The SM2 signature algorithm is an essential component of commercial cryptography systems in China and has been widely applied in various fields. However, the risks associated with private key leakage and the issue of forward security in signatures continue to receive significant attention. To address these concerns, this paper proposes a puncturable signature scheme based on SM2 (SM2-PS), ensuring historical signatures' security even during key leakage. The SM2-PS scheme supports puncturing specific parts of a message, and its key puncturing operation requires only a single deletion of critical elements from a Bloom filter. Under the assumption of the elliptic curve discrete logarithm problem, the SM2-PS scheme enjoys existential unforgeability against chosen-message attacks. Performance analysis and comparisons show that the SM2-PS scheme improves computational efficiency in key generation and signature verification by up to 51.83% and 94.43%, respectively, while the signature length is only 0.156 KB.

Convolution is the core component of convolutional neural networks, and its performance significantly impacts the network's efficiency. Current convolution optimization methods focus on both computational speed and memory usage. By compactly organizing the input image into two-dimensional matrices, the MEC approach reduces the intermediate matrix's memory overhead and is a memory-efficient convolution acceleration technique. However, In the processing of large-scale inputs, generating multiple tall and narrow two-dimensional block matrices fails to fully exploit the peak performance of matrix multiplication, resulting in decreased computational efficiency. This paper proposes a convolutional optimization algorithm CMEC based on three- dimensional block matrices. First, data is acquired by sliding a three- dimensional window across the original image, and rearranging the input image and kernel into three- dimensional intermediate matrices. Further, the input block matrix and kernel matrix are multiplied in parallel, and a highly optimized matrix acceleration library is utilized to enhance the computational speed. Finally, the computational results are converted to the standard output format. The experimental results show that, compared with the MEC algorithm, the CMEC algorithm has the same memory usage of the intermediate matrix, but achieves an average performance improvement of 61% on the CPU for computing a single convolutional layer, up to 71% on the GPU, and obtains at least 50% performance improvement in the convolutional neural network.

Dengue fever is an acute infectious disease caused by the transmission of dengue virus by the main vectors Aedes albopictus and Aedes aegypti. At present, a feasible method to control the transmission of dengue fever is to release mosquitoes carrying Wolbachia to produce a CI effect with wild mosquitoes, so as to block the transmission of the disease. The competition mechanism between different mosquitoes will affect the effectiveness of releasing Wolbachia carrying mosquitoes. Therefore, in order to explore the effects of interspecific competition and mating between Aedes aegypti and Aedes albopictus on mosquito population dynamics, this paper established a population competition model to simulate the population dynamics of Aedes aegypti and Aedes albopictus under different conditions, based on the experiment and latest research results of the preferential interspecific mating between Aedes albopictus and Aedes aegypti. The global asymptotic stabilities of the trivial equilibrium point, boundary equilibrium point and positive equilibrium point are proved. The theoretical results of this study are consistent with the experimental results in the literature, that is, the high interspecific mating and remating rate of Aedes albopictus leads to its advantage in the competition and reproduction with Aedes aegypti. Understanding this mechanism will help prevent and control the vector mosquitoes. This paper helps to provide scientific guidance on the subsequent development of release strategies for Wolbachia infected mosquitoes to control the spread of dengue fever.

Ammonia (NH₃) detection plays a crucial role in various fields, including environmental analysis, air conditioning compressors, respiratory diagnostics, and the fertilizer industry. As a key concern in environmental and safety monitoring, its corresponding sensors are particularly important. Although traditional NH₃ sensors have seen improvements in detection speed, there are limitations to their functions such as high operating temperatures. This underscores the necessity to develop sensors capable of rapidly detecting NH₃ at room temperature. This study employs a liquid-phase laser ablation method to synthesize micro-nano tungsten trioxide (WO₃) materials with high oxygen vacancies for highly efficient room-temperature NH₃ sensors. The preparation method demonstrates advantages such as excellent controllability, high purity, high production efficiency, and simple equipment requirements. The synthesized WO₃ material achieves a 56% response to NH₃ at room temperature, outperforming similar sensors, showing promising potential for developing high-performance room-temperature NH₃ sensors.

An acrylate copolymer dispersant P(BA-AA-HEA) was synthesized by free radical solution polymerization using butyl acrylate (BA), acrylic acid (AA) and hydroxyethyl acrylate (HEA) as monomers. The polymer was characterized and analyzed by Fourier transform infrared spectroscopy (FT-IR), nuclear magnetic resonance spectroscopy (NMR) and gel permeation chromatography (GPC). P(BA-AA-HEA) was applied to the dispersion of ultrafine aluminum hydroxide powder particles in an epoxy resin matrix. The effects of the addition amount of P(BA-AA-HEA) on the viscosity, anti-sedimentation, stability and shear strength of aluminum hydroxide-epoxy resin composites were investigated, and compared with commercially available Y016 dispersant. The results show that both P(BA-AA-HEA) and Y016 dispersants can make the aluminum hydroxide powder particles more easily dispersed in the epoxy resin matrix, which effectively making the aluminum hydroxide-epoxy resin composite more fluidity, and the viscosity is reduced by about 60%. At the same time, compared with the commercially available Y016 dispersant, the aluminum hydroxide-epoxy resin composite prepared by the P(BA-AA-HEA) has better anti-settling performance, stability and higher shear strength. Specifically, compared with the Y016 dispersant group, the P(BA-AA-HEA) group has an excellent anti-sedimentation effect of aluminum hydroxide powder particles while maintaining the viscosity of aluminum hydroxide-epoxy resin composite at about 26 000 mPa·s, such as no obvious settlement within 7 days;the shear strength of the material increased from 9.246 MPa to 11.617 MPa after adding P(BA-AA-HEA). The results of this study are expected to be used in the industrial application of epoxy resin system formulations.

Quantum walks benefit from the superposition property of probability amplitudes, allowing them to appear on multiple paths simultaneously, thereby achieving quadratic or even exponential acceleration in the diffusion of quantum information. This study focuses on the discrete-time quantum walk (DTQW) search algorithm within the framework of an undirected graph G=(V, E). By employing unitary transformations of coin and shift operators, a stepwise framework for the DTQW search algorithm is constructed. The SKW search algorithm of DTQW is specifically applied to searching for the marked node states in a 4-node undirected graph. Through state collapse observation, the target node is retrieved probabilistically with a success rate of 1/4. Results indicate that when n sufficiently large quantum systems maintain strong entanglement, quantum walks can transition to classical random walks. The paper further elaborates on the quadratic speedup mechanism of the DTQW search algorithm under bidirectional migration conditions.

This paper uses qualitative and quantitative empirical research methods to analyze the policy effects of the Hydrogen fuel cell vehicle industry. To deeply explore the main factors that affect the development willingness of enterprises in terms of policy understanding, policy adaptability, policy implementation effectiveness, and policy involvement, the SEM model is used to analyze the influencing factors and their mechanisms in depth. Research has found that ① the effectiveness of policy implementation is the most significant direct factor affecting the willingness of enterprises to develop, and the introduction of policies has a direct support and impact effect on enterprise development;② the adaptability of enterprises to the introduction of policies for the hydrogen fuel cell industry is not optimistic;③ the current government support policies are not ideal for supporting enterprises;④ the overall involvement score of enterprises in support policies is average;the level of importance attached by enterprises is deeper than their level of understanding, and their understanding of policies is not high, with only 18.18% indicating "very satisfied". Therefore, based on these research findings, it is proposed that the government should focus on improving policy adaptability and policy involvement, pay attention to enterprise issues, optimize policy rationality, adjust policy orientation in a timely manner, and strengthen policy publicity and guidance, among other highly targeted policy recommendations.

The establishment and optimization of ecological networks in strategic locations is a useful strategy to enhance the connection of regional landscape structures and the general functioning of ecosystems, taking into account the spatial distribution and connectivity of ecosystem service values. There isn't enough research being done in this field right now. The study used land use data from 2000 to 2020 to determine the future ecosystem service value of the Nanling Mountains region, identify high-value locations, and maximize the value of the ecosystem network. It was based on the PLUS-InVEST model and the “source-corridor” paradigm. The ecological network in the Nanling Mountains region was established and optimized by identifying high value locations, and the future value of ecosystem services in the Nanling Mountains region was computed using land use data from 2000 to 2020. The findings indicate that: The typical ecosystem service value of the region exhibits a general fluctuating and decreasing trend, with the lowest value predicted for 2030;the landscape composition is relatively stable within the total area of about 114 000 km² of the Nanling Mountains area, with woodland as the dominant type;with the ecological source area in a regulated distribution and more fragmented edges, the ecological network of the Nanling Mountains region exhibits a spatial distribution that is dense in the west and sparse in the east. The study elucidates the critical domains for ecological network optimization, derived from the goal of giving priority to the preservation of ecological pinch points and emphasizing the rehabilitation of ecological barrier points. The study's findings offer evidence in favor of enhancing the ecosystem service network's spatial structure and creating a pattern of long-term ecological security.

As an effective mode of industrial spatial organisation, industrial parks have a special role in driving regional economic growth. This study analyzes the basic characteristics of the 111 industrial parks in the Pearl River Delta, and explores the mechanisms of different industrial parks on county economic growth by type. The results show that: ①The characteristics of industrial parks in the Pearl River Delta show that the construction of industrial parks is conducive to promoting the economic growth of counties;however, the intensity of the role of different levels of industrial parks on the county economy has a decreasing trend, in the order of national,provincial,important level industrial parks.②The mechanisms by which industrial parks with different levels of innovation drive county economic development are different, and are explained as the result of three different effects: multiplier effect, agglomeration effect and spillover effect. Industrial parks with low levels of innovation drive the county's economic development through the regional multiplier effect of providing employment for the county;industrial parks with high levels of innovation drive the county's economy through the technology spillover effect, but it is relatively weak;and industrial parks with medium levels of innovation have no clear role in the competition for local resources, as the negative effect of competition for local resources cancels out with the positive effect of external spillovers.