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Data heterogeneity, insufficient scalability, and data privacy protection are the technological challenges of personalized recommendations. This study proposes a new federated learning algorithm (FedSarah) to address low scalability caused by data heterogeneity and uneven computing power in consumer-centric personalized recommendation systems while protecting data privacy of consumers. The algorithm updates the stochastic gradient estimates using a recursive framework on consumer clients. The outer loop calculates the entire gradient for updating global model, and the inner loop calculates the stochastic gradient based on the accumulated stochastic information for updating local models. To increase the stability of convergence, the inner loop modifies intrinsic parameters to change the number of training rounds and the direction of model update on consumer clients. The detailed mathematical analysis and experiments demonstrate that FedSarah has good convergence. In addition, it’s shown that the algorithm can achieve a performance improvement of nearly 5% in terms of accuracy compared to the traditional FedAvg and FedProx algorithms under the condition of heterogeneous data. Furthermore, under the condition of effective privacy protection on consumers’ data, the new algorithm can significantly lessen the impact of data heterogeneity on the real-time service of consumer-centric personalized recommendation systems with low communication latency. The code is available at https://github.com/DashingJ-82/FedSarah.git.

The development of an ultralow-Pt catalyst layer (CL) without sacrificing proton-exchange membrane (PEM) fuel cell performance and durability is urgently needed to boost fuel cell commercialization. Besides material development, advanced CL microstructure design is required to ensure optimal multi-physics transfer and enhanced electrochemical surface area (ECSA). However, this is largely hindered by current poor understanding of the complex “gas-liquid-heat-electron-proton” transfers, in conjunction with the electrochemical reactions, and is also greatly influenced by the temporal CL microstructure evolution during long-term operation. Herein, we present several important research and development directions after critically examining the multi-physics transfer in fresh CLs and the microstructure evolution of degraded CLs. This knowledge is essential to designing and fabricating ultralow-Pt CLs for next-generation cost-effective, high-performance, and durable PEM fuel cells and to meet the urgent need for development of new research tools, including pore- and cell-scale models, experimental methods, machine learning algorithms, and their rational combinations.

Three-dimensional printing is a revolutionary strategy to fabricate dental implants. Especially, 3D-printed dental implants modified with nanoscaled titanium oxide layer (H-SLM) have impressively shown quick osseointegration, but the accurate mechanism remains elusive. Herein, we unmask a domino effect that the hydrophilic surface of the H-SLM facilitates blood wetting, enhances the blood shear rate, promotes blood clotting, and changes clot features for quick osseointegration. Combining computational fluid dynamic simulation and biological verification, we find a blood shear rate during blood wetting of the hydrophilic H-SLM 1.2-fold higher than that of the raw 3D-printed implant, which activates blood clot formation. Blood clots formed on the hydrophilic H-SLM demonstrate anti-inflammatory and pro-osteogenesis effects, leading to a 1.5-fold higher bone-to-implant contact and a 1.8-fold higher mechanical anchorage at the early stage of osseointegration. This mechanism deepens current knowledge between osseointegration speed and implant surface characteristics, which is instructive in surface nanoscaled modification of multiple 3D-printed intrabony implants.

The increasing popularity of 6G communication within the Internet of Vehicles (IoV) ecosystem is expected to induce a surge in both user numbers and data volumes. This expansion will cause substantial challenges in ensuring network security and privacy protection, as well as in addressing the associated issue of inadequate cloud computing resources. In this article, we propose a Quantum Efficient Privacy Protection (QEPP) protocol that leverages reversible information hiding in quantum point clouds. This protocol utilizes quantum communication technology in edge-to-cloud communication of the IoV to transmit sensitive information embedded in quantum state data, thereby ensuring privacy protection. It employs quantum error-correction coding and efficient coding techniques to extract information and recover the carriers. In addition, the protocol utilizes an improved quantum Grover algorithm in the cloud to accelerate the processing speed of quantum data. By addressing security vulnerabilities and improving cloud-computing capabilities, the QEPP can effectively accommodate critical requirements, including precision, timeliness, and robust privacy protection.

Electrocardiogram (ECG) is the main criterion for arrhythmia detection. As a means of identification, ECG leakage seems to be a common occurrence due to the development of the Internet of Medical Things. The advent of the quantum era makes it difficult for classical blockchain technology to provide security for ECG data storage. Therefore, from the perspective of safety and practicality, this article proposes a quantum arrhythmia detection system called QADS, which achieves secure storage and sharing of ECG data based on quantum blockchain technology. Furthermore, a quantum neural network is used in QADS to recognize abnormal ECG data, which contributes to further cardiovascular disease diagnosis. Each quantum block stores the hash of the current and previous block to construct a quantum block network. The new quantum blockchain algorithm introduces a controlled quantum walk hash function and a quantum authentication protocol to guarantee legitimacy and security while creating new blocks. In addition, this article constructs a hybrid quantum convolutional neural network called HQCNN to extract the temporal features of ECG to detect abnormal heartbeats. The simulation experimental results show that HQCNN achieves an average training and testing accuracy of 94.7% and 93.6%. And the detection stability is much higher than classical CNN with the same structure. HQCNN also has certain robustness under the perturbation of quantum noise. Besides, this article demonstrates through mathematical analysis that the proposed quantum blockchain algorithm has strong security and can effectively resist various quantum attacks, such as external attacks, Entanglement-Measure attack and Interception-Measurement-Repeat attack.

Traffic congestion prediction (TCP) plays a vital role in intelligent transportation systems due to its importance of traffic management. Methods for TCP have emerged greatly with the development of machine learning. However, TCP is always a challenging work due to the dynamic characteristics of traffic data and the complex structure of traffic network. This paper presents a new quantum algorithm that can capture temporal and spatial features of traffic data simultaneously for TCP. The algorithm consists of the following steps. First, we give a closed-form solution in the Schrödinger approach theoretically to analyze this TCP problem in time dimension. Then we can get the temporal features from the solution. At last, we construct a quantum graph convolutional network and apply temporal features into it. Thus, the temporal-spatial quantum graph convolutional neural network is proposed. The feasibility of this method is proved through experiments on the simulation platform. The experimental results show the average error rate is 0.21 and can resist perturbation effectively.

•Mass diffusion and viscous flow processes are simulated via pore-scale lattice Boltzmann methods.•Apparent permeability and diffusivity are predicted in single nanopores and nanoporous media.•A dimensional diffusion-flow ratio is proposed to evaluate the dominant transport mechanism.•Dominant transport mechanism is elucidated in single nanopores and nanoporous media.

Ionic thermoregulated osmotic energy conversion in nanochannels synergistically utilizes osmotic and thermal energy for power generation based on ionic selective transport in charged nano-membranes under salinity gradients and thermal regulations. Currently, no explicit general dimensionless formulas exist that reflect the relationship between impact factors and performance to guide performance designs. In this study, data-driven insight is presented to establish a framework for obtaining explicit and general relational expressions based on data augmentation using the similarity principle and deep learning. The original database is derived from a finite element simulation with 10,000 dimensional samples, then augmented to 30,000 dimensional samples via similarity principle-based data augmentation. Subsequently, a deep neural network model with decay algorithms is employed to expand the database to new 300,000 dimensional samples with a prediction accuracy exceeding 98 %, which are further converted to dimensionless forms for multiple linear regression. Three dimensionless and explicit formulas for the electrical potential, output power, and energy conversion efficiency are obtained, which indicate determination coefficients of 0.91, 0.93, and 0.92, respectively. Furthermore, considering actual experimental and application situations, the modified dimensionless formula of the output power predicts the experimental results with an average error of 7.80 %. This study efficiently alleviates experimental burden and facilitates engineering applications.

As a computing service platform closer to users, fog computing has many advantages such as extremely low latency, good mobility, accurate location perception and wide distribution. It has developed rapidly in recent years. However, due to the wide distribution of fog nodes, complex network environments, and limited resources, the security of fog nodes is vulnerable to a variety of attacks, such as denial of service and abuse of resources. In order to effectively deal with these attacks, this paper proposes a quantum fog computing model based on blind quantum computation and verifiable quantum secret sharing. The model mainly relies on blind quantum computation to realize the security joint operation characteristics of multiple fog nodes, and the identity verifiable and channel detection protection features provided by the quantum secret sharing protocol, which can not only efficiently perform the functions of the classic fog computing, but also guarantee the security of information transmission and data calculation. Through the complete security analysis, the new quantum fog computing model proposed in this paper can effectively resist on a variety of fog computing attacks, thus achieving information security protection in both the content and process of fog computing.

In order to study the effect of different high heat input on the microstructure and properties of coarse-grained heat-affected zone (CGHAZ) of 500 MPa high-strength low-alloy steel, the welding thermal simulation experiments under different welding heat input conditions were carried out. The results show that as the heat input increases from 50 kJ·cm−1to 400 kJ·cm−1, the acicular ferrite (AF) appeared to increase firstly and then gradually decreased. However, the grain boundary ferrite (GBF) and the granular bainite (GB) gradually decreased. The impact toughness of CGHAZ with 100 kJ·cm−1showed the highest value, about 154 J, and the microhardness decreased slightly with the increase in heat input. The fracture mechanism changed from ductile fracture to cleavage fracture. Under the condition of 100 kJ·cm−1heat input, the Mn–S–Al–Ti–Ca–O complex inclusions formed in the matrix can effectively induce the nucleation of AF in the CGHAZ, and the secondary AF can be induced by the primary AF sympathetically, thus improving the welding impact toughness.

Thermal management of H2gas storage in a tank is crucial for determining the H2gas deliverable capacity. In this study, a strategy for the design of an excellent comprehensive performance fuel storage tank from the screening of microscopic materials to the design of macroscopic particle adsorption tank performance is proposed. The best metal–organic framework (MOF) for H2deliverable capacity in a computation-ready experimental MOF database is first screened using a grand canonical Monte Carlo (GCMC) method. An upscale model that combines the finite volume method with GCMC is then established to investigate the H2charging and discharging processes in a screened best MOF-filled adsorption particle tank that is integrated with a phase-change material (PCM) jacket. The process of the heat and mass transfer in the screened best MOF particle adsorption tank with and without the PCM jacket-inserted metal foam is studied. The results show that the prescreened XAWVUN has the highest gravimetric and considerable volumetric deliverable capacity among 503 MOFs, which can reach up to 23.1 mol·kg–1and 20.8 kg·m–3at 298 K and pressures between 35 000 kPa (adsorption pressure) and 160 kPa (desorption pressure), respectively. The H2deliverable capacity can be maximized by 3.2 and 12.1% for PCM jackets inserted with metal foam in the H2charging and discharging processes when it is compared with the case without the PCM jacket, respectively. The above study will facilitate the development of new equipment for hydrogen storage.

•A STSF configuration is proposed as the cathode flow field of AC-PEMFC.•A 3D multiphase model is applied and validated against the experiment.•The STSF improves the water content by reducing the internal temperature.•A superior output voltage and mass-specific power density are achieved.

Water slip at solid surfaces is important for a wide range of micro-/nanofluidic applications. While it is known that water slip behavior depends on surface functionalization, how it impacts the molecular level dynamics and mass transport at the interface is still not thoroughly understood. In this paper, we use nonequilibrium molecular dynamics simulations to investigate the slip behavior of water confined between gold surfaces functionalized by self-assembled monolayer (SAM) molecules with different polar functional groups. We observe a positive-to-negative slip transition from hydrophobic to hydrophilic SAM functionalizations, which is found to be related to the stronger interfacial interaction between water molecules and more hydrophilic SAM molecules. The stronger interaction increases the surface friction and local viscosity, making water slip more difficult. More hydrophilic functionalization also slows down the interfacial water relaxation and leads to more pronounced water trapping inside the SAM layer, both of which impede water slip. The results from this work will provide useful insights into the understanding of the water slip at functionalized surfaces and design guidelines for various applications.

The integration of electrode compression in a vanadium redox flow battery (VRFB) with optimized operating conditions is essential for achieving the maximum net discharge power. This study presents the development of a 3D steady-state model for VRFB aimed at maximizing net discharge power (Pnet) by optimizing key working conditions, including electrode compression ratio (CR), applied current density (Iapp), and electrolyte inflow rate (Qin). The comprehensive impacts of CR, Iapp, and Qinon VRFB charging and discharging curves, energy efficiency (EE), and system efficiency (SE), and Pnetwere investigated. Subsequently, the optimization of CRand Qinunder a fixed applied current density range of 20–400 mA/cm2was carried out employing a hybrid methodology integrating artificial neural network (ANN) and genetic algorithms (GA). Results reveals that increasing CRdoes not linearly improve system efficiency and net discharge power, with an optimal CRidentified to maximize net discharge power. The optimal CRvaries with operating conditions and is influenced by factors such as Qinand Iapp. Notably, both CRand Qinnegatively impact net discharge power due to increased pump losses, while Iappand state of charge (SOC) positively affect net discharge power through enhanced electron transfer and higher active substance concentration, respectively. The optimal CRis identified around 65 % for Iappexceeding 60 mA/cm2. Furthermore, the optimal Qincorrelates directly with increasing Iapp, as higher Iapprates necessitate greater Qinto sustain active species supply. This study offers an optimization approach for addressing coupled operating conditions and provides insights for achieving high net discharge power in VRFB operation.

Gas diffusion in nanoporous media is significantly different from its bulk counterpart owing to the nanoconfinement effect. In this study, a local effective diffusivity lattice Boltzmann model (LED-LBM) is proposed to explore the gas diffusion behavior under nanoconfinement. The nanoconfinement effect is incorporated into the local effective diffusivity via a spatial position-dependent mean free path. The proposed LED-LBM is validated against molecular dynamics simulation results for methane gas diffusion in a nanoscale channel. Using this model, the spatial variations in the local effective diffusivity and gas mass flux in 3D nanoporous media are visualized, and the predominant factors influencing their variation and gas diffusivity are disclosed. The results show that the spatial variation features of the local effective diffusivity and gas mass flux are strongly influenced by the pore shape and average Knudsen number. The gas diffusivity in nanoporous media is significantly lower than its bulk counterpart owing to the nanoconfinement effect, and their differences increase with the average Knudsen number. To quantify the magnitude of the nanoconfinement effect, a new concept, namely, the confinement scope, is further defined. Finally, a semiempirical formula is established to predict the gas diffusivity in nanoconfined porous media, which is expressed as a function of the bulk diffusivity, average Knudsen number, and porosity.

Abstract: Interest in large-scale energy storage technologies has risen in recent decades with the rapid development of renewable energy. The redox flow battery satisfies the energy storage demands well owing to its advantages of scalability, flexibility, high round-trip efficiency, and long durability. As a critical component of the redox flow battery, the bipolar plates provide mechanical support for the electrodes and act as a physical separator between adjacent cells, as well as constructing the internal circuit and guiding the electrolyte flow. The present work offers a comprehensive review of the development of bipolar plates in redox flow batteries, covering materials, structures, and manufacturing methods. In terms of materials, the effects of material types and composition on the compactness, mechanical strength, and electrical conductivity are summarized in detail. Furthermore, the corrosion mechanisms of bipolar plates and the corresponding detection and mitigation methods are discussed. In addition, the structures of the bipolar plates refer to the flow field designs on the surface. The advantages and disadvantages of these existing flow fields are described, and the tendencies for further optimization are also discussed. The manufacturing of composite bipolar plates in terms of material cost and preparation methods is also outlined. Based on the summary of previous research, this work provides suggestions for the future development of high-performance bipolar plates. Graphical Abstract:

With the development of quantum network, quantum continuous-variables have practical significance of improving communication. This paper proposes a new continuous-variable quantum network coding protocol (CVQNC) based on the butterfly network model with the hybrid channel of quantum channel and classical channel to realise the cross transmission of quantum information and classical information. The new protocol not only is conducive to the realisation of quantum network, but also can reduce the communication cost of quantum network effectively. It can be seen from the throughput and fidelity analysis that this protocol has a higher throughput than discrete-variable quantum network encoding scheme and classical information network encoding scheme. The ceiling of fidelity in this protocol is 4/9. According to the analysis of simple intercept attack and spectroscope attack, it is secure for the protocol to transmit quantum information and classical information by resisting on the eavesdropping attack of the third-party effectively.

Liquid hydrogen (LH2) holds great potential in both aerospace and civil markets due to its high energy density. However, on account of the low boiling point and latent heat of vaporization of LH2, the high performance insulation storage system is the key to its efficient storage. One of the most efficient insulation methods for a LH2storage system is considered to be Variable Density Multilayer Insulation (VDMLI) coupled with Vapor-Cooled Shield (VCS). This study establishes a quasi-two-dimensional (quasi-2D) thermodynamic model of liquid hydrogen storage system with VDMLI and VCS. The quasi-2D model incorporates the temperature gradient of VCS and its impact on VDMLI. The model can reveal the two-dimensional temperature and heat distribution in insulation systems, predict heat leakage and evaporation rate, and can be utilized for optimizing the design of the VCS structure. Using a NASA's tank as an example, the analysis conducted with the model indicates that the presence of VCS reduces the average temperature gradient of the inner VDMLI. The upper half of the tank exhibits a significantly smaller temperature gradient compared to the lower half, resulting in lower heat leakage. This effect becomes more pronounced as the VCS moves outward of the tank. Additionally, the VCS absorbs more heat in the inlet section than that in the outlet section, and this disparity becomes increasingly significant as the VCS moves outward of the tank. The model can also be employed to optimize the position of the VCS, resulting in a 69.73 % reduction in daily evaporation rate compared to NASA's original design. Lastly, a graphical method for the quick design of VCS structure is proposed which is based on calculated data for daily evaporation rate and apparent thermal conductivity. This method enables the retrieval of the corresponding apparent thermal conductivity based on the desired evaporation rate, facilitates the rapid determination of the range of VCS position, and allows for the quick prediction of the evaporation rate based on the VCS position. In conclusion, this research presents a new approach for the performance analysis and optimization design of liquid hydrogen storage system with VDMLI and VCS.

Quantum cloud computing facilitates the rapid processing of vast amounts of data and provides robust network services. To enhance the efficiency and security of data transmission in cloud computing, this study proposes a quantum cloud office model and presents a novel quantum dialogue protocol particularly designed for this model. The proposed protocol enables authenticated communication among office correspondents. Leveraging the unique properties of multiple quantum degrees of freedom, this protocol expands the channel capacity and enhances transmission efficiency. Compared to previous measurement-device-independent quantum dialogue (MDI-QD) protocols, this protocol not only further improves transmission efficiency but also enables mutual authentication between correspondents, effectively defending against the risk of man-in-the-middle attacks. The utilization of a cross-Kerr medium for Bell measurements offers a 50% increase in efficiency compared to linear optical equipment. This novel protocol is tailored to the data transmission process within the cloud office model, thereby enhancing the communication efficiency and reinforcing secure data transmission.

Shale gas is becoming an increasingly promising alternative energy resource because of its high efficiency and environment-friendly characteristic. The amount of adsorbed gas on the shale matrix surfaces and dissolved gas in the shale matrix bulk is the dominant factor in the long-term productivity of shale reservoir. Although experimental measurements have been extensively carried out to investigate the gas adsorption and diffusion properties in the shale matrix, they cannot provide the detailed information on the microscopic transport mechanism of shale gas during the gas production process. Molecular simulation can accurately visualize the gas adsorption/desorption and diffusion processes in the shale matrix. In the present study, the recent research advances of molecular simulation on gas adsorption/desorption and diffusion in the shale matrix are reviewed. Firstly, the density functional theory (DFT) for shale gas molecule desorption/adsorption on the surface of the matrix crystal is illustrated. Then, the grand canonical Monte Carlo (GCMC) method predicting the amount of shale gas desorption/adsorption in the shale matrix crystal is introduced. Finally, molecular dynamics simulation (MD) for gas diffusion in the shale matrix is elucidated. Further developments of the molecular simulation method in shale gas production are also discussed.

As one of important research branches of quantum information hiding, quantum steganography embeds secret information into quantum images for covert communication by integrating quantum secure communication technology and classical steganography. In this paper, based on the novel enhanced quantum representation (NEQR), a novel quantum steganography algorithm is proposed to transfer secret information by virtue of quantum watermarked image. In order to achieve this goal, the least significant qubit (LSQb) of quantum carrier image is replaced with the secret information by implementing quantum circuit. Compared with the previous quantum steganography algorithms, the communicating parties can recover the secret information tampered, meanwhile the tampers can be located effectively. In the experiment result, the peak signal-to-noise ratios (PSNRs) are calculated for different quantum watermarked images and quantum watermarks, which demonstrate the imperceptibility of the algorithm is good and the secret information embedded can be recovered by virtue of its self-adaptive mechanism.

Osmotic energy conversion is a promising method of sustainable electricity generation using seawater and river water. Artificial pure NaCl solutions are commonly used, whereas the effects of multivalent-ion ingredients present in natural seawater on osmotic power generation remain unclear. In this study, the impacts of coexisting ions in multicomponent seawater (MS) are experimentally assessed using graphene oxide membrane (GOM). Divalent cation in MS shows inferior transport to monovalent cation, thereby presenting a lower power density than when using pure NaCl solutions. Inspired by experimental results, an interfacial binding rope theory is proposed to clarify ion-wall interactions and cation transport in sub-nanochannels with hydrophilic functional groups. The binding rope networks include direct cation-wall connections mediated by composition-changed hydration shells, indirect connections by H-bonds linking solvated water molecules and functional groups, and electrostatic attractions between cations and negatively charged surfaces. The theory feasibility is confirmed by first-principles calculations focusing on the charge distribution, binding site and length, surface electrification, and cation diffusivity and selectivity in GOM sub-nanochannels. Divalent cation diffuses slower than monovalent cation in both pure solutions and confined channels. For the mixed solution in channels, both monovalent and divalent cations show worse diffusivities due to additional monovalent-divalent electrostatic repulsions, as well as inferior cation selectivity due to weakened deprotonation reactions. Bridged by environment-controlled interfacial potential distribution, ion diffusivity, and ion selectivity, this theory guides the improvement of MS-based osmotic performance under regulations of concentration gradient, pH, and temperature. A power density of 8.52 W m–2and stable output within 27 days are achieved. The interfacial binding rope theory could be popularized to refine the transport mechanisms of various cations in diverse hydrophilic sub-nanochannel materials, promoting the application of osmotic power generation and other nanoscale technologies.

This work numerically investigates the importance of controlling the wake of upstream body in the tandem cylinders aiming at aerodynamics noise reduction. The two-dimensional unsteady Reynolds-averaged Navier–Stokes approach with the k–ω turbulence model and Ffowcs Williams–Hawkings method are employed to simulate the flow field and the aerodynamics noise, respectively. The flow in the porous media is calculated by a volume-averaged model. Analogy to the mass-spring-damper system, one preliminary model is proposed to reveal the key role of stabilizing the upstream body wake. The simulations of different porous materials coating designs are implemented to corroborate the model and provide more details of flow modification by porous materials coating. Results indicate that the porous materials coating designed on the upstream cylinder can decrease the wake impingement on the downstream cylinder via suppressing the vortex shedding. Subsequently, not only the tonal noise but also the broadband noise level of tandem system can be reduced. It is also clarified that the effects of downstream cylinder absorption and downstream cylinder wake control by porous materials coating is not comparable with the upstream cylinder wake control. The present study gives a new idea to flow control and noise reduction of the multibody systems considering efficiency and economy.

Video synopsis aims at retrieving interested events and reducing human labor on browsing long surveillance video. Traditional video synopsis methods based on energy function minimization is high computational and time consuming. Besides, the unchronological tubes shifting strategy may cause chaotic temporality and uncomfortable collisions. We propose a spatiotemporal events rearrangement optimization algorithm, which formulates the events rearrangement problem as iteration judgment on trajectory correlation and events compactability to generate the output synopsis video. An events subsection modification strategy has been presented to solve the spatial incompleteness of certain single event caused by imperfect object tracking. The experimental results have shown that the output synopsis video reserves the chronological order and avoids collisions of events.

Recently, many quantum digital signature (QDS) schemes have been proposed to authenticate the integration of a message. However, these quantum signature schemes just consider the situation for bit messages, and the signing-verifying of one-bit modality. So, their signature efficiency is very low. In this paper, we propose a scheme based on an application of Fibonacci-, Lucas- and Fibonacci-Lucas matrix coding to quantum digital signatures based on a recently proposed quantum key distribution (QKD) system. Our scheme can sign a large number of digital messages every time. Moreover, these special matrices provide a method to verify the integration of information received by the participants, to authenticate the identity of the participants, and to improve the efficiency for signing-verifying. Therefore, our signature scheme is more practical than the existing schemes.

As a special factorization category of finite groups, logarithmic signature (LS) is used as the main component of cryptographic keys that operate within secret key cryptosystems such as PGM and public key cryptosystems like MST1, MST2and MST3. An LS with the shortest length is called a minimal logarithmic signature (MLS) that constitutes of the smallest sized blocks and offers the lowest complexity, and is therefore desirable for cryptographic constructions. However, the existence of MLSs for finite groups should be firstly taken into an account. The MLS conjecture states that every finite simple group has an MLS. If it holds, then by the consequence of Jordan-Hölder Theorem, every finite group would have an MLS. In fact, many cryptographers and mathematicians are keen for solving this problem. Some effective work has already been done in search of MLSs for finite groups. Recently, we have made some progress towards searching a minimal length key for MST cryptosystems and presented a theoretical proof of MLS conjecture. 根据有限单群的分类定理,本文利用有限群论、代数群论、射影几何等学科的相关理论给出了剩余四种单群极小对数签名的结构,最终从理论上完成MLS 猜想的证明,为MST 密码系统提供了广阔的应用平台。具体成果如下: (a) 给出了一类经典单群极小对数签名的构造。(b) 给出了一类经典单群—射影特殊酉群极小对数签名的构造。 (c) 构造了所有十类特殊李型群的极小对数签名。 (d) 构造了剩余十三类零散群的极小对数签名。

The gas transport mechanism in shale reservoirs is extremely complex and is a typical multiscale and multiphysics coupled transport process, considering the complex shale rock structure, wide distribution of micropores and nanopores in shale gas reservoirs, diverse gas occurrence forms, and large pore size spans. An accurate understanding of the shale gas transport process and mechanism is important for effective exploration of shale gas reservoirs. In this work, a review of the recent progress in the prediction of shale gas transport in porous media is presented. The basic theory of gas transport in nanopores is discussed. The gas transport in organic and inorganic matter and the gas adsorption effect are covered. Then, gas transport simulations with conventional multiscale numerical methods, including molecular dynamics and lattice Boltzmann simulations, are reviewed, and the multiscale modeling methods are discussed. Furthermore, the application of artificial intelligence (AI) methods in shale gas transport research is discussed. The focus is on the characterization of the shale porous geometry, including porosity, tortuosity, pore size distribution, and reconstruction of the shale porous medium. The application of AI-based methods such as neural networks and machine learning for the prediction of porous flow properties is discussed. This study intends to provide a comprehensive review of shale gas transport characteristics and to enable the accessibility of AI tools in the research of shale gas.

A serious problem in cloud computing is privacy information protection. This study proposes a new private comparison protocol using Einstein-Podolsky-Rosen (EPR) pairs. This protocol allows two parties to secretly compare their classical information. Quantum dense coding enables the comparison task to be completed with the help of a classical semi-honest center. A one-step transmission scheme and designed decoy photons can be used against various quantum attacks. The new protocol can ensure fairness, efficiency, and security. The classical semi-honest center cannot learn any information about the private inputs of the players. Moreover, this scheme can be easily generalized using the general EPR pairs in order to improve the transmission efficiency. (1)本文设计一种新的公平、有效、安全的量子隐私对比协议。(2)与以前的诚实第三方和量子第三方不同, 本文的协议只依赖于经典的半诚实中心。(3)不像以前的协议可信第三方可能获取部分隐私信息, 本文中的经典半诚实中心不能获取对比双方的隐私消息。(4)本文的协议具有较好的扩展性, 可以拓展到基于多层量子态的隐私对比协议。

Composite phase change materials (PCMs) can increase the overall effective thermal conductivity of latent heat thermal energy storage (LHTES) systems and improve their heat transfer performance. However, owing to density differences caused by solid–liquid phase change, void cavities with low thermal conductivity are generated in small spaces where the volume shrinks, thereby increasing the heat transfer resistance. To analyze the pore-scale effects of void cavities on the thermal performance of composite PCMs, a model without void cavities and six models with randomly distributed void cavities were established in this study. A graphics processing unit (GPU) accelerated multiple-relaxation time lattice Boltzmann method was adopted to implement the phase change process and obtain the evolutions of temperature distribution, average liquid fraction, and energy storage performance. The results indicated that, as the volume fraction of the void cavities increased, the average liquid fraction of the composite PCMs slightly increased, whereas the heat storage significantly decreased. At a Fourier number of 0.1, the heat storage per unit width of the composite PCMs was reduced by 3.81 %, 8.02 %, and 11.22 % when the volume fractions were 5 %, 10 %, and 15 %, respectively, compared to the case without void cavities. Additionally, the composite PCMs with large pore-size void cavities had slightly better heat storage efficiency than those with small pore sizes at the same volume fraction of void cavities. It was also found that the LHTES cavity with right-half void cavities had the minimal influence on the heat storage performance.

A serious obstacle to large-scale quantum algorithms is the large number of elementary gates, such as the controlled-NOT gate or Toffoli gate. Herein, we present an improved linear-depth ripple-carry quantum addition circuit, which is an elementary circuit used for quantum computations. Compared with previous addition circuits costing at least two Toffoli gates for each bit of output, the proposed adder uses only a single Toffoli gate. Moreover, our circuit may be used to construct reversible circuits for modular multiplication, Cxmod M with x< M, arising as components of Shor’s algorithm. Our modular-multiplication circuits are simpler than previous constructions, and may be used as primitive circuits for quantum computations.

Essential characteristics for watermark registration and detection without data modification can be used in anaudio zero-watermarking scheme. In this paper, a novel audio zero-watermarking scheme based on discrete wavelet transform (DWT) and discrete cosine transform (DCT) is presented. The watermark is registered by comparing the mean absolute values of the adjacent frame coefficients after DWT and DCT. Simulation results show that the proposed scheme is strongly robust to common attacks such as AWGN, downsampling, low-pass filtering, requantization, and MP3 compression. A performance analysis of the proposed scheme shows that all bit error rates after attacks are zero.

The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks. This paper presents a multilevel pattern mining architecture to support automatic network management by discovering interesting patterns from telecom network monitoring data. This architecture leverages and combines existing frequent itemset discovery over data streams, association rule deduction, frequent sequential pattern mining, and frequent temporal pattern mining techniques while also making use of distributed processing platforms to achieve high-volume throughput.

The accuracy of the traditional assessment method of the quality of experience (QoE) has been facing challenges with the growth of high-definition (HD) video streaming services. Image display-quality damage is the main factor that affects the QoE in HD video services through UDP network transmission. In this paper, we introduce a novel objective factor known as image damage accumulation (IDA) to assess user's QoE in HD video services. First, this paper quantitatively analyzed the effect on user quality of experience by IDA and established a mapping relationship between mean opinion scores and IDA. Furthermore, the probability of image damage caused by compression and transmission were analyzed. Based on this analysis, an objective QoE assessment and prediction method for HD video stream service that evaluated the user experience according to IDA are proposed. The proposed method can achieve assessment and prediction accuracy on three distinct subjective tests.

Fully developed flow and heat transfer in metal-foam filled tube with uniform wall temperature (UWT) is semi-analytically investigated based on the Brinkman-Darcy model and the two-equation model, in which the inertia term, axial conduction, and thermal dispersion are ignored. A two-dimensional numerical simulation that adopts the full governing equations is also conducted to analyze the effects of neglected terms on flow and thermal transport performance by comparing with the semi-analytical solution. The effects of the relevant parameters and thermal boundary conditions including UWT and uniform heat flux (UHF) on the heat transfer characteristics are discussed based on the semi-analytical solution. The results show that the inertia term has a significant effect on the prediction of pressure drop, but has a relatively mild effect on Nusselt number. The axial conduction has significant effect on the Nusselt number at lower Reynolds number, and the effects of thermal dispersion can be neglected when the thermal conductivity ratio between fluid and solid is remarkably smaller for air/metal foam as example (kf/ks<3×10−3). The predicted Nusselt number of the semi-analytical solution is about 8% to 15% lower than that of the numerical solution with full model in the range of 4×10−5

Information security protection is always one of very significant and fundamental issues in edge computing, generally including cryptography, authentication, intrusion detection, privacy protection, and other technologies, and so forth. Quantum authentication is one of the latest extensions of authentication technology in quantum field. So far, most of the quantum identity authentication protocols proposed are based on noise‐free environments. However, due to the existence of quantum noise in quantum channels is inevitable, the noise immunity is very important to quantum identity authentication. In this article, a novel quantum identity authentication protocol based on three‐photon error avoidance code is proposed. In this protocol, quantum information is encoded on the noiseless subsystem, so the protocol can effectively resist on the interference of noise in the quantum channel to information transmission. The comprehensive analysis of antinoise performance and the security analysis on various eavesdropping attacks shows that the new protocol proposed in this article has not only good antinoise performance but also good security. In this article, a novel quantum identity authentication protocol based on three‐photon error avoidance code is proposed. The comprehensive analysis of antinoise performance and the security analysis on various eavesdropping attacks shows that the new protocol proposed in this article has not only good antinoise performance, but also good security.