Frontiers in Science and Engineering is a monthly online, international, peer-reviewed journal, dedicated to publish empirical, academic, theoretical and review research articles that contribute to the practice in science, engineering, and related topics. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
Design and Experimental Validation of an Automatic Inspection Robot Control System based on Multi-Sensor Fusion
To address the problems of high labor intensity, low efficiency, and safety risks in traditional manual inspection, as well as the insufficient environmental adaptability and limited path adjustment capability of existing inspection robots, an automatic inspection robot system based on multi-sensor fusion is designed. The system employs a Raspberry Pi 5 as the main control platform and integrates a Mecanum-wheel mobile mechanism, ultrasonic sensors, infrared sensors, and a camera pan-tilt module to accomplish the overall structural design, hardware selection, drive system development, and fusion control program implementation. In terms of software control, ultrasonic obstacle avoidance, infrared line tracking, and multi-sensor fusion decision-making functions are realized, and two operating modes, namely manual remote control and automatic inspection, are established. System debugging and experimental results demonstrate that the robot is capable of stable locomotion, path tracking, obstacle detection, and obstacle avoidance, thereby achieving the expected design objectives. The proposed system features a simple structure, low cost, convenient operation, and relatively stable performance, and can provide a useful reference for the design and application of low-cost intelligent inspection robots.
Multi-Sensor Fusion, Inspection Robot, Ultrasonic Obstacle Avoidance, Infrared Line Tracking, Automatic Inspection.
Copyright (c) 2026 Frontiers in Science and Engineering https://creativecommons.org/licenses/by-nc/4.0
Research on Strategies for Enhancing Roadside Green-Space Plant Landscapes: A Case Study of Urban Arterial Roads in Hangzhou
Plant landscapes play an indispensable role in shaping the character of roads. Additionally, the construction of road plant landscapes can mitigate the impacts of urban expansion. Therefore, exploring the plant landscapes of road green spaces is of great value. This study focuses on urban road greening construction, investigating the road greening in Hangzhou city. Through field surveys of the green spaces along the main roads in Hangzhou's urban area, and using plant community research methods, this study aims to understand the plant health, species composition, and population characteristics of the main road green spaces in Hangzhou city. Subsequently, it evaluates the landscape of Hangzhou's main road green spaces and conducts specific analyses on typical roads. This provides a reference for future urban road greening construction, creating reasonable growth spaces for road greening plants and fostering better ornamental effects.
Landscape Architecture, Urban Roads, Landscape Enhancement, Coping Strategies.
Research on Restraining Factors and Countermeasures of Old Residential Area Renovation Projects
In the context of urban renewal, the renovation of old residential communities has garnered significant attention from academia and policymakers as a crucial component of urban revitalization efforts. Facing multiple constraints during renovation processes, this study systematically identified 19 key limiting factors through literature analysis, case studies, and expert interviews to explore their underlying mechanisms. By applying the ISM model to construct hierarchical factor structures and employing the C-OWA operator for quantitative weight analysis, the research reveals five core constraints: policy standardization and regulatory completeness, rational renovation planning, resident satisfaction levels, government implementation intensity, and social capital participation. The study further delineates hierarchical transmission pathways among these critical factors. Based on these findings, a three-tiered policy framework is proposed, encompassing strengthened government coordination, improved policy standards, optimized design methodologies, enhanced resident satisfaction, and stimulated social capital engagement. This framework provides theoretical foundations and practical references for targeted interventions in old community renovation initiatives.
Renovation of Old Residential Areas, Restraining Factors, ISM Model, C-OWA Combination Number Operator Model.
Study on the Creep Model Considering Full-Process Damage in Rocks
Rock creep exhibits significant nonlinear characteristics, which become particularly pronounced during the accelerating creep stage under high shear stress, primarily due to the continuous accumulation of internal damage. The Nishihara model fails to adequately describe this phenomenon. To better characterize the full-stage creep process, this study introduces a damage variable into the component model based on damage mechanics theory and Lemaitre's strain equivalence principle, taking into account the full-process damage evolution. First, based on damage mechanics theory and the strain equivalence principle, a composite creep model consisting of a damaged generalized Kelvin model and a triggered nonlinear damage acceleration element is constructed. Finally, the Levenberg–Marquardt nonlinear least squares method is applied to fit selected experimental data, verifying the rationality of the theoretical model. The results show that the proposed full-process damage creep model can effectively describe the entire rock creep process, with the correlation coefficient between the fitted curves and experimental data exceeding 0.95.
Shear Creep, Damage Creep, Nonlinearity, Damage Variable.
Detection and Analysis of Drug Residues in Surface and Groundwater based on Liquid Chromatography Tandem Mass Spectrometry Technology
The large-scale development of pharmaceutical consumption and livestock breeding has made drug residues a typical trace emerging pollutant in water environments. The residual status of drugs in surface and groundwater, as core drinking water sources and ecological water, is directly related to ecological stability and human health. This study focuses on fluoroquinolones, sulfadiazine antibiotics, and antipyretic analgesics as target analytes, combined with the characteristics of aquatic matrix, optimizing solid-phase extraction pretreatment and LC-MS/MS detection parameters, establishing trace detection methods, and conducting regional water sample measurements. The entire experiment followed relevant national standards for water environment monitoring, and the data are authentic, reproducible, and free from any fabrication. The detection limit of this method is 0.002-0.010 μg/L, the quantification limit is 0.008-0.040 μg/L, the recovery rate is 68.2%-97.5%, the relative standard deviation is ≤ 5.5%, and the linear correlation coefficient is ≥ 0.996, which meets the requirements of trace detection technology. 19 types of drug residues were detected in surface water, with a total concentration of 15.62-81.34 ng/L, and fluoroquinolones were the dominant pollutants; 7-11 types of conventional groundwater were detected, with a total concentration of 14.85-48.62 ng/L. Groundwater pollution was significant in arid sandy soil areas, with a maximum total concentration of 265.37 ng/L. This method offers practical technical support and data reference for the normalized monitoring of drug residues in water environments and regional pollution prevention and control.
Liquid Chromatography-Tandem Mass Spectrometry, Surface Water, Groundwater, Drug Residues, Trace Detection, Solid-Phase Extraction.
China's social and economic development is constantly moving forward, the industrial level is further developing, and the demand for energy production is constantly increasing. With the increasing scale of coal mine engineering, higher requirements are put forward for mining technology. Intelligent coal mining can not only improve the level of production management, but also increase coal production. This paper introduces the necessity of applying intelligent mining technology, then discusses the convenience brought by intelligent mining technology, discusses the specific technology, researches and discusses the limitations and development prospects. Only by analyzing the application of intelligent coal mining can we ensure the safe and sustainable development of mining engineering, so as to promote the development of our country's economy and promote the all-round development of society. In recent years, with the development of economy and the progress of science and technology, people's living needs have been continuously improved. Coal mining resources have a great impact on social life, the development of mining engineering in our country continues to move forward, in the field of technology and development management principles have made great progress, intelligent mining technology application ability and level further improved. In the future, while solving the problem of resource limitation, the application of intelligent coal mine provides the prerequisite for the development of mining engineering, and also provides the possibility for its further development. Therefore, the intelligent mining of coal mines is gradually bringing us convenience, which not only increases the efficient mining of coal, but also guarantees the life safety of workers.
Intelligent Mining Technology, Automation, Big Data, 5G, Intelligent.
Prediction and Nonlinear Analysis of Dynamic Gas Foil Bearing-High-Speed Rotor System
To address the instability problem of foil-driven hydrodynamic gas bearing-rotor systems in high-speed oil-free rotating machinery, this paper establishes a high-fidelity transient multi-field coupled dynamic prediction model. The core of this model is that it skips the traditional linear stiffness/damping simplification and directly obtains the transient film force by solving the unsteady Reynolds equations that account for the squeezing effect. The paper details the numerical process of solving the transient flow field using the Alternating Direction Implicit (ADI) method and integrates it with the Timoshenko beam finite element rotor model. The transient response of the rotor under aeroelastic coupling effect is simulated using the prediction-correction multi-field coupled trajectory method. The bifurcation evolution law of the system over a wide speed range is investigated in detail. The study finds that after exceeding the critical speed of 14000 r/min, the system undergoes Hopf bifurcation induced by instability at the equilibrium point, subsequently evolving into a limit cycle motion with significant subsynchronous characteristics. With further increases in speed, the subsynchronous eddy frequency ratio evolves from 0.5X to 0.21X, revealing the frequency modulation mechanism caused by the nonlinear film force.
Dynamic Gas Bearings, ADI Algorithm, Nonlinear Dynamics, Fluid-Structure Interaction.
Selective Oxidation of Glycerol Produces Valuable Products
Under the situation of green economy, glycerol, as a polyol containing three hydroxyl groups, has high versatility and can be reacted to produce many different and more valuable fine chemicals and products. Glycerol is produced in large quantities in the process of biodiesel production, which is an important by-product of biodiesel production. Therefore, glycerol is considered as a potential platform chemical. Various value-added products of C3-C1 can be obtained by selective oxidation of glycerol via photocatalysis, electrocatalysis and photoelectrocatalysis, to improve the selectivity and yield of the resulting oxidation products. In this paper, the recent progress in the preparation of high value-added products by selective oxidation of glycerol in photocatalysis, electrocatalysis and photoelectrocatalysis is reviewed. The efficiency of various catalysts for glycerol conversion was emphasized. Various factors affecting the catalytic process were discussed. On this basis, the strategies for increasing the yield of glycerol, the limitations of existing catalysts and the future research directions are put forward. The mechanism of selective oxidation of glycerol by various catalytic methods is also discussed.
Glycerol, Selective Oxidation, Photocatalysis, Electrocatalysis, Photoelectrocatalysis, High Value-Added Product.
Research Progress of Grouting Materials at Home and Abroad and Future Development Trends
Grouting technology is a core reinforcement and anti-seepage method in the field of geotechnical engineering, and its application efficiency relies critically on the performance breakthrough and technological innovation of grouting materials. In recent years, the research on grouting materials worldwide has entered a period of rapid development. Scholars at home and abroad have conducted in-depth exploration around the core directions such as material research and development, performance evaluation, and construction application, and have achieved a series of results with practical value and theoretical significance. At the same time, they are also facing common challenges such as deepening basic research and improving the technical system. This paper systematically elaborates on the research status at home and abroad, core differences and future development trends from three aspects.
Grouting Materials, Geotechnical Engineering, Performance Evaluation, Construction Technology, Research Progress.
Preparation and Properties of Octadecylamine Modified Carbon Nanotubes
Carbon nanotubes (CNTs) have become an ideal reinforcement filler for polymer composites due to their unique one-dimensional hollow structure and excellent mechanical properties. However, the chemical inertness and easy agglomeration of the CNTs' surface limit their wide application. In this paper, the "oxidation amidation" two-step method was used to modify the surface of multi-walled carbon nanotubes. Firstly, carboxyl active sites (O-CNTs) were introduced on the surface of CNTs by hydrogen peroxide oxidation, and then octadecylamine was grafted onto the surface of CNTs by amide reaction with 1,1'-carbonyl diimidazole (CDI) as an activator to prepare hydrophobic functionalized carbon nanotubes (A-CNTs). The structure, morphology, and surface properties of CNTs before and after modification were systematically characterized by Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and contact angle test. The results showed that the oxidation treatment successfully introduced oxygen-containing functional groups such as carboxyl groups on the surface of CNTs, and octadecylamine was covalently grafted to the surface of CNTs through amide bonds, and the nitrogen element was evenly distributed after grafting; XRD analysis showed that the main crystal structure of CNTs was not destroyed during the modification process; The contact angle test showed that the contact angle of the original CNTs was 98.2°, the O-CNTs after oxidation was 107.1°, and the A-CNTs after octadecylamine modification increased to 137.9°, realizing the transition from hydrophobic to strong hydrophobic.
CNTs, Octadecylamine, Surface Modification, Amidation, Hydrophobic Modification.
Advances in Smart Contact Lenses for Tear Glucose Monitoring: A Review
Diabetes mellitus, a chronic metabolic disorder affecting a growing global population, demands accurate real-time glucose monitoring for effective management. Traditional finger-prick blood glucose testing is invasive, painful, and incapable of long-term continuous monitoring, driving the development of non-invasive alternatives. Tear glucose monitoring via smart contact lenses has emerged as a promising approach due to its non-invasiveness, real-time responsiveness, and improved patient compliance. This review systematically summarizes recent progress in smart contact lens technology for tear glucose sensing.
Diabetes Mellitus, Smart Contact Lenses, Tear Glucose Monitoring, Electrochemical Sensors.
The Impasse and Solutions for Product Liability in the Field of Autonomous Vehicles
Currently, autonomous driving technology is transitioning from technical testing to large-scale commercial application. Compared to traditional industrial products, autonomous driving technology is characterized by both complexity and autonomy, making it difficult to adapt to traditional product liability standards. This not only affects the effective remedy of the legitimate rights and interests of victims but also hinders the innovative development of the industry. This paper takes the application of product liability for autonomous vehicles as its research object, combining relevant legal provisions and practical cases to analyze the application dilemmas of autonomous vehicles in terms of the scope of product liability subjects, defect identification, and the difficulty in proving causation, and provides corresponding solutions.
Autonomous Vehicles, Product Liability, Defect Determination, Causation.
Interface Regulation Coupled with Crystal Plane Engineering: Alloy deposition-Modified Zinc Anode Enabling Dual Inhibition of Dendrite Growth and Corrosion
Aqueous zinc-ion batteries (AZIBs) demonstrate irreplaceable application prospects in large-scale energy storage due to their inherent safety, low cost, and high theoretical capacity. However, issues such as dendritic disorderly growth, hydrogen evolution reaction (HER), and corrosion of zinc anodes severely compromise electrode structural integrity, becoming a core bottleneck restricting the commercialization of AZIBs. To achieve efficient protection of zinc anodes, study employed room-temperature immersion deposition using metal nitrate as precursors to construct a Zn@M metallic deposited modification layer on zinc foil surfaces, forming an integrated physical barrier and chemically regulated protective system. The metallic modification layer provides comprehensive protection through multiple synergistic mechanisms: the conductive network co-constructed by homogenizes interfacial electric field distribution and Zn2+ ion flux, while their synergistic effect guides zinc deposition preferentially along thermodynamically stable (101) crystal planes, fundamentally suppressing dendritic growth. Additionally, this modification layer restructures Zn2+ solvation structures, reduces free water activity, and significantly inhibits side reactions such as HER and corrosion. This study proposes a simple, efficient, and cost-controlled bimetallic co-modification strategy for zinc anodes, elucidating an integrated protective mechanism of "electric field optimization-crystal plane orientation control-interfacial stabilization-side reaction inhibition", laying a critical foundation for the practical application of high-performance aqueous zinc-ion batteries (AZIBs).
Aqueous Zinc-Ion Battery, Zinc Anode Protection, Dendrite Inhibition, Corrosion Protection, Interface Regulation.
Adding Tungsten to Synthesize Multi-metal Catalysts and Growing High-quality Carbon Nanotube
Recently, the need for sustainable development of a large population and the uneven distribution of resources have compelled people to make new breakthroughs in the energy revolution. The field of energy technology has been rapidly advancing, and researchers are increasingly focusing on energy materials. Single-walled carbon nanotubes (SWCNTs) play a vital role in this area. However, the initial challenge of producing SWCNTs in large batches hampers their widespread application. This study successfully synthesized a catalyst consisting of Fe-Co-W using an impregnation-calcination technique and achieved high-yield production of SWCNTs. The results indicate that the addition of W enables the formation of stable FeWO4 and CoWO4 phases from Fe and Co, significantly enhancing the system's stability. Subsequent growth of SWCNTs demonstrates that the catalyst performs exceptionally well, achieving a yield of 241% at a temperature of 900°C. This research contributes to the industrial-scale production of single-walled carbon nanotubes and the advancement of new energy materials.
New Energy Materials, SWCNTs, Catalysts, CVD.
A Transmission Line Icing Detection Method based on Improved Canny and Hough Transform
To address the issues of noise interference in edge detection of transmission line icing images and inaccurate thickness calculation due to scattered straight line detection, a detection method based on an improved Canny operator and optimized Hough transform is proposed. The Canny adaptive double threshold is achieved through the percentile sorting of gradient magnitude to enhance the robustness of edge extraction; the optimized Hough transform with line fitting is adopted to fuse scattered edges into complete icing edge lines ; and the thickness conversion is completed in combination with the camera imaging principle. Experiments show that this method can effectively improve the accuracy of icing thickness detection and has engineering application value.
Detection of Ice Coating on Transmission Lines, Improved Canny Operator, Adaptive Double Threshold, Optimized Hough Transform, Camera Imaging Principle.
Research on Competitive Strategies of Agricultural Product Live-streaming E-commerce Enterprises in the Digital Intelligence Era
In the digital and intelligent era, live-streaming e-commerce for agricultural products has become an important carrier for the digital transformation of agriculture. The industry is experiencing rapid expansion, but enterprises are facing development challenges such as intensified competition, homogenization of models, and imperfect supply chains. This paper takes live-streaming e-commerce enterprises for agricultural products as the research object, utilizes the PEST model and Porter's Five Forces model, analyzes the competitive environment of enterprises from both macro and micro dimensions, and combines the current development status of the industry to sort out the core issues in digital and intelligent transformation. Finally, it proposes a three-in-one competitive strategy of "digital and intelligent + scenario-based + branding" and an ecological collaborative implementation path. The research results can provide practical references for live-streaming e-commerce enterprises for agricultural products to break through development bottlenecks and enhance their core competitiveness. At the same time, it helps standardize and digitize the industry, promoting the deep integration of rural revitalization and the digital economy.
Digital Intelligence Era, Live-streaming E-commerce for Agricultural Products, Competitive Strategy, PEST Model, Porter's Five Forces Model.
Neural Oscillations and Fronto-Parietal Network Dysregulation in Decision-Making under Uncertainty in Adolescent Depression
Adolescence is a critical developmental period characterized by ongoing prefrontal–limbic maturation, heightened emotional reactivity, and increased sensitivity to social and environmental feedback, making this stage particularly vulnerable to depressive disorders. Adolescent Major Depressive Disorder (MDD) is associated with pervasive negative cognitive biases, diminished reward responsiveness, and heightened loss aversion, which collectively drive conservative or avoidance-oriented decision-making under conditions of uncertainty. Behavioral evidence indicates that these biases impair adaptive cost–benefit evaluation, limit exploration, and reinforce withdrawal and low motivation. Neurophysiological studies using electroencephalography (EEG) reveal that these behavioral alterations are underpinned by disruptions in neural oscillations and large-scale network dynamics: beta-band activity supports reward integration and goal-directed behavior, frontal midline theta reflects heightened monitoring of negative outcomes and cognitive control, and alpha oscillations mediate inhibitory regulation and attentional gating. In adolescent depression, aberrant modulation of these frequency bands, together with imbalanced fronto–parietal connectivity and reduced engagement of motivational circuits, promotes rigid, risk-averse strategies. Understanding these neural mechanisms provides insight into maladaptive decision-making and suggests that longitudinal studies integrating EEG with structural and functional neuroimaging, as well as interventions such as cognitive training or neurofeedback targeting beta, theta, and alpha dynamics, may enhance reward processing, reduce excessive loss monitoring, and support adaptive neurocognitive development in depressed adolescents.
Adolescent Depression, Decision-making under Uncertainty, Neural Oscillations, Fronto–parietal networks, Reward and Loss Processing.
A Review of Rolling Bearing Fault Diagnosis Methods based on Empirical Mode Decomposition
Empirical Mode Decomposition (EMD) has unique advantages in processing nonlinear and non-stationary signals due to its adaptability, and has been widely applied in the research on fault diagnosis of rolling bearings.This paper systematically combs the relevant literatures in this field in the past five years. From the perspective of the evolution of methods, the research has experienced a gradual deepening process from a single decomposition method to the fusion of multiple technologies and from traditional machine learning to deep learning integration.The existing research mainly focuses on three directions: improvement of decomposition algorithms, enhancement of noise suppression, and construction of intelligent recognition models, and has achieved remarkable progress in diagnostic accuracy and robustness.Analysis shows that the current research still has problems such as the disconnection between laboratory data and industrial practice, insufficient adaptability to complex working conditions, and lack of model interpretability.Future research needs to further focus on the design of lightweight algorithms, the improvement of cross-domain adaptability, and the fusion path of physical knowledge and data-driven methods.
Empirical Mode Decomposition, Rolling Bearing, Fault Diagnosis.
Study on the Removal of PFAS by Functionalized Porous Organic Polymers
Per- and polyfluoroalkyl substances (PFAS) have emerged as a globally significant new class of persistent organic pollutants due to their exceptional chemical stability, environmental persistence, and pronounced bioaccumulative toxicity. Among existing remediation technologies, adsorption is widely recognized as the most promising approach for treating trace and low-concentration PFAS in water bodies due to its high removal efficiency, low operational energy consumption, and ease of operation. Porous organic polymers (POPs), as an emerging platform material, offer an ideal molecular engineering platform for efficient PFAS capture due to their exceptional high specific surface area, precisely tunable pore size distribution, and outstanding physicochemical stability. This paper systematically reviews the design and synthesis strategies for representative POPs, including conjugated microporous polymers (CMPs), hypercrosslinked polymers (HCPs), intrinsically microporous polymers (PIMs), porous aromatic frameworks (PAFs), and covalent organic frameworks (COFs). It focuses on analyzing the intrinsic mechanisms by which functionalization with key groups such as amino and fluorine groups enhances adsorption capacity and selectivity, and delves into the synergistic enhancement processes of electrostatic forces, hydrophobic interactions, and fluorine-affinity interactions in complex aqueous environments. Furthermore, addressing current technical challenges such as the difficulty in removing short-chain PFAS and interference from competing ions in complex real-world aqueous matrices, this paper objectively evaluates the potential and limitations of POPs in practical engineering applications.
PFAS, Porous Organic Polymers, Synthesis Mechanism, Functionalization, Adsorption Removal.
Agricultural New Quality Productive Forces: Connotative Features and Research Prospects
Agricultural new quality productive forces serve as a crucial lever for advancing agricultural modernization and building a leading agricultural nation. This paper primarily conducts a literature review to elucidate the connotation and characteristics of agricultural new quality productive forces and offers research prospects for future inquiry. It argues that future efforts should be advanced in a coordinated manner across four dimensions: subject incentives, factor allocation, data empowerment, and technological innovation. By constructing a pattern of multi-subject collaborative governance and removing institutional barriers to factor allocation, a systematic transition from traditional productive forces to new quality productive forces can be achieved, thereby injecting lasting momentum into high-quality agricultural development and the building of a leading agricultural nation.
Agricultural New Quality Productive Forces, Connotative Features, Practical Challenges, Development Pathways.
Research Progress and Application Prospects of Micro-arc Oxidation Technology for Magnesium Alloys
As a lightweight high-performance metallic material, magnesium alloys demonstrate significant application potential in fields such as aerospace, automotive manufacturing, and biomedical engineering. However, their high chemical reactivity leads to susceptibility to corrosion and degradation in service environments, severely limiting their engineering applications. Micro-arc oxidation (MAO) technology, also known as plasma electrolytic oxidation (PEO), effectively addresses the corrosion protection of magnesium alloys by in-situ generating a ceramic oxide layer on the metal surface. This paper systematically elaborates on the fundamental principles, process optimization, coating performance enhancement, and multidisciplinary applications of micro-arc oxidation technology for magnesium alloys. It comprehensively analyzes the current research status and development trends of this technology, providing theoretical guidance and technical references for the surface modification of magnesium alloy materials.
Micro-arc Oxidation, ZK60 Magnesium Alloy, Process Parameters, Application.
How Does Artificial Intelligence Empower the Development of New-Quality Productivity?
In the current era where a new round of technological revolution and industrial transformation is intertwined, leveraging artificial intelligence to empower the cultivation of new-quality productivity has become a core path for driving development. This paper focuses on the policy of the New Generation Artificial Intelligence Innovation and Development Pilot Zones, selecting panel data from 30 provinces in China from 2012 to 2022 as the analysis sample. It employs a multi-period difference-in-differences model and, in combination with the CRITIC entropy weighting method, constructs a comprehensive evaluation system for new-quality productivity covering labor, labor resources, labor objects, and factor combination efficiency to empirically test the policy effects of the pilot zones. The study finds that the pilot zone policy significantly promotes the enhancement of new-quality productivity, and this effect remains robust after a series of robustness checks such as the parallel trends test and placebo test. Mediation effect tests indicate that industrial structure upgrading and talent aggregation are important transmission paths through which the pilot zone policy empowers new-quality productivity. Heterogeneity analysis shows that the policy effect exhibits significant regional differences, being most pronounced in the eastern region, followed by the western region, while the impact in the central and northeastern regions is not statistically significant. Additionally, provinces with higher levels of openness and marketization gain more pronounced positive benefits from this policy. The research conclusions provide empirical evidence and practical reference for optimizing artificial intelligence development policies and promoting the cultivation of new-quality productivity.
New Quality Productivity, Artificial Intelligence, New Generation Artificial Intelligence Innovation Development Pilot Zone, Policy Effect.
Numerical Simulation of Seismic Performance of Ultra High Performance Concrete Columns
In order to study the seismic performance of ultra-high-performance concrete (UHPC) columns, ABAQUS finite element software was used to simulate the seismic performance tests of UHPC columns under horizontal loads. The simulation results were compared with existing experimental results, showing good agreement. Based on this, the hysteresis curves and skeleton curves of UHPC columns under different parameters were studied using the variable control method to investigate the effects of axial compression ratio, stirrup spacing, and longitudinal reinforcement ratio on the seismic performance of UHPC columns. The results show that with the increase of the axial compression ratio, the bearing capacity of UHPC columns is significantly improved. However, the area of the hysteresis curve decreases with increasing axial compression ratio, ductility is reduced, failure mode tends to become brittle, and seismic performance decreases as the axial compression ratio increases. Changes in stirrup spacing and longitudinal reinforcement ratio can both improve the seismic performance of UHPC columns.
Ultra-high Performance Concrete, Seismic Performance, Low-cycle Repeated Loading, Numerical Simulation.
Design and Implementation of the Front End of Online Bookstore
With the rapid development of the Internet, e-commerce will gradually become the mainstream business model of this century. Online bookstores are a new type of book sales channel that has emerged with the development of these network technologies. It combines human and electronic communication methods, relies on computer networks, and is based on communication technology to achieve online transactions for book sales. Compared with traditional storefront bookstores, online bookstores have new business modes and sales channels; Its 24-hour and all-round service is unmatched by physical bookstores; The main reason for opening an online bookstore is its low cost. Compared with other products, book transportation is almost not afraid of collision and breakage, and has no timeliness; At the same time, books have unique advantages of single function, simple form, easy judgment and selection, and are most suitable for online transactions; Once again, the low unit price has lowered the threshold for consumers to shop online for the first time, making online bookstores the pioneers of e-commerce. This online bookstore mainly includes two parts: front-end customer operation and back-end administrator management. The front-end mainly implements user registration and login, browsing books by category, commenting on books, viewing shopping carts, placing orders, viewing book purchase records, modifying user personal information, changing user passwords, etc. The backend administrator mainly maintains the book information and user information in the database.
JSP, Visual Code, Electronic Commerce, Online Bookstore.
MHQ-SAT: An End-to-End SAT Solver with a Multi-Head Hierarchical Query Mechanism
The Boolean Satisfiability Problem (SAT), as a representative NP-complete problem, plays a crucial role in integrated circuit verification, automated reasoning, and combinatorial optimization. In recent years, end-to-end SAT solvers based on graph neural networks (GNNs) have alleviated the reliance on handcrafted heuristics by learning the structural relationships between variables and clauses. However, existing neural SAT solvers with query-based mechanisms typically rely on a single query perspective, which limits their ability to capture diverse reasoning paths within complex constraint structures. As a result, their reasoning stability and generalization performance on large-scale instances remain insufficient. To address these limitations, this paper proposes MHQ-SAT, an end-to-end SAT solving model based on a multi-head hierarchical query mechanism. Built upon the QuerySAT framework, MHQ-SAT introduces a multi-head variable query mechanism and clause-level hierarchical attention modeling. By constructing multiple query perspectives in parallel, the proposed model enhances the expressive capacity of implicit reasoning processes. Meanwhile, a clause-level attention mechanism is employed to dynamically characterize the relative importance of different clauses during reasoning, enabling the model to focus on critical constraint structures. Furthermore, MHQ-SAT integrates query-driven clause updates with gated variable update mechanisms, achieving efficient information interaction between variables and clauses as well as stable iterative reasoning. Extensive experiments on randomly generated 3-SAT and k-SAT benchmarks demonstrate that MHQ-SAT consistently outperforms NeuroSAT, QuerySAT, and other baseline methods across various variable scales and reasoning step settings. In particular, on medium- and large-scale SAT instances, MHQ-SAT exhibits superior robustness and reasoning stability in terms of solution accuracy and the proportion of unsolved instances. Ablation studies further validate the effectiveness of the multi-head query mechanism and clause-level hierarchical modeling in improving overall performance. These results indicate that the proposed multi-head hierarchical query mechanism provides an effective and learnable reasoning enhancement paradigm for end-to-end SAT solving.
Boolean Satisfiability Problem, Graph Neural Networks, End-to-End Solving, Multi-Head Query, Hierarchical Attention.
Mix Design and Performance Study of Early-Strength Concrete based on Orthogonal Experiment
To investigate the influence mechanism of C-S-H nano-nuclei on the early strength of high-performance concrete in which fly ash partially replaces cement, this study employed an orthogonal experimental method to systematically explore the synergistic effects of three key factors-fly ash content, nano-C-S-H nuclei content, and curing age-on the mechanical properties of early-strength concrete. A four-level, three-factor orthogonal experimental design (L16(4³)) was adopted, with a total of 17 groups of concrete specimens prepared. Their compressive strength, splitting tensile strength, and elastic modulus were tested at different ages ranging from 4 hours to 7 days. Through range analysis and mean comparison, the primary and secondary influence order of each factor on the performance indicators, as well as the variation patterns, were clarified.The results indicate that curing age is the most significant factor affecting the compressive strength, splitting tensile strength, and elastic modulus of early-strength concrete, followed by the content of nano-C-S-H nuclei, while the influence of fly ash content is relatively weaker. As the fly ash content increases (10%–40%), the early compressive strength of concrete shows a slow declining trend. The appropriate incorporation of nano-C-S-H nuclei (2%–4%) can significantly enhance early strength, but excessive addition may lead to a reduction in strength. With the extension of curing time, all mechanical properties improve markedly. Based on comprehensive performance analysis, the optimal mix proportion for early-strength concrete is determined as 20% fly ash content, 2% nano-C-S-H nuclei content, and 7 days of curing. Verification shows that, compared to the reference group without supplementary materials, the optimized group exhibits increases of 19% in compressive strength, 33.3% in splitting tensile strength, and 8% in elastic modulus, demonstrating excellent early-strength performance and engineering applicability.This study quantitatively analyzes the effects of material proportioning and curing regime on the early mechanical behavior of concrete under a dual-admixture system through orthogonal experiments, providing experimental evidence and theoretical references for the mix design and performance regulation of early-strength concrete.
Orthogonal Experiment, C-S-H Crystals, Concrete, Compressive Strength, Splitting Tensile Strength, Elastic Modulus.
Grouting Methods in Geotechnical Engineering: A Comprehensive Review and Outlook
The technique of rock and soil mass reinforcement has been widely used in engineering field and has solved many difficult problems in geotechnical engineering. As an important part of rock and soil consolidation technology, grouting method is also the most common foundation treatment method. Through pneumatic, hydraulic or electrochemical principles, some curable grout is injected into natural or artificial cracks or pores to improve various physical and mechanical parameters of the medium, so as to meet the needs of practical engineering. This paper reviews the development of grouting method, discusses the research status and technical characteristics of grouting method, and looks forward to the future development of grouting method from three aspects: grouting materials, admixtures and grouting technology.
Grouting Method, Rock and Soil Reinforcement, Grouting Material.
The Dilemma and Optimization Path of Reading for the Blind in the Era of Smart Media in China
In the context of the era of smart media, the blind community in China faces a significant reading gap. The structural contradiction between technological empowerment and the social support system exacerbates their cultural marginalization. This article analyzes the deep-seated dilemmas of reading for the blind from three dimensions: technological adaptability defects, imbalance in the supply of resources for the blind, and lagging service support system. Specifically, the accessibility design of smart media has long been marginalized; Braille books suffer from lagging technological iteration and limited content; and there is a universality trap in blind devices. Braille reading materials and audio resources are subject to exorbitant prices and scarce supply due to the exclusion of rights in the production mechanism. Furthermore, the public service system is trapped in formalism due to institutional stagnation and practical dysfunction. Based on this, a three-pronged collaborative governance framework of "technology adaptation, resource integration, and institutional guarantee" is proposed, advocating the construction of a universally accessible public goods supply system, promoting the deep integration of intelligent technology ethics and humanistic care, and reconstructing the service ecosystem through multi-stakeholder collaboration.
Smart Media Era, Blind Reading, Barrier-Free Design, Service Supply System.
Short-Term Wind Power Prediction based on Adaptive Hybrid Swarm Intelligence Optimization
Wind power prediction is crucial for ensuring the safe and stable operation of high-penetration renewable energy power systems. Addressing the nonlinear and non-stationary characteristics of wind power sequences and the challenges of hyperparameter optimization in deep learning models, this paper proposes a short-term wind power prediction method based on adaptive hybrid swarm intelligence optimization. First, an adaptive elite hybrid algorithm (SAE-PSO-GWO) integrating Grey Wolf Optimizer and Particle Swarm Optimization is constructed, incorporating elite opposition-based learning and parameter adaptive mechanisms to balance global exploration and local exploitation capabilities. Subsequently, a prediction model combining multi-scale CNN and LSTM is designed to extract multi-scale temporal features and model long-term dependencies. Finally, SAE-PSO-GWO is employed to automatically optimize the model hyperparameters. Experimental results demonstrate that the proposed algorithm exhibits superior convergence accuracy and stability on the CEC2010 test functions. On wind power datasets, the optimized model achieves MAE, RMSE, SMAPE, and R² values of 57.89, 116.87, 14.17%, and 0.9680, respectively, representing improvements of approximately 14.38%, 19.48%, 4.90%, and 1.83% compared to baseline models. This verifies the effectiveness of the proposed method in enhancing prediction accuracy and robustness.
Wind Power Prediction, Hybrid Swarm Intelligence Optimization, Hyperparameter Optimization, Multi-scale Feature Extraction, Deep Learning.
A Literature Review on the Fabrication and Performance of Graphene-reinforced Nickel-based Composites
Nickel-based composites have attracted extensive attention owing to their outstanding corrosion resistance, wear resistance, and high specific strength. However, conventional particulate reinforcements often compromise thermal and electrical conductivity. Graphene, distinguished by its exceptional intrinsic strength, superior electrical and thermal conductivity, and ultralow density, offers a promising strategy for designing nickel-based composites that reconcile structural robustness with functional heat and charge transport. Focusing on the “fabrication and properties of graphene-reinforced nickel-based composites,” this review systematically summarizes recent advances in the field, with particular emphasis on processing strategies, property optimization, and critical scientific challenges. Current mainstream fabrication routes include electrodeposition (ED), powder metallurgy (PM), chemical vapor deposition (CVD), and molecular-level mixing (MLM). Each technique exerts a pronounced influence on microstructural evolution, interfacial characteristics, and macroscopic performance. Representative findings indicate that the PM route can enhance hardness at relatively low graphene loadings while maintaining strength levels; for instance, at 0.1 wt% graphene, the hardness increases to 181 ± 39 HV, with tensile strength approaching that of pure nickel. The ED approach, through jet and direct current electrodeposition, improves graphene dispersion and interfacial bonding, and introduces the concept of “interfacial self-healing” to enhance irradiation tolerance. The CVD route enables in situ growth and incorporation of high-quality graphene, reporting a substantial increase in yield strength at 1.0 vol% graphene while preserving considerable ductility. The MLM combined with spark plasma sintering (SPS) facilitates well-defined interfacial architectures at the molecular scale, simultaneously maintaining structural integrity and markedly improving tensile and yield strengths. From a performance perspective, the mechanical reinforcement imparted by graphene is primarily attributed to effective load transfer, grain refinement strengthening, dislocation pinning, and robust interfacial bonding. Nevertheless, excessive graphene incorporation may deteriorate ductility and toughness, necessitating a careful balance between content and dispersion state. Furthermore, graphene’s intrinsic self-lubricating behavior promotes the formation of lubricating or transfer films at sliding interfaces, thereby reducing friction coefficients and enhancing wear resistance. Its two-dimensional barrier effect suppresses the ingress of corrosive species, improving corrosion resistance. In terms of thermal and electrical transport, experimental evidence indicates that the thermal conductivity of the composites can be enhanced by approximately 15% relative to pure nickel. Overall, a relatively well-established “processing–microstructure–property” paradigm has emerged in this field. However, practical engineering applications remain constrained by challenges such as achieving uniform graphene dispersion while preserving structural integrity, precisely controlling interfacial reactions and bonding, and realizing cost-effective, reproducible, large-scale fabrication. Future efforts should concentrate on breakthroughs in “homogeneous dispersion–stable interfaces–scalable reproducibility,” while advancing application-oriented validation in lightweight aerospace structures, high-strength and wear-resistant automotive components, high-thermal/electrical-conductivity electronic devices, and energy storage electrodes.
Graphene, Nickel-Based Composites, Electrodeposition, Powder Metallurgy, Chemical Vapor Deposition, Molecular-Level Mixing.