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.

In order to improve the catalytic activity of catalysts for the catalytic oxidation of CO, a batch of xMn / CeO2-L ( nanowire) catalysts with different manganese ( Mn) loading amounts were prepared by hydrothermal method and wet impregnation method. The effect of different Mn loading amounts on the catalytic performance of cerium based catalysts was investigated. According to the evaluation of CO activity, 0. 75Mn / CeO2-L catalyst showed the best catalytic performance ( T50 = 129℃ , T90 = 179 ℃ ) , which was about 221 ℃ and 171 ℃ lower than that of CeO2-L catalyst, significantly improving the CO catalytic activity of cerium based catalysts. X-ray powder diffraction( XRD) , N2 adsorption desorption determination ( BET) , X-ray photoelectron spectroscopy ( XPS) ,Raman and H2 temperature reduction procedure ( H2-TPR) characterization were carried out. There sults showed that 0.75Mn / CeO2-L catalyst had higher oxygen vacancy content, indicating that an appropriate amount of Mn loading could enhance the oxygen vacancy of CeO2-L catalyst. In addition, the electrical conductivity of the catalyst was tested by the four-probe method, and it was found that there was a linear correlation between the electrical conductivity of the catalyst and the catalytic activity ( R2 ( T50 ) = 0.998 and R2 ( T 90) = 0.998) and the oxygen vacancy ( R2 ( I D/ I F2g) = 0.999) . The results show that for pure CeO2-L catalysts, loading Mn can effectively increase the electrical conductivity of xMn / CeO2-L catalysts, thereby promoting the ion migration rate on the catalyst surface and enhancing the catalytic activity of xMn / CeO2-L. This experiment is conducive to the realization of low-temperature and high-efficiency catalysis in the vehicle exhaust gas treatment system and reducing CO pollution.

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.

Since the implementation of policies such as the “ Ten Rules of the Atmosphere, ” particulate matter like PM2. 5 has been better controlled in China, while ozone concentration has shown a rising trend, and has become an important pollutant in China after PM2. 5 . Given that high temperatures can further catalyze ozone production, this study examines the characteristics of temperature and ozone concentration and their interrelationship in South China. Using temperature data from the ERA5 reanalysis data ( ERA5Land Hourly) provided by the European Centre for Medium Range Weather Fore casts ( ECMWF) and ozone concentration data from ground level air quality monitoring stations, we investigated the spatial and temporal distribution patterns of temperature and ozone, their correlation, and the variation of ozone concentration with distance from the coast in 2015 and 2020. The findings reveal the following: ①Spatially, both temperature and ozone concentrations exhibit spatial autocorrelation, with distinct cold and hot spot patterns; temporally, both variables display seasonal variations, peaking in summer and fall and decreasing in winter and spring. ②A positive correlation exists be tween temperature and ozone concentration, with the relationship being most pronounced on an hourly scale ( r = 0.97 in 2015 and r = 0. 96 in 2020) . ③Ozone concentration varies with coastal proximity, peaking within 10 - 50 km of the coast and displaying a fluctuating decline in the 50 - 300 km range.④Ozone suppression occurs at a cutoff temperature of 28 ℃ in South China. This study provides valuable insights for ozone mitigation and regional environmental protection efforts by exploring the spatial temporal characteristics of temperature and ozone concentration, their correlations, and the influence of coastal distance on ozone levels.

This article mainly utilizes the recursive relation of tensor product decomposition formulas for all irreducible complex representations of a dihedral group, and obtains the adjoint subring of the complex representation ring over r( Dn ) . By studying the indecomposable Z+-sub-bimodules over the adjoint subring, the universal grading structure of the fusion ring r( Dn ) is characterized.

Counties are an important component of China's urban system and a key support for the integrated development of urban and rural areas. Changes in the number and structure of rural populations are of great significance for promoting the construction of new urbanization and rural revitalization. This paper takes the counties in Guangdong Province as the research object, uses statistical data such as the “Guangdong Rural Statistical Yearbook”, and employs methods such as multi-scale geographically weighted regression (MGWR) and geographical delection to study the spatio-temporal evolution of rural population distribution in Guangdong Province's counties from 2010 to 2020 and its influencing factors. The results show that: ① In terms of time, the changes in the rural population of the entire province present a dynamic trend of first increasing and then decreasing, which can be divided into a period of sustained growth (2010-2014) and a period of significant decrease (2014-2020); ② Spatially, the distribution of rural population density in Guangdong Province's counties generally shows a spatial pattern of “higher in the Pearl River Delta and eastern and western Guangdong, while lower in northern Guangdong”, and the decrease and growth of rural population present a spatial pattern of “mainly growth in the Pearl River Delta and decrease in eastern, western and northern Guangdong”; ③ The factors influencing the distribution of rural population are diverse. Per capita GDP and industrial structure upgrading have a negative effect on the distribution of rural population, while the level of medical services and the total value of agricultural production have a positive impact. The effects of labor productivity and grain output change over time; ④ The influencing factors of rural population distribution in counties show an enhancing effect through two-way interaction, and the level of medical services and the total value of agricultural production are the dominant interacting factors and show differentiation over time. This study not only enriches the theoretical and empirical research on the dynamic changes of the rural population in China, but also provides a scientific basis for promoting new urbanization and rural revitalization in a targeted manner.

Metal organic frameworks ( MOFs) , with their diverse chemical structures, exhibit broad application potential in fields such as gas storage and separation, catalysis, and drug storage and de livery. With the rapid expansion of MOFs varieties and application domains, traditional experimental methods and molecular simulations can no longer sufficiently evaluate the performance of new MOFs in a short time. Given the vast number of MOFs and the enormous amount of data related to their structures and properties, integrating machine learning methods into the design and development of MOFs will undoubtedly bring significant benefits. By constructing machine learning models, the complex structure property relationships of MOFs can be effectively elucidated, accelerating the performance prediction and material design processes. In this review, we comprehensively summarize and analyze research on MOFs adsorption and separation utilizing machine learning methods. First, various MOFs databases, feature descriptors, algorithms, and evaluation metrics suitable for machine learning work flows are discussed. Next, the role of machine learning in facilitating high throughput computational screening and accelerating research on the adsorption and separation of gases such as CH4 , CO2 , and H2 in MOFs are explored. Finally, this paper discusses the opportunities and challenges faced by ma chine learning in supporting big databased computational simulations of MOFs gas adsorption, separation, and storage. Through this comprehensive review and analysis, researchers can better understand and apply machine learning and big data mining to accelerate the design and development of MOFs, providing new research directions and technical support for related fields.

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.

It is critical to predict stock price fluctuations accurately in financial investment. Stock price fluctuations are influenced by multiple factors and have nonlinear characteristics, making traditional linear prediction methods often ineffective. We first selected 5 representative stock indices and 5 large-cap stocks of A-shares as samples, used their daily closing price data from 2020 to 2023, to map their price time series to a high-dimensional space by using the phase space reconstruction (PSR) technique, and reveal their chaotic characteristics. Then, based on the deep learning method Gated Recurrent Unit (GRU), we developed a PSR-GRU prediction method to generate stock price prediction results. Finally, we compared the predicted results with those obtained from classical prediction models. We found that stock price fluctuations have chaotic characteristics, and the PSR-GRU exhibits superior performance in stock price prediction.

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 studies the automorphism group of the complex representation ring r( D4 ) of the dihedral group D4 of order 8 and all the ring automorphisms of r( D4 ) are computed. It is shown that the automorphism group of r( D4 ) is isomorphic to the direct product of the symmetric group of degree 3 and the cyclic group of order 2.

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.

Hyperlipidemia, as a significant risk factor for atherosclerotic cardiovascular disease, has contributed to the increasing global burden of cardiovascular diseases, making it a major public health issue worldwide. Traditional lipid-lowering medications such as statins and fibrates have limitations, including side effects and poor tolerance, which makes the development of novel, safe, and effective drugs imperative. Peptide-based drugs, with their high bioavailability, potent activity, low toxicity, and ability to regulate lipid metabolism through multiple targets, have emerged as a new direction in lipid-lowering drug research. Lipid-lowering peptides are derived from a wide range of sources, including plants, animals, and microorganisms, and can be classified into natural and synthetic peptides. These peptides exert lipid-lowering effects through various mechanisms, such as inhibiting cholesterol synthesis, promoting lipid metabolism, and suppressing lipid absorption, with some peptides exhibiting multiple mechanisms of action. In recent years, various peptide drugs have entered the market, with PCSK9 inhibitors, such as evolocumab, demonstrating significant efficacy in clinical applications. Additionally, many novel therapeutic peptides are currently in preclinical and clinical development stages, showing promising prospects for future advancements.

In the contemporary emphasis on maintaining social stability and industrial safety, the issue of low-temperature icing, induced by environmental factors affecting transportation, large-scale machinery, and power transmission lines, stands as an urgent challenge requiring immediate attention. Over the past few years, the rapid development of traditional Superhydrophobic Surface(SHBS) anti-icing coatings has been notable; however, these coatings have also revealed significant limitations, particularly their tendency to lose hydrophobic and anti-icing properties under extreme conditions. In contrast, Superhydrophobic(SH) coatings with photothermal effects have demonstrated sustained effectiveness in harsh environments, offering a promising avenue for further research. This paper begins by elucidating the mechanisms of surface icing, detailing the process by which liquid droplets condense on substrate surfaces. It then reviews various photothermal materials and traditional methods for preparing SHBS. Subsequently, the paper illustrates several composite preparation techniques for SHBS with photothermal effects through specific examples. Finally, after a concise explanation of the photothermal SH anti-icing mechanism, the paper highlights the current limitations of photothermal SH anti-icing surfaces and outlines potential directions for future research.

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.

The 6xxx (Al-Mg-Si) series aluminum alloys, with moderate strength and good formability, are widely used in automotive structural parts. As vehicle products evolve and safety demands grow, traditional 6xxx extrusions can no longer meet performance requirements. Adding transition elements (retained in α-Al matrix via rapid solidification during casting and dispersed via high-temperature homogenization) effectively enhances alloy properties. Here, a 6xxx alloy extrusion was developed by modifying 6061 composition with 0.1 wt.% Vanadium (V), using three-stage homogenization, hot extrusion, and aging. Microstructure and mechanical properties were characterized via SEM, EBSD, and tensile testing. Results show the original alloy has coarse recrystallized grains, while the V-added alloy features fine recrystallized and partially recrystallized fibrous grains: core recrystallization fraction decreases from 62.7% to 29.2%, and average grain size refines from 93 μm to 11.8 μm. Homogenization spheroidizes needle-like β-Al(FeMnCrV)Si to spherical α-Al(FeMnCrV)Si phases. The V-added T6 extrusion exhibits +31 MPa UTS, +20 MPa YS, and +6.1% elongation vs. the original. Reduced extrusion speed causes near-surface abnormal grain growth in the V-added alloy, decreasing YS to the original level but maintaining higher UTS. This work demonstrates vanadium addition and homogenization effectively refine microstructure, while emphasizing extrusion process optimization to balance mechanical properties.

All-dielectric nanostructures support unique electromagnetic resonance modes in visible band, and have important application prospects in the fields of directional light scattering and nonlinear optical response. The nanostructures with various morphologies of high refractive index silicon (Si) have become important basic components of nanostructures in this field. The imaginary part of the refractive index of titanium dioxide (TiO₂) nanostructures with medium refractive index and wide band gap is close to 0 in visible band, and the extremely low absorption property leads to stronger scattering than silicon. To this end, TiO₂ nanospheres with different sizes were prepared by femtosecond (fs) laser-induced backward transfer method, and the regulation of size-dependent resonance mode in visible band was studied. Based on Mie theory, the multipole resonance mode was analyzed, and it was found that the magnetic dipole (MD) and electric dipole (ED) characteristic peaks of TiO₂ nanospheres of a hundred nanometers in diameter were broadened and overlapped, resulting in a mode coupling between them, and the ED resonance mode becomes not obvious, while the high-order magnetic quadrupole (MQ) resonance mode has the characteristics of narrow bandwidth. The numerical simulation results show that the MQ resonance mode has a stronger local field enhancement factor. Controlled tuning of size-dependent resonant modes can be applied to nanoscale displays and photonic devices.

The vertical column densities ( VCD) of tropospheric formaldehyde ( HCHO) observed by satellites have become an important means for studying the spatiotemporal evolution of volatile organic compounds ( VOCs) at the regional scale. Exploring the spatiotemporal evolution of HCHO VCD in the troposphere is of great significance for the coordinated control of PM2. 5 and O3 pollution in the Guangdong-Hong Kong-Macao Greater Bay Area ( GBA) and even in Guangdong Province. To explore the spatiotemporal evolution of tropospheric HCHO VCD in the GBA, this research processed Level 2 formaldehyde observations from Ozone Monitoring Instrument ( OMI) using a self-developed oversampling algorithm to achieve kilometer-level monitoring of tropospheric HCHO VCD in the GBA from 2013 to 2022. The influencing factors of tropospheric HCHO VCD in the GBA were diagnosed from the perspectives of natural and anthropogenic sources. Research has found that the HCHO VCD of GBA showed a rising trend from 2013 to 2022. Compared with 2013, HCHO VCD increased by 11 3% in 2022. Low HCHO VCD are mainly distributed in the surrounding areas of the GBA with higher terrain and coastal areas, while high VCD are mainly located in the central area of the GBA, with Guangzhou, Foshan, Dongguan as the high value center region, as well as parts in Zhaoqing, Huizhou, and Jiangmen. The average VCD in GBA shows a periodic pattern of winter < spring < autumn < summer. Cities such as Zhaoqing, Dongguan, Guangzhou, and Foshan exhibit winter < spring< autumn < summer, while coastal cities including Jiangmen, Zhongshan, Shenzhen, Hong Kong, and Zhuhai present winter < spring < summer < autumn. The increase in vegetation in the GBA holds a positive contribution to the rise in tropospheric HCHO VCD, but it is not very significant. The correlation coefficient between nighttime light radiation intensity and tropospheric HCHO VCD is not high, while the annual GDP of GBA shows a significant positive correlation with tropospheric HCHO VCD, indicating that GDP growth plays an important role in the ascension of tropospheric HCHO VCD.

To investigate the vibration mitigation performance of the Variable Friction Pendulum Tuned Mass Damper (VFP-TMD) for high-rise structures, the structure is modeled as an Euler-Bernoulli cantilever beam to accurately characterize its dynamic properties. This study presents the configuration of the VFP-TMD device and experimental validation is conducted through tests on variable friction pendulum bearing. A model of the VFP-TMD system subjected to wind-induced excitation is proposed. The optimal parameters of the VFP-TMD are obtained based on the fixed-point theory, and the optimal parameters corresponding to different VFP-TMD mass ratios are provided and analyzed parametrically. A case study involving a landscape tower is performed to analyze wind-induced vibrations. The research results indicate that the proposed optimal parameters achieve superior vibration reduction effects for this system, yielding a peak damping ratio of 51.31% and an average damping ratio of 54.62%.

In laser soldering, the Precise control of the temperature of the weld joint is critical to the quality of the weld. Existing soldering temperature control for laser soft brazing is realized based on Proportional-Integral-Differential ( PID) control. The traditional PID control method cannot effectively deal with the problem of brazing material specific heat capacity and laser absorption rate changing with temperature due to its fixed parameters. In the process of using the traditional PID to control the temperature, the response speed and control accuracy of the system are reduced, the error value between the actual output temperature and the target temperature is large, and the output power fluctuation is also large. For this reason, this paper proposes a temperature control method based on Model-Predictive Control ( MPC) , which can dynamically adjust the control parameters and reduce the hysteresis or overshoot of PID when facing temperature changes by predicting the future temperature changes using a process model. Experimental results show that the MPC method significantly improves the temperature control accuracy of the solder joints, with a temperature error variance value of 32% of that of PID control and a maximum absolute error of 67% of that of PID control. These improvements effectively enhance the wettability and fluidity of the brazing material, improve the uniformity and solder quality of the solder joints, and significantly enhance the yield of laser soft brazing.

In recent decades, due to the intertwined effects of multiple factors such as global warming and intense human activities, the surface processes of global river basins have changed significantly. River geomorphologic changes are an important indicator of the long-term evolution of rivers. However, most current studies focus on a single aspect in river geomorphologic changes; systematic analysis of river dynamics from a macro perspective has not received enough attention. This study designed a new river geomorphologic change index, superimposing and analyzing the river changes in the Pearl River Basin from different periods, thereby revealing the spatiotemporal dynamics of the rivers in the Pearl River Basin. The study shows that: ① The stability of river geomorphology in the Pearl River Basin is relatively high, and the stability is gradually increasing with the intervention of human activities; ② Between 1995 and 2015, the Pearl River Basin experienced the greatest increase in average river area and the smallest decrease, indicating the most dynamic changes in river morphology during this period; ③ the stability of large rivers in the Pearl River Basin is higher than those of medium-sized rivers; ④ The stability in the middle and lower reaches of the Pearl River Basin is relatively high, but is low in the upper reaches. The Hejiang tributary basin reported the highest stability, while the Beipanjiang tributary basin reported the lowest stability. This study emphasizes the key role of retaining wide river corridors and restoring natural riverbed geomorphology for maintaining natural landforms, and puts forward suggestions for optimizing basin management and disaster prevention and mitigation.

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.

The survivor average causal effect (SACE) can be used to measure the differential impact of receiving different treatments on subjects who would survive under any treatment condition. It represents an important area of research in causal inference. Since the samples of subjects who would always survive in both the treatment and control groups cannot be directly observed, SACE is typically unidentifiable, allowing only for the estimation of its bounds. In the literature, mainstream methods for deriving sharp bounds on SACE rely on multi-parameter linear programming, generating closed-form solutions by enumerating all vertices of the constraint polyhedron in the dual problem. If monotonicity and stochastic dominance conditions are not satisfied, the enumeration method cannot be used to solve this multi-parameter linear programming problem. This paper addresses the sharp bounds of SACE within the principal stratification framework, considering “truncated by death”, stable unit treatment effect, and ignorability assumptions. The optimization problem is solved based on polynomial equations derived from first-order Karush-Kuhn-Tucker (KKT) conditions. The LaLonde dataset from the National Supported Work Demonstration (NSW) project in the United States was empirically selected to calculate the sharp bounds of the SACE under complete covariates for the “always-survivor”.

The Three Gorges Reservoir area is the hardest hit area for landslide occurrence in China, and the dams water storage and flood discharge accelerated the slope activities along the Yangtze River and its tributaries, reactivating a large number of ancient landslides. The Songjiawuchang landslide occurred in Dongdukou Town, Badong County. In this paper, the time series deformation of this land slide was obtained by collecting 15 views of ALOS2 / PALSAR2 images from April 2020 to September 2021, and the area was divided according to the stratigraphic distribution and the slip pattern, with an emphasis on analysing the characteristics and causes of the slip. In addition, the reliability of the de formation results was verified by statistical stability region information. The results show that: ① During the monitoring period, the Songjiawuchang landslide showed an ‘ upper section middle section lower section stepped slip, with a bias towards the right side, and the largest deformation appeared in the right side of the middle section ( Q2R) , with a rate of - 193 9 mm / yr. ② Through the extraction of the profile lines and feature points, the temporal and spatial morphology of the landslide deformation was further explained, and it was found that the stepped slip was consistent with the stratigraphic distribution; ③ Using the Pearson correlation test, it is concluded that the overall slip rate of the landslide is jointly affected by the cumulative precipitation and water level changes.

Abstract: Endocrine disruptors are difficult to remove from wastewater due to their stable chemical structure, and their continuous release in the aqueous environment remains a challenge of great concern in water treatment. In this paper, a copper-doped graphene like catalyst ( Cu@ IANC) synthesized from algae was constructed with Cu-centered electron-rich regions and Cu-centered electron-poor regions. In the reactive aqueous solution containing bisphenol A ( BPA) and 10 mM H2O2 , the degradation of BPA by Cu@ IANC exhibited excellent activity and stability. In the reactive aqueous solution, BPA was complexed in the electron-poor region on the Cu@ IANC surface by π-π and hydrogen bonding, while H2O2 was adsorbed in the electron-rich region on the Cu@ IANC surface, resulting in the formation of a multipoint adsorption pattern on the Cu@ IANC surface. In this adsorption mode, BPA was electronically delocalized by the Cu-π electrostatic force and captured by H2O2 to generate hydroxyl radicals ( · OH) . The generated · OH was free in aqueous solution to attack BPA and its intermediates. The synergistic interaction of H2O2 and Cu-π electrostatic forces over biochar-based Fen- ton-like catalysts is a low-cost option for the effective degradation of environmental endocrine.

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.

Anti-homomorphism is the map reversing operation which plays the same role with homo- morphism, it is essential in the study of structures and properties of algebraic systems. According to the isomorphism theorems of homomorphism in rings, this paper parallels the anti-homomorphism to the structure of ring theory and gives isomorphism theorems under anti-homomorphism in order to characterize more results about the structure and properties of rings.

People′s health is the foundation of social civilization and progress, and an important symbol of national prosperity and strength. The Party and the country prioritize the people′s health in their strategic development, proposing the ″Healthy China″ strategy. In August 2016, the Political Bureau of the CPC Central Committee held a meeting to review and adopt The Outline of the Healthy China 2030 Plan, which has made institutional arrangements to better protect people′s health at present and in the future. However, there is still a lack of theoretical interpretation and practical research on the construction of a Healthy China from a geographical perspective. From the perspective of Chinese traditional culture, this paper puts forward the basic connotation of Healthy China construction, takes man-land relationship, spatial analysis and regionalization theory as the core theoretical basis of geography serving Healthy China construction. Based on the outline of the Healthy China 2030 Plan, an evaluation index system for the construction of Healthy China has been established with reference to the health evaluation indicators formulated by the World Health Organization, including five dimensions: health status, health risk, health service, health system and healthy life. Based on this, the progress of Healthy China construction in China is evaluated in accordance with the Sustainable Development Goals of the United Nations, and a geographical path of Healthy China construction is explored. This study has a positive significance for the planning of Healthy China according to local conditions, fully reflecting the scientificity, rationality and fairness of the construction, and provides a scientific basis for China to complete the goals of the program within the specified time, achieve the United Nations Sustainable Development Goals and the requirements of the World Health Organization, and realize the general goal of comprehensively improving the health of the people.

Based on the development of Xinyang City, Henan Province, from 2010 to 2020, this study adopts a factor integration perspective. It constructs a multi-dimensional coupled system—comprising the Patch-generating Land Use Simulation (PLUS) model, a population flow model, a Principal Component Analysis-Back Propagation (PCA-BP) model for land scale prediction, and a GDP prediction model—to simulate the flow and integration patterns of key factors such as talent, capital, and land in 2035. Three scenarios were established: a baseline scenario, an economic priority development scenario, and an agricultural protection development scenario. The results indicate that: under the economic priority scenario, the proportion of urban land is the highest, the population is concentrated in urban areas, and GDP growth is the fastest. Under the agricultural protection scenario, cultivated land is effectively protected, the scope of population outflow is the most extensive, and economic growth is more balanced. Under the baseline scenario, urban-rural development is relatively moderate. The rational allocation of urban-rural factors is crucial to rural revitalization, and policy interventions significantly affect the direction and efficiency of factor flows. By employing machine learning methods to explore path selection and scenario simulation for rural revitalization, this research not only broadens the theoretical paradigms and policy support mechanisms for the field but also provides methodologies and findings that can contribute to the formulation of urban-rural development policies in other regions.

The Tiered Medical Treatment System (TMTS) plays a pivotal role in exploring the implementation pathways of the Healthy China strategy. Under TMTS, the patterns of residents seeking medical care can be categorized into three types: receiving effective treatment at primary healthcare institutions; undergoing initial diagnosis at primary healthcare institutions but requiring referral to higher-level hospitals; or directly choosing higher-level medical facilities for treatment. To achieve a comprehensive consideration of these three patterns, this study introduces two parameters, the primary healthcare rate (α) and referral rate (β), based on a two-step floating catchment area method. Taking Guangzhou city as a case study, this research investigates residents′ patterns of seeking medical care under TMTS and their impact on spatial accessibility to healthcare services, aiming to provide references for optimizing medical resource allocation. The results indicate that when the primary healthcare rate α=0, overall medical accessibility is the worst; however, when α=0.1 and β=0.05, overall medical accessibility reaches its highest level. Under a fixed primary healthcare rate α, lower referral rates contribute to higher overall accessibility. Overall, residents′ medical accessibility in Guangzhou′s districts exhibits a multi-layered spatial pattern centered on the main urban area and decreasing outward toward peripheral areas. The study finds that the TMTS improves the utilization rates of healthcare institutions at all levels and enhances the accessibility and convenience for residents seeking medical care. Additionally, this system contributes to promoting the equitable allocation of medical resources. These findings provide crucial theoretical support and policy recommendations for optimizing the referral mechanism and resource allocation within TMTS.

This paper focuses on the long wavelength limit for the Euler-Poisson system arising in plasma including three species in a three dimensional case. The goal of this study is to deduce rigorously the modified Korteweg-de Vries-ZK(mKdV-ZK) equation, under the Gardner-Morikawa transform ε^1/2(x₁－Vt)→x₁,ε^1/2x₂→x₂,ε^1/2x₃→x₃,ε^3/2t→t, asε→0. By employing delicate energy method, we give uniform in ε estimate for the error between the mKdV-ZKequation and the Euler-Poisson system.

Solar energy has great potential as a clean energy source, but its volatility and instability limit its wide application. Phase change materials (PCMs), as efficient thermal energy storage media with good thermal management properties, can facilitate the utilization of solar energy. Sodium dihydrogen phosphate dodecahydrate (Na₂HPO₄·12H₂O) is an inorganic phase change material that is inexpensive and readily available, with good thermal conductivity and a high latent heat of phase change, but its widespread use introduces a high concentration of corrosive ions, leading to severe corrosion of the metal container. In order to better realise the application of Na₂HPO₄·12H₂O, it is particularly important to study its corrosion mechanism on metal containers and explore effective corrosion inhibition methods. In this study, we investigated the synergistic inhibition effect of benzotriazole (BTA) and thiourea (TU) composite corrosion inhibitor on the corrosion of Q235 carbon steel in Na₂HPO₄·12H₂O molten liquid. The protective mechanism of BTA and TU composite corrosion inhibitors on metal surfaces was investigated by electrochemical techniques including open circuit potentials (OCP), electrochemical impedance spectroscopy (EIS) and polarisation curves with surface characterisation methods such as scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM). The results demonstrated that the combined effect of BTA and TU markedly enhanced the corrosion inhibition efficacy. In the 24-hour immersion experiment, the composite corrosion inhibitor system exhibited the highest corrosion inhibition efficacy (98.26%), a figure that was considerably higher than the inhibition efficacy of a single corrosion inhibitor. EIS tests have shown that the corrosion inhibitors BTA and TU are effective in reducing metal corrosion by forming a dense protective film on the metal surface. The BTA300TU100 composite corrosion inhibitor has the best protective effect on the metal surface with high corrosion inhibition efficiency and thicker oxide film. For the application of inorganic phase change materials Na₂HPO₄·12H₂O in solar thermal energy storage, this study provides an effective corrosion inhibition strategy.

This investigation delves into the blow-up criteria for strong solutions of the Landau-Lifshitz-Gilbert (LLG) equation, with particular emphasis on when these solutions cease to exist. We construct a comprehensive model and derive multiple blow-up criteria, encompassing Serrin-type, Besov-type, BMO-type, and Beale-Kato-Majda (BKM) type within two- and three-dimensional spaces.

In physical engineering, due to the different materials of objects, there is an object composed of two different materials, and the structure of different areas in an object will be different. For this reason, the eigenvalue problem of two phase elliptic partial differential equation is discussed when there are two different materials in one object. In one dimension, it is equivalent to the eigen value problem of ordinary differential equation. In two dimensions, the system is transformed into one dimension eigenvalue problem by the method of separating variables. According to the characteristics of boundary conditions, the eigenvalues and eigenfunctions are obtained by using block regions.

Urban traffic congestion is one of the major challenges in modern cities. In urban traffic, drivers tend to choose the lane that seems the least congested at present because of limited vision, but this ″local optimal″ choice may lead to lower overall traffic efficiency. In order to solve this problem, this paper proposes an intelligent diversion system for urban highway and expressway. The system captures real-time video data through cameras in the traffic network, and uses Yolo and DeepSORT algorithm to accurately detect and track vehicles. These data are further mapped into a graph structure, and the graph neural network model is used to predict the lane-level traffic flow. Based on the forecast results, the system generates and updates the diversion information in real time, and recommends the best driving route to the driver through the road information board. The system has been deployed and performed reliably at the Chungang interchange section of South China Expressway in Guangzhou. Experimental data show that the system can improve the evenness of lane-level traffic flow, increase traffic efficiency, and verify the effectiveness of the intelligent diversion system.

This paper improves the weak Galerkin generalized multiscale (WG-GMS) finite element method by integrating oversampling and online adaptive techniques to solve second-order elliptic equations with high-contrast coefficients. The oversampling technique reduces errors caused by boundary conditions by expanding the sampling region for the multiscale basis functions. Additionally, the online adaptive method constructs new online multiscale basis functions based on the maximum residual, thereby providing an improved function approximation space and improving the accuracy of the numerical solution. Numerical results demonstrate that the proposed oversampling and online adaptive mixed WG-GMS finite element methods are effective in solving second-order elliptic equations with high-contrast coefficients, achieving higher accuracy in the numerical solutions.

This study examined the relationship between the seismic responses of cable-stayed bridges and the parameters of pulse-type ground motions. Based on this analysis, a simplified single-degree-of-freedom method for calculating longitudinal deck displacement was developed. The method's effectiveness was validated using various seismic inputs and bridge structures. Furthermore, the study analyzed the deck displacement response characteristics of cable-stayed bridges equipped with viscous dampers under different pulse waves and evaluated the dampers' shock-absorption performance during actual pulse-type earthquakes. The results provide a basis for rapidly determining viscous damper parameters and designing shock-absorption systems for cable-stayed bridges in pulse-type earthquake conditions.

An IRS-assisted broadcast communication system composed of a transmitter, an intelligent reflecting surface (IRS), and multiple receivers was investigated, focusing on a novel IRS phase-shift optimization scheme that does not require channel state information (CSI). Existing research on optimizing IRS-assisted communication systems commonly assumes that CSI can be obtained. However, because IRS typically contains a large number of reflecting elements, the overhead for channel estimation increases with the number of these elements, making the acquisition of CSI prohibitively costly and limiting the practical applicability of such methods. To address this challenge, a scheme is proposed that utilizes only the received signal strength observed by the receivers to optimize the IRS phase shifts, aiming to maximize the minimum received signal power at receivers. Due to the lack of CSI, the received signal power cannot be derived through analytical expressions, preventing the use of conventional convex optimization approaches. To solve this problem, the system optimization is modeled as a Markov Decision Process (MDP), and a deep reinforcement learning algorithm based on proximal policy optimization is introduced to determine the optimal IRS phase shifts. Simulation results show that the proposed scheme achieves favorable system performance.

The oxygen abundance serves as a pivotal probe for unveiling the chemical evolution of galaxies. While estimating oxygen abundance via spectral emission lines remains the most prevalent approach, significant discrepancies among different methods for the same target source introduce substantial uncertainties in abundance determination and studies of galactic chemical evolution. In this study, by utilizing observational data for HⅡ regions in the extragalactic galaxy NGC 0925, obtained with the 2.16 m telescope in the National Astronomical Observatory′s, oxygen abundances are estimated through multiple methods. We compare and quantify the estimates from the four widely used strong-line diagnostics (N2, R23,O3N2, N2O2) and the Bayesian multi-line statistical inference NebulaBayes. In the Bayesian statistical inference, we generate 27 abundance estimates by adjusting different emission-line combinations. The observed spectral emission lines include seven features: [O Ⅱ] λ3727, [O Ⅲ] λ5007, [N Ⅱ] λ6583, [S Ⅱ] λ λ6717, 6731, Hα, and Hβ. Results demonstrate that the mean oxygen abundance derived from all methods is approximately 8.3 (in 12+log(O/H)), with the maximum and minimum estimates 9.068 and 7.179, respectively. Comparative analysis reveals that the Bayesian method exhibits strong consistency with the N2 index (12+log(O/H)~8.36 with the difference~0.085 dex) when adopting all the seven emission lines; the R23 method (12+log(O/H)~8.112) lead to the maximal difference (0.33 dex). Among the seven lines, [O Ⅱ] λ3727 and [N Ⅱ] λ6583 emerge as critical diagnostic features for oxygen abundance determination. Absence of them induces substantial difference (|Δ| > 0.3 dex), disrupts ionization equilibrium constraints, skews posterior probability distributions toward extreme values, and significantly enlarges uncertainty ranges. Conversely, exclusion of non-critical lines such as [S Ⅱ] λ λ6717, 6731 only causes subtle differences (|Δ| ≤ 0.1 dex) with upper and lower limits equal in uncertainties. These findings provide observational benchmarks for refining oxygen abundance calibration methodologies. Based on the analysis, we suggest prioritizing spectroscopic coverage of [O Ⅱ] λ3727 and [N Ⅱ] λ6583 in abundance determinations, coupled with Bayesian multi-line statistical constraints to reduce systematic errors. The results in this work offer methodological guidance for constructing high-precision models of galactic chemical evolution.

Pedestrian walking behavior exhibits strong subjectivity, and the dynamic response of footbridges under random crowd loading has attracted widespread attention. This study considers subjective behaviors in pedestrian walking, such as following, overtaking, and avoidance, and establishes a pedestrian flow model using Cellular Automata. Based on the modal superposition method, an efficient computational approach for human-induced vibration response is developed. The variation of resonant response with crowd density and the influence of bridge frequency on the most critical crowd density are analyzed. The results indicate that: ① At high crowd densities, pedestrian step frequency may decrease, causing the frequency of walking loads to deviate from the natural frequency of the bridge. As a result, the resonant response does not necessarily increase with higher crowd density; ② Under high-density crowd conditions, attention should be paid to the impact of the second harmonic of walking forces on bridge vibration response, as it may induce significant resonant responses in higher-frequency modes.