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.

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.

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.

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.

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.

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.

Based on the dual-system theory, this study explores distinct categories of adolescent self-control and their relationship with smartphone addiction. A random sampling method was used to survey 2 203 middle school students on self-control and smartphone addiction. Latent profile analysis (LPA) was employed to classify self-control types and examine their associations with smartphone addiction. Adolescent self-control was categorized into three groups: Low Control-Low Impulse Group (6.49%): scored lowest on problem-solving, future time perspective, impulsivity, distractibility, and low delay of gratification;High Control-Low Impulse Group (40.22%): scored highest on problem-solving and future time perspective, with low impulsivity, distractibility, and delay issues; Moderate Control-High Impulse Group (53.29%): scored intermediately in problem-solving and future time perspective, but highest in impulsivity, distractibility, and low delay of gratification. This group exhibited significantly higher smartphone addiction scores compared to the others, reaching clinically addictive levels. Distinct self-control profiles are critically linked to smartphone addiction, with high impulsivity and insufficient self-control significantly increasing addiction risk.

To address the low material handling efficiency of Automated Guided Vehicle Systems (AGVS) in hot pressing workshop, a simulation model based on a unidirectional guided network layout was developed, using an automotive brake friction material enterprise A as a case study. First, task allocation was carried out under the original AGVS scheduling strategy, and offline path planning was performed using the A star algorithm. Results showed that the average transport distance per AGV task was reduced by 23.64% compared with pre-planning, thereby verifying the effectiveness of path optimization. On this basis, the AGVS scheduling strategy was further optimized by dynamically assigning tasks according to the distance between AGV locations and task origins, adopting task-by-task cyclic assignment and the Hungarian algorithm for concurrent tasks, and redefining the rules for AGV return after unloading. Simulation results indicate that the optimized strategy effectively reduces the average transport distance and task completion time per AGV, while lowering production costs. This study provides valuable insights for improving AGVS transport efficiency and advancing scheduling optimization in intelligent manufacturing workshops.

Conducting shallow structure tomography in Hong Kong is of great significance for engineering construction, urban underground space utilization, and geological disaster prevention. In this study, we deployed a linear array of 48 node seismometers at a construction site in northern Hong Kong and collected ambient noise data for about 2 days. The effects of different stacking durations and stacking methods on the Noise Cross-correlation Function (NCF) were tested, indicating that the signal-to-noise ratio of NCF can be effectively improved by considering weighted methods during short-time stacking. We used the passive source-based Multi-channel Analysis of Surface Wave (MASW) method to extract the Rayleigh wave dispersion curve and inverted it to obtain the two-dimensional S-wave profile of the test site. Our results demonstrate that shallow S-wave tomography based on ambient noise data can quickly, safely and non-invasively constrain shallow structures, showing great potential for underground engineering applications.

The current study examined parent-child interactions and positive youth development (PYD) among 703 rural left-behind children (grades 3~6) in Meizhou City using self-report questionnaires. Latent profile analysis (LPA) was employed to explore the subcategories of parent-child interaction and their predictive effects on positive development. The results revealed that: ① left-behind children could be classified into three distinct subgroups based on parent-child interactions: the “low parent-child interaction group” (28.59%), the “moderate parent-child interaction group” (49.64%), and the “high parent-child interaction group” (21.76%); ② children in the “high parent-child interaction group” scored significantly higher on the overall PYD score and its five dimensions compared to the other groups. These findings not only validate the applicability of latent profile analysis in this study but also highlight the differential impact of varying levels of parent-child interactions on the positive development of left-behind children. The results provide important insights into the latent profile specificity of parent-child interactions among rural left-behind children and lay a theoretical foundation for developing differentiated intervention strategies. This study has significant academic value and practical implications for advancing research on the mental health of left-behind children and promoting relevant interventions.

Under the geological conditions influenced by the interaction between water-rich sand layers and the Pearl River system, seepage in the retaining structures of deep foundation pits adjacent to the river frequently occurs, leading to incidents such as ground collapse, pipeline subsidence, and fractures. These issues severely hinder project development progress and jeopardize the safety of the surrounding environment. This paper analyzes the causes of localized leakage in a deep excavation supported by secant pile walls under the water-rich sandy stratum conditions adjacent to the Pearl River in Tianhe District, Guangzhou, using practical case studies. Based on factors such as excavation depth and available working space at the top of the pit, a series of leakage control measures were implemented. These included vertical surface grouting, local excavation, inter-pile oblique grouting consolidation, steel plate sealing, enhanced shotcreting with mesh reinforcement, and rapid bottom sealing. These measures ensured the successful completion of the underground construction phase and can serve as an engineering reference for other similar projects.

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.

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.

Accurate prediction of long-term settlements, particularly post-construction settlements, of soft clayey soil has also been a challenge in geotechnical engineering. Terzaghi's one dimensional consolidation theory does not consider soil creep, hence it fails to accurately predict the long-term settlement. There is currently no consensus on how to account for soil creep when calculating settlements of soft soil. Some scholars advocate that there is no need to consider the influnce of soil creep during the primary consolidation and there exists a unique relationship between the end-of-the-primary-consolidation (EOP) void ratio and vertical effective stress (Hypothesis A). While other scholars believe that soil creep does occur during and after primary consolidation, and the EOP void ratio depends on the primary consolidation duration (Hypothesis B). Recently, more and more scholars have proven the rationality of Hypothesis B, and settlement calculation methods based on Hypothesis B have also been adopted by Canadian and European codes. However, most codes of practice involving settlement calculations in China are still based on Hypothesis A. This paper selects Mesri's settlement/compression calculation model, Yin-Graham elastic viscoplastic model and Soft Soil Creep model, MIT-SR model, to compare and analyze their elaboration, theoretical framework and main formulas. We hope to take this opportunity to enlighten the thinking of geotechnical practitioners on the time effect and settlement calculation of soft soil. At the end of the paper, Yin's Simplified Hypothesis B method for settlement calculation is introduced along with its application, further demonstrating its validity.

As the core driving force of urban development, the spatial distribution and quantitative changes of population are of key significance to urban planning. Based on the GIS center of gravity model, grey GM(1, 1) model, BP neural network and GA-BP neural network, this study used the year-end permanent resident population data of Guangzhou City from 2010 to 2024 to explore the evolution path of population center of gravity and the future population number of Guangzhou City. By comparing the three forecasted population models, it was found that GA-BP neural network had the best prediction effect and predicted the population in 2035 accordingly; ① The results show that the population center of gravity in Guangzhou City shifted to the southeast from 2010 to 2024, with the largest shift from 2020 to 2024 and will continue to shift to the southeast in the future; ② It is estimated that by 2035, the population of Liwan, Yuexiu, Huangpu and Conghua will be basically stable, the population of Haizhu, Tianhe and Baiyun will decrease, and the population of Panyu, Huadu, Nansha and Zengcheng will increase; ③ The central urban area needs to continue to relieve the high-density population, and Nansha and Panyu should prevent the risk of “separation of industry and city” and simultaneously support public service facilities. The research results can provide a scientific basis for the territorial spatial planning and policy formulation of Guangzhou City, help to enhance the city's competitiveness and sustainable development capacity, and provide a reference for the high-quality development of urbanization in China.

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.

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.

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.

The advancement of computer technology faces dual challenges posed by the physical limits of silicon-based chips and the energy efficiency bottleneck of von Neumann architectures, driving the shift toward emerging paradigms such as biomolecular computing. Deoxyribozyme (DNAzyme), as essential tools for biocomputation, have been largely confined to single-layer logic operations. This study proposes a modular molecular circuit design strategy by introducing allosteric regulation chains into the dynamic catalytic mechanism of DNAzyme, enabling the construction of programmable logic gates, including weighted-sum gates, threshold gates, and subtraction gates. Through cascading, molecular neurons and a molecular classifier were successfully implemented. This research, verified by NUPACK simulations and biochemical experiments, indicates that the designed logic gates can stably achieve specific computations. Furthermore, through Visual DSD simulations and experiments, the functions of molecular neurons and classifiers have been confirmed. This research provides a novel technical pathway for developing sophisticated biocomputing systems.

In the multi-attribute group decision-making problem in the context of probabilistic interval-valued intuitionistic hesitant fuzzy number (PIVIHFN), the concept of weighted probabilistic interval-valued intuitionistic hesitant fuzzy set (WPIVIHFS) is proposed, in order to reflect the decision-making role of the expert in the whole process. Based on the theory knowledge of WPIVIHFS and TOPSIS idea, a decision algorithm of optimal scheme is set up. WPIVIHFS is described by six-dimensional point coordinates, such as median and clarity of interval-valued membership, median and clarity of interval-valued non-membership, probability and expert weight. Based on the description of WPIVIHFS in six-dimensional point coordinates, the correlation algorithm of weighted probabilistic interval-valued intuitionistic hesitant fuzzy element (WPIVIHFE) is established. The entropy method is used to calculate the objective weight of the attribute. Finally, the decision algorithm is applied to the problem of choosing the construction site of not-in-my-backyard facility. The research shows that WPIVIHFS contains the weight of review experts and contains higher-dimensional decision data information, so the decision algorithm based on WPIVIHFS has better applicability.

With the rapid development of information technology, the survey and design industry is undergoing digital transformation, and Building Information Modeling (BIM) technology provides a 3D digital solution for the entire life cycle of engineering projects. Survey BIM achievements integrate data such as geological models, geographic information, and underground pipe networks, providing an accurate data foundation for engineering construction. However, their value has not been fully exploited in practical applications.Taking the Longhua District Maternal and Child Health Hospital Project in Shenzhen as the research object, this paper addresses the application bottlenecks of survey BIM achievements in the construction phase, such as software barriers and viewing convenience, and proposes a solution combining lightweight processing and mobile terminal query technology. Specifically, model lightweighting is achieved through triangulation-based geometric optimization and on-demand loading of attribute data, while operational fluency is enhanced by integrating visibility preprocessing and component reuse technologies. Based on the lightweight model, a mobile application is developed to realize real-time query of geological conditions, intelligent review of pipelines, and dynamic guidance for pile foundation construction.The research shows that this solution can effectively break through the limitations of traditional applications, improve the intelligent application level of survey BIM achievements in the construction phase, and provide efficient data support for engineering construction.

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.

Geological hazard susceptibility assessment is an important foundation and effective means for identifying high-risk areas and disaster prevention and reduction. Using the Analytic Hierarchy Process and GIS spatial analysis methods, the vulnerability of geological hazards in Zhangjiakou was evaluated by constructing an evaluation index system and calculating the weight of indicator factors, and the risk level was classified. At the same time, the comparison and verification were conducted based on the historical disaster point data and assessment results that have occurred. Research shows that: ① Using the analytic hierarchy process, the evaluation index system and evaluation results of Zhangjiakou's geological hazard vulnerability based on three indicators and their factors of topography, ecology, and geological landforms are scientifically credible; ② The overall risk of geological disasters in Zhangjiakou is relatively high, with the proportion of areas in the four risk zones from high to low being 38.59%,27.79%,19.21%, and 14.40%, respectively; ③ By comparing the data of historical disaster points, it was confirmed that nearly 60% of historical disasters occurred in areas with high or above risk levels, and the risk classification results are highly consistent with the actual historical situation; ④ The causes of major geological disasters in Zhangjiakou are highly related to regional topography, climate, rivers, geological tectonic zones, and human activities.

This study is designed to thoroughly investigate the impact mechanisms of chlorine disinfectant dosing strategies on the formation of disinfection by-products (DBPs) in drinking water cast iron pipelines. Secondary chlorination can effectively maintain the residual chlorine concentration in water, thereby ensuring long-term disinfection efficacy. The experimental data demonstrates that under the condition of 1.0 mg·L^-1 chlorine dosing at the water plant and an additional 1.0 mg·L^-1 secondary chlorination (Group 1-1), the control of DBPs in the simulated pipeline network effluent on the fifth day is optimal, with the concentration of trihalomethanes (THMs) being only 37.44 μg·L^-1 and virtually no nitrogen-containing DBPs generated. Further investigation revealed that the extracellular polymeric substances (EPS) in the effluent of Group 1-1 on the fifth day exhibit a higher proportion of β-sheet and α-helix protein secondary structures. This endows the suspended biofilm in the water with both coagulability and hydrophobicity, thereby inhibiting the chemical reactivity between EPS substances and chlorine disinfectants, leading to a significant reduction in the formation of DBPs, especially nitrogen-containing DBPs. During the water distribution process following chlorine disinfection in cast iron pipelines, EPS substances, primarily proteinaceous in nature, serve as a crucial source of DBPs precursors. Combining the protein/polysaccharide ratio and Zeta potential of EPS in water can significantly enhance the potential estimation accuracy of DBPs formation. The findings of this study provide a vital theoretical foundation and technical support for optimizing chlorine disinfectant dosing strategies in drinking water disinfection and pipeline distribution processes.

In this study, by analyzing the imaging data for the nearby spiral galaxy M81 (NGC 3031) obtained with the Spitzer Space Telescope at 3.6 μm and 4.5 μm, morphological parameters at the two bands and color index for the bulge and the disk of the galaxy are obtained, based on which, spatial distributions of the surface brightness and the color index for the galaxy and its substructures are deeply investigated. The software GALFIT is used to decompose the galaxy with two Sérsic components. By separating the bulge and the disk from the galaxy, images of the color index (3.6~4.5 μm) for the two substructures are created. In the results, the Sérsic index of M81 at 3.6 μm and 4.5 μm band is 4.27 and 5.13, respectively, confirming it as a classical bulge. The Sérsic index n ≈ 1.1 of the disk complies with the feature of an exponential disk. The effective radius of the bulge in the 3.6 μm band (72.24 arcsec) is smaller than in the 4.5 μm band (87.03 arcsec), and hence more compact in morphology, which may be related to the difference in sensitivity to stellar population properties at different bands. Analysis of the color index shows that the color difference between the bulge and the disk is not obvious (the color index is -0.08), but the overall color index for the galaxy (about -0.09) is bluer than those for the bulge and the disk. In the radial profiles, the color index of the disk decreases gradually with the radius, with the gradient about 0.33 mag/arcsec², suggesting a decrease in stellar population age from the center to the edge. The color index for the bulge slightly decreases within a small radial range (< 70 arcsec), with the gradient about 0.13 mag/arcsec², suggesting older central stars than those at outer areas. The overall color index for the galaxy shows a flat trend extending to large radii, suggesting similar ages for outer stars. In the center, the color index for the disk is larger than that for the bulge, which may be caused by different processes in the formation and evolution of different substructures. In the next work, we will conduct the multi-band decomposition of the galaxy, and construct spatially resolved spectral energy distributions for its substructure, respectively.

With the development of urban construction, when engineering construction is carried out in the central area of the city, different construction projects often affect each other and operational conflict occurs. The side wall of a foundation pit that has been excavated and constructed has become the new normal as the tunnel starting hole. This paper takes the formation of the starting hole door of the mining tunnel of the sidewall cut-off support pile of a foundation pit pile supporting system in Guangzhou as the background. The method of finite element numerical simulation and actual measured data comparison and analysis is used to study the influence of the instantaneous and subsequent construction of the pile supporting system on the stress and strain of the foundation pit support structure. The research results show that the moment of the foundation pit pile cut-off has a significant impact on the foundation pit support structure within a range of 1 times the hole diameter, especially the foundation pit support structure close to the hole opening. The stress-strain distribution in the subsequent foundation pit excavation process evenly allocates the impact of the pile cut-off construction on the local foundation pit support structure. The moment the foundation pit support pile is cut-off, the foundation pit support structure within the range of 1 times the hole diameter from the entrance of the pile cut-off, especially the foundation pit support structure close to the entrance of the pile cut-off shows obvious steep displacement change and stress concentration. The displacement and stress changes of the support structure outside the distance from the entrance of the pile cut-off are relatively small. As the foundation pit continues to be excavated, the foundation pit support structure outside the range of 1 times the hole diameter from the entrance of the pile cut-off gradually begins to share the impact of the pile cut-off on the foundation pit support structure, and the final displacement trend and internal force distribution of the foundation pit support structure show obvious structural integrity and spatial ductility.

Emerging contaminants are widely detected in actual natural water bodies and have been the subject of considerable research interest due to their high ecotoxicity and the difficulty of their removal by conventional water treatment technologies. However, there is a paucity of literature on the mechanisms of pollutant interactions and their removal in actual water bodies under coexistence states. In this paper, we investigated the interactions between bisphenol A (BPA), which has a high detection rate in natural water bodies, and its coexisting pollutants, such as tetracycline (TC), diphenhydramine (DP), and phenytoin (PHT), as well as their transformation kinetics on the surface of the iron-carbon catalyst. A series of characterization tools were used to probe the pollutants interactions and electron transfer, confirming the formation of BPA-TC/DP/PHT composite complexes by BPA with TC, DP and PHT, respectively. The adsorption coordination of the composite complex with the surface of the iron-carbon catalyst resulted in a larger surface charge leaving the domain, which triggered the electron capture conduction on the surface of dissolved oxygen in water and the surface cleavage of the adsorbed complexes. The BPA degradation rate decreased to 62.1%, 53.6% and 70.0%, respectively, however, the degradation rates of BPA-complexed TC, DP and PHT increased by 17.2%, 31.6% and 44.8%, respectively, and the corresponding reaction rate constants increased by 2.195, 1.810 and 3.459 times, respectively. The products are low toxicity or harmless substances, and the catalytic system with environmental benefits.

Under innovation-driven development strategy, the relationship between informal connections and the innovation performance of enterprises has increasingly become a hot topic of common concern for scholars and the government in recent years. Based on the CiteSpace econometric analysis of the WOS and CNKI databases, 36 377 domestic and foreign literatures on the two themes of “informal connection” and “innovation performance” over the past four decades from 1985 to 2024 were selected for econometric analysis. The results show that: The research contents and focuses of domestic and foreign scholars on these two topics are highly related to the institutional environment, economic development level and enterprise innovation ability of the country and region. Research on the influence mechanism of informal connections on enterprise innovation performance focuses on three aspects: internal enterprise, inter-enterprise communication, and the interaction effect between enterprises and other subjects. However, the mechanism exploration of how informal connections affect enterprise innovation at a deeper level remains to be explored. In the future, further discussions can be carried out from entry points such as quantitative measurement of informal connections, dynamic analysis, and the interaction between formal and informal connections.

Shield tunneling construction technology is widely used in urban rail transit construction due to its advantages of high excavation efficiency and high safety. The large-diameter shield tunneling of intercity railways have long excavation distances and deep burial depths. During the construction process, strong and rich water as well as extremely fragmented strata may be encountered, which will lead to difficulties such as drainage failure, low construction efficiency, and slow ground reinforcement effect. This paper summarizes and generalizes the engineering difficulties and construction processes encountered by the earth pressure shield tunneling of an intercity project in Shenzhen successfully crossing extremely fractured and water rich rock formations with large burial depths. The construction measures for the large-diameter earth pressure balance shield tunneling machine crossing the surrounding rock areas with large burial depths and water rich fractures are obtained. This area with a burial depth of up to 80 meters and a length of about 150 meters. During the construction process, the shield tunneling machine frequently encountered jamming and gushing, making it extremely difficult to excavate. Various methods were tried, and finally, ground reinforcement was adopted, thick slurry assisted excavation was used, and a combination of drainage and blocking was used to successfully cross the three extreme conditions. Due to the long excavation distance, it is inevitable to carry out excavation operations and replace cutting tools. It is extremely difficult to replace cutting tools in such extreme formations. A combination of ground grouting and grouting in the tunnel to fill the silo was attempted, and finally, atmospheric pressure excavation and tool replacement were successfully achieved. The research content and shield tunneling measures in this article can provide guidance for shield tunneling construction under similar extreme conditions such as long-distance crossing of strong water rich and extremely fractured strata.

To evaluate the integrity of multi-girder widened bridges, a quantitative evaluation method based on response spectrum similarity for transverse cooperative working performance was established. The study focused on a short- and medium-span girder bridge in Guangdong province, constructed in 1996 and widened in 2012. Vertical acceleration sensors were installed at the mid-span bottom of each girder. Leveraging the characteristics of structural health monitoring data, a high-quality dynamic response spectrum was obtained through the ensemble averaging algorithm. The evaluation index was then constructed using the calculated acceleration spectrum to comprehensively assess the bridge's integrity. The analysis results indicated that the acceleration spectrum patterns of each girder were highly consistent, with similar characteristic frequencies. The spectral similarity between adjacent girders exceeded 0.90, reflecting good transverse cooperative working performance. The first singular value spectra of the new and old bridges were highly similar, with a singular value spectrum similarity of 0.91, demonstrating that the widened bridge continues to exhibit cooperative performance effectively. These findings confirm the integrity of the multi-girder widened bridge, consistent with conclusions drawn from various quasi-static time-domain responses, thereby validating the feasibility and scientific basis of the proposed evaluation method.

In order to achieve the testing and acceptance of the two state attitude integrated instrument, a testing system with graphic display and atmospheric calculation functions has been developed. Based on the requirements analysis, the overall architecture was determined, a display processing unit was designed, the current consumption acquisition schemes were compared, software was developed, and measurement interfaces were kept. Then, common faults and corresponding measures were summarized, and key difficulties were solved by establishing a fault tree. A standardized process was proposed for troubleshooting. Finally, the joint debugging effect between the comprehensive testing system and the tested instrument and its components was verified through experiments, and all functional items were tested to be qualified. The indicated airspeed error is close to 0 km/h, the pressure altitude error is less than 10m, and the lifting speed error is less than 0.4 m/s. The research results show that the development of the testing system is correct, and its performance and quality meet the expected standards, demonstrating strong practicality.

Driven by the digital economy, the digital transformation of the construction waste recycling industry has emerged as an inevitable pathway to advance the sector's in-depth integration and high-quality upgrading. Developing scientifically sound and effective transformation strategies is therefore critical to addressing the current bottlenecks constraining industrial development. To tackle the challenge of stakeholder collaboration amid this industrial transformation, this study first constructs a four-party evolutionary game model involving the government, developers, construction firms, and recycling enterprises. It then systematically analyzes the strategy selection logic of each stakeholder and the stability conditions of the system's equilibrium points. Further, the study integrates system dynamics (SD) to establish an SD-evolutionary game hybrid model. Scenario simulations are conducted focusing on core variables, including the scale of government subsidies, enterprises' digital transformation costs, transformation benefits for individual stakeholders, and collaborative transformation gains for two or three parties. These simulations help unveil the dynamic evolutionary patterns and feedback mechanisms underlying multi-stakeholder strategies, ultimately leading to the proposal of collaborative strategies for the industry's digital transformation. The results indicate three key findings: ① Government subsidies positively incentivize enterprises' willingness to transform, but such subsidies require dynamic adjustment—excessively high or low subsidy levels will diminish stakeholders' transformation motivation. ② The additional benefits gained by developers, construction firms, and resource utilization enterprises through collaborative transformation exhibit a significant positive correlation with each stakeholder's willingness to pursue digital transformation. ③ The improvement of regional digital infrastructure and the development level of the digital economy directly influence the effectiveness of transformation cost control, while enhancing collaborative innovation capabilities within the industrial chain constitutes the core pathway to increasing stakeholders' collaborative benefits. This research not only provides theoretical support for clarifying the multi-stakeholder behavioral logic of the construction waste recycling industry in the context of digital transformation but also offers practical references for governments to formulate industrial collaborative governance policies and for enterprises to optimize their transformation decisions.

Sugarcane provides over 70% of the world's sugar raw materials, making an accurate prediction of its maturity period is crucial for ensuring sugar production and optimizing harvest resource allocation. Satellite remote sensing offers a powerful tool for large-scale crop growth monitoring, yet challenges persist in understanding the underlying mechanisms of maturity prediction. This study addresses this gap by focusing on two key meteorological factors affecting sugarcane development—temperature and solar radiation—using effective accumulated degree days (AGDD) and accumulated solar radiation (ASR) as driving variables. We developed a hybrid remote sensing-meteorological maturity prediction model through three key steps. First, normalized difference vegetation index (NDVI) time series were reconstructed using Double-Logistic models with spatial-temporal fused Landsat-MODIS time series datasets. Second, three critical growth stages including germination, tillering and elongation, were extracted from the reconstructed NDVI time series. Third, the AGDD-based and ASR-based maturity prediction models initiated from each identified growth stage were developed. The predicted maturity dates were validated using the multi-year phenological data from Guangxi and Yunnan provinces. The validation results demonstrated that the ASR-based models consistently outperformed AGDD-based models across all tested growth stages, and models initialized from the germination stage achieved the highest accuracy (RMSE=17.7 days, RRMSE=5.3%). This research establishes a methodological framework for large-scale sugarcane maturity prediction, offering technological support for precise agriculture management in sugarcane production systems.

Influenza viruses are major respiratory pathogens that can cause large-scale human outbreaks and pose a serious threat to global health. Many historical influenza pandemics have originated from swine or avian influenza viruses or reassortant hybrids. The development of interpretable and generalizable predictive models for human-to-human transmission is therefore critically important for early warning systems. This study presents a deep learning model incorporating attention mechanisms to predict the transmission risk of swine influenza virus to humans. The model combines convolutional neural networks and bidirectional gated recurrent units to capture local patterns and long-range dependencies in viral genomic sequences. Its key innovation lies in an interpretable attention mechanism that not only improves performance but also identifies and visualizes critical genomic regions related to host adaptation, such as PB1, PA, and HA segments. Using five-fold cross-validation, the model achieved an average AUROC exceeding 0.99, outperforming baseline models by approximately 0.150 in AUROC. The attention weights showed strong agreement with established biological evidence, confirming the model's biological relevance. In summary, the proposed model demonstrates high predictive accuracy and provides valuable support for public health surveillance and early warning systems against influenza transmission.

MicroRNAs (miRNAs) play key regulatory roles on cellular functions such as apoptosis and angiogenesis. The pathogenesis of complex diseases such as cancer is fundamentally linked to dysregulation of these cellular functions. Quantifying impact on abnormal cellular functions of miRNAs enables an understanding of the mechanism of disease progression and identifying novel therapeutic targets. Although traditional molecular biological experiments can verify the relationship between miRNAs and abnormal cellular functions in diseases, they have significant limitations such as long experimental cycle and high cost. To address such problems, in this paper, the impact of miRNAs on abnormal cellular functions in disease by the shortest path between differentially expressed miRNAs and functional genes was quantified. The proposed method is applied to lung cancer and colorectal cancer datasets to identify miRNAs associated with abnormal disease functions. The results of literature and KEGG pathway enrichment analysis show that SP-MFA can effectively identify miRNAs associated with abnormal cellular functions in diseases.

"Zero-waste City" is a new urban development model and governance concept. Based on the evaluation index system of "Zero-waste City" construction pilot work plan in China, and 233 questionnaire data analysis, the research used the applied management entropy theory and busselator model, to investigate and evaluate the system dissipation structure of "Zero-waste City" management system. It concluded that, the dissipation structure of "Zero-waste City" management system in China has not yet been formed, and the main factors affecting the formation of "Zero-waste City" in China are the number of units for the construction of zero-waste cities, the amount of safe disposal of industrial hazardous materials, the coverage rate of medical waste collection and disposal systems, the amount of waste discharged from construction, the penetration rate of sanitary toilets in rural areas, the political completion rate of informal landfill sites, the formulation of policy regulations or policy documents in cities without waste, and the quantification of household waste. The formation of a "Zero-waste City" needs to reduce its internal positive entropy environment, and requires the government, enterprises, and the public to establish a sufficiently large negative entropy external environment to enable "Zero-waste City" management system in China to evolve into a dissipative structure. Finally, the suggestion was put forward to construct a "Zero-waste City".

The involvement of microRNAs (miRNAs) in various diseases has been established. Thus, discovering miRNA-disease associations (MDAs) aids in the understanding of disease pathogenesis and makes it easier to develop effective therapeutics that target miRNAs. Compared with traditional biological experimental methods, identifying MDAs through computational methods has been proven to be low-cost and efficient. This study introduces the MDAES method for MDA prediction by integrating miRNA expression data and similarity networks. In MDAES, the optimal kernels of miRNAs and diseases are first constructed through multiple kernel learning (MKL) from their similarity kernels. Next, MDAES applies a regression model to obtain feature representations of miRNAs as well as diseases. Finally, by integration of the similarity network features of miRNAs and diseases, as well as the features of miRNA expression data as input to the deep neural network (DNN), MDAs are predicted. As a result, MDAES exhibits good performance on three benchmark datasets (AUCs >0.95) and outperforms the currently employed methods. Case study assessments of both breast and lung cancers demonstrate that 96% and 100%, of the top 30 predictions are linked to the two cancers, respectively. Overall, MDAES has great potential as a reliable and practical model to identify MDAs.

The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is one of the most economically active regions in China. Its extensive fish pond aquaculture activities play an important role in the sustainable supply of regional aquatic products. However, the carbon balance contribution caused by the high-intensity aquaculture activities in these fish ponds is still lacking in quantitative research. This study used the Sentinel-3 Ocean and Land Colorimeter (OLCI) data, combined with a semi-analytical inversion algorithm based on key bands (Oa08, Oa09, Oa017), and performed atmospheric correction through the SeaDas software to improve the reflectance accuracy, providing reliable data for carbon concentration inversion, and then estimating the carbon concentration of phytoplankton in fish ponds in the GBA from 2016 to 2024.The results show that: ① Overall, the carbon concentration of phytoplankton in fish ponds in the GBA presents a spatial distribution of high in the northwest and low in the southeast, mainly showing a trend of gradually weakening from inland cities to coastal cities, and the concentration differences between different cities are obvious. ② The seasonal changes in the carbon concentration of phytoplankton in aquaculture fish ponds in the GBA are more significant than the interannual changes. The high concentration season is autumn, with an average concentration of 2.193 mg/L; followed by summer and winter, with 1.314 and 1.465 mg/L respectively; the lowest concentration is in spring, which is 0.632 mg/L. ③ The high concentration areas are mainly distributed in inland areas such as Zhaoqing City and Foshan City in the northwest, and the low concentration is mainly distributed in the coastal areas in the southeast. ④ The interannual variation of phytoplankton carbon concentration showed a statistically insignificant increasing trend, and showed a slight upward trend year by year in the Sen's slope estimation, with an annual increase rate of 0.01~0.05 mg/L, mainly concentrated in Huizhou, Foshan and Hong Kong. The study verified the application potential of the Sentinel-3 OLCI satellite in estimating carbon flux in aquaculture areas, clarified the spatiotemporal dynamic changes of phytoplankton carbon concentration in small fish pond ecosystems, and its important impact on the regional carbon cycle. The results provide a scientific basis for optimizing environmental management in the GBA and studying carbon dynamics in similar aquaculture systems.

Vehicle-to-Infrastructure (V2I) technology, as a key component of the Vehicle Infrastructure Cooperative System (VICS), holds potential for alleviating traffic congestion, enhancing safety, and reducing emissions. This study aims to optimize signalized intersection control through V2I to minimize vehicle emissions. The spatiotemporal influence range of intersections was determined as 300 m based on DSRC communication. A dynamic speed control model and an emission model based on specific power method were established. Simulations were conducted via MATLAB to compare vehicle operational efficiency and emissions with and without V2I control. Simulation parameters included a control area of 600 m and traffic volume of 900 pcu/h. Results show that,V2I control significantly reduced emissions of CO, CO₂, NO_x, and HC by 13.5%, 9.6%, 19.9%, and 11.1%, respectively, while improving traffic efficiency, demonstrating its effectiveness in energy conservation and emission reduction.