Lithium-air batteries(LABs)are regarded as a next-generation energy storage option due to their relatively high energy density.The cyclic stability and lifespan of LABs are mainly influenced by the formation and decom...Lithium-air batteries(LABs)are regarded as a next-generation energy storage option due to their relatively high energy density.The cyclic stability and lifespan of LABs are mainly influenced by the formation and decomposition of lithium-based oxides at the air cathode,which not only lead to a low cathode catalytic efficiency but also restrict the electrochemical reversibility and cause side reaction problems.Carbon materials are considered key to solving these problems due to their conductivity,functional flexibility,and adjustable pore structure.This paper considers the research progress on carbon materials as air cathode catalytic materials for LABs,focusing on their structural characteristics,electrochemical behavior,and reaction mechanisms.Besides being used as air cathodes,carbon materials also show potential for being used as protective layers for metal anodes or as anode materials for LABs.展开更多
A general process for the construction of azaaryl alkanes was achieved by employing the photoredox/palladium dual catalysis under mild visible light irradiation. The palladium catalyst ligated with a diphosphamide lig...A general process for the construction of azaaryl alkanes was achieved by employing the photoredox/palladium dual catalysis under mild visible light irradiation. The palladium catalyst ligated with a diphosphamide ligand exhibited high effectiveness in facilitating the modular three-components transformation. Furthermore, the cascade transformation was not restricted to constructing tertiary carbon centers;it also encompassed the synthesis of more challenging quaternary carbon centers with sixteen representative azaarene-derived substrates as reactants. In addition, alkyl 1,4-dihydropyridines(DHP), alkyl BF_(3)K, and alkyl carboxylic acids were identified as precursors for alkyl radicals. Mechanistic investigations revealed the involvement of two different active benzylic nucleophiles in the cascade transformation. One is azabenzylic radical, which generate the terminal product through an “inner sphere” reductive elimination process. The other is azabenzylic anions, generated through visible light induced radical anion cross-over, leading to the formation of terminal products via an “outer sphere” reaction pathway.The efficiency of current modular transformation was also demonstarted by the concise of oliceridine, a prominent USFDA drug for pain management.展开更多
Thermoelectric materials,capable of converting temperature gradients into electrical power,have been traditionally limited by a trade-off between thermopower and electrical conductivity.This study introduces a novel,b...Thermoelectric materials,capable of converting temperature gradients into electrical power,have been traditionally limited by a trade-off between thermopower and electrical conductivity.This study introduces a novel,broadly applicable approach that enhances both the spin-driven thermopower and the thermoelectric figure-of-merit(zT)without compromising electrical conductivity,using temperature-driven spin crossover.Our approach,supported by both theoretical and experimental evidence,is demonstrated through a case study of chromium doped-manganese telluride,but is not confined to this material and can be extended to other magnetic materials.By introducing dopants to create a high crystal field and exploiting the entropy changes associated with temperature-driven spin crossover,we achieved a significant increase in thermopower,by approximately 136μV K^(-1),representing more than a 200%enhancement at elevated temperatures within the paramagnetic domain.Our exploration of the bipolar semiconducting nature of these materials reveals that suppressing bipolar magnon/paramagnon-drag thermopower is key to understanding and utilizing spin crossover-driven thermopower.These findings,validated by inelastic neutron scattering,X-ray photoemission spectroscopy,thermal transport,and energy conversion measurements,shed light on crucial material design parameters.We provide a comprehensive framework that analyzes the interplay between spin entropy,hopping transport,and magnon/paramagnon lifetimes,paving the way for the development of high-performance spin-driven thermoelectric materials.展开更多
We report on the measurement of shear viscosity in an ultracold Fermi gas with variable temperatures and tunable interactions.A quadrupole mode excitation in an isotropic harmonic trap is used to quantify the shear vi...We report on the measurement of shear viscosity in an ultracold Fermi gas with variable temperatures and tunable interactions.A quadrupole mode excitation in an isotropic harmonic trap is used to quantify the shear viscosity of the quantum gas within the hydrodynamic regime.The shear viscosity of the system as a function of temperature has been investigated,and the results closely align with calculations in the high-temperature limit utilizing a new definition of the cutoff radius.Through an adiabatic sweep across the Bardeen–Cooper–Schrieffer(BCS)to Bose–Einstein condensate(BEC)crossover,we find that the minimum value of the shear viscosity,as a function of interaction strength,is significantly shifted toward the BEC side.Furthermore,the behavior of the shear viscosity is asymmetric on both sides of the location of the minimum.展开更多
Recent advancements in computational and database technologies have led to the exponential growth of large-scale medical datasets,significantly increasing data complexity and dimensionality in medical diagnostics.Effi...Recent advancements in computational and database technologies have led to the exponential growth of large-scale medical datasets,significantly increasing data complexity and dimensionality in medical diagnostics.Efficient feature selection methods are critical for improving diagnostic accuracy,reducing computational costs,and enhancing the interpretability of predictive models.Particle Swarm Optimization(PSO),a widely used metaheuristic inspired by swarm intelligence,has shown considerable promise in feature selection tasks.However,conventional PSO often suffers from premature convergence and limited exploration capabilities,particularly in high-dimensional spaces.To overcome these limitations,this study proposes an enhanced PSO framework incorporating Orthogonal Initializa-tion and a Crossover Operator(OrPSOC).Orthogonal Initialization ensures a diverse and uniformly distributed initial particle population,substantially improving the algorithm’s exploration capability.The Crossover Operator,inspired by genetic algorithms,introduces additional diversity during the search process,effectively mitigating premature convergence and enhancing global search performance.The effectiveness of OrPSOC was rigorously evaluated on three benchmark medical datasets—Colon,Leukemia,and Prostate Tumor.Comparative analyses were conducted against traditional filter-based methods,including Fast Clustering-Based Feature Selection Technique(Fast-C),Minimum Redundancy Maximum Relevance(MinRedMaxRel),and Five-Way Joint Mutual Information(FJMI),as well as prominent metaheuristic algorithms such as standard PSO,Ant Colony Optimization(ACO),Comprehensive Learning Gravitational Search Algorithm(CLGSA),and Fuzzy-Based CLGSA(FCLGSA).Experimental results demonstrated that OrPSOC consistently outperformed these existing methods in terms of classification accuracy,computational efficiency,and result stability,achieving significant improvements even with fewer selected features.Additionally,a sensitivity analysis of the crossover parameter provided valuable insights into parameter tuning and its impact on model performance.These findings highlight the superiority and robustness of the proposed OrPSOC approach for feature selection in medical diagnostic applications and underscore its potential for broader adoption in various high-dimensional,data-driven fields.展开更多
Precise manipulation of the catalytic spin configuration and delineation of the relationship between spin related properties and oxidation pathways remain significant challenges in Fenton-like processes.Herein,encapsu...Precise manipulation of the catalytic spin configuration and delineation of the relationship between spin related properties and oxidation pathways remain significant challenges in Fenton-like processes.Herein,encapsulated cobalt nanoparticles and cobalt-nitrogen-doped carbon moieties,endowed with confinement effects and variations in shell curvature were constructed via straightforward pyrolysis strategies,inducing alterations in magnetic anisotropy,electronic energy levels and spin polarization.The enhanced spin polarization at cobalt sites leads to a reduction in crystal field splitting energy and an increase in electronic spin density.This phenomenon facilitated electron transfer from cobalt orbitals to pz orbitals of oxygen species within peroxymonosulfate molecules,thereby promoting the formation of high-valent cobalt species.The encapsulation effectively stabilized cobalt nanoparticles,mitigating their dissolution or deactivation during reactions,which in turn enhances stability and durability in continuous flow processes.The high-valent cobalt species within the shell exhibit increased exposure and generate localized high concentrations,thereby intensifying interactions with migrating pollutants and enabling efficient and selective oxidation of emerging compounds with elevated redox potentials.This work underscores the profound impact of confined encapsulation curvature and spin polarization characteristics of metal sites on catalytic oxidation pathways and performance,opening novel avenues for spin engineering in practical environmental catalysis.展开更多
In order to maximize the advantages of high energy density in Li metal batteries,it is necessary to match cathode materials with high specific capacities.Ni-rich layered oxides have been shown to reversibly embed more...In order to maximize the advantages of high energy density in Li metal batteries,it is necessary to match cathode materials with high specific capacities.Ni-rich layered oxides have been shown to reversibly embed more Li+during charge and discharge processes due to the increased Ni content in their crystal structure,thereby providing higher energy density.However,a significant challenge associated with Ni-rich layered oxide cathodes is the crossover effect,which arises from the dissolution of Ni^(2+)from the cathode,leading to a rapid decline in battery capacity.Through the delocalization-induced effect of solvent molecules,Ni^(2+)is transformed into a fluorinated transition metal inorganic phase layer,thereby forming a corrosion-resistant Li metal interface.This prevents solvent molecules from being reduced and degraded by Li metal anode.The surface of the Li metal anode exhibits a smooth and flat deposition morphology after long-term cycling.Furthermore,the introduction of Ni^(2+)can enhance the concentration gradient of transition metal ions near the cathode,thereby suppressing the dissolution process of transition metal ions.Even the NCM955 cathode with a mass load of 22 mg cm^(−2)also has great capacity retention after cycling.The Ni^(2+)induced by high electronegative functional groups of solvent under the electron delocalization effect,preventing the Ni ions dissolution of cathode and constructing a corrosion-resistant Li metal interface layer.This work provides new insights into suppressing crossover effects in Li metal batteries with high nickel cathodes.展开更多
Differential evolution(DE)algorithms are simple and efficient evolutionary algorithms that performwell in various optimization problems.Unfortunately,they inevitably stagnate when differential evolutionary algorithms ...Differential evolution(DE)algorithms are simple and efficient evolutionary algorithms that performwell in various optimization problems.Unfortunately,they inevitably stagnate when differential evolutionary algorithms are used to solve complex problems(e.g.,real-world artificial neural network(ANN)training problems).To resolve this issue,this paper proposes a framework based on an efficient elite centroid operator.It continuously monitors the current state of the population.Once stagnation is detected,two dedicated operators,centroid-based mutation(CM)and centroid-based crossover(CX),are executed to replace the classical mutation and binomial crossover operations in DE.CM and CX are centred on the elite centroid composed of multiple elite individuals,constituting a framework consisting of elitism centroid-based operations(CMX)to improve the performance of the individuals who fall into stagnation.In CM,elite centroid provide evolutionary direction for stagnant individuals,and in CX,elite plasmoids address the limitation that stagnant individuals can only obtain limited information about the population.The CMX framework is simple enough to easily incorporate into both classically well-known DEs with constant population sizes and state-of-the-art DEs with varying populations.Numerical experiments on benchmark functions show that the proposed CMX method can significantly enhance the classical DE algorithm and its advanced variants in solving the stagnation problem and improving performance.展开更多
We investigate the mixed-state entanglement between two spins embedded in the XXZ Heisenberg chain under thermal equilibrium.By deriving an analytical expression for the entanglement of two-spin thermal states and ext...We investigate the mixed-state entanglement between two spins embedded in the XXZ Heisenberg chain under thermal equilibrium.By deriving an analytical expression for the entanglement of two-spin thermal states and extending this analysis to larger spin chains,we demonstrate that mixed-state entanglement is profoundly shaped by both disorder and temperature.Our results reveal a sharp distinction between many-body localized and ergodic phases,with entanglement vanishing above diferent fnite temperature thresholds.Furthermore,by analyzing non-adjacent spins,we uncover an approximate exponential decay of entanglement with separation.This work advances the understanding of the quantum-to-classical transition by linking the entanglement properties of small subsystems to the broader thermal environment,ofering an explanation for the absence of entanglement in macroscopic systems.These fndings provide critical insights into quantum many-body physics,bridging concepts from thermalization,localization,and quantum information theory.展开更多
Background:Whether lactated Ringer's solution is clinically superior to normal saline for routine intravenous administration of fluids is uncertain.Methods:In an open-label,two-period,two-sequence,cross-sectional,...Background:Whether lactated Ringer's solution is clinically superior to normal saline for routine intravenous administration of fluids is uncertain.Methods:In an open-label,two-period,two-sequence,cross-sectional,cluster-randomized,crossover trial,we assigned hospitals in Ontario,Canada,to use either lactated Ringer's solution or normal saline hospital-wide for a period of 12 weeks.展开更多
The interplay between dimensionality and superconductivity is a central theme in understanding the behavior of low-dimensional superconductors. In this work, we investigate the dimensional crossover from quasi-two-dim...The interplay between dimensionality and superconductivity is a central theme in understanding the behavior of low-dimensional superconductors. In this work, we investigate the dimensional crossover from quasi-two-dimensional(quasi-2D) to three-dimensional(3D) superconductivity in(Li,Fe)OHFeSe_(1-x)S_(x) single crystals driven by sulfur doping.Through detailed structural, electrical, and magnetic characterization, we identify a critical doping level(x = 0.53) where the system transitions from quasi-2D to 3D superconducting behavior. Reduced superconducting fluctuations and nonFermi liquid behavior near this critical point suggest the presence of competition between intralayer and interlayer pairing mechanisms. Fluctuation conductivity analysis reveals that the coherence length along the c-axis, ζ_(c)(0), and the interlayer coupling strength, Γ, increase significantly at x = 0.53, marking the onset of 3D superconductivity. These findings provide new insights into the role of dimensionality and interlayer coupling in modulating superconducting properties, positioning(Li,Fe)OHFeSe_(1-x)S_(x) as a unique platform for exploring crossover physics in iron-based superconductors.展开更多
CO_(2)-to-CO electrolyzer technology converts carbon dioxide into carbon monoxide using electrochemical methods,offering significant environmental and energy benefits by aiding in greenhouse gas mitigation and promoti...CO_(2)-to-CO electrolyzer technology converts carbon dioxide into carbon monoxide using electrochemical methods,offering significant environmental and energy benefits by aiding in greenhouse gas mitigation and promoting a carbon circular economy.Recent study by Strasser et al.in Nature Chemical Engineering presents a high-performance CO_(2)-to-CO electrolyzer utilizing a NiNC catalyst with nearly 100%faradaic efficiency,employing innovative diagnostic tools like the carbon crossover coefficient(CCC)to address transport-related failures and optimize overall efficiency.Strasser’s research demonstrates the potential of NiNC catalysts,particularly NiNC-IMI,for efficient CO production in CO_(2)-to-CO electrolyzers,highlighting their high selectivity and performance.However,challenges such as localized CO_(2)depletion and mass transport limitations underscore the need for further optimization and development of diagnostic tools like CCC.Strategies for optimizing catalyst structure and operational parameters offer avenues for enhancing the performance and reliability of electrochemical CO_(2)reduction catalysts.展开更多
This study introduces a novel mathematical model to describe the progression of cholera by integrating fractional derivatives with both singular and non-singular kernels alongside stochastic differential equations ove...This study introduces a novel mathematical model to describe the progression of cholera by integrating fractional derivatives with both singular and non-singular kernels alongside stochastic differential equations over four distinct time intervals.The model incorporates three key fractional derivatives:the Caputo-Fabrizio fractional derivative with a non-singular kernel,the Caputo proportional constant fractional derivative with a singular kernel,and the Atangana-Baleanu fractional derivative with a non-singular kernel.We analyze the stability of the core model and apply various numerical methods to approximate the proposed crossover model.To achieve this,the approximation of Caputo proportional constant fractional derivative with Grünwald-Letnikov nonstandard finite difference method is used for the deterministic model with a singular kernel,while the Toufik-Atangana method is employed for models involving a non-singular Mittag-Leffler kernel.Additionally,the integral Caputo-Fabrizio approximation and a two-step Lagrange polynomial are utilized to approximate the model with a non-singular exponential decay kernel.For the stochastic component,the Milstein method is implemented to approximate the stochastic differential equations.The stability and effectiveness of the proposed model and methodologies are validated through numerical simulations and comparisons with real-world cholera data from Yemen.The results confirm the reliability and practical applicability of the model,providing strong theoretical and empirical support for the approach.展开更多
Transducing thermal energy into mechanical movements via molecular reconfigurations offers a cutting-edge approach to thermal actuating materials,which could be applied to sensors,energy harvesting and storage devices...Transducing thermal energy into mechanical movements via molecular reconfigurations offers a cutting-edge approach to thermal actuating materials,which could be applied to sensors,energy harvesting and storage devices[1].Thermal expansion is a pivotal aspect in solid state chemistry,intricately intertwined with various factors such as crystal structure,chemical composition,electronic configuration,microstructure,and defects.Most materials undergo isotropic and positive thermal expansion(PTE)because of the disharmonic vibrational amplitudes of their chemical bonds.Moreover,anisotropic thermal expansion(ATE)and negative thermal expansion(NTE)are fascinating physical attributes of solids,which can originate from electronic or magnetic mechanisms,as well as through a transverse phonon mechanism in insulating lattice solids.展开更多
Meiotic recombination is essential for sexual reproduction and its regulation has been extensively studied in many taxa.However,genome-wide recombination landscape has not been reported in ciliates and it remains unkn...Meiotic recombination is essential for sexual reproduction and its regulation has been extensively studied in many taxa.However,genome-wide recombination landscape has not been reported in ciliates and it remains unknown how it is affected by the unique features of ciliates:the synaptonemal complex(SC)-independent meiosis and the nuclear dimorphism.Here,we show the recombination landscape in the model ciliate Tetrahymena thermophila by analyzing single-nucleotide polymorphism datasets from 38 hybrid progeny.We detect 1021 crossover(CO)events(35.8 per meiosis),corresponding to an overall CO rate of 9.9 cM/Mb.However,gene conversion by non-crossover is rare(1.03 per meiosis)and not biased towards G or C alleles.Consistent with the reported roles of SC in CO interference,we find no obvious sign of CO interference.CO tends to occur within germ-soma common genomic regions and many of the 44 identified CO hotspots localize at the centromeric or subtelomeric regions.Gene ontology analyses show that CO hotspots are strongly associated with genes responding to environmental changes.We discuss these results with respect to how nuclear dimorphism has potentially driven the formation of the observed recombination landscape to facilitate environmental adaptation and the sharing of machinery among meiotic and somatic recombination.展开更多
The fungal disease caused by Magnaporthe oryzae is one of the most devastating diseases that endanger many crops worldwide.Evidence shows that sexual reproduction can be advantageous for fungal diseases as hybridizati...The fungal disease caused by Magnaporthe oryzae is one of the most devastating diseases that endanger many crops worldwide.Evidence shows that sexual reproduction can be advantageous for fungal diseases as hybridization facilitates host-jumping.However,the pervasive clonal lineages of M.oryzae observed in natural fields contradict this expectation.A better understanding of the roles of recombination and the fungi-specific repeat-induced point mutation(RIP)in shaping its evolutionary trajectory is essential to bridge this knowledge gap.Here we systematically investigate the RIP and recombination landscapes in M.oryzae using a whole genome sequencing data from 252 population samples and 92 cross progenies.Our data reveal that the RIP can robustly capture the population history of M.oryzae,and we provide accurate estimations of the recombination and RIP rates across different M.oryzae clades.Significantly,our results highlight a parent-of-origin bias in both recombination and RIP rates,tightly associating with their sexual potential and variations of effector proteins.This bias suggests a critical trade-off between generating novel allelic combinations in the sexual cycle to facilitate host-jumping and stimulating transposon-associated diversification of effectors in the asexual cycle to facilitate host coevolution.These findings provide unique insights into understanding the evolution of blast fungus.展开更多
The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems.It involves determining the optimal execution sequences for a set of jobs on various ...The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems.It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives.The Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ)is an effective approach for solving the multi-objective job shop scheduling problem.Nevertheless,it has some limitations in solving scheduling problems,including inadequate global search capability,susceptibility to premature convergence,and challenges in balancing convergence and diversity.To enhance its performance,this paper introduces a strengthened dominance relation NSGA-Ⅲ algorithm based on differential evolution(NSGA-Ⅲ-SD).By incorporating constrained differential evolution and simulated binary crossover genetic operators,this algorithm effectively improves NSGA-Ⅲ’s global search capability while mitigating pre-mature convergence issues.Furthermore,it introduces a reinforced dominance relation to address the trade-off between convergence and diversity in NSGA-Ⅲ.Additionally,effective encoding and decoding methods for discrete job shop scheduling are proposed,which can improve the overall performance of the algorithm without complex computation.To validate the algorithm’s effectiveness,NSGA-Ⅲ-SD is extensively compared with other advanced multi-objective optimization algorithms using 20 job shop scheduling test instances.The experimental results demonstrate that NSGA-Ⅲ-SD achieves better solution quality and diversity,proving its effectiveness in solving the multi-objective job shop scheduling problem.展开更多
Light alkanes non-oxidative dehydrogenation is an attractive non-oil route for olefins production.The alkane dehydrogenation reaction is limited by thermodynamic equilibrium,and the C-H bond cleavage is commonly consi...Light alkanes non-oxidative dehydrogenation is an attractive non-oil route for olefins production.The alkane dehydrogenation reaction is limited by thermodynamic equilibrium,and the C-H bond cleavage is commonly considered as the rate-determined step.The valence state of metal sites in catalysts will influence the stabilization of the vital intermediate(i.e.,C_(x)H_(y)...M^(δ+)...H)during the C-H bond cleavage process,which in turn affects the catalytic reactivity.Herein,we explicitly investigated the effect of different valence states of framework-Fe in silicate-1 zeolite on ethane dehydrogenation reaction through the combination of experimental and theoretical study.Fe(Ⅱ)-S-1 and Fe(Ⅲ)-S-1 catalysts are successfully synthesized by ligand-assisted in situ crystallization method,In-situ C_(2)H_6-FTIR shows the higher coverage of hydrocarbon intermediates on Fe(Ⅱ)-S-1,Under the same evaluation co nditio n,Fe(Ⅱ)-S-1 exhibits a higher space time yield of ethylene.Density functional theory(DFT)results reveal that the more coordinate-unsaturated and electron-enriched Fe(Ⅱ)sites boost the first C-H bond activation by slight deformation and efficient electron donation with C_(2)H_(5)^(*)species.Remarkably,the second C-H bond cleavage on Fe(Ⅱ)-S-1 undergoes a spin-crossing process from quintet state to triplet state,which involves a two-electro n-two-orbital interaction,further promoting the formation of ethylene.Microkinetic analysis is consistent with the experimental and DFT results.This work could provide methodology for elucidating the effect of metal valence states on catalytic performance as well as offer guidance for designing more efficient Fe-zeolite catalysts.展开更多
Genetic algorithms(GAs)are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization problems.AsimpleGAbeginswith a set of solutions represented by a population of chromosomes...Genetic algorithms(GAs)are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization problems.AsimpleGAbeginswith a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter chromosomes.It uses a crossover operator to create better offspring chromosomes and thus,converges the population.Also,it uses a mutation operator to explore the unexplored areas by the crossover operator,and thus,diversifies the GA search space.A combination of crossover and mutation operators makes the GA search strong enough to reach the optimal solution.However,appropriate selection and combination of crossover operator and mutation operator can lead to a very good GA for solving an optimization problem.In this present paper,we aim to study the benchmark traveling salesman problem(TSP).We developed several genetic algorithms using seven crossover operators and six mutation operators for the TSP and then compared them to some benchmark TSPLIB instances.The experimental studies show the effectiveness of the combination of a comprehensive sequential constructive crossover operator and insertion mutation operator for the problem.The GA using the comprehensive sequential constructive crossover with insertion mutation could find average solutions whose average percentage of excesses from the best-known solutions are between 0.22 and 14.94 for our experimented problem instances.展开更多
Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key de...Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key degeneration and slow evolution within populations.These challenges significantly hinder key recovery efforts.This paper proposes a screening correlation power analysis framework combined with a genetic algorithm,named SFGA-CPA,to address these issues.SFGA-CPA introduces three operations designed to exploit CPA characteris-tics:propagative operation,constrained crossover,and constrained mutation.Firstly,the propagative operation accelerates population evolution by maximizing the number of correct bytes in each individual.Secondly,the constrained crossover and mutation operations effectively address key degeneration by preventing the compromise of correct bytes.Finally,an intelligent search method is proposed to identify optimal parameters,further improving attack efficiency.Experiments were conducted on both simulated environments and real power traces collected from the SAKURA-G platform.In the case of simulation,SFGA-CPA reduces the number of traces by 27.3%and 60%compared to CPA based on multiple screening methods(MS-CPA)and CPA based on simple GA method(SGA-CPA)when the success rate reaches 90%.Moreover,real experimental results on the SAKURA-G platform demonstrate that our approach outperforms other methods.展开更多
文摘Lithium-air batteries(LABs)are regarded as a next-generation energy storage option due to their relatively high energy density.The cyclic stability and lifespan of LABs are mainly influenced by the formation and decomposition of lithium-based oxides at the air cathode,which not only lead to a low cathode catalytic efficiency but also restrict the electrochemical reversibility and cause side reaction problems.Carbon materials are considered key to solving these problems due to their conductivity,functional flexibility,and adjustable pore structure.This paper considers the research progress on carbon materials as air cathode catalytic materials for LABs,focusing on their structural characteristics,electrochemical behavior,and reaction mechanisms.Besides being used as air cathodes,carbon materials also show potential for being used as protective layers for metal anodes or as anode materials for LABs.
基金supported by the NKRD Program of China (No. 2021YFA1500401)the National Natural Science Foundation of China (Nos. 22101305, 21821003, 21890380, 21771197 and 22003079)+4 种基金the MOE Project (No. 22qntd2303)the LIRTP of Guangdong Pearl River Talents Program (No. 2017BT01C161)the NSF of Guangdong Province (No. 2021A1515010298)the NSF of Guangzhou City (No. 202201011333)the Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT) of Ministry of Education of China。
文摘A general process for the construction of azaaryl alkanes was achieved by employing the photoredox/palladium dual catalysis under mild visible light irradiation. The palladium catalyst ligated with a diphosphamide ligand exhibited high effectiveness in facilitating the modular three-components transformation. Furthermore, the cascade transformation was not restricted to constructing tertiary carbon centers;it also encompassed the synthesis of more challenging quaternary carbon centers with sixteen representative azaarene-derived substrates as reactants. In addition, alkyl 1,4-dihydropyridines(DHP), alkyl BF_(3)K, and alkyl carboxylic acids were identified as precursors for alkyl radicals. Mechanistic investigations revealed the involvement of two different active benzylic nucleophiles in the cascade transformation. One is azabenzylic radical, which generate the terminal product through an “inner sphere” reductive elimination process. The other is azabenzylic anions, generated through visible light induced radical anion cross-over, leading to the formation of terminal products via an “outer sphere” reaction pathway.The efficiency of current modular transformation was also demonstarted by the concise of oliceridine, a prominent USFDA drug for pain management.
基金funding support by the National Science Foundation(NSF)under grant numbers CBET-2110603the Air Force Office of Scientific Research(AFOSR)under contract number FA9550-12-1-0225supported by the State of North Carolina and the National Science Foundation(award number ECCS-2025064).
文摘Thermoelectric materials,capable of converting temperature gradients into electrical power,have been traditionally limited by a trade-off between thermopower and electrical conductivity.This study introduces a novel,broadly applicable approach that enhances both the spin-driven thermopower and the thermoelectric figure-of-merit(zT)without compromising electrical conductivity,using temperature-driven spin crossover.Our approach,supported by both theoretical and experimental evidence,is demonstrated through a case study of chromium doped-manganese telluride,but is not confined to this material and can be extended to other magnetic materials.By introducing dopants to create a high crystal field and exploiting the entropy changes associated with temperature-driven spin crossover,we achieved a significant increase in thermopower,by approximately 136μV K^(-1),representing more than a 200%enhancement at elevated temperatures within the paramagnetic domain.Our exploration of the bipolar semiconducting nature of these materials reveals that suppressing bipolar magnon/paramagnon-drag thermopower is key to understanding and utilizing spin crossover-driven thermopower.These findings,validated by inelastic neutron scattering,X-ray photoemission spectroscopy,thermal transport,and energy conversion measurements,shed light on crucial material design parameters.We provide a comprehensive framework that analyzes the interplay between spin entropy,hopping transport,and magnon/paramagnon lifetimes,paving the way for the development of high-performance spin-driven thermoelectric materials.
基金supported by the National Key R&D Program(Grant No.2022YFA1404102)the National Natural Science Foundation of China(Grant Nos.U23A2073,12374250,and 12121004)+1 种基金Chinese Academy of Sciences(Grant No.YJKYYQ20170025)Hubei Province(Grant No.2021CFA027).
文摘We report on the measurement of shear viscosity in an ultracold Fermi gas with variable temperatures and tunable interactions.A quadrupole mode excitation in an isotropic harmonic trap is used to quantify the shear viscosity of the quantum gas within the hydrodynamic regime.The shear viscosity of the system as a function of temperature has been investigated,and the results closely align with calculations in the high-temperature limit utilizing a new definition of the cutoff radius.Through an adiabatic sweep across the Bardeen–Cooper–Schrieffer(BCS)to Bose–Einstein condensate(BEC)crossover,we find that the minimum value of the shear viscosity,as a function of interaction strength,is significantly shifted toward the BEC side.Furthermore,the behavior of the shear viscosity is asymmetric on both sides of the location of the minimum.
文摘Recent advancements in computational and database technologies have led to the exponential growth of large-scale medical datasets,significantly increasing data complexity and dimensionality in medical diagnostics.Efficient feature selection methods are critical for improving diagnostic accuracy,reducing computational costs,and enhancing the interpretability of predictive models.Particle Swarm Optimization(PSO),a widely used metaheuristic inspired by swarm intelligence,has shown considerable promise in feature selection tasks.However,conventional PSO often suffers from premature convergence and limited exploration capabilities,particularly in high-dimensional spaces.To overcome these limitations,this study proposes an enhanced PSO framework incorporating Orthogonal Initializa-tion and a Crossover Operator(OrPSOC).Orthogonal Initialization ensures a diverse and uniformly distributed initial particle population,substantially improving the algorithm’s exploration capability.The Crossover Operator,inspired by genetic algorithms,introduces additional diversity during the search process,effectively mitigating premature convergence and enhancing global search performance.The effectiveness of OrPSOC was rigorously evaluated on three benchmark medical datasets—Colon,Leukemia,and Prostate Tumor.Comparative analyses were conducted against traditional filter-based methods,including Fast Clustering-Based Feature Selection Technique(Fast-C),Minimum Redundancy Maximum Relevance(MinRedMaxRel),and Five-Way Joint Mutual Information(FJMI),as well as prominent metaheuristic algorithms such as standard PSO,Ant Colony Optimization(ACO),Comprehensive Learning Gravitational Search Algorithm(CLGSA),and Fuzzy-Based CLGSA(FCLGSA).Experimental results demonstrated that OrPSOC consistently outperformed these existing methods in terms of classification accuracy,computational efficiency,and result stability,achieving significant improvements even with fewer selected features.Additionally,a sensitivity analysis of the crossover parameter provided valuable insights into parameter tuning and its impact on model performance.These findings highlight the superiority and robustness of the proposed OrPSOC approach for feature selection in medical diagnostic applications and underscore its potential for broader adoption in various high-dimensional,data-driven fields.
文摘Precise manipulation of the catalytic spin configuration and delineation of the relationship between spin related properties and oxidation pathways remain significant challenges in Fenton-like processes.Herein,encapsulated cobalt nanoparticles and cobalt-nitrogen-doped carbon moieties,endowed with confinement effects and variations in shell curvature were constructed via straightforward pyrolysis strategies,inducing alterations in magnetic anisotropy,electronic energy levels and spin polarization.The enhanced spin polarization at cobalt sites leads to a reduction in crystal field splitting energy and an increase in electronic spin density.This phenomenon facilitated electron transfer from cobalt orbitals to pz orbitals of oxygen species within peroxymonosulfate molecules,thereby promoting the formation of high-valent cobalt species.The encapsulation effectively stabilized cobalt nanoparticles,mitigating their dissolution or deactivation during reactions,which in turn enhances stability and durability in continuous flow processes.The high-valent cobalt species within the shell exhibit increased exposure and generate localized high concentrations,thereby intensifying interactions with migrating pollutants and enabling efficient and selective oxidation of emerging compounds with elevated redox potentials.This work underscores the profound impact of confined encapsulation curvature and spin polarization characteristics of metal sites on catalytic oxidation pathways and performance,opening novel avenues for spin engineering in practical environmental catalysis.
基金the support from Yunnan Fundamental Research Projects(202301BE070001-029,202401CF070129,202501CF070181)National Natural Science Foundation of China(22209012,22479067)Kunming University of Science and Technology Analysis and Testing Fund Support Project(2023T20220172)。
文摘In order to maximize the advantages of high energy density in Li metal batteries,it is necessary to match cathode materials with high specific capacities.Ni-rich layered oxides have been shown to reversibly embed more Li+during charge and discharge processes due to the increased Ni content in their crystal structure,thereby providing higher energy density.However,a significant challenge associated with Ni-rich layered oxide cathodes is the crossover effect,which arises from the dissolution of Ni^(2+)from the cathode,leading to a rapid decline in battery capacity.Through the delocalization-induced effect of solvent molecules,Ni^(2+)is transformed into a fluorinated transition metal inorganic phase layer,thereby forming a corrosion-resistant Li metal interface.This prevents solvent molecules from being reduced and degraded by Li metal anode.The surface of the Li metal anode exhibits a smooth and flat deposition morphology after long-term cycling.Furthermore,the introduction of Ni^(2+)can enhance the concentration gradient of transition metal ions near the cathode,thereby suppressing the dissolution process of transition metal ions.Even the NCM955 cathode with a mass load of 22 mg cm^(−2)also has great capacity retention after cycling.The Ni^(2+)induced by high electronegative functional groups of solvent under the electron delocalization effect,preventing the Ni ions dissolution of cathode and constructing a corrosion-resistant Li metal interface layer.This work provides new insights into suppressing crossover effects in Li metal batteries with high nickel cathodes.
基金funded by National Special Project Number for International Cooperation under Grant 2015DFR11050the Applied Science and Technology Research and Development Special Fund Project of Guangdong Province under Grant 2016B010126004.
文摘Differential evolution(DE)algorithms are simple and efficient evolutionary algorithms that performwell in various optimization problems.Unfortunately,they inevitably stagnate when differential evolutionary algorithms are used to solve complex problems(e.g.,real-world artificial neural network(ANN)training problems).To resolve this issue,this paper proposes a framework based on an efficient elite centroid operator.It continuously monitors the current state of the population.Once stagnation is detected,two dedicated operators,centroid-based mutation(CM)and centroid-based crossover(CX),are executed to replace the classical mutation and binomial crossover operations in DE.CM and CX are centred on the elite centroid composed of multiple elite individuals,constituting a framework consisting of elitism centroid-based operations(CMX)to improve the performance of the individuals who fall into stagnation.In CM,elite centroid provide evolutionary direction for stagnant individuals,and in CX,elite plasmoids address the limitation that stagnant individuals can only obtain limited information about the population.The CMX framework is simple enough to easily incorporate into both classically well-known DEs with constant population sizes and state-of-the-art DEs with varying populations.Numerical experiments on benchmark functions show that the proposed CMX method can significantly enhance the classical DE algorithm and its advanced variants in solving the stagnation problem and improving performance.
基金supported by the National Natural Science Foundation of China(Grant Nos.92365202,12475011,and 11921005)the National Key R&D Program of China(Grant No.2024YFA1409002)Shanghai Municipal Science and Technology Major Project(Grant No.2019SHZDZX01)。
文摘We investigate the mixed-state entanglement between two spins embedded in the XXZ Heisenberg chain under thermal equilibrium.By deriving an analytical expression for the entanglement of two-spin thermal states and extending this analysis to larger spin chains,we demonstrate that mixed-state entanglement is profoundly shaped by both disorder and temperature.Our results reveal a sharp distinction between many-body localized and ergodic phases,with entanglement vanishing above diferent fnite temperature thresholds.Furthermore,by analyzing non-adjacent spins,we uncover an approximate exponential decay of entanglement with separation.This work advances the understanding of the quantum-to-classical transition by linking the entanglement properties of small subsystems to the broader thermal environment,ofering an explanation for the absence of entanglement in macroscopic systems.These fndings provide critical insights into quantum many-body physics,bridging concepts from thermalization,localization,and quantum information theory.
文摘Background:Whether lactated Ringer's solution is clinically superior to normal saline for routine intravenous administration of fluids is uncertain.Methods:In an open-label,two-period,two-sequence,cross-sectional,cluster-randomized,crossover trial,we assigned hospitals in Ontario,Canada,to use either lactated Ringer's solution or normal saline hospital-wide for a period of 12 weeks.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 52272268, 52250308, and 52102338)Beijing National Laboratory for Condensed Matter Physics (Grant No. 2024BNLCMPKF016)Fundamental Research Funding of Universities directly under the Chinese Central Government (Grant No. 2-9-2022-038)。
文摘The interplay between dimensionality and superconductivity is a central theme in understanding the behavior of low-dimensional superconductors. In this work, we investigate the dimensional crossover from quasi-two-dimensional(quasi-2D) to three-dimensional(3D) superconductivity in(Li,Fe)OHFeSe_(1-x)S_(x) single crystals driven by sulfur doping.Through detailed structural, electrical, and magnetic characterization, we identify a critical doping level(x = 0.53) where the system transitions from quasi-2D to 3D superconducting behavior. Reduced superconducting fluctuations and nonFermi liquid behavior near this critical point suggest the presence of competition between intralayer and interlayer pairing mechanisms. Fluctuation conductivity analysis reveals that the coherence length along the c-axis, ζ_(c)(0), and the interlayer coupling strength, Γ, increase significantly at x = 0.53, marking the onset of 3D superconductivity. These findings provide new insights into the role of dimensionality and interlayer coupling in modulating superconducting properties, positioning(Li,Fe)OHFeSe_(1-x)S_(x) as a unique platform for exploring crossover physics in iron-based superconductors.
基金the University of Oxford for the Mathematical, Physical and Life Sciences Division (MPLS) Enterprise and Innovation Fellowshipthe support of Massachusetts Institute of Technology+1 种基金the support of the National Key R&D Program of China (2021YFB3801600)the National Natural Science Foundation of China (22325204)。
文摘CO_(2)-to-CO electrolyzer technology converts carbon dioxide into carbon monoxide using electrochemical methods,offering significant environmental and energy benefits by aiding in greenhouse gas mitigation and promoting a carbon circular economy.Recent study by Strasser et al.in Nature Chemical Engineering presents a high-performance CO_(2)-to-CO electrolyzer utilizing a NiNC catalyst with nearly 100%faradaic efficiency,employing innovative diagnostic tools like the carbon crossover coefficient(CCC)to address transport-related failures and optimize overall efficiency.Strasser’s research demonstrates the potential of NiNC catalysts,particularly NiNC-IMI,for efficient CO production in CO_(2)-to-CO electrolyzers,highlighting their high selectivity and performance.However,challenges such as localized CO_(2)depletion and mass transport limitations underscore the need for further optimization and development of diagnostic tools like CCC.Strategies for optimizing catalyst structure and operational parameters offer avenues for enhancing the performance and reliability of electrochemical CO_(2)reduction catalysts.
文摘This study introduces a novel mathematical model to describe the progression of cholera by integrating fractional derivatives with both singular and non-singular kernels alongside stochastic differential equations over four distinct time intervals.The model incorporates three key fractional derivatives:the Caputo-Fabrizio fractional derivative with a non-singular kernel,the Caputo proportional constant fractional derivative with a singular kernel,and the Atangana-Baleanu fractional derivative with a non-singular kernel.We analyze the stability of the core model and apply various numerical methods to approximate the proposed crossover model.To achieve this,the approximation of Caputo proportional constant fractional derivative with Grünwald-Letnikov nonstandard finite difference method is used for the deterministic model with a singular kernel,while the Toufik-Atangana method is employed for models involving a non-singular Mittag-Leffler kernel.Additionally,the integral Caputo-Fabrizio approximation and a two-step Lagrange polynomial are utilized to approximate the model with a non-singular exponential decay kernel.For the stochastic component,the Milstein method is implemented to approximate the stochastic differential equations.The stability and effectiveness of the proposed model and methodologies are validated through numerical simulations and comparisons with real-world cholera data from Yemen.The results confirm the reliability and practical applicability of the model,providing strong theoretical and empirical support for the approach.
基金supported by the National Natural Science Foundation of China(22171155)Natural Science Foundation of Shandong Province(ZR2022YQ07)Taishan Scholar Program(tsqn202306166).
文摘Transducing thermal energy into mechanical movements via molecular reconfigurations offers a cutting-edge approach to thermal actuating materials,which could be applied to sensors,energy harvesting and storage devices[1].Thermal expansion is a pivotal aspect in solid state chemistry,intricately intertwined with various factors such as crystal structure,chemical composition,electronic configuration,microstructure,and defects.Most materials undergo isotropic and positive thermal expansion(PTE)because of the disharmonic vibrational amplitudes of their chemical bonds.Moreover,anisotropic thermal expansion(ATE)and negative thermal expansion(NTE)are fascinating physical attributes of solids,which can originate from electronic or magnetic mechanisms,as well as through a transverse phonon mechanism in insulating lattice solids.
基金supported by the Wuhan Branch,Supercomputing Center,Chinese Academy of Sciences,Chinasupported by the National Aquatic Biological Resource Center(NABRC)+4 种基金supported by the Bureau of Frontier Sciences and Education,Chinese Academy of Sciences(ZDBS-LY-SM026)the National Natural Science Foundation of China(32370457,32122015,32130011,31900316,and 31900339)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0480000)PJA3 grant of ARC Foundation(ARCPJA2021060003830)Equipes 2022 grant of Foundation Recherche Medicale(EQU202203014651).
文摘Meiotic recombination is essential for sexual reproduction and its regulation has been extensively studied in many taxa.However,genome-wide recombination landscape has not been reported in ciliates and it remains unknown how it is affected by the unique features of ciliates:the synaptonemal complex(SC)-independent meiosis and the nuclear dimorphism.Here,we show the recombination landscape in the model ciliate Tetrahymena thermophila by analyzing single-nucleotide polymorphism datasets from 38 hybrid progeny.We detect 1021 crossover(CO)events(35.8 per meiosis),corresponding to an overall CO rate of 9.9 cM/Mb.However,gene conversion by non-crossover is rare(1.03 per meiosis)and not biased towards G or C alleles.Consistent with the reported roles of SC in CO interference,we find no obvious sign of CO interference.CO tends to occur within germ-soma common genomic regions and many of the 44 identified CO hotspots localize at the centromeric or subtelomeric regions.Gene ontology analyses show that CO hotspots are strongly associated with genes responding to environmental changes.We discuss these results with respect to how nuclear dimorphism has potentially driven the formation of the observed recombination landscape to facilitate environmental adaptation and the sharing of machinery among meiotic and somatic recombination.
基金funded by the National Natural Science Foundation of China(32270664 and 32170327)the National Key Research and Development Program of China(2023YFD2200102 and 2023YFD2200104)Jiangsu Collaborative Innovation Center for Modern Crop Production。
文摘The fungal disease caused by Magnaporthe oryzae is one of the most devastating diseases that endanger many crops worldwide.Evidence shows that sexual reproduction can be advantageous for fungal diseases as hybridization facilitates host-jumping.However,the pervasive clonal lineages of M.oryzae observed in natural fields contradict this expectation.A better understanding of the roles of recombination and the fungi-specific repeat-induced point mutation(RIP)in shaping its evolutionary trajectory is essential to bridge this knowledge gap.Here we systematically investigate the RIP and recombination landscapes in M.oryzae using a whole genome sequencing data from 252 population samples and 92 cross progenies.Our data reveal that the RIP can robustly capture the population history of M.oryzae,and we provide accurate estimations of the recombination and RIP rates across different M.oryzae clades.Significantly,our results highlight a parent-of-origin bias in both recombination and RIP rates,tightly associating with their sexual potential and variations of effector proteins.This bias suggests a critical trade-off between generating novel allelic combinations in the sexual cycle to facilitate host-jumping and stimulating transposon-associated diversification of effectors in the asexual cycle to facilitate host coevolution.These findings provide unique insights into understanding the evolution of blast fungus.
基金in part supported by the Key Research and Development Project of Hubei Province(Nos.2020BAB1141,2023BAB094)the Key Project of Science and Technology Research ProgramofHubei Educational Committee(No.D20211402)+1 种基金the Teaching Research Project of Hubei University of Technology(No.XIAO2018001)the Project of Xiangyang Industrial Research Institute of Hubei University of Technology(No.XYYJ2022C04).
文摘The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems.It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives.The Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ)is an effective approach for solving the multi-objective job shop scheduling problem.Nevertheless,it has some limitations in solving scheduling problems,including inadequate global search capability,susceptibility to premature convergence,and challenges in balancing convergence and diversity.To enhance its performance,this paper introduces a strengthened dominance relation NSGA-Ⅲ algorithm based on differential evolution(NSGA-Ⅲ-SD).By incorporating constrained differential evolution and simulated binary crossover genetic operators,this algorithm effectively improves NSGA-Ⅲ’s global search capability while mitigating pre-mature convergence issues.Furthermore,it introduces a reinforced dominance relation to address the trade-off between convergence and diversity in NSGA-Ⅲ.Additionally,effective encoding and decoding methods for discrete job shop scheduling are proposed,which can improve the overall performance of the algorithm without complex computation.To validate the algorithm’s effectiveness,NSGA-Ⅲ-SD is extensively compared with other advanced multi-objective optimization algorithms using 20 job shop scheduling test instances.The experimental results demonstrate that NSGA-Ⅲ-SD achieves better solution quality and diversity,proving its effectiveness in solving the multi-objective job shop scheduling problem.
基金the financial support from the National Natural Science Foundation of China (22035009,22178381)the National Key R&D Program of China (2021YFA1501301,2021YFC2901100)。
文摘Light alkanes non-oxidative dehydrogenation is an attractive non-oil route for olefins production.The alkane dehydrogenation reaction is limited by thermodynamic equilibrium,and the C-H bond cleavage is commonly considered as the rate-determined step.The valence state of metal sites in catalysts will influence the stabilization of the vital intermediate(i.e.,C_(x)H_(y)...M^(δ+)...H)during the C-H bond cleavage process,which in turn affects the catalytic reactivity.Herein,we explicitly investigated the effect of different valence states of framework-Fe in silicate-1 zeolite on ethane dehydrogenation reaction through the combination of experimental and theoretical study.Fe(Ⅱ)-S-1 and Fe(Ⅲ)-S-1 catalysts are successfully synthesized by ligand-assisted in situ crystallization method,In-situ C_(2)H_6-FTIR shows the higher coverage of hydrocarbon intermediates on Fe(Ⅱ)-S-1,Under the same evaluation co nditio n,Fe(Ⅱ)-S-1 exhibits a higher space time yield of ethylene.Density functional theory(DFT)results reveal that the more coordinate-unsaturated and electron-enriched Fe(Ⅱ)sites boost the first C-H bond activation by slight deformation and efficient electron donation with C_(2)H_(5)^(*)species.Remarkably,the second C-H bond cleavage on Fe(Ⅱ)-S-1 undergoes a spin-crossing process from quintet state to triplet state,which involves a two-electro n-two-orbital interaction,further promoting the formation of ethylene.Microkinetic analysis is consistent with the experimental and DFT results.This work could provide methodology for elucidating the effect of metal valence states on catalytic performance as well as offer guidance for designing more efficient Fe-zeolite catalysts.
基金the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(Grant Number IMSIU-RP23030).
文摘Genetic algorithms(GAs)are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization problems.AsimpleGAbeginswith a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter chromosomes.It uses a crossover operator to create better offspring chromosomes and thus,converges the population.Also,it uses a mutation operator to explore the unexplored areas by the crossover operator,and thus,diversifies the GA search space.A combination of crossover and mutation operators makes the GA search strong enough to reach the optimal solution.However,appropriate selection and combination of crossover operator and mutation operator can lead to a very good GA for solving an optimization problem.In this present paper,we aim to study the benchmark traveling salesman problem(TSP).We developed several genetic algorithms using seven crossover operators and six mutation operators for the TSP and then compared them to some benchmark TSPLIB instances.The experimental studies show the effectiveness of the combination of a comprehensive sequential constructive crossover operator and insertion mutation operator for the problem.The GA using the comprehensive sequential constructive crossover with insertion mutation could find average solutions whose average percentage of excesses from the best-known solutions are between 0.22 and 14.94 for our experimented problem instances.
基金supported by the Hunan Provincial Natrual Science Foundation of China(2022JJ30103)“the 14th Five-Year”Key Disciplines and Application Oriented Special Disciplines of Hunan Province(Xiangjiaotong[2022],351)the Science and Technology Innovation Program of Hunan Province(2016TP1020).
文摘Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key degeneration and slow evolution within populations.These challenges significantly hinder key recovery efforts.This paper proposes a screening correlation power analysis framework combined with a genetic algorithm,named SFGA-CPA,to address these issues.SFGA-CPA introduces three operations designed to exploit CPA characteris-tics:propagative operation,constrained crossover,and constrained mutation.Firstly,the propagative operation accelerates population evolution by maximizing the number of correct bytes in each individual.Secondly,the constrained crossover and mutation operations effectively address key degeneration by preventing the compromise of correct bytes.Finally,an intelligent search method is proposed to identify optimal parameters,further improving attack efficiency.Experiments were conducted on both simulated environments and real power traces collected from the SAKURA-G platform.In the case of simulation,SFGA-CPA reduces the number of traces by 27.3%and 60%compared to CPA based on multiple screening methods(MS-CPA)and CPA based on simple GA method(SGA-CPA)when the success rate reaches 90%.Moreover,real experimental results on the SAKURA-G platform demonstrate that our approach outperforms other methods.
