Generative image steganography is a technique that directly generates stego images from secret infor-mation.Unlike traditional methods,it theoretically resists steganalysis because there is no cover image.Currently,th...Generative image steganography is a technique that directly generates stego images from secret infor-mation.Unlike traditional methods,it theoretically resists steganalysis because there is no cover image.Currently,the existing generative image steganography methods generally have good steganography performance,but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information extraction.Therefore,this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping rule.Firstly,the reference image is disentangled by a content and an attribute encoder to obtain content features and attribute features,respectively.Then,a mean mapping rule is introduced to map the binary secret information into a noise vector,conforming to the distribution of attribute features.This noise vector is input into the generator to produce the attribute transformed stego image with the content feature of the reference image.Additionally,we design an adversarial loss,a reconstruction loss,and an image diversity loss to train the proposed model.Experimental results demonstrate that the stego images generated by the proposed method are of high quality,with an average extraction accuracy of 99.4%for the hidden information.Furthermore,since the stego image has a uniform distribution similar to the attribute-transformed image without secret information,it effectively resists both subjective and objective steganalysis.展开更多
Variable material screw-based material extrusion(S-MEX)3D printing technology provides a novel approach for fabricating composites with continuous material gradients.Nevertheless,achieving precise alignment between th...Variable material screw-based material extrusion(S-MEX)3D printing technology provides a novel approach for fabricating composites with continuous material gradients.Nevertheless,achieving precise alignment between the process parameters and material compositions is challenging because of fluctuations in the melt rheological state caused by material variations.In this study,an invertible extrusion prediction model for 0-40 wt% short carbon fiber reinforced polyether-ether-ketone(SCF/PEEK)in the S-MEX process was established using an invertible neural network(INN)that demonstrated the capabilities of forward flow rate prediction and inverse process optimization with accuracies of 0.852 and 0.877,respectively.Moreover,a strategy for adjusting the screw speeds using process parameters obtained from the INN was developed to maintain a consistent flow rate during the variable material printing process.Benefiting from uniform flow,the linewidth accuracy was improved by 77%,and the surface roughness was reduced by 51%.Adjusting the process parameters by using an INN offers significant potential for flow rate control and the enhancement of the overall performance of variable material 3D printing.展开更多
Using neural networks for supervised learning means learning a function that maps input <em>x</em> to output <em>y</em>. However, in many applications, the inverse learning is also wanted, <...Using neural networks for supervised learning means learning a function that maps input <em>x</em> to output <em>y</em>. However, in many applications, the inverse learning is also wanted, <em>i.e.</em>, inferring <em>y</em> from <em>x</em>, which requires invertibility of the learning. Since the dimension of input is usually much higher than that of the output, there is information loss in the forward learning from input to output. Thus, creating invertible neural networks is a difficult task. However, recent development of invertible learning techniques such as normalizing flows has made invertible neural networks a reality. In this work, we applied flow-based invertible neural networks as generative models to inverse molecule design. In this context, the forward learning is to predict chemical properties given a molecule, and the inverse learning is to infer the molecules given the chemical properties. Trained on 100 and 1000 molecules, respectively, from a benchmark dataset QM9, our model identified novel molecules that had chemical property values well exceeding the limits of the training molecules as well as the limits of the whole QM9 of 133,885 molecules, moreover our generative model could easily sample many molecules (<em>x</em> values) from any one chemical property value (<em>y</em> value). Compared with the previous method in the literature that could only optimize one molecule for one chemical property value at a time, our model could be trained once and then be sampled any multiple times and for any chemical property values without the need of retraining. This advantage comes from treating inverse molecule design as an inverse regression problem. In summary, our main contributions were two: 1) our model could generalize well from the training data and was very data efficient, 2) our model could learn bidirectional correspondence between molecules and their chemical properties, thereby offering the ability to sample any number of molecules from any <em>y</em> values. In conclusion, our findings revealed the efficiency and effectiveness of using invertible neural networks as generative models in inverse molecule design.展开更多
As neural radiance fields continue to advance in 3D content representation,the copyright issues surrounding 3D models oriented towards implicit representation become increasingly pressing.In response to this challenge...As neural radiance fields continue to advance in 3D content representation,the copyright issues surrounding 3D models oriented towards implicit representation become increasingly pressing.In response to this challenge,this paper treats the embedding and extraction of neural radiance field watermarks as inverse problems of image transformations and proposes a scheme for protecting neural radiance field copyrights using invertible neural network watermarking.Leveraging 2D image watermarking technology for 3D scene protection,the scheme embeds watermarks within the training images of neural radiance fields through the forward process in invertible neural networks and extracts them from images rendered by neural radiance fields through the reverse process,thereby ensuring copyright protection for both the neural radiance fields and associated 3D scenes.However,challenges such as information loss during rendering processes and deliberate tampering necessitate the design of an image quality enhancement module to increase the scheme’s robustness.This module restores distorted images through neural network processing before watermark extraction.Additionally,embedding watermarks in each training image enables watermark information extraction from multiple viewpoints.Our proposed watermarking method achieves a PSNR(Peak Signal-to-Noise Ratio)value exceeding 37 dB for images containing watermarks and 22 dB for recovered watermarked images,as evaluated on the Lego,Hotdog,and Chair datasets,respectively.These results demonstrate the efficacy of our scheme in enhancing copyright protection.展开更多
Recent research advances in implicit neural representation have shown that a wide range of video data distributions are achieved by sharing model weights for Neural Representation for Videos(NeRV).While explicit metho...Recent research advances in implicit neural representation have shown that a wide range of video data distributions are achieved by sharing model weights for Neural Representation for Videos(NeRV).While explicit methods exist for accurately embedding ownership or copyright information in video data,the nascent NeRV framework has yet to address this issue comprehensively.In response,this paper introduces MarkINeRV,a scheme designed to embed watermarking information into video frames using an invertible neural network watermarking approach to protect the copyright of NeRV,which models the embedding and extraction of watermarks as a pair of inverse processes of a reversible network and employs the same network to achieve embedding and extraction of watermarks.It is just that the information flow is in the opposite direction.Additionally,a video frame quality enhancement module is incorporated to mitigate watermarking information losses in the rendering process and the possibility ofmalicious attacks during transmission,ensuring the accurate extraction of watermarking information through the invertible network’s inverse process.This paper evaluates the accuracy,robustness,and invisibility of MarkINeRV through multiple video datasets.The results demonstrate its efficacy in extracting watermarking information for copyright protection of NeRV.MarkINeRV represents a pioneering investigation into copyright issues surrounding NeRV.展开更多
The connectedness of the invertibles question for arbitrary nest has been reduced to the case of the lower triangular operators with respect to a fixed orthonormal basis en for n 1. For each f ∈ H∞, let Tf be the To...The connectedness of the invertibles question for arbitrary nest has been reduced to the case of the lower triangular operators with respect to a fixed orthonormal basis en for n 1. For each f ∈ H∞, let Tf be the Toeplitz operator. In this paper we prove that Tf can be connected to the identity through a path in the invertible group of the lower triangular operators if f satisfies certain conditions.展开更多
We study the structure of invertible substitutions on three-letter alphabet. We show that there exists a finite set S of invertible substitutions such that any invertible substitution can be written as I wσ 1σ ...We study the structure of invertible substitutions on three-letter alphabet. We show that there exists a finite set S of invertible substitutions such that any invertible substitution can be written as I wσ 1σ 2…σ k,where I w is the inner automorphism associated with w, and σ j∈ S for 1≤j≤k. As a consequence,M is the matrix of an invertible substitution if and only if it is a finite product of non-negative elementary matrices.展开更多
A logarithm representation of evolution operators is defined. Generators of invertible evolution families are characterized by the logarithm representation. In this article, using the logarithm representation, a conce...A logarithm representation of evolution operators is defined. Generators of invertible evolution families are characterized by the logarithm representation. In this article, using the logarithm representation, a concept of evolution operators without satisfying the semigroup property is introduced. In conclusion the existence of alternative infinitesimal generator is clarified.展开更多
An embedding from a group algebra to a matrix algebra is given in this paper. By using it, a criterion for an invertible element in a group algebra is proven.
This paper presents in organized form a number of results that have appeared in the literature in the last two decades,concerning the design of control laws for multi-input multi-output nonlinear systems,with emphasis...This paper presents in organized form a number of results that have appeared in the literature in the last two decades,concerning the design of control laws for multi-input multi-output nonlinear systems,with emphasis on the problem of stabilizing an equilibrium,and addresses,at a broad level generality,systems that are invertible from an input-output viewpoint.展开更多
Some properties of a finite automaton composed of two weakly invertible finite automata with delay 1 are given, where each of those two automata has the output set of each state with the same size. And for a weakly in...Some properties of a finite automaton composed of two weakly invertible finite automata with delay 1 are given, where each of those two automata has the output set of each state with the same size. And for a weakly invertible finite automaton M with delay 2 satisfying the properties mentioned in this paper, two weakly invertible finite automata with delay 1 are constructed such that M is equivalent to a sub-finite-automaton of the composition of those two. So a method to decompose this a kind of weakly invertible finite automata with delay 2 is presented.展开更多
By introducing the notion of 'prime substitution' it is shown that the set of invertible substitutions over an alphabet of more than three letters is not finitely generated. Some examples are given.
Inclines are the additively idempotent semirings in which products are less than or equal to either factor. In this paper, some necessary and sufficient conditions for a matrix over L to be invertible are given, where...Inclines are the additively idempotent semirings in which products are less than or equal to either factor. In this paper, some necessary and sufficient conditions for a matrix over L to be invertible are given, where L is an incline with 0 and 1. Also it is proved that L is an integral incline if and only if GLn（L） = PLn （L） for any n （n 〉 2）, in which GLn（L） is the group of all n × n invertible matrices over L and PLn（L） is the group of all n × n permutation matrices over L. These results should be regarded as the generalizations and developments of the previous results on the invertible matrices over a distributive lattice.展开更多
In this paper we obtain a criterion under which the bijectivity of the canonical morphism of a weak Galois extension associated to a weak invertible entwining structure is equivalent to the existence of a strong conne...In this paper we obtain a criterion under which the bijectivity of the canonical morphism of a weak Galois extension associated to a weak invertible entwining structure is equivalent to the existence of a strong connection form. Also we obtain an explicit formula for a strong connection under equivariant projective conditions or under coseparability conditions.展开更多
This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper cons...This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.展开更多
Converting subsurface offset domain common image gathers(ODCIGs)to angle domain common image gathers(ADCIGs)through a Radon Transform(RT)in either the spatial or wavenumber domain is efficient and valid except for the...Converting subsurface offset domain common image gathers(ODCIGs)to angle domain common image gathers(ADCIGs)through a Radon Transform(RT)in either the spatial or wavenumber domain is efficient and valid except for the distortion of both frequency spectrum and amplitude versus angle(AVA)effect.This paper presents two modifications to the existing method to keep the frequency spectrum of the resultant ADCIGs the same as the input data and to preserve the relative amplitudes.The spectrum invariance is achieved by replacing the conventional RT or slant slack by an invertible RT.Amplitude preservation is obtained by applying an amplitude correction factor in the angle domain.Tests on both synthetic and field datasets validate the accuracy of these modifications.展开更多
Despite the intrinsic durability of polymeric hole transport materials,poly-triarylamines(PTAA)-based inverted perovskite solar cells(PSCs)have lagged behind their counterparts in efficiency,primarily due to poor surf...Despite the intrinsic durability of polymeric hole transport materials,poly-triarylamines(PTAA)-based inverted perovskite solar cells(PSCs)have lagged behind their counterparts in efficiency,primarily due to poor surface wettability,insufficient interfacial contact,and unfavorable energy level alignment at the PTAA/perovskite interface.Here,we report a highly effective interfacial engineering strategy employing the ionic liquid 1,3-dimethylimidazolium dimethyl phosphate(DMIMPH)as a multifunctional interfacial modifier.The incorporation of DMIMPH improves PTAA wettability,promoting the growth of high-quality perovskite films with enhanced interfacial contact.Concurrently,DMIMPH effectively tunes the energy levels of PTAA,enhances its electrical conductivity,and passivates interfacial defects with more efficient hole extraction and charge transport.Moreover,its interaction with residual PbI_(2) modulates perovskite crystallization kinetics,yielding highly crystalline perovskite films with enlarged grain sizes,reduced PbI_(2) residue,and suppressed trap densities.As a result,PTAA-based p-i-n PSCs employing this approach achieve a record certified power conversion efficiency(PCE)of 24.52%,with a champion efficiency of 25.12%—the highest certified value for PTAA-based perovskite devices to date.Impressively,the DMIMPH-modified PSCs without encapsulation maintained 87.48%of their initial efficiency after 1600 h in air.This strategy offers an effective pathway for advancing the performance and stability of polymer-based inverted PSCs.展开更多
Organic electrochemical transistors(OECTs)are promising for next-generation bioelectronics due to their high performance and biocompatibility.Nevertheless,they still face tremendous operational stability challenges du...Organic electrochemical transistors(OECTs)are promising for next-generation bioelectronics due to their high performance and biocompatibility.Nevertheless,they still face tremendous operational stability challenges due to the limited robustness of the organic mixed ionic-electronic conductor(OMIEC)channel.Here,by modulating the molecular weight(MW)of OMiEC,enhanced OECT and relevant circuit operation stabilities are demonstrated,showing more than 3,000,0o0 full cycles(~42 h)with less than 15%current variation in an OECT,and 150,000 cycles(~4 h)with less than 5%voltage variation in an OECT-based inverter,which are among the highest of reported OECT-based electronics.Specifically,p(g2T-T),a typical p-type OMIEC,with varying MW(7-43 kDa),is synthesized,where lower-MW p(g2T-T)(~9 kDa)exhibits superior device performance and cycling stability in OECTs,outperforming those in high-MW counterparts(>30 kDa).It is indicated that low-MW p(g2T-T)maintains higher volumetric capacitance,ordered orientation,and reduced swelling.Therefore,irreversible microstructural degradation is effectively avoided,along with better performance yield.Furthermore,MW regulation enables physiological signal sensing with high tolerance to body fluid environments for 7 days.These findings highlight MW modulation as a versatile approach to suppress excessive swelling,advancing the design of durable OECT-based electronics.展开更多
The hybrid series-parallel microgrid attracts more attention by combining the advantages of both the series-stacked voltage and parallel-expanded capacity.Low-voltage distributed generations(DGs)are connected in serie...The hybrid series-parallel microgrid attracts more attention by combining the advantages of both the series-stacked voltage and parallel-expanded capacity.Low-voltage distributed generations(DGs)are connected in series to form the intra-string,and then multiple strings are interconnected in parallel.For the existing control strategies,both intra-string and inter-string depend on the centralized or distributed control with high communication reliance.It has limited scalability and redundancy under abnormal conditions.Alternatively,in this study,an intra-string distributed and inter-string decentralized control framework is proposed.Within the string,a few DGs close to the AC bus are the leaders to get the string power information and the rest DGs are the followers to acquire the synchronization information through the droop-based distributed consistency.Specifically,the output of the entire string has the active power−angular frequency(ω-P)droop characteristic,and the decentralized control among strings can be autonomously guaranteed.Moreover,the secondary control is designed to realize multi-mode objectives,including on/off-grid mode switching,grid-connected power interactive management,and off-grid voltage quality regulation.As a result,the proposed method has the ability of plug-and-play capabilities,single-point failure redundancy,and seamless mode-switching.Experimental results are provided to verify the effectiveness of the proposed practical solution.展开更多
基金supported in part by the National Natural Science Foundation of China(Nos.62202234,62401270)the China Postdoctoral Science Foundation(No.2023M741778)the Natural Science Foundation of Jiangsu Province(Nos.BK20240706,BK20240694).
文摘Generative image steganography is a technique that directly generates stego images from secret infor-mation.Unlike traditional methods,it theoretically resists steganalysis because there is no cover image.Currently,the existing generative image steganography methods generally have good steganography performance,but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information extraction.Therefore,this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping rule.Firstly,the reference image is disentangled by a content and an attribute encoder to obtain content features and attribute features,respectively.Then,a mean mapping rule is introduced to map the binary secret information into a noise vector,conforming to the distribution of attribute features.This noise vector is input into the generator to produce the attribute transformed stego image with the content feature of the reference image.Additionally,we design an adversarial loss,a reconstruction loss,and an image diversity loss to train the proposed model.Experimental results demonstrate that the stego images generated by the proposed method are of high quality,with an average extraction accuracy of 99.4%for the hidden information.Furthermore,since the stego image has a uniform distribution similar to the attribute-transformed image without secret information,it effectively resists both subjective and objective steganalysis.
基金supported by National Natural Science Foundation of China(Grant Nos.12202547,62461160259)Shaanxi Province Qingchuangyuan“Scientist and Engineering”Team Construction Project(Grant Nos.2022KXJ-102,2022KXJ-106)+1 种基金Fundamental Research Funds for the Central UniversitiesProgram for Innovation Team of Shaanxi Province(Grant No.2023-CX-TD-17).
文摘Variable material screw-based material extrusion(S-MEX)3D printing technology provides a novel approach for fabricating composites with continuous material gradients.Nevertheless,achieving precise alignment between the process parameters and material compositions is challenging because of fluctuations in the melt rheological state caused by material variations.In this study,an invertible extrusion prediction model for 0-40 wt% short carbon fiber reinforced polyether-ether-ketone(SCF/PEEK)in the S-MEX process was established using an invertible neural network(INN)that demonstrated the capabilities of forward flow rate prediction and inverse process optimization with accuracies of 0.852 and 0.877,respectively.Moreover,a strategy for adjusting the screw speeds using process parameters obtained from the INN was developed to maintain a consistent flow rate during the variable material printing process.Benefiting from uniform flow,the linewidth accuracy was improved by 77%,and the surface roughness was reduced by 51%.Adjusting the process parameters by using an INN offers significant potential for flow rate control and the enhancement of the overall performance of variable material 3D printing.
文摘Using neural networks for supervised learning means learning a function that maps input <em>x</em> to output <em>y</em>. However, in many applications, the inverse learning is also wanted, <em>i.e.</em>, inferring <em>y</em> from <em>x</em>, which requires invertibility of the learning. Since the dimension of input is usually much higher than that of the output, there is information loss in the forward learning from input to output. Thus, creating invertible neural networks is a difficult task. However, recent development of invertible learning techniques such as normalizing flows has made invertible neural networks a reality. In this work, we applied flow-based invertible neural networks as generative models to inverse molecule design. In this context, the forward learning is to predict chemical properties given a molecule, and the inverse learning is to infer the molecules given the chemical properties. Trained on 100 and 1000 molecules, respectively, from a benchmark dataset QM9, our model identified novel molecules that had chemical property values well exceeding the limits of the training molecules as well as the limits of the whole QM9 of 133,885 molecules, moreover our generative model could easily sample many molecules (<em>x</em> values) from any one chemical property value (<em>y</em> value). Compared with the previous method in the literature that could only optimize one molecule for one chemical property value at a time, our model could be trained once and then be sampled any multiple times and for any chemical property values without the need of retraining. This advantage comes from treating inverse molecule design as an inverse regression problem. In summary, our main contributions were two: 1) our model could generalize well from the training data and was very data efficient, 2) our model could learn bidirectional correspondence between molecules and their chemical properties, thereby offering the ability to sample any number of molecules from any <em>y</em> values. In conclusion, our findings revealed the efficiency and effectiveness of using invertible neural networks as generative models in inverse molecule design.
基金supported by the National Natural Science Foundation of China,with Fund Numbers 62272478,62102451the National Defense Science and Technology Independent Research Project(Intelligent Information Hiding Technology and Its Applications in a Certain Field)and Science and Technology Innovation Team Innovative Research Project Research on Key Technologies for Intelligent Information Hiding”with Fund Number ZZKY20222102.
文摘As neural radiance fields continue to advance in 3D content representation,the copyright issues surrounding 3D models oriented towards implicit representation become increasingly pressing.In response to this challenge,this paper treats the embedding and extraction of neural radiance field watermarks as inverse problems of image transformations and proposes a scheme for protecting neural radiance field copyrights using invertible neural network watermarking.Leveraging 2D image watermarking technology for 3D scene protection,the scheme embeds watermarks within the training images of neural radiance fields through the forward process in invertible neural networks and extracts them from images rendered by neural radiance fields through the reverse process,thereby ensuring copyright protection for both the neural radiance fields and associated 3D scenes.However,challenges such as information loss during rendering processes and deliberate tampering necessitate the design of an image quality enhancement module to increase the scheme’s robustness.This module restores distorted images through neural network processing before watermark extraction.Additionally,embedding watermarks in each training image enables watermark information extraction from multiple viewpoints.Our proposed watermarking method achieves a PSNR(Peak Signal-to-Noise Ratio)value exceeding 37 dB for images containing watermarks and 22 dB for recovered watermarked images,as evaluated on the Lego,Hotdog,and Chair datasets,respectively.These results demonstrate the efficacy of our scheme in enhancing copyright protection.
基金supported by the National Natural Science Foundation of China,with Fund Numbers 62272478,62102451the National Defense Science and Technology Independent Research Project(Intelligent Information Hiding Technology and Its Applications in a Certain Field)and Science and Technology Innovation Team Innovative Research Project“Research on Key Technologies for Intelligent Information Hiding”with Fund Number ZZKY20222102.
文摘Recent research advances in implicit neural representation have shown that a wide range of video data distributions are achieved by sharing model weights for Neural Representation for Videos(NeRV).While explicit methods exist for accurately embedding ownership or copyright information in video data,the nascent NeRV framework has yet to address this issue comprehensively.In response,this paper introduces MarkINeRV,a scheme designed to embed watermarking information into video frames using an invertible neural network watermarking approach to protect the copyright of NeRV,which models the embedding and extraction of watermarks as a pair of inverse processes of a reversible network and employs the same network to achieve embedding and extraction of watermarks.It is just that the information flow is in the opposite direction.Additionally,a video frame quality enhancement module is incorporated to mitigate watermarking information losses in the rendering process and the possibility ofmalicious attacks during transmission,ensuring the accurate extraction of watermarking information through the invertible network’s inverse process.This paper evaluates the accuracy,robustness,and invisibility of MarkINeRV through multiple video datasets.The results demonstrate its efficacy in extracting watermarking information for copyright protection of NeRV.MarkINeRV represents a pioneering investigation into copyright issues surrounding NeRV.
基金The NSF (10971079) of Chinathe Basic Research Foundation (201001001,201103194) of Jilin University
文摘The connectedness of the invertibles question for arbitrary nest has been reduced to the case of the lower triangular operators with respect to a fixed orthonormal basis en for n 1. For each f ∈ H∞, let Tf be the Toeplitz operator. In this paper we prove that Tf can be connected to the identity through a path in the invertible group of the lower triangular operators if f satisfies certain conditions.
文摘We study the structure of invertible substitutions on three-letter alphabet. We show that there exists a finite set S of invertible substitutions such that any invertible substitution can be written as I wσ 1σ 2…σ k,where I w is the inner automorphism associated with w, and σ j∈ S for 1≤j≤k. As a consequence,M is the matrix of an invertible substitution if and only if it is a finite product of non-negative elementary matrices.
文摘A logarithm representation of evolution operators is defined. Generators of invertible evolution families are characterized by the logarithm representation. In this article, using the logarithm representation, a concept of evolution operators without satisfying the semigroup property is introduced. In conclusion the existence of alternative infinitesimal generator is clarified.
文摘An embedding from a group algebra to a matrix algebra is given in this paper. By using it, a criterion for an invertible element in a group algebra is proven.
文摘This paper presents in organized form a number of results that have appeared in the literature in the last two decades,concerning the design of control laws for multi-input multi-output nonlinear systems,with emphasis on the problem of stabilizing an equilibrium,and addresses,at a broad level generality,systems that are invertible from an input-output viewpoint.
文摘Some properties of a finite automaton composed of two weakly invertible finite automata with delay 1 are given, where each of those two automata has the output set of each state with the same size. And for a weakly invertible finite automaton M with delay 2 satisfying the properties mentioned in this paper, two weakly invertible finite automata with delay 1 are constructed such that M is equivalent to a sub-finite-automaton of the composition of those two. So a method to decompose this a kind of weakly invertible finite automata with delay 2 is presented.
文摘By introducing the notion of 'prime substitution' it is shown that the set of invertible substitutions over an alphabet of more than three letters is not finitely generated. Some examples are given.
基金National Natural Science Foundation of China （60174013） Research Foundation for Doctoral Program of Higher Education （20020027013）+1 种基金 Science and Technology Key Project Foundation of Ministry of Education （03184） Major State Basic Research Development Program of China （2002CB312200）
文摘Inclines are the additively idempotent semirings in which products are less than or equal to either factor. In this paper, some necessary and sufficient conditions for a matrix over L to be invertible are given, where L is an incline with 0 and 1. Also it is proved that L is an integral incline if and only if GLn（L） = PLn （L） for any n （n 〉 2）, in which GLn（L） is the group of all n × n invertible matrices over L and PLn（L） is the group of all n × n permutation matrices over L. These results should be regarded as the generalizations and developments of the previous results on the invertible matrices over a distributive lattice.
基金Supported by Ministerio de Educació n, Xunta de Galicia and by FEDER (Grant Nos. MTM2010-15634,MTM2009-14464-C02-01, PGIDT07PXB322079PR)
文摘In this paper we obtain a criterion under which the bijectivity of the canonical morphism of a weak Galois extension associated to a weak invertible entwining structure is equivalent to the existence of a strong connection form. Also we obtain an explicit formula for a strong connection under equivariant projective conditions or under coseparability conditions.
基金Supported by the Fundamental Research Funds for the Central Universities(2024ZYGXZR047)the National Natural Science Foundation of China(62373156)the Guangdong Basic and Applied Basic Research Foundation(2024A1515011736)。
文摘This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.
文摘Converting subsurface offset domain common image gathers(ODCIGs)to angle domain common image gathers(ADCIGs)through a Radon Transform(RT)in either the spatial or wavenumber domain is efficient and valid except for the distortion of both frequency spectrum and amplitude versus angle(AVA)effect.This paper presents two modifications to the existing method to keep the frequency spectrum of the resultant ADCIGs the same as the input data and to preserve the relative amplitudes.The spectrum invariance is achieved by replacing the conventional RT or slant slack by an invertible RT.Amplitude preservation is obtained by applying an amplitude correction factor in the angle domain.Tests on both synthetic and field datasets validate the accuracy of these modifications.
基金supported by the Research Projects of the Department of Education of Guangdong Province 2024ZDZX3079The financial support from the Guangdong Basic and Applied Basic Research Foundation(No.2023A1515011677)+4 种基金the Scientific and Technical Innovation Council of Shenzhen(20220812165832002)the Research Projects of Department of Education of Guangdong Province-2023GCZX015the Innovation Team Project of Guangdong(2022KCXTD055)the China Postdoctoral Science Foundation(Certificate Number:2024M763441)is gratefully acknowledgedsupported by the Postdoctoral Fellowship Program of CPSF under Grant Number GZB20250031 and Research Projects of the Department of Education of Guangdong Province 2023GCZX015。
文摘Despite the intrinsic durability of polymeric hole transport materials,poly-triarylamines(PTAA)-based inverted perovskite solar cells(PSCs)have lagged behind their counterparts in efficiency,primarily due to poor surface wettability,insufficient interfacial contact,and unfavorable energy level alignment at the PTAA/perovskite interface.Here,we report a highly effective interfacial engineering strategy employing the ionic liquid 1,3-dimethylimidazolium dimethyl phosphate(DMIMPH)as a multifunctional interfacial modifier.The incorporation of DMIMPH improves PTAA wettability,promoting the growth of high-quality perovskite films with enhanced interfacial contact.Concurrently,DMIMPH effectively tunes the energy levels of PTAA,enhances its electrical conductivity,and passivates interfacial defects with more efficient hole extraction and charge transport.Moreover,its interaction with residual PbI_(2) modulates perovskite crystallization kinetics,yielding highly crystalline perovskite films with enlarged grain sizes,reduced PbI_(2) residue,and suppressed trap densities.As a result,PTAA-based p-i-n PSCs employing this approach achieve a record certified power conversion efficiency(PCE)of 24.52%,with a champion efficiency of 25.12%—the highest certified value for PTAA-based perovskite devices to date.Impressively,the DMIMPH-modified PSCs without encapsulation maintained 87.48%of their initial efficiency after 1600 h in air.This strategy offers an effective pathway for advancing the performance and stability of polymer-based inverted PSCs.
基金supported by the National Key R&D Program of China(2024YFB3211600)the National Natural Science Foundation of China(Nos.62273073,52273316)+4 种基金the National Key R&D Program of China(2023YFC2411800,2022YFE0134800)the Natural Science Foundation of Sichuan(2025ZNSFSC0515)Chengdu Science Technology Bureau(2023-YF06-00028-HZ)and the Fundamental Research Funds for the Central Universities(ZYGX2025TS009,ZYGX2024XJ029,ZYGX2024XJ031)Sci-entific Research Innovation Capability Support Project for Young Faculty(ZYGXQNJSKYCXNLZCXM-M1P).
文摘Organic electrochemical transistors(OECTs)are promising for next-generation bioelectronics due to their high performance and biocompatibility.Nevertheless,they still face tremendous operational stability challenges due to the limited robustness of the organic mixed ionic-electronic conductor(OMIEC)channel.Here,by modulating the molecular weight(MW)of OMiEC,enhanced OECT and relevant circuit operation stabilities are demonstrated,showing more than 3,000,0o0 full cycles(~42 h)with less than 15%current variation in an OECT,and 150,000 cycles(~4 h)with less than 5%voltage variation in an OECT-based inverter,which are among the highest of reported OECT-based electronics.Specifically,p(g2T-T),a typical p-type OMIEC,with varying MW(7-43 kDa),is synthesized,where lower-MW p(g2T-T)(~9 kDa)exhibits superior device performance and cycling stability in OECTs,outperforming those in high-MW counterparts(>30 kDa).It is indicated that low-MW p(g2T-T)maintains higher volumetric capacitance,ordered orientation,and reduced swelling.Therefore,irreversible microstructural degradation is effectively avoided,along with better performance yield.Furthermore,MW regulation enables physiological signal sensing with high tolerance to body fluid environments for 7 days.These findings highlight MW modulation as a versatile approach to suppress excessive swelling,advancing the design of durable OECT-based electronics.
基金supported by the Smart Grid-National Science and Technology Major Project(2025ZD0804500)the National Natural Science Foundation of China under Grant 52307232the Hunan Provincial Natural Science Foundation of China under Grant 2024JJ4055.
文摘The hybrid series-parallel microgrid attracts more attention by combining the advantages of both the series-stacked voltage and parallel-expanded capacity.Low-voltage distributed generations(DGs)are connected in series to form the intra-string,and then multiple strings are interconnected in parallel.For the existing control strategies,both intra-string and inter-string depend on the centralized or distributed control with high communication reliance.It has limited scalability and redundancy under abnormal conditions.Alternatively,in this study,an intra-string distributed and inter-string decentralized control framework is proposed.Within the string,a few DGs close to the AC bus are the leaders to get the string power information and the rest DGs are the followers to acquire the synchronization information through the droop-based distributed consistency.Specifically,the output of the entire string has the active power−angular frequency(ω-P)droop characteristic,and the decentralized control among strings can be autonomously guaranteed.Moreover,the secondary control is designed to realize multi-mode objectives,including on/off-grid mode switching,grid-connected power interactive management,and off-grid voltage quality regulation.As a result,the proposed method has the ability of plug-and-play capabilities,single-point failure redundancy,and seamless mode-switching.Experimental results are provided to verify the effectiveness of the proposed practical solution.
