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
Efficient and accurate identification of candidate causal genes within quantitative trait loci(QTL)is a significant challenge in genetic research.Conventional linkage analysis methods often require substantial time an...Efficient and accurate identification of candidate causal genes within quantitative trait loci(QTL)is a significant challenge in genetic research.Conventional linkage analysis methods often require substantial time and resources to identify causal genes.This paper proposes a QTG-LGBM method for prioritizing causal genes in maize based on the Light GBM algorithm.QTG-LGBM dynamically adjusts gene weights and sample proportions during training to mitigate the effects of class imbalance.The method prevents overfitting in datasets with small samples by introducing a regularization term.Experimental results on maize traits,including plant height(PH),flowering time(FT),and tassel branch number(TBN),demonstrated that QTG-LGBM outperforms the commonly used methods QTG-Finder,GBDT,XGBoost,Bernoulli NB,SVM,CNN,and ensemble learning.We validated the generalization of QTG-LGBM using Arabidopsis,rice,Setaria,and sorghum.We also applied QTG-LGBM using reported QTL that affect traits of maize PH,FT and TBN,and FT in Arabidopsis,rice,and sorghum,as well as known causal genes within the QTL.When examining the top 20%of ranked genes,QTG-LGBM demonstrated a significantly higher recall rate of causal genes compared to random selection methods.We identified key gene features affecting phenotypes through feature importance analysis.QTG-LGBM is available at http://www.deepcba.com/QTG-LGBM.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
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
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
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
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
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
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
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
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
3-Nitro-1,2,4-triazol-5-one(NTO)is a typical high-energy,low-sensitivity explosive,and accurate concentration monitoring is critical for crystallization process control.In this study,a high-precision quantitative anal...3-Nitro-1,2,4-triazol-5-one(NTO)is a typical high-energy,low-sensitivity explosive,and accurate concentration monitoring is critical for crystallization process control.In this study,a high-precision quantitative analytical model for NTO concentration in ethanol solutions was developed by integrating real-time ATR-FTIR spectroscopy with chemometric and machine learning techniques.Dynamic spectral data were obtained by designing multi-concentration gradient heating-cooling cycle experiments,abnormal samples were eliminated using the isolation forest algorithm,and the effects of various preprocessing methods on model performance were systematically evaluated.The results show that partial least squares regression(PLSR)exhibits superior generalization ability compared to other models.Vibrational bands corresponding to C=O and–NO_(2)were identified as key predictors for concentration estimation.This work provides an efficient and reliable solution for real-time concentration monitoring during NTO crystallization and holds significant potential for process analytical applications in energetic material manufacturing.展开更多
Objective To quantitatively analyze the policy of centralized drug procurement centralized drug procurement in order to provide reference for the subsequent policy formulation and improvement.Methods Text mining metho...Objective To quantitatively analyze the policy of centralized drug procurement centralized drug procurement in order to provide reference for the subsequent policy formulation and improvement.Methods Text mining method was used to process 15 centralized drugs procurement policies issued at the national level during 2015-2022,and a PMC index evaluation model of centralized drug procurement policies was established.Then,15 centralized drug procurement policies were quantitatively analyzed from the overall and comparative perspective through an evaluation model.Results and Conclusion The average PMC index of 15 centralized drug procurement policies was 6.95,which was acceptable on the whole.Among them,eight were excellent and seven were acceptable.As to the first-order variables,the centralized drugs procurement policy still lacks incentives and constraints.The comparative results show that there are differences in the content and structure of policies,but they are strongly related to each other.Chinese centralized drug procurement policy has been basically formed,which is closely related to medical insurance and medical policies.However,it is still necessary to pay attention to the structure of the policy to ensure the elaboration of the policy content.展开更多
The challenge of aerodynamic noise is a key obstacle in the advancement of low-pressure tube ultra-high-speed maglev transportation,demanding urgent resolution.This study utilizes a broadband noise source model to per...The challenge of aerodynamic noise is a key obstacle in the advancement of low-pressure tube ultra-high-speed maglev transportation,demanding urgent resolution.This study utilizes a broadband noise source model to perform a quantitative analysis of the aerodynamic noise produced by ultra-high-speed maglev trains operating in low-pressure environments.Initially,an external flow field calculation model for the ultra-high-speed maglev train is presented.Subsequently,numerical simulations based on the broadband noise source model are used to examine the noise characteristics.The impact of the train speed and pressure level on noise generation is investigated accordingly.Subsequently,a correlation formula is derived.The results reveal that the amplitude of sound source changes in the streamlined region of the head and tail cars of the train is large,and the amplitude of changes for the middle car is smaller.The noise source strength increases with speed,with a quadrupole noise source becoming dominant when the train speed exceeds 600 km/h.At a speed of 1000 km/h,the noise source intensity from the streamlined area at the rear of the train overcomes that at the front.Furthermore,the noise source decreases as the pressure level in the tube decreases.When the pressure level drops to 0.01 atm,the quadrupole noise source intensity of a train running at 600 km/h significantly weakens and falls below that of the dipole noise source.展开更多
Optimization and simplification of optical systems represent a milestone in advancing the development of handheld and portable laser-induced breakdown spectroscopy(LIBS)systems towards smaller,more integrated forms.Th...Optimization and simplification of optical systems represent a milestone in advancing the development of handheld and portable laser-induced breakdown spectroscopy(LIBS)systems towards smaller,more integrated forms.This research,for the first time,conducted a comprehensive optimization design and comparative analysis of three compact LIBS system optical paths:the paraxial optical path(OP),the off-axis OP,and the reflective OP.The differences in spectral intensity and stability among these paths were revealed,providing a scientific basis for selecting the optimal OP for LIBS systems.The research found that the paraxial OP excels in spectral performance and quantitative analysis accuracy,making it the preferred choice for compact LIBS systems.Specifically,the paraxial OP significantly enhances spectral intensity,achieving a 6 times improvement over the off-axis OP and an even more remarkable 150 times increase compared to the reflective OP,greatly enhancing detection sensitivity.Additionally,the relative standard deviation,spectral stability index,maintains a consistently low level,ranging from 10.9%to 13.4%,significantly outperforming the other two OPs and ensuring the reliability of analytical results.In the field of quantitative analysis,the paraxial OP also demonstrates higher accuracy,precision,and sensitivity,comparing to other OPs.The quantitative analysis models for Si,Cu,and Ti elements exhibit excellent fitting,providing users with high-quality quantitative analysis results that are of great significance for applications in material science,environmental monitoring,industrial inspection,and other fields.In summary,this study not only confirms the enormous application potential of the paraxial OP in compact LIBS systems but also provides valuable practical experience and theoretical support for the miniaturization and integration of LIBS systems.Looking ahead,with continuous technological advancements,the design of the paraxial OP is expected to further propel the widespread adoption of LIBS technology in portable,on-site detection applications.展开更多
A growing number of skin laser treatments have rapidly evolved and increased their role in the field of dermatology,laser treatment is considered to be used for a variety of pigmentary dermatosis as well as aesthetic ...A growing number of skin laser treatments have rapidly evolved and increased their role in the field of dermatology,laser treatment is considered to be used for a variety of pigmentary dermatosis as well as aesthetic problems.The standardized assessment of laser treatment efficacy is crucial for the interpretation and comparison of studies related to laser treatment of skin disorders.In this study,we propose an evaluation method to quantitatively assess laser treatment efficacy based on the image segmentation technology.A tattoo model of Sprague Dawley(SD)rats was established and treated by picosecond laser treatments at varying energy levels.Images of the tattoo models were captured before and after laser treatment,and feature extraction was conducted to quantify the tattooed area and pigment gradation.Subsequently,the clearance rate,which has been a standardized parameter,was calculated.The results indicate that the clearance rates obtained through this quantitative algorithm are comparable and exhibit smaller standard deviations compared with scale scores(4.59%versus 7.93%in the low-energy group,4.01%versus 9.05%in the medium-energy group,and 4.29%versus 10.23%in the high-energy group).This underscores the greater accuracy,objectivity,and reproducibility in assessing treatment responses.The quantitative evaluation of pigment removal holds promise for facilitating faster and more robust assessments in research and development.Additionally,it may enable the optimization of treatments tailored to individual patients,thereby contributing to more effective and personalized dermatological care.展开更多
The implementation of core competencies clarifies social talent needs and guides math classroom evaluation.Lower-grade primary students,highly malleable,need targeted teacher guidance.Teaching evaluation should meet t...The implementation of core competencies clarifies social talent needs and guides math classroom evaluation.Lower-grade primary students,highly malleable,need targeted teacher guidance.Teaching evaluation should meet the talent demands of the times,focusing on core literacy and essential character development.From this perspective,primary math teachers should optimize evaluation,build a diversified system,help students grow in math,find their learning position,and advance confidently.展开更多
AIM:To investigate the effect of 0.01%low-concentration atropine(LA)on quantitative contrast sensitivity function(qCSF)in children with myopia.METHODS:This paired case-control study included 90 eyes of 58 children who...AIM:To investigate the effect of 0.01%low-concentration atropine(LA)on quantitative contrast sensitivity function(qCSF)in children with myopia.METHODS:This paired case-control study included 90 eyes of 58 children who were sex-,age-,and refractionmatched and equally divided into two groups:the 0.01%LA group had undergone 6mo use of daily 0.01%atropine and control group was naïve to LA.Routine ophthalmic examinations and qCSF test without refractive correction were performed.Two groups were compared in monocular and binocular qCSF parameters,including the area under logCSF,CSF acuity,and contrast sensitivity(CS)at 1.0-18.0 cycle per degree(cpd).RESULTS:In the monocular comparison,the CSF acuity of the LA group was significantly higher than that of the control group(7.58±5.51 vs 6.37±4.22 cpd,P<0.05).The subgroup analysis showed that in the 6-9y group,CSF acuity was significantly higher in the LA group than the control group(8.76±6.19 vs 6.54±4.25 cpd,P<0.05),and in the Female group,low refraction sphere group,and high refraction cylinder group,the CS at high spatial frequencies(12.0 and 18.0 cpd)were significantly higher in the LA group than in the control group(all P<0.05).In the binocular test,CSF acuity and CS at 12.0 cpd were significantly higher in the LA group than in the control group(10.95±7.00 vs 8.65±5.12 cpd;0.17±0.33 vs 0.06±0.16,respectively;both P<0.05).CONCLUSION:Use of LA may result in improved CS in children with early onset myopia.展开更多
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 Biological Breeding-Major Projects(2023ZD04067)Hubei Provincial Natural Science Foundation of China(2023AFB832)+1 种基金Guizhou Provincial Basic Research Program(Natural Science)(MS[2025]096)Major Project of Hubei Hongshan Laboratory(2022HSZD031)。
文摘Efficient and accurate identification of candidate causal genes within quantitative trait loci(QTL)is a significant challenge in genetic research.Conventional linkage analysis methods often require substantial time and resources to identify causal genes.This paper proposes a QTG-LGBM method for prioritizing causal genes in maize based on the Light GBM algorithm.QTG-LGBM dynamically adjusts gene weights and sample proportions during training to mitigate the effects of class imbalance.The method prevents overfitting in datasets with small samples by introducing a regularization term.Experimental results on maize traits,including plant height(PH),flowering time(FT),and tassel branch number(TBN),demonstrated that QTG-LGBM outperforms the commonly used methods QTG-Finder,GBDT,XGBoost,Bernoulli NB,SVM,CNN,and ensemble learning.We validated the generalization of QTG-LGBM using Arabidopsis,rice,Setaria,and sorghum.We also applied QTG-LGBM using reported QTL that affect traits of maize PH,FT and TBN,and FT in Arabidopsis,rice,and sorghum,as well as known causal genes within the QTL.When examining the top 20%of ranked genes,QTG-LGBM demonstrated a significantly higher recall rate of causal genes compared to random selection methods.We identified key gene features affecting phenotypes through feature importance analysis.QTG-LGBM is available at http://www.deepcba.com/QTG-LGBM.
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.
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).
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.
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.
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 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 Aeronautical Science Foundation of China(Grant No.20230018072011)。
文摘3-Nitro-1,2,4-triazol-5-one(NTO)is a typical high-energy,low-sensitivity explosive,and accurate concentration monitoring is critical for crystallization process control.In this study,a high-precision quantitative analytical model for NTO concentration in ethanol solutions was developed by integrating real-time ATR-FTIR spectroscopy with chemometric and machine learning techniques.Dynamic spectral data were obtained by designing multi-concentration gradient heating-cooling cycle experiments,abnormal samples were eliminated using the isolation forest algorithm,and the effects of various preprocessing methods on model performance were systematically evaluated.The results show that partial least squares regression(PLSR)exhibits superior generalization ability compared to other models.Vibrational bands corresponding to C=O and–NO_(2)were identified as key predictors for concentration estimation.This work provides an efficient and reliable solution for real-time concentration monitoring during NTO crystallization and holds significant potential for process analytical applications in energetic material manufacturing.
文摘Objective To quantitatively analyze the policy of centralized drug procurement centralized drug procurement in order to provide reference for the subsequent policy formulation and improvement.Methods Text mining method was used to process 15 centralized drugs procurement policies issued at the national level during 2015-2022,and a PMC index evaluation model of centralized drug procurement policies was established.Then,15 centralized drug procurement policies were quantitatively analyzed from the overall and comparative perspective through an evaluation model.Results and Conclusion The average PMC index of 15 centralized drug procurement policies was 6.95,which was acceptable on the whole.Among them,eight were excellent and seven were acceptable.As to the first-order variables,the centralized drugs procurement policy still lacks incentives and constraints.The comparative results show that there are differences in the content and structure of policies,but they are strongly related to each other.Chinese centralized drug procurement policy has been basically formed,which is closely related to medical insurance and medical policies.However,it is still necessary to pay attention to the structure of the policy to ensure the elaboration of the policy content.
基金funded by the Talent Program(Ph.D.Fund)of Chengdu Technological University(grant number 2024RC025)the Natural Science Foundation of Sichuan Province(grant number 2022NSFSC1892)Fundamental Research Funds for the Central Universities(grant number XJ2021KJZK054).
文摘The challenge of aerodynamic noise is a key obstacle in the advancement of low-pressure tube ultra-high-speed maglev transportation,demanding urgent resolution.This study utilizes a broadband noise source model to perform a quantitative analysis of the aerodynamic noise produced by ultra-high-speed maglev trains operating in low-pressure environments.Initially,an external flow field calculation model for the ultra-high-speed maglev train is presented.Subsequently,numerical simulations based on the broadband noise source model are used to examine the noise characteristics.The impact of the train speed and pressure level on noise generation is investigated accordingly.Subsequently,a correlation formula is derived.The results reveal that the amplitude of sound source changes in the streamlined region of the head and tail cars of the train is large,and the amplitude of changes for the middle car is smaller.The noise source strength increases with speed,with a quadrupole noise source becoming dominant when the train speed exceeds 600 km/h.At a speed of 1000 km/h,the noise source intensity from the streamlined area at the rear of the train overcomes that at the front.Furthermore,the noise source decreases as the pressure level in the tube decreases.When the pressure level drops to 0.01 atm,the quadrupole noise source intensity of a train running at 600 km/h significantly weakens and falls below that of the dipole noise source.
基金financially supported by National Natural Science Foundation of China (Nos.62305392 and 62305123)Independent Research and Development Project of Naval Engineering University (No.2023504050)the Nursery Plan Project of Navel University of Engineering (2022)。
文摘Optimization and simplification of optical systems represent a milestone in advancing the development of handheld and portable laser-induced breakdown spectroscopy(LIBS)systems towards smaller,more integrated forms.This research,for the first time,conducted a comprehensive optimization design and comparative analysis of three compact LIBS system optical paths:the paraxial optical path(OP),the off-axis OP,and the reflective OP.The differences in spectral intensity and stability among these paths were revealed,providing a scientific basis for selecting the optimal OP for LIBS systems.The research found that the paraxial OP excels in spectral performance and quantitative analysis accuracy,making it the preferred choice for compact LIBS systems.Specifically,the paraxial OP significantly enhances spectral intensity,achieving a 6 times improvement over the off-axis OP and an even more remarkable 150 times increase compared to the reflective OP,greatly enhancing detection sensitivity.Additionally,the relative standard deviation,spectral stability index,maintains a consistently low level,ranging from 10.9%to 13.4%,significantly outperforming the other two OPs and ensuring the reliability of analytical results.In the field of quantitative analysis,the paraxial OP also demonstrates higher accuracy,precision,and sensitivity,comparing to other OPs.The quantitative analysis models for Si,Cu,and Ti elements exhibit excellent fitting,providing users with high-quality quantitative analysis results that are of great significance for applications in material science,environmental monitoring,industrial inspection,and other fields.In summary,this study not only confirms the enormous application potential of the paraxial OP in compact LIBS systems but also provides valuable practical experience and theoretical support for the miniaturization and integration of LIBS systems.Looking ahead,with continuous technological advancements,the design of the paraxial OP is expected to further propel the widespread adoption of LIBS technology in portable,on-site detection applications.
基金supported by The Shanghai Science and Technology Commission(21S31902700)。
文摘A growing number of skin laser treatments have rapidly evolved and increased their role in the field of dermatology,laser treatment is considered to be used for a variety of pigmentary dermatosis as well as aesthetic problems.The standardized assessment of laser treatment efficacy is crucial for the interpretation and comparison of studies related to laser treatment of skin disorders.In this study,we propose an evaluation method to quantitatively assess laser treatment efficacy based on the image segmentation technology.A tattoo model of Sprague Dawley(SD)rats was established and treated by picosecond laser treatments at varying energy levels.Images of the tattoo models were captured before and after laser treatment,and feature extraction was conducted to quantify the tattooed area and pigment gradation.Subsequently,the clearance rate,which has been a standardized parameter,was calculated.The results indicate that the clearance rates obtained through this quantitative algorithm are comparable and exhibit smaller standard deviations compared with scale scores(4.59%versus 7.93%in the low-energy group,4.01%versus 9.05%in the medium-energy group,and 4.29%versus 10.23%in the high-energy group).This underscores the greater accuracy,objectivity,and reproducibility in assessing treatment responses.The quantitative evaluation of pigment removal holds promise for facilitating faster and more robust assessments in research and development.Additionally,it may enable the optimization of treatments tailored to individual patients,thereby contributing to more effective and personalized dermatological care.
文摘The implementation of core competencies clarifies social talent needs and guides math classroom evaluation.Lower-grade primary students,highly malleable,need targeted teacher guidance.Teaching evaluation should meet the talent demands of the times,focusing on core literacy and essential character development.From this perspective,primary math teachers should optimize evaluation,build a diversified system,help students grow in math,find their learning position,and advance confidently.
基金Supported by National Key Research and Development Program of China(No.2023YFA0915000)。
文摘AIM:To investigate the effect of 0.01%low-concentration atropine(LA)on quantitative contrast sensitivity function(qCSF)in children with myopia.METHODS:This paired case-control study included 90 eyes of 58 children who were sex-,age-,and refractionmatched and equally divided into two groups:the 0.01%LA group had undergone 6mo use of daily 0.01%atropine and control group was naïve to LA.Routine ophthalmic examinations and qCSF test without refractive correction were performed.Two groups were compared in monocular and binocular qCSF parameters,including the area under logCSF,CSF acuity,and contrast sensitivity(CS)at 1.0-18.0 cycle per degree(cpd).RESULTS:In the monocular comparison,the CSF acuity of the LA group was significantly higher than that of the control group(7.58±5.51 vs 6.37±4.22 cpd,P<0.05).The subgroup analysis showed that in the 6-9y group,CSF acuity was significantly higher in the LA group than the control group(8.76±6.19 vs 6.54±4.25 cpd,P<0.05),and in the Female group,low refraction sphere group,and high refraction cylinder group,the CS at high spatial frequencies(12.0 and 18.0 cpd)were significantly higher in the LA group than in the control group(all P<0.05).In the binocular test,CSF acuity and CS at 12.0 cpd were significantly higher in the LA group than in the control group(10.95±7.00 vs 8.65±5.12 cpd;0.17±0.33 vs 0.06±0.16,respectively;both P<0.05).CONCLUSION:Use of LA may result in improved CS in children with early onset myopia.
