The quantitative rules of the transfer and variation of errors,when the Gaussian integral functions F.(z) are evaluated sequentially by recurring,have been expounded.The traditional viewpoint to negate the applicabili...The quantitative rules of the transfer and variation of errors,when the Gaussian integral functions F.(z) are evaluated sequentially by recurring,have been expounded.The traditional viewpoint to negate the applicability and reliability of upward recursive formula in principle is amended.An optimal scheme of upward-and downward-joint recursions has been developed for the sequential F(z) computations.No additional accuracy is needed with the fundamental term of recursion because the absolute error of Fn(z) always decreases with the recursive approach.The scheme can be employed in modifying any of existent subprograms for Fn<z> computations.In the case of p-d-f-and g-type Gaussians,combining this method with Schaad's formulas can reduce,at least,the additive operations by a factor 40%;the multiplicative and exponential operations by a factor 60%.展开更多
A combinatory method of determining the turbulent fluxes in the surface layer has been developed and their general representations have been thus obtained.The universal functions of the (M-O) similarity in the surface...A combinatory method of determining the turbulent fluxes in the surface layer has been developed and their general representations have been thus obtained.The universal functions of the (M-O) similarity in the surface layer can be de- termined by the method.The results calculated by using the ITCE's data indicate that the method is feasible.展开更多
I. INTRODUCTION The exploration for a unified basis of the combinatory logic and the predicate calculus will promote laying a strict and thorough mathematical foundation of the programming language possessing itself o...I. INTRODUCTION The exploration for a unified basis of the combinatory logic and the predicate calculus will promote laying a strict and thorough mathematical foundation of the programming language possessing itself of the functional and logic paradigms. The purpose of this note, proceeding from the algebraic oersoective, is to formulize the first-order mathematical展开更多
The optimization of polymer structures aims to determine an optimal sequence or topology that achieves a given target property or structural performance.This inverse design problem involves searching within a vast com...The optimization of polymer structures aims to determine an optimal sequence or topology that achieves a given target property or structural performance.This inverse design problem involves searching within a vast combinatorial phase space defined by components,se-quences,and topologies,and is often computationally intractable due to its NP-hard nature.At the core of this challenge lies the need to evalu-ate complex correlations among structural variables,a classical problem in both statistical physics and combinatorial optimization.To address this,we adopt a mean-field approach that decouples direct variable-variable interactions into effective interactions between each variable and an auxiliary field.The simulated bifurcation(SB)algorithm is employed as a mean-field-based optimization framework.It constructs a Hamiltonian dynamical system by introducing generalized momentum fields,enabling efficient decoupling and dynamic evolution of strongly coupled struc-tural variables.Using the sequence optimization of a linear copolymer adsorbing on a solid surface as a case study,we demonstrate the applica-bility of the SB algorithm to high-dimensional,non-differentiable combinatorial optimization problems.Our results show that SB can efficiently discover polymer sequences with excellent adsorption performance within a reasonable computational time.Furthermore,it exhibits robust con-vergence and high parallel scalability across large design spaces.The approach developed in this work offers a new computational pathway for polymer structure optimization.It also lays a theoretical foundation for future extensions to topological design problems,such as optimizing the number and placement of side chains,as well as the co-optimization of sequence and topology.展开更多
Neuroscience (also known as neurobiology) is a science that studies the structure, function, development, pharmacology and pathology of the nervous system. In recent years, C. Cotardo has introduced coding theory into...Neuroscience (also known as neurobiology) is a science that studies the structure, function, development, pharmacology and pathology of the nervous system. In recent years, C. Cotardo has introduced coding theory into neuroscience, proposing the concept of combinatorial neural codes. And it was further studied in depth using algebraic methods by C. Curto. In this paper, we construct a class of combinatorial neural codes with special properties based on classical combinatorial structures such as orthogonal Latin rectangle, disjoint Steiner systems, groupable designs and transversal designs. These neural codes have significant weight distribution properties and large minimum distances, and are thus valuable for potential applications in information representation and neuroscience. This study provides new ideas for the construction method and property analysis of combinatorial neural codes, and enriches the study of algebraic coding theory.展开更多
Measuring the lifecycle of low-carbon energy technologies is critical to better understanding the innovation pattern.However,previous studies on lifecycle either focus on technical details or just provide a general ov...Measuring the lifecycle of low-carbon energy technologies is critical to better understanding the innovation pattern.However,previous studies on lifecycle either focus on technical details or just provide a general overview,due to the lack of connection with innovation theories.This article attempts to fill this gap by analyzing the lifecycle from a combinatorial innovation perspective,based on patent data of ten low-carbon energy technologies in China from 1999 to 2018.The problem of estimating lifecycle stages can be transformed into analyzing the rise and fall of knowledge combinations.By building the international patent classification(IPC)co-occurrence matrix,this paper demonstrates the lifecycle evolution of technologies and develops an efficient quantitative index to define lifecycle stages.The mathematical measurement can effectively reflect the evolutionary pattern of technologies.Additionally,this article relates the macro evolution of lifecycle to the micro dynamic mechanism of technology paradigms.The sign of technology maturity is that new inventions tend to follow the patterns established by prior ones.Following this logic,this paper identifies different trends of paradigms in each technology field and analyze their transition.Furthermore,catching-up literature shows that drastic transformation of technology paradigms may open“windows of opportunity”for laggard regions.From the results of this paper,it is clear to see that latecomers can catch up with pioneers especially when there is a radical change in paradigms.Therefore,it is important for policy makers to capture such opportunities during the technology lifecycle and coordinate regional innovation resources.展开更多
In the context of reducing its carbon emissions,the Chinese steel industry is currently undergoing an intelligent transformation to enhance its profitability and sustainability.The optimization of production planning ...In the context of reducing its carbon emissions,the Chinese steel industry is currently undergoing an intelligent transformation to enhance its profitability and sustainability.The optimization of production planning and scheduling plays a pivotal role in realizing these objectives such as improving production efficiency,saving energy,reducing carbon emissions,and enhancing quality.However,current practices in steel enterprises are largely dependent on experience-driven manual decision approaches supported by information systems,which are inadequate to meet the complex requirements of the industry.This study explores the current situation in production planning and scheduling,analyzes the characteristics and limitations of existing methods,and emphasizes the necessity and trends of intelligent systems.It surveys the current literature on production planning and scheduling in steel enterprises and analyzes the theoretical advancements and practical challenges associated with combinatorial and sequential optimization in this field.A key focus is on the limitations of current models and algorithms in effectively addressing the multi-objective and multiconstraint characteristics of steel produc-tion.To overcome these challenges,a novel framework for intelligent production planning and scheduling is proposed.This framework leverages data-and knowledge-driven decision-making and scenario adaptability,enabling the system to respond dynamically to real-time production conditions and market fluctuations.By integrating artificial intelligence and advanced optimization methodologies,the proposed framework improves the efficiency,cost-effectiveness,and environmental sustainability of steel manufacturing.展开更多
The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic ...The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic customer demands.These uncertainties make traditional deterministic models inadequate,often leading to suboptimal or infeasible solutions.To address these challenges,this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms(GA)with Local Search(LS),while incorporating stochastic uncertainty modeling through probabilistic travel times.The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance.This adaptivity enhances the algorithm’s ability to balance exploration and exploitation during the optimization process.Travel time uncertainties are modeled using Gaussian noise,and solution robustness is evaluated through scenario-based simulations.We test our method on a set of benchmark problems from Solomon’s instance suite,comparing its performance under deterministic and stochastic conditions.Results show that the proposed hybrid approach achieves up to a 9%reduction in expected total travel time and a 40% reduction in time window violations compared to baseline methods,including classical GA and non-adaptive hybrids.Additionally,the algorithm demonstrates strong robustness,with lower solution variance across uncertainty scenarios,and converges faster than competing approaches.These findings highlight the method’s suitability for practical logistics applications such as last-mile delivery and real-time transportation planning,where uncertainty and service-level constraints are critical.The flexibility and effectiveness of the proposed framework make it a promising candidate for deployment in dynamic,uncertainty-aware supply chain environments.展开更多
The quantum alternating operator ansatz algorithm(QAOA+)is widely used for constrained combinatorial optimization problems(CCOPs)due to its ability to construct feasible solution spaces.In this paper,we propose a prog...The quantum alternating operator ansatz algorithm(QAOA+)is widely used for constrained combinatorial optimization problems(CCOPs)due to its ability to construct feasible solution spaces.In this paper,we propose a progressive quantum algorithm(PQA)to reduce qubit requirements for QAOA+in solving the maximum independent set(MIS)problem.PQA iteratively constructs a subgraph likely to include the MIS solution of the original graph and solves the problem on it to approximate the global solution.Specifically,PQA starts with a small-scale subgraph and progressively expands its graph size utilizing heuristic expansion strategies.After each expansion,PQA solves the MIS problem on the newly generated subgraph using QAOA+.In each run,PQA repeats the expansion and solving process until a predefined stopping condition is reached.Simulation results show that PQA achieves an approximation ratio of 0.95 using only 5.57%(2.17%)of the qubits and 17.59%(6.43%)of the runtime compared with directly solving the original problem with QAOA+on Erd?s-Rényi(3-regular)graphs,highlighting the efficiency and scalability of PQA.展开更多
In the light of a question of J. L. Krivine about the consistency of an extensional λ-theory,an extensional combinatory logic ECL+U(G)+RU_∞+ is established, with its consistency model provedtheoretically and it is s...In the light of a question of J. L. Krivine about the consistency of an extensional λ-theory,an extensional combinatory logic ECL+U(G)+RU_∞+ is established, with its consistency model provedtheoretically and it is shown the it is not equivalent to any system of universal axioms. It is expressed bythe theory in first order logic that, for every given group G of order n, there simultaneously exist infinitelymany universal retractions and a surjective n-tuple notion, such that each element of G acts as a permutationof the components of the n-tuple, and as an Ap-automorphism of the model; further each of the universalretractions is invarian under the action of the Ap-automorphisms induced by G The difference between thetheory and that of Krivine is the G need not be a symmetric group.展开更多
The clinical benefit of combination therapy is significant,but it is not easy to define the mechanism of complexity and diversity.Previous studies illustrate that phillygenin(Phi)binds in the allosteric inhibit pocket...The clinical benefit of combination therapy is significant,but it is not easy to define the mechanism of complexity and diversity.Previous studies illustrate that phillygenin(Phi)binds in the allosteric inhibit pocket of protein kinase B(AKT),and swertiamarin(Swe)acts on the pleckstrin homology(PH)domain of AKT.However,the combined synergistic effect of relieving the inflammatory response has yet to be elucidated.Based on high sensitivity,specificity and fast-responsibility fluorescent sensors,the Förster resonance energy transfer(FRET)technique offers a route to provide clear insights into physiological and pathological processes.In the study,molecular docking,the fluorescent probes of Phi and Swe for FRET were designed and synthesized.FRET analysis shown that Swe and Phi concurrently acted on the PH domain and allosterically inhibited pocket of AKT,respectively.The combination of Swe and Phi significantly increased the heat stability of AKT and decreased protease-induced degeneration.In lipopolysaccharides(LPS)-induced mice and cells,the combination arrested AKT activation,nuclear factor kappa-B(NF-κB)phosphorylation,and the expression of tumor necrosis factor-α(TNF-α),interleukin(IL)-6 and IL-8.In conclusion,FRET revealed Phi and Swe concurrently targeted AKT on different domains and the combination of Phi and Swe enhanced the anti-inflammatory effect.展开更多
We introduce Quafu-Qcover,an open-source cloud-based software package developed for solving combinatorial optimization problems using quantum simulators and hardware backends.Quafu-Qcover provides a standardized and c...We introduce Quafu-Qcover,an open-source cloud-based software package developed for solving combinatorial optimization problems using quantum simulators and hardware backends.Quafu-Qcover provides a standardized and comprehensive workflow that utilizes the quantum approximate optimization algorithm(QAOA).It facilitates the automatic conversion of the original problem into a quadratic unconstrained binary optimization(QUBO)model and its corresponding Ising model,which can be subsequently transformed into a weight graph.The core of Qcover relies on a graph decomposition-based classical algorithm,which efficiently derives the optimal parameters for the shallow QAOA circuit.Quafu-Qcover incorporates a dedicated compiler capable of translating QAOA circuits into physical quantum circuits that can be executed on Quafu cloud quantum computers.Compared to a general-purpose compiler,our compiler demonstrates the ability to generate shorter circuit depths,while also exhibiting superior speed performance.Additionally,the Qcover compiler has the capability to dynamically create a library of qubits coupling substructures in real-time,utilizing the most recent calibration data from the superconducting quantum devices.This ensures that computational tasks can be assigned to connected physical qubits with the highest fidelity.The Quafu-Qcover allows us to retrieve quantum computing sampling results using a task ID at any time,enabling asynchronous processing.Moreover,it incorporates modules for results preprocessing and visualization,facilitating an intuitive display of solutions for combinatorial optimization problems.We hope that Quafu-Qcover can serve as an instructive illustration for how to explore application problems on the Quafu cloud quantum computers.展开更多
Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization prob-lem.Based on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from ...Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization prob-lem.Based on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from the perspectives of network update strategy,initialization method,and parameter selection.This paper compares the performance of the proposed algorithms with the performance of existing SOM network algorithms on the TSP and compares them with several heuristic algorithms.Simulations show that compared with existing SOM networks,the improved SOM network proposed in this paper improves the convergence rate and algorithm accuracy.Compared with iterated local search and heuristic algorithms,the improved SOM net-work algorithms proposed in this paper have the advantage of fast calculation speed on medium-scale TSP.展开更多
To address the problem of identifying multiple types of additives in lubricating oil,a method based on midinfrared spectral band selection using the eXtreme Gradient Boosting(XGBoost)algorithm combined with the ant co...To address the problem of identifying multiple types of additives in lubricating oil,a method based on midinfrared spectral band selection using the eXtreme Gradient Boosting(XGBoost)algorithm combined with the ant colony optimization(ACO)algorithm is proposed.The XGBoost algorithm was used to train and test three additives,T534(alkyl diphenylamine),T308(isooctyl acid thiophospholipid octadecylamine),and T306(trimethylphenol phosphate),separately,in order to screen for the optimal combination of spectral bands for each additive.The ACO algorithm was used to optimize the parameters of the XGBoost algorithm to improve the identification accuracy.During this process,the support vector machine(SVM)and hybrid bat algorithms(HBA)were included as a comparison,generating four models:ACO-XGBoost,ACO-SVM,HBA-XGboost,and HBA-SVM.The results showed that all four models could identify the three additives efficiently,with the ACO-XGBoost model achieving 100%recognition of all three additives.In addition,the generalizability of the ACO-XGBoost model was further demonstrated by predicting a lubricating oil containing the three additives prepared in our laboratory and a collected sample of commercial oil currently in use。展开更多
Peptide drugs are known for their high biological safety.However,compared with small molecule drugs,peptide drugs are easily oxidized and hydrolyzed as well as short in half-life.Herein,inspired by the long circulatio...Peptide drugs are known for their high biological safety.However,compared with small molecule drugs,peptide drugs are easily oxidized and hydrolyzed as well as short in half-life.Herein,inspired by the long circulation of albumin in blood,we screened albumin binding peptides(ABPs)from a one-bead one-compound(OBOC)peptide library to increase the half-life of peptide drugs.Beads displaying random peptides were screened using fluorescent labeled human serum albumin.Fluorescent beads with specific binding to albumin were isolated for sequencing.The selected ABPs can effectively bind to albumin,thus possessing the long circulation of albumin.The dissociation constant(K_(D))of ABPs to albumin is up to 1×10^(-8)mol/L.Once one of ABPs(ABP2)was coupled to triptorelin,the circulation half-life of triptorelin in mice was significantly prolonged to 263.50 h much longer than that of triptorelin alone(179.07 h).In addition,the combination therapy using ABP-conjugated triptorelin and doxorubicin(DOX)can effectively inhibit the proliferation of tumor cells in mice.The OBOC screening strategy and resulting ABPs showed great potential for enhancing the delivery efficiency of peptide drugs.展开更多
The subsea production system is a vital equipment for offshore oil and gas production.The control system is one of the most important parts of it.Collecting and processing the signals of subsea sensors is the only way...The subsea production system is a vital equipment for offshore oil and gas production.The control system is one of the most important parts of it.Collecting and processing the signals of subsea sensors is the only way to judge whether the subsea production control system is normal.However,subsea sensors degrade rapidly due to harsh working environments and long service time.This leads to frequent false alarm incidents.A combinatorial reasoning-based abnormal sensor recognition method for subsea production control system is proposed.A combinatorial algorithm is proposed to group sensors.The long short-term memory network(LSTM)is used to establish a single inference model.A counting-based judging method is proposed to identify abnormal sensors.Field data from an offshore platform in the South China Sea is used to demonstrate the effect of the proposed method.The results show that the proposed method can identify the abnormal sensors effectively.展开更多
Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well wi...Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex problems.Given the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.展开更多
Sugar aminotransferases(SATs)catalyze the installation of chiral amines onto specific keto sugars,pro-ducing bioactive amino sugars.Their activity has been utilized in artificial reactions,such as using the SAT WecE t...Sugar aminotransferases(SATs)catalyze the installation of chiral amines onto specific keto sugars,pro-ducing bioactive amino sugars.Their activity has been utilized in artificial reactions,such as using the SAT WecE to transform valienone into the valuable a-glucosidase inhibitor valienamine.However,the low thermostability and limited activity on non-natural substrates have hindered their applications.Simultaneously improving stability and enzyme activity is particularly challenging owing to the acknowledged inherent trade-off between stability and activity.A customized combinatorial active-site saturation test-iterative saturation mutagenesis(CAST-ISM)strategy was used to simultaneously enhance the stability and activity of WecE toward valienone.Fourteen hotspots related to improving the stability-\activity trade-off were identified based on evolutionary conservation and the average mutation folding energy assessment of 57 residues in the active site of WecE.Positive mutagenesis and combinatorial mutations of these specific residues were accomplished via site-directed saturation mutagenesis(SSM)and iterative evolution cycles.Compared with those of the wild-type(WT)WecE,the quadruple mutant M4(Y321F/K209F/V318R/F319V)displayed a 641.49-fold increase in half-life(t_(1/2))at 40℃ and a 31.37-fold increase in activity toward the non-natural substrate valienone.The tri-ple mutant M3(Y321F/K209F/V318R)demonstrated an 83.04-fold increase in(t_(1/2))at 40℃and a 37.77-fold increase in activity toward valienone.The underlying mechanism was dependent on the strengthened interface interactions and shortened transamination reaction catalytic distance,compared with those of the WT,which improved the stability and activity of the obtained mutants.Thus,we accomplished a general target-oriented strategy for obtaining stable and highly active SATs for artificial amino-sugar biosynthesis applications.展开更多
In this paper,we firstly establish a combinatorial identity with a free parameter x,and then by means of derivative operation,several summation formulae concerning classical and generalized harmonic numbers,as well as...In this paper,we firstly establish a combinatorial identity with a free parameter x,and then by means of derivative operation,several summation formulae concerning classical and generalized harmonic numbers,as well as binomial coefficients are derived.展开更多
Pretreated wheat insoluble arabinoxylan was converted to oligosaccharides of structural variants using combinatorial enzyme approach. The digestive products were separated by preparative scale chromatographic Amberlit...Pretreated wheat insoluble arabinoxylan was converted to oligosaccharides of structural variants using combinatorial enzyme approach. The digestive products were separated by preparative scale chromatographic Amberlite XAD-2 column. Fractions containing feruloyl oligosaccharides (FOS) were isolated, pooled, freeze-dried, and demonstrated to possess antimicrobial activity. The FOS suppressed cell growth of the test organism ATCC 8739 E. coli with a MIC value of 0.028% (w/v, 35˚C, 24 hr). The antimicrobial action was observed exceeding 72 hr of culture incubation. The FOS product could be a useful source of prebiotics or preservatives. The present results further confirm the science and application of the concept of combinatorial enzyme technique.展开更多
文摘The quantitative rules of the transfer and variation of errors,when the Gaussian integral functions F.(z) are evaluated sequentially by recurring,have been expounded.The traditional viewpoint to negate the applicability and reliability of upward recursive formula in principle is amended.An optimal scheme of upward-and downward-joint recursions has been developed for the sequential F(z) computations.No additional accuracy is needed with the fundamental term of recursion because the absolute error of Fn(z) always decreases with the recursive approach.The scheme can be employed in modifying any of existent subprograms for Fn<z> computations.In the case of p-d-f-and g-type Gaussians,combining this method with Schaad's formulas can reduce,at least,the additive operations by a factor 40%;the multiplicative and exponential operations by a factor 60%.
基金This study is part of the results in HEIFE supported by the National Natural Science Foundation of China.
文摘A combinatory method of determining the turbulent fluxes in the surface layer has been developed and their general representations have been thus obtained.The universal functions of the (M-O) similarity in the surface layer can be de- termined by the method.The results calculated by using the ITCE's data indicate that the method is feasible.
基金Project supported by the National High Technique Planning Foundation
文摘I. INTRODUCTION The exploration for a unified basis of the combinatory logic and the predicate calculus will promote laying a strict and thorough mathematical foundation of the programming language possessing itself of the functional and logic paradigms. The purpose of this note, proceeding from the algebraic oersoective, is to formulize the first-order mathematical
基金supported by the Fundamental Research Funds for the Central Universities(No.2024JBZX029)Shijiazhuang High Level Science and Technology Innovation and Entrepreneurship Talent Project(No.08202307)the National Natural Science Foundation of China(NSFC)(No.22173004).
文摘The optimization of polymer structures aims to determine an optimal sequence or topology that achieves a given target property or structural performance.This inverse design problem involves searching within a vast combinatorial phase space defined by components,se-quences,and topologies,and is often computationally intractable due to its NP-hard nature.At the core of this challenge lies the need to evalu-ate complex correlations among structural variables,a classical problem in both statistical physics and combinatorial optimization.To address this,we adopt a mean-field approach that decouples direct variable-variable interactions into effective interactions between each variable and an auxiliary field.The simulated bifurcation(SB)algorithm is employed as a mean-field-based optimization framework.It constructs a Hamiltonian dynamical system by introducing generalized momentum fields,enabling efficient decoupling and dynamic evolution of strongly coupled struc-tural variables.Using the sequence optimization of a linear copolymer adsorbing on a solid surface as a case study,we demonstrate the applica-bility of the SB algorithm to high-dimensional,non-differentiable combinatorial optimization problems.Our results show that SB can efficiently discover polymer sequences with excellent adsorption performance within a reasonable computational time.Furthermore,it exhibits robust con-vergence and high parallel scalability across large design spaces.The approach developed in this work offers a new computational pathway for polymer structure optimization.It also lays a theoretical foundation for future extensions to topological design problems,such as optimizing the number and placement of side chains,as well as the co-optimization of sequence and topology.
文摘Neuroscience (also known as neurobiology) is a science that studies the structure, function, development, pharmacology and pathology of the nervous system. In recent years, C. Cotardo has introduced coding theory into neuroscience, proposing the concept of combinatorial neural codes. And it was further studied in depth using algebraic methods by C. Curto. In this paper, we construct a class of combinatorial neural codes with special properties based on classical combinatorial structures such as orthogonal Latin rectangle, disjoint Steiner systems, groupable designs and transversal designs. These neural codes have significant weight distribution properties and large minimum distances, and are thus valuable for potential applications in information representation and neuroscience. This study provides new ideas for the construction method and property analysis of combinatorial neural codes, and enriches the study of algebraic coding theory.
基金supported by the Natural Science Foundation of China(Grants No.42122006,42471187).
文摘Measuring the lifecycle of low-carbon energy technologies is critical to better understanding the innovation pattern.However,previous studies on lifecycle either focus on technical details or just provide a general overview,due to the lack of connection with innovation theories.This article attempts to fill this gap by analyzing the lifecycle from a combinatorial innovation perspective,based on patent data of ten low-carbon energy technologies in China from 1999 to 2018.The problem of estimating lifecycle stages can be transformed into analyzing the rise and fall of knowledge combinations.By building the international patent classification(IPC)co-occurrence matrix,this paper demonstrates the lifecycle evolution of technologies and develops an efficient quantitative index to define lifecycle stages.The mathematical measurement can effectively reflect the evolutionary pattern of technologies.Additionally,this article relates the macro evolution of lifecycle to the micro dynamic mechanism of technology paradigms.The sign of technology maturity is that new inventions tend to follow the patterns established by prior ones.Following this logic,this paper identifies different trends of paradigms in each technology field and analyze their transition.Furthermore,catching-up literature shows that drastic transformation of technology paradigms may open“windows of opportunity”for laggard regions.From the results of this paper,it is clear to see that latecomers can catch up with pioneers especially when there is a radical change in paradigms.Therefore,it is important for policy makers to capture such opportunities during the technology lifecycle and coordinate regional innovation resources.
基金supported by the Key Program of the National Natural Science Foundation of China(Nos.52334008 and 51734004).
文摘In the context of reducing its carbon emissions,the Chinese steel industry is currently undergoing an intelligent transformation to enhance its profitability and sustainability.The optimization of production planning and scheduling plays a pivotal role in realizing these objectives such as improving production efficiency,saving energy,reducing carbon emissions,and enhancing quality.However,current practices in steel enterprises are largely dependent on experience-driven manual decision approaches supported by information systems,which are inadequate to meet the complex requirements of the industry.This study explores the current situation in production planning and scheduling,analyzes the characteristics and limitations of existing methods,and emphasizes the necessity and trends of intelligent systems.It surveys the current literature on production planning and scheduling in steel enterprises and analyzes the theoretical advancements and practical challenges associated with combinatorial and sequential optimization in this field.A key focus is on the limitations of current models and algorithms in effectively addressing the multi-objective and multiconstraint characteristics of steel produc-tion.To overcome these challenges,a novel framework for intelligent production planning and scheduling is proposed.This framework leverages data-and knowledge-driven decision-making and scenario adaptability,enabling the system to respond dynamically to real-time production conditions and market fluctuations.By integrating artificial intelligence and advanced optimization methodologies,the proposed framework improves the efficiency,cost-effectiveness,and environmental sustainability of steel manufacturing.
文摘The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic customer demands.These uncertainties make traditional deterministic models inadequate,often leading to suboptimal or infeasible solutions.To address these challenges,this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms(GA)with Local Search(LS),while incorporating stochastic uncertainty modeling through probabilistic travel times.The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance.This adaptivity enhances the algorithm’s ability to balance exploration and exploitation during the optimization process.Travel time uncertainties are modeled using Gaussian noise,and solution robustness is evaluated through scenario-based simulations.We test our method on a set of benchmark problems from Solomon’s instance suite,comparing its performance under deterministic and stochastic conditions.Results show that the proposed hybrid approach achieves up to a 9%reduction in expected total travel time and a 40% reduction in time window violations compared to baseline methods,including classical GA and non-adaptive hybrids.Additionally,the algorithm demonstrates strong robustness,with lower solution variance across uncertainty scenarios,and converges faster than competing approaches.These findings highlight the method’s suitability for practical logistics applications such as last-mile delivery and real-time transportation planning,where uncertainty and service-level constraints are critical.The flexibility and effectiveness of the proposed framework make it a promising candidate for deployment in dynamic,uncertainty-aware supply chain environments.
基金supported by the National Natural Science Foundation of China(Grant Nos.62371069,62372048,and 62272056)BUPT Excellent Ph.D.Students Foundation(Grant No.CX2023123)。
文摘The quantum alternating operator ansatz algorithm(QAOA+)is widely used for constrained combinatorial optimization problems(CCOPs)due to its ability to construct feasible solution spaces.In this paper,we propose a progressive quantum algorithm(PQA)to reduce qubit requirements for QAOA+in solving the maximum independent set(MIS)problem.PQA iteratively constructs a subgraph likely to include the MIS solution of the original graph and solves the problem on it to approximate the global solution.Specifically,PQA starts with a small-scale subgraph and progressively expands its graph size utilizing heuristic expansion strategies.After each expansion,PQA solves the MIS problem on the newly generated subgraph using QAOA+.In each run,PQA repeats the expansion and solving process until a predefined stopping condition is reached.Simulation results show that PQA achieves an approximation ratio of 0.95 using only 5.57%(2.17%)of the qubits and 17.59%(6.43%)of the runtime compared with directly solving the original problem with QAOA+on Erd?s-Rényi(3-regular)graphs,highlighting the efficiency and scalability of PQA.
基金a post-doctor grant of the Chinese Academy of Sciences.
文摘In the light of a question of J. L. Krivine about the consistency of an extensional λ-theory,an extensional combinatory logic ECL+U(G)+RU_∞+ is established, with its consistency model provedtheoretically and it is shown the it is not equivalent to any system of universal axioms. It is expressed bythe theory in first order logic that, for every given group G of order n, there simultaneously exist infinitelymany universal retractions and a surjective n-tuple notion, such that each element of G acts as a permutationof the components of the n-tuple, and as an Ap-automorphism of the model; further each of the universalretractions is invarian under the action of the Ap-automorphisms induced by G The difference between thetheory and that of Krivine is the G need not be a symmetric group.
基金supported by the National Natural Science Foundation of China(No.81973449).
文摘The clinical benefit of combination therapy is significant,but it is not easy to define the mechanism of complexity and diversity.Previous studies illustrate that phillygenin(Phi)binds in the allosteric inhibit pocket of protein kinase B(AKT),and swertiamarin(Swe)acts on the pleckstrin homology(PH)domain of AKT.However,the combined synergistic effect of relieving the inflammatory response has yet to be elucidated.Based on high sensitivity,specificity and fast-responsibility fluorescent sensors,the Förster resonance energy transfer(FRET)technique offers a route to provide clear insights into physiological and pathological processes.In the study,molecular docking,the fluorescent probes of Phi and Swe for FRET were designed and synthesized.FRET analysis shown that Swe and Phi concurrently acted on the PH domain and allosterically inhibited pocket of AKT,respectively.The combination of Swe and Phi significantly increased the heat stability of AKT and decreased protease-induced degeneration.In lipopolysaccharides(LPS)-induced mice and cells,the combination arrested AKT activation,nuclear factor kappa-B(NF-κB)phosphorylation,and the expression of tumor necrosis factor-α(TNF-α),interleukin(IL)-6 and IL-8.In conclusion,FRET revealed Phi and Swe concurrently targeted AKT on different domains and the combination of Phi and Swe enhanced the anti-inflammatory effect.
基金supported by the National Natural Science Foundation of China(Grant No.92365206)the support of the China Postdoctoral Science Foundation(Certificate Number:2023M740272)+1 种基金supported by the National Natural Science Foundation of China(Grant No.12247168)China Postdoctoral Science Foundation(Certificate Number:2022TQ0036)。
文摘We introduce Quafu-Qcover,an open-source cloud-based software package developed for solving combinatorial optimization problems using quantum simulators and hardware backends.Quafu-Qcover provides a standardized and comprehensive workflow that utilizes the quantum approximate optimization algorithm(QAOA).It facilitates the automatic conversion of the original problem into a quadratic unconstrained binary optimization(QUBO)model and its corresponding Ising model,which can be subsequently transformed into a weight graph.The core of Qcover relies on a graph decomposition-based classical algorithm,which efficiently derives the optimal parameters for the shallow QAOA circuit.Quafu-Qcover incorporates a dedicated compiler capable of translating QAOA circuits into physical quantum circuits that can be executed on Quafu cloud quantum computers.Compared to a general-purpose compiler,our compiler demonstrates the ability to generate shorter circuit depths,while also exhibiting superior speed performance.Additionally,the Qcover compiler has the capability to dynamically create a library of qubits coupling substructures in real-time,utilizing the most recent calibration data from the superconducting quantum devices.This ensures that computational tasks can be assigned to connected physical qubits with the highest fidelity.The Quafu-Qcover allows us to retrieve quantum computing sampling results using a task ID at any time,enabling asynchronous processing.Moreover,it incorporates modules for results preprocessing and visualization,facilitating an intuitive display of solutions for combinatorial optimization problems.We hope that Quafu-Qcover can serve as an instructive illustration for how to explore application problems on the Quafu cloud quantum computers.
基金the National Natural Science Foundation of China (No.61627810)the National Science and Technology Major Program of China (No.2018YFB1305003)the National Defense Science and Technology Outstanding Youth Science Foundation (No.2017-JCJQ-ZQ-031)。
文摘Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization prob-lem.Based on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from the perspectives of network update strategy,initialization method,and parameter selection.This paper compares the performance of the proposed algorithms with the performance of existing SOM network algorithms on the TSP and compares them with several heuristic algorithms.Simulations show that compared with existing SOM networks,the improved SOM network proposed in this paper improves the convergence rate and algorithm accuracy.Compared with iterated local search and heuristic algorithms,the improved SOM net-work algorithms proposed in this paper have the advantage of fast calculation speed on medium-scale TSP.
基金the Beijing Natural Science Foundation(Grant No.2232066)the Open Project Foundation of State Key Laboratory of Solid Lubrication(Grant LSL-2212).
文摘To address the problem of identifying multiple types of additives in lubricating oil,a method based on midinfrared spectral band selection using the eXtreme Gradient Boosting(XGBoost)algorithm combined with the ant colony optimization(ACO)algorithm is proposed.The XGBoost algorithm was used to train and test three additives,T534(alkyl diphenylamine),T308(isooctyl acid thiophospholipid octadecylamine),and T306(trimethylphenol phosphate),separately,in order to screen for the optimal combination of spectral bands for each additive.The ACO algorithm was used to optimize the parameters of the XGBoost algorithm to improve the identification accuracy.During this process,the support vector machine(SVM)and hybrid bat algorithms(HBA)were included as a comparison,generating four models:ACO-XGBoost,ACO-SVM,HBA-XGboost,and HBA-SVM.The results showed that all four models could identify the three additives efficiently,with the ACO-XGBoost model achieving 100%recognition of all three additives.In addition,the generalizability of the ACO-XGBoost model was further demonstrated by predicting a lubricating oil containing the three additives prepared in our laboratory and a collected sample of commercial oil currently in use。
基金supported by National Natural Science Foundation of China(Nos.51890891,51890894,52073027,and 51773017)National Key R&D Program of China(No.2018YFE0205400)the Fundamental Research Funds for the Central Universities(No.FRFDF-19–001)。
文摘Peptide drugs are known for their high biological safety.However,compared with small molecule drugs,peptide drugs are easily oxidized and hydrolyzed as well as short in half-life.Herein,inspired by the long circulation of albumin in blood,we screened albumin binding peptides(ABPs)from a one-bead one-compound(OBOC)peptide library to increase the half-life of peptide drugs.Beads displaying random peptides were screened using fluorescent labeled human serum albumin.Fluorescent beads with specific binding to albumin were isolated for sequencing.The selected ABPs can effectively bind to albumin,thus possessing the long circulation of albumin.The dissociation constant(K_(D))of ABPs to albumin is up to 1×10^(-8)mol/L.Once one of ABPs(ABP2)was coupled to triptorelin,the circulation half-life of triptorelin in mice was significantly prolonged to 263.50 h much longer than that of triptorelin alone(179.07 h).In addition,the combination therapy using ABP-conjugated triptorelin and doxorubicin(DOX)can effectively inhibit the proliferation of tumor cells in mice.The OBOC screening strategy and resulting ABPs showed great potential for enhancing the delivery efficiency of peptide drugs.
基金supported by the National Key Research and Development Program of China (No.2022YFC2806102)the National Natural Science Foundation of China (No.52171287,52325107)+3 种基金High-tech Ship Research Project of Ministry of Industry and Information Technology (No.2023GXB01-05-004-03,No.GXBZH2022-293)the Science Foundation for Distinguished Young Scholars of Shandong Province (No.ZR2022JQ25)the Taishan Scholars Project (No.tsqn201909063)the Fundamental Research Funds for the Central Universities (No.24CX10006A)。
文摘The subsea production system is a vital equipment for offshore oil and gas production.The control system is one of the most important parts of it.Collecting and processing the signals of subsea sensors is the only way to judge whether the subsea production control system is normal.However,subsea sensors degrade rapidly due to harsh working environments and long service time.This leads to frequent false alarm incidents.A combinatorial reasoning-based abnormal sensor recognition method for subsea production control system is proposed.A combinatorial algorithm is proposed to group sensors.The long short-term memory network(LSTM)is used to establish a single inference model.A counting-based judging method is proposed to identify abnormal sensors.Field data from an offshore platform in the South China Sea is used to demonstrate the effect of the proposed method.The results show that the proposed method can identify the abnormal sensors effectively.
基金supported by the Open Project of Xiangjiang Laboratory (22XJ02003)Scientific Project of the National University of Defense Technology (NUDT)(ZK21-07, 23-ZZCX-JDZ-28)+1 种基金the National Science Fund for Outstanding Young Scholars (62122093)the National Natural Science Foundation of China (72071205)。
文摘Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex problems.Given the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.
基金supported by the National Key Research and Development Program of China(2018YFE0200501 and 2020YFA0907700)the National Natural Science Foundation of China(32271306 and 21977067).
文摘Sugar aminotransferases(SATs)catalyze the installation of chiral amines onto specific keto sugars,pro-ducing bioactive amino sugars.Their activity has been utilized in artificial reactions,such as using the SAT WecE to transform valienone into the valuable a-glucosidase inhibitor valienamine.However,the low thermostability and limited activity on non-natural substrates have hindered their applications.Simultaneously improving stability and enzyme activity is particularly challenging owing to the acknowledged inherent trade-off between stability and activity.A customized combinatorial active-site saturation test-iterative saturation mutagenesis(CAST-ISM)strategy was used to simultaneously enhance the stability and activity of WecE toward valienone.Fourteen hotspots related to improving the stability-\activity trade-off were identified based on evolutionary conservation and the average mutation folding energy assessment of 57 residues in the active site of WecE.Positive mutagenesis and combinatorial mutations of these specific residues were accomplished via site-directed saturation mutagenesis(SSM)and iterative evolution cycles.Compared with those of the wild-type(WT)WecE,the quadruple mutant M4(Y321F/K209F/V318R/F319V)displayed a 641.49-fold increase in half-life(t_(1/2))at 40℃ and a 31.37-fold increase in activity toward the non-natural substrate valienone.The tri-ple mutant M3(Y321F/K209F/V318R)demonstrated an 83.04-fold increase in(t_(1/2))at 40℃and a 37.77-fold increase in activity toward valienone.The underlying mechanism was dependent on the strengthened interface interactions and shortened transamination reaction catalytic distance,compared with those of the WT,which improved the stability and activity of the obtained mutants.Thus,we accomplished a general target-oriented strategy for obtaining stable and highly active SATs for artificial amino-sugar biosynthesis applications.
基金Supported by Zhoukou Normal University High-Level Talents Start-Up Funds Research Project(Grant No.ZKNUC2022007)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX240725).
文摘In this paper,we firstly establish a combinatorial identity with a free parameter x,and then by means of derivative operation,several summation formulae concerning classical and generalized harmonic numbers,as well as binomial coefficients are derived.
文摘Pretreated wheat insoluble arabinoxylan was converted to oligosaccharides of structural variants using combinatorial enzyme approach. The digestive products were separated by preparative scale chromatographic Amberlite XAD-2 column. Fractions containing feruloyl oligosaccharides (FOS) were isolated, pooled, freeze-dried, and demonstrated to possess antimicrobial activity. The FOS suppressed cell growth of the test organism ATCC 8739 E. coli with a MIC value of 0.028% (w/v, 35˚C, 24 hr). The antimicrobial action was observed exceeding 72 hr of culture incubation. The FOS product could be a useful source of prebiotics or preservatives. The present results further confirm the science and application of the concept of combinatorial enzyme technique.
