With the rapid development of quantum computers, cryptographic algorithms against quantum attacks have become a research hotspot in cryptography. McEliece encryption system based on error-correcting codes, proposed by Robert McEliece in 1978, is an asymmetric encryption algorithm against quantum attacks. In this paper, firstly, the definitions and basic properties of several common error-correcting codes, such as Reed-Solomon codes, Goppa codes, and Twisted Reed-Solomon codes are introduced. Secondly, the encryption and decryption process of McEliece public-key encryption system based on error-correcting codes is described in detail, and the security of the encryption system is analyzed from the perspective of NP-Hard problems. Finally, on the basis of previous research results, combined with recent research hotspots, several considerations and open problems are proposed to point out the direction for future research.

The rational construction of heterostructures based on two or more semiconductor materials can integrate the advantages of multiple components, promote the separation of photogenerated carriers, expand the range of light absorption and retain the high redox capacity of photocatalysts, which have great potential applications as photoelectrodes in the process of solar energy utilization and conversion. Due to various advantages of hematite (α-Fe₂O₃) such as abundant content, suitable bandgap and high theoretical hydrogen evolution efficiency, the construction of heterogeneous structures based on α-Fe₂O₃ has become an important research area. In this review, the basics of photocatalytic mechanism and heterojunctions are briefly introduced, then, Z-scheme heterojunctions that exhibit unique photogenerated carrier flow pathways and excellent photocatalytic performance is specifically described. Finally, after the systematic review of state-of-the-art Z-scheme heterojunction materials based on α-Fe₂O₃ in recent years, some emerging agenda are outlined for future oriented research.

Osteoporosis is a systemic metabolic bone disease that can cause reduced bone mass and increase the risk of fracture due to microstructural degradation. At present, western medicine treatment is often accompanied by more serious adverse reactions, which reduce patients’ compliance, thus affecting the treatment effect. Traditional Chinese medicine is characterized by small adverse reactions, multiple ways and multiple targets. Under the guidance of the theory of “the main kidney bone produces marrow”, it is found that Rhizoma drynariae repair has a role in treating osteoporosis.The total flavones of R. drynariae are the main active components of R. drynariae which play an anti-osteoporosis role. With the continuous in-depth study of the pharmacology of traditional Chinese medicine, the total flavones of R. drynariae can regulate the osteogenic proliferation, differentiation and apoptosis of bone cells from multiple links, promote bone formation, increase bone mass, and achieve the role of preventing and treating osteoporosis. The signaling pathways involved include Wnt/β-catenin signaling pathway, MAPK signaling pathway, OPG/RANKL/RANK signaling pathway, BMPs signaling pathway, PI3K/AKT/mTOR signaling pathway, etc. This article summarized the molecular mechanism of the total flavones of R. drynariae and its main active components in the prevention and treatment of osteoporosis in recent years, discussed the exact mechanism of the anti-osteoporosis effect of osteoporotic in vivo, and provided help for the research and development of new anti-osteoporosis drugs.

Considering the random and nonlinear characteristics of traffic flow that result in low prediction accuracy, a combined prediction model based on quadratic decomposition and fusion of multiple features is proposed, where the trend and periodic features in traffic flow are extracted by using the time series decomposition method, the residual components are quadratically decomposed by the optimized variational mode decomposition, the scored amount is reconstructed, the external features of the traffic flow are selected by the correlation coefficient method, and three different models are established to predict the components after fusing the external features. Reinforcement learning is used to optimize the weights of each model, and the final prediction result is obtained by weighted sum. Using the simulation analysis of traffic flow in Changsha urban area, experimental results show that compared with the long short-term memory neural network model. Combined model of convolutional neural networks and gated cyclic units, BP after quadratic decomposition and lightweight gradient lifter after quadratic decomposition, the model established in this paper has a better prediction effect on urban road traffic flow, with an average absolute error of 2.622 and a root mean square error of 3.479. The prediction errors are better than the existing models, which verifies the effectiveness of the proposed model.

Under the dual background of network power strategy and "double carbon" goal, in order to solve the power supply pressure and energy saving and emission reduction problems caused by the increase of density and data volume of 5G mobile network, a low-carbon optimization operation strategy based on the collaboration of 5G base stations (BSs) and integrated energy system (IES) is proposed. Firstly, in order to optimize the energy management of the BSs and strengthen the interaction between the BSs and IES, the BSs sleep mechanism and the demand response model of the BSs energy storage battery are introduced, and their operation effects in different time and space are compared. Secondly, in order to promote the efficient coupling utilization between the BSs and IES electric-thermal energy, a 5G BSs waste heat model is established, which is coupled with the photothermal power station in IES to give full play to the energy supply potential of the two. Finally, in order to measure the low-carbon benefits brought by the addition of the BSs, the reward and punishment ladder carbon trading mechanism is introduced into the system decision-making, and the three-stage optimization scheduling model of the cooperative operation of 5G BSs and IES is constructed. The optimization model is simulated and analyzed under different operation scenarios. The results show that the operating costs of IES and 5G BSs decreased by 20.3% and 22.5% respectively after collaborative scheduling, and the carbon emissions of IES decreased by 24.2%.

Aiming at the nonlinear characteristics of wind power, a combined prediction method for wind power is proposed, which combines gray relational analysis (GRA), improves sparrow algorithm (ISSA), support vector regression (SVR) and error correction model (EC). GRA is used to select the influential factors with a large degree of correlation with wind power as the input of the model. Adaptive weight factor and Levy flight strategy are introduced to improve the performance of traditional SSA, and ISSA-SVR model is established to obtain the initial predicted value. The error correction model is established to get the predicted error value. Finally, the initial predicted error value and the predicted error value are combined with the adder to get the final result. The simulation results show that the average determination coefficient of the model is 0.999 6 and 0.998 5, the average absolute error is 0.226 6 kW and 0.014 6 MW, and the root mean square error is 0.277 7 kW and 0.021 3 MW, respectively, when predicting the wind power of two wind farms. Compared with other traditional models, the prediction accuracy is higher.

To further improve the accuracy of over-voltage type identification during the operation and maintenance of high-voltage transmission lines, this paper proposes an improved Residual Network (ResNet) method for lightning over-voltage identification of transmission lines. The improvement of the traditional ResNet-50 network includes the following three aspects. Firstly, the 7×7 convolution kernel is replaced by three 3 × 3 convolution kernels to improve the feature extraction ability of the network. Secondly, the ReLU activation function of the traditional ResNet-50 network is replaced by the ReLU-Softplus activation function to improve the convergence speed of the network. Then, adjust the ResNet-50 network structure to enhance the role of batch standardization. Finally, a lightning overvoltage identification model of transmission lines is constructed by combining transfer learning and improved residual network. The experimental results show that the improved residual network converges in the 70th step and the recognition accuracy is 97.25%. The recognition accuracy and convergence speed are better than other models.

The Internet of Things (IoT) has been widely applied in the primary, secondary and tertiary industries in China. IoT devices (such as cameras) have generated a huge amount of image and video multimedia data, and the value contained in it has been paid more and more attention. How to meet the new demand of value-added data exchange and paid sharing and build a safe and fair data transaction mechanism is one of the important foundations of data element value exchange. In view of problems such as privacy leakage and lack of security in the scheme of using traditional third parties to conduct Internet of Things data transaction, this paper realizes secure transaction of Internet of Things data by using technical features such as traceability and tamper-proof of blockchain, and turns security transaction of Internet of Things data into two-stage Stackelberg game. The double-chain architecture is used to ensure the security and privacy protection of the transaction process, and the perceptive hash technology is used to realize data right confirmation, so as to protect the rights and interests of all participants in the transaction to the greatest extent. The improvement of the proposed scheme in time, TPS and zero-knowledge proof, as well as the trend of optimal profit distribution after two-stage Stackelberg game are verified by experiments, further verifying the advantages and feasibility of the proposed scheme. Finally, the possible security threats of this scheme are analyzed, and it is proved that the scheme can effectively resist the risks of collusive attack, denial and frame-up under different scenarios.

The association of sentiment among microblog texts has not been considered by previous research. A microblog opinion summarization method based on Transformer and TextRank is proposed in this paper. Firstly, the word vectors of the texts are encoded and quantified by encoder and quantization space of Transformer. Then according to the quantization results, the opinion categories of microblog textset are divided by semanteme clustering, and the important categories are selected for summary extraction. Then the sentiment feature vector and the microblog text feature vector are concatenated. Then TextRank algorithm with sentiment features is used in every category, and the microblog text with the highest weight is extracted as the summary text. Finally, the most representative summary texts in all categories are combined to obtain the final microblog opinion summarizations. The experimental results show that, after adding the sentiment polarity influence factor, the ROUGE values of the proposed method has significantly improved compared with the baseline method. The maximum F-measure values of Rouge-1, Rouge-2 and Rouge-SU4 can top out at 0.493 7, 0.255 5, 0.270 6 respectively. It proves that the proposed method is effective for the task of extracting microblog opinion summarizations.

The traditional deep learning model network applied to rolling bearing fault identification has low diagnosis accuracy and long training time. To overcome these disadvantages, this paper proposes a multi-scale attention reverse residuals convolutional neural network (MARCNN). Firstly, multi-scale feature extraction module adopts multi-scale convolution to obtain different levels of original signal features and adaptively extract fault feature information. Secondly, feature graph expansion standard convolution is used to construct the shallow convolution module to improve the shallow network learning ability. Finally, SE-Mobile module is constructed to mine deep fault features and reduce the number of model parameters. All modules combine attention mechanism to integrate feature weights of different dimensions to improve model feature learning ability. The experimental results show that the model can reduce the number of parameters and improve the training speed, and the accuracy of the model can reach 99.98%, 98.41% and 94.98% under fixed, Gaussian noise and variable load conditions, respectively. It is shown that the model has a certain anti-noise and generalization ability.

The number, position distribution and distribution density of the diamond particles fixed on the diamond wire are important parameters to measure the surface quality of the diamond wire, and also important indicators to measure the cutting ability of the diamond wire. Aiming at the problems of small, dense and adhesive diamond particles, such as difficult to extract their features and low accuracy, a method of surface quality detection based on improved YOLOv5 diamond wire is proposed by using deep learning technology. First, in the image processing stage, the threshold segmentation technology is used to preliminarily divide large and small particles; Secondly, in the backbone network part, the CA (coordinated attention) attention module is added to obtain high-quality single-particle boundary features in the adhesive particles; The C2 (CA+CBL) module is designed again to preserve the semantic information between different layers by feature fusion, thus improving the detection accuracy of dense small objects; Finally, replace CSP2_X with a convolution structure, reduce the calculation amount, and reduce the receptive field of the output characteristic map of different scales to avoid the virtualization of particle characteristics, thus affecting the particle detection accuracy. Experiments show that the improved network model can effectively identify the images of diamond particles with different shapes, sizes, adhesion and density, the average accuracy (AP) of the particles, and the large particles are 83.80%, and 90.70%, respectively, and the mean average precision (mAP) is 87.20%.

A stochastic model of two prey, one predator with Holling Ⅱ and Monod-Haldane type functional responses is investigated in the presence of white noise and Markov switching in a polluted environment. The uniqueness of the existence of a global positive solution of the model is proved, sufficient conditions for the persistence and extinction of the population in a time-averaged sense are established, and the model is shown to have a unique stationary distribution under certain conditions using the Lyapunov function. Finally, the theoretical results are illustrated by numerical simulations.

The application of event-triggered mechanism in the network system with complex structure and limited communication resources can reduce the number of updates of the control protocol, thus decreasing the total amount of information transmission in the network. In this paper, a centralized event-triggered agreement protocol is designed for a leader-following multi-agent systems with nonlinear dynamics. Then, based on Lyapunov stability theory, a sufficient condition for partial component consensus of the nonlinear system is derived. Meanwhile, it is analyzed that the triggered interval of event-triggered protocol has a minimum positive lower bound. Finally, numerical simulations verify the correctness of the theoretical results.

To study the compounds of Rabdosia stracheyi, twelve triterpenoids were isolated from the aerial part of R. stracheyi by means of various column chromatographic techniques, including silica gel, ODS, Sephadex LH-20 and preparative RP-HPLC. The structures of the isolated triterpenoids were determined on the basis of analyses of spectroscopic methods (¹H- and ¹³C-NMR spectroscopy), high-resolution electrospray ionization mass spectrometry (HR-ESI-MS), and comparison of their spectroscopic data with previously reported data. The triterpenoids were identified as friedelinol (1), oleanolic acid (2), 3β-hydroxy-oleana-11, 13(18) -dien-28-oic acid (3), 2α, 3α-dihydroxy olean-12-en-28-oic acid (4), 2a, 3a, 24-trihydroxyolean-12-en-28-olic acid (5), 2α, 3β, 24-trihydroxy olea-12en-28oic acid (6), cleistocalyxin (7), uvaol (8), 2α-hydroxy ursolicacid (9), methyl 2a, 3a, 24-trihydroxy ursa-12, 20(30)-dien-28 oate (10), maquatic acid (11) and 2α, 3β, 24-trihydroxyurs-12, 20(30)-dien-oic acid (12). All compounds were isolated from R. stracheyi for the first time.

In order to study the antioxidant activity and composition of Zhuang medicine Stahlianthus involucratus, the antioxidant capacity and chemical composition of Stahlianthus involucratus were analyzed through DPPH、O₂^-· and ·OH free radical scavenging experiments and UPLC-Q-Orbitrap HRMS. The results showed that different extracts of Stahlianthus involucratus had certain antioxidant effect, and the ethyl acetate extracts had the strongest antioxidant ability. In total, 14 compounds were identified from Stahlianthus involucratus for the first time, including curcumol, curdione, α-cyperone, azelaic acid, citric acid, protocatechuic aldehyde, isoschaftoside, uridine, L-tyrosine, nicotinamide, L-tryptophan, mannitol and 3-butylidenephthalide. There is a certain antioxidant capacity in the Stahlianthus involucratus, protocatechuic aldehyde, nicotinamide and other components may be the substances that directly play the key role. This study provides a reference for the development and utilization of Stahlianthus involucratus.

Guilin City is an innovative demonstration area of the National Sustainable Development Agenda. Clarifying the evolution characteristics and driving mechanism of its ecological footprint can effectively promote the sustainable development of Guilin City. Based on the three-dimensional ecological footprint model, this paper analyzes the dynamic changes of Guilin’s ecological footprint from 2009 to 2018, and uses the partial least squares method to reveal the factors that affect the dynamic changes of ecological footprint. The research results showed that: 1) The per capita ecological carrying capacity of Guilin was relatively stable from 2009 to 2018. The per capita ecological footprint first increased and then decreased, reaching a peak of 1.859 hm²/person in 2015. The per capita ecological deficit first increases and then decreases, and the ecosystem is overloaded due to excessive resource consumption. 2) From 2009 to 2018, the per capita footprint of Guilin remained basically unchanged. The per capita footprint depth first increased and then decreased, reaching the maximum value in 2015. During the study period, the per capita footprint depth was greater than 1. 3) The stock-to-flow utilization ratio and the ecological pressure index both increased first and then decreased. The stock-to-flow utilization ratio was at a peak in 2014, and the ecological stress index peaked in 2017. 4) City scale has a significant negative driving effect on the ecological footprint. Economic development and social consumption have a positive driving effect on the ecological footprint, the added value of the secondary industry has a significant impact, and the regional GDP, the added value of the primary industry and the per capita disposable income of urban residents have an important impact on the ecological footprint.

In Arabidopsis thaliana, lectin receptor-like kinases (LecRKs) contain 86 members and are widely involved in plant resistance to biotic and abiotic stresses. AtLecRKIII.2 is a member of the LecRKs family and its specific function has not been reported. Here, three-primer method and real-time quantitative PCR are used to identify homozygous deletion mutants and overexpression plants of AtLecRKIII.2 gene. Analysis of promoter cis-acting elements reveals that AtLecRKIII.2 gene has multiple regulatory elements related to stress, hormone and other responses. Tissue expression pattern analysis shows that AtLecRKIII.2 gene has the highest expression in fruit pods, followed by stems. The analysis of adversity and hormone response patterns shows that AtLecRKIII.2 gene has different degrees of response to exogenous hormones (IAA, BL, GA), PEG8000, high temperature and low temperature. The experimental results of germination rate and root length shows that after treated with NaCl or Mannitol, the seed germination rate of LecRKIII.2-OE is higher than that of the wild type, while lecrkiii.2 is lower than that of the wild type. After treated with auxin, the elongation of LecRKIII.2-OE roots is significantly inhibited and the expression level of auxin-related genes in LecRKIII.2-OE is significantly changed. The above research results indicate that the AtLecRKIII.2 gene may positively regulate the tolerance of Arabidopsis to salt stress and osmotic stress and the growth and development of roots. The above results provide reference data for further research of the physiological function of AtLecRKIII.2 gene in plant abiotic stress and hormone signal transduction.

Transect and focal animal scanning method were used to collect the birds’ feeding behavior on fruit plants in Guilin Botanical. The information of the interaction relationship between them were analyze to discuss the utilization rule of birds on fruit plants and the seasonal changes of network parameters. 2 174 interactions events were recorded between 14 bird species (2 orders and 7 families) and 13 plant species (8 orders and 11 families) throughout the year. Each plant species interacted with 7.15±0.88 birds, and each bird species interacted with 6.57±1.20 plant species. The interaction connectance (C=0.51), weighted nestedness (0.93) and interaction diversity (H₂=3.81) of the network were higher, while the specialization (H′₂=0.10) was lower. Cayratia japonica and Cinnamomum camphora were the most consumed by birds, while Pycnonotus xanthorrhus, Hemixos castanonotus and Ixos mcclellandii are the bird species that consumed most of the fruit plants, including the 13 plant species. The feeding frequency of birds in autumn (38.79%) and winter (33.15%) accounts for the largest proportion of the total annual feeding frequency. The weighted nestedness (ωNODF=0.92) and interaction diversity (H₂=4.78) between birds and fruit plants is the largest in autumn, the largest connectance (C=0.53) in winter, and the largest specialization (H′₂=0.27) in summer. The results shows that the interaction relationship between animals and plants in urban green space can be complex and variable according to different seasons. The network analysis can provide important information for studying the changes of ecosystem function state in rapidly changing habitats.

High-fat diet was used to construct a mouse obesity model, and it was found that the traditional high-fat diet had problems such as poor palatability, long modeling time, and low molding rate. In response to these problems, the obesity model of C57BL/6J mice was established by improving the traditional high-fat diet formula and using the method of interval feeding. After modeling, serum biochemical indexes, fat weight, and histopathological changes of liver, fat and pancreas were detected. The results showed that: 1) feeding the improved high-fat diet could shorten the modeling time, and the mouse obesity model could be established in only 6 weeks under the interval feeding method; 2) the serum liver function and renal function of the high-fat diet group related to Biochemical indicators were normal, blood lipids was elevated (P<0.01), and histopathological tissue sections showed mild to moderate edema in liver tissue, increased adipocyte volume, and no abnormality in pancreatic tissue. The improved high-fat feed in this experiment had high palatability and could increase the body weight of mice in a short time, which was shorter than the same type of high-fat feed on the market and had food safety.

In this study, 23 endophytic bacteria isolated from the medicinal plant Tripterygium wilfordii were applied as experimental strains to determine the production of IAA, ACC deaminase and siderophore and phosphate solubilization capacity in the monoculture and dual mixed culture (253 combinations). By comparison, the effects of coexistence and interactions of endophytic bacteria on growth-promoting substance production were evaluated. The results indicated that interactions between co-cultured bacteria obviously changed the production of various growth-promoting substances. Compared with the monoculture of strains, abilities of phosphate solubilization and IAA secretion in most of the mixed culture had great improvement. The strains that were co-cultured with LY4 were found to have larger increment of phosphate solubilization. The strain mixtures including LG3, LJ3 or LJ12 showed higher secretion of IAA. Higher ACC deaminase activity were tested from the strain mixtures including LJ12. The strains LJ12 and LY3 had important contribution to siderophore production of their strain mixtures. The growth-promoting index of the mixtures of most of the strains showed no significant correlation to those of the single strains. The growth-promoting properties of the mixtures of the endophytic bacteria did not depend on the abilities of the single strains.

To ameliorate heavy metal pollution and improve safe utilization rate of farmland by combining agricultural measures and soil conditioners, this research explored the effects of soil conditioners (biochar and pectin) on soil physical and chemical properties and the passivation of heavy metals Pb and Cd under different water conditions (75% soil saturation moisture capacity and waterlogged condition). The typical vegetable soil in South China was chosen as the research subject with a soil culture experiment for 30 and 60 days. The results showed that the pH values were higher and the available heavy metal contents were lower under waterlogged condition than under 75% soil saturation moisture capacity. The application of biochar and pectin could increase soil pH value and organic matter contents under both the two water conditions, while the effects on soil alkali hydrolyzable nitrogen, available phosphorus and available potassium contents were different due to different water conditions. Under 75% soil saturation moisture capacity, the application of biochar and pectin could significantly reduce the available Cd contents in soil, which were lower with the application amount of the two conditioners increasing. However, under the waterlogged condition, the effect of pectin on soil available lead content with different biochar application amounts was not consistent, but the passivation effect of soil culture for 60 days was better than that for 30 days. The multivariate analysis of variance indicated that, in general, the types and formulations of soil conditioners had greater impact on the soil physical and chemical properties and the available heavy metal contents than other factors, such as soil incubation time and water conditions. Therefore, for the increasing shortage of cultivated land resources and the more urgent need to improve the quality of cultivated land soil, it is an effective way to reduce the heavy metal availability in the moderately contaminated farmland soil and realize the full and safe utilization of cultivated land by appropriate water management, adjustment of different cultivation modes and appropriate soil conditioners.