bluuebunny/crossref_metadata_2025 huggingface dataset:
What motivates academics in Egypt toward generative AI tools? An integrated model of TAM, SCT, UTAUT2, perceived ethics, and academic integrity
Authors: Mohamed Eldakar Metwaly Ali , Khafaga Shehata Ahmed Maher , Abdelrahman Ammar Abdelrahman Saber
Published: January 2025

In recent years, the adoption of AI technologies in academia has increased, prompting a need to explain factors driving scholars to adopt or plan to adopt AI technologies in research routines. This study integrates three models into one integrated model: TAM, UTAUT, and SCT. These three models are combined to understand how GenAI self-efficacy, perceived ethics, academic integrity, social influence, facilitating conditions, perceived risks, ease of use, and perceived usefulness influenced the participants’ intention to adopt GenAI in research. Following this, data were collected from Egyptian academics linked to Egyptian universities. There were 742 responses to this question. Data were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The paper's results showed that GenAI self-efficacy, social influence, and perceived ethics are significantly related to perceptions of ease of use, usefulness, and intention to use GenAI. Facilitating conditions have a negative effect on perceived ease of use, and perceived risk does not affect perceived usefulness or intention to use significantly. Notably, the result found that ethics and academic integrity affect perceptions of GenAI's usage and utility. This guide illustrates how universities must take proactive steps to influence how AI will be used and reinforces the importance of using these tools within an ethical lens. This paper emphasizes the need to balance the use of generative AI and ethical practices. It examines the role of ethics and academic integrity in perceptions that influence attitudes toward the use of generative AI. They represent a step forward in our understanding of how to induce AI adoption–in this case, in the academic context, and specifically in Egypt. Additionally, it places sound emphasis on the role of AI technology and how it can be beneficial whilst advocating for a sensible approach in that application, which includes ethical principles.
Fault compensation-based adaptive tracking control for nonlinear systems with actuator saturation and multiple sensor faults
Authors: Guo Yao-Yao , Han Yu-Qun , Sun Jing-Jing , Zhu Shan-Liang
Published: January 2025

An adaptive tracking control scheme based on a multi-dimensional Taylor network(MTN) is proposed for nonlinear systems with multiple sensor faults and actuator saturation. This article utilizes a smooth hyperbolic tangent function to transform the non-smooth actuator saturation model into a smooth linear model, thus addressing the challenges posed by actuator saturation on the system. By applying a third-order absolute value Lyapunov function and incorporating it into the adaptive control design process, the estimation of fault losses and design of compensation coefficients are carried out to eliminate the effects of sensor faults. Experimental results demonstrate that the proposed controller can eliminate the impact of sensor faults and actuator saturation, ensuring that all signals in the closed-loop system remain within bounded ranges. Additionally, it can drive the tracking error to converge to a small region near the origin.
Synthesis of selenium containing quinoline probe for superoxide sensing and its anticancer activity study
Authors: Salunke Shrikrishna T , Shelar Divyesh S , Salunkhe Snehal S , Singh Pinky R , Vaidya Shashikant P , Manjare Sudesh T
Published: January 2025

Herein, we have reported the highly effective use of the Knoevenagel condensation reaction to synthesize organoselenium containing quinoline-based probe. The probe was characterized by Nuclear Magnetic Resonance and Infra-Red spectroscopy and mass spectrometry. The probe selectively detects KO2 with high sensitivity over other reactive oxygen species and biothiols. Photo-induced electron transfer process is responsible for fluorescence “ turn-on” event through transformation of selenide to selenoxide. The probe reacted with KO2 in less than a second with lower detection limit (0.14 μM). The probe have better anticancer potency as compared to standard drug Cisplatin.
Science Process Skills and Study Habits of Secondary School Students on Their Cognitive Outcomes in Biology
Authors: Thamarasseri Ismail , Martin Divya
Published: January 2025

The study investigates the science process skills and study habits of secondary school students on their cognitive outcomes in biology. Using a survey method, data were collected from 300 students selected through stratified random sampling from schools in Kottayam District, Kerala. Data were gathered employing instruments designed to assess science process skills, study habits, and cognitive outcomes. Findings underscore the importance of fostering science process skills and study habits to improve academic performance. The study offers insights for educators and policymakers to develop strategies that enhance biology education and promote the practical application of knowledge at the secondary level.
Research on information retrieval and knowledge discovery in future learning center with virtual reality technology
Authors: Ji Ying
Published: January 2025

To enhance user experience, search accuracy, and retrieval speed, ensuring easier access to required information for learners, this study utilized the K-means algorithm to gather extensive behavioral data from students’ virtual learning environments, including browsing, searching, and interaction information. An information retrieval model was subsequently developed, employing a vector space model to represent documents and queries. Document clustering was performed using the K-means algorithm to boost retrieval efficiency. Additionally, student clustering through the K-means algorithm led to the creation of student profiles, enabling a more precise understanding of their academic interests and needs. In terms of knowledge recommendation, a personalized recommendation process was designed. By analyzing students’ historical behaviors, a model of their knowledge interests was established, and based on this model, a tailored knowledge recommendation strategy was formulated for each student. The study results indicated that the search accuracy of virtual reality technology reached 93%, with an average response time of 2.5 seconds, surpassing traditional learning environments. This demonstrates that the proposed method provides a valuable reference for information retrieval and knowledge discovery in future learning centers.
Multi-objective optimization of traditional residential timber frames based on response surface methodology
Authors: Yuanyao Miao , Dongbo Li , Chunyan Liu , Yan Wang , Xiguang Liu , Bo Wen
Published: January 2025

Traditional residential timber frames, embodying centuries of Chinese craftsmanship, continue to thrive. In today’s era of increasingly scarce global resources, optimizing these timber frames not only preserves their legacy but also contributes to structural weight reduction, aligning with the goal of lightweight construction. To determine the optimal design dimensions for these frames, this study introduces a combined optimization approach using Response Surface Methodology (RSM) and Multi-Objective Genetic Algorithm (MOGA). Using the Optimal Space-Filling (OSF) method, sample points within the design domain were collected to establish a response surface model, correlating frame dimensions with key structural metrics: maximum deformation, maximum Mises stress, and total mass. The model’s fitting accuracy was also evaluated. MOGA was employed to optimize the response surface model, yielding Pareto-optimal solutions. Additionally, a parametric sensitivity analysis was conducted on the frame based on the response surface model. Simulation experiments demonstrate that the optimal span-to-depth ratio of the frame is 0.23. Compared to the initial frame structure, the optimized frame exhibited a 10.09% reduction in mass, a 27.47% decrease in maximum deformation, and a 2.46% reduction in maximum Mises stress. The findings of this study provide valuable insights for related engineering applications and a calculation model for the fatigue damage degree of concrete was proposed.
Fatigue performance test of concrete and study on damage assessment model
Authors: Yuanyao Miao , Ditao Niu
Published: January 2025

Fatigue performance tests on concrete specimens were conducted using a three-point equal amplitude loading method. As the number of fatigue loadings increased, microcracks inside the concrete extended and expanded, forming through-cracks that gradually developed into macroscopic, large cracks that rapidly propagated across the entire cross-section. Under different stress levels, the specimens exhibited a relatively stable ultimate residual strain value when fatigue failure occurred, while the maximum strain varied significantly. The development of bending fatigue deformation followed a three-stage pattern. Microscopic testing methods such as SEM electron microscope scanning and mercury intrusion porosimetry (MIP) were employed to analyze the whole process of deterioration and evolution of microcracks and pore structures in fatigue-damaged concrete. Fatigue loading damage resulted in a significant reduction in harmless and less harmful pores, or micropores, inside the concrete, while the proportion of harmful and more harmful pores increased substantially. Macroscopically, this was manifested as further intensification of fatigue performance deterioration. The entire fatigue development pattern is a process of continuous damage accumulation, culminating in instantaneous brittle fatigue fracture at failure. Based on the fundamental theory of continuum damage mechanics, the damage degree D was determined by quantifying the cumulative damage of concrete using residual strain. A fatigue damage evolution equation was derived from theoretical deductions, and a calculation model for the fatigue damage degree of concrete was proposed.
Study on failure pressure and life prediction of defective pipelines based on numerical simulation
Authors: Huang Zhiwei , Wang Dong , Yao Zhilan , Zhao Xiuyang , Han Jianxiao
Published: January 2025

In order to further control the running state of water supply and drainage pipeline, and provide reference for later maintenance. This study used Abaqus to construct simulation models for pipelines of X52, X65, and X80 grades under various corrosion defects, analyzing the variations in pipeline failure pressure due to corrosion depth, length, and width. Additionally, it proposed a predictive model for the failure pressure of corroded pipelines and utilized a BP neural network model to assess the remaining service life of corroded pipelines. The results show that the numerical model and strength evaluation, when compared with actual burst results, have a minimum relative error of only 1.45% in simulation. The failure pressure of flawed pipes diminishes as the corrosion depth and length increase, but remains relatively constant with corrosion width. Meanwhile, every time the corrosion defect depth coefficient increases by 0.1, the failure pressure decreases by 0.9–2.6 MPa. A formula has been fitted to the corrosion depth and length, with parameters [Formula: see text], [Formula: see text], and [Formula: see text] being 1.3141, −0.3053, and 0.5212, respectively, and a correlation coefficient R of 0.977. The BP neural network model exhibits a low mean square error of 0.014, indicating its effectiveness in calculating the remaining lifespan of corroded pipelines.
Multi-source heterogeneous data fusion technology for electric power based on big data mining
Authors: Liu Zhongjian , Qian Ruixin , Jin Xianing , Zhao Hanlin , Li Hongyi , Hu Danlei , Hu Hanghai
Published: January 2025

With the rapid development of smart grid technology, a large amount of multi-source heterogeneous data has been generated in the power system, and its effective utilization is crucial for the optimization operation, demand prediction, and anomaly detection of the power system. However, the fusion processing of multi-source heterogeneous data faces many challenges, such as inconsistent data format, granularity, and quality, and direct fusion can easily lead to information redundancy and contradictions. A multi-source heterogeneous data fusion technology based on big data mining has been proposed to address the above issues. This method combines the advantages of convolutional neural networks and gated recurrent units to automatically extract features from image and sequence data and handle long-term dependency issues in time series data. Meanwhile, the K-means clustering algorithm is used to preprocess the data and train a specialized ConvGRU model. The results showed that in short-term load forecasting and abnormal electricity consumption behaviour detection tasks, the accuracy of this method reached 96.3% and 98.7%, respectively, with AUC values of 0.994 and 0.996. Compared to models that use only CNN or GRU, the performance is significantly improved. This method effectively solves the problem of integrating and processing multi-source heterogeneous power data, improves the accuracy and efficiency of power system data analysis, and provides strong support for the optimized operation of smart grids.
Abnormal traffic identification algorithm of large-scale network based on linear discriminant analysis
Authors: Zhang Dawei
Published: January 2025

With the increasing emphasis on network security, monitoring and identifying abnormal network traffic has become a research hotspot in the field of network security. In order to efficiently identify abnormal network traffic, this study proposes the use of linear discriminant analysis to process the data features of network traffic. The processing method is to separate different categories of features through mapping. Then, the principal component analysis method is used for feature normalization and a new feature matrix with low fit is constructed. The features in this matrix not only have independence, but also retain the differential characteristics of the samples. Finally, by introducing support vector machines to classify the feature matrix, the anomaly recognition of the samples is completed. The experimental results show that the feature extraction algorithm proposed in this study can achieve a maximum feature separation of 95%, and not only can complete classification within 39 ms as quickly as possible, but also has an error rate of only 0.5%. The classifier can achieve a maximum recognition rate of 98.6% for different types of abnormal traffic, and the highest accuracy rate can reach 99.1%. In summary, the improved classifier proposed in the study has excellent performance and can be used in network traffic recognition applications.
Undergraduates’ online teaching satisfaction and influencing factors based on grounded theory under the background of Internet Plus
Authors: Xiao Min , Su Lin
Published: January 2025

The advent of the Internet + era has led to a significant increase in the prevalence of online instruction within higher education institutions. This underscores the critical importance of investigating students’ contentment with virtual learning experiences. This paper employs a qualitative research methodology based on grounded theory, utilizing 215 survey questionnaires completed by undergraduate students at Shanghai Dianji University. The study analyses the satisfaction of undergraduates with online teaching through open, spindle, and selective decoding and presents corresponding countermeasures and suggestions.
The role of artificial intelligence in personalized music teaching quality evaluation
Authors: Zhao Shiwei
Published: January 2025

With the increasing emphasis on personalized learning in the field of education, music teaching has gradually turned to personalized methods to meet the diversified needs of students. In order to ensure the high efficiency and pertinence of music teaching, it becomes particularly important to evaluate the quality of music teaching. The purpose of this study is to explore the role of artificial intelligence technology in personalized music teaching quality evaluation. This paper reviews the historical evolution and current personalized trend of music teaching through literature, and summarizes the basic theory and application model of artificial intelligence technology. On this basis, the empirical research method is used to carry out detailed data collection, model construction, data verification and analysis. The results show that by applying artificial intelligence technology, the quality of music teaching can be evaluated more accurately and efficiently, so as to provide targeted feedback and suggestions for teachers. This discovery not only brings a new evaluation tool to the field of music education, but also opens up a new research direction for the application of educational technology.
Optimization of automatic English translation system in cross-border trade based on deep learning
Authors: Zhou Xuan , Shi Cuiping
Published: January 2025

The purpose of this study is to explore the optimization method and application value of deep learning in automatic English translation system in cross-border trade. Through the comprehensive study of deep learning and automatic translation, the key role of deep learning in translation system is revealed. The study analyzes the needs and language barriers of English translation in cross-border trade and systematically evaluates different deep learning model optimization strategies. In this paper, the performance of the model is significantly improved through the comprehensive optimization of data preprocessing, model structure optimization, and performance evaluation. The experimental results show that the optimized model performs well on several performance indicators, which proves the great potential and practical application value of deep learning technology in the automatic translation system of cross-border trade English. This study provides scientific theoretical guidance and practical reference for English translation in cross-border trade practice, which is expected to help solve the language barrier in cross-border trade and promote the smooth and diversified development of international trade.
Investigation on text generative model based on deep learning in natural language processing
Authors: Zheng Xianqiu , Zhang Zhidong , Wang Liqin , Wu Jinhua , Dong Zuofeng
Published: January 2025

In the current landscape, there is a growing urgency for advanced text generation technology, prompting a surge of interest in the exploration of highly efficient text generative models based on deep learning. In this paper, the long short-term memory (LSTM) unit was selected as the text generator and used as the decoder to generate its own retelling text. The feature extractor was BERT (Bidirectional Encoder Representation from Transformers), and the embedding layer of BERT included three parts: words, fragments, and locations. The BLEU (Bilingual Evaluation Understudy) score was used to measure the similarity between real text and generated text. The BLEU score for text paraphrasing generation under the LSTM network method was 0.98, while the BLEU score for text paraphrasing generation under the Transformer network method was 0.89. The BLEU score of text paraphrase generation under the Transformer-based sequence to sequence model method was 0.97, and the BLEU score of text paraphrase generation under the Transformer’s general text generative model method was 0.96. The LSTM network method was the best method compared with other methods. This article met the technical requirements of modern society for generating abstracts, and the readability and completeness of abstracts were further improved.
The commodity recommendation algorithm for automatic security sale system based on the internet of things
Authors: Li Zhi , Yao Yuxuan , Yuan Yuan
Published: January 2025

The objective of this paper is to investigate the promptness of recommendation data in automated product recommendation systems, enhancing their ability to facilitate product promotions and compute user similarities. This study also aims to streamline and refine the product purchasing process. To ease the user’s decision-making, an innovative design for the user terminal’s official account is proposed, creating an effective communication link between users and automated sales products. Second, based on the traditional user-based collaborative filtering recommendation algorithm, user characteristics, time factors, and promotion functions are integrated into the product recommendation algorithm model. To ensure the timeliness of recommendation information and avoid resource waste caused by expired products, time factors and promotion functions are incorporated into the recommendation algorithm model. Finally, a comprehensive test is conducted on the performance of the product recommendation system designed in this experiment. The results show that the average absolute error of the recommended model is reduced by 4.3%, and the improvement effect is significant. The average accuracy rate is increased by about 3.0% compared with the traditional recommendation algorithm. This paper aims to provide important technical support for the improvement of the product recommendation algorithm in the automatic sale system. Besides, this paper provides users with good recommendation services and convenient product purchase processes.
Digital economy and international competitiveness of manufacturing industry: A study on the moderating effect based on education level
Authors: Zhang Peijian , Liu Qinglin
Published: January 2025

This study utilizes data from a provincial panel comprising 31 provinces in China spanning the period from 2011 to 2021. Fixed-effect and random-effect models are employed to investigate the impact of the digital economy on international competitiveness within the manufacturing sector, along with its underlying mechanisms. Additionally, this study examines how educational attainment within the digital economy regulates and enhances promotion of international competitiveness in manufacturing industries. The findings reveal that there is a positive linear relationship between digitization and enhanced international competitiveness in manufacturing industries. Moreover, educational level plays a positive moderating role in facilitating this enhancement brought about by digitization. An increase in educational level leads to greater promotion of international competitiveness through digitization within manufacturing industries. Furthermore, regional heterogeneity reveals that higher levels of education amplify the moderating effect of education on promoting international competitiveness through digitization within these industries. Therefore, regional education has become crucial for fostering international competitiveness in these sectors. The government needs to increase investment in education, upgrade the quality of education, and develop the skilled and innovative talent needed for manufacturing through a strategic and multi-dimensional approach.
Does administrative monopoly affect enterprise innovation? An empirical analysis based on the perspective of factor mismatch in China
Authors: Wang Yanfei , Yu Liangchun
Published: January 2025

In the process of reforming from planned economy to market economy, the phenomenon of administrative monopoly has had a far-reaching impact on the development of China’s economy. Based on the perspective of factor mismatch, this paper examines the impact of administrative monopoly on enterprise innovation and its realization path, utilizing panel data from 30 Chinese provincial regions spanning 8 years from 2008 to 2015. The results of the study show that administrative monopoly significantly hinders the innovation activities of enterprises, showing a negative impact on both the output and input sides of innovation. By triggering factor mismatch, administrative monopoly has a hindering effect on enterprise innovation activities. Specifically, the intervention of administrative monopoly in the market leads to the mismatch of capital and labor factors in the market. When the interaction terms of administrative monopoly with capital mismatch and labor mismatch are added to the empirical model of administrative monopoly, it is found that the hindering effect of these interaction terms on enterprises is greatly enhanced. In the case of a single factor of capital mismatch and labor mismatch or the co-existence of both factors, their hindering effect on firms’ innovation is significantly enhanced. In addition, it is also found that capital mismatch has a more serious hindering effect on firm innovation than labor mismatch.
Ontogenetic modeling and numerical simulation of soft rock damage considering chemical correlation
Authors: Zhao Shutian , Yi Zhengnan , Peng Fanyao
Published: January 2025

Soft rocks are significant in geo-engineering. It is important to consider the effect of chemical correlation on damage ontology modeling of soft rocks, particularly for red sandstone. Chemical correlation may significantly impact their mechanical properties and damage behavior. The objective of this study was to investigate the creep mechanical behavior of red sandstone under the influence of water-rock chemical corrosion damage using Na2SO4 solution as a chemical corrosion medium for groundwater. Solutions with different concentrations and pH values were developed, and semi-open immersion tests and uniaxial compression tests were conducted to understand the changes in porosity, longitudinal wave velocity, and long-term strength of red sandstone specimens. This analysis took into account the water-rock chemical corrosion effect. A model for the intrinsic structure of fractional-order creep damage was built and fitted for study in water-rock chemical corrosion environments. The results indicated that the porosity of the red sandstone specimens increases with higher acidity and alkalinity levels and higher concentrations of the chemical medium solution. Additionally, the longitudinal wave velocity of the specimens decreases with these same factors. The longitudinal wave velocity was 2.439 m/s at a pH of 3 in a 0.10 mol/L solution, and the porosity of the red sandstone specimens was similarly at its highest level at 9.97%. Strongly acidic and alkaline solutions cause more chemical deterioration in red sandstone. The highest chemical damage value at a concentration of 0.10 mol/L was 0.196 at a pH of 3, which was 0.024 more than at a pH of 5. The specimens experienced more severe accelerated creep deformation in strong acid and alkaline environments, resulting in varying degrees of peak stress reduction. The long-term strength was between 60% and 70% of the short-term strength. The damage intrinsic model had a tiny and well-fitted error when compared to the test data. The prediction of creep deformation caused by chemical corrosion of red sandstone in water can be achieved by creating an ontological model of red sandstone damage through numerical simulation.
Architectural analysis of Baizhang Temple: Birthplace of “Zen forest and clean rules”
Authors: Zheng Yunyang , Liu Tian , Hu Hao , Yang Tong
Published: January 2025

Under the background of exploring traditional architectural culture, the purpose of this paper is to analyze and study the spatial form of Fengxin Baizhang Temple, the most representative and largest temple in Yichun area, the “Zen capital,” explore its site selection and spatial layout characteristics, and summarize the spatial organization and construction strategies of Baizhang Zen temple architecture. Meanwhile, in the current stage of paying attention to the protection and renewal of traditional temples, some common design methods suitable for local Zen temples are found in order to provide some reference for the study and protection of Zen temples. The study says: Baizhang Temple, a classic mountain temple, was strategically sited in accordance with the principles of ancient architectural feng shui and Zen philosophy. The overall spatial pattern and sequence are complete, among which the dimensions of leading space, main space, and auxiliary space account for 37.50%, 26.80%, and 35.70%, respectively. The ratio D/H between the visual distance D and the building height H of the four main Buddhist temples and the adjacent courtyard space is greater than 1.0. The perspective angles range from 22° to 35°. The courtyard space is mainly concentrated type, supplemented by a few scattered type, and the layout combination is consistent with the overall spatial form of the temple.
The path of improving the efficiency of college teaching based on information fusion technology
Authors: Hu Xinbo , Zhao Yanzhi , Huang Yanmei
Published: January 2025

This study discusses the way to improve the efficiency of high learning teaching based on information fusion technology. First, it analyzes the current situation and challenges of university teaching, and the application of information fusion technology in education. Then, the general situation of information fusion technology and the basic principle of factor analysis and its application in education research are introduced in detail. Through factor analysis, this study finds out and summarizes the key factors affecting the efficiency of high school teaching, and builds a factor analysis model suitable for high school teaching. Based on this, it puts forward some promotion strategies such as optimizing teaching content and methods, strengthening teachers’ role and ability, cultivating students’ learning ability and interest, and improving evaluation mechanism and feedback system. Through the actual case analysis, the effectiveness of the path of improving high learning teaching efficiency based on information fusion technology is verified. Finally, the practical significance of this study is summarized, and the limitations and future research directions are pointed out.
Spatial distribution of negative air ions (NAIs) in urban green spaces of Nyingchi City, Tibet Plateau
Authors: Li Wenbo , Zhao Wentao , Bai Binjie , Xin Zhen
Published: January 2025

Taking Nyingchi City as an example, this study explored the distribution of negative air ions (NAIs) in urban green spaces of plateau. Six representative areas of different types of urban green spaces in the main urban area of Nyingchi City were selected for NAIs observation and measurement. The results demonstrated that the NAI concentration in summer was significantly higher than the other three seasons in the study area. The NAI concentration in Fujian Park was significantly higher than the other observation sites, in the order of Fujian Park > the green space of Guangfu Avenue > Wetland Park of Happiness Community > the ecological scenic area of Biri Holy Mountain > Gala Peach Blossom Village > the scenic area of Cypress King’s Garden. Pearson’s correlation analysis showed that the NAI concentration was positively correlated with positive air ions and humidity, while humidity was positively correlated with NAIs and positive air ions, but negatively correlated with temperature and CO2 concentration ( p < 0.05). The correlations between the other variables all have p > 0.05, indicating no statistically significant correlations among them. PCA analysis showed that the highest loading was positive ions with a value of 0.929, and the loading of humidity was −0.876, positively and negatively correlated, respectively.
Gap insulation state assessment and early warning method for carbon fiber composite core conductor
Authors: Xu Yabing , Wang Xiaokai , Xu Hongfu , Liu Chenchen
Published: January 2025

In today’s fast-progressing economy and society, demands on the quality of electricity are increasing, and accordingly, the size of the electricity supply system is growing. The structure is becoming more and more complex; if the power system fails, it will lead to large-scale blackout accidents. Especially for carbon fiber composite core wires made of expensive carbon fiber materials, it will cause greater economic losses and serious social impacts. This article proposes a gap insulation state evaluation model for carbon fiber composite core wires, including considering altitude factors. Comparison of minimum safe clearance distance between carbon fiber composite core wire and steel core aluminum stranded wire through calculation of wind deflection angle. It can achieve online assessment of the risk of conductor wind-induced flashover. In addition, the practicality and functionality of this model have been verified through real-world examples.
Enhancing multi-timescale coordinated control strategy for a transmission system with MES
Authors: Xin Tian , Long Zhao , Ergang Zhao , Xuanyu Qiu , Shuyang Li , Kai Li
Published: January 2025

To address the issue of renewable energy fluctuations in new electrical systems, we have proposed a multi-time scale coordinated control strategy aimed at optimizing the performance of the system, particularly multi-energy storage (MES) systems. This strategy integrates various control methods across different energy time scales, significantly improving the power response characteristics of the system. Compared to single energy storage systems, MES systems exhibit notable advantages in stabilizing power fluctuations and extending energy storage lifespans. The strategy, divided into day-ahead optimization and intraday adjustment stages, effectively mitigates the impact of renewable energy forecasting errors, ensuring safe and stable operation. With a focus on enhancing operational efficiency and overall reliability, our research contributes to the advancement of MES systems within modern electrical systems.
Impact time history reconstruction using dynamic weighted graph neural network under sensor fault situations
Authors: Huang Chun , Tao Chongcong , Ji Hongli , Qiu Jinhao
Published: January 2025

This article introduces a dynamic weighted graph neural network (DWGNN) for precise reconstruction of impact force time histories under both fault and nonfault conditions in sensor networks. The DWGNN model integrates a one-dimensional convolutional neural network for extracting features from sensor signals and a graph neural network that dynamically adjusts its weight matrix based on node feature similarity, thereby reducing the impact of faulty sensor signals. Incorporating physical constraints, such as the distances between impact and sensor locations, improves the model’s performance. This innovative approach enables the accurate reconstruction of impact forces using only nonfaulty training data. Experimental validation on a stiffened metal plate, with mixed artificially generated and real measured signals, demonstrates the DWGNN model’s high accuracy and robustness. Data augmentation with fault signals significantly enhances the model’s accuracy under challenging fault conditions, proving the DWGNNs potential for real-time structural health monitoring and fault diagnosis in complex engineering structures.
College Success for First-Generation College Students From One-Parent Households
Authors: May-Trifiletti Jennifer A. , Clayton Ashley B. , Toutkoushian Robert K.
Published: January 2025

This study examined college planning, enrollment, and degree completion among first-generation college students (FGCS) from one-parent households. We used several different definitions of FGCS. We found that students who did not live with any college-educated parents were less likely to enroll in a 4-year college or earn a bachelor's degree. Students in two-parent households with one college-educated parent were also less likely to enroll in a 4-year college or earn a bachelor's degree. In contrast, students from one-parent households with one college-educated parent experienced outcomes similar to those of students living with two college-educated parents. This suggests that living in a household with the maximum number of college-educated parents possible relative to household size is important for students’ educational outcomes. This study has implications for defining FGCS and understanding how and why parent education affects students’ outcomes and for practitioners and policymakers seeking to meet the needs of FGCS.
PoKER: a probability of kill estimation rate model for air-to-air missiles using machine learning on stochastic targets
Authors: Dantas Joao PA , Costa Andre N , Geraldo Diego , Maximo Marcos ROA , Yoneyama Takashi
Published: January 2025

This work introduces PoKER, a novel probabilistic model engineered to optimize missile launch effectiveness in air-to-air scenarios, specifically within Beyond Visual Range (BVR) air combat. Unlike conventional Weapon Engagement Zone (WEZ) models that delineate zones based on static distances such as maximum, minimum, and no-escape ranges, PoKER applies machine learning to predict kill probabilities more accurately by integrating the stochastic behaviors of targets and missile miss distances. This model dynamically evaluates target behavior, greatly expanding the predictive capabilities of engagement analysis. By factoring in elements such as warhead lethality, target and shooter orientations, and the specific conditions of engagement, PoKER provides important insights into engagement dynamics and quantifies success probabilities. Consequently, it can potentially be an important tool for BVR air combat pilots, improving operational decision-making within this specialized combat domain.
Reinforcement learning based recovery flight control for flapping-wing micro-aerial vehicles under extreme attitudes
Authors: Yu Yang , Lu Qiang , Zhang Botao
Published: January 2025

This article deals with the recovery flight problem of flapping-wing micro-aerial vehicles under extreme attitude by using a reinforcement learning approach. First, the reinforcement learning-based control policy is proposed to enable the flapping-wing micro-aerial vehicles to be recovery flight rapidly and keep the angular acceleration as small as possible. Then, a hybrid control approach is designed to significantly improve the flight stability by combining the reinforcement learning-based control approach with the proportional-derivative control approach. Finally, simulation results show the effectiveness of the reinforcement learning-based method and the hybrid control method for the flapping-wing micro-aerial vehicles under extreme attitudes.
Real-time controller design and onboard attitude estimation of a quadrotor with collision safety through ultrasonic sensors
Authors: Yunus Rumshaa
Published: January 2025

Quadrotors are small-sized, inexpensive aerial systems widely used for various indoor operations. Stable flight is a challenge for quadrotors due to low-cost sensors and indoor flight safety constraints add to their complexity. In this study, an Arduino based quadrotor is designed to test 2nd order Complementary filters for state estimation along with a controller with collision safety for indoor flight. Ultrasonic sensors are used for object detection during flight. Detailed hardware assembling along with the implementation of Complementary filter and PID controller is discussed. System tunning is done using the Heuristic method and system response is tested in real time. This study proves that by using the above techniques, a stable flight is achieved with collision safety using ultrasonic sensors.
Women’s mental health in the doctoral context: Protective function of the psychological capital and academic motivation
Authors: Deroncele-Acosta Angel , Norabuena-Figueroa Roger Pedro , Norabuena-Figueroa Emerson Damian
Published: January 2025

Background:

Science recognizes the anxieties, depression, stress, and “turbulences” that women face in doctoral studies, but women’s mental health in this context is still little addressed, even though it is a critical aspect for the well-being, persistence, and success of women doctoral candidates, who continue to be underrepresented in many professional fields.

Objectives:

The study aims to evaluate the relationship between academic motivation, psychological capital, and university academic performance (UAP) and to identify factors of female mental health success.

Design:

A cross-sectional, mixed-methods study was conducted with a sample of 108 female doctoral students from a university in Lima, during the first quarter of 2024.

Methods:

In the quantitative phase, three standardized scales were administered to assess academic motivation, psychological capital, and university academic performance (UAP). In the qualitative phase, interviews were conducted to gather relevant information on mental health.

Results:

The findings emphasize five important points: (1) levels and the relationship between psychological capital, academic motivation, and performance, (2) motivational behavior according to study cycles, (3) risk and protection profiles, (4) protective functions, and (5) mental health success factors. The results indicate that 36% of the women have a low level of psychological capital, 34% have a medium level of academic motivation, and 37% have a high level of UAP, likewise “Intrinsic Motivation toward Accomplishment” is the positive core where most of these women converge. Significant differences were found between the study cycles with academic motivation and “University Academic Performance,” and a significant gap between these variables. The risk profile (which limits performance) and the protective profile which allows high performance are determined; this positive profile is identified by women who present a high level of “Self-efficacy.” The study demonstrates that “Psychological Capital” and “Academic Motivation” along with the dimensions of “Self-efficacy” and “Intrinsic Motivation to Experience Stimulation” serve protective functions. Fourteen success factors for women’s mental health were identified and organized into four main approaches: Optimism, Hope, Resilience, and Self-efficacy.

Conclusion:

Limitations and future projections are discussed. The practical implications include implementing psychological support programs, fostering intrinsic motivation, integrating psychological assessments, establishing support networks, and making tailored curricular adjustments.
Salutogenic Architecture, Non-Therapeutic Environments and the Health of the Elderly: A Systematic Review
Authors: Rakhshani Zohre , Khakzand Mehdi
Published: January 2025

Background: Despite a lot of studies that have been conducted on the effects of the built environment on the health of the elderly and environmental salutogenic factors, a limited number of studies have investigated the architectural physical factors clearly. Purpose and Aim: This paper investigated the architectural elements in the non-therapeutic built environment that can achieve salutogenic goals for the elderly. It also aimed to provide an answer to the question of how architectural design might be used to physically bring salutogenic theory to life. Method: In this review study, data were collected systematically using the PRISMA checklist. The three lists of keywords used for the initial search were “built environment” or “architecture,” “elderly,” and “health,” and were supplemented with synonyms for a second search in four databases: Scopus, Science Direct, Web of Science, and PubMed, in the period from 2000 to 2024. By applying inclusion and exclusion criteria, 26 articles were selected for review and data extraction. The data were then qualitatively analyzed, and two reviewers independently verified the analysis. Conclusions: This study found that architectural elements can be salutogenic by supporting the comprehensibility, manageability, and meaningfulness. Porches, Stoop, above-grade entrances, and balconies are key elements in the home that support the sense of coherence. In assisted living facilities, walls were recognized as the only physical factor supporting the sense of coherence due to the creation of a personal, distinct, meaningful, comprehensible, and manageable space.
Variations in Neuromuscular Functions After Platelet-Rich Plasma and Dextrose Injections in Chronic Lateral Epicondylitis: A Randomized Controlled Study
Authors: Chen Yueh , Hong Chih-Kai , Hsu Kai-Lan , Kuan Fa-Chuan , Su Wei-Ren , Chen Yi-Ching , Hwang Ing-Shiou
Published: January 2025

Background:

Lateral epicondylitis is caused by overuse and manifests as pain, weakness, and difficulty with object manipulation. Platelet-rich plasma (PRP) and dextrose injections have shown promise in reducing pain and improving function.

Hypothesis:

PRP is more effective for force precision control of the extensor carpi radialis brevis (ECRB) muscle than dextrose injection for patients with chronic lateral epicondylitis (CLE).

Study Design:

Randomized, double-blinded clinical trial.

Level of Evidence:

Level 1.

Methods:

A total of 62 participants (25 healthy subjects and 37 CLE patients) were assigned randomly to either PRP (19) or dextrose (18) groups. Assessments included maximal voluntary contraction (MVC), wrist extension force, questionnaires, sonography, and electromyography assessments.

Results:

PRP and dextrose had similar effects on clinical questionnaire scores. Compared with pre-test values, only PRP demonstrated a significant increase in MVC (PRP, 75.3 ± 107.7%; P < 0.01; dextrose, 34.0 ± 66.1%; P = 0.08), and greater reduction in force fluctuations (PRP, –27.4 ± 13.3%; P < 0.01; dextrose, –5.4 ± 33.2%; P = 0.22) during post-test wrist extension. After treatment, the PRP group experienced a roughly 41.7% increase in motor units (MUs) with recruitment thresholds (Rec_TH) (pre-test, 3.67 ± 6.15% MVC; post-test, 5.20 ± 8.02% MVC; P < 0.01). The dextrose group showed no significant change (–3.74%) in MU Rec_THs (pre-test, 3.48 ± 6.80% MVC; post-test, 3.35 ± 6.62% MVC; P = 0.75). PRP increased the MU discharge rate with Rec_THs at <30% MVC, whereas dextrose administration elevated MU discharge rate with Rec_THs >20% MVC.

Conclusion:

PRP may be more effective than dextrose in improving neuromuscular control of the ECRB muscle, particularly for enhancing the scaling of force during wrist extension, attributed to distinct MU activation strategies.

Clinical Relevance:

Detailed comparison and head-to-head analysis of PRP and dextrose injections offers more options for patients considering injections.
Diagnostic challenges in SLIPPERS syndrome: Case report
Authors: Acır İbrahim , Sezen Ahmetcan , Aygün Murat Serhat , Altıntaş Ayşe
Published: January 2025

Background

SLIPPERS (Supratentorial Lymphocytic Inflammation with Parenchymal Perivascular Enhancement Responsive to Steroids) is a rare variant of a syndrome called CLIPPERS (Chronic Lymphocytic Inflammation with Ponsine Perivascular Enhancement Responsive to Steroids). SLIPPERS is characterized by distinct supratentorial lesions that share radiological and pathological characteristics with CLIPPERS. The ongoing issue is whether these syndromes should be considered as a distinct disease entity or simply a form for a variety of underlying conditions such as granulomatosis, vasculitis, and infectious diseases.

Case

We present a unique case of SLIPPERS observed in a 26-year-old woman with no notable medical or familial background. Laboratory findings ruled out certain diseases from the list of differentials and cranial MRI showed T2 hyperintense areas with linear-patchy enhancements, a pattern consistent with SLIPPERS syndrome. Consequently, patient was diagnosed with SLIPPERS syndrome and received methylprednisolone therapy.

Conclusion

Both SLIPPERS and CLIPPERS are complicated syndromes posing diagnostic challenges and requiring careful investigation to avoid misdiagnosis. Following a thorough differential diagnosis, appropriate treatment can be initiated, and follow-up is required.