In this paper,we first establish the dual Brunn-Minkowski inequality for the star duals for the Lp radial sum.Furthermore,we give some Brunn-Minkowski inequalities for the star duals of intersection bodies for the Lp ...In this paper,we first establish the dual Brunn-Minkowski inequality for the star duals for the Lp radial sum.Furthermore,we give some Brunn-Minkowski inequalities for the star duals of intersection bodies for the Lp radial sum and the Lp harmonic Blaschke sum.展开更多
The main result of this paper is the identification of the sequential order dual [∧(X)]so containing sequentially order continuous linear functionals on the ordered generalized sequence space ∧(X) with its generaliz...The main result of this paper is the identification of the sequential order dual [∧(X)]so containing sequentially order continuous linear functionals on the ordered generalized sequence space ∧(X) with its generalized Kothe dual ∧x(Xso), defined corresponding to the dual pair <X, Xso>.展开更多
This paper is concerned with the characterization of the duals of wavelet frames of L(2)(R).The sufficient and necessary conditions for them are obtained.
The characteristic tilting modules of quasi-hereditary algebras which are dual extensions of directed monomial algebras are explicitly constructed; and it is shown that the Ringel dual of the dual extension of an arbi...The characteristic tilting modules of quasi-hereditary algebras which are dual extensions of directed monomial algebras are explicitly constructed; and it is shown that the Ringel dual of the dual extension of an arbitrary hereditary algebra has triangular decomposition and bipartite quiver.展开更多
[Background]High harmonic cavities are widely used in electron storage rings to lengthen thebunch,lower the bunch peak current,thereby reducing the IBS effect,enhancing the Touschek lifetime,as well asproviding Landau...[Background]High harmonic cavities are widely used in electron storage rings to lengthen thebunch,lower the bunch peak current,thereby reducing the IBS effect,enhancing the Touschek lifetime,as well asproviding Landau damping,which is particularly important for storage rings operating with ultra-low emittance or atlow beam energy.[Purpose]To further increase the bunch length without additional hardware costs,the phasemodulation in a dual-RF system is considered.[Methods]In this paper,turn-by-turn simulations incorporating randomsynchrotron radiation excitation are conducted,and a brief analysis is presented to explain the bunch lengtheningmechanism.[Results]Simulation results reveal that the peak current can be further reduced,thereby mitigating IBSeffects and enhancing the Touschek lifetime.Although the energy spread increases,which tends to reduce thebrightness of higher-harmonic radiation from the undulator,the brightness of the fundamental harmonic can,in fact,beimproved.展开更多
Achieving simultaneous enhancement of crystallinity and optimal domain size remains a fundamental challenge in organic photovoltaics(OPVs),where conventional crystallization strategies often trigger excessive aggregat...Achieving simultaneous enhancement of crystallinity and optimal domain size remains a fundamental challenge in organic photovoltaics(OPVs),where conventional crystallization strategies often trigger excessive aggregation of small-molecule acceptors.This work pioneers a kinetic paradigm for resolving the crystallinity-domain size trade-off in organic photovoltaics through dual-additive-guided stepwise crystallization.By strategically pairing 1,2-dichlorobenzene(o-DCB,low binding energy to Y6)and 1-fluoronaphthalene(FN,high binding energy),we achieve temporally decoupled crystallization control:o-DCB first mediates donor-acceptor co-crystallization during film formation,constructing a metastable network,whereupon FN induces confined Y6 crystallization within this framework during thermal annealing,refining nanostructure without over-aggregation.Morphology studies reveal that this synergy enhances crystallinity of(100)diffraction peaks by 21%–10%versus single-additive controls(o-DCB/FN alone),while maintaining optimal domain size.These morphological advantages yield balanced carrier transport(μh/μe=1.23),near-unity exciton dissociation(98.53%),and a champion power conversion efficiency(PCE)of 18.08%for PM6:Y6,significantly surpassing single-additive devices(o-DCB:17.20%;FN:17.53%).Crucially,the dual-additive strategy demonstrates universal applicability across diverse active layer systems,achieving an outstanding PCE of 19.27%in PM6:L8-BO-based devices,thereby establishing a general framework for morphology control in high-efficiency OPVs.展开更多
The dissolvable polysulfides and sluggish Li_2S conversion kinetics are acknowledged as two significant challenges in the application lithium-sulfur(Li-S)batteries.Herein,we introduce a dual-doping strategy to modulat...The dissolvable polysulfides and sluggish Li_2S conversion kinetics are acknowledged as two significant challenges in the application lithium-sulfur(Li-S)batteries.Herein,we introduce a dual-doping strategy to modulate the electronic structure of MoS_(2),thereby obtaining a multifunctional catalyst that serves as an efficient sulfur host.The W/V dual single-atomdoped MoS_(2)grown on carbon nanofibers(CMWVS)demonstrates a strong adsorption ability for lithium polysulfides,suppressing the shuttle effects.Additionally,the doping process also results in the phase transition from 2H-MoS_(2)to 1T-MoS_(2)and generates sufficient edge sulfur atoms,promoting the charge/electron transfer and enriching the reaction sites.All these merits contribute to the superior conversion reaction kinetics,leading to the outstanding Li-S battery performance.When fabricated as cathodes by compositing with sulfur,the CMWVS/S cathode delivers a high capacity of 1481.7 mAh g^(-1)at 0.1 C(1 C=1672 mAh g^(-1))and maintains 816.3 m Ah g^(-1)after 1000 cycles at 1.0 C,indicating outstanding cycling stability.Even under a high sulfur loading of 7.9 mg cm^(-2)and lean electrolyte conditions(E/S ratio of 9.0μL mg^(-1)),the cathode achieves a high areal capacity of 8.2 m Ah cm^(-2),showing great promise for practical Li-S battery applications.This work broadens the scope of doping strategies in transition-metal dichalcogenides by tailoring their electronic structures,providing insightful direction for the rational development of high-efficiency electrocatalysts for advanced Li-S battery applications.展开更多
Albeit notable endeavors in the construction of organophosphorodithioates,the direct catalytic enantioselective synthesis of organophosphorodithioates still stands for a long-lasting challenge.Herein,an efficient orga...Albeit notable endeavors in the construction of organophosphorodithioates,the direct catalytic enantioselective synthesis of organophosphorodithioates still stands for a long-lasting challenge.Herein,an efficient organocatalytic enantioselective nucleophilic addition of vinylidene ortho-quinone methide with phosphinothioic thioanhydride as nucleophilic reagent has been achieved by the dual catalysis of cinchona alkaloid-derived squaramide and 4-dimethylaminopyridine.This protocol provides a straightforward approach for accessing a variety of axially chiral phosphorodithiolated styrenes in good yields(up to 98 %yield) with high stereoselectivities(up to 97 % ee and >99:1 E/Z).展开更多
The Vertical Total Electron Content(VTEC)of the ionosphere is a crucial parameter for describing the distribution and dynamic changes within the ionosphere.The study utilizes Dual Hybrid Attentional UNet(DHA-UNet)mode...The Vertical Total Electron Content(VTEC)of the ionosphere is a crucial parameter for describing the distribution and dynamic changes within the ionosphere.The study utilizes Dual Hybrid Attentional UNet(DHA-UNet)model to achieve higher forecasting performance for global VTEC predictions under the condition of data acquisition delays.Initially,this study uses the first Hybrid Attentional UNet(HA-UNet)model to predict the intermediate missing data.The missing data are caused by delays in data processing,making the Global Ionosphere Map(GIM)for the current day unavailable.Subsequently,the predicted results from the first HA-UNet model are concatenated with the input data to serve as the input data for the second HA-UNet model,yielding the final prediction results.The performance of DHA-UNet model is then evaluated under varying solar and geomagnetic activity conditions.Evaluation results demonstrate that the DHA-UNet model exhibits higher forecasting accuracy and stability compared to commonly used temporal and spatiotemporal forecasting models.Compared to CODG VTEC,the DHA-UNet model achieves Mean Absolute Error(MAE)values of 2.60 TECU,3.07 TECU,3.78 TECU,and 6.45TECU during quiet,weak,moderate,and strong geomagnetic storm periods,respectively,in years of high solar activity.In years of low solar activity,the model achieves MAE values of 1.00 TECU,1.15 TECU,and 1.54 TECU during quiet,weak,and moderate geomagnetic storm periods,respectively.Even during strong geomagnetic storms,55%of the residuals from the DHA-UNet model fall within the-5.0 TECU to 5.0 TECU range,surpassing other commonly used models.Compared to the C1PG forecasting product,the DHA-UNet model shows particularly notable improvements in accuracy during the spring and winter seasons,as well as in mid-to high-latitude regions.展开更多
Sodium-based dual-ion batteries(SDIBs)have been attracting increasing attention in recent years owing to their low cost,environmental benignancy,and high operating voltage.However,the sluggish ion kinetics of conventi...Sodium-based dual-ion batteries(SDIBs)have been attracting increasing attention in recent years owing to their low cost,environmental benignancy,and high operating voltage.However,the sluggish ion kinetics of conventional carbon anodes that cannot match the fast capacitive anion intercalation behavior of graphite cathodes constraints on improving power density of SDIBs.Herein,we present an ingenious carbon microdomain engineering strategy to fabricate high-performance carbon anode with ion-mediated high-activity nitrogen species and molecular-scale closed-pore architectures.Experimental characterizations and theoretical investigations demonstrate that Zn^(2+)-mediated structural engineering tailors oxidized nitrogen species,which proficiently accelerate the sodium-ion desolvation kinetics;meanwhile the acetate-mediated pore-forming process modulates closed pores,which synergistically afford abundant sodium storage sites for high plateau-region capacity.As a result,the optimized microdomain engineered carbon material(MEC_(3))tailored with the optimal amount of zinc acetate demonstrates an outstanding plateau-region capacity of 253 mAh g^(-1)even at 1 C,among the highest reported values.Consequently,the MEC_(3)||expanded graphite dual-ion battery exhibits an unprecedented cycling stability at high current rate,maintaining 80.6%capacity retention after 10,000 cycles at 10 C,among the best reports.This microdomain engineering strategy provides a new design principle for overcoming kinetic limitations of carbonaceous materials in plateau-dominated sodium storage systems.展开更多
Clock synchronization has important applications in multi-agent collaboration(such as drone light shows,intelligent transportation systems,and game AI),group decision-making,and emergency rescue operations.Synchroniza...Clock synchronization has important applications in multi-agent collaboration(such as drone light shows,intelligent transportation systems,and game AI),group decision-making,and emergency rescue operations.Synchronization method based on pulse-coupled oscillators(PCOs)provides an effective solution for clock synchronization in wireless networks.However,the existing clock synchronization algorithms in multi-agent ad hoc networks are difficult to meet the requirements of high precision and high stability of synchronization clock in group cooperation.Hence,this paper constructs a network model,named DAUNet(unsupervised neural network based on dual attention),to enhance clock synchronization accuracy in multi-agent wireless ad hoc networks.Specifically,we design an unsupervised distributed neural network framework as the backbone,building upon classical PCO-based synchronization methods.This framework resolves issues such as prolonged time synchronization message exchange between nodes,difficulties in centralized node coordination,and challenges in distributed training.Furthermore,we introduce a dual-attention mechanism as the core module of DAUNet.By integrating a Multi-Head Attention module and a Gated Attention module,the model significantly improves information extraction capabilities while reducing computational complexity,effectively mitigating synchronization inaccuracies and instability in multi-agent ad hoc networks.To evaluate the effectiveness of the proposed model,comparative experiments and ablation studies were conducted against classical methods and existing deep learning models.The research results show that,compared with the deep learning networks based on DASA and LSTM,DAUNet can reduce the mean normalized phase difference(NPD)by 1 to 2 orders of magnitude.Compared with the attention models based on additive attention and self-attention mechanisms,the performance of DAUNet has improved by more than ten times.This study demonstrates DAUNet’s potential in advancing multi-agent ad hoc networking technologies.展开更多
Male sexual behaviors,including mounting,intromission,and ejaculation,are not only critical for reproduction but also serve as a model for understanding how the brain orchestrates sequential motor and motivational pro...Male sexual behaviors,including mounting,intromission,and ejaculation,are not only critical for reproduction but also serve as a model for understanding how the brain orchestrates sequential motor and motivational processes.While previous studies have identified key brain regions involved in sexual behaviors,such as the medial preoptic area(MPOA)and the nucleus accumbens(NAc)[14],the neural mechanisms governing the transitions between different phases of male sexual behavior remain poorly understood.展开更多
To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capabl...To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.展开更多
Lithology identificationwhile drilling technology can obtain rock information in real-time.However,traditional lithology identificationmodels often face limitations in feature extraction and adaptability to complex ge...Lithology identificationwhile drilling technology can obtain rock information in real-time.However,traditional lithology identificationmodels often face limitations in feature extraction and adaptability to complex geological conditions,limiting their accuracy in challenging environments.To address these challenges,a deep learning model for lithology identificationwhile drilling is proposed.The proposed model introduces a dual attention mechanism in the long short-term memory(LSTM)network,effectively enhancing the ability to capture spatial and channel dimension information.Subsequently,the crayfishoptimization algorithm(COA)is applied to optimize the model network structure,thereby enhancing its lithology identificationcapability.Laboratory test results demonstrate that the proposed model achieves 97.15%accuracy on the testing set,significantlyoutperforming the traditional support vector machine(SVM)method(81.77%).Field tests under actual drilling conditions demonstrate an average accuracy of 91.96%for the proposed model,representing a 14.31%improvement over the LSTM model alone.The proposed model demonstrates robust adaptability and generalization ability across diverse operational scenarios.This research offers reliable technical support for lithology identification while drilling.展开更多
Metabolic-associated fatty liver disease(MAFLD)is the most prevalent chronic liver disease globally,with no effective pharmacological treatments available for early-stage cases.Rutin,a bioactive flavonoid from Sophora...Metabolic-associated fatty liver disease(MAFLD)is the most prevalent chronic liver disease globally,with no effective pharmacological treatments available for early-stage cases.Rutin,a bioactive flavonoid from Sophora japonica L.,exhibits diverse pharmacological effects,but its multi-pathway mechanisms in improving MAFLD remain unclear.In this study,we employed a high-fat diet(HFD)-induced MAFLD mouse model to investigate the therapeutic effects of rutin supplementation.Rutin supplementation significantly reduced blood lipid and liver lipid levels and alleviated liver injury in MAFLD model mice.Fecal microbiota transplantation experiments revealed that rutin alleviated MAFLD by modulating the gut microbiota composition.Through 16S rRNA sequencing analysis and non-targeted metabolomics analysis of the normal control(NC),HFD and rutin groups,rutin was found to alter key species(Ruminococcus torques)and associated metabolites(e.g.,7-dehydrocholesterol,short-chain fatty acids),suggesting a mechanism involving the gut microbiota.Antibiotic treatment experiments revealed that rutin alleviates MAFLD via the blood entry pathway.Network pharmacology analysis showed that rutin can directly act on targets closely related to MAFLD development,including tumor protein p53,epidermal growth factor receptor,and prostaglandin-endoperoxide synthase 2,as well as key signaling pathways such as PI3K/AKT and MAPK.Transcriptomics analysis of the NC,HFD and rutin groups revealed that rutin may ameliorate MAFLD through PI3K/AKT and MAPK signaling pathways,which might be enhanced by the gut microbiota and blood entry pathways.In conclusion,rutin can treat MAFLD through both the gut microbiota and blood entry pathways,resulting in a synergistic effect.Our study provides a novel strategy for evaluating functional food components and offers a scientific basis for dietary flavonoid-based interventions against MAFLD.展开更多
In recent years the crucial role of CD4^(+)T cells in tumor immunomodulation has garnered increasing recognition.While conventional cancer immunotherapy research has predominantly focused on the cytotoxic function of ...In recent years the crucial role of CD4^(+)T cells in tumor immunomodulation has garnered increasing recognition.While conventional cancer immunotherapy research has predominantly focused on the cytotoxic function of CD8+T cells,emerging evidence has now shown that CD4^(+)T cells enhance antitumor immunity by delivering co-stimulatory signals,secreting cytokines,and promoting cytotoxic T lymphocyte(CTL)activation and display unique immunoregulatory capabilities through direct tumor cell killing or remodeling of the tumor microenvironment.The high heterogeneity and functional plasticity of CD4^(+)T cell subsets significantly influence clinical responses to immunotherapy with underlying mechanisms involving multi-level regulatory networks,including epigenetic modulation and metabolic reprogramming.Deciphering the functional heterogeneity of CD4^(+)T cells and the interactions with the tumor microenvironment will provide essential mechanistic insights for next-generation immunotherapies,such as immune checkpoint inhibitors and chimeric antigen receptor T(CAR-T)therapies,thereby advancing personalized treatment paradigms.展开更多
The construction of spot electricity markets plays a pivotal role in power system reforms,where market clearing systems profoundly influence market efficiency and security.Current clearing systems predominantly adopt ...The construction of spot electricity markets plays a pivotal role in power system reforms,where market clearing systems profoundly influence market efficiency and security.Current clearing systems predominantly adopt a single-system architecture,with research focusing primarily on accelerating solution algorithms through techniques such as high-efficiency parallel solvers and staggered decomposition of mixed-integer programming models.Notably absent are systematic studies evaluating the adaptability of primary-backup clearing systems incontingency scenarios—a critical gap given redundant systems’expanding applications in operational environments.This paper proposes a comprehensive evaluation framework for analyzing dual-system adaptability,demonstrated through an in-depth case study of the Inner Mongolia power market.First,we establish the innovative“Dual-Active Heterogeneous”architecture that enables independent parallelized operation and fault-isolated redundancy.Subsequently,key performance indices are quantitatively evaluated across four critical dimensions:unit commitment decisions,generator output constraints,transmission section congestion patterns,and clearing price formation mechanisms.An integrated fuzzy evaluation methodology incorporating grey relational analysis is employed for objective indicator weighting,enabling systematic quantification of system superiority under specific grid operating states.Empirical results based on actual operational data from 200 generation units demonstrate the framework’s efficacy in guiding optimal system selection,with particularly strong performance observed during peak load periods.The proposed approach shows high generalization potential for other regional markets employing redundant clearing mechanisms—particularly those with increasing renewable penetration and associated uncertainty.展开更多
In massive multiple-input multiple-output(MIMO)systems utilizing frequency division duplexing,optimizing system performance requires user equipment(UE)to compress downlink channel state information(CSI)and transmit it...In massive multiple-input multiple-output(MIMO)systems utilizing frequency division duplexing,optimizing system performance requires user equipment(UE)to compress downlink channel state information(CSI)and transmit it to the base station(BS).As the number of antennas increases,there is a significant rise in the overhead related to CSI feedback,posing considerable challenges to the precise acquisition of CSI by the BS.Existing approaches to CSI feedback utilizing deep learning techniques face challenges such as significant feedback overhead and limited precision in the reconstruction process.This study presents a novel lightweight CSI feedback framework known as the dual attention neural network(DANet).Within the DANet architecture,a dual attention module(DAM)is designed to enhance the network's performance.This DAM includes both channel attention blocks and spatial attention blocks.The channel attention blocks direct the model's focus toward channel features rich in information content while simultaneously suppressing less significant features.This approach enables the extraction of temporal correlations within the CSI matrix.The spatial attention block aids in extracting the correlation between the delay domain and the angle domain in the CSI matrix.By enhancing neural network performance,the DAM reduces information dispersion while enhancing the representation of global interactions.Simulation results demonstrate that DANet exhibits superior normalized mean square error and cosine similarity with comparable complexity compared to existing advanced CSI feedback methods.展开更多
Traditional strategies for designing hyperhalogens,superatoms with exceptional electron-withdrawing capacity,rely on complex superhalogen assembly,posing significant experimental challenges.Here,we introduce a non-inv...Traditional strategies for designing hyperhalogens,superatoms with exceptional electron-withdrawing capacity,rely on complex superhalogen assembly,posing significant experimental challenges.Here,we introduce a non-invasive dual external field(DEF) approach combining solvent effects and an oriented external electric field(OEEF) to construct hyperhalogens,as demonstrated by density functional theory(DFT) calculations.Our DEF strategy proves versatile,successfully designing hyperhalogens not only in simplified Ag_n^(-) model systems but also in the experimentally synthesized Ag_(25) nanocluster.Using the 3D Ag_(19)^(-) structure as a model,we further reveal the DEF's pivotal role in O_(2) activation,where solvent-OEEF synergy induces tunable O-O bond elongation and charge transfer,proportional to field strength.Our findings establish a field-driven paradigm for hyperhalogen design that preserves native cluster composition,providing a theoretical foundation for tailoring high-performance catalysts through precise activesite modulation.展开更多
Hydrogen,as a zero-carbon secondary energy carrier,provides a unified pathway for low-carbon energy transformation.In electro–hydrogen coupling systems(EHCSs),surplus renewable power is stored via water electrolysis ...Hydrogen,as a zero-carbon secondary energy carrier,provides a unified pathway for low-carbon energy transformation.In electro–hydrogen coupling systems(EHCSs),surplus renewable power is stored via water electrolysis and later reconverted to electricity using fuel cells or gas turbines,enhancing the system’s flexibility and reliability in support of deep decarbonization.This study constructs an electricity–hydrogen energy-recycling model based on a coupling relationship considering the bidirectional conversion between electricity and hydrogen.A multistage carbon-emission-reduction indicator constraint is also established.Additionally,the green-certificate and carbon trading markets are introduced to optimize equipment investment and operation costs while achieving carbon-emission reduction.A case study reveals that the proposed EHCS planning model effectively allocates carbon emissions across different system stages,while mitigating economic repercussions,thus ensuring closer alignment with China’s emission-reduction policies.Incorporating diverse market mechanisms significantly enhances the system’s economy and decision-making flexibility,particularly in addressing future challenges in the energy market.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No.10671119)the Shanghai Leading Academic Discipline Project (Grant No.J50101)the Shanghai University Graduate Innovation Foundation Project (GrantNo.SHUCX092003)
文摘In this paper,we first establish the dual Brunn-Minkowski inequality for the star duals for the Lp radial sum.Furthermore,we give some Brunn-Minkowski inequalities for the star duals of intersection bodies for the Lp radial sum and the Lp harmonic Blaschke sum.
文摘The main result of this paper is the identification of the sequential order dual [∧(X)]so containing sequentially order continuous linear functionals on the ordered generalized sequence space ∧(X) with its generalized Kothe dual ∧x(Xso), defined corresponding to the dual pair <X, Xso>.
文摘This paper is concerned with the characterization of the duals of wavelet frames of L(2)(R).The sufficient and necessary conditions for them are obtained.
文摘The characteristic tilting modules of quasi-hereditary algebras which are dual extensions of directed monomial algebras are explicitly constructed; and it is shown that the Ringel dual of the dual extension of an arbitrary hereditary algebra has triangular decomposition and bipartite quiver.
基金National Natural Science Foundation of China(12405168)The Fundamental Research Funds for the Central Universities,China(2024CDJXY004)。
文摘[Background]High harmonic cavities are widely used in electron storage rings to lengthen thebunch,lower the bunch peak current,thereby reducing the IBS effect,enhancing the Touschek lifetime,as well asproviding Landau damping,which is particularly important for storage rings operating with ultra-low emittance or atlow beam energy.[Purpose]To further increase the bunch length without additional hardware costs,the phasemodulation in a dual-RF system is considered.[Methods]In this paper,turn-by-turn simulations incorporating randomsynchrotron radiation excitation are conducted,and a brief analysis is presented to explain the bunch lengtheningmechanism.[Results]Simulation results reveal that the peak current can be further reduced,thereby mitigating IBSeffects and enhancing the Touschek lifetime.Although the energy spread increases,which tends to reduce thebrightness of higher-harmonic radiation from the undulator,the brightness of the fundamental harmonic can,in fact,beimproved.
基金supported by the Shaanxi Provincial High level Talent Introduction Project(5113220044)the Shaanxi Outstanding Youth Project(2023-JC-JQ-33)+8 种基金the Youth Science and Technology Talent Promotion Project of Jiangsu Association for Science and Technology(TJ-2022-088)the Project funded by China Postdoctoral Science Foundation(2023TQ0273,2023TQ0274,2023M742833)the NationalNatural Science Foundation of China(62304181)the Natural Science Basic Research Program of Shaanxi(2023-JC-QN-0726,2025JC-YBQN-469)the GuangdongBasic and Applied Basic Research Foundation(2022A1515110286,2024A1515012538)the Basic Research Programs of Taicang(TC2024JC04)the Suzhou Science and Technology Development Plan Innovation Leading Talent Project(ZXL2023183)the Fundamental Research Funds for the Central Universities(G2022KY05108,G2024KY0605,G2023KY0601)and the Aeronautical Science Foundation of China(2018ZD53047).
文摘Achieving simultaneous enhancement of crystallinity and optimal domain size remains a fundamental challenge in organic photovoltaics(OPVs),where conventional crystallization strategies often trigger excessive aggregation of small-molecule acceptors.This work pioneers a kinetic paradigm for resolving the crystallinity-domain size trade-off in organic photovoltaics through dual-additive-guided stepwise crystallization.By strategically pairing 1,2-dichlorobenzene(o-DCB,low binding energy to Y6)and 1-fluoronaphthalene(FN,high binding energy),we achieve temporally decoupled crystallization control:o-DCB first mediates donor-acceptor co-crystallization during film formation,constructing a metastable network,whereupon FN induces confined Y6 crystallization within this framework during thermal annealing,refining nanostructure without over-aggregation.Morphology studies reveal that this synergy enhances crystallinity of(100)diffraction peaks by 21%–10%versus single-additive controls(o-DCB/FN alone),while maintaining optimal domain size.These morphological advantages yield balanced carrier transport(μh/μe=1.23),near-unity exciton dissociation(98.53%),and a champion power conversion efficiency(PCE)of 18.08%for PM6:Y6,significantly surpassing single-additive devices(o-DCB:17.20%;FN:17.53%).Crucially,the dual-additive strategy demonstrates universal applicability across diverse active layer systems,achieving an outstanding PCE of 19.27%in PM6:L8-BO-based devices,thereby establishing a general framework for morphology control in high-efficiency OPVs.
基金supported by the National Natural Science Foundation of China(52402166)the Science and Technology Development Fund+2 种基金Macao SAR(0065/2023/AFJ,0116/2022/A3)the Australian Research Council(DE220100154)the Natural Science Foundation of Guangdong Province(2025A1515011120)。
文摘The dissolvable polysulfides and sluggish Li_2S conversion kinetics are acknowledged as two significant challenges in the application lithium-sulfur(Li-S)batteries.Herein,we introduce a dual-doping strategy to modulate the electronic structure of MoS_(2),thereby obtaining a multifunctional catalyst that serves as an efficient sulfur host.The W/V dual single-atomdoped MoS_(2)grown on carbon nanofibers(CMWVS)demonstrates a strong adsorption ability for lithium polysulfides,suppressing the shuttle effects.Additionally,the doping process also results in the phase transition from 2H-MoS_(2)to 1T-MoS_(2)and generates sufficient edge sulfur atoms,promoting the charge/electron transfer and enriching the reaction sites.All these merits contribute to the superior conversion reaction kinetics,leading to the outstanding Li-S battery performance.When fabricated as cathodes by compositing with sulfur,the CMWVS/S cathode delivers a high capacity of 1481.7 mAh g^(-1)at 0.1 C(1 C=1672 mAh g^(-1))and maintains 816.3 m Ah g^(-1)after 1000 cycles at 1.0 C,indicating outstanding cycling stability.Even under a high sulfur loading of 7.9 mg cm^(-2)and lean electrolyte conditions(E/S ratio of 9.0μL mg^(-1)),the cathode achieves a high areal capacity of 8.2 m Ah cm^(-2),showing great promise for practical Li-S battery applications.This work broadens the scope of doping strategies in transition-metal dichalcogenides by tailoring their electronic structures,providing insightful direction for the rational development of high-efficiency electrocatalysts for advanced Li-S battery applications.
基金financial support from Natural Science Foundation of China (No.22161005)Guangxi Natural Science Foundation (Nos.2021GXNSFDA075005,2024GXNSFFA010001)。
文摘Albeit notable endeavors in the construction of organophosphorodithioates,the direct catalytic enantioselective synthesis of organophosphorodithioates still stands for a long-lasting challenge.Herein,an efficient organocatalytic enantioselective nucleophilic addition of vinylidene ortho-quinone methide with phosphinothioic thioanhydride as nucleophilic reagent has been achieved by the dual catalysis of cinchona alkaloid-derived squaramide and 4-dimethylaminopyridine.This protocol provides a straightforward approach for accessing a variety of axially chiral phosphorodithiolated styrenes in good yields(up to 98 %yield) with high stereoselectivities(up to 97 % ee and >99:1 E/Z).
基金funded by the National Key R&D Program of China(No.2022YFB3904402)the National Natural Science Foundation of China(Nos.42474037 and U2233217)。
文摘The Vertical Total Electron Content(VTEC)of the ionosphere is a crucial parameter for describing the distribution and dynamic changes within the ionosphere.The study utilizes Dual Hybrid Attentional UNet(DHA-UNet)model to achieve higher forecasting performance for global VTEC predictions under the condition of data acquisition delays.Initially,this study uses the first Hybrid Attentional UNet(HA-UNet)model to predict the intermediate missing data.The missing data are caused by delays in data processing,making the Global Ionosphere Map(GIM)for the current day unavailable.Subsequently,the predicted results from the first HA-UNet model are concatenated with the input data to serve as the input data for the second HA-UNet model,yielding the final prediction results.The performance of DHA-UNet model is then evaluated under varying solar and geomagnetic activity conditions.Evaluation results demonstrate that the DHA-UNet model exhibits higher forecasting accuracy and stability compared to commonly used temporal and spatiotemporal forecasting models.Compared to CODG VTEC,the DHA-UNet model achieves Mean Absolute Error(MAE)values of 2.60 TECU,3.07 TECU,3.78 TECU,and 6.45TECU during quiet,weak,moderate,and strong geomagnetic storm periods,respectively,in years of high solar activity.In years of low solar activity,the model achieves MAE values of 1.00 TECU,1.15 TECU,and 1.54 TECU during quiet,weak,and moderate geomagnetic storm periods,respectively.Even during strong geomagnetic storms,55%of the residuals from the DHA-UNet model fall within the-5.0 TECU to 5.0 TECU range,surpassing other commonly used models.Compared to the C1PG forecasting product,the DHA-UNet model shows particularly notable improvements in accuracy during the spring and winter seasons,as well as in mid-to high-latitude regions.
基金support from the National Key R&D Program of China(2022YFB2402600)the National Natural Science Foundation of China(52125105,52572282,52472269,52273312,22309200)+3 种基金Guangdong Basic and Applied Basic Research Foundation(2024A1515010201,2024A1515012379,2024A1515011670,2023A1515011519)Guangdong Special Support Program Outstanding Young Talents in Science and Technology Innovation(2021TQ05L894)Shenzhen Science and Technology Planning Project(JSGG20220831104004008,SGDX20230116092055008,KCXST20221021111606016)the NSRF via the Program Management Unit for Human Resources&Institutional Development,Research and Innovation(B49G680115).
文摘Sodium-based dual-ion batteries(SDIBs)have been attracting increasing attention in recent years owing to their low cost,environmental benignancy,and high operating voltage.However,the sluggish ion kinetics of conventional carbon anodes that cannot match the fast capacitive anion intercalation behavior of graphite cathodes constraints on improving power density of SDIBs.Herein,we present an ingenious carbon microdomain engineering strategy to fabricate high-performance carbon anode with ion-mediated high-activity nitrogen species and molecular-scale closed-pore architectures.Experimental characterizations and theoretical investigations demonstrate that Zn^(2+)-mediated structural engineering tailors oxidized nitrogen species,which proficiently accelerate the sodium-ion desolvation kinetics;meanwhile the acetate-mediated pore-forming process modulates closed pores,which synergistically afford abundant sodium storage sites for high plateau-region capacity.As a result,the optimized microdomain engineered carbon material(MEC_(3))tailored with the optimal amount of zinc acetate demonstrates an outstanding plateau-region capacity of 253 mAh g^(-1)even at 1 C,among the highest reported values.Consequently,the MEC_(3)||expanded graphite dual-ion battery exhibits an unprecedented cycling stability at high current rate,maintaining 80.6%capacity retention after 10,000 cycles at 10 C,among the best reports.This microdomain engineering strategy provides a new design principle for overcoming kinetic limitations of carbonaceous materials in plateau-dominated sodium storage systems.
文摘Clock synchronization has important applications in multi-agent collaboration(such as drone light shows,intelligent transportation systems,and game AI),group decision-making,and emergency rescue operations.Synchronization method based on pulse-coupled oscillators(PCOs)provides an effective solution for clock synchronization in wireless networks.However,the existing clock synchronization algorithms in multi-agent ad hoc networks are difficult to meet the requirements of high precision and high stability of synchronization clock in group cooperation.Hence,this paper constructs a network model,named DAUNet(unsupervised neural network based on dual attention),to enhance clock synchronization accuracy in multi-agent wireless ad hoc networks.Specifically,we design an unsupervised distributed neural network framework as the backbone,building upon classical PCO-based synchronization methods.This framework resolves issues such as prolonged time synchronization message exchange between nodes,difficulties in centralized node coordination,and challenges in distributed training.Furthermore,we introduce a dual-attention mechanism as the core module of DAUNet.By integrating a Multi-Head Attention module and a Gated Attention module,the model significantly improves information extraction capabilities while reducing computational complexity,effectively mitigating synchronization inaccuracies and instability in multi-agent ad hoc networks.To evaluate the effectiveness of the proposed model,comparative experiments and ablation studies were conducted against classical methods and existing deep learning models.The research results show that,compared with the deep learning networks based on DASA and LSTM,DAUNet can reduce the mean normalized phase difference(NPD)by 1 to 2 orders of magnitude.Compared with the attention models based on additive attention and self-attention mechanisms,the performance of DAUNet has improved by more than ten times.This study demonstrates DAUNet’s potential in advancing multi-agent ad hoc networking technologies.
基金supported by the National Natural Science Foundation of China(32525031,32500896,32571210,and 32171233)the China Postdoctoral Science Foundation(2025M772776 and BX20250148)+2 种基金the Sanqin Talent Special Support Program(2024STD04)the Natural Science Foundation of Shandong Province of China(ZR2025MS1180)the Natural Science Foundation of Shaanxi Province of China(2019JC-07,2021TD-37,2023-ZDLSF-23,and 2024JC-YBMS-146).
文摘Male sexual behaviors,including mounting,intromission,and ejaculation,are not only critical for reproduction but also serve as a model for understanding how the brain orchestrates sequential motor and motivational processes.While previous studies have identified key brain regions involved in sexual behaviors,such as the medial preoptic area(MPOA)and the nucleus accumbens(NAc)[14],the neural mechanisms governing the transitions between different phases of male sexual behavior remain poorly understood.
基金funded by the Science and Technology Projects of State Grid Corporation of China(Project No.J2024136).
文摘To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.
基金supported by the National Key Research and Development Program for Young Scientists,Chin(Grant No.2021YFC2900400)the Sichuan-Chongqing Science and Technology Innovation Cooperation Program Project,China(Grant No.2024TIAD-CYKJCXX0269)the National Natural Science Foundation of China,China(Grant No.52304123).
文摘Lithology identificationwhile drilling technology can obtain rock information in real-time.However,traditional lithology identificationmodels often face limitations in feature extraction and adaptability to complex geological conditions,limiting their accuracy in challenging environments.To address these challenges,a deep learning model for lithology identificationwhile drilling is proposed.The proposed model introduces a dual attention mechanism in the long short-term memory(LSTM)network,effectively enhancing the ability to capture spatial and channel dimension information.Subsequently,the crayfishoptimization algorithm(COA)is applied to optimize the model network structure,thereby enhancing its lithology identificationcapability.Laboratory test results demonstrate that the proposed model achieves 97.15%accuracy on the testing set,significantlyoutperforming the traditional support vector machine(SVM)method(81.77%).Field tests under actual drilling conditions demonstrate an average accuracy of 91.96%for the proposed model,representing a 14.31%improvement over the LSTM model alone.The proposed model demonstrates robust adaptability and generalization ability across diverse operational scenarios.This research offers reliable technical support for lithology identification while drilling.
基金funded by the Natural Science Foundation of Shandong Province(ZR2023MH263)the China Postdoctoral Science Foundation(2023M733918,2023T160729)the Central Government Guidance Foundation for Local Science and Technology Development(YDZX2024133).
文摘Metabolic-associated fatty liver disease(MAFLD)is the most prevalent chronic liver disease globally,with no effective pharmacological treatments available for early-stage cases.Rutin,a bioactive flavonoid from Sophora japonica L.,exhibits diverse pharmacological effects,but its multi-pathway mechanisms in improving MAFLD remain unclear.In this study,we employed a high-fat diet(HFD)-induced MAFLD mouse model to investigate the therapeutic effects of rutin supplementation.Rutin supplementation significantly reduced blood lipid and liver lipid levels and alleviated liver injury in MAFLD model mice.Fecal microbiota transplantation experiments revealed that rutin alleviated MAFLD by modulating the gut microbiota composition.Through 16S rRNA sequencing analysis and non-targeted metabolomics analysis of the normal control(NC),HFD and rutin groups,rutin was found to alter key species(Ruminococcus torques)and associated metabolites(e.g.,7-dehydrocholesterol,short-chain fatty acids),suggesting a mechanism involving the gut microbiota.Antibiotic treatment experiments revealed that rutin alleviates MAFLD via the blood entry pathway.Network pharmacology analysis showed that rutin can directly act on targets closely related to MAFLD development,including tumor protein p53,epidermal growth factor receptor,and prostaglandin-endoperoxide synthase 2,as well as key signaling pathways such as PI3K/AKT and MAPK.Transcriptomics analysis of the NC,HFD and rutin groups revealed that rutin may ameliorate MAFLD through PI3K/AKT and MAPK signaling pathways,which might be enhanced by the gut microbiota and blood entry pathways.In conclusion,rutin can treat MAFLD through both the gut microbiota and blood entry pathways,resulting in a synergistic effect.Our study provides a novel strategy for evaluating functional food components and offers a scientific basis for dietary flavonoid-based interventions against MAFLD.
基金supported by The National Key Research and Development Program of China(Grant No.2021YFA0910100)Healthy Zhejiang One Million People Cohort(Grant No.K-20230085)+6 种基金supported by National Natural Science Foundation of China(Grant Nos.82304946 and 82573745)Post-doctoral Innovative Talent Support Program(Grant No.BX2023375)567 Foundation of Zhejiang Province(Grant No.LMS25H160006)supported by the National Natural Science Foundation of China(Grant No.82473489)the Medical Science and Technology Project of Zhejiang Province(Grant No.WKJ-ZJ-2202)the Natural Science Foundation of Zhejiang Province(Grant No.LBD24H290001)supported by the National Natural Science Foundation of China(Grant No.82403546).
文摘In recent years the crucial role of CD4^(+)T cells in tumor immunomodulation has garnered increasing recognition.While conventional cancer immunotherapy research has predominantly focused on the cytotoxic function of CD8+T cells,emerging evidence has now shown that CD4^(+)T cells enhance antitumor immunity by delivering co-stimulatory signals,secreting cytokines,and promoting cytotoxic T lymphocyte(CTL)activation and display unique immunoregulatory capabilities through direct tumor cell killing or remodeling of the tumor microenvironment.The high heterogeneity and functional plasticity of CD4^(+)T cell subsets significantly influence clinical responses to immunotherapy with underlying mechanisms involving multi-level regulatory networks,including epigenetic modulation and metabolic reprogramming.Deciphering the functional heterogeneity of CD4^(+)T cells and the interactions with the tumor microenvironment will provide essential mechanistic insights for next-generation immunotherapies,such as immune checkpoint inhibitors and chimeric antigen receptor T(CAR-T)therapies,thereby advancing personalized treatment paradigms.
基金supported by NARI Relays Electric Co.,Ltd.under the Project“Research on Evaluation of Clearing Results and Switching Criteria for Primary-Backup Systems in Electricity SpotMarkets”(Project No.CGSQ240800443).
文摘The construction of spot electricity markets plays a pivotal role in power system reforms,where market clearing systems profoundly influence market efficiency and security.Current clearing systems predominantly adopt a single-system architecture,with research focusing primarily on accelerating solution algorithms through techniques such as high-efficiency parallel solvers and staggered decomposition of mixed-integer programming models.Notably absent are systematic studies evaluating the adaptability of primary-backup clearing systems incontingency scenarios—a critical gap given redundant systems’expanding applications in operational environments.This paper proposes a comprehensive evaluation framework for analyzing dual-system adaptability,demonstrated through an in-depth case study of the Inner Mongolia power market.First,we establish the innovative“Dual-Active Heterogeneous”architecture that enables independent parallelized operation and fault-isolated redundancy.Subsequently,key performance indices are quantitatively evaluated across four critical dimensions:unit commitment decisions,generator output constraints,transmission section congestion patterns,and clearing price formation mechanisms.An integrated fuzzy evaluation methodology incorporating grey relational analysis is employed for objective indicator weighting,enabling systematic quantification of system superiority under specific grid operating states.Empirical results based on actual operational data from 200 generation units demonstrate the framework’s efficacy in guiding optimal system selection,with particularly strong performance observed during peak load periods.The proposed approach shows high generalization potential for other regional markets employing redundant clearing mechanisms—particularly those with increasing renewable penetration and associated uncertainty.
基金National Natural Science Foundation of China(12005108)。
文摘In massive multiple-input multiple-output(MIMO)systems utilizing frequency division duplexing,optimizing system performance requires user equipment(UE)to compress downlink channel state information(CSI)and transmit it to the base station(BS).As the number of antennas increases,there is a significant rise in the overhead related to CSI feedback,posing considerable challenges to the precise acquisition of CSI by the BS.Existing approaches to CSI feedback utilizing deep learning techniques face challenges such as significant feedback overhead and limited precision in the reconstruction process.This study presents a novel lightweight CSI feedback framework known as the dual attention neural network(DANet).Within the DANet architecture,a dual attention module(DAM)is designed to enhance the network's performance.This DAM includes both channel attention blocks and spatial attention blocks.The channel attention blocks direct the model's focus toward channel features rich in information content while simultaneously suppressing less significant features.This approach enables the extraction of temporal correlations within the CSI matrix.The spatial attention block aids in extracting the correlation between the delay domain and the angle domain in the CSI matrix.By enhancing neural network performance,the DAM reduces information dispersion while enhancing the representation of global interactions.Simulation results demonstrate that DANet exhibits superior normalized mean square error and cosine similarity with comparable complexity compared to existing advanced CSI feedback methods.
基金supported by the National Natural Science Foundation of China (NSFC,Nos.12474274,92161101)the Innovation Project of Jinan Science and Technology Bureau(No.2021GXRC032)the Natural Science Foundation of Shandong Province (No.ZR2024MA091)。
文摘Traditional strategies for designing hyperhalogens,superatoms with exceptional electron-withdrawing capacity,rely on complex superhalogen assembly,posing significant experimental challenges.Here,we introduce a non-invasive dual external field(DEF) approach combining solvent effects and an oriented external electric field(OEEF) to construct hyperhalogens,as demonstrated by density functional theory(DFT) calculations.Our DEF strategy proves versatile,successfully designing hyperhalogens not only in simplified Ag_n^(-) model systems but also in the experimentally synthesized Ag_(25) nanocluster.Using the 3D Ag_(19)^(-) structure as a model,we further reveal the DEF's pivotal role in O_(2) activation,where solvent-OEEF synergy induces tunable O-O bond elongation and charge transfer,proportional to field strength.Our findings establish a field-driven paradigm for hyperhalogen design that preserves native cluster composition,providing a theoretical foundation for tailoring high-performance catalysts through precise activesite modulation.
基金supported by State Grid Jiangsu Electric Power Co.,Ltd.Technology Project(Research on Planning and Operation Technology of Electric–Hydrogen Coupling System Driven by the Electric–Carbon–Green Certificate Market):J2024005.
文摘Hydrogen,as a zero-carbon secondary energy carrier,provides a unified pathway for low-carbon energy transformation.In electro–hydrogen coupling systems(EHCSs),surplus renewable power is stored via water electrolysis and later reconverted to electricity using fuel cells or gas turbines,enhancing the system’s flexibility and reliability in support of deep decarbonization.This study constructs an electricity–hydrogen energy-recycling model based on a coupling relationship considering the bidirectional conversion between electricity and hydrogen.A multistage carbon-emission-reduction indicator constraint is also established.Additionally,the green-certificate and carbon trading markets are introduced to optimize equipment investment and operation costs while achieving carbon-emission reduction.A case study reveals that the proposed EHCS planning model effectively allocates carbon emissions across different system stages,while mitigating economic repercussions,thus ensuring closer alignment with China’s emission-reduction policies.Incorporating diverse market mechanisms significantly enhances the system’s economy and decision-making flexibility,particularly in addressing future challenges in the energy market.
