Phase transitions,as one of the most intriguing phenomena in nature,are divided into first-order phase transitions(FOPTs)and continuous ones in current classification.While the latter shows striking phenomena of scali...Phase transitions,as one of the most intriguing phenomena in nature,are divided into first-order phase transitions(FOPTs)and continuous ones in current classification.While the latter shows striking phenomena of scaling and universality,the former has recently also been demonstrated to exhibit scaling and universal behavior within a mesoscopic,coarse-grained Landau-Ginzburg theory.Here we apply this theory to a microscopic model-the paradigmatic Ising model,which undergoes FOPTs between two ordered phases below its critical temperature-and unambiguously demonstrate universal scaling behavior in such FOPTs.These results open the door for extending the theory to other microscopic FOPT systems and experimentally testing them to systematically uncover their scaling and universal behavior.展开更多
Monte Carlo(MC) simulations have been performed to refine the estimation of the correction-toscaling exponent ω in the 2D φ^(4)model,which belongs to one of the most fundamental universality classes.If corrections h...Monte Carlo(MC) simulations have been performed to refine the estimation of the correction-toscaling exponent ω in the 2D φ^(4)model,which belongs to one of the most fundamental universality classes.If corrections have the form ∝ L^(-ω),then we find ω=1.546(30) andω=1.509(14) as the best estimates.These are obtained from the finite-size scaling of the susceptibility data in the range of linear lattice sizes L ∈[128,2048] at the critical value of the Binder cumulant and from the scaling of the corresponding pseudocritical couplings within L∈[64,2048].These values agree with several other MC estimates at the assumption of the power-law corrections and are comparable with the known results of the ε-expansion.In addition,we have tested the consistency with the scaling corrections of the form ∝ L^(-4/3),∝L^(-4/3)In L and ∝L^(-4/3)/ln L,which might be expected from some considerations of the renormalization group and Coulomb gas model.The latter option is consistent with our MC data.Our MC results served as a basis for a critical reconsideration of some earlier theoretical conjectures and scaling assumptions.In particular,we have corrected and refined our previous analysis by grouping Feynman diagrams.The renewed analysis gives ω≈4-d-2η as some approximation for spatial dimensions d <4,or ω≈1.5 in two dimensions.展开更多
Tai'an city,located in Shandong Province,China,is rich in geothermal resources,characterized by shallow burial,high water temperature,and abundant water supply,making them high value for exploitation.However,corro...Tai'an city,located in Shandong Province,China,is rich in geothermal resources,characterized by shallow burial,high water temperature,and abundant water supply,making them high value for exploitation.However,corrosion and scaling are main challenges that hinder the widespread application and effective utilization of geothermal energy.This study focuses on the typical geothermal fields in Tai'an,employing qualitative evaluations of the geochemical saturation index with temperature,combined with the corrosion coefficient,Ryznar index,boiler scale,and hard scale assessment,to predict corrosion and scaling trends in the geothermal water of the study area.The results show that the hydrochemical types of geothermal water in the study area are predominantly Na-Ca-SO^(4)and Ca-Na-SO_(4)-HCO_(3),with the water being weakly alkaline.Simulations of saturation index changes with temperature reveal that calcium carbonate scaling is dominant scaling type in the area,with no evidence of calcium sulfate scaling.In the Daiyue Qiaogou geothermal field,the water exhibited corrosive bubble water properties,moderate calcium carbonate scaling,and abundant boiler scaling.Feicheng Anjiazhuang geothermal field showed non-corrosive bubble water,moderate calcium carbonate scaling,and significant boiler scaling.The Daidao'an geothermal field presented corrosive semi-bubble water,moderate calcium carbonate scaling,and abundant boiler scaling.The findings provide a foundation for the efficient exploitation of geothermal resources in the region.Implementing anti-corrosion and scale prevention measures can significantly enhance the utilization of geothermal energy.展开更多
Context:In the dynamic and constantly evolving world of agriculture,promoting innovation and ensuring sustainable growth are crucial.A planned division of tasks and responsibilities within agricultural systems,known a...Context:In the dynamic and constantly evolving world of agriculture,promoting innovation and ensuring sustainable growth are crucial.A planned division of tasks and responsibilities within agricultural systems,known as efficient role allocation,is necessary to make this vision a reality.Climate-smart agriculture(CSA)movement enjoys widespread support from the research and development community because it seeks to improve livelihoods in response to climate change.Objective:This study explores an innovative approach to optimizing role assignment within agricultural frameworks to effectively scale AI-driven innovations.By leveraging advanced algorithms and machine learning techniques,the research aims to streamline the allocation of tasks and responsibilities among various stakeholders,including farmers,agronomists,technicians,and AI systems.Methods:The methodology involves the development of a dynamic role assignment model that considers factors such as expertise,resource availability,and real-time environmental data.This model is tested in various agricultural scenarios to evaluate its impact on operational efficiency and innovation scalability.The findings demonstrate that optimized role assignment not only enhances the performance of AI applications but also fosters a collaborative ecosystem that is adaptable to changing agricultural demands.Results:&Discussion:This research finds a number of elements that affect how well duties are distributed within agricultural frameworks,including organizational frameworks,leadership,resource accessibility,and cooperative efforts through AI.In addition to advocating for its comprehensive integration into the sector's culture,this paper offers a collection of best practices and techniques for optimizing role allocation in agriculture.Additionally,the study gives a thorough overview,summary,and analysis of a few papers that are specifically concerned with scaling innovation in the field of agricultural research for development.Significance:Furthermore,the study highlights the potential of AI to transform traditional farming practices,reduce labor-intensive processes,and improve decision-making accuracy.The proposed approach serves as a blueprint for agricultural enterprises aiming to adopt AI technologies while ensuring optimal utilization of human and technological resources.By addressing the challenges of role ambiguity and resource allocation,this research contributes to the broader goal of achieving sustainable and resilient agricultural systems through technological innovation.展开更多
Kibble-Zurek scaling is the scaling of the density of topological defects formed via the Kibble-Zurek mechanism with respect to the rate at which a system is cooled across a continuous phase transition.Recently,the de...Kibble-Zurek scaling is the scaling of the density of topological defects formed via the Kibble-Zurek mechanism with respect to the rate at which a system is cooled across a continuous phase transition.Recently,the density of the topological defects formed via the Kibble-Zurek mechanism was estimated for a system cooled through a first-order phase transition rather than conventional continuous transitions.Here we address the problem of whether such defects generated across a first-order phase transition exhibit Kibble-Zurek scaling similar to the case in continuous phase transitions.We show that any possible Kibble-Zurek scaling for the topological defects can only be a very rough approximation due to an intrinsic field responsible for the scaling.However,complete universal scaling for other properties does exist.展开更多
Cowl-induced incident Shock Wave/Boundary Layer Interactions (SWBLI) under the influence of gradual expansion waves are frequently observed in supersonic inlets. However, the analysis and prediction of interaction len...Cowl-induced incident Shock Wave/Boundary Layer Interactions (SWBLI) under the influence of gradual expansion waves are frequently observed in supersonic inlets. However, the analysis and prediction of interaction lengths have not been sufficiently investigated. First, this study presents a theoretical scaling analysis and validates it through wind tunnel experiments. It conducts detailed control volume analysis of mass conservation, considering the differences between inviscid and viscous cases. Then, three models for analysing interaction length under gradual expansion waves are derived. Related experiments using schlieren photography are conducted to validate the models in a Mach 2.73 flow. The interaction scales are captured at various relative distances between the shock impingement location and the expansion regions with wedge angles ranging from 12° to 15° and expansion angles of 9°, 12°, and 15°. Three trend lines are plotted based on different expansion angles to depict the relationship between normalised interaction length and normalised interaction strength metric. In addition, the relationship between the coefficients of the trend line and the expansion angles is introduced to predict the interaction length influenced by gradual expansion waves. Finally, the estimation of normalised interaction length is derived for various coefficients within a unified form.展开更多
We propose the scaling rule of Morse oscillator,based on this rule and by virtue of the Her-mann-Feymann theorem,we respectively obtain the distribution of potential and kinetic ener-gy of the Morse Hamiltonian.Also,w...We propose the scaling rule of Morse oscillator,based on this rule and by virtue of the Her-mann-Feymann theorem,we respectively obtain the distribution of potential and kinetic ener-gy of the Morse Hamiltonian.Also,we derive the exact upper limit of physical energy level.Further,we derive some recursive relations for energy matrix elements of the potential and other similar operators in the context of Morse oscillator theory.展开更多
Driven critical dynamics in quantum phase transitions holds significant theoretical importance,and also has practical applications in fast-developing quantum devices.While scaling corrections have been shown to play i...Driven critical dynamics in quantum phase transitions holds significant theoretical importance,and also has practical applications in fast-developing quantum devices.While scaling corrections have been shown to play important roles in fully characterizing equilibrium quantum criticality,their impact on nonequilibrium critical dynamics has not been extensively explored.In this work,we investigate the driven critical dynamics in a two-dimensional quantum Heisenberg model.We find that in this model the scaling corrections arising from both finite system size and finite driving rate must be incorporated into the finite-time scaling form in order to properly describe the nonequilibrium scaling behaviors.In addition,improved scaling relations are obtained from the expansion of the full scaling form.We numerically verify these scaling forms and improved scaling relations for different starting states using the nonequilibrium quantum Monte Carlo algorithm.展开更多
The unexpected scaling phenomena have resulted in significant damages to the oil and gas industries,leading to issues such as heat exchanger failures and pipeline clogging.It is of practical and fundamental importance...The unexpected scaling phenomena have resulted in significant damages to the oil and gas industries,leading to issues such as heat exchanger failures and pipeline clogging.It is of practical and fundamental importance to understand the scaling mechanisms and develop efficient anti-scaling strategies.However,the underlying surface interaction mechanisms of scalants(e.g.,calcite)with various substrates are still not fully understood.In this work,the colloidal probe atomic force microscopy(AFM)technique has been applied to directly quantify the surface forces between calcite particles and different metallic substrates,including carbon steel(CR1018),low alloy steel(4140),stainless steel(SS304)and tungsten carbide,under different water chemistries(i.e.,salinity and pH).Measured force profiles revealed that the attractive van der Waals(VDW)interaction contributed to the attachment of the calcium carbonate particles on substrate surfaces,while the repulsive electric double layer(EDL)interactions could inhibit the attachment behaviors.High salinity and acidic p H conditions of aqueous solutions could weaken the EDL repulsion and promote the attachment behavior.The adhesion of calcite particles with CR1018 and4140 substrates was much stronger than that with SS304 and tungsten carbide substrates.The bulk scaling tests in aqueous solutions from an industrial oil production process showed that much more severe scaling behaviors of calcite was detected on CR1018 and 4140 than those on SS304 and tungsten carbide,which agreed with surface force measurement results.Besides,high salinity and acidic p H can significantly enhance the scaling phenomena.This work provides fundamental insights into the scaling mechanisms of calcite at the nanoscale with practical implications for the selection of suitable antiscaling materials in petroleum industries.展开更多
As a branch of quantum image processing,quantum image scaling has been widely studied.However,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolatio...As a branch of quantum image processing,quantum image scaling has been widely studied.However,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolation,the quantum version of bicubic interpolation has not yet been studied.In this work,we present the first quantum image scaling scheme for bicubic interpolation based on the novel enhanced quantum representation(NEQR).Our scheme can realize synchronous enlargement and reduction of the image with the size of 2^(n)×2^(n) by integral multiple.Firstly,the image is represented by NEQR and the original image coordinates are obtained through multiple CNOT modules.Then,16 neighborhood pixels are obtained by quantum operation circuits,and the corresponding weights of these pixels are calculated by quantum arithmetic modules.Finally,a quantum matrix operation,instead of a classical convolution operation,is used to realize the sum of convolution of these pixels.Through simulation experiments and complexity analysis,we demonstrate that our scheme achieves exponential speedup over the classical bicubic interpolation algorithm,and has better effect than the quantum version of bilinear interpolation.展开更多
The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on...The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.展开更多
According to the description effect range, the method of scaling system in cartography is with the precision of four grades： nominal scaling, ordinal scaling, interval scaling and ratio scaling. The authors have rese...According to the description effect range, the method of scaling system in cartography is with the precision of four grades： nominal scaling, ordinal scaling, interval scaling and ratio scaling. The authors have researched their innate character and inherent relations. The essence of evaluation partialordering set （A ,≤） is the mapping of evaluation object （X, ≤） under fixed condition. The collection and classification of xi ∈ X corresponds how to express Aj ∈ A, i.e. , V xi ∈ X→f（xi ） = Aj → A, Aj is the image of xi under mapping f. The function relation between evaluation partial-ordering set （A, ≤） and evaluation object （X, ≤） is decided by the space character and the way of collection and classification. The different space character and way of collection and classification will produce the different express method and evaluation result, accordingly the authors give out the mathematical definitions for nominal scaling, ordinal scaling, interval scaling and ratio scaling respectively. These results have been proved through the examples.展开更多
Urea-assisted natural seawater electrolysis is an emerging technology that is effective for grid-scale carbon-neutral hydrogen mass production yet challenging.Circumventing scaling relations is an effective strategy t...Urea-assisted natural seawater electrolysis is an emerging technology that is effective for grid-scale carbon-neutral hydrogen mass production yet challenging.Circumventing scaling relations is an effective strategy to break through the bottleneck of natural seawater splitting.Herein,by DFT calculation,we demonstrated that the interface boundaries between Ni_(2)P and MoO_(2) play an essential role in the selfrelaxation of the Ni-O interfacial bond,effectively modulating a coordination number of intermediates to control independently their adsorption-free energy,thus circumventing the adsorption-energy scaling relation.Following this conceptual model,a well-defined 3D F-doped Ni_(2)P-MoO_(2) heterostructure microrod array was rationally designed via an interfacial engineering strategy toward urea-assisted natural seawater electrolysis.As a result,the F-Ni_(2)P-MoO_(2) exhibits eminently active and durable bifunctional catalysts for both HER and OER in acid,alkaline,and alkaline sea water-based electrolytes.By in-situ analysis,we found that a thin amorphous layer of NiOOH,which is evolved from the Ni_(2)P during anodic reaction,is real catalytic active sites for the OER and UOR processes.Remarkable,such electrode-assembled urea-assisted natural seawater electrolyzer requires low voltages of 1.29 and 1.75 V to drive 10 and600 mA cm^(-2)and demonstrates superior durability by operating continuously for 100 h at 100 mA cm^(-2),beyond commercial Pt/C||RuO_(2) and most previous reports.展开更多
An unstably stratified flow entering into a stably stratified flow is referred to as penetrative convection,which is crucial to many physical processes and has been thought of as a key factor for extreme weather condi...An unstably stratified flow entering into a stably stratified flow is referred to as penetrative convection,which is crucial to many physical processes and has been thought of as a key factor for extreme weather conditions.Past theoretical,numerical,and experimental studies on penetrative convection are reviewed,along with field studies providing insights into turbulence modeling.The physical factors that initiate penetrative convection,including internal heat sources,nonlinear constitutive relationships,centrifugal forces and other complicated factors are summarized.Cutting-edge methods for understanding transport mechanisms and statistical properties of penetrative turbulence are also documented,e.g.,the variational approach and quasilinear approach,which derive scaling laws embedded in penetrative turbulence.Exploring these scaling laws in penetrative convection can improve our understanding of large-scale geophysical and astrophysical motions.To better the model of penetrative turbulence towards a practical situation,new directions,e.g.,penetrative convection in spheres,and radiation-forced convection,are proposed.展开更多
The efficiency of the aircraft Ice Protection Systems(IPSs)needs to be verified through icing wind tunnel tests.However,the scaling method for testing the IPSs has not been systematically established yet,and further r...The efficiency of the aircraft Ice Protection Systems(IPSs)needs to be verified through icing wind tunnel tests.However,the scaling method for testing the IPSs has not been systematically established yet,and further research is needed.In the present study,a scaling method specifically designed for thermal IPSs was derived from the governing equation of thin water film.Five scaling parameters were adopted to address the heat and mass transfer involved in the thermal anti-icing process.For method validation,icing wind tunnel tests were conducted using a jet engine nacelle model equipped with a bleed air IPS.The non-dimensional surface temperature and runback ice closely matched for both the reference and scaled conditions.The validation confirms that the scaling method is capable of achieving the similarity of surface temperature and the runback ice coverage.The anti-icing scaling method can serve as an important supplement to the existing icing similarity theory.展开更多
The estimation of residual displacements in a structure due to an anticipated earthquake event has increasingly become an important component of performance-based earthquake engineering because controlling these displ...The estimation of residual displacements in a structure due to an anticipated earthquake event has increasingly become an important component of performance-based earthquake engineering because controlling these displacements plays an important role in ensuring cost-feasible or cost-effective repairs in a damaged structure after the event.An attempt is made in this study to obtain statistical estimates of constant-ductility residual displacement spectra for bilinear and pinching oscillators with 5%initial damping,directly in terms of easily available seismological,site,and model parameters.None of the available models for the bilinear and pinching oscillators are useful when design spectra for a seismic hazard at a site are not available.The statistical estimates of a residual displacement spectrum are proposed in terms of earthquake magnitude,epicentral distance,site geology parameter,and three model parameters for a given set of ductility demand and a hysteretic energy capacity coefficient in the case of bilinear and pinching models,as well as for a given set of pinching parameters for displacement and strength at the breakpoint in the case of pinching model alone.The proposed scaling model is applicable to horizontal ground motions in the western U.S.for earthquake magnitudes less than 7 or epicentral distances greater than 20 km.展开更多
Phase transitions and critical phenomena are among the most intriguing phenomena in nature and society.They are classified into first-order phase transitions(FOPTs)and continuous ones.While the latter shows marvelous ...Phase transitions and critical phenomena are among the most intriguing phenomena in nature and society.They are classified into first-order phase transitions(FOPTs)and continuous ones.While the latter shows marvelous phenomena of scaling and universality,whether the former behaves similarly is a long-standing controversial issue.Here we definitely demonstrate complete universal scaling in field driven FOPTs for Langevin equations in both zero and two spatial dimensions by rescaling all parameters and subtracting nonuniversal contributions with singular dimensions from an effective temperature and a special field according to an effective theory.This offers a perspective different from the usual nucleation and growth but conforming to continuous phase transitions to study FOPTs.展开更多
The interpretation of representations and generalization powers has been a long-standing challenge in the fields of machine learning(ML)and artificial intelligence.This study contributes to understanding the emergence...The interpretation of representations and generalization powers has been a long-standing challenge in the fields of machine learning(ML)and artificial intelligence.This study contributes to understanding the emergence of universal scaling laws in quantum-probabilistic ML.We consider the generative tensor network(GTN)in the form of a matrix-product state as an example and show that with an untrained GTN(such as a random TN state),the negative logarithmic likelihood(NLL)L generally increases linearly with the number of features M,that is,L≃kM+const.This is a consequence of the so-called“catastrophe of orthogonality,”which states that quantum many-body states tend to become exponentially orthogonal to each other as M increases.This study reveals that,while gaining information through training,the linear-scaling law is suppressed by a negative quadratic correction,leading to L≃βM−αM^(2)+const.The scaling coefficients exhibit logarithmic relationships with the number of training samples and quantum channelsχ.The emergence of a quadratic correction term in the NLL for the testing(training)set can be regarded as evidence of the generalization(representation)power of the GTN.Over-parameterization can be identified by the deviation in the values ofαbetween the training and testing sets while increasingχ.We further investigate how orthogonality in the quantum-feature map relates to the satisfaction of quantum-probabilistic interpretation and the representation and generalization powers of the GTN.Unveiling universal scaling laws in quantum-probabilistic ML would be a valuable step toward establishing a white-box ML scheme interpreted within the quantum-probabilistic framework.展开更多
The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software w...The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two state-of-the-art methods.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.12175316).
文摘Phase transitions,as one of the most intriguing phenomena in nature,are divided into first-order phase transitions(FOPTs)and continuous ones in current classification.While the latter shows striking phenomena of scaling and universality,the former has recently also been demonstrated to exhibit scaling and universal behavior within a mesoscopic,coarse-grained Landau-Ginzburg theory.Here we apply this theory to a microscopic model-the paradigmatic Ising model,which undergoes FOPTs between two ordered phases below its critical temperature-and unambiguously demonstrate universal scaling behavior in such FOPTs.These results open the door for extending the theory to other microscopic FOPT systems and experimentally testing them to systematically uncover their scaling and universal behavior.
文摘Monte Carlo(MC) simulations have been performed to refine the estimation of the correction-toscaling exponent ω in the 2D φ^(4)model,which belongs to one of the most fundamental universality classes.If corrections have the form ∝ L^(-ω),then we find ω=1.546(30) andω=1.509(14) as the best estimates.These are obtained from the finite-size scaling of the susceptibility data in the range of linear lattice sizes L ∈[128,2048] at the critical value of the Binder cumulant and from the scaling of the corresponding pseudocritical couplings within L∈[64,2048].These values agree with several other MC estimates at the assumption of the power-law corrections and are comparable with the known results of the ε-expansion.In addition,we have tested the consistency with the scaling corrections of the form ∝ L^(-4/3),∝L^(-4/3)In L and ∝L^(-4/3)/ln L,which might be expected from some considerations of the renormalization group and Coulomb gas model.The latter option is consistent with our MC data.Our MC results served as a basis for a critical reconsideration of some earlier theoretical conjectures and scaling assumptions.In particular,we have corrected and refined our previous analysis by grouping Feynman diagrams.The renewed analysis gives ω≈4-d-2η as some approximation for spatial dimensions d <4,or ω≈1.5 in two dimensions.
基金funded by the Key R&D Program of Henan,China(No.241111321000)China Geological Survey Program(DD20221676).
文摘Tai'an city,located in Shandong Province,China,is rich in geothermal resources,characterized by shallow burial,high water temperature,and abundant water supply,making them high value for exploitation.However,corrosion and scaling are main challenges that hinder the widespread application and effective utilization of geothermal energy.This study focuses on the typical geothermal fields in Tai'an,employing qualitative evaluations of the geochemical saturation index with temperature,combined with the corrosion coefficient,Ryznar index,boiler scale,and hard scale assessment,to predict corrosion and scaling trends in the geothermal water of the study area.The results show that the hydrochemical types of geothermal water in the study area are predominantly Na-Ca-SO^(4)and Ca-Na-SO_(4)-HCO_(3),with the water being weakly alkaline.Simulations of saturation index changes with temperature reveal that calcium carbonate scaling is dominant scaling type in the area,with no evidence of calcium sulfate scaling.In the Daiyue Qiaogou geothermal field,the water exhibited corrosive bubble water properties,moderate calcium carbonate scaling,and abundant boiler scaling.Feicheng Anjiazhuang geothermal field showed non-corrosive bubble water,moderate calcium carbonate scaling,and significant boiler scaling.The Daidao'an geothermal field presented corrosive semi-bubble water,moderate calcium carbonate scaling,and abundant boiler scaling.The findings provide a foundation for the efficient exploitation of geothermal resources in the region.Implementing anti-corrosion and scale prevention measures can significantly enhance the utilization of geothermal energy.
文摘Context:In the dynamic and constantly evolving world of agriculture,promoting innovation and ensuring sustainable growth are crucial.A planned division of tasks and responsibilities within agricultural systems,known as efficient role allocation,is necessary to make this vision a reality.Climate-smart agriculture(CSA)movement enjoys widespread support from the research and development community because it seeks to improve livelihoods in response to climate change.Objective:This study explores an innovative approach to optimizing role assignment within agricultural frameworks to effectively scale AI-driven innovations.By leveraging advanced algorithms and machine learning techniques,the research aims to streamline the allocation of tasks and responsibilities among various stakeholders,including farmers,agronomists,technicians,and AI systems.Methods:The methodology involves the development of a dynamic role assignment model that considers factors such as expertise,resource availability,and real-time environmental data.This model is tested in various agricultural scenarios to evaluate its impact on operational efficiency and innovation scalability.The findings demonstrate that optimized role assignment not only enhances the performance of AI applications but also fosters a collaborative ecosystem that is adaptable to changing agricultural demands.Results:&Discussion:This research finds a number of elements that affect how well duties are distributed within agricultural frameworks,including organizational frameworks,leadership,resource accessibility,and cooperative efforts through AI.In addition to advocating for its comprehensive integration into the sector's culture,this paper offers a collection of best practices and techniques for optimizing role allocation in agriculture.Additionally,the study gives a thorough overview,summary,and analysis of a few papers that are specifically concerned with scaling innovation in the field of agricultural research for development.Significance:Furthermore,the study highlights the potential of AI to transform traditional farming practices,reduce labor-intensive processes,and improve decision-making accuracy.The proposed approach serves as a blueprint for agricultural enterprises aiming to adopt AI technologies while ensuring optimal utilization of human and technological resources.By addressing the challenges of role ambiguity and resource allocation,this research contributes to the broader goal of achieving sustainable and resilient agricultural systems through technological innovation.
基金supported by the National Natural Science Foundation of China(Grant No.12175316)。
文摘Kibble-Zurek scaling is the scaling of the density of topological defects formed via the Kibble-Zurek mechanism with respect to the rate at which a system is cooled across a continuous phase transition.Recently,the density of the topological defects formed via the Kibble-Zurek mechanism was estimated for a system cooled through a first-order phase transition rather than conventional continuous transitions.Here we address the problem of whether such defects generated across a first-order phase transition exhibit Kibble-Zurek scaling similar to the case in continuous phase transitions.We show that any possible Kibble-Zurek scaling for the topological defects can only be a very rough approximation due to an intrinsic field responsible for the scaling.However,complete universal scaling for other properties does exist.
基金co-supported by the National Natural Science Foundation of China (No. 12172175)the National Science and Technology Major Project, China (No. J2019-II0014-0035)the Science Center for Gas Turbine Project, China (Nos. P2022-C-II-002-001, P2022-A-II-002-001)
文摘Cowl-induced incident Shock Wave/Boundary Layer Interactions (SWBLI) under the influence of gradual expansion waves are frequently observed in supersonic inlets. However, the analysis and prediction of interaction lengths have not been sufficiently investigated. First, this study presents a theoretical scaling analysis and validates it through wind tunnel experiments. It conducts detailed control volume analysis of mass conservation, considering the differences between inviscid and viscous cases. Then, three models for analysing interaction length under gradual expansion waves are derived. Related experiments using schlieren photography are conducted to validate the models in a Mach 2.73 flow. The interaction scales are captured at various relative distances between the shock impingement location and the expansion regions with wedge angles ranging from 12° to 15° and expansion angles of 9°, 12°, and 15°. Three trend lines are plotted based on different expansion angles to depict the relationship between normalised interaction length and normalised interaction strength metric. In addition, the relationship between the coefficients of the trend line and the expansion angles is introduced to predict the interaction length influenced by gradual expansion waves. Finally, the estimation of normalised interaction length is derived for various coefficients within a unified form.
基金supported by the National Natural Science Foundation of China(No.10874174)。
文摘We propose the scaling rule of Morse oscillator,based on this rule and by virtue of the Her-mann-Feymann theorem,we respectively obtain the distribution of potential and kinetic ener-gy of the Morse Hamiltonian.Also,we derive the exact upper limit of physical energy level.Further,we derive some recursive relations for energy matrix elements of the potential and other similar operators in the context of Morse oscillator theory.
基金supported by the National Natural Science Foundation of China(Grant Nos.12104109,12222515,and 12075324)the Science and Technology Projects in Guangzhou(Grant No.2024A04J2092)the Science and Technology Projects in Guangdong Province(Grant No.211193863020).
文摘Driven critical dynamics in quantum phase transitions holds significant theoretical importance,and also has practical applications in fast-developing quantum devices.While scaling corrections have been shown to play important roles in fully characterizing equilibrium quantum criticality,their impact on nonequilibrium critical dynamics has not been extensively explored.In this work,we investigate the driven critical dynamics in a two-dimensional quantum Heisenberg model.We find that in this model the scaling corrections arising from both finite system size and finite driving rate must be incorporated into the finite-time scaling form in order to properly describe the nonequilibrium scaling behaviors.In addition,improved scaling relations are obtained from the expansion of the full scaling form.We numerically verify these scaling forms and improved scaling relations for different starting states using the nonequilibrium quantum Monte Carlo algorithm.
基金support from Science Foundation of China University of Petroleum,Beijing (No.2462023QNXZ018)the Natural Sciences and Engineering Research Council of Canada (NSERC)+2 种基金Canada Foundation for Innovation (CFI)the Research Capacity Program (RCP)of Albertathe Canada Research Chairs Program。
文摘The unexpected scaling phenomena have resulted in significant damages to the oil and gas industries,leading to issues such as heat exchanger failures and pipeline clogging.It is of practical and fundamental importance to understand the scaling mechanisms and develop efficient anti-scaling strategies.However,the underlying surface interaction mechanisms of scalants(e.g.,calcite)with various substrates are still not fully understood.In this work,the colloidal probe atomic force microscopy(AFM)technique has been applied to directly quantify the surface forces between calcite particles and different metallic substrates,including carbon steel(CR1018),low alloy steel(4140),stainless steel(SS304)and tungsten carbide,under different water chemistries(i.e.,salinity and pH).Measured force profiles revealed that the attractive van der Waals(VDW)interaction contributed to the attachment of the calcium carbonate particles on substrate surfaces,while the repulsive electric double layer(EDL)interactions could inhibit the attachment behaviors.High salinity and acidic p H conditions of aqueous solutions could weaken the EDL repulsion and promote the attachment behavior.The adhesion of calcite particles with CR1018 and4140 substrates was much stronger than that with SS304 and tungsten carbide substrates.The bulk scaling tests in aqueous solutions from an industrial oil production process showed that much more severe scaling behaviors of calcite was detected on CR1018 and 4140 than those on SS304 and tungsten carbide,which agreed with surface force measurement results.Besides,high salinity and acidic p H can significantly enhance the scaling phenomena.This work provides fundamental insights into the scaling mechanisms of calcite at the nanoscale with practical implications for the selection of suitable antiscaling materials in petroleum industries.
基金Project supported by the Scientific Research Fund of Hunan Provincial Education Department,China (Grant No.21A0470)the Natural Science Foundation of Hunan Province,China (Grant No.2023JJ50268)+1 种基金the National Natural Science Foundation of China (Grant Nos.62172268 and 62302289)the Shanghai Science and Technology Project,China (Grant Nos.21JC1402800 and 23YF1416200)。
文摘As a branch of quantum image processing,quantum image scaling has been widely studied.However,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolation,the quantum version of bicubic interpolation has not yet been studied.In this work,we present the first quantum image scaling scheme for bicubic interpolation based on the novel enhanced quantum representation(NEQR).Our scheme can realize synchronous enlargement and reduction of the image with the size of 2^(n)×2^(n) by integral multiple.Firstly,the image is represented by NEQR and the original image coordinates are obtained through multiple CNOT modules.Then,16 neighborhood pixels are obtained by quantum operation circuits,and the corresponding weights of these pixels are calculated by quantum arithmetic modules.Finally,a quantum matrix operation,instead of a classical convolution operation,is used to realize the sum of convolution of these pixels.Through simulation experiments and complexity analysis,we demonstrate that our scheme achieves exponential speedup over the classical bicubic interpolation algorithm,and has better effect than the quantum version of bilinear interpolation.
基金supported by the National Natural Science Foundation of China(62176218,62176027)the Fundamental Research Funds for the Central Universities(XDJK2020TY003)the Funds for Chongqing Talent Plan(cstc2024ycjh-bgzxm0082)。
文摘The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.
文摘According to the description effect range, the method of scaling system in cartography is with the precision of four grades： nominal scaling, ordinal scaling, interval scaling and ratio scaling. The authors have researched their innate character and inherent relations. The essence of evaluation partialordering set （A ,≤） is the mapping of evaluation object （X, ≤） under fixed condition. The collection and classification of xi ∈ X corresponds how to express Aj ∈ A, i.e. , V xi ∈ X→f（xi ） = Aj → A, Aj is the image of xi under mapping f. The function relation between evaluation partial-ordering set （A, ≤） and evaluation object （X, ≤） is decided by the space character and the way of collection and classification. The different space character and way of collection and classification will produce the different express method and evaluation result, accordingly the authors give out the mathematical definitions for nominal scaling, ordinal scaling, interval scaling and ratio scaling respectively. These results have been proved through the examples.
基金supported by the Vietnam National University,Ho Chi Minh City (Grant No.TX2024-50-01)partial supported by National Natural Science Foundation of China (Grant No.22209186)。
文摘Urea-assisted natural seawater electrolysis is an emerging technology that is effective for grid-scale carbon-neutral hydrogen mass production yet challenging.Circumventing scaling relations is an effective strategy to break through the bottleneck of natural seawater splitting.Herein,by DFT calculation,we demonstrated that the interface boundaries between Ni_(2)P and MoO_(2) play an essential role in the selfrelaxation of the Ni-O interfacial bond,effectively modulating a coordination number of intermediates to control independently their adsorption-free energy,thus circumventing the adsorption-energy scaling relation.Following this conceptual model,a well-defined 3D F-doped Ni_(2)P-MoO_(2) heterostructure microrod array was rationally designed via an interfacial engineering strategy toward urea-assisted natural seawater electrolysis.As a result,the F-Ni_(2)P-MoO_(2) exhibits eminently active and durable bifunctional catalysts for both HER and OER in acid,alkaline,and alkaline sea water-based electrolytes.By in-situ analysis,we found that a thin amorphous layer of NiOOH,which is evolved from the Ni_(2)P during anodic reaction,is real catalytic active sites for the OER and UOR processes.Remarkable,such electrode-assembled urea-assisted natural seawater electrolyzer requires low voltages of 1.29 and 1.75 V to drive 10 and600 mA cm^(-2)and demonstrates superior durability by operating continuously for 100 h at 100 mA cm^(-2),beyond commercial Pt/C||RuO_(2) and most previous reports.
基金supported by the Heilongjiang Touyan Innovative Program Teammade possible through the generous support of the NSFC (Grant No. 52176065)the Fundamental Research Funds for the Central Universities(Grant No. 2022FRFK060022)
文摘An unstably stratified flow entering into a stably stratified flow is referred to as penetrative convection,which is crucial to many physical processes and has been thought of as a key factor for extreme weather conditions.Past theoretical,numerical,and experimental studies on penetrative convection are reviewed,along with field studies providing insights into turbulence modeling.The physical factors that initiate penetrative convection,including internal heat sources,nonlinear constitutive relationships,centrifugal forces and other complicated factors are summarized.Cutting-edge methods for understanding transport mechanisms and statistical properties of penetrative turbulence are also documented,e.g.,the variational approach and quasilinear approach,which derive scaling laws embedded in penetrative turbulence.Exploring these scaling laws in penetrative convection can improve our understanding of large-scale geophysical and astrophysical motions.To better the model of penetrative turbulence towards a practical situation,new directions,e.g.,penetrative convection in spheres,and radiation-forced convection,are proposed.
基金supported by the National Major Science and Technology Projects of China(J2019-Ⅲ-0010-0054).
文摘The efficiency of the aircraft Ice Protection Systems(IPSs)needs to be verified through icing wind tunnel tests.However,the scaling method for testing the IPSs has not been systematically established yet,and further research is needed.In the present study,a scaling method specifically designed for thermal IPSs was derived from the governing equation of thin water film.Five scaling parameters were adopted to address the heat and mass transfer involved in the thermal anti-icing process.For method validation,icing wind tunnel tests were conducted using a jet engine nacelle model equipped with a bleed air IPS.The non-dimensional surface temperature and runback ice closely matched for both the reference and scaled conditions.The validation confirms that the scaling method is capable of achieving the similarity of surface temperature and the runback ice coverage.The anti-icing scaling method can serve as an important supplement to the existing icing similarity theory.
文摘The estimation of residual displacements in a structure due to an anticipated earthquake event has increasingly become an important component of performance-based earthquake engineering because controlling these displacements plays an important role in ensuring cost-feasible or cost-effective repairs in a damaged structure after the event.An attempt is made in this study to obtain statistical estimates of constant-ductility residual displacement spectra for bilinear and pinching oscillators with 5%initial damping,directly in terms of easily available seismological,site,and model parameters.None of the available models for the bilinear and pinching oscillators are useful when design spectra for a seismic hazard at a site are not available.The statistical estimates of a residual displacement spectrum are proposed in terms of earthquake magnitude,epicentral distance,site geology parameter,and three model parameters for a given set of ductility demand and a hysteretic energy capacity coefficient in the case of bilinear and pinching models,as well as for a given set of pinching parameters for displacement and strength at the breakpoint in the case of pinching model alone.The proposed scaling model is applicable to horizontal ground motions in the western U.S.for earthquake magnitudes less than 7 or epicentral distances greater than 20 km.
基金supported by the National Natural Science Foundation of China(Grant No.12175316).
文摘Phase transitions and critical phenomena are among the most intriguing phenomena in nature and society.They are classified into first-order phase transitions(FOPTs)and continuous ones.While the latter shows marvelous phenomena of scaling and universality,whether the former behaves similarly is a long-standing controversial issue.Here we definitely demonstrate complete universal scaling in field driven FOPTs for Langevin equations in both zero and two spatial dimensions by rescaling all parameters and subtracting nonuniversal contributions with singular dimensions from an effective temperature and a special field according to an effective theory.This offers a perspective different from the usual nucleation and growth but conforming to continuous phase transitions to study FOPTs.
基金supported in part by the Beijing Natural Science Foundation (Grant No. 1232025)the Ministry of Education Key Laboratory of Quantum Physics and Photonic Quantum Information (Grant No. ZYGX2024K020)Academy for Multidisciplinary Studies, Capital Normal University.
文摘The interpretation of representations and generalization powers has been a long-standing challenge in the fields of machine learning(ML)and artificial intelligence.This study contributes to understanding the emergence of universal scaling laws in quantum-probabilistic ML.We consider the generative tensor network(GTN)in the form of a matrix-product state as an example and show that with an untrained GTN(such as a random TN state),the negative logarithmic likelihood(NLL)L generally increases linearly with the number of features M,that is,L≃kM+const.This is a consequence of the so-called“catastrophe of orthogonality,”which states that quantum many-body states tend to become exponentially orthogonal to each other as M increases.This study reveals that,while gaining information through training,the linear-scaling law is suppressed by a negative quadratic correction,leading to L≃βM−αM^(2)+const.The scaling coefficients exhibit logarithmic relationships with the number of training samples and quantum channelsχ.The emergence of a quadratic correction term in the NLL for the testing(training)set can be regarded as evidence of the generalization(representation)power of the GTN.Over-parameterization can be identified by the deviation in the values ofαbetween the training and testing sets while increasingχ.We further investigate how orthogonality in the quantum-feature map relates to the satisfaction of quantum-probabilistic interpretation and the representation and generalization powers of the GTN.Unveiling universal scaling laws in quantum-probabilistic ML would be a valuable step toward establishing a white-box ML scheme interpreted within the quantum-probabilistic framework.
文摘The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two state-of-the-art methods.
