Reversible data hiding in encrypted domain combines the dual advantages of encryption technology and data hiding technology, aiming to achieve privacy protection of data content on public channels,and reversible data embedding, so as to cope with the increasingly complex application requirements in the cloud environment. The research significance of reversible data hiding in encrypted domain is discussed from four application scenarios: encrypted data management, covert communication of intelligence, military collaborative operations, and technological integration innovation. Then, the reversible data hiding in encrypted domain is classified according to the operation relationship between data embedding and data encryption, and the technological development under different embed-ding frameworks is also reviewed. Furthermore, technical difficulties of reversible data hiding in encrypted domain are analyzed from four aspects, including embedding performance improvement, separability implementation, image encryption security, and application requirements for cloud environment. Finally, subsequent research directions are analyzed and prospected.

Anaerobic digestion of excess sludge is one of the most effective technologies for anaerobic digestion treatment, which has the dual function of reducing environmental pollution and providing energy. The study compared and analyzed the current research hotspots in anaerobic digestion of excess sludge based on the relevant articles in the CNKI database and the Web of Science core database from 2003 to 2023 via bibliometric methods and visualization tools. The application of anaerobic digestion of excess sludge to produce methane is an important purpose for excess sludge treatment, and there is an important correlation between pretreatment technology and excess sludge treatment. The application of different pretreatment technologies, such as physical, chemical and biological enzymes, have a significant impact on biogas production, and a more appropriate pretreatment technology for the physical and chemical properties of the sludge can further increase the degree of excess sludge resource utilization while saving costs.

For the issue of missing data occurring in the data collection process of intelligent transportation systems, a road network traffic data recovery model is proposed in this paper based on the dynamic generative adversarial network. Firstly, the approach in this paper are constructed various missing traffic data matrices by considering the spatial-temporal properties of traffic data and the set missing patterns and missing rates. Then iteratively trains a GAN was composed of two fully connected neural networks based on a game idea. By introducing a novel dynamic adaptive mechanism, this study can automatically identify the optimal number of iterations of the generator and discriminator during the model computation, and finally generates the complete traffic data matrix and repair the missing values. California PeMS and Guangzhou traffic speed datasets are used to complete the D-GAN model construction, and multiple evaluation metrics are employed to assess the repair performance of D-GAN. Experimental results show that the repair accuracy of D-GAN is higher for random missing patterns compared with non-random missing patterns; and the repair accuracy of D-GAN degrades accelerated with increasing missing rates. However, the repair performance of D-GAN outperforms the baseline models (e.g., BGCP, prophet-RF, and GAIN) under various missing conditions.

Since 5G is concentrated on crowded areas, the number of base stations required is large and the energy consumption is large, so operators need to pay a lot on power purchase. In order to reduce the cost on power purchase, this paper proposes a regional energy storage allocation strategy for 5G base stations based on Floyd algorithm. Firstly, the 5G base regional storage station in the power supply network is equivalent to a series of nodes, and the transmission loss rate matrix is calculated according to the distance information between nodes. Secondly, the energy storage situation of each node is analyzed, and the nodes are divided into energy supply nodes and demand nodes according to their energy storage conditions. Finally, based on the Floyd algorithm, the energy in the energy storage network is reasonably allocated. The simulation results show that the system proposed in this paper reaches a stable state after two years of operation or 150 days of operation, respectively, and the system no longer needs to purchase additional power from the utility grid. While reducing the pressure on the power supply of the grid, it also reduces the cost on power purchase of operators.

In the context of the "double carbon" target, this paper proposes an integrated energy system (IES) based on Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) and Integrated Demand Response (IDS) to solve the large-scale wind abandonment problem caused by the "heat-and-power" model of CHP units. Firstly, a coupled operation model of CHP units and AA-CAES plants is established on both sides of the "source-storage" side to analyze the mechanism of coupled operation to achieve thermal-electrolytic coupling. Secondly, price-based and alternative demand response mechanisms are introduced on the "load" side to explore the potential of load-side optimization. Then, a carbon capture system and a ladder-type carbon trading mechanism are introduced in IES to constrain carbon emissions, and a fuzzy opportunity planning constraint model is introduced to analyze the impact of scenery uncertainty on system dispatch based on the objective of minimum carbon emissions and lowest comprehensive cost of IES operation. Finally, the actual data of a region in Northwest China are used to verify the calculation. AA-CAES power plant coupled operation can improve the wind power consumption rate by 84.55%, and reduce the total cost and carbon emission by 11.42% and 20.28% compared with uncoupled operation. The introduction of comprehensive demand response mechanism can further improve the wind power consumption rate by 35.00%, reduce the total cost and carbon emission by 20.93% and 24.43%. The increase of scenery uncertainty will increase the interaction cost with external grid.

In order to solve the problems of poor operation flexibility and difficulty in the wind and solar absorption of the existing integrated energy system, and at the same time, to make full use of hydrogen energy to achieve carbon emission reduction goals, a joint optimal operation method of electricity-hydrogen-heat integrated energy system based on concentrating solar power plant and flexible load is proposed. Firstly, based on the model of concentrating solar power plant and a hydrogen energy system with waste heat utilization containing electricity to hydrogen, an integrated energy system of electricity-hydrogen-heat is constructed. Secondly, based on the characteristics and adjustment value of the electricity-hydrogen-heat flexible load on the demand side, a model of electricity-hydrogen-heat flexible load with translational and transferable load reduction is constructed. Then a joint optimization operation model of electricity-hydrogen-heat integrated energy system based on the characteristics of electricity-hydrogen-heat flexible load regulation is further constructed. Finally, the simulation of the proposed method can balance economic operation and low-carbon effect, which can not only improve the joint operation capacity of concentrating solar power plant and hydrogen energy system but also effectively improve the operating economy and low carbon of the system. The peak-to-valley difference of electricity, hydrogen and heat load is reduced by 6.68%, 11.95% and 8.35%, respectively. Besides, the total operating cost of the system is reduced by 24.4%.

Exploiting intra-modal and inter-modal information is helpful for improving the performance of multimodal sen-timent analysis. So, a multimodal sentiment analysis based on cross-modal cross-attention network is proposed. Firstly, VGG-16 network is utilized to map the multimodal data into the global feature space. Simultaneously, the Swin Transformer network is used to map the multimodal data into the local feature space. And the intra-modal self-attention and inter-modal cross-attention features are constructed. Then, a cross-modal cross-attention fusion module is designed to achieve the deep fusion of the intra-modal and inter-modal features, enhancing the represen-tation reliability of the multimodal feature. Finally, the softmax function is used to obtain the results of the sentiment analysis. The experimental results on two open source datasets CMU-MOSI and CMU-MSOEI show that the proposed model can achieve an accuracy of 45.9% and 54.1% respectively in the seven-classification task. Compared with the current classical MCGMF model, the accuracy of the proposed model has improved by 0.66% and 2.46%, and the overall performance improvement is significant.

Aiming at solving the NP-complete IaaS model cloud resource scheduling problem, an optimal solution method based on answer set program is proposed, and its correctness is analyzed. First of all, it is determined that the way to reduce the energy consumption of the cloud platform is to shut down as many hosts as possible while satisfying the CPU usage of the virtual machine, and formulated the cloud resource scheduling problem. Secondly, combined with the formal description and the strategy of reducing the energy consumption of the cloud platform, the cloud resource scheduling problem is coded as a descriptive (optimization) problem with ASP, and its correctness is analyzed. Finally, the experiment is carried out on the public PlanetLab data set. The experimental results show that the ASP method can not only guarantee the quality of service but also reduce the energy consumption of the cluster, which can save more than 13% of the energy. This shows that ASP method is effective in cloud resource scheduling, and provides a new effective cloud resource scheduling method that is easy to understand, easy to modify and can make full use of the latest ASP tools.

Community detection algorithms are critical research tools in the field of complex networks. However, traditional community detection genetic algorithms have the problems with poor initial population quality and low computational efficiency under large-scale networks. To address this, an improved community detection genetic algorithm based on matrix computation acceleration is proposed. To tackle the problem of subpar initial population quality, a novel initialization operator is proposed to construct high-quality initial communities using the closure coefficient with biases node selection. To address the issue of low computational efficiency, the traditional community detection genetic algorithm operators are restructured based on matrix operations, enabling the use of GPU acceleration to enhance computational efficiency. Experimental results indicate that the proposed algorithm maintains good partitioning accuracy and demonstrates higher computational efficiency than other algorithms of the same type under different scales of real networks and LFR synthetic networks.

Based on progressive type-Ⅱ hybrid samples, the reliability analysis of Lomax distributed multicomponent stress-strength model is studied. Assuming that stress and strength have the same scale parameters and different shape parameters, the maximum likelihood estimation of the reliability function is obtained by using the maximum likelihood theory and the iterative method when the scale parameters are unknown and the asymptotic confidence interval is given. By using Bayesian theory, Tierney Kadane (TK) approximation method and MCMC algorithm, the Bayesian estimation of unknown parameters and reliability under the square error loss function is discussed, and the maximum a posteriori density confidence interval (HPD) is given. Finally, Monte-Carlo simulation method is used to compare and analyze the estimated results. The simulation results show that the Bayesian estimation is better than the maximum likelihood estimation on the whole, and the mean square error (MSE) of the two estimates decreases gradually with the increase of the sample, and the effect of (HPD) confidence interval is better than the asymptotic confidence interval.

In order to study the stability of the walking periodic gait of a bipedal robot on an upper slope, a walking impulse hybrid system is established by using the Lagrangian method, and the existence and stability conditions of the periodic gait are obtained by constructing a Poincaré mapping and analyzing the fixed points of the mapping. The results show that under the condition that the slope angle is 0.1 rad, when an appropriate parameter is selected in the linear pulse thrust, there is a stable period -1 gait of the biped robot walking on the slope, and the different values of constant term of pulse thrustproduce different types of period -1 gait, and the period -1 gait with different motion states is produced when the walking system state parameters are changed.

Recently, hypergraph synchronization is a hot topic in network science. However, the study of synchronization on hypergraphs with uncertain coupling mechanism is not reported. Therefore, a general framework for uncertain-coupled hypergraphs is proposed in this paper. The dimension of the error system is reduced by the simultaneous block diagonalization technique for the matrix, which facilitates the calculation of the Lyapunov exponents. On this basis, the necessary condition of synchronization of the uncertain-coupled hypergraph is obtained. Then, the sufficient condition of synchronization of the uncertain-coupled hypergraph is also obtained based on the Lyapunov stability theory. Finally, numerical simulations are conducted to verify the theoretical results.

A Beckmann rearrangement of ketoximes reaction using triphenylphosphine/NBS as an effective catalyst in acetonitrile is developed. The results indicate that conversion of oximes to amides can reach excellent yields (76%-99% yield) under mild reaction conditions. There are many merits about this method, such as low corrosion, high yields, large-scale preparation, environmental friendliness, simple work-up procedure, and short reaction time. The reaction mechanism is also proposed. The absorption and emission spectrum characteristics of the compounds are also examined. The N-phenyl-[1,1′-biphenyl]-4-carboxamide and 4-nitro-N-phenylbenzamide have a large Stokes shifts of 118, 151 nm, respectively. The results indicate that altering the substitution of aromatic group can be an effective means to regulate the Stoke’s shift.

In order to explore the electronic properties of cluster MnPS₃, a model of cluster MnPS₃ is designed, which is optimized by density functional theory at B3LYP/def2-tzvp level, and nine optimal configurations are obtained. The electron properties of MnPS₃ cluster are comprehensively analyzed by means of atomic charge, population and electron spin density. Among them, it can be seen from the population analysis of MnPS₃ cluster that the electrons flow to the remaining orbitals mainly from the 3d orbitals of Mn atom, 3s and 3p orbitals of P atom and 3s orbitals of S atom. Through the analysis of the charge quantity of each atom in the cluster, it can be seen that Mn atom and P atom are the main providers of electrons, and the electron loss ability of Mn atom is stronger than that of P atom, while S atom is the main accepter of electrons. The analysis of electron spin density of MnPS₃ cluster shows that if the electrons are evenly distributed between atoms and there are more spin-down electrons between atoms, the MnPS₃ cluster can have better stability.

Photocatalytic hydrogen production technology is an effective way to realize the conversion of solar energy to green hydrogen energy, but its practical application is limited by its high cost and low efficiency. Here, a kind of carbon-coated Co₃ZnC nanoparticle (Co₃ZnC@C) was synthesized by a simple precipitation-calcination method. As a cocatalyst, Co₃ZnC@C was coupled with photocatalyst g-C₃N₄ to construct a noble metal-free composite photocatalyst Co₃ZnC@C/g-C₃N₄. The experimental results show that the photocatalytic hydrogen production rate of Co₃ZnC@C/g-C₃N₄ is 109 times higher than that of g-C₃N₄, because Co₃ZnC@C, as a co-catalyst supported on the surface of g-C₃N₄, can improve the charge separation efficiency and accelerate the surface hydrogen evolution reaction rate. The research broadens the application range of metal carbide materials and provides a new way for the design of advanced solar energy conversion photocatalysts.

The antifungal activity of Trichoderma spirale strain SgG4 from Sarcandra glabra against plant pathogenic fungi was studied. Theantifungal activity of SgG4 fermentation products was determined by mycelial growth rate method. The active extract of the fermentation product was separated and purified by silica gel column chromatography combined with activity tracing. The structure of the active compound was identified by nuclear magnetic resonance spectrum and mass spectrometry. The result showed that the antifungal active substance mainly existed in the ethyl acetate extract of fermentation product, which had good inhibitory activity against 13 plant pathogenic fungi, with EC₅₀ values ranging from 0.000 2 to 2.475 7 g/L, among which the inhibitory activity against Ceratocystis paradoxa was the best. An antifungal compound was isolated from the ethyl acetate extract of the fermentation product and identified as Trichoderma acid. At the mass concentration of 0.1 g/L, Trichoderma acid had inhibitory effects on 13 plant pathogenic fungi, among which, the inhibitory rate against Pestalotiopsis theae, Phytophthora parasitica, Ceratocystis paradoxa and Athelia rolfsii was 100%, and the inhibitory rate against the other 9 plant pathogenic fungi is 21.43%-85.71%. It can be seen that Trichoderma acid has good antifungal activity and wide antifungal spectrum, and has a good development and application prospect in microbial source fungicides.

Knockout of gonadal soma-derived factor (gsdf), led to the abnormal proliferation of germ cells and sexual reversal of XY males to females. Differences in transcriptome data of wild-type XY testis, XX ovary, and gsdf-deficient XY giant testis or XY giant ovary showed that the expression level of igf2bp2 (insulin-like growth factor 2 mRNA binding protein 2) was significantly higher in wild-type XY sperms than that in wild-type XX ovary and gsdf-deficient XY sperms and XY ovary, and confirmed by RT-qPCR, suggesting that igf2bp2 expression may be regulated by gsdf signal. The molecular structure of vertebrate igf2bp2 was highly homology evolutionary conserved. RT-qPCR showed that igf2bp2 mRNA was highly expressed in early embryogenesis, especially in the stage of gastrulation. The expression of igf2bp2 was in early embryogenesis and predominant testis in adulthood, suggesting that igf2bp2 may play an important role in early embryonic development, sex differentiation and spermatogenesis. Immunofluorescence assay revealed that the signal of positive reaction of anti-Igf2bp2 antibody in wild-type XY testis was stronger than that of XX ovary, gsdf-deficient XY testis or XY ovary. The presence or absence of gsdf signaling was positively correlated with igf2bp2 expression during gonadal developmental differentiation in medaka, thus may potentially promote igf2bp2 expression, which was opposite to the inhibition of igf2bp3 expression. gsdf-regulatory role of igf2bp2/igf2bp3 expression during medaka spermatogenesis may be a conserved molecular mechanism in vertebrate gonadal differentiation and spermatogenesis.

Nesting during the breeding period is an important stage in the life history of birds and is crucial to successful breeding. Since 1997, more and more individuals of Black-winged Stilt have been found breeding on the coast of Guangxi, China. To understand the breeding strategy of this new colonization population, this shorebird was chosen as a model to study its nest site selection. From March to June, 2022, a total of 37 nests were found. The outer, inner diameter and nest height were (18.806±3.728) cm, (9.759±1.365) cm and (3.006±1.561) cm respectively. Principal component analysis showed that the nest variables of Stilts were related to vegetation, social, concealment, nest material and disturbance. Higher height of herb (14.844 ± 1.549) cm, far from the road (357.108 ± 71.118) m and certain concealment level (1.622 ± 0.206 3) played the key roles in nest-site selection. Results of the comparison between successful and unsuccessful nests showed that the distance to the road, open water area of the foraging ground and concealment are significantly different.

The current indoor screening methods for biocontrol bacteria tend to ignore the basic role of plants; to overcome this drawback, this paper compares the methods of indoor screening for biocontrol bacteria of dual culture, liquid medium screening and seedling substrate screening, then develops a new device based on the improved seedling substrate screening method. This device was modified of the PP-500 mL tissue culture bottle which resistant to high temperature (135 ℃) and high pressure (0.15 MPa). The columnar space of the tissue culture bottle was divided into 3 zones, there were plant growing zone, plant pathogen culture zone, and the candidate biocontrol strain culture one. Each zone was separated by a 0.45 μm nitrate fiber filter membrane. The plant growing zone was open, but the plant pathogen and the candidate biocontrol strain culture zones were closed with a lid. In this device, root exudates of plant growing in approximation of natural conditions and soil exudates were used as substrates to screen candidate biocontrol bacteria, so the results obtained were more reliable. The antagonistic effect of pathogen and candidate biocontrol bacteria was reflected by the change of cell density in this device, which was easy to detect and the result was definite. The device had the advantages of simple structure, low cost and convenient operation. It can be used for batch screening of candidate biocontrol bacteria against various plant root pathogens, but not suitable for screening of that against pathogens of leaf and stalk.