Zhaoqing, an important place where the peasant movement took place in Guangdong, is an area where the peasant movement was launched earlier, developed rapidly and had significant influence. The red heritage resources of the peasant movements in Zhaoqing are abundant, widely distributed, and the demonstration construction efforts are significant, which have educational value in cultivating students' spirit of hard work and perseverance, cultivating students' sense of patriotism and promoting the spirit of unity and cooperation. To better realize the educational function of the red heritage of the peasant movement in Zhaoqing, it can be achieved through integrating the red heritage resources of the peasant movement in Zhaoqing, leveraging the educational value of this red heritage, and enhancing the educational effectiveness of it.

Immune milk containing immunoglobulin A (IgA), immunoglobulin G (IgG), and lactoferrin (IF), as a nutritional supplement that can be added to foods, not only provides essential iron and amino acids but also has the potential to improve immune function and contribute to disease prevention. Methods: Between April 2023 and July 2023, a total of 279 randomly selected kindergarten children in Zhenhai District were included in the study and divided into three groups. These children consumed immune skim milk powder for 3 months. Children’s height, weight, BMI, and disease resistance capability were recorded. Results: The mean heights/weights for Groups 1-3 before intervention are 112.11±0.65/19.02±0.35, 118.84±0.53/21.97±0.44, 104.36±0.54/16.55±0.34, with height/weight increasing as:  1.70±0.05/0.36±0.14, 1.49±0.06/0.71±0.08, 1.52±0.10/0.50±0.08 at the end of the research. Statistical differences in the three groups between three-month post-intervention and pre-intervention were all significant (P<0.01), there were also significant differences were also observed in male and female children. The heights and weights of children are above the standard growth development levels. The health status of the 301 children, including 60.13% upper respiratory tract infections, 4.65% diarrhea, and 3.65% hand-foot-mouth disease, was lower than those reported in the literature. Conclusion: Immune milk containing IgG, IgA, and lactoferrin might enhance children’s immune capability and disease resistance. IgA, IgG, and LF have the potential to be used in both dietary supplements and medicines to improve the health of both humans and animals.

China's air transport volume has steadily ranked second globally and continues to grow rapidly. However, there is a significant gap in civil aviation infrastructure, and airports are reaching saturation. Developing strategies based on resilience theory has become an industry consensus. Aiming at the flight support operations in the airport movement area, we construct a complex network analysis model. In this model, we abstract nodes into an Activity On Vertex network (AOV net). We then employ the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model to identify key nodes, providing data support for the cascading failure model. Focusing on the stability and recovery mechanisms of the flight support system, we establish a resilience evaluation system that incorporates metrics such as network efficiency, the relative scale of the largest connected component, etc., and conduct an empirical application of complex network theory. The conclusions drawn from this study guide the formulation of control strategies.

With the extensive use of intelligent monitoring systems in contemporary power system, it is becoming a significant challenge to make the power grid operate stably in achieving high robust fault diagnosis of transformers across operating conditions and environmental domains. In this work, a transfer learning enhanced deep CNN-LSTM cross-domain transformer fault diagnosis model (TL-DCNN-LSTM) is presented. The model, built on the classical CNN-LSTM, applies Convolutional Neural Network (CNN) to capture multi-scale spatial features, which are from the original current (or vibration) signal, between the circuit and gearbox, and employs Long Short-Term Memory Network (LSTM) to learn the time-dependent patterns of the fault signal. To address the distribution discrepancy between the source domain and the target domain, the paper presents a transfer learning mechanism, where the Maximum Mean Discrepancy (MMD) loss is embedded in the deep feature space to reduce feature distribution differences between different domains. Meanwhile, a domain-wise batch normalization (DSBN) block is introduced to maintain the discrepancy in domain. Furthermore, an auxiliary domain discriminator and adversarial training strategy are proposed to enhance the domain irrelevance and discrimination of the feature representation. The TL-DCNN-LSTM model obtains a cross-domain diagnosis accuracy of over 96.7%, which is substantially higher than traditional CNN, LSTM and common fine-tuning methods.

As the core competencies in English education and the new curriculum standards are progressively implemented, primary school English teachers have recognized the importance of integrating excellent traditional Chinese culture into their teaching. However, the integration of this culture in practice has not been as effective as expected. This paper explores the significance of incorporating excellent traditional Chinese culture into primary school English teaching, analyzes the current state and reasons for cultural integration, and investigates strategies to enhance the effective integration and penetration of this culture in teaching. The goal is to improve students' cross-cultural communication skills, strengthen their cultural and national confidence, and support the inheritance and promotion of excellent traditional Chinese culture.

Traditional Chinese medicine (TCM) culture is the crystallization of the wisdom of the Chinese nation over thousands of years, with a profound cultural heritage and a unique theoretical system. This paper analyzes classroom teaching of TCM culture from three aspects: the connotation and characteristics of TCM culture, the importance of TCM culture for international students of traditional Chinese medicine, and the current status of TCM culture teaching. Teaching methods and measures include online-offline blended teaching, integrating classic TCM texts and culture into clinical teaching, and improving the Chinese proficiency of international students, so as to enrich international students' knowledge of TCM culture and enhance their Chinese language level.

With the acceleration of digital transformation in the construction industry, the application of BIM technology in civil engineering teaching has become the key to improving the quality of talent cultivation. This article focuses on the application of BIM technology in civil engineering teaching, systematically elaborating on the specific implementation strategies of project-based teaching method, flipped classroom and blended online and offline teaching, cross disciplinary collaborative teaching and other practical paths; Taking a large-scale commercial complex construction project as a case study, this paper conducts an in-depth analysis of the BIM course teaching process, and evaluates the teaching effectiveness by comparing and analyzing the learning and practical ability data of students in 2021 and 2022. Research has shown that innovative teaching models based on BIM technology have significantly improved students' professional literacy and practical abilities, providing important references for the reform of teaching in civil engineering and the cultivation of composite talents in the industry.

Exoplanetary science stands as one of the most cutting-edge and promising research fields in modern astronomy, playing a pivotal role in unraveling fundamental scientific questions regarding planetary formation, evolution, and the origins of life. Among various detection methods, the transit method has emerged as one of the most successful techniques due to its high efficiency and reliability. This paper systematically elaborates on the fundamental principles of the transit method, which infers the existence of transiting exoplanets and their physical parameters (such as radius and orbital period) by detecting periodic dips in stellar brightness. This paper further presents current research developments of the transit method, while also examining the method's inherent limitations and prospective research directions. The high-precision detection capability of the transit method will continue to advance exoplanetary science, providing critical support in the search for habitable planets and potential biosignatures

Integrating red culture into vocational education is an important way to fulfill the fundamental task of cultivating students' moral character and nurturing talent. It is an effective method to enrich revolutionary spirit and fine traditions, and an important measure to foster students' patriotic feelings. Considering the current development status of vocational education, we explore the existing deficiencies. Focusing on inheriting the red gene, promoting the revolutionary spirit, and cultivating skilled talents with both moral integrity and practical abilities, we aim to promote the high-quality development of vocational education. Addressing the practical needs of contemporary college students, such as career development planning, employment concepts, and shaping professional values, and conducting in-depth research on innovative integration models of red culture and vocational education. By analyzing typical cases, we propose practical and operable solutions, which will provide important theoretical basis and methodological references for the reform, innovation, and the enhancement of the connotation of vocational education.

In the context of the deep integration of digital technology revolution and new urbanization strategy, the construction of smart cities has become an important path to solve the "urban disease" and achieve modernization of governance. This study adopts literature research and case analysis methods to systematically sort out the connotation, characteristics, and development evolution of smart cities. Through analysis, the current status of smart city construction in China is obtained, and the shortcomings in the current process of smart city construction in China are pointed out. In response to the shortcomings, this study proposes a "five in one" improvement strategy of policy innovation and capital synergy, reconstruction of new infrastructure system, technological breakthroughs and achievement transformation, circulation of data elements, and upgrading of security system. It provides practical reference for the transformation of Chinese path to modernization cities, and also provides experience for the construction of smart cities in developing countries.

Under the background of "double carbon", China actively promotes the development of new energy vehicles, and charging piles and other infrastructures have become key. This study focuses on the rural areas of Shijiazhuang, aiming to analyze the current situation of charging piles, identify and solve problems, and help new energy vehicles to the countryside. The study adopts a survey questionnaire to investigate the rural population in ten counties and three county-level cities around Shijiazhuang, and finds that the layout of rural charging piles is unreasonable, the number is insufficient, and there are barriers to their use through text mining, descriptive statistics, cross-tabulation analysis, decision tree modeling, K-modes cluster analysis, and structural equation modeling. Users can be categorized into long-distance high-frequency fast-charging, close-distance convenience type, and medium-distance planning type, and the quality of facilities, convenience and other factors significantly affect satisfaction and willingness to use. Based on this, the study proposes optimizing the layout, making charging prices transparent, simplifying the APP, increasing the number, deepening the environmental protection publicity, improving the infrastructure, and exploring multi-dimensional use, in order to promote the development of charging piles and new energy vehicles in rural areas.

This paper delineates five historical stages of human understanding of the universe, tracing the evolution from ancient mythology to modern scientific theories. Initially, myths like "Pangu Creating the World" explained cosmic origins, followed by rational interpretations during the Warring States period, as seen in the works of Zhuangzi and Hui Shi. The geocentric and heliocentric models of Ptolemy and Copernicus marked further advancements. Modern materialism, exemplified by Marx and Engels, introduced dialectical perspectives, while Lemaître’s "Big Bang" theory and Hawking’s "singularity" hypothesis blended scientific speculation with mythological elements. The final stage presents a novel "materialist" theory positing that the universe comprises infinite hierarchical structures of infinitesimal particles, forming atomic, molecular, and cosmic scales. This framework challenges idealist cosmologies, refutes Einstein’s "black hole" paradox, and reinterprets gravitational sources as "vacuum energy." By synthesizing empirical observations with philosophical inquiry, the study asserts a deterministic, infinitely scalable universe, displacing metaphysical narratives with a unified materialist ontology.

Non-invasive diagnostic techniques have made significant strides in the early detection and management of cardiovascular diseases. Advances in imaging modalities, such as echocardiography, cardiac MRI (CMR), CT, and PET/SPECT, have enhanced diagnostic accuracy and allowed for detailed assessment of heart function and structure, while reducing the risks associated with invasive procedures. In parallel, the emergence of electrocardiography (ECG) and wearable devices has enabled real-time monitoring, aiding in the detection of arrhythmias and chronic disease management. Furthermore, blood-based biomarkers, including troponins, natriuretic peptides, and microRNAs, have shown promise for early detection, risk stratification, and prognosis prediction, although they often need to be integrated with imaging and ECG data for comprehensive evaluations. Artificial intelligence (AI) and machine learning are transforming cardiovascular diagnostics by improving image reconstruction, ECG interpretation, and multi-modal data integration, offering personalized assessments and enhanced diagnostic precision. However, challenges such as cost, accessibility, regulatory hurdles, and clinician adoption remain significant barriers. Future research should focus on improving the accessibility, affordability, and interoperability of diagnostic tools across healthcare systems. With continued innovation, non-invasive techniques are poised to play an increasingly pivotal role in early intervention and improved outcomes for patients with heart diseases.

This article conducts research on the ideological and political teaching practice of professional course teachers in vocational colleges, revealing their core contradictions and optimization directions. To solve the practical dilemma of vocational college teachers who generally recognize the value of ideological and political education in courses, but are limited by the single teaching content and methods, the integration of ideological and political elements into mechanization, and the lack of systematic training. This article first proposes an optimization path centered on "three-dimensional breakthroughs", which involves innovating modular teaching content that deeply integrates professional and ideological education, promoting diversified methods such as case teaching and situational practice, and constructing a normalized teacher training system and interdisciplinary collaboration mechanism; Secondly, the practice of using typical course ideological and political cases as the main focus, supplemented by dynamic evaluation feedback mechanisms, has proven that it can significantly improve teaching effectiveness. Curriculum ideological and political education is an important driving force for the connotative development of vocational education, and its long-term development needs to be promoted through institutional improvement and resource coordination.

With the rapid development of the digital era, the widespread adoption of the internet has been accompanied by a surge in cybersecurity threats. This study proposes a practical theoretical framework supported by data-driven analysis to enhance national cybersecurity governance.Task 1: Utilizing datasets from ITU, INTERPOL, and VCDB, preprocessed data (with outliers removed) were visualized through heatmaps to analyze the global distribution of cyber threats. Clustered bar charts and stacked histograms further dissected regional variations in cybersecurity incident success rates, prevention rates, prosecution rates, and reporting rates. Results reveal that the distribution of cyber threats correlates with a nation’s economic development level and cybersecurity infrastructure robustness.Task 2: The Global Cybersecurity Index (GCI) was employed to evaluate national cybersecurity capabilities. Missing values in GCI’s five pillars were addressed via Lagrangian interpolation. Principal Component Analysis (PCA) identified six countries with the highest contribution rates, while the entropy weight method optimized the pillars into two core dimensions: collaboration and technology. Incorporating policy time lag effects, this framework pinpointed effective policies for mitigating cybersecurity incidents.Task 3: A multivariate linear regression model quantified the impact of demographic factors (e.g., internet penetration rate and education level) on cyber threat distribution. Finally, a neural network-based multivariate time series model predicted the theoretical impact of policy interventions on threat dynamics, complemented by sensitivity analysis to objectively assess the framework’s strengths and limitations.

Electrical materials play a pivotal role in electrical engineering, yet conventional research methodologies relying on experimental approaches and theoretical calculations face challenges of low efficiency and high costs. The rapid advancement of artificial intelligence (AI) technology has introduced novel tools for electrical material research, significantly enhancing the efficiency of material design, performance prediction, and experimental optimization. This paper systematically reviews recent progress in AI applications across semiconductor, alloy, energy storage, and metallic materials. In semiconductor research, machine learning has improved analytical precision through optimization of Hubbard U parameters and prediction of perovskite defect transition levels. For alloy materials, AI combined with active learning strategies has accelerated the discovery and performance optimization of high-entropy alloys.Our analysis reveals that AI technology substantially reduces material development cycles and experimental costs through multi-source data integration, quantitative model construction, and multi-objective optimization strategies. Looking forward, with advancements in data science and computational capabilities, AI is poised to play an increasingly critical role in multi-scale material design, performance prediction, and novel material development for electrical engineering, thereby driving technological innovations in power and electronic systems.

This article reviews the research progress on the pathological mechanism and clinical impact of endometrial injury. Endometrial injury is a common gynecological disease, with a complex pathogenesis involving multiple aspects such as inflammatory response, fibrosis formation, and abnormal angiogenesis. This article explores in detail these pathological mechanisms and analyzes the serious impact of endometrial damage on female reproductive health, including infertility, recurrent miscarriage, and menstrual abnormalities. In addition, the article also introduces commonly used diagnostic methods and treatment strategies, providing reference for clinical practice. Finally, this article looks forward to future research directions and emphasizes the necessity of conducting in-depth studies on the mechanisms of endometrial injury and developing new treatment methods.

Background: Low back pain (LBP), affecting ~10% of the global population, is a major public health challenge, with elevated prevalence in China (20.88–29.88%). Lumbar disc herniation (LDH), a leading cause of LBP (12–43% of cases), involves nucleus pulposus displacement and annulus fibrosus compromise. While conservative therapies resolve symptoms in 75% of patients, refractory cases necessitate surgery. Percutaneous Endoscopic Lumbar Discectomy (PELD) is a minimally invasive option with favorable outcomes. This systematic review and meta-analysis evaluate the efficacy of minimally invasive surgeries for LDH, focusing on pain reduction, functional improvement, and recurrence.

Methods: Following PRISMA guidelines, PubMed, Scopus, and Web of Science were systematically searched using keywords related to LDH, minimally invasive surgery, and clinical outcomes. Eligible studies included confirmed LDH diagnoses, detailed surgical data, and postoperative outcome measures. Two researchers independently screened articles and extracted data. Meta-analyses (RevMan 5.4, STATA 17.0) employed random-effects models to calculate mean differences (MDs) and odds ratios (ORs). Sensitivity and publication bias analyses were conducted.

Results: Among 11,626 screened articles, 14 studies (1,108 patients) met inclusion criteria. All procedures significantly reduced back and leg pain at 3, 6, and 12 months postoperatively. Unilateral Biportal Endoscopic (UBE) surgery demonstrated the largest improvements in Visual Analog Scale (VAS) scores for back and leg pain across all intervals. PELD with annular suture yielded the highest Oswestry Disability Index (ODI) improvements (MD: 65.32 at 3 months; 70.93 at 12 months). UBE also outperformed other techniques in functional outcomes. Recurrence rates between Microendoscopic Lumbar Discectomy (MELD) and PELD were comparable (OR: 0.90; 95% CI: 0.37–2.22).

Conclusion: Minimally invasive surgeries, particularly UBE and PELD with annular suture, significantly improve pain and function in LDH patients. Despite methodological heterogeneity, results robustly support their efficacy. Personalized surgical selection and standardized protocols are critical to optimizing outcomes. Future research should prioritize identifying patient-specific predictors of success to guide precision interventions. This analysis provides evidence-based insights to enhance clinical decision-making and patient quality of life.

The capability of financial risk management directly impacts a company's competitiveness. Financial risks such as financing risks and investment risks inevitably exist during corporate operations. Financial risk control affects resource integration capabilities and may even lead to corporate bankruptcy, making it crucial for enterprises to strengthen financial risk management. Big data technology provides new approaches for financial risk management. This paper analyzes the current financial risk management status of Du Technology Co., Ltd., identifies existing issues through financial indicators, and proposes innovative management strategies for corporate financial risks in the big data era. These strategies include enhancing internal controls, improving internal auditing, establishing financial risk early-warning mechanisms, and promoting financial personnel transformation, aiming to strengthen operational stability.

The development of philanthropy plays a significant role in fostering a harmonious society and narrowing the wealth gap. This study focuses on Zhejiang Province and constructs a measurement indicator system for the willingness to participate in personal philanthropy. Using data collected through questionnaires and empirical analysis with Stata 18, the study examines the measurement of philanthropic willingness and its influencing factors. The results indicate significant differences in philanthropic willingness across various prefecture-level cities, with Jiaxing and Jinhua standing out. Factors such as moral values, trust in charitable organizations, and tax incentives have a significant positive impact on philanthropic willingness, while income level shows a negative relationship with philanthropic participation. This paper proposes recommendations to improve institutional frameworks, optimize incentives, promote philanthropic culture, and enhance platforms to strengthen public trust in philanthropy and increase public participation. These findings provide empirical support and policy references for the high-quality development of philanthropy in Zhejiang Province.