This study utilizes two complementary models,the Time-Varying Parameter Vector Autoregressive Diebold–Yilmaz(TVP-VAR-DY)and the Time-Varying Parameter Vector Autoregressive Barunik–Křehlik(TVP-VAR-BK),to investigate...This study utilizes two complementary models,the Time-Varying Parameter Vector Autoregressive Diebold–Yilmaz(TVP-VAR-DY)and the Time-Varying Parameter Vector Autoregressive Barunik–Křehlik(TVP-VAR-BK),to investigate the dynamic volatility transmission between exchange rates and stock returns in major commodity-exporting and-importing countries.The analysis focuses on periods of quantitative easing(QE)and quantitative tightening(QT)from March 15,2020 to December 30,2022.The countries examined are Canada and Australia(major commodity exporters)and the UK and Germany(major commodity importers).An essential contribution of this paper is new empirical insights into the dynamics of stock market returns and the transmission of volatility between these markets and exchange rates during the QE and QT periods.The results reveal that causality primarily flows from stock markets to exchange rates,especially during the QT period across all investment horizons.The Toronto Stock Exchange(TSX)emerges as the principal net driver among the markets under study.Furthermore,the Canadian exchange rate(USDCAD)and the Australian Stock Exchange(ASX)are the most significantly affected indices within the network across various investment horizons(excluding the long-term).These findings underscore the importance for investors and policymakers to consider the interplay between exchange rates and stock market returns,particularly in the context of the QE and QT periods,as well as other economic,political,and health-related events.Our findings are relevant to various stakeholders,including governments,traders,portfolio managers,and multinationals.展开更多
The concept of local shock strength and a quantitative measure index str of local shock strength are proposed,derived from the oblique shock relation and the monotonic relationship between total pressure loss ratio an...The concept of local shock strength and a quantitative measure index str of local shock strength are proposed,derived from the oblique shock relation and the monotonic relationship between total pressure loss ratio and normal Mach number.Utilizing the high density gradient characteristic of shock waves and the oblique shock relation,a post-processing algorithm for two-dimensional flow field data is developed.The objective of the post-processing algorithm is to obtain specific shock wave location coordinates and calculate the corresponding str from flow filed data under the calibration of the oblique shock relation.Valida-tion of this post-processing algorithm is conducted using a standard model example that can be solved analytically.Combining the concept of local shock strength with the post-processing algorithm,a local shock strength quantitative mapping approach is established for the first time.This approach enables a quantitative measure and visualization of local shock strength at distinct locations,represented by color mapping on the shock structures.The approach can be applied to post-processing numerical sim-ulation data of two-dimensional flows.Applications to the intersection of two left-running oblique shock waves(straight shock waves),the bow shock in front of a cylinder(curved shock wave),and Mach reflection(mixed straight and curved shock waves)demonstrate the accuracy,and effectiveness of the mapping approach in investigating diverse shock wave phenomena.The quan-titative mapping approach of str may be a valuable tool in the design of supersonic/hypersonic vehicles and the exploration of shock wave evolution.展开更多
Pythium stalk rot(PSR)is a destructive disease of maize,severely affecting yield and grain quality.The identification of quantitative trait loci(QTL)or genes for resistance to PSR forms the basis of diseaseresistant h...Pythium stalk rot(PSR)is a destructive disease of maize,severely affecting yield and grain quality.The identification of quantitative trait loci(QTL)or genes for resistance to PSR forms the basis of diseaseresistant hybrids breeding.In this study,a major QTL,Resistance to Pythium stalk rot 1(RPSR1),was identified from a set of recombinant inbred lines derived from MS71 and POP.Using a recombinant progeny testing strategy,RPSR1 was fine-mapped in a 472 kb interval.Through candidate gene expression,gene knock-down and knock-out studies,a leucine-rich repeat receptor-like kinase gene,PEP RECEPTOR 2(ZmPEPR2),was assigned as a PSR resistance gene.These results provide insights into the genetic architecture of resistance to PSR in maize,which should facilitate breeding maize for resistance to stalk rot.展开更多
All-vanadium flow batteries(VFBs)are one of the most promising large-scale energy storage technologies.Conducting an operando quantitative analysis of the polarizations in VFBs under different conditions is essential ...All-vanadium flow batteries(VFBs)are one of the most promising large-scale energy storage technologies.Conducting an operando quantitative analysis of the polarizations in VFBs under different conditions is essential for developing high power density batteries.Here,we employ an operando decoupling method to quantitatively analyze the polarizations in each electrochemical and chemical reaction of VFBs under different catalytic conditions.Results show that the reduction reaction of V^(3+)presents the largest activation polarization,while the reduction reaction of VO_(2)^(+)primarily contributes to concentration polarizations due to the formation of the intermediate product V_(2)O_(3)^(3+).Additionally,it is found that the widely used electrode catalytic methods,incorporating oxygen functional groups and electrodepositing Bi,not only enhance the reaction kinetics but also exacerbate concentration polarizations simultaneously,especially during the discharge process.Specifically,in the battery with the high oxygen-containing electrodes,the negative side still accounts for the majority of activation loss(75.3%)at 200 mA cm^(-2),but it comes down to 36,9% after catalyzing the negative reactions with bismuth.This work provides an effective way to probe the limiting steps in flow batteries under various working conditions and offers insights for effectively enhancing battery performance for future developments.展开更多
Supercritical CO_(2)(SC-CO_(2))fracturing stands out a promising waterless stimulation technique in the development of unconventional resources.While numerous studies have delved into the inducedfracture mechanism of ...Supercritical CO_(2)(SC-CO_(2))fracturing stands out a promising waterless stimulation technique in the development of unconventional resources.While numerous studies have delved into the inducedfracture mechanism of SC-CO_(2),the small scale of rock samples and synthetic materials used in many studies have limited a comprehensive understanding of fracture propagation in unconventional formations.In this study,cubic tight sandstone samples with dimensions of 300 mm were employed to conduct SC-CO_(2)fractu ring experiments under true-triaxial stre ss conditions.The spatial morphology and quantitative attributes of fracture induced by water and SC-CO_(2)fracturing were compared,while the impact of in-situ stress on fracture propagation was also investigated.The results indicate that the SCCO_(2)fracturing takes approximately ten times longer than water fracturing.Furthermore,under identical stress condition,the breakdown pressure(BP)for SC-CO_(2)fracturing is nearly 25%lower than that for water fracturing.A quantitative analysis of fracture morphology reveals that water fracturing typically produces relatively simple fracture pattern,with the primary fracture distribution predominantly controlled by bedding planes.In contrast,SC-CO_(2)fracturing results in a more complex fracture morphology.As the differential of horizontal principal stress increases,the BP for SC-CO_(2)fractured rock exhibits a downward trend,and the induced fracture morphology becomes more simplified.Moreover,the presence of abnormal in-situ stress leads to a further increase in the BP for SC-CO_(2)fracturing,simultaneously enhancing the development of a more conductive fracture network.These findings provide critical insights into the efficiency and behavior of SC-CO_(2)fracturing in comparison to traditional water-based fracturing,offering valuable implication for its potential applications in unconventional reservoirs.展开更多
Quantitative detection of trace small-sized nanoplastics(<100 nm)remains a significant challenge in surface-enhanced Raman scattering(SERS).To tackle this issue,we developed a hydrophobic CuO@Ag nanowire substrate ...Quantitative detection of trace small-sized nanoplastics(<100 nm)remains a significant challenge in surface-enhanced Raman scattering(SERS).To tackle this issue,we developed a hydrophobic CuO@Ag nanowire substrate and introduced a multiplex-feature analysis strategy based on the coffee ring effect.This substrate not only offers high Raman enhancement but also exhibits a high probability of detection(POD),enabling rapid and accurate identification of 50 nm polystyrene nanoplastics over a broad concentration range(1–10−10 wt%).Importantly,experimental results reveal a strong correlation between the coffee ring formation and the concentration of nanoplastic dispersion.By incorporating Raman signal intensity,coffee ring diameter,and POD as combined features,we established a machine learning-based mapping between nanoplastic concentration and coffee ring characteristics,allowing precise predictions of dispersion concentration.The mean squared error of these predictions is remarkably low,ranging from 0.21 to 0.54,representing a 19 fold improvement in accuracy compared to traditional linear regression-based methods.This strategy effectively integrates SERS with wettability modification techniques,ensuring high sensitivity and fingerprinting capabilities,while addressing the limitations of Raman signal intensity in accurately reflecting concentration changes at ultra-low levels,providing a new idea for precise SERS measurements of nanoplastics.展开更多
Bone age assessment(BAA)aims to determine whether a child’s growth and development are normal concerning their chronological age.To predict bone age more accurately based on radiographs,and for the left-hand X-ray im...Bone age assessment(BAA)aims to determine whether a child’s growth and development are normal concerning their chronological age.To predict bone age more accurately based on radiographs,and for the left-hand X-ray images of different races model can have better adaptability,we propose a neural network in parallel with the quantitative features from the left-hand bone measurements for BAA.In this study,a lightweight feature extractor(LFE)is designed to obtain the featuremaps fromradiographs,and amodule called attention erasermodule(AEM)is proposed to capture the fine-grained features.Meanwhile,the dimensional information of the metacarpal parts in the radiographs is measured to enhance the model’s generalization capability across images fromdifferent races.Ourmodel is trained and validated on the RSNA,RHPE,and digital hand atlas datasets,which include images from various racial groups.The model achieves a mean absolute error(MAE)of 4.42 months on the RSNA dataset and 15.98 months on the RHPE dataset.Compared to ResNet50,InceptionV3,and several state-of-the-art methods,our proposed method shows statistically significant improvements(p<0.05),with a reduction in MAE by 0.2±0.02 years across different racial datasets.Furthermore,t-tests on the features also confirm the statistical significance of our approach(p<0.05).展开更多
Risk management often plays an important role in decision making un-der uncertainty.In quantitative risk management,assessing and optimizing risk metrics requires eficient computing techniques and reliable theoretical...Risk management often plays an important role in decision making un-der uncertainty.In quantitative risk management,assessing and optimizing risk metrics requires eficient computing techniques and reliable theoretical guarantees.In this pa-per,we introduce several topics on quantitative risk management and review some of the recent studies and advancements on the topics.We consider several risk metrics and study decision models that involve the metrics,with a main focus on the related com-puting techniques and theoretical properties.We show that stochastic optimization,as a powerful tool,can be leveraged to effectively address these problems.展开更多
Mg-4.8Zn-0.8Y,Mg-18Zn-3Y,Mg-15Zn-5Y,Mg-30Zn-5Y and Mg-42Zn-7Y(wt%)alloys containing icosahedral quasicrystalline phases were prepared using the ordinary solidification method.The impact of Mg matrix porosity on the te...Mg-4.8Zn-0.8Y,Mg-18Zn-3Y,Mg-15Zn-5Y,Mg-30Zn-5Y and Mg-42Zn-7Y(wt%)alloys containing icosahedral quasicrystalline phases were prepared using the ordinary solidification method.The impact of Mg matrix porosity on the tensile strength and hardness of the alloys was studied.The porosity of the Mg matrix was quantitatively assessed using scanning electron microscope and Image-Pro Plus 6.0 software.Tensile tests were conducted at room temperature.Results show that the maximum tensile strength of the alloy is 175.56 MPa,with a corresponding Mg matrix porosity of 76.74%.Through fitting analysis,it is determined that the maximum tensile strength is achieved when the porosity of the Mg matrix is 64.87%.The microhardness test results indicate a gradual decrease in alloy hardness with increasing the porosity of Mg matrix.This study provides an effective quantitative analysis method for enhancing the mechanical properties of magnesium alloys.展开更多
[Objectives]To establish an HPLC method for the quantitative determination of multiple phenolic acid components in Tetracera asiatica medicinal material,providing a basis for establishing its quality standards.[Method...[Objectives]To establish an HPLC method for the quantitative determination of multiple phenolic acid components in Tetracera asiatica medicinal material,providing a basis for establishing its quality standards.[Methods]An Inertsil ODS-C 18 column(250 mm×4.6 mm,5μm)was used.The mobile phase consisted of acetonitrile-0.2% phosphoric acid solution(10:90).The flow rate was 1.0 mL/min.The detection wavelength was 274 nm.The column temperature was 25℃.The injection volume was 10μL.The content of three components,gallic acid,protocatechuic acid,and protocatechualdehyde,was determined in 13 batches of T.asiatica.[Results]Gallic acid showed good linearity within the range of 0.020-6.400μg/mL,protocatechuic acid within 0.201-6.432μg/mL,and protocatechualdehyde within 0.202-6.464μg/mL(r>0.9990).The average recovery rates ranged from 98.61%to 101.17%,with RSD s between 1.21%and 2.69%.[Conclusions]The quantitative determination method established in this study is simple and feasible,and can provide a basis for the quality evaluation of T.asiatica.展开更多
Quantitative structure-retention relationship(QSRR)is an important tool in chromatography.QSRR examines the correlation between molecular structures and their retention behaviors during chromatographic separation.This...Quantitative structure-retention relationship(QSRR)is an important tool in chromatography.QSRR examines the correlation between molecular structures and their retention behaviors during chromatographic separation.This approach involves developing models for predicting the retention time(RT)of analytes,thereby accelerating method development and facilitating compound identification.In addition,QSRR can be used to study compound retention mechanisms and support drug screening efforts.This review provides a comprehensive analysis of QSRR workflows and applications,with a special focus on the role of artificial intelligence-an area not thoroughly explored in previous reviews.Moreover,we discuss current limitations in RT prediction and propose promising solutions.Overall,this review offers a fresh perspective on future QSRR research,encouraging the development of innovative strategies that enable the diverse applications of QSRR models in chromatographic analysis.展开更多
Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interacti...Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interaction network for these QTGs has not yet been established.In this study,we use 18K-rice lines to identify QTGs and their epistatic interactions affecting rice heading date.We identify 264 pairs of interacting quantitative trait loci(QTL)and construct a comprehensive genetic network of these QTL.On average,the epistatic effects of QTL pairs are estimated to be approximately 12.5%of additive effects of identified QTL.Importantly,epistasis varies among different alleles of several heading date genes.Additionally,57 pairs of interacting QTGs are also significant in their epistatic effects on 12 other agronomic traits.The identified QTL genetic interactions are further validated using near-isogenic lines,yeast two-hybrid,and split-luciferase complementation assays.Overall,this study provides a genetic network of rice heading date genes,which plays a crucial role in regulating rice heading date and influencing multiple related agronomic traits.This network serves as a foundation for understanding the genetic mechanisms of rice quantitative traits and for advancing rice molecular breeding.展开更多
The dynamic,heterogeneous nature of Edge computing in the Internet of Things(Edge-IoT)and Industrial IoT(IIoT)networks brings unique and evolving cybersecurity challenges.This study maps cyber threats in Edge-IoT/IIoT...The dynamic,heterogeneous nature of Edge computing in the Internet of Things(Edge-IoT)and Industrial IoT(IIoT)networks brings unique and evolving cybersecurity challenges.This study maps cyber threats in Edge-IoT/IIoT environments to the Adversarial Tactics,Techniques,and Common Knowledge(ATT&CK)framework by MITRE and introduces a lightweight,data-driven scoring model that enables rapid identification and prioritization of attacks.Inspired by the Factor Analysis of Information Risk model,our proposed scoring model integrates four key metrics:Common Vulnerability Scoring System(CVSS)-based severity scoring,Cyber Kill Chain–based difficulty estimation,Deep Neural Networks-driven detection scoring,and frequency analysis based on dataset prevalence.By aggregating these indicators,the model generates comprehensive risk profiles,facilitating actionable prioritization of threats.Robustness and stability of the scoring model are validated through non-parametric correlation analysis using Spearman’s and Kendall’s rank correlation coefficients,demonstrating consistent performance across diverse scenarios.The approach culminates in a prioritized attack ranking that provides actionable guidance for risk mitigation and resource allocation in Edge-IoT/IIoT security operations.By leveraging real-world data to align MITRE ATT&CK techniques with CVSS metrics,the framework offers a standardized and practically applicable solution for consistent threat assessment in operational settings.The proposed lightweight scoring model delivers rapid and reliable results under dynamic cyber conditions,facilitating timely identification of attack scenarios and prioritization of response strategies.Our systematic integration of established taxonomies with data-driven indicators strengthens practical risk management and supports strategic planning in next-generation IoT deployments.Ultimately,this work advances adaptive threat modeling for Edge/IIoT ecosystems and establishes a robust foundation for evidence-based prioritization in emerging cyber-physical infrastructures.展开更多
This work established a quantitative method to access the shear stability of aerobic granular sludge(AGS)and validated its feasibility by using the mature AGS from a pilot-scale(50 tons/day)membrane bioreactor(MBR)for...This work established a quantitative method to access the shear stability of aerobic granular sludge(AGS)and validated its feasibility by using the mature AGS from a pilot-scale(50 tons/day)membrane bioreactor(MBR)for treating real municipal wastewater.The results showed that the changing rate( S)of the peak area(S)of granule size distribution(GSD)exhibited an exponential relationship(R^(2)≥0.76)with the shear time(y=a−b·c^(x)),which was a suitable indicative index to reflect the shear stability of different AGS samples.The limiting granule size(LGS)was defined and proposed to characterize the equilibrium size for AGS after being sheared for a period of time,whose value in terms of Dv50 showed high correlation(R^(2)=0.92)with the parameter a.The free Ca^(2+)(28.44-34.21 mg/L)in the influent specifically interacted with polysaccharides(PS)in the granule’s extracellular polymeric substance(EPS)as a nucleation site,thereby inducing the formation of Ca precipitation to enhance its Young’s modulus,while Ca^(2+) primarily interacted with PS in soluble metabolic product(SMP)during the initial granulation process.Furthermore,the Young’s modulus significantly affected the parameter a related to shear stability(R^(2)=0.99).Since the parameter a was more closely related(R^(2)=1.00)to S than that of the parameter b or c,the excellent correlation(R^(2)=0.99)between the parameter a and the wet density further verified the feasibility of this method.展开更多
BACKGROUND Scientifically sound and reasonable care strategies in surgical nursing play a crucial role in facilitating postoperative recovery and preventing complications.This study focused on the application of quant...BACKGROUND Scientifically sound and reasonable care strategies in surgical nursing play a crucial role in facilitating postoperative recovery and preventing complications.This study focused on the application of quantitative assessment strategies to postoperative care.By quantitatively analyzing the effects of nursing interventions,we explored their feasibility and effectiveness at improving postoperative recovery quality and reducing the incidence of complications.This study provides a scientific basis for nursing practice and offers new insights into nursing management with significant clinical value.AIM To analyze the efficacy of postoperative quantitative assessment strategy-based nursing care for patients with colorectal cancer(CRC).METHODS This randomized controlled trial evaluated the ability of nursing interventions using a quantitative assessment strategy to prevent postoperative complications and enhance patient recovery.Patients with CRC were randomly divided into routine nursing(RN)and quantitative assessment strategy nursing(QASN)groups.The RN group received standard care,while the QASN group also underwent screenings for visual analog scale for pain,Barthel Index for functional recovery,and self-rating anxiety scale and self-rating depression scale for psychological status.Follow-ups were conducted on postoperative days 1,7,14,28,and 56.RESULTS The participants’baseline characteristics did not significantly differ between study groups,thereby ensuring the reliability of the results.The QASN vs RN group showed significant improvements in pain management(visual analog scale scores)and psychological status(self-rating anxiety scale and self-rating depression scale scores)and a reduced incidence of postoperative complications(P<0.05).The follow-up evaluations at specified intervals confirmed these findings,indicating that quantitative assessment strategies significantly enhanced patients’postoperative pain management and psychological well-being.CONCLUSION Nursing interventions using structured quantitative assessments demonstrated significantly improved postoperative recovery and quality of life in patients with CRC,supporting their integration into standard postoperative care protocols.展开更多
Objective:To monitor the incidence of immune-related adverse events(irAEs)in patients treated with immune checkpoint inhibitors(ICIs)and programmed cell death protein-1(PD-1),and to evaluate the effectiveness of nursi...Objective:To monitor the incidence of immune-related adverse events(irAEs)in patients treated with immune checkpoint inhibitors(ICIs)and programmed cell death protein-1(PD-1),and to evaluate the effectiveness of nursing interventions using a quantitative scoring system.Methods:A retrospective analysis was performed on 65 cancer patients who received PD-1 therapy at the Oncology Department of Baotou Cancer Hospital from December 2023 to December 2024.The study examined the clinical features and blood test results related to irAEs.The National Cancer Institute’s Common Terminology Criteria for Adverse Events(NCI-CTCAE)was used to grade the severity of these events,which were classified into five levels.Based on the NCI-CTCAE scores,appropriate nursing measures were implemented,and a comprehensive risk assessment framework was developed.Results:The study group showed lower complication rates,overall incidence,and average hospital stay compared to the control group(P<0.05).Among the 65 patients,twenty-eight(43.07%)experienced a total of 35 irAEs,with 2(5.71%)being grade 3 or 4.The most frequent irAEs were dermatological conditions(34.29%),particularly rash with itching.The occurrence of irAEs did not correlate with patient gender,age,blood parameters(hemoglobin,white blood cell count,platelet count,etc.),or liver function(P>0.05),but it was associated with tumor type(P<0.05).Conclusion:PD-1 treatment is generally safe,with a low incidence of severe(grade 3 or higher)irAEs.Close monitoring is essential to ensure early detection,intervention,and management of irAEs,thereby maintaining a low level of adverse events and enhancing the safety and efficacy of PD-1 therapy.Implementing a quantitative risk scoring system for nursing care can decrease the rate of complications,enhance patient safety,and potentially reduce hospital stays and medical costs.展开更多
Design patterns offer reusable solutions for common software issues,enhancing quality.The advent of generative large language models(LLMs)marks progress in software development,but their efficacy in applying design pa...Design patterns offer reusable solutions for common software issues,enhancing quality.The advent of generative large language models(LLMs)marks progress in software development,but their efficacy in applying design patterns is not fully assessed.The recent introduction of generative large language models(LLMs)like ChatGPT and CoPilot has demonstrated significant promise in software development.They assist with a variety of tasks including code generation,modeling,bug fixing,and testing,leading to enhanced efficiency and productivity.Although initial uses of these LLMs have had a positive effect on software development,their potential influence on the application of design patterns remains unexplored.This study introduces a method to quantify LLMs’ability to implement design patterns,using Role-Based Metamodeling Language(RBML)for a rigorous specification of the pattern’s problem,solution,and transformation rules.The method evaluates the pattern applicability of a software application using the pattern’s problem specification.If deemed applicable,the application is input to the LLM for pattern application.The resulting application is assessed for conformance to the pattern’s solution specification and for completeness against the pattern’s transformation rules.Evaluating the method with ChatGPT 4 across three applications reveals ChatGPT’s high proficiency,achieving averages of 98%in conformance and 87%in completeness,thereby demonstrating the effectiveness of the method.Using RBML,this study confirms that LLMs,specifically ChatGPT 4,have great potential in effective and efficient application of design patterns with high conformance and completeness.This opens avenues for further integrating LLMs into complex software engineering processes.展开更多
Background Quantitative flow ratio(QFR)based lesion selection for percutaneous coronary intervention(PCI)treatment has shown clinical benefits in terms of reduced risk for myocardial infarction and repeat revasculariz...Background Quantitative flow ratio(QFR)based lesion selection for percutaneous coronary intervention(PCI)treatment has shown clinical benefits in terms of reduced risk for myocardial infarction and repeat revascularization.Whether this benefit is consistent across different age groups still needs further investigation.Methods In this prespecified subgroup study of FAVORⅢChina trial,we compared long-term clinical outcomes between QFR-guided and angiography-guided PCI among different age groups among 3825 enrolled subjects.The primary endpoint was major adverse cardiac events(MACEs),a composite of all-cause death,myocardial infarction,and ischemia-driven revascularization.Results Of the 3825 patients,1717(44.9%)were aged≥65 years.At baseline,patients≥65 had higher rates of hypertension,hyperlipidaemia,stroke history(P<0.0001),and peripheral vascular disease(P=0.024)and had higher SYNTAX scores(P=0.0095).Compared with standard angiography guidance,the QFR-guided strategy consistently reduced the 1-year(≥65 years,6.04%vs.9.19%,HR=0.65,95%CI:0.46–0.92;<65 years,5.53%vs.8.43%,HR=0.65,95%CI:0.47–0.91)and 3-year MACE rates in both age groups(≥65 years,11.8%vs.15.2%,HR:0.75,95%CI:0.58–0.98;<65 years,9.5%vs.14.6%,HR=0.63;95%CI:0.49–0.81),without a significant interaction(Pinteraction=0.99).Within the QFR-guided group,the 3-year MACE rate in patients with deferred vessels was numerically greater in patients aged≥65 years than in those aged<65 years(8.3%vs.3.0%,P=0.10).Conclusions Although with higher rate of comorbidities and more complex coronary anatomy,the long-term benefit of the QFR-guided PCI strategy remained consistent in patients≥65 years,compared with those<65 years.展开更多
Cryptocurrency,a booming decentralised asset designed based on the blockchain architecture,is particularly important to the market at the present time by studying the volatility risk of cryptocurrencies.In this paper,...Cryptocurrency,a booming decentralised asset designed based on the blockchain architecture,is particularly important to the market at the present time by studying the volatility risk of cryptocurrencies.In this paper,we empirically analyse the volatility risk of cryptocurrencies through quantitative analysis models,comprehensively using the Markov state transition GARCH model with skewed distribution(Skew-MSGARCH)and the autoregressive conditional volatility density ARJI model introducing the Poisson jump factor,and selecting the earliest developed and the most mature currency price volatility daily return series,to deeply explore the volatility risk of digital cryptocurrencies.risk.Finally,it can be seen through in-depth analyses that the expectation factor and information inducement are the main reasons leading to the exacerbation of the volatility risk of digital cryptocurrencies.It is recommended that this situation be optimised and improved in terms of the value function of digital cryptocurrencies themselves and the implementation of systematic risk management and regulatory innovation.As an important component of the digital economy,blockchain technology can effectively regulate and improve the volatility of digital cryptocurrencies under macroeconomic policies,thereby maintaining the security and stability of emerging financial markets.展开更多
0 INTRODUCTION Gas injection refers to the natural gas charging into pre-existing oil reservoirs,which often leads to notable changes in gas-oil ratio(GOR),oil density,and phase states,depending on the pressure-temper...0 INTRODUCTION Gas injection refers to the natural gas charging into pre-existing oil reservoirs,which often leads to notable changes in gas-oil ratio(GOR),oil density,and phase states,depending on the pressure-temperature condition of the reservoirs(Meulbroek et al.,1998;Blanc and Connan,1994;Evans et al.,1971).展开更多
文摘This study utilizes two complementary models,the Time-Varying Parameter Vector Autoregressive Diebold–Yilmaz(TVP-VAR-DY)and the Time-Varying Parameter Vector Autoregressive Barunik–Křehlik(TVP-VAR-BK),to investigate the dynamic volatility transmission between exchange rates and stock returns in major commodity-exporting and-importing countries.The analysis focuses on periods of quantitative easing(QE)and quantitative tightening(QT)from March 15,2020 to December 30,2022.The countries examined are Canada and Australia(major commodity exporters)and the UK and Germany(major commodity importers).An essential contribution of this paper is new empirical insights into the dynamics of stock market returns and the transmission of volatility between these markets and exchange rates during the QE and QT periods.The results reveal that causality primarily flows from stock markets to exchange rates,especially during the QT period across all investment horizons.The Toronto Stock Exchange(TSX)emerges as the principal net driver among the markets under study.Furthermore,the Canadian exchange rate(USDCAD)and the Australian Stock Exchange(ASX)are the most significantly affected indices within the network across various investment horizons(excluding the long-term).These findings underscore the importance for investors and policymakers to consider the interplay between exchange rates and stock market returns,particularly in the context of the QE and QT periods,as well as other economic,political,and health-related events.Our findings are relevant to various stakeholders,including governments,traders,portfolio managers,and multinationals.
基金supported by the National Natural Science Foundation of China(Grant No.12372233)the Fund of NPU-Duke China Seed Program(Grant No.119003067)the“111 Project”of China(Grant No.B17037-106).
文摘The concept of local shock strength and a quantitative measure index str of local shock strength are proposed,derived from the oblique shock relation and the monotonic relationship between total pressure loss ratio and normal Mach number.Utilizing the high density gradient characteristic of shock waves and the oblique shock relation,a post-processing algorithm for two-dimensional flow field data is developed.The objective of the post-processing algorithm is to obtain specific shock wave location coordinates and calculate the corresponding str from flow filed data under the calibration of the oblique shock relation.Valida-tion of this post-processing algorithm is conducted using a standard model example that can be solved analytically.Combining the concept of local shock strength with the post-processing algorithm,a local shock strength quantitative mapping approach is established for the first time.This approach enables a quantitative measure and visualization of local shock strength at distinct locations,represented by color mapping on the shock structures.The approach can be applied to post-processing numerical sim-ulation data of two-dimensional flows.Applications to the intersection of two left-running oblique shock waves(straight shock waves),the bow shock in front of a cylinder(curved shock wave),and Mach reflection(mixed straight and curved shock waves)demonstrate the accuracy,and effectiveness of the mapping approach in investigating diverse shock wave phenomena.The quan-titative mapping approach of str may be a valuable tool in the design of supersonic/hypersonic vehicles and the exploration of shock wave evolution.
基金supported by National Natural Science Foundation of China(32302371 to Junbin Chen)the National Key Research and Development Program,Ministry of Science and Technology of China(2022YFD1201802 to Wangsheng Zhu)Research Program from State Key Laboratory of Maize Biobreeding(SKLMB2424 to Wangsheng Zhu).
文摘Pythium stalk rot(PSR)is a destructive disease of maize,severely affecting yield and grain quality.The identification of quantitative trait loci(QTL)or genes for resistance to PSR forms the basis of diseaseresistant hybrids breeding.In this study,a major QTL,Resistance to Pythium stalk rot 1(RPSR1),was identified from a set of recombinant inbred lines derived from MS71 and POP.Using a recombinant progeny testing strategy,RPSR1 was fine-mapped in a 472 kb interval.Through candidate gene expression,gene knock-down and knock-out studies,a leucine-rich repeat receptor-like kinase gene,PEP RECEPTOR 2(ZmPEPR2),was assigned as a PSR resistance gene.These results provide insights into the genetic architecture of resistance to PSR in maize,which should facilitate breeding maize for resistance to stalk rot.
基金supported by the Guangdong Major Project of Basic and Applied Basic Research(2023B0303000002)the National Natural Science Foundation of China(No.52206089)+3 种基金the Guangdong Basic and Applied Basic Research Foundation(2024A1515010288,2023B1515120005)the Natural Science Foundation of Shenzhen(JCYJ20230807093315033)the Shenzhen Engineering Research Center,Southern University of Science and Technology(No.XMHT20230208003)high level of special funds(G03034K001)。
文摘All-vanadium flow batteries(VFBs)are one of the most promising large-scale energy storage technologies.Conducting an operando quantitative analysis of the polarizations in VFBs under different conditions is essential for developing high power density batteries.Here,we employ an operando decoupling method to quantitatively analyze the polarizations in each electrochemical and chemical reaction of VFBs under different catalytic conditions.Results show that the reduction reaction of V^(3+)presents the largest activation polarization,while the reduction reaction of VO_(2)^(+)primarily contributes to concentration polarizations due to the formation of the intermediate product V_(2)O_(3)^(3+).Additionally,it is found that the widely used electrode catalytic methods,incorporating oxygen functional groups and electrodepositing Bi,not only enhance the reaction kinetics but also exacerbate concentration polarizations simultaneously,especially during the discharge process.Specifically,in the battery with the high oxygen-containing electrodes,the negative side still accounts for the majority of activation loss(75.3%)at 200 mA cm^(-2),but it comes down to 36,9% after catalyzing the negative reactions with bismuth.This work provides an effective way to probe the limiting steps in flow batteries under various working conditions and offers insights for effectively enhancing battery performance for future developments.
基金funded by the National Natural Scientific Foundation of China(Nos.52304008,52404038,52474043)the China Postdoctoral Science Foundation(No.2023MD734223)+1 种基金the Key Laboratory of Well Stability and Fluid&Rock Mechanics in Oil and Gas Reservoir of Shaanxi Province(No.23JS047)the Youth Talent Lifting Program of Xi'an Science and Technology Association(No.959202413078)。
文摘Supercritical CO_(2)(SC-CO_(2))fracturing stands out a promising waterless stimulation technique in the development of unconventional resources.While numerous studies have delved into the inducedfracture mechanism of SC-CO_(2),the small scale of rock samples and synthetic materials used in many studies have limited a comprehensive understanding of fracture propagation in unconventional formations.In this study,cubic tight sandstone samples with dimensions of 300 mm were employed to conduct SC-CO_(2)fractu ring experiments under true-triaxial stre ss conditions.The spatial morphology and quantitative attributes of fracture induced by water and SC-CO_(2)fracturing were compared,while the impact of in-situ stress on fracture propagation was also investigated.The results indicate that the SCCO_(2)fracturing takes approximately ten times longer than water fracturing.Furthermore,under identical stress condition,the breakdown pressure(BP)for SC-CO_(2)fracturing is nearly 25%lower than that for water fracturing.A quantitative analysis of fracture morphology reveals that water fracturing typically produces relatively simple fracture pattern,with the primary fracture distribution predominantly controlled by bedding planes.In contrast,SC-CO_(2)fracturing results in a more complex fracture morphology.As the differential of horizontal principal stress increases,the BP for SC-CO_(2)fractured rock exhibits a downward trend,and the induced fracture morphology becomes more simplified.Moreover,the presence of abnormal in-situ stress leads to a further increase in the BP for SC-CO_(2)fracturing,simultaneously enhancing the development of a more conductive fracture network.These findings provide critical insights into the efficiency and behavior of SC-CO_(2)fracturing in comparison to traditional water-based fracturing,offering valuable implication for its potential applications in unconventional reservoirs.
基金the National Natural Science Foundation of China(No.12174229 and 22375117)Natural Science Foundation of Shandong Province(No.ZR2022YQ02 and ZR2023MB149)Taishan Scholars Program of Shandong Province(No.tsqn202306152)for financial support.
文摘Quantitative detection of trace small-sized nanoplastics(<100 nm)remains a significant challenge in surface-enhanced Raman scattering(SERS).To tackle this issue,we developed a hydrophobic CuO@Ag nanowire substrate and introduced a multiplex-feature analysis strategy based on the coffee ring effect.This substrate not only offers high Raman enhancement but also exhibits a high probability of detection(POD),enabling rapid and accurate identification of 50 nm polystyrene nanoplastics over a broad concentration range(1–10−10 wt%).Importantly,experimental results reveal a strong correlation between the coffee ring formation and the concentration of nanoplastic dispersion.By incorporating Raman signal intensity,coffee ring diameter,and POD as combined features,we established a machine learning-based mapping between nanoplastic concentration and coffee ring characteristics,allowing precise predictions of dispersion concentration.The mean squared error of these predictions is remarkably low,ranging from 0.21 to 0.54,representing a 19 fold improvement in accuracy compared to traditional linear regression-based methods.This strategy effectively integrates SERS with wettability modification techniques,ensuring high sensitivity and fingerprinting capabilities,while addressing the limitations of Raman signal intensity in accurately reflecting concentration changes at ultra-low levels,providing a new idea for precise SERS measurements of nanoplastics.
基金supported by the grant from the National Natural Science Foundation of China(No.72071019)grant from the Natural Science Foundation of Chongqing(No.cstc2021jcyj-msxmX0185).
文摘Bone age assessment(BAA)aims to determine whether a child’s growth and development are normal concerning their chronological age.To predict bone age more accurately based on radiographs,and for the left-hand X-ray images of different races model can have better adaptability,we propose a neural network in parallel with the quantitative features from the left-hand bone measurements for BAA.In this study,a lightweight feature extractor(LFE)is designed to obtain the featuremaps fromradiographs,and amodule called attention erasermodule(AEM)is proposed to capture the fine-grained features.Meanwhile,the dimensional information of the metacarpal parts in the radiographs is measured to enhance the model’s generalization capability across images fromdifferent races.Ourmodel is trained and validated on the RSNA,RHPE,and digital hand atlas datasets,which include images from various racial groups.The model achieves a mean absolute error(MAE)of 4.42 months on the RSNA dataset and 15.98 months on the RHPE dataset.Compared to ResNet50,InceptionV3,and several state-of-the-art methods,our proposed method shows statistically significant improvements(p<0.05),with a reduction in MAE by 0.2±0.02 years across different racial datasets.Furthermore,t-tests on the features also confirm the statistical significance of our approach(p<0.05).
文摘Risk management often plays an important role in decision making un-der uncertainty.In quantitative risk management,assessing and optimizing risk metrics requires eficient computing techniques and reliable theoretical guarantees.In this pa-per,we introduce several topics on quantitative risk management and review some of the recent studies and advancements on the topics.We consider several risk metrics and study decision models that involve the metrics,with a main focus on the related com-puting techniques and theoretical properties.We show that stochastic optimization,as a powerful tool,can be leveraged to effectively address these problems.
基金National Natural Science Foundation of China(12072166)Inner Mongolia Autonomous Region Science and Technology Plan Project(2021GG0254)+2 种基金Supported by Key Laboratory of Infinite-Dimensional Hamiltonian System and Its Algorithm Application(Inner Mongolia Normal University),Ministry of Education(2023KFZD02)Inner Mongolia Autonomous Region Applied Mathematics Center Independent Research Key Project(ZZYJZD2022002)Inner Mongolia Autonomous Region Universities Basic Scientific Business Fee Research Project(JY20220075)。
文摘Mg-4.8Zn-0.8Y,Mg-18Zn-3Y,Mg-15Zn-5Y,Mg-30Zn-5Y and Mg-42Zn-7Y(wt%)alloys containing icosahedral quasicrystalline phases were prepared using the ordinary solidification method.The impact of Mg matrix porosity on the tensile strength and hardness of the alloys was studied.The porosity of the Mg matrix was quantitatively assessed using scanning electron microscope and Image-Pro Plus 6.0 software.Tensile tests were conducted at room temperature.Results show that the maximum tensile strength of the alloy is 175.56 MPa,with a corresponding Mg matrix porosity of 76.74%.Through fitting analysis,it is determined that the maximum tensile strength is achieved when the porosity of the Mg matrix is 64.87%.The microhardness test results indicate a gradual decrease in alloy hardness with increasing the porosity of Mg matrix.This study provides an effective quantitative analysis method for enhancing the mechanical properties of magnesium alloys.
基金Supported by Regional Science Foundation of China,National Natural Science Foundation(No.82160820)General Program of Guizhou Provincial Natural Science Foundation[QianKeHe Foundation-ZK(2023)General153].
文摘[Objectives]To establish an HPLC method for the quantitative determination of multiple phenolic acid components in Tetracera asiatica medicinal material,providing a basis for establishing its quality standards.[Methods]An Inertsil ODS-C 18 column(250 mm×4.6 mm,5μm)was used.The mobile phase consisted of acetonitrile-0.2% phosphoric acid solution(10:90).The flow rate was 1.0 mL/min.The detection wavelength was 274 nm.The column temperature was 25℃.The injection volume was 10μL.The content of three components,gallic acid,protocatechuic acid,and protocatechualdehyde,was determined in 13 batches of T.asiatica.[Results]Gallic acid showed good linearity within the range of 0.020-6.400μg/mL,protocatechuic acid within 0.201-6.432μg/mL,and protocatechualdehyde within 0.202-6.464μg/mL(r>0.9990).The average recovery rates ranged from 98.61%to 101.17%,with RSD s between 1.21%and 2.69%.[Conclusions]The quantitative determination method established in this study is simple and feasible,and can provide a basis for the quality evaluation of T.asiatica.
基金supported by the Shanghai Sailing Program,China(Grant No.:23YF1413300).
文摘Quantitative structure-retention relationship(QSRR)is an important tool in chromatography.QSRR examines the correlation between molecular structures and their retention behaviors during chromatographic separation.This approach involves developing models for predicting the retention time(RT)of analytes,thereby accelerating method development and facilitating compound identification.In addition,QSRR can be used to study compound retention mechanisms and support drug screening efforts.This review provides a comprehensive analysis of QSRR workflows and applications,with a special focus on the role of artificial intelligence-an area not thoroughly explored in previous reviews.Moreover,we discuss current limitations in RT prediction and propose promising solutions.Overall,this review offers a fresh perspective on future QSRR research,encouraging the development of innovative strategies that enable the diverse applications of QSRR models in chromatographic analysis.
基金supported by the National Natural Science Foundation of China(32222064 and 32341030)the Natural Science Foundation of Shanghai(22ZR1445800)Zhejiang Provincial Natural Science Foundation of China(LQ24C130008).
文摘Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interaction network for these QTGs has not yet been established.In this study,we use 18K-rice lines to identify QTGs and their epistatic interactions affecting rice heading date.We identify 264 pairs of interacting quantitative trait loci(QTL)and construct a comprehensive genetic network of these QTL.On average,the epistatic effects of QTL pairs are estimated to be approximately 12.5%of additive effects of identified QTL.Importantly,epistasis varies among different alleles of several heading date genes.Additionally,57 pairs of interacting QTGs are also significant in their epistatic effects on 12 other agronomic traits.The identified QTL genetic interactions are further validated using near-isogenic lines,yeast two-hybrid,and split-luciferase complementation assays.Overall,this study provides a genetic network of rice heading date genes,which plays a crucial role in regulating rice heading date and influencing multiple related agronomic traits.This network serves as a foundation for understanding the genetic mechanisms of rice quantitative traits and for advancing rice molecular breeding.
基金supported by the“Regional Innovation System&Education(RISE)”through the Seoul RISE Center,funded by the Ministry of Education(MOE)and the Seoul Metropolitan Government(2025-RISE-01-018-05)supported by Quad Miners Corp。
文摘The dynamic,heterogeneous nature of Edge computing in the Internet of Things(Edge-IoT)and Industrial IoT(IIoT)networks brings unique and evolving cybersecurity challenges.This study maps cyber threats in Edge-IoT/IIoT environments to the Adversarial Tactics,Techniques,and Common Knowledge(ATT&CK)framework by MITRE and introduces a lightweight,data-driven scoring model that enables rapid identification and prioritization of attacks.Inspired by the Factor Analysis of Information Risk model,our proposed scoring model integrates four key metrics:Common Vulnerability Scoring System(CVSS)-based severity scoring,Cyber Kill Chain–based difficulty estimation,Deep Neural Networks-driven detection scoring,and frequency analysis based on dataset prevalence.By aggregating these indicators,the model generates comprehensive risk profiles,facilitating actionable prioritization of threats.Robustness and stability of the scoring model are validated through non-parametric correlation analysis using Spearman’s and Kendall’s rank correlation coefficients,demonstrating consistent performance across diverse scenarios.The approach culminates in a prioritized attack ranking that provides actionable guidance for risk mitigation and resource allocation in Edge-IoT/IIoT security operations.By leveraging real-world data to align MITRE ATT&CK techniques with CVSS metrics,the framework offers a standardized and practically applicable solution for consistent threat assessment in operational settings.The proposed lightweight scoring model delivers rapid and reliable results under dynamic cyber conditions,facilitating timely identification of attack scenarios and prioritization of response strategies.Our systematic integration of established taxonomies with data-driven indicators strengthens practical risk management and supports strategic planning in next-generation IoT deployments.Ultimately,this work advances adaptive threat modeling for Edge/IIoT ecosystems and establishes a robust foundation for evidence-based prioritization in emerging cyber-physical infrastructures.
基金supported by the Key Technologies Research and Development Program of Guangzhou (No.2023B03J1284)Guangdong Yuehai Water Investment Co.,Ltd. (No.CC80-QT01-2020-0010).
文摘This work established a quantitative method to access the shear stability of aerobic granular sludge(AGS)and validated its feasibility by using the mature AGS from a pilot-scale(50 tons/day)membrane bioreactor(MBR)for treating real municipal wastewater.The results showed that the changing rate( S)of the peak area(S)of granule size distribution(GSD)exhibited an exponential relationship(R^(2)≥0.76)with the shear time(y=a−b·c^(x)),which was a suitable indicative index to reflect the shear stability of different AGS samples.The limiting granule size(LGS)was defined and proposed to characterize the equilibrium size for AGS after being sheared for a period of time,whose value in terms of Dv50 showed high correlation(R^(2)=0.92)with the parameter a.The free Ca^(2+)(28.44-34.21 mg/L)in the influent specifically interacted with polysaccharides(PS)in the granule’s extracellular polymeric substance(EPS)as a nucleation site,thereby inducing the formation of Ca precipitation to enhance its Young’s modulus,while Ca^(2+) primarily interacted with PS in soluble metabolic product(SMP)during the initial granulation process.Furthermore,the Young’s modulus significantly affected the parameter a related to shear stability(R^(2)=0.99).Since the parameter a was more closely related(R^(2)=1.00)to S than that of the parameter b or c,the excellent correlation(R^(2)=0.99)between the parameter a and the wet density further verified the feasibility of this method.
文摘BACKGROUND Scientifically sound and reasonable care strategies in surgical nursing play a crucial role in facilitating postoperative recovery and preventing complications.This study focused on the application of quantitative assessment strategies to postoperative care.By quantitatively analyzing the effects of nursing interventions,we explored their feasibility and effectiveness at improving postoperative recovery quality and reducing the incidence of complications.This study provides a scientific basis for nursing practice and offers new insights into nursing management with significant clinical value.AIM To analyze the efficacy of postoperative quantitative assessment strategy-based nursing care for patients with colorectal cancer(CRC).METHODS This randomized controlled trial evaluated the ability of nursing interventions using a quantitative assessment strategy to prevent postoperative complications and enhance patient recovery.Patients with CRC were randomly divided into routine nursing(RN)and quantitative assessment strategy nursing(QASN)groups.The RN group received standard care,while the QASN group also underwent screenings for visual analog scale for pain,Barthel Index for functional recovery,and self-rating anxiety scale and self-rating depression scale for psychological status.Follow-ups were conducted on postoperative days 1,7,14,28,and 56.RESULTS The participants’baseline characteristics did not significantly differ between study groups,thereby ensuring the reliability of the results.The QASN vs RN group showed significant improvements in pain management(visual analog scale scores)and psychological status(self-rating anxiety scale and self-rating depression scale scores)and a reduced incidence of postoperative complications(P<0.05).The follow-up evaluations at specified intervals confirmed these findings,indicating that quantitative assessment strategies significantly enhanced patients’postoperative pain management and psychological well-being.CONCLUSION Nursing interventions using structured quantitative assessments demonstrated significantly improved postoperative recovery and quality of life in patients with CRC,supporting their integration into standard postoperative care protocols.
基金Baotou City Health Science and Technology Plan(Project No.:2023wsjkkj109)。
文摘Objective:To monitor the incidence of immune-related adverse events(irAEs)in patients treated with immune checkpoint inhibitors(ICIs)and programmed cell death protein-1(PD-1),and to evaluate the effectiveness of nursing interventions using a quantitative scoring system.Methods:A retrospective analysis was performed on 65 cancer patients who received PD-1 therapy at the Oncology Department of Baotou Cancer Hospital from December 2023 to December 2024.The study examined the clinical features and blood test results related to irAEs.The National Cancer Institute’s Common Terminology Criteria for Adverse Events(NCI-CTCAE)was used to grade the severity of these events,which were classified into five levels.Based on the NCI-CTCAE scores,appropriate nursing measures were implemented,and a comprehensive risk assessment framework was developed.Results:The study group showed lower complication rates,overall incidence,and average hospital stay compared to the control group(P<0.05).Among the 65 patients,twenty-eight(43.07%)experienced a total of 35 irAEs,with 2(5.71%)being grade 3 or 4.The most frequent irAEs were dermatological conditions(34.29%),particularly rash with itching.The occurrence of irAEs did not correlate with patient gender,age,blood parameters(hemoglobin,white blood cell count,platelet count,etc.),or liver function(P>0.05),but it was associated with tumor type(P<0.05).Conclusion:PD-1 treatment is generally safe,with a low incidence of severe(grade 3 or higher)irAEs.Close monitoring is essential to ensure early detection,intervention,and management of irAEs,thereby maintaining a low level of adverse events and enhancing the safety and efficacy of PD-1 therapy.Implementing a quantitative risk scoring system for nursing care can decrease the rate of complications,enhance patient safety,and potentially reduce hospital stays and medical costs.
文摘Design patterns offer reusable solutions for common software issues,enhancing quality.The advent of generative large language models(LLMs)marks progress in software development,but their efficacy in applying design patterns is not fully assessed.The recent introduction of generative large language models(LLMs)like ChatGPT and CoPilot has demonstrated significant promise in software development.They assist with a variety of tasks including code generation,modeling,bug fixing,and testing,leading to enhanced efficiency and productivity.Although initial uses of these LLMs have had a positive effect on software development,their potential influence on the application of design patterns remains unexplored.This study introduces a method to quantify LLMs’ability to implement design patterns,using Role-Based Metamodeling Language(RBML)for a rigorous specification of the pattern’s problem,solution,and transformation rules.The method evaluates the pattern applicability of a software application using the pattern’s problem specification.If deemed applicable,the application is input to the LLM for pattern application.The resulting application is assessed for conformance to the pattern’s solution specification and for completeness against the pattern’s transformation rules.Evaluating the method with ChatGPT 4 across three applications reveals ChatGPT’s high proficiency,achieving averages of 98%in conformance and 87%in completeness,thereby demonstrating the effectiveness of the method.Using RBML,this study confirms that LLMs,specifically ChatGPT 4,have great potential in effective and efficient application of design patterns with high conformance and completeness.This opens avenues for further integrating LLMs into complex software engineering processes.
文摘Background Quantitative flow ratio(QFR)based lesion selection for percutaneous coronary intervention(PCI)treatment has shown clinical benefits in terms of reduced risk for myocardial infarction and repeat revascularization.Whether this benefit is consistent across different age groups still needs further investigation.Methods In this prespecified subgroup study of FAVORⅢChina trial,we compared long-term clinical outcomes between QFR-guided and angiography-guided PCI among different age groups among 3825 enrolled subjects.The primary endpoint was major adverse cardiac events(MACEs),a composite of all-cause death,myocardial infarction,and ischemia-driven revascularization.Results Of the 3825 patients,1717(44.9%)were aged≥65 years.At baseline,patients≥65 had higher rates of hypertension,hyperlipidaemia,stroke history(P<0.0001),and peripheral vascular disease(P=0.024)and had higher SYNTAX scores(P=0.0095).Compared with standard angiography guidance,the QFR-guided strategy consistently reduced the 1-year(≥65 years,6.04%vs.9.19%,HR=0.65,95%CI:0.46–0.92;<65 years,5.53%vs.8.43%,HR=0.65,95%CI:0.47–0.91)and 3-year MACE rates in both age groups(≥65 years,11.8%vs.15.2%,HR:0.75,95%CI:0.58–0.98;<65 years,9.5%vs.14.6%,HR=0.63;95%CI:0.49–0.81),without a significant interaction(Pinteraction=0.99).Within the QFR-guided group,the 3-year MACE rate in patients with deferred vessels was numerically greater in patients aged≥65 years than in those aged<65 years(8.3%vs.3.0%,P=0.10).Conclusions Although with higher rate of comorbidities and more complex coronary anatomy,the long-term benefit of the QFR-guided PCI strategy remained consistent in patients≥65 years,compared with those<65 years.
文摘Cryptocurrency,a booming decentralised asset designed based on the blockchain architecture,is particularly important to the market at the present time by studying the volatility risk of cryptocurrencies.In this paper,we empirically analyse the volatility risk of cryptocurrencies through quantitative analysis models,comprehensively using the Markov state transition GARCH model with skewed distribution(Skew-MSGARCH)and the autoregressive conditional volatility density ARJI model introducing the Poisson jump factor,and selecting the earliest developed and the most mature currency price volatility daily return series,to deeply explore the volatility risk of digital cryptocurrencies.risk.Finally,it can be seen through in-depth analyses that the expectation factor and information inducement are the main reasons leading to the exacerbation of the volatility risk of digital cryptocurrencies.It is recommended that this situation be optimised and improved in terms of the value function of digital cryptocurrencies themselves and the implementation of systematic risk management and regulatory innovation.As an important component of the digital economy,blockchain technology can effectively regulate and improve the volatility of digital cryptocurrencies under macroeconomic policies,thereby maintaining the security and stability of emerging financial markets.
基金supported by the National Natural Science Foundation of China(NSFC)(No.42272169)the efficient exploration and development technologies and integrated demonstration project for deep and ultra-deep carbonate oil and gas reservoirs in the Tarim Basin(No.2025ZD1402301)+1 种基金the Integrated Project of the Joint Fund for Enterprise Innovation and Development of the National Natural Science Foundation of China(No.U24B6001)the Bureau-Level Scientific Research Project of Northwest Oilfield Company(No.KJ202501).
文摘0 INTRODUCTION Gas injection refers to the natural gas charging into pre-existing oil reservoirs,which often leads to notable changes in gas-oil ratio(GOR),oil density,and phase states,depending on the pressure-temperature condition of the reservoirs(Meulbroek et al.,1998;Blanc and Connan,1994;Evans et al.,1971).
