Eurasia Journal of Science and Technology
type: channel
description: Eurasia Journal of Science and Technology (EJST) (Print ISSN: 2663-1024; Online ISSN: 2663-1016) is an international, peer-reviewed, open access journal published by Upubscience Publisher House. It covers a broad range of topics in science and technology, including engineering, computer science, environmental science, and applied physics. The journal publishes original research articles, reviews, and short communications.
publisher: Upubscience Publisher House
language: en
publication name: Eurasia Journal of Science and Technology
issn: 2663-1024
copyright: This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
items: AUTOMATIC SLEEP STAGE CLASSIFICATION USING MULTI-PHYSIOLOGICAL SIGNALS BASED ON PCBSLEEPNET
items: NON-DESTRUCTIVE TESTING METHOD FOR THE WIRE ROPE WITH DIFFERENT SURFACE WEAR
items: EXPERIMENTAL DATA FITTING AND INFLUENCING FACTORS ANALYSIS OF TEA WITHERING
items: WATER DAMAGE RESISTANCE OF LOW-TEMPERATURE MODIFIED ASPHALT MIXTURE
items: HYBRID FEATURE-ENHANCED 4D GAUSSIAN SPLATTING FOR DYNAMIC SCENE RECONSTRUCTION
items: DESIGN AND IMPLEMENTATION OF A KA-BAND SILICON-BASED 3D-HETEROGENEOUS-INTEGRATED 8-CHANNEL TRANSMIT MICROSYSTEM
items: CAN CONSUMER’S IDENTITY MANAGEMENT AFFECT PLATFORM’S BEHAVIOR-BASED PERSONALIZED PRICING?
items: AN INTEGRATED MULTI-SOURCE INFORMATION FUSION APPROACH FOR ENTERPRISE USER PORTRAIT CONSTRUCTION IN TECHNOLOGICAL DEMAND IDENTIFICATION
items: MATHEMATICAL MODELING AND HIGH-ORDER FINITE DIFFERENCE METHODS FOR SPATIAL FRACTIONAL FITZHUGH-NAGUMO EQUATIONS
items: DEEP LEARNING IN STROKE REHABILITATION COMPENSATORY MOVEMENT DETECTION: FROM LABORATORY BENCHMARKS TO CLINICAL REALITY
items: RAIL DAMAGE DETECTION SYSTEM BASED ON FUSION OF PLANAR CAPACITIVE SENSING AND VISION
items: OPTIMAL CROP PLANTING STRATEGIES BASED ON INTEGER LINEAR PROGRAMMING AND MONTE CARLO MODELS
items: FATIGUE LIFE ANALYSIS OF METRO AXLEBOX BEARINGS BASED ON A VEHICLE-BEARING COUPLED DYNAMICS MODEL
items: ULTRAFINE PALLADIUM NANOPARTICLES SUPPORTED ON THE MFI ZEOLITE FOR METHANE COMBUSTION REACRION
items: LIFE ATTITUDE PROFILES AMONG CHINESE UNIVERSITY STUDENTS: A SURVEY STUDY OF POSITIVE, LYING-FLAT, BUDDHA-LIKE, AND NEGATIVE MINDSETS
items: NEURAL-NETWORK-ASSISTED MODEL PREDICTIVE CONTROL FOR ACTUATORS IN NUCLEAR POWER PLANT DRIVE SYSTEMS
items: A CONTROL-DRIVEN DATA ASSET CLASSIFICATION METHOD FROM A RIGHTS PERSPECTIVE
items: INTELLIGENT FOLLOWING CAR BASED ON ULTRASONIC POSITIONING
items: RESEARCH PROGRESS ON HIGH-NITROGEN AUSTENITIC STAINLESS STEEL
items: OPTIMAL PLANTING STRATEGY BASED ON GOAL PROGRAMMING
items: UNSUPERVISED SEGMENTATION OF DEFORMING 3D MESHES VIA DEFORMATION-AWARE GRAPH CUTS
items: GROUP PHARMACOKINETICS OF FLUCONAZOLE IN PATIENTS WITH SEVERE INFECTION
items: EXTENSION OF NEW MODEL WITH GOOD APPROXIMATION BASED ON RECURRENCE RELATION
items: ROBUST MULTI-OBJECTIVE CROP PLANNING IN MOUNTAINOUS NORTHERN CHINA VIA LP–NSGA-II–MONTE CARLO
items: THE CORRELATION BETWEEN LIFESTYLE AND PREVALENCE OF HIP JOINT DISEASE IN PLATEAU AREAS
items: LATERAL FORCE OF MIXING DRUM IN CONCRETE MIXER TRUCK BASED ON EDEM
items: OPTIMAL CROP PLANTING STRATEGY BASED ON PARTICLE SWARM ALGORITHM
items: A RETRIEVAL-AUGMENTED GENERATION FRAMEWORK FOR EXPLAINABLE ACADEMIC PAPER QUALITY ASSESSMENT
items: THE FORMATION MECHANISM OF EMERGENCY RESPONSE CAPACITY IN MAJOR EMERGENCIES AT THE GRASS-ROOTS LEVEL
items: BASED ON UNITY3D, TWO-PLAYER COOPERATION CAPTURES THE DESIGN AND IMPLEMENTATION OF THE GOBLIN GAME "INK WALKER"

AUTOMATIC SLEEP STAGE CLASSIFICATION USING MULTI-PHYSIOLOGICAL SIGNALS BASED ON PCBSLEEPNET
type: item
description: Automatic sleep staging, a key technology in sleep medicine, faces feature selection challenges due to multi-modal physiological signal heterogeneity. This study establishes a framework to evaluate bioelectrical signals' impacts on deep neural network feature representation, aiming to identify optimal integration paradigms.We propose a multi-branch hybrid neural network with: 1) a three-channel parallel convolutional module incorporating cascaded residual and dilated convolutions for time-frequency feature extraction, and 2) bidirectional long short-term memory (BiLSTM) layers for temporal dependency modeling. We systematically analyzed multi-channel electroencephalogram (EEG), single-channel physiological signals, and their combinations covering both single-channel and multi-channel configurations of EEG, electrooculogram (EOG), and electromyogram (EMG). Results demonstrate that six-channel EEG configurations outperformed single/dual-channel implementations. In the single- and dual-channel EEG settings, the C3-M2 and C4-M1 + C3-M2 channels exhibited superior performance. EEG maintained superior classification capability over EOG/EMG. The tri-modal fusion (EEG+EOG+EMG) achieved peak performance (accuracy: 89.5%, Cohen’s κ: 0.85). This demonstrates EEG's central role in sleep staging, while EOG/EMG synergistically enhance model performance. The findings reveal heterogeneous bioelectric signal interactions in deep neural networks, providing foundations for optimizing signal fusion strategies and model architectures.
subject: Articles
  topic: section
subject: Deep learning
  topic: keywords
subject: Sleep staging
  topic: keywords
subject: Multi-physiological signals
  topic: keywords
subject: Polysomnography
  topic: keywords
creator: YuLi Yang
creator: Ying Liu
creator: HaoWei Zhang
rights: Copyright (c) 2026 YuLi Yang; Ying Liu; HaoWei Zhang https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-03
publication date: 2026-04-03
starting page: 1
ending page: 8
doi: 10.61784/ejst3140

NON-DESTRUCTIVE TESTING METHOD FOR THE WIRE ROPE WITH DIFFERENT SURFACE WEAR
type: item
description: Steel wire ropes, as key load-bearing components, suffer from significant wear and broken wire damage during their service period, which poses a serious threat to operational safety. Addressing the issues such as the single excitation method in traditional eddy current detection methods, the large noise interference from the phase wave, and the low accuracy of damage quantitative identification, this paper proposes a new non-destructive testing method that combines a dual-level excitation structure with signal processing. Firstly, a dual-level excitation structure composed of three asymmetric magnetic poles on the left, middle, and right sides was designed. By using differentiated permanent magnet grades (N35/N52/N52) and a 60 mm magnetic pole spacing, two independent intervals with significantly different excitation intensities (up to 7.7%) were formed within the steel wire rope, effectively reducing mutual interference. Subsequently, through finite element simulation analysis, the influence of magnetic pole parameters on the excitation effect was investigated, and a signal processing method based on offset superposition and sliding average filtering was proposed to effectively suppress periodic phase wave noise. Experimental results show that this method established a high-precision cubic polynomial quantitative model between the number of broken wires and the peak-to-peak value of the eddy current signal (coefficient of determination R² = 0.995), and compared with existing detection devices, the error rate of broken wire identification was significantly reduced from 51.3% to 13.3%. This research provides an effective technical means for the precise quantitative identification of wire rope wear and broken wire damage, especially composite damage.
subject: Articles
  topic: section
subject: Wire rope
  topic: keywords
subject: Surface wear
  topic: keywords
subject: Nondestructive testing
  topic: keywords
creator: LiShuo Wu
creator: Kun Huang
creator: GongNing Li
creator: XiangDong Chang
creator: LiQun Xiong
creator: Zhou Zhou
rights: Copyright (c) 2026 LiShuo Wu; Kun Huang; GongNing Li; XiangDong Chang; LiQun Xiong; Zhou Zhou https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-02
publication date: 2026-04-02
starting page: 92
ending page: 108
doi: 10.61784/ejst3139

EXPERIMENTAL DATA FITTING AND INFLUENCING FACTORS ANALYSIS OF TEA WITHERING
type: item
description: With the continuous progress of tea factory intelligence and modernization, the construction of tea withering mode plays the important role on the product quality in the process of tea withering. It is very important to analyze the construction of tea withering model and the analysis of influencing factors for the improvement of product quality in the process of tea withering. In this paper, the weight of each factor of tea withering on the trend and time of water loss and weight loss of the whole withering was successfully analyzed by means of multiple regression analysis. When withering to 50 % weight loss, the weight of each factor from large to small is temperature, humidity, tea green layer number, tea green density. At the same time, multiple regression analysis was used to predict the trend of withering water loss and weight loss under different conditions. The model data fitting can better control the withering time, and has positive significance for the post-mortem investigation of the withering process.
subject: Articles
  topic: section
subject: Withering process
  topic: keywords
subject: Factor analysis
  topic: keywords
subject: MATLAB curve fitting
  topic: keywords
subject: Multiple regression analysis
  topic: keywords
subject: Stability evaluation
  topic: keywords
creator: ZhenHua Shao
creator: GuoShi Li
creator: JiaLiang Ye
creator: JiaCheng Ye
creator: YuQin Liu
creator: MeiXue Lin
creator: PengFu Ye
rights: Copyright (c) 2026 ZhenHua Shao; GuoShi Li; JiaLiang Ye; JiaCheng Ye; YuQin Liu; MeiXue Lin; PengFu Ye https://creativecommons.org/licenses/by-nc/4.0
date: 2026-03-27
publication date: 2026-03-27
starting page: 83
ending page: 91
doi: 10.61784/ejst3138

WATER DAMAGE RESISTANCE OF LOW-TEMPERATURE MODIFIED ASPHALT MIXTURE
type: item
description: This paper analyzes the influence law of water damage on the strength and stability of low-temperature modified asphalt mixture, and discusses the action mechanism of raw material characteristics, mix proportion design, construction technology and environmental factors on water stability. The research shows that the water damage of low-temperature modified asphalt mixture is mainly caused by asphalt film peeling, aggregate softening and internal structure damage due to water intrusion; the addition of modified components such as rubber powder and polymer resin can significantly improve the water damage resistance of the mixture; optimizing the asphalt-aggregate ratio, improving the aggregate gradation and adopting reasonable construction temperature control measures can effectively reduce the risk of water damage.
subject: Articles
  topic: section
subject: Low-temperature modified asphalt mixture
  topic: keywords
subject: Water damage resistance
  topic: keywords
subject: Anti-stripping
  topic: keywords
subject: Prevention and control measures
  topic: keywords
subject: Water stability
  topic: keywords
creator: XiaoPeng Tong
rights: Copyright (c) 2026 XiaoPeng Tong https://creativecommons.org/licenses/by-nc/4.0
date: 2026-03-24
publication date: 2026-03-24
starting page: 78
ending page: 82
doi: 10.61784/ejst3137

HYBRID FEATURE-ENHANCED 4D GAUSSIAN SPLATTING FOR DYNAMIC SCENE RECONSTRUCTION
type: item
description: Real-time modeling of dynamic scenes is a pivotal challenge in computer vision and graphics. Methods employing canonical space deformation with 3D Gaussians have achieved compelling speed, but a fundamental limitation persists: their feature representation often fails to capture the complex interplay of spatial, temporal, and multi-scale information in dynamic settings. This paper introduces a hybrid feature enhancement framework that systematically addresses this core issue. Our key idea is to forge a powerful and adaptive feature representation through the synergistic co-design of three modules: a Spatial Relation Module that explicitly encodes geometric context, a Dynamic Feature Adapter that employs gating for temporal conditioning, and a Multi-scale Integration Module that dynamically aggregates features across scales. The primary contribution of our work is this unified architecture designed to robustly enhance the feature backbone of deformation-based dynamic Gaussian representations. Extensive experiments on major benchmarks, including D-NeRF and HyperNeRF, demonstrate that our framework consistently elevates reconstruction quality, achieving superior performance over state-of-the-art methods on key metrics like PSNR and SSIM, thereby validating its general effectiveness.
subject: Articles
  topic: section
subject: 4D Gaussian splatting
  topic: keywords
subject: Hybrid feature enhanced
  topic: keywords
subject: Dynamic scene reconstruction
  topic: keywords
creator: Sha Li
creator: WanXiang Qin
rights: Copyright (c) 2026 Sha Li; WanXiang Qin https://creativecommons.org/licenses/by-nc/4.0
date: 2026-03-24
publication date: 2026-03-24
starting page: 70
ending page: 77
doi: 10.61784/ejst3136

DESIGN AND IMPLEMENTATION OF A KA-BAND SILICON-BASED 3D-HETEROGENEOUS-INTEGRATED 8-CHANNEL TRANSMIT MICROSYSTEM
type: item
description: This paper presents the design and implementaion of a Ka-band Silicon-Based 3D-Heterogeneous-Integrated 8-channel transmit microsystem. By introducing capacitive and inductive transition structures in the 3D passive interconnections of the microsystem, up to 40GHz broadband impedance matching is realized. Meanwhile, a three-layer Cu-Sn bonded silicon interposer architecture and its corresponding fabrication process are developed for the implementation of the two stacked sub-modules. And sub-modules stacking and fan-out of ball grid array (BGA) pins are achieved using solders and solder balls with differentiated temperature gradients. The fabricated 8-channel transmit microsystem features 1 input port and 8 output ports, with an operating frequency band over 27–32 GHz, a saturated output power of 23 dBm, an overall dimensions of 9.1 mm × 8.5 mm × 3.25 mm, and a weight of less than 0.1 g per channel.
subject: Articles
  topic: section
subject: 3D heterogeneous integration
  topic: keywords
subject: Microsystem
  topic: keywords
subject: Silicon interposer
  topic: keywords
subject: Metal bonding
  topic: keywords
subject: Temperature gradient
  topic: keywords
creator: Ming Wei
rights: Copyright (c) 2026 Ming Wei https://creativecommons.org/licenses/by-nc/4.0
date: 2026-03-13
publication date: 2026-03-13
starting page: 56
ending page: 69
doi: 10.61784/ejst3135

CAN CONSUMER’S IDENTITY MANAGEMENT AFFECT PLATFORM’S BEHAVIOR-BASED PERSONALIZED PRICING?
type: item
description: With the development of big data and platform economy, platforms can easily gather consumer information through first-period purchase and exercise personalized pricing. When consumers realize it, they may engage in identity management to bypass the platform’s attempt to price discriminate. Therefore, it is significant to clarify the impact of identity management on platform’s behavior-based price discrimination, and whether platforms continue to compete consumers if they realize that consumers may engage in identity management. We introduce the identity management into the standard framework of behavior-based price discrimination, then we analyze and compare equilibrium results with and without identity management. The main findings are as the follows: (i) when consumers are active in identity management, the competition between platforms is intensified in the information collection stage, but it is softened in the information application stage, and platforms can exercise perfect price discrimination to consumers. (ii) The consumer identity management leads to lower consumer surplus and higher social welfare. When consumers become farsighted, platforms can be better off. (iii) platforms still have incentives to compete with consumers and gather consumer information, even though platforms predict that consumers are active in the identity management. (iv) Compared to one-sided market, the consumer identity management in two-sided market makes platforms more willing to implement perfect price discrimination.
subject: Articles
  topic: section
subject: Behavior-based price discrimination
  topic: keywords
subject: Personalized pricing
  topic: keywords
subject: Identity management
  topic: keywords
subject: Platform
  topic: keywords
creator: KaiHua Bao
creator: ZhiQiang Zhang
creator: Ting Zhang
rights: Copyright (c) 2026 KaiHua Bao; ZhiQiang Zhang; Ting Zhang https://creativecommons.org/licenses/by-nc/4.0
date: 2026-03-09
publication date: 2026-03-09
starting page: 31
ending page: 55
doi: 10.61784/ejst3134

AN INTEGRATED MULTI-SOURCE INFORMATION FUSION APPROACH FOR ENTERPRISE USER PORTRAIT CONSTRUCTION IN TECHNOLOGICAL DEMAND IDENTIFICATION
type: item
description: In the context of the innovation-driven development paradigm, the accurate identification of enterprise technological demands has become a core theoretical and practical issue in the field of technology transfer. Traditional demand identification paradigms are constrained by single-dimensional text analysis, leading to the lack of a systematic understanding of technological demands. To address this gap, this study proposes an integrated multi-source information fusion approach for enterprise user portrait construction oriented to technological demand identification. This approach systematically clarifies the connotation of enterprise technological demand portraits, defines the multi-dimensional information sources of portrait construction based on methodological logic, establishes a feature extraction system based on the dual dimensions of explicit and potential demands, and explores the mechanism of technological demand reconstruction through multi-source information fusion. This study enriches the methodological system of user portrait and technological demand identification, and provides technical guidance for breaking the information asymmetry in technology transfer.
subject: Articles
  topic: section
subject: Technological demand
  topic: keywords
subject: Enterprise user portrait
  topic: keywords
subject: Multi-source information fusion approach
  topic: keywords
subject: Demand identification
  topic: keywords
subject: Feature extraction
  topic: keywords
creator: HongYu Su
rights: Copyright (c) 2025 HongYu Su https://creativecommons.org/licenses/by-nc/4.0
date: 2025-12-22
publication date: 2025-12-22
starting page: 36
ending page: 43
doi: 10.61784/ejst3123

MATHEMATICAL MODELING AND HIGH-ORDER FINITE DIFFERENCE METHODS FOR SPATIAL FRACTIONAL FITZHUGH-NAGUMO EQUATIONS
type: item
description: Mathematical modeling of the spatial fractional-order FitzHugh-Nagumo equations provides a critical framework for describing the propagation of electrical potentials in heterogeneous cardiac tissues, a problem that continues to attract significant research attention. Due to the geometrically irregular cross-sections of cardiac tissue, numerical solutions on conventional regular or approximately irregular domains remain limited, and analytical solutions are generally unavailable. In this study, we employ a high-order finite difference method in space coupled with a fourth-order Runge-Kutta scheme in time to solve this nonlinear fractional-order system. Numerical experiments are conducted to validate the high-order convergence and computational stability of the proposed numerical approach.
subject: Articles
  topic: section
subject: Riesz fractional derivative
  topic: keywords
subject: FitzHugh-Nagumo model
  topic: keywords
subject: Finite difference method
  topic: keywords
subject: The fourth-order explicit Runge-Kutta method
  topic: keywords
creator: WenYe Jiang
creator: QiZhi Zhang
creator: Yu Li
rights: Copyright (c) 2025 WenYe Jiang; QiZhi Zhang; Yu Li https://creativecommons.org/licenses/by-nc/4.0
date: 2025-12-25
publication date: 2025-12-25
starting page: 44
ending page: 50
doi: 10.61784/ejst3125

DEEP LEARNING IN STROKE REHABILITATION COMPENSATORY MOVEMENT DETECTION: FROM LABORATORY BENCHMARKS TO CLINICAL REALITY
type: item
description: Stroke rehabilitation is going through some pretty major changes right now. We're seeing a gradual move away from those subjective clinical scales toward more objective, automated assessments—though it's not happening as fast as some people hoped. Traditional methods like the Fugl-Meyer Assessment (FMA) are still considered the gold standard in clinics, but they've got some real problems. They're time-consuming, different raters often give different scores, and they tend to hit ceiling effects that miss subtle improvements patients are making.This review looks at important studies from 2016 to 2025. We trace how automated detection systems evolved from those lab-based depth sensors to RGB cameras you can use at home and wearable IMUs. We compare different sensing technologies and look at public datasets. There's also this "sim-to-real" gap issue - basically, models trained on healthy actors often don't work well with real patients, which is a big problem. The algorithms have changed a lot too, going from traditional machine learning to foundation models. Clinical metrics have also expanded beyond simple detection to things like severity grading.At the end, we talk about what this all means for tele-rehabilitation and why getting clinicians to actually adopt these technologies is still really challenging. We suggest a roadmap that focuses on privacy-preserving collaboration and long-term validation studies, though honestly implementing all of this won't be easy.
subject: Articles
  topic: section
subject: Stroke rehabilitation
  topic: keywords
subject: Compensatory movement
  topic: keywords
subject: Deep learning
  topic: keywords
subject: Multimodal fusion
  topic: keywords
creator: Xiao Xu
creator: HaoNan Qin
creator: LanShu Zhou
rights: Copyright (c) 2026 Xiao Xu; HaoNan Qin; LanShu Zhou https://creativecommons.org/licenses/by-nc/4.0
date: 2026-01-12
publication date: 2026-01-12
starting page: 1
ending page: 6
doi: 10.61784/ejst3127

RAIL DAMAGE DETECTION SYSTEM BASED ON FUSION OF PLANAR CAPACITIVE SENSING AND VISION
type: item
description: This research addresses the specific and crucial application scenario of railway track damage detection by designing and implementing a comprehensive intelligent detection system solution. At the hardware architecture level, the system meticulously selects the high-performance STM32F103 microcontroller as the core control unit. This unit offers fast processing speed, low power consumption, and high reliability, laying a solid foundation for the system's stable operation. Centered around this core control unit, the system integrates various functional modules, including high-precision detection modules like planar capacitive sensors for real-time and accurate collection of track status data. Simultaneously, the OpenMV visual processing module is utilized to achieve precise machine vision recognition of track surface defects, significantly enhancing the intuitiveness and accuracy of detection. Additionally, the system is equipped with a motor drive module to enable precise movement of the detection device. The system not only features excellent hardware configuration but also possesses powerful data processing capabilities, enabling real-time and efficient analysis and processing of the collected massive data, thereby significantly improving detection accuracy and timeliness. In terms of material selection, the system innovatively adopts new energy-saving and environmentally friendly materials, which not only substantially reduce the overall energy consumption of the system but also effectively extend the equipment's service life, markedly enhancing its durability. This system integrates numerous advantages such as efficient detection, energy saving, environmental protection, and low-cost operation, demonstrating broad application prospects and significant market promotion potential in the field of railway operation and maintenance. It is expected to provide a solid and powerful guarantee for the safe and stable operation of railways.
subject: Articles
  topic: section
subject: Microcontroller
  topic: keywords
subject: Sensor
  topic: keywords
subject: Rail damage
  topic: keywords
subject: Planar capacitance
  topic: keywords
subject: High efficiency and energy saving
  topic: keywords
subject: OpenMV visual processing
  topic: keywords
creator: YuYang Xia
creator: ZhongFu Liu
rights: Copyright (c) 2025 YuYang Xia; ZhongFu Liu https://creativecommons.org/licenses/by-nc/4.0
date: 2025-11-11
publication date: 2025-11-11
starting page: 5
ending page: 12
doi: 10.61784/ejst3118

OPTIMAL CROP PLANTING STRATEGIES BASED ON INTEGER LINEAR PROGRAMMING AND MONTE CARLO MODELS
type: item
description: This study investigates optimal crop planting strategies for a mountainous village in North China during 2024–2030 to maximize profits. Two optimization models were developed for different market scenarios. First, assuming stable market and production parameters, an integer linear programming model is developed to maximize profits while incorporating core agricultural constraints: field type compatibility, crop rotation to avoid replanting, and legume rotation. This model solves for optimal planting schemes under two scenarios: (1) surplus production leading to unsold waste, and (2) surplus sales at a 50% discount. Second, to address uncertainties and potential risks in projected sales volume, yield per mu, planting costs, and sales prices over the coming years, a Monte Carlo model was introduced for analysis. This method simulates fluctuations in parameters (e.g., annual sales growth rate of 5%–10%, yield variation of ±10% per mu) through random sampling, calculates maximum average returns, and thereby determines the optimal planting area allocation scheme with risk resilience in uncertain environments.
subject: Articles
  topic: section
subject: Crop planting strategy
  topic: keywords
subject: Integer linear programming
  topic: keywords
subject: Monte Carlo simulation
  topic: keywords
subject: Discount
  topic: keywords
creator: CongCong Wang
creator: YuLu Ding
creator: XuZhe Chen
creator: WeiHao Zhou
creator: TianLe Cheng
rights: Copyright (c) 2025 CongCong Wang; YuLu Ding; XuZhe Chen; WeiHao Zhou; TianLe Cheng https://creativecommons.org/licenses/by-nc/4.0
date: 2025-11-17
publication date: 2025-11-17
starting page: 18
ending page: 24
doi: 10.61784/ejst3120

FATIGUE LIFE ANALYSIS OF METRO AXLEBOX BEARINGS BASED ON A VEHICLE-BEARING COUPLED DYNAMICS MODEL
type: item
description: Considering the nonlinear characteristics of tapered roller bearings, a coupled dynamic model of a metro vehicle and axle box bearings is established. Based on actual track geometry and train operational schedules, the dynamic force on the axle box bearings are simulated and analyzed under full working conditions, including traction, braking, negotiation of curves with different radii, and straight-line running. The simulation results indicate that compared to traditional vehicle dynamics models, the differences in bearing dynamic force predicted by this coupled model are mainly concentrated above 100 Hz. According to the train operational loads and track characteristics, a full life-cycle dynamic load spectrum for the axle box bearings is constructed. Using this load spectrum and a rolling contact finite element model of the bearing, the dynamic stress spectra at critical nodes of each bearing component are analyzed, followed by an assessment of their fatigue life. The computational results show that, compared to traditional L-P method-based fatigue life calculations using rated dynamic force derived from axle weights, the proposed method—which evaluates bearing fatigue life based on actual application conditions—aligns more closely with reality. This approach can provide more accurate data support for the residual life assessment and maintenance strategy formulation of metro axle box bearings.
subject: Articles
  topic: section
subject: Metro axlebox bearing
  topic: keywords
subject: Vehicle-bearing coupled dynamics
  topic: keywords
subject: Dynamic load spectrum
  topic: keywords
subject: Fatigue life
  topic: keywords
creator: YiFan Yang
creator: LinHua Fan
creator: ZhengGang Lu
rights: Copyright (c) 2026 YiFan Yang; LinHua Fan; ZhengGang Lu https://creativecommons.org/licenses/by-nc/4.0
date: 2026-01-23
publication date: 2026-01-23
starting page: 15
ending page: 24
doi: 10.61784/ejst3130

ULTRAFINE PALLADIUM NANOPARTICLES SUPPORTED ON THE MFI ZEOLITE FOR METHANE COMBUSTION REACRION
type: item
description: The environmental impact of methane's incomplete combustion underscores the importance of catalytic oxidation, a process in which palladium (Pd) nanoparticles serve as a highly active catalyst despite their tendency to aggregate during synthesis and operation due to inherent high surface energy. Zeolites, as nanoporous materials with ordered micropore structures and excellent thermal stability, are considered ideal supports for stabilizing noble metal nanoparticles. Herein, MFI-type zeolite nanosheets rich in silanol defects were used as supports to prepare finely dispersed Pd nanocatalysts (Pd/SP-S-1 and Pd/SP-ZSM-5) via incipient wetness impregnation. The resulting catalysts exhibited excellent activity toward methane combustion. The T 90 (temperature for 90% methane conversion) value of Pd/SP-S-1 was 459 °C, which is lower than that of the catalyst supported on conventional S-1 zeolite. Introducing acidity further enhanced the catalytic performance, lowering the T 90 of Pd/SP-ZSM-5 to 426 °C. Moreover, the acidic zeolite framework improved the stability of Pd nanoparticles. The Pd/SP-ZSM-5 catalyst maintained stable activity for nearly 50 h at 430 °C. This work highlights the potential of zeolite-confined Pd catalysts for methane combustion and provides insights into designing synergistic catalytic systems combining metallic and acidic sites.
subject: Articles
  topic: section
subject: Pd nanocatalyst
  topic: keywords
subject: Methane
  topic: keywords
subject: Catalytic combustion
  topic: keywords
subject: Zeolite
  topic: keywords
creator: Tao Cai
creator: Ning Wang
creator: Yue Sun
rights: Copyright (c) 2026 Tao Cai; Ning Wang; Yue Sun https://creativecommons.org/licenses/by-nc/4.0
date: 2026-02-05
publication date: 2026-02-05
starting page: 25
ending page: 30
doi: 10.61784/ejst3131

LIFE ATTITUDE PROFILES AMONG CHINESE UNIVERSITY STUDENTS: A SURVEY STUDY OF POSITIVE, LYING-FLAT, BUDDHA-LIKE, AND NEGATIVE MINDSETS
type: item
description: Introduction: Amid the massification of higher education and rapid social transformation in China, university students face intensified academic competition, uncertain mobility prospects, and heightened psychosocial stress. These conditions make “attitudes toward life” a consequential construct for understanding how students evaluate life circumstances and translate such evaluations into coping and action tendencies. However, existing studies often examine positive functioning and distress-related outcomes separately, with limited integration of co-existing orientations such as engagement, withdrawal, and goal attenuation. Objectives: This study aims to develop a context-sensitive Life Attitude Scale (LAS) and to map the overall pattern and subgroup differences of college students’ life attitudes across four co-existing orientations: positive mindset, lying-flat mindset, Buddha-like mindset, and negative mindset. Methods: A cross-sectional, on-site paper-and-pencil survey was administered to students from nine colleges at a university in Guangzhou, yielding 287 valid responses (effective rate 89.69%). The LAS comprised 19 items across four subscales (5, 5, 5, and 4 items, respectively) rated on a 5-point Likert-type scale; survey data were analyzed in SPSS 27.0 with psychometric screening and nonparametric group comparisons, supplemented by interview materials for contextual interpretation. Results: Descriptive results showed that the positive mindset was highest (M = 4.093), while the lying-flat mindset (M = 2.419) and the negative mindset (M = 2.190) remained comparatively low; the Buddha-like mindset was near the midpoint (M = 2.987). Kruskal-Wallis tests indicated statistically significant differences across selected background variables, including discipline-related variation in positive mindset, as well as gender- and family-background-related variation in low-desire orientations and negative mindset. Discussion: The findings depict an overall positive life or…
subject: Articles
  topic: section
subject: University students
  topic: keywords
subject: Life attitudes
  topic: keywords
subject: Current situation analysis
  topic: keywords
subject: Cognitive differences
  topic: keywords
creator: Liu Yang
rights: Copyright (c) 2025 Liu Yang https://creativecommons.org/licenses/by-nc/4.0
date: 2025-12-29
publication date: 2025-12-29
starting page: 57
ending page: 65
doi: 10.61784/ejst3126

NEURAL-NETWORK-ASSISTED MODEL PREDICTIVE CONTROL FOR ACTUATORS IN NUCLEAR POWER PLANT DRIVE SYSTEMS
type: item
description: This study develops a unified dynamic modeling framework for nuclear-grade actuators, such as fans, pumps, and valves, critical for reactor cooling, feedwater regulation, and ventilation. These actuators exhibit nonlinearities, cross-coupling, and operational constraints, challenging conventional controllers to maintain performance and safety under fluctuating conditions. To address this, a neural-network-assisted model predictive control (NN-MPC) architecture is proposed. The framework incorporates a mask-based input encoding strategy to represent all actuators within a single model, and a fully differentiable neural network is trained to approximate actuator dynamics. A bias-compensation mechanism is introduced to address multi-step prediction drift caused by process variations and aging. The resulting nonlinear MPC integrates actuator constraints, output limitations, rate restrictions, and real-time optimization, ensuring millisecond-level performance required in nuclear applications. The implementation workflow includes real-time execution analysis, anomaly detection, safety fallback logic, and hardware-in-the-loop validation. Experimental results demonstrate that the NN-MPC framework provides accurate modeling, high-performance control, and compliance with nuclear safety requirements. This research offers a robust pathway for advancing intelligent, data-driven control systems in next-generation nuclear power plants.
subject: Articles
  topic: section
subject: Nuclear power plant actuators
  topic: keywords
subject: Neural network prediction model
  topic: keywords
subject: Model predictive control
  topic: keywords
subject: Bias compensation
  topic: keywords
subject: Real-time optimization
  topic: keywords
creator: Yuan Zhang
creator: YanKun Li
creator: Chao Si
rights: Copyright (c) 2025 Yuan Zhang; YanKun Li; Chao Si https://creativecommons.org/licenses/by-nc/4.0
date: 2025-12-12
publication date: 2025-12-12
starting page: 25
ending page: 35
doi: 10.61784/ejst3121

A CONTROL-DRIVEN DATA ASSET CLASSIFICATION METHOD FROM A RIGHTS PERSPECTIVE
type: item
description: Against the backdrop of the digital economy, the process of data assetization is accelerating. However, in operational links such as registration, utilization, and transaction, institutional data rights have failed to be translated into enforceable implementation mechanisms, leading to ambiguous rights, responsibilities, and inefficient circulation. From a rights management perspective, this paper proposes a tripartite classification framework for data assets: identification data resolves issues of attribution, raw material data regulates usage based on clarified ownership, and tool data further enables the distribution of benefits. This framework integrates the national policy of "Tripartite Rights Separation", analyzes the distinct rights characteristics of different data types, and designs differentiated governance pathways. It aims to provide institutional support for data assetization operations and foster the efficient functioning of the data factor market.
subject: Articles
  topic: section
subject: Data assetization
  topic: keywords
subject: Data classification
  topic: keywords
subject: Tripartite rights separation
  topic: keywords
subject: Differentiated governance
  topic: keywords
creator: DaXing Chen
creator: Kun Meng
creator: YuChen Zhao
creator: QiYuan Wang
rights: Copyright (c) 2025 DaXing Chen; Kun Meng; YuChen Zhao; QiYuan Wang https://creativecommons.org/licenses/by-nc/4.0
date: 2025-12-29
publication date: 2025-12-29
starting page: 51
ending page: 56
doi: 10.61784/ejst3124

INTELLIGENT FOLLOWING CAR BASED ON ULTRASONIC POSITIONING
type: item
description: Aiming at the problem of blind area of safety monitoring in electric power operation site, an intelligent following car based on ultrasonic positioning is designed in this paper. The target coordinates are calculated by dual-chip ranging to achieve ± 10 cm accuracy tracking, supporting a maximum identification distance of 10 meters and a dynamic response of 1.5 m/s. The system adopts STM32F103RBT6 main control board, integrates ultrasonic sensor and wireless communication module, and combines with base-station and tag positioning mechanism to solve the problem of monitoring failure caused by manual intervention lag of traditional monitoring equipment. The test shows that the car can last for 4 hours under the condition of slope ≤ 15 ° and load 30 kg, which effectively improves the efficiency of operation safety management and control.
subject: Articles
  topic: section
subject: Intelligent following
  topic: keywords
subject: Ultrasonic positioning
  topic: keywords
subject: Safety monitoring
  topic: keywords
subject: Electric power operation
  topic: keywords
subject: Mobile robot
  topic: keywords
creator: WenFang Yang
creator: BuSheng Luo
creator: Guang Luo
rights: Copyright (c) 2025 WenFang Yang; BuSheng Luo; Guang Luo https://creativecommons.org/licenses/by-nc/4.0
date: 2025-10-29
publication date: 2025-10-29
starting page: 1
ending page: 4
doi: 10.61784/ejst3117

RESEARCH PROGRESS ON HIGH-NITROGEN AUSTENITIC STAINLESS STEEL
type: item
description: Advancements in metallurgical technology, coupled with the ever-growing industrial demand, have continuously driven the development of new materials. High-nitrogen austenitic stainless steel (HNASS), a resource-saving material, has been extensively investigated and rapidly developed owing to its high strength, high plasticity, and excellent corrosion resistance. This paper chronologically outlines the development of Cr–Mn–N series HNASS, which has evolved primarily through nickel-saving high-manganese austenitic stainless steel (such as AISI 200 series stainless steel), low-carbon molybdenum-containing austenitic stainless steel (such as AL6XN), and nickel-free HNASS (such as P900, developed by the VSG company of Germany). The development of HNASS is constrained by advancements in smelting technology. This paper outlines the current smelting methods for high-nitrogen steel, including atmospheric pressure smelting and high-pressure smelting, and summarizes the issues encountered during the smelting process. Welding technology is another key factor limiting the industrial application of HNASS. Extensive research has been conducted to reduce the number of welding defects in high-nitrogen steel. By optimizing welding processes and improving welding filler materials, welding joints with good performance can be obtained. However, welding technology for HNASS with universal applicability and industrialization potential still warrants further research.
subject: Articles
  topic: section
subject: High-performance materials
  topic: keywords
subject: High-nitrogen austenitic stainless steel
  topic: keywords
subject: Smelting technology
  topic: keywords
subject: Pressure electric-slag remelting
  topic: keywords
subject: Welding technology
  topic: keywords
creator: YanYan Hong
creator: XiaoPing Huang
creator: Di Lu
rights: Copyright (c) 2026 YanYan Hong; XiaoPing Huang; Di Lu https://creativecommons.org/licenses/by-nc/4.0
date: 2026-01-15
publication date: 2026-01-15
starting page: 7
ending page: 14
doi: 10.61784/ejst3128

OPTIMAL PLANTING STRATEGY BASED ON GOAL PROGRAMMING
type: item
description: In order to maximize the income of agriculture, this paper established linear programming models for the two cases of more than half selling and more than half selling with the constraints of plot area, continuous cropping restrictions, legume crop rotation, planting plots should not be dispersed and crop planting adaptability restrictions. Then it was solved by genetic algorithm, and the optimization results were divided into four categories according to the category of crops: grain, vegetables, edible fungi and beans. The uncertainty risk is measured by calculating the standard deviation of the expected sales volume, yield per mu, planting cost and sales price of crops, and the objective function of minimizing the risk is determined by the weighted sum of the four risk variances. Then, under the condition that more than half price is sold, a double objective optimization model with the objective function of maximizing income and minimizing risk is established, which is solved by NSGA-II algorithm The substitution and complementarity are incorporated into the risk model through the risk weighting mechanism, and the objective function is updated. Then, the Pareto frontier graph is generated by using NSGA-II algorithm. Compared with the results of problem 2, it is found that after considering the substitution and complementarity of agricultural products, the optimal solution set becomes more replaceable, more selective, and more extensive search space.
subject: Articles
  topic: section
subject: Double objective optimization
  topic: keywords
subject: Genetic algorithm risk model
  topic: keywords
subject: NSGA-II algorithm
  topic: keywords
subject: Pareto frontier
  topic: keywords
creator: Yang Rong
creator: ShunYu Li
creator: YuXin Wang
rights: Copyright (c) 2025 Yang Rong; ShunYu Li; YuXin Wang https://creativecommons.org/licenses/by-nc/4.0
date: 2025-11-17
publication date: 2025-11-17
starting page: 13
ending page: 17
doi: 10.61784/ejst3119

UNSUPERVISED SEGMENTATION OF DEFORMING 3D MESHES VIA DEFORMATION-AWARE GRAPH CUTS
type: item
description: We propose an unsupervised method for segmenting deforming 3D mesh sequences using a deformation-aware graph cut. Our approach constructs a spatiotemporal graph and formulates segmentation as a minimum s-t cut problem. Unary costs, derived from per-vertex deformation energy, separate near-rigid parts from deforming regions, while pairwise costs enforce spatial smoothness. By iteratively applying max-flow/min-cut, the algorithm greedily extracts coherent parts without supervision. Results show the automatic partitioning of complex animations into meaningful, temporally-consistent components, validating our approach.
subject: Articles
  topic: section
subject: Graph cut
  topic: keywords
subject: 3D mesh segmentation
  topic: keywords
subject: Unsupervised learning
  topic: keywords
creator: Yu Su
rights: Copyright (c) 2025 Yu Su https://creativecommons.org/licenses/by-nc/4.0
date: 2025-08-26
publication date: 2025-08-26
starting page: 11
ending page: 16
doi: 10.61784/ejst3107

GROUP PHARMACOKINETICS OF FLUCONAZOLE IN PATIENTS WITH SEVERE INFECTION
type: item
description: Objective: The aim was to investigate the population pharmacokinetics (PopPK) model of Vorticamole (VRC), identify significant covariates and corresponding dose optimization strategies in the existing clinical patient VRC PopPK model, and explore the characteristics of the existing VRC PopPK model. Methods: We searched the PubMed database for clinical PopPK studies of VRC using the nonlinear mixed-effects method from the establishment of the database to May 2025, and screened the relevant references. Results: A total of 29 studies that met the inclusion criteria were finally included. One-compartment and two-compartment models were reported in 21 and 7 studies, respectively, as the best models to describe the PopPK of VRC, and one study used a three-compartment model. More than 40 covariates were included in the screening, with the most common covariates being CYP2C19 phenotype and body weight, and ALB being a secondary covariate. The typical volume of distribution in adult and pediatric patients was similar, but the estimated clearance in pediatric patients was significantly higher than that in adult patients, and the estimated bioavailability in pediatric patients was significantly lower than that in adult patients. The typical values of voriconazole clearance and total apparent volume of distribution exhibit substantial variability, ranging from 2.29–7.35 L/h and 76–194 L, respectively. Twenty-four studies used the exponential model as the basic model to describe the inter-individual variation. Only three studies used external methods to evaluate the model. Conclusion: First, this paper emphasizes the broadness and variability of the estimated PopPK parameters of VRC and provides the covariates that affect the clearance and apparent volume of distribution in such patients. Second, external evaluation of PopPK models should be conducted, and the predictive performance of various models should be further compared to improve the extrapolation ability of the models. …
subject: Articles
  topic: section
subject: Voriconazole
  topic: keywords
subject: Population pharmacokinetics
  topic: keywords
subject: Exposure-response relationship
  topic: keywords
creator: Lu Yao
creator: Wei Bu
creator: Min Luo
creator: Liu Shi
creator: HongBo Xu
creator: WenMei Liang
creator: Yan Chen
creator: Tao Chen
creator: Bao Fu
creator: Lei Gong
rights: Copyright (c) 2025 Lu Yao; Wei Bu; Min Luo; Liu Shi; HongBo Xu; WenMei Liang; Yan Chen; Tao Chen; Bao Fu; Lei Gong https://creativecommons.org/licenses/by-nc/4.0
date: 2025-09-01
publication date: 2025-09-01
starting page: 39
ending page: 55
doi: 10.61784/ejst3111

EXTENSION OF NEW MODEL WITH GOOD APPROXIMATION BASED ON RECURRENCE RELATION
type: item
description: By using novel recurrence relation, some models with good approximation are constructed, which include three aspects: extension of curve of degree n, extension of surface of degree n over rectangular domain. First, based on a novel recurrence relation, we define a Quasi-Bernstein-basis of degree n with multiple parameters, which includes the classical Bernstein basis of degree n as a special case and has similar properties with the classic Bernstein basis. And the definition, properties, comer cutting algorithm, adjustable effect and quantification of approximation of related curves are discussed in detail. Next, tased on Quasi-Bernstein-basis, we develop a tensor product surface with multiple parameters over rectangular domain, and discuss continuity of Quasi-Bézier-surface at length. Compared with the existing methods, the proposed models keep can beautiful properties of classical method and the multiple parameters introduced in these models can flexibly adjust shape of the generated model and possess good approximation.
subject: Articles
  topic: section
subject: Recurrence relation
  topic: keywords
subject: Bernstein basis
  topic: keywords
subject: Corner cutting algorithm
  topic: keywords
subject: De Cateljau-type algotithm
  topic: keywords
creator: PeiPei Ji
creator: JunHui Yang
rights: Copyright (c) 2025 PeiPei Ji; JunHui Yang https://creativecommons.org/licenses/by-nc/4.0
date: 2025-10-18
publication date: 2025-10-18
starting page: 75
ending page: 81
doi: 10.61784/ejst3116

ROBUST MULTI-OBJECTIVE CROP PLANNING IN MOUNTAINOUS NORTHERN CHINA VIA LP–NSGA-II–MONTE CARLO
type: item
description: This paper addresses the optimization of crop planting strategies for a mountainous rural village in northern China, characterized by diverse land resources and strict crop rotation requirements. A comprehensive mathematical modeling framework is developed, incorporating linear programming, genetic algorithms (NSGA-II), and Monte Carlo simulation to address multi-objective optimization and uncertainty in agricultural production. The study considers multiple practical constraints, including land type suitability, crop rotation, legume planting frequency, and limitations on greenhouse cultivation. The results reveal that the proposed models can effectively generate robust, adaptive cropping plans that maximize economic returns while reducing planting risks under both stable and fluctuating market conditions. The integration of Monte Carlo simulation enables the model to account for yield, price, and cost uncertainty, providing decision-makers with reliable strategies for risk management. The findings offer theoretical and practical guidance for agricultural planners and farmers, and the modeling framework has strong scalability for application in diverse environments.
subject: Articles
  topic: section
subject: Crop planting optimization
  topic: keywords
subject: Crop rotation
  topic: keywords
subject: Genetic algorithm
  topic: keywords
subject: Monte carlo simulation
  topic: keywords
subject: Uncertainty management
  topic: keywords
subject: Agricultural decision-making
  topic: keywords
creator: ChiHo Thong
creator: Jun Ren
creator: ShuHao Liu
rights: Copyright (c) 2025 ChiHo Thong; Jun Ren; ShuHao Liu https://creativecommons.org/licenses/by-nc/4.0
date: 2025-08-15
publication date: 2025-08-15
starting page: 1
ending page: 10
doi: 10.61784/ejst3105

THE CORRELATION BETWEEN LIFESTYLE AND PREVALENCE OF HIP JOINT DISEASE IN PLATEAU AREAS
type: item
description: This study systematically analyzed the relationship between lifestyle habits and the incidence of hip joint disease in high-altitude areas, focusing specifically on the mechanisms by which factors such as low oxygen levels, strong ultraviolet radiation, traditional infant swaddling methods, and unique walking patterns influence hip joint health. This study provides a scientific basis for the prevention and control of hip joint disease in high-altitude areas.
subject: Articles
  topic: section
subject: Plateau area
  topic: keywords
subject: Prevalence of hip arthritis
  topic: keywords
subject: Relevance
  topic: keywords
creator: JianCheng Li
creator: Peng Zhou
creator: KaiZhao Pang
creator: JiRong Li
rights: Copyright (c) 2025 JianCheng Li; Peng Zhou; KaiZhao Pang; JiRong Li https://creativecommons.org/licenses/by-nc/4.0
date: 2025-08-30
publication date: 2025-08-30
starting page: 32
ending page: 38
doi: 10.61784/ejst3110

LATERAL FORCE OF MIXING DRUM IN CONCRETE MIXER TRUCK BASED ON EDEM
type: item
description: Concrete demonstrates fluid properties, which results in specific dynamic behaviors during the transit of concrete mixer trucks. A defining operational trait of these vehicles is that their Concrete Mixing Drum sustain continuous rotation while the trucks are in motion. When a concrete mixer truck makes a turn, the concrete inside the Concrete Mixing Drum undergoes load migration—a phenomenon primarily induced by the combined effects of the concrete’s intrinsic fluidity and the centrifugal force generated by the Concrete Mixing Drum’s rotation. This load migration is often accompanied by dynamic impacts that exert forces on the Concrete Mixing Drum and the vehicle’s chassis. Notably, when the truck’s speed increases slightly, the aforementioned load migration and dynamic impacts further deteriorate the vehicle’s roll stability. Once the roll stability drops below a critical level, the risk of the truck encountering a rollover accident rises significantly, potentially endangering road safety, property, and human lives. To address this pressing issue, the present study focuses on investigating the Lateral Force generated during the concrete mixing process, as these forces are key factors contributing to the compromised roll stability of the vehicle. To achieve this research goal, EDEM software—a specialized tool for discrete element method simulations—was utilized to conduct numerical simulations of the concrete mixing process inside the Concrete Mixing Drum. The simulations were designed to cover two distinct Filling Ratio conditions of the Concrete Mixing Drum: one with a Filling Ratio of 1:1, corresponding to a total mass of concrete and aggregates of 10,000 kg, and the other with a Filling Ratio of 1:1.2, where the total mass of concrete and aggregates amounts to 12,000 kg. Additionally, three different Rotational Speed of the Concrete Mixing Drum—2 rpm (revolutions per minute), 5 rpm, and 10 rpm—were incorporated into the simulations to examine their respective i…
subject: Articles
  topic: section
subject: Concrete mixing drum
  topic: keywords
subject: Filling ratio
  topic: keywords
subject: Rotational speed
  topic: keywords
subject: Lateral force
  topic: keywords
creator: YuHuan Gao
rights: Copyright (c) 2025 YuHuan Gao https://creativecommons.org/licenses/by-nc/4.0
date: 2025-08-29
publication date: 2025-08-29
starting page: 21
ending page: 31
doi: 10.61784/ejst3108

OPTIMAL CROP PLANTING STRATEGY BASED ON PARTICLE SWARM ALGORITHM
type: item
description: With the development of rural economy, optimizing planting strategy is an important research topic in organic planting industry. At present, most experts are not clear about the binding conditions for crop planting. This paper searched for data on agricultural products and local soil conditions in Hutang Town, Changzhou City, Jiangsu Province, and identified data on local cropping strategies for 2023. Based on the above data and the ideas of linear programming and multi-objective programming, the planting strategy optimization model under multiple constraints was established by determining planting risk factors and other indicators to seek the optimal crop planting strategy with maximum returns, and particle swarm optimization algorithm was used to solve the model. Finally, the optimal planting strategy under certain conditions and uncertain factors is obtained, and the complex problems arising from the optimal crop planting strategy are solved.
subject: Articles
  topic: section
subject: Linear programming
  topic: keywords
subject: Monte carlo simulation
  topic: keywords
subject: Poisson process
  topic: keywords
subject: Particle swarm optimization
  topic: keywords
creator: TianYou Zuo
creator: LiangYing Ji
creator: YuSa Liu
rights: Copyright (c) 2025 TianYou Zuo; LiangYing Ji; YuSa Liu https://creativecommons.org/licenses/by-nc/4.0
date: 2025-08-27
publication date: 2025-08-27
starting page: 17
ending page: 20
doi: 10.61784/ejst3109

A RETRIEVAL-AUGMENTED GENERATION FRAMEWORK FOR EXPLAINABLE ACADEMIC PAPER QUALITY ASSESSMENT
type: item
description: With the exponential growth of global scholarly output, traditional academic paper evaluation methods face significant challenges in reliability, consistency, and scalability. Peer review processes suffer from low inter-rater agreement and lengthy decision times, while bibliometric approaches systematically disadvantage emerging fields. To address these systemic limitations, this study proposes a novel evaluation framework leveraging Retrieval-Augmented Generation (RAG) architecture and large language models (LLMs). The framework implements a four-dimensional assessment mechanism—analyzing research questions, methodologies, results, and conclusions—supported by contextual knowledge retrieval and explainable judgment generation. Experimental validation demonstrates the superiority of the RAG-based approach over both human experts and conventional machine learning baselines, achieving an F1-score of 0.77 at the quartile level. Additionally, the system provides transparent evaluative judgments supported by comparable evidence from prior literature. This work contributes to advancing scholarly communication by offering a scalable, explainable, and reliable alternative to existing evaluation paradigms.
subject: Articles
  topic: section
subject: Retrieval-Augmented Generation
  topic: keywords
subject: Academic paper evaluation
  topic: keywords
subject: Contextual knowledge retrieval
  topic: keywords
subject: Explainable AI
  topic: keywords
creator: WeiJing Zhu
creator: RunTao Ren
creator: Wei Xie
creator: CenYing Yang
rights: Copyright (c) 2025 WeiJing Zhu; RunTao Ren; Wei Xie; CenYing Yang https://creativecommons.org/licenses/by-nc/4.0
date: 2025-07-30
publication date: 2025-07-30
starting page: 56
ending page: 61
doi: 10.61784/ejst3102

THE FORMATION MECHANISM OF EMERGENCY RESPONSE CAPACITY IN MAJOR EMERGENCIES AT THE GRASS-ROOTS LEVEL
type: item
description: The emergency response capacity of major emergencies at the grass-roots level includes both potential emergency response capacity elements and emergency response capacity realization mechanisms. The emergency response capability realization mechanism is not only the mechanism for potential emergency response capability elements to be transformed into real emergency response capability, but also the environmental conditions and institutional guarantee for the formation of emergency response capability. In the formation process of emergency response capacity for major emergencies at the grassroots level, potential emergency response capacity elements, emergency response capacity realization mechanism and real emergency response capacity elements interact and influence each other to form a complete emergency response capacity. Therefore, this study will start from the analysis of the role of emergency response capacity realization mechanism on the transformation of potential emergency response capacity into real emergency response capacity, and explain the mechanism of emergency response capacity formation in major emergencies at the grassroots level.
subject: Articles
  topic: section
subject: Grass-roots level
  topic: keywords
subject: Emergencies
  topic: keywords
subject: Emergency response capacity
  topic: keywords
subject: Formation mechanism
  topic: keywords
creator: ZiXuan Liu
creator: HaoLin Tian
rights: Copyright (c) 2025 ZiXuan Liu; HaoLin Tian https://creativecommons.org/licenses/by-nc/4.0
date: 2025-08-04
publication date: 2025-08-04
starting page: 62
ending page: 71
doi: 10.61784/ejst3104

BASED ON UNITY3D, TWO-PLAYER COOPERATION CAPTURES THE DESIGN AND IMPLEMENTATION OF THE GOBLIN GAME "INK WALKER"
type: item
description: This paper takes Ink Walker, a Chinese-style two-player cooperative goblin-catching game developed based on the Unity3D engine, as the research object. Combining practical experience from Game Jam competitions, it explores the design and implementation process of the game. The research centers on three core goals: the visual design of Chinese-style elements, the innovation of two-player collaboration mechanisms, and the cross-platform technical implementation. It unfolds from aspects such as artistic concept design (including the setting of world view and plot, the visual design of characters, goblins, scenes and UI), technical indicators and research methods (covering technical foundations and development toolchains, the technical implementation of core gameplay, system architecture and performance optimization), and performance optimization strategies. By integrating Chinese-style culture with game design, innovating two-player collaboration mechanisms, utilizing Unity3D to realize cross-platform development and conduct performance optimization, it provides technical solutions and creative paradigms for the development of similar Chinese-style games, and has certain theoretical and practical significance.
subject: Articles
  topic: section
subject: Ink Walker
  topic: keywords
subject: Unity3D
  topic: keywords
subject: Two-player cooperation
  topic: keywords
subject: Goblin catching
  topic: keywords
subject: Chinese style
  topic: keywords
subject: Game design and implementation
  topic: keywords
creator: Yue Zhou
rights: Copyright (c) 2025 Yue Zhou https://creativecommons.org/licenses/by-nc/4.0
date: 2025-09-02
publication date: 2025-09-02
starting page: 56
ending page: 62
doi: 10.61784/ejst3113