International Core Journal of Engineering
International Core Journal of Engineering is an international journal to promote all fields of Engineering, it considers original and timely contributions containing new results in mechanical engineering, electrical engineering, civil engineering, chemical engineering, etc. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
Preparation and Application of Plant-Derived Nano-Solutions in Agricultural Disease Control
Global demand for food and threats from plant disease require sustainable tactics for managing pests. Conventional pesticides, though efficient, are plagued with limitations such as persistence in the environment, non‑target toxicity, and resistance building up. Green nano-solutions – nanomaterials made or formulated with plant extracts, biomolecules, or botanically derived substances – are an exciting alternative. These "green" nanotechnologies utilize phytochemicals (polyphenols, flavonoids, etc.) as reducing/capping agents to generate metallic or polymer nanoparticles that show strong antimicrobial potency. Nanoformulations (e.g., nanoencapsulated essential oils) can offer bioactive plant constituents with better stability and controlled release. Herein, we discuss procedures for preparing plant-source nano-pesticides (green synthesis, nanoemulsions, encapsulation, stabilization, and characterization) and list recent experimental findings on their ability to control bacterial, fungal, viral, and nematode pathogenesis. Reports indicate strong inhibition of varied pathogens (e.g., Fusarium, Botrytis, Xanthomonas) by nanoparticles made from biological processes. Mechanisms of action are membrane permeabilization, ion release, and oxidizing insult. Significantly, most of these formulations show low phytotoxicity and reduced non‑target activity under assayed conditions. From a sustainable agricultural perspective, nano-pesticides made from plants offer efficient control of pests with potentially reduced chemical burden and better selectivity. Here, we discuss their merits (efficacy, biodegradability), limitations (scale‑up, regulatory obstacles, incomplete toxicity), ecological concerns (accumulation, soil microbiome effect), and future prospects (sophisticated delivery with precision, field experiments, safety studies with respect to environment). Our review emphasizes that nanotechnologies from plants, compatible with circular‑economy philosophy, can further bring down environmentally safe disease control, with proper assessment of their safety and long‑term impact.
Plant-derived; Nano-solutions; Green; Nanotechnology; Nano-pesticides; Sustainable Agriculture; Plant Disease Management; Green Synthesis; Nanoencapsulation.
Copyright (c) 2025 International Core Journal of Engineering https://creativecommons.org/licenses/by-nc/4.0
Demand Analysis of Air-Ground Integrated Cooperative Urban Anti-Terrorism Operations Capabilities based on GQFD
Urban counter-terrorism operations involve complex environments and high information uncertainty, making Integrated Air-Ground Teaming (IAG-T) a critical model for enhancing operational effectiveness. However, systematically and precisely translating ambiguous operational tasks into clear, quantifiable system capability requirements remains a core challenge in current equipment system development. This study aims to employ a combined approach of Grey System Theory and Quality Function Deployment (GQFD) to construct a scientific requirements analysis model. This model addresses uncertainties in mapping integrated air-ground urban counter-terrorism operational capability requirements, providing a theoretical foundation for equipment system development, tactical formation, and effective support.The paper first analyzes typical urban counter-terrorism scenarios to extract operational mission requirements. It then employs grey system theory to address the incompleteness and ambiguity of expert evaluations, determining grey weights for each requirement. Subsequently, a "mission-capability" relationship matrix is constructed using GQFD, precisely mapping top-level mission requirements to specific integrated air-ground system capabilities. Finally, computational analysis identifies critical capability requirements and their priority sequence.Applying GQFD (Grey Quality Function Deployment) to analyze urban counter-terrorism operational capability requirements for integrated air-ground coordination effectively addresses uncertainty and ambiguity in requirement information, ensuring capability development precisely aligns with operational missions.
Air-Ground Integrated Coordination; Urban Counter-Terrorism; Capability Requirements Analysis; Grey Quality Function Deployment; GQFD.
Study of Public Perception of Intelligent Construction Technology Topics
Intelligent construction technology is an important means to realise the transformation and development of the construction industry. With the growing demand for the transformation and upgrading of the industry, the public discussion on intelligent construction technology is becoming increasingly intense. This study uses crawler software to capture the discussion text related to intelligent construction technology from 2020-2025 on the Zhihu platform, and conducts a quantitative study through text analysis methods such as TF-IDF keyword extraction, LDA topic modelling, and machine learning sentiment analysis (scikit-learn), to examine the social public's concerns, attitudes, and perceptions of intelligent construction technology, and to analyse the public's perspective on the problems in the application of smart construction technology. The results of the study show that the public's concerns about intelligent construction technology are diversified, mainly focusing on five aspects, namely, industry development, talent cultivation, technology application, intelligent transformation, and employment and development direction; the public's attitudes towards intelligent construction technology are polarised; and the public's understanding of intelligent construction technology is diversified. Finally, suggestions for the promotion of intelligent construction technology and the development of intelligent construction are put forward from four perspectives, namely, individuals, schools, industries and society, with a view to providing a reference basis for policy formulation and technology promotion by the government and relevant industries.
Social Public; Intelligent Construction Technology; Intelligent Construction; Textual Analysis Method.
Multi-modal Safe Driving System for New Energy Vehicles based on Microcontrollers
This paper presents a multimodal intelligent safety driving system for new energy vehicles, developed based on STM32 microcontrollers and multimodal visual algorithms. The system integrates real-time dynamic monitoring of the A-pillar blind spot, fatigue driving detection, and battery spontaneous combustion detection. Through optimized distortion correction algorithms, dynamic display solutions, fatigue detection models, and the construction of spontaneous combustion sensors with information transmission systems, it achieves multidimensional safety monitoring. The system innovatively employs object detection and Zhang Dingyou calibration for dynamic A-pillar blind spot monitoring, combines deep learning for fatigue driving detection, and implements battery spontaneous combustion risk warnings through dual data module feedback. In practical application, it reduces the risk of accidents caused by blind spots and fatigue driving, decreases the probability of battery spontaneous combustion, and provides technical support for intelligent cockpits, assisted driving, and new energy vehicle safety, demonstrating broad potential for in-vehicle applications.
New Energy Vehicles; Multimodal Safety Driving System; A-pillar Blind Spot Monitoring; Fatigue Driving Detection; Visual Algorithms.
Research on the Fuzzy Comprehensive Evaluation Method for Interior Design of Small and Medium-Sized Yacht Cabins based on the AHP Method
To address the lack of scientific and objective evaluation standards for the interior design of small- and medium-sized yacht cabins, this study establishes an evaluation system that integrates the Analytic Hierarchy Process (AHP) with the fuzzy comprehensive evaluation method. Firstly, an evaluation index system is constructed from six dimensions: aesthetics, comfort, safety, functionality, cost, and sustainability. Subsequently, AHP is employed to determine the weights of each indicator, thereby reducing the influence of subjective judgments on the evaluation results. On this basis, the fuzzy comprehensive evaluation method is applied to conduct an empirical analysis and quantitative assessment of two yacht models, 500C and 500E. The results show that the interior design of both yachts reaches the “good” level. The study demonstrates that the combined application of AHP and the fuzzy comprehensive evaluation method effectively addresses the multi-level, multi-index, and fuzzy characteristics of yacht cabin design evaluation, providing a scientific and systematic technical approach and theoretical support for the assessment and optimization of yacht interior design.
Yacht Cabin Interior Design; Analytic Hierarchy Process (AHP); Fuzzy Comprehensive Evaluation Method.
Construction of Flowering Period Prediction Model based on Mathematical Modeling
In the context of the rainy weather during the Qingming Festival which may affect the outing for flower viewing, this article conducts an in-depth analysis and modeling on the topic of flower viewing during the Qingming Festival. By using historical data and information about flowers, a comprehensive optimization model is established to predict the weather and plan the flower viewing routes. We predict whether it will rain in a city by establishing a Holt-Winters seasonal model based on historical weather data (such as atmospheric temperature, atmospheric pressure, relative humidity, etc.) to predict whether it will rain during the Qingming Festival. We also establish a forecast model for the opening time and flowering period of flowers such as apricot blossoms and rape flowers in 2026, using the data of the initial flowering time of each year to build a prediction model for flowering prediction, thereby predicting the opening time and flowering period of flowers in 2026. Based on the weather forecast for the Qingming Festival in 2026 and the predicted flowering period, a self-guided tour plan for flower viewing during the Qingming Festival is drafted. By taking into account various factors such as the flowering time and period of flowers, the distance between cities, transportation costs, and weather conditions, an objective optimization model is established to plan the best travel route. This predicts the best route for flower viewing during the Qingming Festival in 2026 and provides a measure for the government to extend the "flower viewing economy" industrial chain, allowing the "flower viewing economy" to have an "extra-long flowering period". In light of the characteristics of the flowering period of different flowers, measures to extend the flowering period are provided, and corresponding measures and suggestions are given to the government and local flower viewing parks to extend the "flower viewing economy" industrial chain.
Holt-Winters; Seasonal Model; Probability of Rain; Flowering Prediction.
Research on Anti-Caking Properties of Potassium Dihydrogen Phosphate Fertiliser
This study aims to solve the caking problem of Potassium Dihydrogen Phosphate (KH₂PO₄) powder in storage. Developed anti caking agent consisting of three optimized components (Surfactant, Emulsifier, and Polyol). The research results indicate that the application of this anti caking agent to the KH₂PO₄ powder has an optimal caking rate of 5.4%. By contrast, the clumping rate of the reference substance is as high as 54.1% at the same condition. Its quality and structure were characterized through contact angle analyzer, surface tension analyzer, and scanning electron microscopy (SEM). This research serves as a reference for the quality and improvement of compound fertilizer.
Anti-caking; Potassium Dihydrogen Phosphate; Surface Tension.
Research on Electrochemical Composite Energy Fracturing Coal Seam Gas Treatment Technology
Using the 2608 transportation roadway of Zhangcun Coal Mine in Lu'an Mining Area as the engineering background, this study compared the differences between gas extraction using electrochemical composite energy pulse fracturing technology and conventional methods. Experimental results showed that after coal seam permeability enhancement treatment, both gas concentration in fracturing holes and auxiliary extraction holes within the affected zone increased significantly. The gas extraction concentration in treated areas reached up to three times higher than that in untreated original extraction holes, with the optimal fracturing influence radius being approximately 5.0~7.5m. Field gas extraction results demonstrated that electrochemical composite energy fracturing effectively modifies multi-scale pore-fracture structures in coal seams, facilitating gas desorption, diffusion, and migration. The gas permeability enhancement and extraction mechanism of electrochemical composite energy fracturing may involve: When shock stress waves penetrate coal seams, they generate stress at both ends of existing fractures, expanding their length and width while creating new fractures. Simultaneously, the stress induces tensile damage to coal matrix particles, causing fracture propagation. This process connects new fractures with existing ones, forming a complex fracture network that enhances gas migration and production capacity.
Electrochemical Composite Energy; Gas Extraction; Extraction Efficiency.
Optimization Design of Integrated High-Temperature Valve Bonnet Heat Dissipation Structure and Orthogonal Sensitivity Analysis of Key Parameters
This study investigates a compact Integrated High-Temperature Upper Bonnet by quantifying how cooling-fin geometry affects the valve-stem packing gland and setting optimization priorities for high-temperature valves. A 3D steady-state thermal model was built in ANSYS Workbench using the Finite Element Method and evaluated under 525 °C process gas. Orthogonal Experimental Design with range analysis assessed fin number, fin diameter depth, and fin spacing. Simulations show that heat conduction across the 1.5 mm stem-to-bonnet gap must be modeled; otherwise the packing-gland peak temperature is overestimated by up to 15.7%. Benchmarking indicates the integrated bonnet (235 mm) matches the cooling of a traditional extended bonnet (380 mm) while reducing height by 38.2%. Parameter influence ranks as fin number (R_A = 36.89) > fin diameter depth (R_B = 21.12) > fin spacing (R_C = 9.50), identifying fin number as the primary design lever. These results validate the integrated bonnet’s thermal performance and compactness and provide quantitative evidence for design and safety certification of high-temperature industrial valve accessories.
Integrated High-Temperature Upper Bonnet; Finite Element Method; Orthogonal Optimization; Cooling Fin; Heat Dissipation; Packing Gland Temperature.
Intelligent Health Management based on Photoelectric-Inertial Fusion Perception Tennis Sports Device
Nowadays, Scientific and technological innovation is reshaping the paradigm of sports development and health governance with unprecedented efforts. Intelligent wearable health management tennis equipment is based on photoelectric technology, sensing technology and artificial intelligence technology. Through the combination of software and hardware, data was accurately collected by the device through multi-modal fusion, the collected motion data and physiological data were analyzed in real time by the device using intelligent algorithms, and high performance and an ultra-low power wireless connection hub were provided for the device by NRF52840. The overall system framework of the equipment was mainly introduced in this paper. The progress results of photoelectric-inertial fusion sensing were summarized in this paper, and the shortcomings and future development of the project at this stage were expounded in this paper.
NRF52840; Photoelectric Sensor; Data Fusion Processing; Tennis Sport.
Strategies and Research Progress of Gelation Methods in Maintaining the Stability of Protein Drugs
Proteins are promising biotherapeutics that offer advantages such as higher specificity, greater activity, and lower toxicity compared to traditional small-molecule drugs. However, due to their complex structures, proteins are prone to degradation and denaturation, which affects the safety and efficacy of drugs. Over the past few decades, lyophilized formulations, liposomes, and polymer nanoparticles have been commonly used for drug delivery, but they have significant limitations. Thus, there is an urgent need for novel carriers to address these issues. This review summarizes the unique advantages of hydrogels in improving protein stability, as they effectively reduce protein aggregation, oxidation, and enzymatic degradation through mechanisms such as confinement effect, hydration regulation, and microenvironment optimization. Studies have shown that gel systems constructed based on natural/synthetic polymers have achieved key applications in vaccine sustained-release carriers, long-acting protein drugs, and tumor-targeted therapy.
The Correlation between Myopia and Pathological Progression in Glaucoma
In recent years, myopia and glaucoma have become two major threats to eye health and are also hot topics in ophthalmic disease research. Among the various areas of investigation, exploring the correlation between myopia and glaucoma lesions has become a core and high-priority research direction, given the growing clinical observation of their comorbidity. This paper systematically classifies and analyzes a large body of relevant studies published in recent years, aiming to synthesize the latest research progress. The analysis reveals that current research on the myopia-glaucoma correlation spans multiple dimensions, including epidemiological risk quantification, ocular structural changes, intraocular pressure regulation, genetic associations, and even racial differences. Relatively mature and consistent results have been obtained in key areas: for instance, how different degrees of myopia (especially high myopia) increase glaucoma risk, and what specific alterations myopia induces in ocular structures to promote glaucomatous damage. However, significant gaps persist in understanding genetic-level influences-only a handful of genes (e.g., SOX21, GSAP) have been preliminarily linked to both diseases, and the shared genetic pathways and regulatory mechanisms remain largely unelucidated. These findings not only help clarify the current state of research in this field but also provide clear guidance for future studies on the myopia-glaucoma correlation. Additionally, they offer valuable clinical clues for optimizing the early screening, diagnosis, and comprehensive management of patients with myopia-glaucoma comorbidity, ultimately contributing to better preservation of patients’ visual function.
Design and Implementation of SHA-512 Hash Function IP Core
To meet the requirements of verifying the correctness, integrity and whether the configuration file has been tampered with during the remote upgrade process of the FPGA configuration file, a SHA-512 IP core is designed to implement the digital signature verification of the configuration file on the FPGA. To facilitate interaction with other modules, the IP core adopts the AXI-stream interface to receive message data. A pipeline design approach is used to make message padding, message expansion and message compression proceed in sequence, reducing the processing delay of the IP core. No third-party IP cores are used in the design, making it easy to transplant and deploy on other domestic FPGAs. Finally, the designed IP core is tested on the AMD XC7K325TFFG676 chip. The test results show that the IP core can perform hash operations on messages and has stable performance.
Hash Function; SHA-512; FPGA; IP Core; Message Padding; Message Compression.
Research Progress of UAV in Precision Agriculture
With the development of precision agriculture, UAVs are widely used in agriculture for their efficiency, low cost, and flexible data - collection capabilities. This paper reviews UAV application research in precision agriculture, focusing on multispectral sensors in crop monitoring, CFD and COMSOL simulations in aerodynamic optimization, and the impact of extreme environments on UAV performance. Sensor technologies have improved crop status assessment accuracy, but flight stability and sensor protection in extreme weather are technical challenges. Although progress has been made in data collection and transmission technologies like LoRa and 5G, there are efficiency bottlenecks in large - scale farmland applications. By reviewing domestic and international studies, key challenges such as multi - factor coupled adaptability evaluation, sensor protection design optimization, and data processing algorithm improvements are identified. This research offers theoretical support for UAV technology's intelligent development in complex agricultural environments.
Unmanned Aerial Vehicle; Precision Agriculture; Sensor Technology; Extreme Weather Adaptability; CFD Simulation.
Advances and Future Directions in Laminated Bamboo Lumber-Steel Splice Connections
With the growing emphasis on green building and sustainable development, laminated bamboo lumber (LBL) has gained increasing attention as a green construction material known for its excellent mechanical properties and short renewal cycle. Connections are crucial for the safe transfer of forces within bamboo structures, and among them, LBL-steel plate connections have become a key focus of research and application due to their ease of construction, reliable force transfer, and good deformation performance. This paper reviews the research progress on LBL-steel plate connections, systematically analyzing the mechanical properties, failure modes, and key influencing factors (such as bolt diameter-to-thickness ratio, end distance, and anchorage depth) of different connection forms, including bolted, screwed, and hybrid connections. Research indicates that the failure modes (e.g., bamboo bearing, bolt bending, screw pull-out, or shear failure) and mechanical properties (e.g., load-bearing capacity, stiffness, ductility) of the connections are highly dependent on their geometrical parameters and connection methods. Existing timber design codes show poor adaptability for bamboo connections, highlighting the urgent need to develop design methods and theoretical models (such as the tri-linear stiffness model and elastic foundation beam theory) tailored to the characteristics of bamboo. Numerical simulation technology, particularly finite element analysis based on cohesive zone models, has become an effective supplementary means for studying the force-transfer mechanisms within connections. Finally, this paper outlines future research directions, including the long-term performance and durability of connections, dynamic response and seismic design, standardization and code development, and the exploration of new connection technologies, aiming to provide references for the refinement of bamboo structure theory and the promotion of its engineering practice.
Laminated Bamboo Lumber-Steel Plate Connections; Mechanical Properties; Connection Design; Connection Performance; Numerical Simulation.
Formation of Force Chains in the Crushing Zone of Roller Crushers and Strategies for Improving Unit Productivity
Addressing issues such as increased crushing force and energy consumption caused by the formation of force chains within the crushing zone during the operation of roller crushers, a new roller-type vibrating crusher that utilizes vibration to eliminate or reduce the formation of stress chains is proposed. Data is used to illustrate the superiority of this new roller-type vibration crusher, while demonstrating the methodology and support provided by EDEM for solving similar problems. Force reduction: The secondary crushing roller experienced a 57.27% reduction in load compared to high-pressure grinding rolls. The following results were obtained through simulation: Kinetic enhancement: Particle velocity increased by 28.5%, accompanied by a 23.34% rise in crushing ratio.Energy efficiency: Specific energy consumption decreased by 36.83%, while unit productivity surged by 58.3%.
New Roller-Type Vibrating Crusher; EDEM; High-Pressure Roller Mill; Comparative Analysis.
STM32-Based Heart Rate Variability Detection
Real-time monitoring of psychological stress is critical to maintaining physical and mental health. Although traditional ECG methods can provide accurate stress assessment, their complexity and high cost limit daily use. To address this issue, this paper designs a heart rate monitoring system based on the STM32F103C8T6 microcontroller, which provides an easy and cost-effective solution for stress monitoring. The system simplifies operations and reduces costs by detecting peak heartbeat signals to estimate interbeat interval (IBI) and analyse heart rate variability (HRV). The system uses the XD-58C PulseSensor for accuracy, including an OLED display for real-time data and a threshold range to ensure validity. Heart rate data can be uploaded to a PC platform for visualisation via serial communication, enabling users to track health trends. The system has been tested for ease of use, broad applicability, stable performance and high utility value to help individuals manage their mental health and as a preventive medicine tool to reduce the risk of disease and improve public health.
Stress Monitoring; STM32F103C8T6; Interbeat Intervals; Heart Rate Variability.
Accuracy Optimization and Engineering Applications of 3D Modeling for Complex Terrains based on UAV Oblique Photogrammetry
With the occurrence of UAV oblique photogrammetry, the collection of geographical information has been greatly optimized especially when it comes to creating 3D models of complicated terrains. It's got clear advantages over ordinary survey techniques like terrestrial laser scanning, manned aerial photogrammetry when it comes to being cheap, easy to operate, and providing detail. But getting the 3 models created of intricate landscapes with steep slopes, lush plantings, great rises and falls, and city canyons all to be very accurate is still very tough. This paper gives a thorough review along with detailed analysis of the essential technologies and methods for improving the exactness of 3D models which are obtained with UAV oblique aerial photographing method in complicated terrain. It covers the whole work flow all the way up to including the best flight missions with the most strategic data and using the latest data processing tools. Main areas include sensor characteristics and tough camera calibrations, the clever setup and location of Ground Control Points (GCPs), and how mixing direct georeferencing system information such as Real-Time Kinematic (RTK) and Post-Processed Kinematic (PPK) positioning data really transforms things. In addition, the paper looks at the meaningful influence of multiple source data synthesizing, combining oblique images with information obtained from sensors like Lidar, terrestrial photogrammetry etc to solve occlusion and to improve the completeness and verisimilitude of the model. analyze all sorts of factors affecting model's accuracy and present a number of mixed improvement approaches. The practical utility and effectiveness of these optimized models are illustrated via an in-depth review of their engineering applications which incorporate geological disaster monitoring, open-pit mine surveying, civil infrastructure inspection, as well as natural resources management. Four detailed tables, and quantified the improvement accuracy, and demonstrated the practical value in real-world project engineering, which could transform such technology into real-world project engineering.
UAV Oblique Photogrammetry; 3D Modeling; Complex Terrain; Accuracy Optimization; Engineering Applications; Ground Control Points (GCPs); Structure from Motion (SfM).
Production Line Balancing Optimization for Wire Harness Assembly Engineering
The rapid development of manufacturing has driven expansion in the automotive industry, placing wire harness manufacturers under dual pressure to enhance production efficiency and reduce costs. Addressing the challenges of low efficiency, uneven production rhythms, and prominent bottlenecks in wire harness assembly operations, this paper proposes a production line balancing method integrating industrial engineering theory with practical application techniques: Design and implement a Python-programmed wire navigation system to streamline wire positioning; Conduct 3D modeling of workstations to optimize layout and task area allocation; Evaluate the effectiveness of the optimization plan using metrics such as production line balancing rate and task duration. This research advances production line balancing in assembly engineering and offers practical reference value for the automotive wire harness manufacturing industry.
Wire Harness Processing; Assembly Engineering; Industrial Engineering; Production Line Balancing; Bottleneck Processes.
Intelligent Networked Vehicle Sensor Synthesis Experiment Box
The diversity of sensor technologies plays a critical role in intelligent connected vehicles (ICVs), yet existing educational platforms face challenges in cost and accessibility. This paper presents a low-cost, modular sensor synthesis experiment box tailored for ICV pedagogy. By integrating heterogeneous sensors (e.g. LiDAR, ultrasonic) with an STM32-based control system, the platform enables hands-on experiments on sensitivity analysis and multi-sensor fusion. Experimental results demonstrate a temperature measurement accuracy of ±1°C, while the user-friendly host computer interface improves operational efficiency by 40% compared to traditional setups. This work provides a scalable solution for sensor education in intelligent transportation systems.
Intelligent Connected Vehicles (ICVs); Multi - sensor Fusion; Sensor Technologies.
Feature Extraction and Stacking Model Analysis for Gallstone Disease Prediction based on UCI Dataset
Gallstone disease (GD) is a prevalent and multifactorial hepatobiliary disorder with complex etiological mechanisms involving metabolic, genetic, and environmental factors. Accurate early diagnosis is crucial to prevent complications such as cholecystitis, pancreatitis, and bile duct obstruction. However, conventional diagnostic procedures, including ultrasonography and computed tomography, are costly, operator-dependent, and not always feasible for population-level screening. In this study, a comprehensive machine learning framework is proposed to identify and predict gallstone occurrence using the UCI Gallstone Disease Dataset. The methodology integrates advanced data preprocessing, normalization, principal component analysis (PCA), multi-strategy feature selection, and a stacking ensemble learning architecture. After data cleaning and Z-score normalization, PCA was employed to reduce redundancy and extract latent diagnostic features explaining over 95% of the total variance. Three feature selection strategies-mutual information (MI), L1-regularized logistic regression, and random forest (RF) importance-were integrated to select the most discriminative clinical features. A stacking model combining Random Forest (RF), XGBoost (XGB), and Support Vector Machine (SVM) as base learners with Logistic Regression (LR) as the meta-classifier was implemented. The ensemble demonstrated strong generalization performance with cross-validation AUC = 0.8789 ± 0.0283, Accuracy = 0.8120 ± 0.0405, and test AUC = 0.9102, Accuracy = 0.8125, Recall = 0.8438, Specificity = 0.7812, and MCC = 0.6262. These findings indicate that the proposed approach effectively balances sensitivity and specificity, offering a practical computational model for gallstone risk screening and diagnosis.
Gallstone Disease; Ensemble Learning; Feature Extraction; Stacking Model; Principal Component Analysis; Biomedical Data Mining; Predictive Modeling.
Research on Deformed Character Generation Method based on CGAN
A deformed character generation model based on Conditional Generative Adversarial Network (CGAN) was developed to reduce the risk of tampering with contract texts. Taking advantage of the characteristics of Chinese characters with "dot" strokes, which have high independence and good deformation concealment, a dataset of "dot" stroke deformed characters was constructed based on edge detection, providing training samples for the Conditional Generative Adversarial Network (CGAN). Based on this, a "dot" stroke deformed character generation model using CGAN was established to achieve the conversion from normal characters to "dot" stroke deformed characters. The model accuracy was verified using Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR). The "dot" stroke deformed characters were applied to anti-tampering of contract texts. The verification results show that compared with normal characters, the "dot" stroke deformed characters generated by the model have an average SSIM of 97.86% and an average PSNR of 19.72 dB, verifying the effectiveness of the model. Compared with manually designed "dot" stroke deformed characters, the average SSIM and PSNR are further improved to 98.44% and 28.58 dB, indicating that the model has high accuracy. After recognition of the replaced "dot" stroke deformed characters in contract texts, the average SSIM reaches 97.82% and the PSNR is 22.82 dB. The "dot" stroke deformed character generation model established in this paper has high accuracy, providing theoretical and practical references for the field of text anti-counterfeiting.
Text Anti-counterfeiting; Deformed Characters;
Research Progress and Future Prospects of Bamboo-Steel Composite Beams
Amid the "dual carbon" strategy and green building trends, traditional steel and concrete structures have drawbacks like high carbon emissions. Bamboo-steel composite beams, merging bamboo and steel advantages, are a viable option, and this paper reviews their research progress. It classifies the beams by bamboo form, cross-sectional structure and connection method, summarizes domestic and foreign studies on composite beam structures and shear connectors, and elaborates on their theoretical analysis (flexural stiffness, serviceability limit state deflection, ultimate limit state moment). Finally, it notes current limitations and prospects for future development, to support engineering application and further research.
Bamboo-steel Composite Beam; Structural Classification; Shear Connector; Theoretical Analysis; Green Building; Dual Carbon Strategy.
Analysis of Factors Affecting the Pixel Performance of CMOS Image Sensors
A CMOS image sensor is a semiconductor device that converts optical signals into electrical signals. It is widely used in various fields such as digital cameras, smartphones, security surveillance, medical imaging, and automotive electronics, serving as the core component of modern imaging technology. The surface of the sensor is composed of an array of millions of tiny photo sensitive units (pixels). Each pixel contains a photodiode and several transistors. This paper investigates the pixel performance of CMOS image sensors, analyzes the factors that affect pixel performance, and summarizes potential improvement methods.
CIS; Temperature; Radiation; Pixel Structure; Manufacturing Process; Analysis and Summary.
Synthesis and Corrosion Inhibition Performance Evaluation of 4-Pyridinecarboxaldehyde-1,4-phenylenediamine Mono-Schiff Base
A planar rigid mono-Schiff base corrosion inhibitor, 4-pyridinecarboxaldehyde-1,4-phenylenediamine (PAM-4), was synthesized in this work. Nuclear magnetic resonance (NMR) spectroscopy confirmed the structure of the compound. The inhibitory effect of PAM-4 on mild steel in 1 mol/L HCl at 25°C, 35°C, and 45°C was assessed through weight loss measurements and electrochemical techniques. Scanning electron microscopy (SEM) was used to examine the surface morphology of mild steel before and after corrosion, demonstrating that PAM-4 provides effective protection. The results reveal that inhibitor concentration and temperature are key factors influencing performance. Inhibition efficiency improved with increasing PAM-4 concentration, achieving a maximum of 91.51% at 1600 mg/L. Conversely, elevated temperatures reduced the inhibition effect.
Corrosion; Corrosion Inhibitor; Mono-Schiff Base; Mild Steel; Corrosion Inhibition Performance.
Application of Unmanned Aerial Vehicles in Emergency Medical Field
This paper focuses on the application of unmanned aerial vehicles (UAVs) in the emergency medical field. Endowed with characteristics such as easy operation, flexibility and rapidity, UAVs play a crucial role in emergency medical services. They enable emergency delivery to enhance response speed, as exemplified by their assistance in patient transfer during the heavy rain in Zhengzhou and the significant improvement in drug delivery efficiency in Suzhou. Additionally, UAVs optimize medical resources to support remote areas, as seen in their use for transporting vaccines during the epidemic. They also enhance safety and provide telemedicine support. The paper further analyzes the technical and management scheduling challenges faced by UAV applications, including limited battery life and system incompatibility, and proposes countermeasures such as improving battery life and optimizing communication. It points out that UAVs will become a core tool in emergency medical services in the future.
Unmanned Aerial Vehicle; Emergency Rescue; Low-Altitude Economy.
Mechanical Behavior and Research Prospects of Curved Pipe Jacking
With the increasing emphasis on the sustainable development of underground space, the importance of trenchless pipe roofing jacking technology has become more prominent. In practical engineering, pipe jacking often needs to advance along a curved path due to geological conditions, environmental interferences, and other factors. Compared with the relatively mature technology of straight pipe jacking, curved pipe jacking demonstrates greater adaptability but also poses more severe challenges in terms of jacking force estimation, trajectory control, soil disturbance prediction, and the performance of pipe segments and joints. This paper systematically analyzes the differences between straight and curved pipe jacking, pointing out that the estimation of the jacking force for curved pipe jacking is a dynamic process influenced by multiple factors, which existing theoretical models struggle to accurately describe. The disturbance effect of curved jacking construction on the surrounding soil is more significant, with the research foundation for horizontal curved pipe jacking being particularly weak. Meanwhile, the mechanical performance of joints, such as flexural stiffness, is crucial for ensuring the success of curved jacking. Therefore, this paper proposes that future research should focus on three core directions: first, developing segmented or distributed theoretical models based on numerical simulations that can reflect the dynamic variation of jacking force; second, establishing accurate prediction models for soil disturbance and settlement specifically for curved pipe jacking, particularly for horizontal curves; third, developing joint design methods that balance mechanical performance, sealing, durability, and economic efficiency, while comparatively studying the mechanical behavior of joints in curved and straight pipe jacking. Relevant research holds significant theoretical and practical importance for enhancing the technical level of curved pipe jacking and ensuring engineering safety.
Curved Pipe Jacking; Soil Disturbance; Pipe Joints.
Research Flexural Test and Crack Development of PVA-steel Fiber Composite Reinforced Recycled Concrete Beams
Excessive crack width and numerous cracks in high-strength recycled concrete beams significantly impair their serviceability. To address this, steel fibers and polyvinyl alcohol (PVA) fibers-known for their excellent crack resistance-were incorporated into high-strength recycled concrete beams to effectively restrict crack development. Through flexural tests on six steel/PVA fiber-reinforced recycled concrete beams, one natural aggregate concrete beam, and one recycled concrete beam without fibers, the effects of PVA fiber volume ratio, steel fiber volume ratio, and PVA-steel hybrid fibers on the average crack width under serviceability limit state, maximum crack width under ultimate limit state, and the number of cracks during loading were investigated. The results demonstrate that the incorporation of hybrid steel and PVA fibers effectively inhibits cracking in recycled concrete beams, reducing the maximum crack width under ultimate load by 47.5%. The failure load of hybrid fiber-reinforced recycled concrete beams exceeded that of both single-fiber recycled beams and the natural concrete beam, while exhibiting crack resistance comparable to that of natural concrete.
Recycled Aggregate Concrete Beam; PVA Fiber; Steel Fiber; Maximum Crack Width; The Number of Cracks.
Research on the Weights of Subjective Evaluation Metrics of Automobile Squeak & Rattle based on Entropy Method
This study aims to objectively quantify the weights of subjective evaluation metrics for automobile squeak and rattle (S&R) using the entropy method. The paper first elaborates on the theoretical foundation and calculation steps of the entropy method, then integrates the core principles of the Analytic Hierarchy Process (AHP) to construct a comprehensive subjective evaluation framework. The test roads and operating conditions for subjective evaluation were clearly defined. In the evaluation experiment, three experienced engineers assessed five passenger vehicles on a proving ground using a 10-point scoring system. The collected rating data were processed using the entropy method to determine the weights of each metric, followed by the calculation of the overall subjective evaluation score for each vehicle. The results demonstrate that the entropy method, relying on objective data, effectively determines metric weights with high objectivity, providing a more scientific assessment approach for target setting in the early stages of vehicle development.
Squeak & Rattle; Subjective Evaluation; Entropy Method; Metric Weights.
Neutrino Tomography with Artificial Neutrino Beams: A Novel Approach to Probing Earth's Internal Structure and Density Profile
Understanding Earth's internal structure is critical for geophysical sciences, but traditional seismic tomography faces limitations such as the inability of S-waves to penetrate the liquid outer core and the difficulty in distinguishing minerals with similar seismic velocities. This study proposes a novel approach using neutrino tomography with artificial neutrino beams to address these challenges. Neutrinos, due to their weak interaction properties, can traverse the entire Earth, making them ideal probes for deep interior exploration. The methodology involves constructing a six-layer spherical Earth model (Continental Crust, Upper Mantle, Transition Zone, Lower Mantle, Outer Core, and Inner Core) based on the Preliminary Reference Earth Model (PREM). By simulating neutrino beams with fixed energy (10 GeV) propagating along six distinct trajectories through these layers, the absorption and survival probabilities of neutrinos are calculated using the Bouguer-Beer-Lambert Law and neutrino-nucleon interaction theory. A system of linear equations is derived to invert the Earth's density profile from the simulated survival data, validated through Monte Carlo simulations (1000 iterations with 10,000 neutrinos per path). Results show strong consistency between inverted densities and PREM, with a maximum relative error of 0.67% (Transition Zone) and a root-mean-square error (RMSE) of ~0.023 g/cm³. Notably, the inner core exhibits the smallest relative error (0.15%), highlighting neutrino tomography's unique advantage in penetrating high-density regions inaccessible to seismic S-waves. This study demonstrates the feasibility of neutrino tomography as a complementary tool to seismic methods, offering new insights into Earth's composition and dynamics with implications for geophysics, planetary science, and resource exploration.
Neutrino Tomography; Earth’s Internal Structure; Density Inversion; Neutrino-Nucleon Interaction; Preliminary Reference Earth Model.