is described by using the gas dynamic model. Methane is considered as the working fluid and its properties are computed based on ideal and real gas assumptions. For the real gas model, the methane properties are obtained by means of calling the NIST REFPROP database. The validity of numerical results is confirmed by previous experimental values. Results from the examinations of pressure pulsation influence demonstrate that discharge resonance requires more specific work than suction resonance in the same harmonic; in the suction system, the first harmonic response reduces the mass flow rate but significantly increases specific work, and the second harmonic response has a strong supercharging effect but the specific work is increased slightly; in the discharge system, the mass flow rate is changed little by pressure pulsations, but the indicated power and specific work are increased significantly; for the real gas model, the in-cylinder temperature during the compression and discharge phases, mass flow rate and indicated power are higher than those for the ideal gas model, whereas the specific work is less for the real gas model than for the ideal gas model.

The influence of graphene oxide (GO) and polyvinyl alcohol (PVA) fiber on the mechanical performance, durability, and microstructure of cement-based materials was investigated in this study. The results revealed that compared with a control sample, the mechanical strength and durability of cement-based materials were significantly improved by adding PVA fiber and GO. The compressive and flexural strength at 28 d were increased by 30.2% and 39.3%, respectively. The chloride migration coefficient at 28 d was reduced from 7.3 × 10−12 m2/s to 4.3 × 10−12 m2/s. Under a sulfate corrosion condition for 135 d, the compressive and flexural strength still showed a 13.9% and 12.3% gain, respectively. Furthermore, from the Mercury Intrusion Porosimetry (MIP) test, with the incorporation of GO, the cumulative porosity decreased from more than 0.13 cm3/g to about 0.03 cm3/g, and the proportion of large capillary pores reduced from around 80% to 30% and that of medium capillary pores increased from approximately 20% to 50%. Scanning electron microscope (SEM) images showed a significant amount of hydration products adhering to the surface of PVA fiber in the GO and PVA fiber modified sample. The addition of GO coupling with PVA fiber in cement-based materials could promote hydration of cement, refine the microstructure, and significantly improve mechanical strength and durability.

High-density surface electromyography (HD-sEMG) is to record muscles’ electrical activity from a restricted area of the skin by using two dimensional arrays of closely spaced electrodes. This technique allows the analysis and modelling of sEMG signals in both the temporal and spatial domains, leading to new possibilities for studying next-generation muscle-computer interfaces (MCIs). sEMG-based gesture recognition has usually been investigated in an intra-session scenario, and the absence of a standard benchmark database limits the use of HD-sEMG in real-world MCI. To address these problems, we present a benchmark database of HD-sEMG recordings of hand gestures performed by 23 participants, based on an 8 × 16 electrode array, and propose a deep-learning-based domain adaptation framework to enhance sEMG-based inter-session gesture recognition. Experiments on NinaPro, CSL-HDEMG and our CapgMyo dataset validate that our approach outperforms state-of-the-arts methods on intra-session and effectively improved inter-session gesture recognition.