Pathological and physiological functional cross-talks ofα-synuclein and tau in the central nervous system

α-Synuclein and tau are abundant multifunctional brain proteins that are mainly expressed in the presynaptic and axonal compartments of neurons,respectively.Previous works have revealed that intracellular deposition ofα-synuclein and/or tau causes many neurodegenerative disorders,including Alzheimer’s disease and Parkinson’s disease.Despite intense investigation,the normal physiological functions and roles ofα-synuclein and tau are still unclear,owing to the fact that mice with knockout of either of these proteins do not present apparent phenotypes.Interestingly,the co-occurrence ofα-synuclein and tau aggregates was found in post-mortem brains with synucleinopathies and tauopathies,some of which share similarities in clinical manifestations.Furthermore,the direct interaction ofα-synuclein with tau is considered to promote the fibrillization of each of the proteins in vitro and in vivo.On the other hand,our recent findings have revealed thatα-synuclein and tau are cooperatively involved in brain development in a stage-dependent manner.These findings indicate strong cross-talk between the two proteins in physiology and pathology.In this review,we provide a summary of the recent findings on the functional roles ofα-synuclein and tau in the physiological conditions and pathogenesis of neurodegenerative diseases.A deep understanding of the interplay betweenα-synuclein and tau in physiological and pathological conditions might provide novel targets for clinical diagnosis and therapeutic strategies to treat neurodegenerative diseases.

Early Triassic Silicic Volcanics of South China:Petrogenesis and Constraints on the Geodynamic Evolution of the Paleo-Tethys Ocean Region

The only occurrence of Lower Triassic silicic volcanic rocks within the South China Block is in the Qinzhou Bay area of Guangxi Province.LA-ICP-MS zircon U-Pb dating reveals that volcanic rocks of the Beisi and Banba formations formed between 248.8±1.6 and 246.5±1.3 Ma,coeval with peraluminous granites of the Qinzhou Bay Granitic Complex.The studied rhyolites and dacites are characterized by high SiO_(2),K_(2)O,and Al_(2)O_(3),and low MgO,CaO,and P_(2)O_(5) contents and are classified as high-K calc-alkaline S-type rocks,with A/CNK=0.98-1.19.The volcanic rocks are depleted in high field strength elements,e.g.,Nb,Ta,Ti,and P,and enriched in large ion lithophile elements,e.g.,Rb,K,Sr,and Ba.Although the analyzed volcanic rocks have extremely enriched zircon Hf isotopic compositions(ε_(Hf)(t)=-29.1 to-6.9),source discrimination indicators and high calculated Ti-in-zircon temperatures(798-835℃)reveal that magma derived from enriched lithospheric mantle not only provided a heat source for anatectic melting of the metasedimentary protoliths but was also an endmember component of the S-type silicic magma.The studied early Triassic volcanics are inferred to have formed immediately before closure of the Paleo-Tethys Ocean in this region,as the associated subduction would have generated an extensional setting in which the mantle-derived upwelling and volcanic activity occurred.

A Blockchain-Based Efficient Cross-Domain Authentication Scheme for Internet of Vehicles

The Internet of Vehicles(IoV)is extensively deployed in outdoor and open environments to effectively address traffic efficiency and safety issues by connecting vehicles to the network.However,due to the open and variable nature of its network topology,vehicles frequently engage in cross-domain interactions.During such processes,directly uploading sensitive information to roadside units for interaction may expose it to malicious tampering or interception by attackers,thus compromising the security of the cross-domain authentication process.Additionally,IoV imposes high real-time requirements,and existing cross-domain authentication schemes for IoV often encounter efficiency issues.To mitigate these challenges,we propose CAIoV,a blockchain-based efficient cross-domain authentication scheme for IoV.This scheme comprehensively integrates technologies such as zero-knowledge proofs,smart contracts,and Merkle hash tree structures.It divides the cross-domain process into anonymous cross-domain authentication and safe cross-domain authentication phases to ensure efficiency while maintaining a balance between efficiency and security.Finally,we evaluate the performance of CAIoV.Experimental results demonstrate that our proposed scheme reduces computational overhead by approximately 20%,communication overhead by around 10%,and storage overhead by nearly 30%.

Effect of Pre-strain on Microstructure and Stamping Performance of High-strength Low-alloy Steel

In this study,pre-strain ranging from 0 to 0.12 was applied through uniaxial tension on high-strength low-alloy(HSLA)specimens with four kinds of grain size.Effect of pre-strain and grain size on me-chanical property was investigated through tensile tests.Microstructures of the pre-strained and tensile tested samples were analyzed,respectively.The 30.8°v-bending and following flattening,as well as Erichson cupping tests,were performed on the pre-strained samples.Results show the elongation ratio of grain and dislocation density increases with pre-strain.Yielding platform is removed when pre-strain is larger than 0.06 while yielding plateau period decreases with pre-strain less than 0.06 due to reduction of pinning effect.The 30.8°v-bending and the following flattening tests are successfully accomplished on all the pre-strained samples with different grain size.Decrease in grain size,along with increase in pre-strain,causes increase in strength and decrease in elongation rate as well as cupping value.Pre-strain causes very slight effect on bending ability,much less than that on mechanical property and cupping test value.Reciprocal impact of the pre-strain and grain size on HSLA steel deformability is inconspicuous.

Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts

Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems.

MOF-derived porous graphitic carbon with optimized plateau capacity and rate capability for high performance lithium-ion capacitors

The development of anode materials with high rate capability and long charge-discharge plateau is the key to improve per-formance of lithium-ion capacitors(LICs).Herein,the porous graphitic carbon(PGC-1300)derived from a new triply interpenetrated co-balt metal-organic framework(Co-MOF)was prepared through the facile and robust carbonization at 1300°C and washing by HCl solu-tion.The as-prepared PGC-1300 featured an optimized graphitization degree and porous framework,which not only contributes to high plateau capacity(105.0 mAh·g^(−1)below 0.2 V at 0.05 A·g^(−1)),but also supplies more convenient pathways for ions and increases the rate capability(128.5 mAh·g^(−1)at 3.2 A·g^(−1)).According to the kinetics analyses,it can be found that diffusion regulated surface induced capa-citive process and Li-ions intercalation process are coexisted for lithium-ion storage.Additionally,LIC PGC-1300//AC constructed with pre-lithiated PGC-1300 anode and activated carbon(AC)cathode exhibited an increased energy density of 102.8 Wh·kg^(−1),a power dens-ity of 6017.1 W·kg^(−1),together with the excellent cyclic stability(91.6%retention after 10000 cycles at 1.0 A·g^(−1)).

Research on Operation Optimization of Energy Storage Power Station and Integrated Energy Microgrid Alliance Based on Stackelberg Game

With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through the deployment of energy storage.To solve the problem of the interests of different subjects in the operation of the energy storage power stations(ESS)and the integrated energy multi-microgrid alliance(IEMA),this paper proposes the optimization operation method of the energy storage power station and the IEMA based on the Stackelberg game.In the upper layer,ESS optimizes charging and discharging decisions through a dynamic pricing mechanism.In the lower layer,IEMA optimizes the output of various energy conversion coupled devices within the IEMA,as well as energy interaction and demand response(DR),based on the energy interaction prices provided by ESS.The results demonstrate that the optimization strategy proposed in this paper not only effectively balances the benefits of the IEMA and ESS but also enhances energy consumption rates and reduces IEMA energy costs.

RRT Autonomous Detection Algorithm Based on Multiple Pilot Point Bias Strategy and Karto SLAM Algorithm

A Rapid-exploration Random Tree(RRT)autonomous detection algorithm based on the multi-guide-node deflection strategy and Karto Simultaneous Localization and Mapping(SLAM)algorithm was proposed to solve the problems of low efficiency of detecting frontier boundary points and drift distortion in the process of map building in the traditional RRT algorithm in the autonomous detection strategy of mobile robot.Firstly,an RRT global frontier boundary point detection algorithm based on the multi-guide-node deflection strategy was put forward,which introduces the reference value of guide nodes’deflection probability into the random sampling function so that the global search tree can detect frontier boundary points towards the guide nodes according to random probability.After that,a new autonomous detection algorithm for mobile robots was proposed by combining the graph optimization-based Karto SLAM algorithm with the previously improved RRT algorithm.The algorithm simulation platform based on the Gazebo platform was built.The simulation results show that compared with the traditional RRT algorithm,the proposed RRT autonomous detection algorithm can effectively reduce the time of autonomous detection,plan the length of detection trajectory under the condition of high average detection coverage,and complete the task of autonomous detection mapping more efficiently.Finally,with the help of the ROS-based mobile robot experimental platform,the performance of the proposed algorithm was verified in the real environment of different obstacles.The experimental results show that in the actual environment of simple and complex obstacles,the proposed RRT autonomous detection algorithm was superior to the traditional RRT autonomous detection algorithm in the time of detection,length of detection trajectory,and average coverage,thus improving the efficiency and accuracy of autonomous detection.

Ca_(2)MnO_(4)-layered perovskite modified by NaNO_(3)for chemical-looping oxidative dehydrogenation of ethane to ethylene

Chemical-looping oxidative dehydrogenation(CL-ODH)is a process designed for the conversion of alkanes into olefins through cyclic redox reactions,eliminating the need for gaseous O_(2).In this work,we investigated the use of Ca_(2)MnO_(4)-layered perovskites modified with NaNO_(3) dopants,serving as redox catalysts(also known as oxygen carriers),for the CL-ODH of ethane within a temperature range of 700-780℃.Our findings revealed that the incorporation of NaNO_(3) as a modifier significantly-nhanced the selectivity for-thylene generation from Ca_(2)MnO_(4).At 750℃and a gas hourly space velocity of 1300 h^(-1),we achieved an-thane conversion up to 68.17%,accompanied by a corresponding-thylene yield of 57.39%.X-ray photoelectron spectroscopy analysis unveiled that the doping NaNO_(3) onto Ca_(2)MnO_(4) not only played a role in reducing the oxidation state of Mn ions but also increased the lattice oxygen content of the redox catalyst.Furthermore,formation of NaNO_(3) shell on the surface of Ca_(2)MnO_(4) led to a reduction in the concentration of manganese sites and modulated the oxygen-releasing behavior in a step-wise manner.This modulation contributed significantly to the enhanced selectivity for ethylene of the NaNO_(3)-doped Ca_(2)MnO_(4) catalyst.These findings provide compelling evidence for the potential of Ca_(2)MnO_(4)-layered perovskites as promising redox catalysts in the context of CL-ODH reactions.

案例教学法结合虚拟仿真技术在助产实验课程中的应用效果研究

目的探讨案例教学法结合虚拟仿真技术在助产实验课程中的应用效果。 方法采用类实验研究设计,于2020年9月至2022年1月,从桂林医学院护理学院助产专业选取2018级和2019级两个班级共135名学生为研究对象,2019级为干预组(n=59),2018级为对照组(n=76)。干预组在传统实验教学的基础上,采用案例教学法结合虚拟仿真技术,课程包括正常分娩(6学时)异常分娩(6学时)脐带脱垂(2学时)、新生儿窒息与复苏(4学时)4部分内容;对照组学生采用传统实验教学。采用课程成绩、自主学习能力问卷、教学满意度问卷进行调查,比较两组学生的教学效果。结果课程结束后,干预组学生的个人操作能力(90.88±2. 14比89.24土3.15),团队操作能力(90.97±2.33比81.28±5.45)和案例分析能力(88.64±3.19比86.70±2.56)均高于对照组(P<0.01)。课程干预前,两组学生自主学习能力得分比较,差异无统计学意义;课程实施后,干预组学生自主学习能力得分(94.78±6.59比88.12±8.36)及各维度得分均高于对照组(P<0.05)。超过94%的干预组学生认为案例教学法结合虚拟仿真技术有效提高了他们自主学习热情、独立思考、团队协作及沟通等综合能力。结论在助产实验课程中应用案例教学法结合虚拟仿真技术,可有效提高学生课程成绩、自主学习能力及综合能力,并得到学生的认可。

Editorial for the special issue“Hydrogen Energy Production,Storage and Utilization”

Hydrogen energy has emerged as a significant energy source for accomplishing energy transformation and achieving carbon neutrality.Hydrogen production,storage and transportation are the key technologies to realize hydrogen energy application and carbon neutralization goal.Apart from the mature technologies of fossil fuel reforming and water electrolysis,new hydrogen production methods(such as solar photolysis,biomass conversion,thermochemical circulation,etc.)have garnered widespread attention and research interest.The lack of safe and efficient hydrogen storage and utilization technology for hydrogen fuel cell systems is the major obstacle to achieving hydrogen economy.In the past decades,global researchers have conducted extensive studies on enhancing the hydrogen storage performance of materials,such as alloy,metal hydride,complex hydride,carbon-based materials,etc.,as well as the technological development of fuel cell power generation systems using solid hydrogen storage materials as hydrogen storage carriers.The themed issue entitled“Hydrogen Energy Production,Storage and Utilization”includes 10 carefully selected papers that address the most recent developments in hydrogen production and storage materials,involving catalyst design,structure characterization,hydrogen ab-/desorption performance and mechanism,and fuel cell coupling system exploit.

Alkali Tolerance of Concrete Internal Curing Agent Based on Sodium Carboxymethyl Starch

Internal curing agents (ICA) based on super absorbent polymer have poor alkali tolerance and reduce the early strength of concrete.An alkali tolerate internal curing agent (CAA-ICA) was designed and prepared by using sodium carboxymethyl starch (CMS) with high hydrophilicity,acrylic acid (AA) containing anionic carboxylic group and acrylamide (AM) containing non-ionic amide group as the main raw materials.The results show that the ratio of CAA-ICA alkali absorption solution is higher than that existing ICA,which solves the low water absorption ratio of the ICA in alkali environment.The water absorption ratio of CAA-ICA in saturated Ca(OH)_(2) solution is 95.8 g·g^(-1),and the alkali tolerance coefficient is 3.4.The application of CAA-ICA in cement-based materials can increase the internal relative humidity and miniaturize the pore structure.The compressive strength of mortar increases up to 12.95%at 28 d,which provids a solution to overcome the reduction of the early strength.

Regulating Effect of Substrate Temperature on Sputteringgrown Ge/Si QDs under Low Ge Deposition

The effect of deposition temperature on the morphology and optoelectronic performance of Ge/Si QDs grown by magnetron sputtering under low Ge deposition(~4 nm)was investigated by atomic force microscopy,Raman spectroscopy,and photoluminescence(PL)tests.The experimental results indicate that temperatures higher than 750℃effectively increase the crystallization rate and surface smoothness of the Si buffer layer,and temperatures higher than 600℃significantly enhance the migration ability of Ge atoms,thus increasing the probability of Ge atoms meeting and nucleating to form QDs on Si buffer layer,but an excessively high temperature will cause the QDs to undergo an Ostwald ripening process and thus develop into super large islands.In addition,some PL peaks were observed in samples containing small-sized,high-density Ge QDs,the photoelectric properties reflected by these peaks were in good agreement with the corresponding structural characteristics of the grown QDs.Our results demonstrate the viability of preparing high-quality QDs by magnetron sputtering at high deposition rate,and the temperature effect is expected to work in conjunction with other controllable factors to further regulate QD growth,which paves an effective way for the industrial production of QDs that can be used in future devices.

Fuzzy C-Means Algorithm Based on Density Canopy andManifold Learning

Fuzzy C-Means(FCM)is an effective and widely used clustering algorithm,but there are still some problems.considering the number of clusters must be determined manually,the local optimal solutions is easily influenced by the random selection of initial cluster centers,and the performance of Euclid distance in complex high-dimensional data is poor.To solve the above problems,the improved FCM clustering algorithm based on density Canopy and Manifold learning(DM-FCM)is proposed.First,a density Canopy algorithm based on improved local density is proposed to automatically deter-mine the number of clusters and initial cluster centers,which improves the self-adaptability and stability of the algorithm.Then,considering that high-dimensional data often present a nonlinear structure,the manifold learning method is applied to construct a manifold spatial structure,which preserves the global geometric properties of complex high-dimensional data and improves the clustering effect of the algorithm on complex high-dimensional datasets.Fowlkes-Mallows Index(FMI),the weighted average of homogeneity and completeness(V-measure),Adjusted Mutual Information(AMI),and Adjusted Rand Index(ARI)are used as performance measures of clustering algorithms.The experimental results show that the manifold learning method is the superior distance measure,and the algorithm improves the clustering accuracy and performs superiorly in the clustering of low-dimensional and complex high-dimensional data.

Two-Way Neural Network Performance PredictionModel Based onKnowledge Evolution and Individual Similarity

Predicting students’academic achievements is an essential issue in education,which can benefit many stakeholders,for instance,students,teachers,managers,etc.Compared with online courses such asMOOCs,students’academicrelateddata in the face-to-face physical teaching environment is usually sparsity,and the sample size is relativelysmall.It makes building models to predict students’performance accurately in such an environment even morechallenging.This paper proposes a Two-WayNeuralNetwork(TWNN)model based on the bidirectional recurrentneural network and graph neural network to predict students’next semester’s course performance using only theirprevious course achievements.Extensive experiments on a real dataset show that our model performs better thanthe baselines in many indicators.

Deformation monitoring of long-span railway bridges based on SBAS-InSAR technology

The deformation monitoring of long-span railway bridges is significant to ensure the safety of human life and property.The interferometric synthetic aperture radar(In SAR)technology has the advantage of high accuracy in bridge deformation monitoring.This study monitored the deformation of the Ganjiang Super Bridge based on the small baseline subsets(SBAS)In SAR technology and Sentinel-1A data.We analyzed the deformation results combined with bridge structure,temperature,and riverbed sediment scouring.The results are as follows:(1)The Ganjiang Super Bridge area is stable overall,with deformation rates ranging from-15.6 mm/yr to 10.7 mm/yr(2)The settlement of the Ganjiang Super Bridge deck gradually increases from the bridge tower toward the main span,which conforms to the typical deformation pattern of a cable-stayed bridge.(3)The sediment scouring from the riverbed cause the serious settlement on the bridge’s east side compared with that on the west side.(4)The bridge deformation negatively correlates with temperature,with a faster settlement at a higher temperature and a slow rebound trend at a lower temperature.The study findings can provide scientific data support for the health monitoring of long-span railway bridges.

Experiment on inducing apoptosis of melanoma cells by micro-plasma jet

As a promising cancer treatment method,cold atmospheric plasma has received widespread attention in recent years.However,previous research has focused more on how to realize and expand the anti-cancer scope of plasma jet.There are also studies on the killing of small-scale cancer cells,but the effects of plasma jet on normal cells and normal cell clusters have been ignored.Therefore,we proposed a 50μm sized micro-plasma jet device,and used the device to treat melanoma cells(A-375)and human glial cells(HA1800)to evaluate their anti-cancer effects and effects on normal cells.The experimental results show that this kind of micro-plasma jet device can effectively inactivate cancer cells in a short period of time,while having little effect on normal cells.This work provides a certain experimental basis for the application offine plasma jet to clinically inactivate cancer cells.

Comprehensive analysis of the protein phosphatase 2A regulatory subunit B56ε in pan-cancer and its role and mechanism in hepatocellular carcinoma

BACKGROUND B56εis a regulatory subunit of the serine/threonine protein phosphatase 2A,which is abnormally expressed in tumors and regulates various tumor cell functions.At present,the application of B56εin pan-cancer lacks a comprehensive analysis,and its role and mechanism in hepatocellular carcinoma(HCC)are still unclear.The Cancer Genome Atlas,Genotype-Tissue Expression,Gene Expression Profiling Interactive Analysis,and Tumor Immune Estimation Resource databases were used to analyze B56εexpression,prognostic mutations,somatic copy number alterations,and tumor immune characteristics in 33 tumors.The relationships between B56εexpression levels and drug sensitivity,immuno-therapy,immune checkpoints,and human leukocyte antigen(HLA)-related genes were further analyzed.Gene Set Enrichment Analysis(GSEA)was performed to reveal the role of B56εin HCC.The Cell Counting Kit-8,plate cloning,wound healing,and transwell assays were conducted to assess the effects of B56εinterference on the malignant behavior of HCC cells.RESULTS In most tumors,B56εexpression was upregulated,and high B56εexpression was a risk factor for adrenocortical cancer,HCC,pancreatic adenocarcinoma,and pheochromocytoma and paraganglioma(all P<0.05).B56εexpression levels were correlated with a variety of immune cells,such as T helper 17 cells,B cells,and macro-phages.There was a positive correlation between B56εexpression levels with immune checkpoint genes and HLA-related genes(all P<0.05).The expression of B56εwas negatively correlated with the sensitivity of most chemotherapy drugs,but a small number showed a positive correlation(all P<0.05).GSEA analysis showed that B56εexpression was related to the cancer pathway,p53 downstream pathway,and interleukin-mediated signaling in HCC.Knockdown of B56εexpression in HCC cells inhibited the proliferation,migration,and invasion capacity of tumor cells.Core Tip:The expression of protein phosphatase 2A(PP2A)subunit B56εis up-regulated in most tumors,and its high expression is a risk factor for adrenocortical cancer,hepatocellular carcinoma(HCC),pancreatic adenocarcinoma,and pheochromocytoma and paraganglioma.B56εexpression levels correlate with immune cells,immune checkpoint genes,human leukocyte antigen-related genes,and the sensitivity of chemotherapy drugs.In HCC,B56εexpression is related to the cancer pathway.Knockdown of B56εexpression in HCC cells can inhibit the proliferation,migration and invasion capacity of tumor cells.Our study supports PP2A subunit B56εas a prognostic marker and potential therapeutic target for HCC.

Intrinsic correlation between the generalized phase equilibrium condition and mechanical behaviors in hydrate-bearing sediments

The phase equilibrium and mechanical behaviors of natural gas hydrate-bearing sediment are essential for gas recovery from hydrate reservoirs.In heating closed systems,the temperature-pressure path of hydrate-bearing sediment deviates from that of pure bulk hydrate,reflecting the porous media effect in phase equilibrium.A generalized phase equilibrium equation was established for hydrate-bearing sediments,which indicates that both capillary and osmotic pressures cause the phase equilibrium curve to shift leftward on the temperature-pressure plane.In contrast to bulk hydrate,hydrate-bearing sediment always contains a certain amount of unhydrated water,which keeps phase equilibrium with the hydrate within the hydrate stability field.With changes in temperature and pressure,a portion of pore hydrate and unhydrated water may transform into each other,affecting the shear strength of hydrate-bearing sediment.A shear strength model is proposed to consider not only hydrate saturation but also the change in temperature and pressure of hydrate-bearing sediment.The model is validated by experimental data with various hydrate saturation,temperature and pressure conditions.The deformation induced by partial dissociation was studied through depressurization tests under constant effective stress.The reduction in gas pressure within the hydrate stability field indeed caused sediment deformation.The dissociation-induced deformation can be reasonably estimated as the difference in volume between hydrate-bearing and hydrate-free sediments from the compression curves.

Flexible planar micro supercapacitor diode

Supercapacitor diode is a novel ion device that performs both supercapacitor energy storage and ion diode rectification functions.However,previously reported devices are limited by their large size and complex processes.In this work,we demonstrate a screen-printed micro supercapacitor diode(MCAPode)that based on the insertion of a finger mode with spinel ZnCo_(2)O_(4) as cathode and activated carbon as anode for the first time,and featuring an excellent area specific capacitance(1.21 mF cm^(-2)at 10 mV s^(-1))and high rectification characteristics(rectification ratioⅠof 11.99 at 40 mV s^(-1)).Taking advantage of the ionic gel electrolyte,which provides excellent stability during repeated flexing and at high temperatures.In addition,MCAPode exhibits excellent electrochemical performance and rectification capability in"AND"and"OR"logic gates.These findings provide practical solutions for future expansion of micro supercapacitor diode applications.