In this paper,an interacting multiple-model(IMM)method based on datadriven identification model is proposed for the prediction of nonlinear dynamic systems.Firstly,two basic models are selected as combination componen...In this paper,an interacting multiple-model(IMM)method based on datadriven identification model is proposed for the prediction of nonlinear dynamic systems.Firstly,two basic models are selected as combination components due to their proved effectiveness.One is Gaussian process(GP)model,which can provide the predictive variance of the predicted output and only has several optimizing parameters.The other is regularized extreme learning machine(RELM)model,which can improve the overfitting problem resulted by empirical risk minimization principle and enhances the overall generalization performance.Then both of the models are updated continually using meaningful new data selected by data selection methods.Furthermore,recursive methods are employed in the two models to reduce the computational burden caused by continuous renewal.Finally,the two models are combined in IMM algorithm to realize the hybrid prediction,which can avoid the error accumulation in the single-model prediction.In order to verify the performance,the proposed method is applied to the prediction of moisture content of alkali-surfactant-polymer(ASP)flooding.The simulation results show that the proposed model can match the process very well.And IMM algorithm can outperform its components and provide a nice improvement in accuracy and robustness.展开更多
This paper presents an adaptive rationalized Haar function approximation method to obtain the optimal injection strategy for alkali-surfactant-polymer(ASP) flooding. In this process, the non-uniform control vector par...This paper presents an adaptive rationalized Haar function approximation method to obtain the optimal injection strategy for alkali-surfactant-polymer(ASP) flooding. In this process, the non-uniform control vector parameterization is introduced to convert original problem into a multistage optimization problem, in which a new normalized time variable is adopted on the combination of the subinterval length. Then the rationalized Haar function approximation method, in which an auxiliary function is introduced to dispose path constraints, is used to transform the multistage problem into a nonlinear programming. Furthermore, an adaptive strategy proposed on the basis of errors is adopted to regulate the order of Haar function vectors. Finally, the nonlinear programming for ASP flooding is solved by sequential quadratic programming. To illustrate the performance of proposed method,the experimental comparison method and control vector parameterization(CVP) method are introduced to optimize the original problem directly. By contrastive analysis of results, the accuracy and efficiency of proposed method are confirmed.展开更多
Multi-objective optimal dispatching schemes with intelligent algorithms are recognized as effective measures to promote the economics and environmental friendliness of microgrid applications.However,the low accuracy a...Multi-objective optimal dispatching schemes with intelligent algorithms are recognized as effective measures to promote the economics and environmental friendliness of microgrid applications.However,the low accuracy and poor convergence of these algorithms have been challenging for system operators.The bird swarm algorithm(BSA),a new bio-heuristic cluster intelligent algorithm,can potentially address these challenges;however,its computational iterative process may fall into a local optimum and result in premature convergence when optimizing small portions of multi-extremum functions.To analyze the impact of a multi-objective economic-environmental dispatching of a microgrid and overcome the aforementioned problems of the BSA,a self-adaptive levy flight strategy-based BSA(LF-BSA)was proposed.It can solve the dispatching problems of microgrid and enhance its dispatching convergence accuracy,stability,and speed,thereby improving its optimization performance.Six typical test functions were used to compare the LF-BSA with three commonly accepted algorithms to verify its excellence.Finally,a typical summer-time daily microgrid scenario under grid-connected operational conditions was simulated.The results proved the feasibility of the proposed LF-BSA,effectiveness of the multi-objective optimization,and necessity of using renewable energy and energy storage in microgrid dispatching optimization.展开更多
Objective:DNA methylation alterations are early events in carcinogenesis and immune signalling in lung cancer.This study aimed to develop a model based on short stature homeobox 2 gene (SHOX2)/prostaglandin E receptor...Objective:DNA methylation alterations are early events in carcinogenesis and immune signalling in lung cancer.This study aimed to develop a model based on short stature homeobox 2 gene (SHOX2)/prostaglandin E receptor 4gene (PTGER4) DNA methylation in plasma,appearance subtype of pulmonary nodules (PNs) and low-dose computed tomography (LDCT) images to distinguish early-stage lung cancers.Methods:We developed a multimodal prediction model with a training set of 257 individuals.The performance of the multimodal prediction model was further validated in an independent validation set of 42 subjects.In addition,we explored the association between SHOX2/PTGER4 DNA methylation and driver gene mutations in lung cancer based on data from The Cancer Genome Atlas (TCGA) portal.Results:There were significant differences between the early-stage lung cancers and benign groups in the methylation levels.The area under a receiver operator characteristic curve (AUC) of SHOX2 in patients with solid nodules,mixed ground-glass opacity nodules and pure ground-glass opacity nodules were 0.693,0.497 and 0.864,respectively,while the AUCs of PTGER4 were 0.559,0.739 and 0.619,respectively.With the highest AUC of0.894,the novel multimodal prediction model outperformed the Mayo Clinic model (0.519) and LDCT-based deep learning model (0.842) in the independent validation set.Database analysis demonstrated that patients with SHOX2/PTGER4 DNA hypermethylation were enriched in TP53 mutations.Conclusions:The present multimodal prediction model could more efficiently distinguish early-stage lung cancer from benign PNs.A prognostic index based on DNA methylation and lung cancer driver gene alterations may separate the patients into groups with good or poor prognosis.展开更多
Objective:To investigate and analyze the cognition of menopause in women over 40 years old.Methods:Using the stratified sampling method,224 females,age ranging from 40 to 60,from our university staff(Xi’an Medical Un...Objective:To investigate and analyze the cognition of menopause in women over 40 years old.Methods:Using the stratified sampling method,224 females,age ranging from 40 to 60,from our university staff(Xi’an Medical University)and the surrounding communities were selected,and both online and offline questionnaires were distributed.Results:(1)224 questionnaires were recovered,with 204 valid questionnaires,among which 100 questionnaires were from our university staff(aged 42-60 years old)and 104 questionnaires from the surrounding communities(aged 40-60 years old);(2)the cognition of menopause among the surveyed population was found to be related to occupation and education level;the cognition of menopause among university staff(76%)was significantly higher than that of the surrounding communities(45.19%);(3)most people were able to accept menopausal hormone therapy;the degree of acceptance among the university staff(80%)was found to be higher than that among the surrounding communities(60.58%).Conclusion:According to the recovered data,women over the age of 40 have less than ideal cognition of menopause,and although the cognitive level of the university staff on menopause was found to be significantly higher than that of the surrounding communities,their cognitive level still requires improvement.展开更多
Three sandwich-like[Ln_(2)Fe_(2)(B-α-FeW_9O_(34))_(2)]^(10-) clusters(Ln_(2)Fe_(4),Ln=Dy(1),Ho(2),and Y(3)) were obtained by reacting Na_9[B-α-SbW_9O_(33)],Ln_(2)O_(3),FeCl_(3)·6H_(2)O and KH_(2)PO_(4).The[B-α...Three sandwich-like[Ln_(2)Fe_(2)(B-α-FeW_9O_(34))_(2)]^(10-) clusters(Ln_(2)Fe_(4),Ln=Dy(1),Ho(2),and Y(3)) were obtained by reacting Na_9[B-α-SbW_9O_(33)],Ln_(2)O_(3),FeCl_(3)·6H_(2)O and KH_(2)PO_(4).The[B-α-FeW_9O_(34)]^(11-) units were formed via the in situ conversion of lacunary polyoxometalates(POM)[B-α-SbW_9O_(33)]^(9-)and the Ln^(3+)ions were generated from the slow dissolution of Ln_(2)O_(3),both of which play important roles in the synthesis of Ln_(2)Fe_(4).Ln_(2)Fe_(4) is the first 3d-4f cluster assembled from d-metal heteroatom-containing POM.The Dy_(2)Fe_(4) cluster exhibits single-molecule magnet properties with an 80 K energy barrier in an optimal DC field.Cyclic voltammetry tests and controlled-potential coulometry experiments show that the polyoxometalate Fe heteroatom in clusters 1-3 is also electrochemically active.展开更多
In this study,BNBT-KNN-xTa_(2)O_(5)was designed and synthesized,successfully achieving a reduction in the relaxor-ferroelectric phase transition temperature.Synergy between temperature-dependent ferroelectric testing ...In this study,BNBT-KNN-xTa_(2)O_(5)was designed and synthesized,successfully achieving a reduction in the relaxor-ferroelectric phase transition temperature.Synergy between temperature-dependent ferroelectric testing and dielectric spectroscopy confirmed that the depoling temperature gradually decreased with increasing doping concentration.Fitting of the relaxation parameter and freezing temperature substantiated that the incorporation of Ta_(2)O_(5)increased the degree of relaxation in BNBT-KNN-xTa_(2)O_(5),thereby effectively lowering the relaxor-ferroelectric phase transition temperature.展开更多
Developing environmental-friendly materials with high-density energy storage is of paramount importance to meet the burgeoning demands for energy storage.In this study,we harness the modulation of a multicomponent sol...Developing environmental-friendly materials with high-density energy storage is of paramount importance to meet the burgeoning demands for energy storage.In this study,we harness the modulation of a multicomponent solid solution by introducing KNN as a third element into the BNT–BST system,thereby achieving a marked enhancement in both energy storage performance and the temperature stability of the dielectric constant.BNBST–4KNN stands out for its exceptional dielectric stability,with a dielectric constant variation rate within 10%across a broad temperature range of 40℃to 400℃,a feat attributed to the flattening and broadening of the Tm peak.BNBT–2KNN exhibits superior energy storage capabilities,with an energy storage density of 1.324 J/cm^(3)and an energy storage efficiency of 72.3%,a result of the P–E loop becoming more slender.These advancements are pivotal for the sustainable progression of energy storage technologies.展开更多
Hydrogel bioadhesives represent promising and efficient alternatives to sutures or staples for gastrointestinal(GI)perforation management.However,several concerns remain for the existing bioadhesives including slow an...Hydrogel bioadhesives represent promising and efficient alternatives to sutures or staples for gastrointestinal(GI)perforation management.However,several concerns remain for the existing bioadhesives including slow and/or weak adhesive,poor mechanical strength,low biocompatibility,and poor biodegradability,which largely limit their clinical application in GI perforation repair.In this work,we introduce an in situ injectable Tetra-PEG hydrogel bioadhesive(SS)composed of tetra-armed poly(ethylene glycol)amine(Tetra-PEG-NH2)and tetra-armed poly(ethylene glycol)succinimidyl succinate(Tetra-PEG-SS)for the sutureless repair of GI defects.The SS hydrogel exhibits rapid gelation behavior and high burst pressure and is capable of providing instant robust adhesion and fluid-tight sealing in the ex vivo porcine intestinal and gastric models.Importantly,the succinyl ester linkers in the SS hydrogel endow the bioadhesive with suitable in vivo degradability to match the new GI tissue formation.The in vivo evaluation in the rat GI injured model further demonstrates the successful sutureless sealing and repair of the intestine and stomach by the SS hydrogel with the advantages of neglectable postsurgical adhesion,suppressed inflammation,and enhanced angiogenesis.Together,our results support potential clinical applications of the SS bioadhesive for the high-efficient repair of GI perforation.展开更多
Electron-correlated materials have been drawing ever-increasing attention due to their fascinating physical behaviors and extensive application scenarios.In this review,a new method for material research and design(R&...Electron-correlated materials have been drawing ever-increasing attention due to their fascinating physical behaviors and extensive application scenarios.In this review,a new method for material research and design(R&D),named structural-functional unit ordering(SFU ordering),which is presented,overcomes the shortcomings—for example,the limitation of finite chemical elements and long R&D circle-of conventional strategy and thus provides guidance for the design of these high-performance functional materials on demand.Meanwhile,with the development of material characterization technologies,SFUs of different scales and types can be directly observed,which,moreover,regulate the corresponding orderings.The review,starts with an introduction of the profile for SFU ordering and the synergistic effect between SFUs.Then,studies on several new high-performance electronic-correlated materials,for example,a ferromagnetic semiconductor with local spin,ferromagnetic metals with spin topologies,ferroelectric thin films with polar topologies,piezoelectric thin films with nanopillars enclosed by charged boundaries,thermoelectric materials with local ferromagnetic nanoparticles and topotactic phase transformation with conducting nanofilaments are stated in detail one by one.The vital aspect is the breaking of local symmetry,the construction,the structure,of SFUs and their orderings existing or theoretically existing,together with the enhanced/new performance.All in all,the main comments of the review tend to the remaining challenges,promising design approaches for the SFUs,and their orderings for high-performance functional materials.展开更多
In this paper we study optimal control problems with the control variable appearing linearly. A novel method for optimization with respect to the switching times of controls containing both bang-bang and singular arcs...In this paper we study optimal control problems with the control variable appearing linearly. A novel method for optimization with respect to the switching times of controls containing both bang-bang and singular arcs is presented. This method transforms the control problem into a finite-dimensional optimization problem by reformulating the control problem as a multi-stage optimization problem. The optimal control problem is partitioned as several stages, with each stage corresponding to a particular control arc. A control vector parameterization approach is applied to convert the control problem to a static nonlinear programming （NLP） problem. The control profiles and stage lengths act as decision variables. Based on the Pontryagin maximal principle, a multi-stage adjoint system is constructed to calculate the gradients required by the NLP solvers. Two examples are studied to demonstrate the effectiveness of this strategy.展开更多
基金supported by National Natural Science Foundation under Grant No.60974039National Natural Science Foundation under Grant No.61573378+1 种基金Natural Science Foundation of Shandong province under Grant No.ZR2011FM002the Fundamental Research Funds for the Central Universities under Grant No.15CX06064A.
文摘In this paper,an interacting multiple-model(IMM)method based on datadriven identification model is proposed for the prediction of nonlinear dynamic systems.Firstly,two basic models are selected as combination components due to their proved effectiveness.One is Gaussian process(GP)model,which can provide the predictive variance of the predicted output and only has several optimizing parameters.The other is regularized extreme learning machine(RELM)model,which can improve the overfitting problem resulted by empirical risk minimization principle and enhances the overall generalization performance.Then both of the models are updated continually using meaningful new data selected by data selection methods.Furthermore,recursive methods are employed in the two models to reduce the computational burden caused by continuous renewal.Finally,the two models are combined in IMM algorithm to realize the hybrid prediction,which can avoid the error accumulation in the single-model prediction.In order to verify the performance,the proposed method is applied to the prediction of moisture content of alkali-surfactant-polymer(ASP)flooding.The simulation results show that the proposed model can match the process very well.And IMM algorithm can outperform its components and provide a nice improvement in accuracy and robustness.
基金Supported by the National Natural Science Foundation of China(61573378)the Fundamental Research Funds for the Central Universities(15CX06064A)
文摘This paper presents an adaptive rationalized Haar function approximation method to obtain the optimal injection strategy for alkali-surfactant-polymer(ASP) flooding. In this process, the non-uniform control vector parameterization is introduced to convert original problem into a multistage optimization problem, in which a new normalized time variable is adopted on the combination of the subinterval length. Then the rationalized Haar function approximation method, in which an auxiliary function is introduced to dispose path constraints, is used to transform the multistage problem into a nonlinear programming. Furthermore, an adaptive strategy proposed on the basis of errors is adopted to regulate the order of Haar function vectors. Finally, the nonlinear programming for ASP flooding is solved by sequential quadratic programming. To illustrate the performance of proposed method,the experimental comparison method and control vector parameterization(CVP) method are introduced to optimize the original problem directly. By contrastive analysis of results, the accuracy and efficiency of proposed method are confirmed.
基金supported by the National Natural Science Foundation of China (No. 52061635103)
文摘Multi-objective optimal dispatching schemes with intelligent algorithms are recognized as effective measures to promote the economics and environmental friendliness of microgrid applications.However,the low accuracy and poor convergence of these algorithms have been challenging for system operators.The bird swarm algorithm(BSA),a new bio-heuristic cluster intelligent algorithm,can potentially address these challenges;however,its computational iterative process may fall into a local optimum and result in premature convergence when optimizing small portions of multi-extremum functions.To analyze the impact of a multi-objective economic-environmental dispatching of a microgrid and overcome the aforementioned problems of the BSA,a self-adaptive levy flight strategy-based BSA(LF-BSA)was proposed.It can solve the dispatching problems of microgrid and enhance its dispatching convergence accuracy,stability,and speed,thereby improving its optimization performance.Six typical test functions were used to compare the LF-BSA with three commonly accepted algorithms to verify its excellence.Finally,a typical summer-time daily microgrid scenario under grid-connected operational conditions was simulated.The results proved the feasibility of the proposed LF-BSA,effectiveness of the multi-objective optimization,and necessity of using renewable energy and energy storage in microgrid dispatching optimization.
基金supported by the National Natural Science Foundation of China(No.81600065 and No.82073805).
文摘Objective:DNA methylation alterations are early events in carcinogenesis and immune signalling in lung cancer.This study aimed to develop a model based on short stature homeobox 2 gene (SHOX2)/prostaglandin E receptor 4gene (PTGER4) DNA methylation in plasma,appearance subtype of pulmonary nodules (PNs) and low-dose computed tomography (LDCT) images to distinguish early-stage lung cancers.Methods:We developed a multimodal prediction model with a training set of 257 individuals.The performance of the multimodal prediction model was further validated in an independent validation set of 42 subjects.In addition,we explored the association between SHOX2/PTGER4 DNA methylation and driver gene mutations in lung cancer based on data from The Cancer Genome Atlas (TCGA) portal.Results:There were significant differences between the early-stage lung cancers and benign groups in the methylation levels.The area under a receiver operator characteristic curve (AUC) of SHOX2 in patients with solid nodules,mixed ground-glass opacity nodules and pure ground-glass opacity nodules were 0.693,0.497 and 0.864,respectively,while the AUCs of PTGER4 were 0.559,0.739 and 0.619,respectively.With the highest AUC of0.894,the novel multimodal prediction model outperformed the Mayo Clinic model (0.519) and LDCT-based deep learning model (0.842) in the independent validation set.Database analysis demonstrated that patients with SHOX2/PTGER4 DNA hypermethylation were enriched in TP53 mutations.Conclusions:The present multimodal prediction model could more efficiently distinguish early-stage lung cancer from benign PNs.A prognostic index based on DNA methylation and lung cancer driver gene alterations may separate the patients into groups with good or poor prognosis.
基金supported by the 2021 College Students Innovation and Entrepreneurship Training Program Project(No.:121521116).
文摘Objective:To investigate and analyze the cognition of menopause in women over 40 years old.Methods:Using the stratified sampling method,224 females,age ranging from 40 to 60,from our university staff(Xi’an Medical University)and the surrounding communities were selected,and both online and offline questionnaires were distributed.Results:(1)224 questionnaires were recovered,with 204 valid questionnaires,among which 100 questionnaires were from our university staff(aged 42-60 years old)and 104 questionnaires from the surrounding communities(aged 40-60 years old);(2)the cognition of menopause among the surveyed population was found to be related to occupation and education level;the cognition of menopause among university staff(76%)was significantly higher than that of the surrounding communities(45.19%);(3)most people were able to accept menopausal hormone therapy;the degree of acceptance among the university staff(80%)was found to be higher than that among the surrounding communities(60.58%).Conclusion:According to the recovered data,women over the age of 40 have less than ideal cognition of menopause,and although the cognitive level of the university staff on menopause was found to be significantly higher than that of the surrounding communities,their cognitive level still requires improvement.
基金supported by the National Natural Science Foundation of China(Nos.21871224,92161104,92161203 and 21721001)Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM No.RD2021040301)。
文摘Three sandwich-like[Ln_(2)Fe_(2)(B-α-FeW_9O_(34))_(2)]^(10-) clusters(Ln_(2)Fe_(4),Ln=Dy(1),Ho(2),and Y(3)) were obtained by reacting Na_9[B-α-SbW_9O_(33)],Ln_(2)O_(3),FeCl_(3)·6H_(2)O and KH_(2)PO_(4).The[B-α-FeW_9O_(34)]^(11-) units were formed via the in situ conversion of lacunary polyoxometalates(POM)[B-α-SbW_9O_(33)]^(9-)and the Ln^(3+)ions were generated from the slow dissolution of Ln_(2)O_(3),both of which play important roles in the synthesis of Ln_(2)Fe_(4).Ln_(2)Fe_(4) is the first 3d-4f cluster assembled from d-metal heteroatom-containing POM.The Dy_(2)Fe_(4) cluster exhibits single-molecule magnet properties with an 80 K energy barrier in an optimal DC field.Cyclic voltammetry tests and controlled-potential coulometry experiments show that the polyoxometalate Fe heteroatom in clusters 1-3 is also electrochemically active.
基金support from the National Key R&D Program of China(No.2021YFB3201100)National Natural Science Foundation of China(No.52172128)National Natural Science Foundation of China(No.52102146).
文摘In this study,BNBT-KNN-xTa_(2)O_(5)was designed and synthesized,successfully achieving a reduction in the relaxor-ferroelectric phase transition temperature.Synergy between temperature-dependent ferroelectric testing and dielectric spectroscopy confirmed that the depoling temperature gradually decreased with increasing doping concentration.Fitting of the relaxation parameter and freezing temperature substantiated that the incorporation of Ta_(2)O_(5)increased the degree of relaxation in BNBT-KNN-xTa_(2)O_(5),thereby effectively lowering the relaxor-ferroelectric phase transition temperature.
基金support from the National Key R&D Program of China(2021YFB3201100)the National Natural Science Foundation of China(52172128).
文摘Developing environmental-friendly materials with high-density energy storage is of paramount importance to meet the burgeoning demands for energy storage.In this study,we harness the modulation of a multicomponent solid solution by introducing KNN as a third element into the BNT–BST system,thereby achieving a marked enhancement in both energy storage performance and the temperature stability of the dielectric constant.BNBST–4KNN stands out for its exceptional dielectric stability,with a dielectric constant variation rate within 10%across a broad temperature range of 40℃to 400℃,a feat attributed to the flattening and broadening of the Tm peak.BNBT–2KNN exhibits superior energy storage capabilities,with an energy storage density of 1.324 J/cm^(3)and an energy storage efficiency of 72.3%,a result of the P–E loop becoming more slender.These advancements are pivotal for the sustainable progression of energy storage technologies.
基金gratefully acknowledge the support for the work from Ministry of Science and Technology of China(2020YFA0908900)National Natural Science Foundation of China(21935011 and 21725403)+2 种基金Shenzhen Science and Technology Innovation Commission(KQTD20200820113012029 and JCYJ20220818100601003)Guangdong Basic and Applied Basic Research Foundation(2022A1515110321,2019A1515110511)Guangdong Provincial Key Laboratory of Advanced Biomaterials(2022B1212010003).
文摘Hydrogel bioadhesives represent promising and efficient alternatives to sutures or staples for gastrointestinal(GI)perforation management.However,several concerns remain for the existing bioadhesives including slow and/or weak adhesive,poor mechanical strength,low biocompatibility,and poor biodegradability,which largely limit their clinical application in GI perforation repair.In this work,we introduce an in situ injectable Tetra-PEG hydrogel bioadhesive(SS)composed of tetra-armed poly(ethylene glycol)amine(Tetra-PEG-NH2)and tetra-armed poly(ethylene glycol)succinimidyl succinate(Tetra-PEG-SS)for the sutureless repair of GI defects.The SS hydrogel exhibits rapid gelation behavior and high burst pressure and is capable of providing instant robust adhesion and fluid-tight sealing in the ex vivo porcine intestinal and gastric models.Importantly,the succinyl ester linkers in the SS hydrogel endow the bioadhesive with suitable in vivo degradability to match the new GI tissue formation.The in vivo evaluation in the rat GI injured model further demonstrates the successful sutureless sealing and repair of the intestine and stomach by the SS hydrogel with the advantages of neglectable postsurgical adhesion,suppressed inflammation,and enhanced angiogenesis.Together,our results support potential clinical applications of the SS bioadhesive for the high-efficient repair of GI perforation.
基金the financial support from the National Key R&D Program of China(2021YFB3201100)the National Natural Science Foundation of China(52172128)the Top Young Talents Programme of Xi'an Jiaotong University.
文摘Electron-correlated materials have been drawing ever-increasing attention due to their fascinating physical behaviors and extensive application scenarios.In this review,a new method for material research and design(R&D),named structural-functional unit ordering(SFU ordering),which is presented,overcomes the shortcomings—for example,the limitation of finite chemical elements and long R&D circle-of conventional strategy and thus provides guidance for the design of these high-performance functional materials on demand.Meanwhile,with the development of material characterization technologies,SFUs of different scales and types can be directly observed,which,moreover,regulate the corresponding orderings.The review,starts with an introduction of the profile for SFU ordering and the synergistic effect between SFUs.Then,studies on several new high-performance electronic-correlated materials,for example,a ferromagnetic semiconductor with local spin,ferromagnetic metals with spin topologies,ferroelectric thin films with polar topologies,piezoelectric thin films with nanopillars enclosed by charged boundaries,thermoelectric materials with local ferromagnetic nanoparticles and topotactic phase transformation with conducting nanofilaments are stated in detail one by one.The vital aspect is the breaking of local symmetry,the construction,the structure,of SFUs and their orderings existing or theoretically existing,together with the enhanced/new performance.All in all,the main comments of the review tend to the remaining challenges,promising design approaches for the SFUs,and their orderings for high-performance functional materials.
基金supported by the Natural Science Foundation of China(No.60974039)the National Science and Technology Major Project(No. 2008ZX05011)
文摘In this paper we study optimal control problems with the control variable appearing linearly. A novel method for optimization with respect to the switching times of controls containing both bang-bang and singular arcs is presented. This method transforms the control problem into a finite-dimensional optimization problem by reformulating the control problem as a multi-stage optimization problem. The optimal control problem is partitioned as several stages, with each stage corresponding to a particular control arc. A control vector parameterization approach is applied to convert the control problem to a static nonlinear programming （NLP） problem. The control profiles and stage lengths act as decision variables. Based on the Pontryagin maximal principle, a multi-stage adjoint system is constructed to calculate the gradients required by the NLP solvers. Two examples are studied to demonstrate the effectiveness of this strategy.
