Photovoltaic(PV)power generation has highly penetrated in distribution networks,providing clean and sustainable energy.However,its uncertain and intermittent power outputs significantly impair network operation,leadin...Photovoltaic(PV)power generation has highly penetrated in distribution networks,providing clean and sustainable energy.However,its uncertain and intermittent power outputs significantly impair network operation,leading to unexpected power loss and voltage fluctuation.To address the uncertainties,this paper proposes a multi-timescale affinely adjustable robust reactive power dispatch(MTAAR-RPD)method to reduce the network power losses as well as alleviate voltage deviations and fluctuations.The MTAAR-RPD aims to coordinate on-load tap changers(OLTCs),capacitor banks(CBs),and PV inverters through a three-stage structure which covers multiple timescales of“hour-minute-second”.The first stage schedules CBs and OLTCs hourly while the second stage dispatches the base reactive power outputs of PV inverter every 15 min.The third stage affinely adjusts the inverter reactive power output based on an optimized Q-P droop controller in real time.The three stages are coordinately optimized by an affinely adjustable robust optimization method.A solution algorithm based on a cutting plane algorithm is developed to solve the optimization problem effectively.The proposed method is verified through theoretical analysis and numerical simulations.展开更多
By some basic transforms and invariant theory, we give two results： 1） an algorithm, which can be used to judge if two Boolean functions are affinely equivalent and to obtain the equivalence relationship if they are...By some basic transforms and invariant theory, we give two results： 1） an algorithm, which can be used to judge if two Boolean functions are affinely equivalent and to obtain the equivalence relationship if they are equivalent. This is useful in studying Boolean functions and in engineering. For example, we classify all 8-variable homogeneous bent functions of degree 3 into two classes; 2） Reed-Muller codes R（4,6）/R（1,6）, R（3,7）/R（1,7） are classified efficiently.展开更多
In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the op...In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the optimality conditions of the problem,we introduce appropriate affine matrix and construct an affine scaling ARC subproblem with linearized constraints.Composite step methods and reduced Hessian methods are applied to tackle the linearized constraints.As a result,a standard unconstrained ARC subproblem is deduced and its solution can supply sufficient decrease.The fraction to the boundary rule maintains the strict feasibility(for nonnegative constraints on variables)of every iteration point.Reflection techniques are employed to prevent the iterations from approaching zero too early.Under mild assumptions,global convergence of the algorithm is analysed.Preliminary numerical results are reported.展开更多
This paper deals with representations of groups by "affine" automorphisms of compact, convex spaces, with special focus on "irreducible" representations: equivalently"minimal" actions. Wh...This paper deals with representations of groups by "affine" automorphisms of compact, convex spaces, with special focus on "irreducible" representations: equivalently"minimal" actions. When the group in question is P SL(2, R), the authors exhibit a oneone correspondence between bounded harmonic functions on the upper half-plane and a certain class of irreducible representations. This analysis shows that, surprisingly, all these representations are equivalent. In fact, it is found that all irreducible affine representations of this group are equivalent. The key to this is a property called "linear Stone-Weierstrass"for group actions on compact spaces. If it holds for the "universal strongly proximal space"of the group(to be defined), then the induced action on the space of probability measures on this space is the unique irreducible affine representation of the group.展开更多
Heart disease remains a leading cause of mortality worldwide,emphasizing the urgent need for reliable and interpretable predictive models to support early diagnosis and timely intervention.However,existing Deep Learni...Heart disease remains a leading cause of mortality worldwide,emphasizing the urgent need for reliable and interpretable predictive models to support early diagnosis and timely intervention.However,existing Deep Learning(DL)approaches often face several limitations,including inefficient feature extraction,class imbalance,suboptimal classification performance,and limited interpretability,which collectively hinder their deployment in clinical settings.To address these challenges,we propose a novel DL framework for heart disease prediction that integrates a comprehensive preprocessing pipeline with an advanced classification architecture.The preprocessing stage involves label encoding and feature scaling.To address the issue of class imbalance inherent in the personal key indicators of the heart disease dataset,the localized random affine shadowsampling technique is employed,which enhances minority class representation while minimizing overfitting.At the core of the framework lies the Deep Residual Network(DeepResNet),which employs hierarchical residual transformations to facilitate efficient feature extraction and capture complex,non-linear relationships in the data.Experimental results demonstrate that the proposed model significantly outperforms existing techniques,achieving improvements of 3.26%in accuracy,3.16%in area under the receiver operating characteristics,1.09%in recall,and 1.07%in F1-score.Furthermore,robustness is validated using 10-fold crossvalidation,confirming the model’s generalizability across diverse data distributions.Moreover,model interpretability is ensured through the integration of Shapley additive explanations and local interpretable model-agnostic explanations,offering valuable insights into the contribution of individual features to model predictions.Overall,the proposed DL framework presents a robust,interpretable,and clinically applicable solution for heart disease prediction.展开更多
The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aer...The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aerial Vehicles(QUAVs).This scheme mainly consists of predefinedtime estimators and fixed-time tracking controllers,with a hybrid Laplacian matrix describing the communication among these QUAVs.At the first layer,we devise predefined time estimators for leading and following QUAVs,enabling accurate estimation of desired information.In the second layer,we initially devise a fixed-time hybrid observer to estimate unknown disturbances and actuator faults.Fixedtime translational tracking controllers are then proposed,and the intermediary control input from these controllers is used to extract the desired attitude and angular velocities for the fixed-time rotational tracking controllers.We employ an exact tracking differentiator to handle variables that are challenging to differentiate directly.The paper includes a demonstration of the control system stability through mathematical proof,as well as the presentation of simulation results and comparative simulations.展开更多
Artificial intelligence(AI)researchers and cheminformatics specialists strive to identify effective drug precursors while optimizing costs and accelerating development processes.Digital molecular representation plays ...Artificial intelligence(AI)researchers and cheminformatics specialists strive to identify effective drug precursors while optimizing costs and accelerating development processes.Digital molecular representation plays a crucial role in achieving this objective by making molecules machine-readable,thereby enhancing the accuracy of molecular prediction tasks and facilitating evidence-based decision making.This study presents a comprehensive review of small molecular representations and AI-driven drug discovery downstream tasks utilizing these representations.The research methodology begins with the compilation of small molecule databases,followed by an analysis of fundamental molecular representations and the models that learn these representations from initial forms,capturing patterns and salient features across extensive chemical spaces.The study then examines various drug discovery downstream tasks,including drug-target interaction(DTI)prediction,drug-target affinity(DTA)prediction,drug property(DP)prediction,and drug generation,all based on learned representations.The analysis concludes by highlighting challenges and opportunities associated with machine learning(ML)methods for molecular representation and improving downstream task performance.Additionally,the representation of small molecules and AI-based downstream tasks demonstrates significant potential in identifying traditional Chinese medicine(TCM)medicinal substances and facilitating TCM target discovery.展开更多
There is no consensus on the tectonic evolution of the western Jiangnan Orogen(WJO)during 770-750 Ma.Thus,we reported zircon trace elements and U‐Pb‐Hf‐O isotopes and whole-rock geochemistry of the Neoproterozoic t...There is no consensus on the tectonic evolution of the western Jiangnan Orogen(WJO)during 770-750 Ma.Thus,we reported zircon trace elements and U‐Pb‐Hf‐O isotopes and whole-rock geochemistry of the Neoproterozoic tuff located in Longsheng,northern Guangxi,in the WJO,to decipher their origin and tectonic setting.The SIMS U‐Pb zircon age yields a concordia age of 772.1±3.8 Ma,suggesting that the tuff layer formed at 770 Ma.Geochemical data of the tuff and its zircon exhibit continental arc signatures.Oxygen isotopes of the zircon show normal mantle zirconδ^(18)O zircon values of 4.59‰-5.50‰with an average of 5.24‰.The zircon yielded positive ε_(Hf)(t)values of 1.8-5.8 with two-stage model ages of 1.32-1.55 Ga.Based on these data and previous studies,the magma source for the tuff is inferred to have originated from the partial melting of the Mesoproterozoic juvenile crust,as the pre-existing arc materials and mixing with the mantle source under the extensional setting during 770-750 Ma triggered by the slab break-off.We infer that the presence of contemporaneous OIB-type and arc-like magmatism at ca.770-750 Ma along the WJO was related to the slab break-off.展开更多
G protein coupled receptor kinase 2 (GRK2) is a kinase that regulates cardiac signaling activity. Inhibiting GRK2 is a promising mechanism for the treatment of heart failure (HF). Further development and optimization ...G protein coupled receptor kinase 2 (GRK2) is a kinase that regulates cardiac signaling activity. Inhibiting GRK2 is a promising mechanism for the treatment of heart failure (HF). Further development and optimization of inhibitors targeting GRK2 are highly meaningful. Therefore, in order to design GRK2 inhibitors with better performance, the most active molecule was selected as a reference compound from a data set containing 4-pyridylhydrazone derivatives and triazole derivatives, and its scaffold was extracted as the initial scaffold. Then, a powerful optimization-based framework for de novo drug design, guided by binding affinity, was used to generate a virtual molecular library targeting GRK2. The binding affinity of each virtual compound in this dataset was predicted by our developed deep learning model, and the designed potential compound with high binding affinity was selected for molecular docking and molecular dynamics simulation. It was found that the designed potential molecule binds to the ATP site of GRK2, which consists of key amino acids including Arg199, Gly200, Phe202, Val205, Lys220, Met274 and Asp335. The scaffold of the molecule is stabilized mainly by H-bonding and hydrophobic contacts. Concurrently, the reference compound in the dataset was also simulated by docking. It was found that this molecule also binds to the ATP site of GRK2. In addition, its scaffold is stabilized mainly by H-bonding and π-cation stacking interactions with Lys220, as well as hydrophobic contacts. The above results show that the designed potential molecule has similar binding modes to the reference compound, supporting the effectiveness of our framework for activity-focused molecular design. Finally, we summarized the interaction characteristics of general GRK2 inhibitors and gained insight into their molecule-target binding mechanisms, thereby facilitating the expansion of lead to hit compound.展开更多
Conventional adaptive filtering algorithms often exhibit performance degradation when processing multipath interference in raw echoes of spaceborne synthetic aperture radar(SAR)systems due to anomalous outliers,manife...Conventional adaptive filtering algorithms often exhibit performance degradation when processing multipath interference in raw echoes of spaceborne synthetic aperture radar(SAR)systems due to anomalous outliers,manifesting as insufficient convergence and low estimation accuracy.To address this issue,this study proposes a novel robust adaptive filtering algorithm,namely the M-estimation-based minimum error entropy with affine projection(APMMEE)algorithm.This algorithm inherits the joint multi-data-block update mechanism of the affine projection algorithm,enabling rapid adaptation to the dynamic characteristics of raw echoes and achieving fast convergence.Meanwhile,it incorporates the M-estimation-based minimum error entropy(MMEE)criterion,which weights error samples in raw echoes through M-estimation functions,effectively suppressing outlier interference during the algorithm update.Both the system identification simulations and practical multipath interference suppression experiments using raw echoes demonstrate that the proposed APMMEE algorithm exhibits superior filtering performance.展开更多
During the sizing process,yarn congestion fault occurs at the reed teeth of a sizing machine.At present,the yarn congestion fault is generally handled by manual detection.The sizing production line operates on a large...During the sizing process,yarn congestion fault occurs at the reed teeth of a sizing machine.At present,the yarn congestion fault is generally handled by manual detection.The sizing production line operates on a large scale and runs continuously.Untimely handling of the yarn congestion fault causes a large amount of yarn waste.In this research,a machine vision-based algorithm for yarn congestion fault detection is developed.Through the analysis of the congestion fault and interference contour characteristics,the basic idea of image phase subtraction to identify the congestion fault is determined.To address the interference information appearing after image phase subtraction,the image pre-processing methods of Canny edge extraction and mean filtering are employed.According to the fault size and location characteristics,the fault contour detection algorithm based on inter-frame difference is designed.To mitigate the camera vibration interference,the anti-vibration interference algorithm based on affine transformation is studied,and the fault detection algorithm for the total yarn congestion fault is determined.The detection of 20 sets of field data is carried out,and the detection rate reaches 90%.This fault detection algorithm realizes the automatic detection of yarn congestion fault of sizing machine with certain real-time performance and accuracy.展开更多
NH_(4)V_(4)O_(10)(NVO)as a cathode material of zincion battery is prone to collapse in the repeated process of embedding and de-embedding of Zn^(2+),and its application is limited by the instability of the material.He...NH_(4)V_(4)O_(10)(NVO)as a cathode material of zincion battery is prone to collapse in the repeated process of embedding and de-embedding of Zn^(2+),and its application is limited by the instability of the material.Here,calciumdoped ammonium vanadate(CNVO)is successfully synthesized via a one-step hydrothermal approach.The intercalated Ca2+in NVO serves as a firm pillar between the[VO_n]layers to maintain the structure stability during the ion insertion/extraction process.Furthermore,density functional theory(DFT)calculations and ex situ experiments reveal that CNVO demonstrates higher affinity and conductivity compared to NVO,which can effectively improve the kinetics of Zn^(2+)diffusion,reduce the electrostatic repulsion of Zn^(2+)during intercalation and deintercalation,and maintaining the stability of the layered structure.As a result,the CNVO material demonstrates outstanding electrochemical performance,delivering a specific capacity of 183 m Ah·g^(-1)at 5 A·g^(-1).Moreover,it sustains an impressive 91%capacity retention after 1300 cycles.展开更多
The ecological and evolutionary mechanisms underlying montane biodiversity patterns remain unresolved.To understand which factors determined community assembly rules in mountains,biogeographic affinity that represents...The ecological and evolutionary mechanisms underlying montane biodiversity patterns remain unresolved.To understand which factors determined community assembly rules in mountains,biogeographic affinity that represents the biogeographic and evolutionary history of species should incorporate with current environments.We aim to address two following questions:1)How does plant taxonomic and phylogenetic diversity with disparate biogeographic affinitiesvary along the subtropical elevational gradient?2)How do biogeographic affinityand environmental drivers regulate the community assembly?We collected woody plant survey data of 32 forest plots in a subtropical mountain of Mt.Guanshan with typical transitional characteristics,including 250 woody plant species belonging to 56 families and 118 genera.We estimated the effects of biogeographic affinity,climate and soil properties on taxonomic and phylogenetic diversity of plant communities employing linear regression and structural equation models.We found that the richness of temperate-affiliated species increased with elevations,but the evenness decreased,while tropical-affiliatedspecies had no significantpatterns.Winter temperature directly or indirectly via biogeographic affinityshaped the assemblage of woody plant communities along elevations.Biogeographic affinityaffected what kind of species could colonize higher elevations while local environment determined their fitnessto adapt.These results suggest that biogeographic affinityand local environment jointly lead to the dominance of temperate-affiliated species at higher elevations and shape the diversity of woody plant communities along elevational gradients.Our findingshighlight the legacy effect of biogeographic affinityon the composition and structure of subtropical montane forests.展开更多
Revealing the latent low-dimensional geometric structure of high-dimensional data is a crucial task in unsupervised representation learning.Traditional manifold learning,as a typical method for discovering latent geom...Revealing the latent low-dimensional geometric structure of high-dimensional data is a crucial task in unsupervised representation learning.Traditional manifold learning,as a typical method for discovering latent geometric structures,has provided important nonlinear insight for the theoretical development of unsupervised representation learning.However,due to the shallow learning mechanism of the existing methods,they can only exploit the simple geometric structure embedded in the initial data,such as the local linear structure.Traditional manifold learning methods are fairly limited in mining higher-order nonlinear geometric information,which is also crucial for the development of unsupervised representation learning.To address the abovementioned limitations,this paper proposes a novel dynamic geometric structure learning model(DGSL)to explore the true latent nonlinear geometric structure.Specifically,by mathematically analysing the reconstruction loss function of manifold learning,we first provide universal geometric relational function between the curvature and the non-Euclidean metric of the initial data.Then,we leverage geometric flow to design a deeply iterative learning model to optimize this relational function.Our method can be viewed as a general-purpose algorithm for mining latent geometric structures,which can enhance the performance of geometric representation methods.Experimentally,we perform a set of representation learning tasks on several datasets.The experimental results show that our proposed method is superior to traditional methods.展开更多
Sini Decoction(SNT)is a traditional formula recognized for its efficacy in warming the spleen and stomach and dispersing cold.However,elucidating the mechanism of action of SNT remains challenging due to its complex m...Sini Decoction(SNT)is a traditional formula recognized for its efficacy in warming the spleen and stomach and dispersing cold.However,elucidating the mechanism of action of SNT remains challenging due to its complex multiple components.This study utilized a synergistic approach combining two-dimensional fluorescence difference in gel electrophoresis(2D-DIGE)-based drug affinity responsive target stability(DARTS)with label-free quantitative proteomics techniques to identify the direct and indirect protein targets of SNT in myocardial infarction.The analysis identified 590 proteins,with 30 proteins showing significant upregulation and 51 proteins showing downregulation when comparing the SNT group with the model group.Through the integration of 2D-DIGE DARTS with proteomics data and pharmacological assessments,the findings indicate that protein disulfide-isomerase A3(PDIA3)may serve as a potential protein target through which SNT provides protective effects on myocardial cells during myocardial infarction.展开更多
The ion coordination affinities of the commonly found metal ions were evaluated using DFT calculations.The results indicate that the lowest unoccupied molecular orbital(LUMO)energy of metal ions correlates positively ...The ion coordination affinities of the commonly found metal ions were evaluated using DFT calculations.The results indicate that the lowest unoccupied molecular orbital(LUMO)energy of metal ions correlates positively with their binding energies with O(S)ligands,and some metal ions with various valence states also present different affinities.Besides,due to the steric hindrance effects,the mono-and hexa-coordinated metal ions may exhibit different affinities,and the majority of the studied hexa-coordinated metal ions exhibit oxophilicity.These affinity differences perfectly illustrate the activation flotation practice in which the oxyphilic ions are applied to activating oxide minerals,while thiophilic ions are applied to activating sulfide minerals.展开更多
纽结理论是拓扑学的一个重要分支,虚拟纽结理论是经典纽结理论的推广,对它的研究是通过一种图解理论来展开的。虚拟纽结多项式是一类以多项式表达的虚拟纽结不变量,例如Arrow多项式和Wriggle多项式。Affine index多项式是以虚拟纽结图...纽结理论是拓扑学的一个重要分支,虚拟纽结理论是经典纽结理论的推广,对它的研究是通过一种图解理论来展开的。虚拟纽结多项式是一类以多项式表达的虚拟纽结不变量,例如Arrow多项式和Wriggle多项式。Affine index多项式是以虚拟纽结图的整数标记定义的单变量多项式。本文主要计算一类特殊虚拟纽结的Affine index多项式。按照Cheng着色的规则,对虚拟纽结图的每一段弧进行整数标记,计算每个经典交叉点的指标值,进而得到这类特殊虚拟纽结的Affine index多项式的表达式。Knot theory is an important branch of topology. Virtual knot theory is a generalization of classical knot theory, and its research is carried out through a graphic theory. The virtual knot polynomial refers to a class of virtual knot invariant expressed by polynomials, such as the Arrow polynomial and the Wriggle polynomial. The affine index polynomial is a univariate polynomial defined by the integer label of a virtual knot graph. In this paper, we mainly calculate affine index polynomials for a special class of virtual knots. According to the rules of Cheng coloring, we will integer label each arc of the virtual knot graph and calculate the index value of each classical crossings, and then get the expression of the affine index polynomial of this special virtual knot.展开更多
In this article,we explain how the famous Archimedes’principle of flotation can be used to construct various floating bodies.We survey some of the most important results regarding the floating bodies,including their ...In this article,we explain how the famous Archimedes’principle of flotation can be used to construct various floating bodies.We survey some of the most important results regarding the floating bodies,including their relations with affine surface area and projection body,their extensions in different settings such as space forms and log-concave functions,and mention some associated open problems.展开更多
Objective:Salvia miltiorrhiza is widely used in traditional Chinese medicine for treating cardiovascular and cerebrovascular diseases,with tanshinones being its major active components.This study aims to systematicall...Objective:Salvia miltiorrhiza is widely used in traditional Chinese medicine for treating cardiovascular and cerebrovascular diseases,with tanshinones being its major active components.This study aims to systematically elucidate the core transcriptional circuitry controlling tanshinone production,thereby establishing a mechanistic framework to optimize phytochemical yield and advance sustainable cultivation strategies for this pharmaceutically vital species.Methods:Transcriptome profiling revealed that the transcription factor SmWRKY69 is specifically expressed in the root periderm of S.miltiorrhiza.DNA affinity purification sequencing(DAPseq)was used to identify its potential target genes,and cis-element analysis predicted W-box motifs in the promoters of SmCPS1 and SmKSL1.Yeast one-hybrid(Y1H)assays were employed to validate its regulatory interactions with candidate gene promoters.Results:SmWRKY69 was found to directly bind to the promoters of SmCPS1 and SmKSL1,key genes in the tanshinone biosynthetic pathway,through W-box elements,indicating its role as a transcriptional regulator.Conclusion:SmWRKY69 regulates tanshinone biosynthesis by directly targeting SmCPS1 and SmKSL1,providing a valuable genetic target for metabolic engineering to enhance the therapeutic quality of S.miltiorrhiza.展开更多
In this paper,we shall study structures of even lattice vertex operator algebras by using the geometry of the varieties of their semi-conformal vectors.We first give the varieties of semi-conformal vectors of a family...In this paper,we shall study structures of even lattice vertex operator algebras by using the geometry of the varieties of their semi-conformal vectors.We first give the varieties of semi-conformal vectors of a family of vertex operator algebras V_(√kA_(1)) associated to rank-one positive definite even lattices √kA_(1) for arbitrary positive integers k to characterize these even lattice vertex operator algebras.In such a family of lattice vertex operator algebras V_(√kA_(1)),the vertex operator algebra V_(√2A_(1)) is different from others.Hence we describe the varieties of semi-conformal vectors of V_(√2A_(1)) and the fixed vertex operator subalgebra V^(+)√2A_(1).Moreover,as applications,we study the relations between vertex operator algebras V_(√kA_(1) )and L_(sl_(2))(k,0)for arbitrary positive integers k by the viewpoint of semi-conformal homomorphisms of vertex operator algebras.For case k=2,in the series of rational simple affine vertex operator algebras L_(sl_(2))(k,0)for positive integers k,we show that L_(sl_(2))(2,0)is a unique frame vertex operator algebra with rank 3.展开更多
基金supported in part by the Scientific Research Foundation of Nanjing University of Science and Technology(No.AE89991/255)in part by Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment Project,Southeast University+1 种基金in part by the National Natural Science Foundation of China(No.51677025)in part by the Science and Technology Project of State Grid Corporation(No.SGMD0000YXJS1900502)。
文摘Photovoltaic(PV)power generation has highly penetrated in distribution networks,providing clean and sustainable energy.However,its uncertain and intermittent power outputs significantly impair network operation,leading to unexpected power loss and voltage fluctuation.To address the uncertainties,this paper proposes a multi-timescale affinely adjustable robust reactive power dispatch(MTAAR-RPD)method to reduce the network power losses as well as alleviate voltage deviations and fluctuations.The MTAAR-RPD aims to coordinate on-load tap changers(OLTCs),capacitor banks(CBs),and PV inverters through a three-stage structure which covers multiple timescales of“hour-minute-second”.The first stage schedules CBs and OLTCs hourly while the second stage dispatches the base reactive power outputs of PV inverter every 15 min.The third stage affinely adjusts the inverter reactive power output based on an optimized Q-P droop controller in real time.The three stages are coordinately optimized by an affinely adjustable robust optimization method.A solution algorithm based on a cutting plane algorithm is developed to solve the optimization problem effectively.The proposed method is verified through theoretical analysis and numerical simulations.
基金the National Natural Science Foundation of China (Grant Nos. 69973034, 60373087, 60673071)
文摘By some basic transforms and invariant theory, we give two results： 1） an algorithm, which can be used to judge if two Boolean functions are affinely equivalent and to obtain the equivalence relationship if they are equivalent. This is useful in studying Boolean functions and in engineering. For example, we classify all 8-variable homogeneous bent functions of degree 3 into two classes; 2） Reed-Muller codes R（4,6）/R（1,6）, R（3,7）/R（1,7） are classified efficiently.
基金Supported by the National Natural Science Foundation of China(12071133)Natural Science Foundation of Henan Province(252300421993)Key Scientific Research Project of Higher Education Institutions in Henan Province(25B110005)。
文摘In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the optimality conditions of the problem,we introduce appropriate affine matrix and construct an affine scaling ARC subproblem with linearized constraints.Composite step methods and reduced Hessian methods are applied to tackle the linearized constraints.As a result,a standard unconstrained ARC subproblem is deduced and its solution can supply sufficient decrease.The fraction to the boundary rule maintains the strict feasibility(for nonnegative constraints on variables)of every iteration point.Reflection techniques are employed to prevent the iterations from approaching zero too early.Under mild assumptions,global convergence of the algorithm is analysed.Preliminary numerical results are reported.
文摘This paper deals with representations of groups by "affine" automorphisms of compact, convex spaces, with special focus on "irreducible" representations: equivalently"minimal" actions. When the group in question is P SL(2, R), the authors exhibit a oneone correspondence between bounded harmonic functions on the upper half-plane and a certain class of irreducible representations. This analysis shows that, surprisingly, all these representations are equivalent. In fact, it is found that all irreducible affine representations of this group are equivalent. The key to this is a property called "linear Stone-Weierstrass"for group actions on compact spaces. If it holds for the "universal strongly proximal space"of the group(to be defined), then the induced action on the space of probability measures on this space is the unique irreducible affine representation of the group.
基金funded by Ongoing Research Funding Program for Project number(ORF-2025-648),King Saud University,Riyadh,Saudi Arabia.
文摘Heart disease remains a leading cause of mortality worldwide,emphasizing the urgent need for reliable and interpretable predictive models to support early diagnosis and timely intervention.However,existing Deep Learning(DL)approaches often face several limitations,including inefficient feature extraction,class imbalance,suboptimal classification performance,and limited interpretability,which collectively hinder their deployment in clinical settings.To address these challenges,we propose a novel DL framework for heart disease prediction that integrates a comprehensive preprocessing pipeline with an advanced classification architecture.The preprocessing stage involves label encoding and feature scaling.To address the issue of class imbalance inherent in the personal key indicators of the heart disease dataset,the localized random affine shadowsampling technique is employed,which enhances minority class representation while minimizing overfitting.At the core of the framework lies the Deep Residual Network(DeepResNet),which employs hierarchical residual transformations to facilitate efficient feature extraction and capture complex,non-linear relationships in the data.Experimental results demonstrate that the proposed model significantly outperforms existing techniques,achieving improvements of 3.26%in accuracy,3.16%in area under the receiver operating characteristics,1.09%in recall,and 1.07%in F1-score.Furthermore,robustness is validated using 10-fold crossvalidation,confirming the model’s generalizability across diverse data distributions.Moreover,model interpretability is ensured through the integration of Shapley additive explanations and local interpretable model-agnostic explanations,offering valuable insights into the contribution of individual features to model predictions.Overall,the proposed DL framework presents a robust,interpretable,and clinically applicable solution for heart disease prediction.
基金supported by Natural Science Basic Research Plan in Shaanxi Province of China(No.2023-JC-QN-0733)Guangdong Basic and Applied Basic Research Foundation,China(No.2022A1515110753)+2 种基金China Postdoctoral Science Foundation(No.2022M722583)China Industry-UniversityResearch Innovation Foundation(No.2022IT188)National Key Laboratory of Air-based Information Perception and Fusion and the Aeronautic Science Foundation of China(No.20220001068001)。
文摘The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aerial Vehicles(QUAVs).This scheme mainly consists of predefinedtime estimators and fixed-time tracking controllers,with a hybrid Laplacian matrix describing the communication among these QUAVs.At the first layer,we devise predefined time estimators for leading and following QUAVs,enabling accurate estimation of desired information.In the second layer,we initially devise a fixed-time hybrid observer to estimate unknown disturbances and actuator faults.Fixedtime translational tracking controllers are then proposed,and the intermediary control input from these controllers is used to extract the desired attitude and angular velocities for the fixed-time rotational tracking controllers.We employ an exact tracking differentiator to handle variables that are challenging to differentiate directly.The paper includes a demonstration of the control system stability through mathematical proof,as well as the presentation of simulation results and comparative simulations.
基金supported by the Shenzhen Key Laboratory of Intelligent Bioinformatics(No.ZDSYS20220422103800001)the Shenzhen Science and Technology Program(No.JCYJ20230807140709020)+2 种基金National Natural Science Foundation of China(Nos.62402489,U22A2041,and 62373172)the China Postdoctoral Science Foundation(No.2023M743688)Guangdong Basic and Applied Basic Research Foundation(Nos.2024A1515011960 and 2023A1515110570)。
文摘Artificial intelligence(AI)researchers and cheminformatics specialists strive to identify effective drug precursors while optimizing costs and accelerating development processes.Digital molecular representation plays a crucial role in achieving this objective by making molecules machine-readable,thereby enhancing the accuracy of molecular prediction tasks and facilitating evidence-based decision making.This study presents a comprehensive review of small molecular representations and AI-driven drug discovery downstream tasks utilizing these representations.The research methodology begins with the compilation of small molecule databases,followed by an analysis of fundamental molecular representations and the models that learn these representations from initial forms,capturing patterns and salient features across extensive chemical spaces.The study then examines various drug discovery downstream tasks,including drug-target interaction(DTI)prediction,drug-target affinity(DTA)prediction,drug property(DP)prediction,and drug generation,all based on learned representations.The analysis concludes by highlighting challenges and opportunities associated with machine learning(ML)methods for molecular representation and improving downstream task performance.Additionally,the representation of small molecules and AI-based downstream tasks demonstrates significant potential in identifying traditional Chinese medicine(TCM)medicinal substances and facilitating TCM target discovery.
基金supported by the National Natural Science Foundation of China(No.41972069)National Major Science and Technology Project on Deep Earth(No.2024ZD1001208)the China Geological Survey(No.DD20221645,DD20221648).
文摘There is no consensus on the tectonic evolution of the western Jiangnan Orogen(WJO)during 770-750 Ma.Thus,we reported zircon trace elements and U‐Pb‐Hf‐O isotopes and whole-rock geochemistry of the Neoproterozoic tuff located in Longsheng,northern Guangxi,in the WJO,to decipher their origin and tectonic setting.The SIMS U‐Pb zircon age yields a concordia age of 772.1±3.8 Ma,suggesting that the tuff layer formed at 770 Ma.Geochemical data of the tuff and its zircon exhibit continental arc signatures.Oxygen isotopes of the zircon show normal mantle zirconδ^(18)O zircon values of 4.59‰-5.50‰with an average of 5.24‰.The zircon yielded positive ε_(Hf)(t)values of 1.8-5.8 with two-stage model ages of 1.32-1.55 Ga.Based on these data and previous studies,the magma source for the tuff is inferred to have originated from the partial melting of the Mesoproterozoic juvenile crust,as the pre-existing arc materials and mixing with the mantle source under the extensional setting during 770-750 Ma triggered by the slab break-off.We infer that the presence of contemporaneous OIB-type and arc-like magmatism at ca.770-750 Ma along the WJO was related to the slab break-off.
基金supported by the National Natural Science Foundation of China Excellent Young Scientist Fund(22422801)the National Natural Science Foundation of China General Project(22278053)+1 种基金the National Natural Science Foundation of China General Project(22078041)Dalian High-level Talents Innovation Support Program(2023RQ059).
文摘G protein coupled receptor kinase 2 (GRK2) is a kinase that regulates cardiac signaling activity. Inhibiting GRK2 is a promising mechanism for the treatment of heart failure (HF). Further development and optimization of inhibitors targeting GRK2 are highly meaningful. Therefore, in order to design GRK2 inhibitors with better performance, the most active molecule was selected as a reference compound from a data set containing 4-pyridylhydrazone derivatives and triazole derivatives, and its scaffold was extracted as the initial scaffold. Then, a powerful optimization-based framework for de novo drug design, guided by binding affinity, was used to generate a virtual molecular library targeting GRK2. The binding affinity of each virtual compound in this dataset was predicted by our developed deep learning model, and the designed potential compound with high binding affinity was selected for molecular docking and molecular dynamics simulation. It was found that the designed potential molecule binds to the ATP site of GRK2, which consists of key amino acids including Arg199, Gly200, Phe202, Val205, Lys220, Met274 and Asp335. The scaffold of the molecule is stabilized mainly by H-bonding and hydrophobic contacts. Concurrently, the reference compound in the dataset was also simulated by docking. It was found that this molecule also binds to the ATP site of GRK2. In addition, its scaffold is stabilized mainly by H-bonding and π-cation stacking interactions with Lys220, as well as hydrophobic contacts. The above results show that the designed potential molecule has similar binding modes to the reference compound, supporting the effectiveness of our framework for activity-focused molecular design. Finally, we summarized the interaction characteristics of general GRK2 inhibitors and gained insight into their molecule-target binding mechanisms, thereby facilitating the expansion of lead to hit compound.
基金supported by Shandong Provincial Natural Science Foundation(No.ZR2022MF314).
文摘Conventional adaptive filtering algorithms often exhibit performance degradation when processing multipath interference in raw echoes of spaceborne synthetic aperture radar(SAR)systems due to anomalous outliers,manifesting as insufficient convergence and low estimation accuracy.To address this issue,this study proposes a novel robust adaptive filtering algorithm,namely the M-estimation-based minimum error entropy with affine projection(APMMEE)algorithm.This algorithm inherits the joint multi-data-block update mechanism of the affine projection algorithm,enabling rapid adaptation to the dynamic characteristics of raw echoes and achieving fast convergence.Meanwhile,it incorporates the M-estimation-based minimum error entropy(MMEE)criterion,which weights error samples in raw echoes through M-estimation functions,effectively suppressing outlier interference during the algorithm update.Both the system identification simulations and practical multipath interference suppression experiments using raw echoes demonstrate that the proposed APMMEE algorithm exhibits superior filtering performance.
基金National Key Research and Development Program of China(No.2017YFB1304001)。
文摘During the sizing process,yarn congestion fault occurs at the reed teeth of a sizing machine.At present,the yarn congestion fault is generally handled by manual detection.The sizing production line operates on a large scale and runs continuously.Untimely handling of the yarn congestion fault causes a large amount of yarn waste.In this research,a machine vision-based algorithm for yarn congestion fault detection is developed.Through the analysis of the congestion fault and interference contour characteristics,the basic idea of image phase subtraction to identify the congestion fault is determined.To address the interference information appearing after image phase subtraction,the image pre-processing methods of Canny edge extraction and mean filtering are employed.According to the fault size and location characteristics,the fault contour detection algorithm based on inter-frame difference is designed.To mitigate the camera vibration interference,the anti-vibration interference algorithm based on affine transformation is studied,and the fault detection algorithm for the total yarn congestion fault is determined.The detection of 20 sets of field data is carried out,and the detection rate reaches 90%.This fault detection algorithm realizes the automatic detection of yarn congestion fault of sizing machine with certain real-time performance and accuracy.
基金supported by the National Natural Science Foundation of China(No.51602193)ClassⅢPeak Discipline of Shanghai-Materials Science and Engineering(High-Energy Beam Intelligent Processing and Green Manufacturing)UK Research and Innovation(UKRI)under the UK government’s Horizon Europe funding guarantee(No.101077226,EP/Y008707/1)
文摘NH_(4)V_(4)O_(10)(NVO)as a cathode material of zincion battery is prone to collapse in the repeated process of embedding and de-embedding of Zn^(2+),and its application is limited by the instability of the material.Here,calciumdoped ammonium vanadate(CNVO)is successfully synthesized via a one-step hydrothermal approach.The intercalated Ca2+in NVO serves as a firm pillar between the[VO_n]layers to maintain the structure stability during the ion insertion/extraction process.Furthermore,density functional theory(DFT)calculations and ex situ experiments reveal that CNVO demonstrates higher affinity and conductivity compared to NVO,which can effectively improve the kinetics of Zn^(2+)diffusion,reduce the electrostatic repulsion of Zn^(2+)during intercalation and deintercalation,and maintaining the stability of the layered structure.As a result,the CNVO material demonstrates outstanding electrochemical performance,delivering a specific capacity of 183 m Ah·g^(-1)at 5 A·g^(-1).Moreover,it sustains an impressive 91%capacity retention after 1300 cycles.
基金financialsupport from the Jiangxi Natural Science Foundation(20242BAB25345)to Z.Z.the Innovation Program of Shanghai Municipal Education Commission(2023ZKZD36)to J.Z.
文摘The ecological and evolutionary mechanisms underlying montane biodiversity patterns remain unresolved.To understand which factors determined community assembly rules in mountains,biogeographic affinity that represents the biogeographic and evolutionary history of species should incorporate with current environments.We aim to address two following questions:1)How does plant taxonomic and phylogenetic diversity with disparate biogeographic affinitiesvary along the subtropical elevational gradient?2)How do biogeographic affinityand environmental drivers regulate the community assembly?We collected woody plant survey data of 32 forest plots in a subtropical mountain of Mt.Guanshan with typical transitional characteristics,including 250 woody plant species belonging to 56 families and 118 genera.We estimated the effects of biogeographic affinity,climate and soil properties on taxonomic and phylogenetic diversity of plant communities employing linear regression and structural equation models.We found that the richness of temperate-affiliated species increased with elevations,but the evenness decreased,while tropical-affiliatedspecies had no significantpatterns.Winter temperature directly or indirectly via biogeographic affinityshaped the assemblage of woody plant communities along elevations.Biogeographic affinityaffected what kind of species could colonize higher elevations while local environment determined their fitnessto adapt.These results suggest that biogeographic affinityand local environment jointly lead to the dominance of temperate-affiliated species at higher elevations and shape the diversity of woody plant communities along elevational gradients.Our findingshighlight the legacy effect of biogeographic affinityon the composition and structure of subtropical montane forests.
基金supported in part by the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(2022QNRC001)the National Natural Science Foundation of China(62406315)+2 种基金China Postdoctoral Science Foundation(2025M771504)GuangDong Basic and Applied Basic Research Foundation(2024A1515110108)Shaanxi Provincial Key Research and Development Program(2025SF-YBXM-023).
文摘Revealing the latent low-dimensional geometric structure of high-dimensional data is a crucial task in unsupervised representation learning.Traditional manifold learning,as a typical method for discovering latent geometric structures,has provided important nonlinear insight for the theoretical development of unsupervised representation learning.However,due to the shallow learning mechanism of the existing methods,they can only exploit the simple geometric structure embedded in the initial data,such as the local linear structure.Traditional manifold learning methods are fairly limited in mining higher-order nonlinear geometric information,which is also crucial for the development of unsupervised representation learning.To address the abovementioned limitations,this paper proposes a novel dynamic geometric structure learning model(DGSL)to explore the true latent nonlinear geometric structure.Specifically,by mathematically analysing the reconstruction loss function of manifold learning,we first provide universal geometric relational function between the curvature and the non-Euclidean metric of the initial data.Then,we leverage geometric flow to design a deeply iterative learning model to optimize this relational function.Our method can be viewed as a general-purpose algorithm for mining latent geometric structures,which can enhance the performance of geometric representation methods.Experimentally,we perform a set of representation learning tasks on several datasets.The experimental results show that our proposed method is superior to traditional methods.
基金supported by the National Natural Science Foundation of China(Nos.82073814,82122066,and 82104328)the"Dawn"Program of the Shanghai Education Commission(No.22SG34)+1 种基金the National Key Research and Development Program of the Ministry of China(No.2022YFC2704603)Shanghai Sailing Program(No.20YF1458900).
文摘Sini Decoction(SNT)is a traditional formula recognized for its efficacy in warming the spleen and stomach and dispersing cold.However,elucidating the mechanism of action of SNT remains challenging due to its complex multiple components.This study utilized a synergistic approach combining two-dimensional fluorescence difference in gel electrophoresis(2D-DIGE)-based drug affinity responsive target stability(DARTS)with label-free quantitative proteomics techniques to identify the direct and indirect protein targets of SNT in myocardial infarction.The analysis identified 590 proteins,with 30 proteins showing significant upregulation and 51 proteins showing downregulation when comparing the SNT group with the model group.Through the integration of 2D-DIGE DARTS with proteomics data and pharmacological assessments,the findings indicate that protein disulfide-isomerase A3(PDIA3)may serve as a potential protein target through which SNT provides protective effects on myocardial cells during myocardial infarction.
基金financially supported by the National Natural Science Foundation of China(Nos.52074356,U20A20269)the Key Technology Research and Development Program,China(No.2022YFC2904503)+4 种基金the Special Fund for the Construction of Hunan Province,China(No.2023SK2061)the Science and Technology Innovation Program of Hunan Province,China(No.2022RC1183)the Changsha Science and Technology Project(Changsha Outstanding Innovative Youth Training Program),ChinaInnovation-driven Project of Central South University,China(No.2023CXQD002)Higher Education Discipline Innovation Project,China(No.B14034)。
文摘The ion coordination affinities of the commonly found metal ions were evaluated using DFT calculations.The results indicate that the lowest unoccupied molecular orbital(LUMO)energy of metal ions correlates positively with their binding energies with O(S)ligands,and some metal ions with various valence states also present different affinities.Besides,due to the steric hindrance effects,the mono-and hexa-coordinated metal ions may exhibit different affinities,and the majority of the studied hexa-coordinated metal ions exhibit oxophilicity.These affinity differences perfectly illustrate the activation flotation practice in which the oxyphilic ions are applied to activating oxide minerals,while thiophilic ions are applied to activating sulfide minerals.
文摘纽结理论是拓扑学的一个重要分支,虚拟纽结理论是经典纽结理论的推广,对它的研究是通过一种图解理论来展开的。虚拟纽结多项式是一类以多项式表达的虚拟纽结不变量,例如Arrow多项式和Wriggle多项式。Affine index多项式是以虚拟纽结图的整数标记定义的单变量多项式。本文主要计算一类特殊虚拟纽结的Affine index多项式。按照Cheng着色的规则,对虚拟纽结图的每一段弧进行整数标记,计算每个经典交叉点的指标值,进而得到这类特殊虚拟纽结的Affine index多项式的表达式。Knot theory is an important branch of topology. Virtual knot theory is a generalization of classical knot theory, and its research is carried out through a graphic theory. The virtual knot polynomial refers to a class of virtual knot invariant expressed by polynomials, such as the Arrow polynomial and the Wriggle polynomial. The affine index polynomial is a univariate polynomial defined by the integer label of a virtual knot graph. In this paper, we mainly calculate affine index polynomials for a special class of virtual knots. According to the rules of Cheng coloring, we will integer label each arc of the virtual knot graph and calculate the index value of each classical crossings, and then get the expression of the affine index polynomial of this special virtual knot.
基金supported by the Research Funding of Wuhan Polytechnic University(2024RZ083)Elisabeth M.Werner’s work was supported by the NSF grant DMS-2103482.Deping Ye’s work was supported by an NSERC grant,Canada.Ning Zhang’s work was supported by the NSF of China(11901217,11971005).
文摘In this article,we explain how the famous Archimedes’principle of flotation can be used to construct various floating bodies.We survey some of the most important results regarding the floating bodies,including their relations with affine surface area and projection body,their extensions in different settings such as space forms and log-concave functions,and mention some associated open problems.
文摘Objective:Salvia miltiorrhiza is widely used in traditional Chinese medicine for treating cardiovascular and cerebrovascular diseases,with tanshinones being its major active components.This study aims to systematically elucidate the core transcriptional circuitry controlling tanshinone production,thereby establishing a mechanistic framework to optimize phytochemical yield and advance sustainable cultivation strategies for this pharmaceutically vital species.Methods:Transcriptome profiling revealed that the transcription factor SmWRKY69 is specifically expressed in the root periderm of S.miltiorrhiza.DNA affinity purification sequencing(DAPseq)was used to identify its potential target genes,and cis-element analysis predicted W-box motifs in the promoters of SmCPS1 and SmKSL1.Yeast one-hybrid(Y1H)assays were employed to validate its regulatory interactions with candidate gene promoters.Results:SmWRKY69 was found to directly bind to the promoters of SmCPS1 and SmKSL1,key genes in the tanshinone biosynthetic pathway,through W-box elements,indicating its role as a transcriptional regulator.Conclusion:SmWRKY69 regulates tanshinone biosynthesis by directly targeting SmCPS1 and SmKSL1,providing a valuable genetic target for metabolic engineering to enhance the therapeutic quality of S.miltiorrhiza.
基金Supported by National Natural Science Foundation of China(Grant No.12475002).
文摘In this paper,we shall study structures of even lattice vertex operator algebras by using the geometry of the varieties of their semi-conformal vectors.We first give the varieties of semi-conformal vectors of a family of vertex operator algebras V_(√kA_(1)) associated to rank-one positive definite even lattices √kA_(1) for arbitrary positive integers k to characterize these even lattice vertex operator algebras.In such a family of lattice vertex operator algebras V_(√kA_(1)),the vertex operator algebra V_(√2A_(1)) is different from others.Hence we describe the varieties of semi-conformal vectors of V_(√2A_(1)) and the fixed vertex operator subalgebra V^(+)√2A_(1).Moreover,as applications,we study the relations between vertex operator algebras V_(√kA_(1) )and L_(sl_(2))(k,0)for arbitrary positive integers k by the viewpoint of semi-conformal homomorphisms of vertex operator algebras.For case k=2,in the series of rational simple affine vertex operator algebras L_(sl_(2))(k,0)for positive integers k,we show that L_(sl_(2))(2,0)is a unique frame vertex operator algebra with rank 3.
