Journal of the European Academy Open University
《Journal of the European Academy Open University》（欧洲学院开放大学学报）是由欧洲学院开放大学校友会与中国建筑文化出版社联合创办，旨在推进欧洲学院开放大学与国际接轨，提升欧洲学院开放大学在国际的影响力并推动全球科技水平的进步。根据2025年欧洲学院开放大学开设专业表，《Journal of the European Academy Open University》的收稿范围为全科，我刊拥有完整的投稿、审稿、出版流程，欢迎各位投稿，投稿邮箱：Journal@edu.aeou.cn
Construction of a Nanostructured Stabilization System for Sea Cucumber Lipids and Their Precise Intestinal Release Mechanism
The annual output of sea cucumber processing by-products in China exceeds 100,000 tons, which are rich in functional lipids such as cerebrosides and EPA/DHA, making them a valuable resource for high-value utilization. However, disadvantages such as the easy oxidation of sea cucumber lipids, intolerance in the gastrointestinal tract, and lack of targeting seriously affect their efficacy. Using sea cucumber processing by-products as raw materials, this paper starts from three aspects: nanostructured stabilization construction, targeted intestinal delivery, and precise release mechanisms. It elaborates on the green and highly efficient preparation of sea cucumber lipids, the triple stabilization system of protein self-assembly, liposomes, and hydrogels, and the pH-enzyme dual-responsive precise release pathway. It reveals the structure-activity relationship and in vivo transport laws, providing a theoretical basis and technical route for the high-value utilization of sea cucumber functional lipids and the creation of novel special dietary foods.
Copyright (c) 2026 Journal of the European Academy Open University https://creativecommons.org/licenses/by-nc/4.0
Cytological Evaluation of Sea Cucumber Fucoidan Inhibiting the Activity of Helicobacter pylori in vitro
Objective: To study the inhibitory effect of sea cucumber fucoidan on Helicobacter pylori (H. pylori) in vitro and its cytological mechanism, laying a foundation for the further development of natural anti-H. pylori drugs. Methods: Sea cucumber fucoidan was prepared by water extraction and alcohol precipitation. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) against H. pylori standard strains and clinical drug-resistant strains were determined using the micro-dilution method. Human gastric mucosal epithelial cells (GES-1) were used as experimental subjects and divided into different concentration groups of sea cucumber fucoidan, an H. pylori infection group, and a negative control group. Cell viability was measured using the CCK-8 method; Giemsa staining was used to observe changes in cell morphology; and the expression levels of inflammatory cytokines IL-1β and TNF-α were detected by ELISA. Results: Sea cucumber fucoidan effectively inhibited the growth of H. pylori. The MIC for the standard strain and clinical drug-resistant strain was 18 mg/mL and 36 mg/mL, respectively, while the MBC was 36 mg/mL and 72 mg/mL, respectively. Compared with the H. pylori infection group, at the same time point, the sea cucumber fucoidan treatment group showed higher cell survival rates, lighter degrees of cell damage, and lower levels of IL-1β and TNF-α (P < 0.05), which gradually decreased as the concentration of sea cucumber fucoidan increased. Conclusion: Sea cucumber fucoidan can inhibit the reproduction of H. pylori in vitro, reduce the possibility of gastric mucosal epithelial cell damage and inflammatory reactions caused by H. pylori, and has great potential to be developed into a novel anti-H. pylori drug.
Study on the Isolation and Purification Process of Fucoidan from Sea Cucumber Blanching Liquid Waste
Shandong Province regards marine biomedicine as the core direction for the high-quality development of the marine economy. The blanching liquid produced during sea cucumber processing is often directly discharged in large quantities, which on one hand causes resource waste and environmental pollution, and on the other hand, presents a challenge for the low-cost, large-scale preparation of sea cucumber fucoidan with high anti-Helicobacter pylori activity. This paper elaborates on the theoretical basis for the isolation and purification of sea cucumber fucoidan, systematically optimizes key processes such as multi-stage membrane separation, composite enzymatic hydrolysis-ethanol precipitation, and CPC (Cetylpyridinium chloride) precipitation-chromatography. Furthermore, it explores strategies for molecular weight homogenization and activity retention, providing technical support for the high-value utilization of blanching liquid and laying the foundation of high-quality raw materials for the development of anti-Helicobacter pylori functional products.
Green and efficient preparation technology for lipid bioactive compounds derived from sea cucumber processing by-products
Driven by the need to enhance the value of by-products from sea cucumber processing, this study first conducts a systematic and rigorous analysis of the compositional characteristics, physicochemical properties and extraction mechanisms of active lipid compounds in sea cucumbers. This analysis highlights the shortcomings of traditional solvent-based methods in terms of efficiency, energy consumption and safety. Consequently, a green preparation technology system has been established, centred on the synergy between low-carbon physical methods and bioconversion. This system integrates key technologies such as supercritical fluid extraction, molecular distillation and gradient separation, to achieve the efficient extraction and precise purification of lipid bioactive components. By incorporating nano-stabilisation and delivery strategies, the stability and bioavailability of the target bioactive substances are effectively enhanced. Consequently, this study provides a comprehensive and reliable technical pathway for the green development of sea cucumber processing by-products.
Supercritical CO₂ Extraction of Squid Yellow High-Polyunsaturated Fatty Acid Fish Oil
To achieve high-value utilization of squid processing by-products and address the challenges facing Shidao's offshore fisheries industry, this study utilized squid yellow as the raw material and employed supercritical CO₂ extraction technology to extract high-PUFA fish oil. The research systematically investigated raw material pretreatment, extraction process parameter optimization, product quality assessment, and the process's suitability for industrial-scale application. Results demonstrated an average fish oil extraction rate of 18.6%, PUFA content exceeding 65%, and an oxidation value stable at 4.5±0.2 meq/kg—all meeting regulatory standards with no solvent residues, significantly outperforming traditional solvent extraction methods. The process features modular scalability, excellent compatibility with local raw materials and policies in Shidao, and offers both economic and ecological benefits. This study provides a viable technical solution for high-value utilization of squid yellow and supports the extension of the offshore fisheries processing value chain.
Study on Quality Improvement Effect of Phosphate-Free Water Retainer on Squid
This study addresses the issues of water loss and texture deterioration during squid processing by developing a phosphate-free water retainer treatment process. Immersion concentration, time, and temperature parameters were established, and comparative experiments were conducted. Water-holding capacity, water loss rate, texture parameters, and protein structure changes were measured to analyze the regulatory effects of treatment conditions on quality. Results demonstrated that the phosphate-free system exhibited excellent performance in stabilizing water binding states and improving tissue structure. Under medium concentration conditions, samples showed the lowest centrifugal water loss and stable mass retention. Texture testing revealed reduced hardness and improved elasticity, with tissue state becoming more uniform. Electrophoresis results indicated protein transformation from high molecular weight to medium-low molecular weight, with increased exposure of hydrophilic groups and enhanced water-binding capacity. This system achieves water regulation and texture optimization without phosphate addition, demonstrating stable processing adaptability and providing support for subsequent process refinement and quality enhancement.
Neuroprotective Effects of GDNF-Overexpressing Neural Stem Cells on Ischemic Stroke in Rats
To investigate the neuroprotective effects of glial cell line-derived neurotrophic factor (GDNF)-overexpressing neural stem cells (NSCs) in a rat model of ischemic stroke, this study evaluated their impact on neurological deficits, infarct volume, and inflammatory cytokine levels. Ninety healthy male SD rats were randomly divided into four groups: sham group, model group, NSC-vector group, and NSC-GDNF group. Except for the sham group, all other groups were subjected to middle cerebral artery occlusion (MCAO) to establish the ischemic stroke model. After successful modeling, corresponding interventions were administered according to group assignments. Neurological deficit scores were evaluated at 24h, 72h, and 7d post-intervention, and infarct volume percentages were measured at day 7. Results showed that the NSC-GDNF group exhibited significantly reduced neurological deficit scores (2.16±0.57 at day 7) and markedly decreased infarct volume percentage (11.37±2.42%) compared to other groups (P<0.05). These findings demonstrate that GDNF-overexpressing NSCs significantly improve neurological function and reduce infarct volume in ischemic stroke rats, providing a reliable experimental foundation for stem cell-based targeted therapy in clinical ischemic stroke treatment.
Geopolitical Tensions, Currency Collapse, and Public Health: Protecting Civilians in Crisis Zones
Recent geopolitical tensions in the Middle East have triggered cascading crises that extend far beyond security: severe currency depreciation, hyperinflation, shortages of essential medicines and food, and a steady erosion of population health and health system capacity. For ordinary civilians—especially children, pregnant women, older adults, and those with chronic illnesses—these shocks are not abstract economic indicators but daily threats to survival and dignity. Sharp currency devaluation has rendered savings nearly worthless, pushing basic goods and healthcare out of reach for millions. As import-dependent health systems face disrupted supply chains, medications, diagnostics, and medical consumables become scarce or unaffordable. Inflation further reduces real household income, worsening malnutrition, mental distress, and preventable mortality. Such socioeconomic collapse undermines the foundations of universal health coverage and global health security, turning economic stress into a public health emergency. From a health policy perspective, crisis-affected populations deserve consistent protection: unimpeded access to humanitarian and medical assistance, safeguarding of critical health infrastructure, and policy responses that prioritize equity and humanitarian principles. Evidence repeatedly shows that sanctions, conflict, and economic instability disproportionately harm vulnerable groups and generate long-term public health scars. The international health community has a responsibility to advocate for civilian protection, evidence-based humanitarian response, and peaceful resolution of disputes. Health is not a casualty of geopolitics; it is a universal right that must be upheld even in the most challenging contexts.
Research on Intelligent Pipeline Robot Navigation and Defect Identification Based on Multi-Sensor Fusion
With the increasing complexity of pipeline inspection and maintenance requirements, traditional single sensor methods have exposed significant technical bottlenecks in dealing with changing pipeline environments. This study proposes an intelligent pipeline robot navigation and defect recognition framework based on multi-sensor fusion. By integrating the complementary characteristics of lidar, visual sensors, and inertial measurement units (IMUs), a laser vision inertial multimodal data fusion system is constructed. The system adopts a hierarchical progressive architecture, with the bottom layer achieving spatiotemporal alignment and dynamic compensation of multi-source data through extended Kalman filtering. The middle layer uses improved ICP algorithm and visual SLAM technology to complete environmental modeling and pose estimation. The top layer is based on lightweight convolutional neural networks to achieve accurate recognition of defect types and positions. The experiment shows that the proposed method achieves centimeter level positioning accuracy and 92.7% defect recognition accuracy in complex pipeline scenes, significantly improving the system's environmental adaptability and detection reliability under interference such as lighting changes and metal reflections compared to traditional methods. At the level of multimodal data fusion, an innovative nonlinear optimization framework based on UKF has been proposed, which achieves collaborative optimization of pose estimation and feature extraction by unifying the state vectors of modeling navigation and defect recognition tasks. Experimental verification shows that the framework can control the cumulative positioning error within ± 8cm in typical complex scenarios such as pipeline bends and branch nodes, and improve system robustness by more than 40% through multi-sensor redundancy design. In response to the detection requirements of different pipe diameters, the system successfully verified its universality within the range of 200mm to 800mm pipe diameters by adaptively adjusting sensor scanning parameters and robotic arm configurations. The navigation drift in small pipe diameter scenarios was reduced by 42% compared to traditional methods, and the coverage rate of large-scale pipeline detection reached 98.3%. Engineering application testing has shown that this technology improves pipeline inspection efficiency by 4.2 times that of manual operation, reduces operation and maintenance costs by about 65%, and the related achievements have been industrialized in the transformation project of material feeding robots in petrochemical enterprises, significantly reducing equipment downtime and manual intervention frequency. The study further explored the cross domain migration potential of multi-sensor fusion technology, and quickly adapted the core algorithm to scenarios such as oil and gas pipelines, urban comprehensive pipe galleries, and industrial drainage systems through modular hardware design and open software architecture. In oil and gas pipeline inspection, the system has achieved a defect recognition accuracy of 0.1mm level; In the application of comprehensive pipe gallery, the positioning accuracy reaches ± 3cm; in industrial drainage scenarios, the accuracy of low light environment recognition remains at 89.7%. The defect knowledge base based on cloud edge collaboration has accumulated over 100000 sets of sample data, supporting rapid adaptation to new scene requirements through transfer learning. This study not only provides high-precision and strong robustness technical solutions for the field of pipeline inspection, but also proposes a layered fusion architecture and adaptive optimization strategy, which provides reusable methodological support for a wider range of engineering scenarios such as mobile robots and industrial monitoring, promoting the evolution of intelligent perception systems towards global intelligent monitoring networks.
Global Fan Repatriation Marketing Strategy：A Feasibility Analysis for Subsidizing Overseas 22/7 Fans to Attend the 22/7 10th Anniversary Live Performance at Budokan
As Japanese idol group 22/7 approaches its tenth anniversary with a stated aspiration to perform at Nippon Budokan, questions of audience density and symbolic scale become central. This article evaluates a speculative but numerically grounded proposal: reimbursing international fans for airfare and accommodation to ensure a fully realized Budokan event. Drawing on publicly observable fan distribution metrics and recent overseas live attendance figures, the study models a scenario in which overseas mobilization guarantees capacity fulfillment.
Research on Intelligent Analysis Framework for Time Series Data and Financial Risk Early Warning in the Digital Economy
With the rapid development of the digital economy, the scale and complexity of financial market transactions have grown exponentially. Traditional risk warning models based on static data are no longer able to meet the needs of dynamic risk identification. This study addresses the challenge of dynamic correlation analysis of time-series data and innovatively constructs an intelligent analysis framework that integrates spatiotemporal attention mechanism and time-series graph neural network, achieving unified modeling and real-time warning of market risk, credit risk, and liquidity risk. This framework captures key time nodes and risk transmission paths through spatiotemporal attention mechanisms, and combines time-series graph neural networks to analyze dynamic relationships between financial institutions, effectively solving the problem of information fragmentation in traditional methods for modeling multidimensional time-series data. The introduction of CRITIC objective weighting method to optimize multi model fusion strategy, combined with ARIMA-GARCH combination model and deep learning algorithm, significantly improved the cross scale correlation analysis ability between high-frequency trading data and macroeconomic indicators. The research has broken through the limitations of traditional models at the methodological level, achieving accurate characterization of risk contagion networks through dynamic weight allocation and real-time correlation analysis. Real time test data shows that the response delay of the framework in abnormal transaction detection is reduced by 96% compared to traditional systems, the accuracy of risk event warning is 92.4%, and the warning signal is sent out on average 14.3 minutes in advance. In the bond default warning task, the AUC value of the model reached 0.91 in the 9 months before default, which was 0.14 higher than the traditional logistic regression model, and the recall rate increased to 87%, effectively reducing the risk of underreporting. The experiment of multi-source heterogeneous data fusion shows that after integrating satellite images and supply chain data, the KS value of the enterprise credit evaluation model increases by 45.2%, and the recognition accuracy of credit risk for manufacturing enterprises increases by 18.7%. The study further validated the robustness of spatiotemporal joint modeling in extreme market environments. In the 2022 global financial market volatility test, the framework successfully alerted regional bank liquidity crises 23 trading days in advance. On a theoretical level, this study improves the spatiotemporal dynamic analysis paradigm of financial risk warning and proposes a risk evolution modeling method based on deep learning and graph network technology. On a practical level, the framework can be directly embedded into financial institution risk control systems through modular design and real-time data interfaces, achieving dynamic assessment and graded warning of risk signals. The empirical results show that institutions adopting this framework have improved their risk disposal response efficiency by 40%, and the average annual risk exposure reduction brought about by capital allocation optimization is 3% -5%. The research provides a solution with both progressiveness technology and operational feasibility for financial risk prevention and control in the digital economy era, and its methodological breakthrough provides an important reference for research in complex system modeling, multi-source data fusion and other fields.
Study on the Appropriate Application of Traditional Chinese Medicine Formulas in Integrated Traditional Chinese and Western Medicine Diagnosis and Treatment Scenarios-Taking Common Chronic Diseases (Hypertension/Diabetes/Chronic Gastritis) as an Example
Objective: Based on a big data set of 84,294 traditional Chinese medicine (TCM) prescriptions, a four-dimensional matching model (Fitting Model, FM) integrating "syndrome type-target point-functionality-ingredient" was constructed. The matching degree was quantitatively calculated to elucidate the precise matching patterns of TCM prescriptions for hypertension, diabetes, and chronic gastritis, thereby providing mechanistic and verifiable protocols for integrated traditional Chinese and Western medicine clinical medication. Methods: 1. Data standardization: The efficacy of herbal formulas (69,407 unique values) was classified into 12 major categories according to the "Comprehensive Dictionary of Chinese Herbal Formulas". Active ingredients F = α × J + β × R + γ × SJRSα/β/γwere extracted from the TCMSP database by associating drug components, while Western drug targets were determined by referencing DrugBank. Model construction: A fitness score formula was proposed (where represents the matching degree of syndrome type, represents the synergy degree of target, represents the mitigation degree of side effects, and represents the weight coefficient, calibrated to 0.35/0.40/0.25 via AHP hierarchical analysis method). 3. Screening and validation: Suitable herbal formulas were screened using the FM model, and the binding energy between drug components and targets was validated through molecular docking (AutoDock Vina). The risk of combination therapy was quantified by incorporating the "Precautions" field from the database. Results: A total of 328 high- F ≥ 8.0F均值 = 8.6F均值 = 8.4F均值 = 8.71RriskRrisk ≥ 8.0 adaptability formulations were screened, including 96 for hypertension, 112 for diabetes, and 120 for chronic gastritis. Molecular docking validation demonstrated that the binding energies of core drug components to targets were all <-5.0 kcal/mol (e.g., Uncaria rhynchophylla isuncaria alkaloid-CACNA1C: -7.2 kcal/mol). The combination risk scoring indicated that high-risk combinations accounted for only 4.2%, with clear avoidance strategies available for all. Conclusion: The FM model can effectively quantify the compatibility of traditional Chinese medicine (TCM) formulations. High-compatibility formulations achieve synergy with Western medicines through "strong component-target binding" and "precise efficacy-side effect matching", providing verifiable scientific evidence for the integrated diagnosis and treatment of three chronic diseases using TCM and Western medicine.
Integrated traditional Chinese and Western medicine
Study on the Adaptability of Traditional Chinese Medicine Prescriptions under Integrated Traditional Chinese and Western Medicine: A Case Study of Common Chronic Diseases (Hypertension, Diabetes Mellitus, Chronic Gastritis)
Based on a TCM prescription database containing 81,219 valid records, this study focused on three clinically high-incidence chronic diseases (hypertension, diabetes mellitus, and chronic gastritis), constructed an evaluation system and quantitative model for the adaptability of TCM prescriptions in the diagnosis and treatment scenario of integrated traditional Chinese and Western medicine (TCM-WM), and systematically explored the adaptive application rules and characteristics of TCM prescriptions in this diagnosis and treatment mode. Combining text mining technology, statistical analysis and model verification methods, the study conducted an in-depth analysis from three core dimensions: prescription source distribution, drug composition characteristics, and quantitative adaptability score. The results showed that there were 4,428 hypertension-related prescriptions with an average adaptability score of 4.15; 1,659 diabetes-related prescriptions with an average adaptability score of 3.92; and 2,885 chronic gastritis-related prescriptions with an average adaptability score of 3.83. A significant positive correlation was found between the number of drugs and the adaptability score (r=0.118, p<0.001), and there were extremely significant statistical differences in the adaptability scores of TCM prescriptions for different chronic diseases (F=58.974, p<0.001). The research results can provide solid data support and scientific methodological reference for the precise screening and standardized application of TCM prescriptions in integrated TCM-WM diagnosis and treatment, and offer new ideas for the optimization of integrated TCM-WM treatment regimens for chronic diseases.
Lonely Confined Spaces: A Social Stratification Study of Dwelling Duration in University Library Toilet Stalls
Background: Toilet stalls serve multiple functions for students: avoiding acquaintances, scrolling phones, and escaping academic pressure. Existing research rarely examines dwelling durations among status groups. Methods: 30‑day fieldwork in six male stalls of a “Double First‑Class” university library (n=327). Findings: (1) Doctoral students' average dwelling (8.7 min) > master's (4.2) > undergrad (2.3); (2) Backpack +3.5 min; (3) Video audio correlates with duration (r=0.67, p<0.05). Conclusion: Toilet stalls are micro‑fields for status performance and pressure relief. Future research should examine squatting posture vs. publication counts.
How Many Car Trips Is Chinese New Year Firecracker Use Equivalent To? A National PM2.5 Emission Perspective
This study develops a transparent, stepwise estimation framework to quantify nationwide PM2.5 emissions from minimal firecracker use during the Chinese New Year. Under conservative assumptions we estimate approximately 1,014 tons of PM2.5 nationwide. This represents roughly 1–2% of China’s annual vehicular particulate emissions. The results illustrate if you set off firecrackers during the Chinese New Year, you would need to give up approximately 100–200 kilometers of car travel to compensate for the environmental “sin” you have committed. The results indicate that setting off firecrackers during the Chinese New Year is roughly equivalent to 100–200 kilometers of car travel, meaning that you would need to forgo that distance to compensate for the resulting environmental impact.
The Sacramental Masquerade of Ave Mujica: An Exegetical Investigation of Latin Nomenclature and Sanctified Personaein the Proto-Canonical Mythos of a Post-Secular Gothic Anime
This study undertakes a solemn yet deliberately absurde exegetical investigation of BanG Dream! Ave Mujica, a fictional Gothic metal ensemble from contemporary Japanese animation, read here as a proto-canonical mythos with latent theological resonances. Employing the hermeneutical lens of Latinate nomenclature, symbolic anthropology, and historical theological tropes, this paper examines how the five personae — Oblivionis, Mortis, Doloris, Timoris, and Amoris — function as theological signifiers analogous to Christian motifs of oblivion and kenosis, death and transfiguration, sorrow and lamentation, reverential fear, and sacrificial love. Drawing upon canonical and Christian mystical sources and patristic hagiography, we argue that the seemingly secular and aesthetic conventions of Ave Mujica enact a sacramental masquerade through which affective identities are dramatized. Within this framework even the scripted conceit that the members awaken like dolls under moonlight acquires an apocalyptic gloss consonant with resurrection symbolism. Ultimately, the paper proposes that Ave Mujica — though never intended as doctrinal text — yields a mythic theology of affective experience, wherein secular performative spectacle and ancient theological archetypes intersect in a post-secular cultural liturgy that both mirrors and mocks the classical interpretation of sacred personae.
Ave Mujica, Latin nomenclature, theological symbolism, Christian motifs, apophatic tradition, symbolic anthropology, post-secular mythos, affective identity, Gothic animation
From the stage to the vegetable garden: Mujica's Mutsumi and her cucumber timing experiment
This article studies the process of Mutsumi planting cucumbers in actual combat and using the timing prediction model to predict its growth trend in a semi-serious way. Although it comes from the animation BanG Dream! The setting of Ave Mujica, this article introduces real style background, timing prediction modelling and random generation of simulation data, and shows the training process, error evaluation and visualisation output for follow-up research or fan creation reference.
Time sequence prediction; analogue data generation; LSTM; cucumber growth; Ave Mujica; Mutsumi
Research on Mechanism Optimization for Fact Verification in Financial Institution Inspections from a Collaborative Governance Perspective: Focusing on the “Face-to-Face Meeting Communication” Model
Within the supervisory inspection framework of financial institutions, the fact verification phase constitutes the critical nexus between problem identification and corrective action implementation. Conventional unidirectional and fragmented verification models are susceptible to information distortion, accountability ambiguity, and rectification delays. Grounded in collaborative governance theory and contextualized within the current paradigm of enhanced financial regulation and risk mitigation, this paper conducts an in-depth examination of a collaborative verification mechanism. This mechanism is centered on "face-to-face meeting communication" and integrates three key stakeholders: the inspection department, the inspected unit, and the issue closure department (typically the responsible business line management unit). It emphasizes the concurrent determination of a rectification plan during the fact verification process. This approach aims to foster greater acceptance and cooperation from the inspected unit and to preemptively mitigate delays and disputes during the issue closure phase that often arise from subjective interpretive differences. Through theoretical analysis, mechanism design, case application, and the integration of structured comparative and analytical tables (Tables 1-6), this paper substantiates the model's practical value in enhancing regulatory efficacy, strengthening internal controls, and promoting a compliance culture. It also offers insights for optimizing regulatory policies and institutional internal control procedures, supported by an expanded reference list of 30 sources aligned with international scholarly standards.
Research on Anomaly Detection and Root Cause Analysis of Performance Degradation in Photovoltaic Power Stations
To address abnormal phenomena such as sudden power drops during photovoltaic power plant operation, this study proposes a data-driven anomaly detection and root cause analysis method to enhance system maintenance efficiency and power generation benefits. Utilising 5-minute operational data from a 50kW photovoltaic power plant, combined with NASA meteorological data, an integrated anomaly detection framework and multi-dimensional feature engineering system were constructed. K-Means++ clustering and LightGBM classification models were employed for pattern recognition and root cause tracing of detected anomalies. Experiments demonstrate: 1) The anomaly detection framework achieves an F1 score of 0.87; 2) Three distinct power loss patterns and their distribution ratios are identified; 3) The LightGBM root cause classification model attains an average accuracy of 88%. The proposed method effectively diagnoses the root causes of performance degradation in photovoltaic systems, providing both theoretical foundations and technical support for implementing predictive maintenance.
Optimization Research on Hospital Informatization Construction Based on 2023 Medical Resource Statistical Data
Based on 15 national medical and health institution statistical documents in 2023, this study systematically sorts out core indicators such as the number of hospitals, bed capacity grouping, and distribution of primary-level institutions. Adopting quantitative analysis methods, it reveals the coupling correlation mechanism between medical resource allocation and hospital informatization construction. The study introduces the Theil index to measure the regional balance of medical resources, and combined with 5 types of core data tables, clarifies the core characteristics of China's medical resources: "small and medium-sized hospitals as the mainstay, uneven regional distribution, and weak foundation of primary-level institutions", as well as their constraints on hospital informatization construction. By constructing a "resource-demand-investment" three-dimensional matching model, a targeted hierarchical and classified informatization construction path is proposed, providing an optimized scheme with both data support and practical feasibility to solve the current practical dilemmas of "investment imbalance, supply-demand mismatch, and data fragmentation" in hospital informatization construction.
A Study of Integrated Traditional Chinese Medicine (TCM) Intervention for Diabetic Peripheral Neuropathy Rehabilitation: Based on the Spleen-Kidney Correlation Theory
This study thoroughly explores the practical application value and efficacy of a comprehensive treatment regimen based on the traditional Chinese medicine (TCM) theory of "Spleen-Kidney Correlation" in the rehabilitation process of diabetic peripheral neuropathy (DPN). By systematically reviewing the historical origins, core connotations, and significant position of the "Spleen-Kidney Correlation" theory within the TCM theoretical framework, and integrating modern medical understanding of the pathogenesis of DPN, this study further analyzes the pathological characteristics of the disease from a TCM perspective. It proposes a comprehensive treatment strategy primarily guided by the principles of strengthening the spleen and kidney, as well as promoting collateral circulation and activating blood flow. During the implementation of the study, we rigorously designed a scientific research framework, established clear inclusion and exclusion criteria for study subjects, and adopted a randomized controlled trial method to ensure the reliability and comparability of the data. By systematically observing the physiological indicators, symptom improvement, and changes in quality of life of patients after receiving the comprehensive Traditional Chinese Medicine (TCM) treatment regimen, we comprehensively evaluated the clinical efficacy of this protocol.
Integrated Traditional Chinese Medicine (TCM) Intervention
Strengthening Spleen and Tonifying Kidney
Promoting Blood Circulation and Unblocking Collaterals
A Systematic Review of the Impact of Maize Mold Exposure on Lung Health of Farmers in the Central and Eastern Plains of China Under Long-term Rainy Conditions
The central and eastern plains of China are major maize-producing areas. In October 2025, prolonged rainy weather led to massive mold growth on maize in producing regions such as Shandong and Henan. Farmers lacked effective protection when harvesting and shelling maize in the rain, resulting in direct exposure to high concentrations of mold spores and a significant increase in the risk of lung infectious diseases. This paper systematically reviews the promoting effect of rainy weather on mold growth and the impact of mold spore exposure on lung health, analyzes the pathological mechanisms and epidemiological characteristics of farmers' lung infections, evaluates the effectiveness of current prevention and control measures, puts forward targeted environmental and health intervention strategies, and provides suggestions for future research directions and policy formulation. The aim is to improve the health security level of farmers and contribute to the sustainable development of food security and public health.
Copyright (c) 2025 Journal of the European Academy Open University https://creativecommons.org/licenses/by-nc/4.0
Research on Power Regulation Characteristics and Optimisation Strategies for Photovoltaic Power Stations under Low Irradiance Conditions Based on Operational Data Mining
Addressing issues such as inadequate power regulation capability and reduced generation efficiency in photovoltaic power stations under low irradiance conditions, this study proposes a performance optimisation method based on operational data mining. Utilising actual operational data from a 50kW photovoltaic power station, an improved variational modal decomposition and fuzzy C-means clustering method were employed to analyse the system's power regulation characteristics under low irradiance conditions. Integrating NASA meteorological data, a system performance evaluation model accounting for multiple environmental factors was established, alongside an adaptive optimisation control strategy. Research indicates: the system exhibits pronounced power regulation lag under low irradiance, with response times extended by 42% compared to normal conditions. The proposed optimisation control strategy enhances power generation efficiency by 5.8% and reduces power fluctuations by 37.2% under low irradiance. [Conclusion] The proposed method effectively improves the operational performance of photovoltaic systems under low irradiance, providing a novel technical pathway to enhance power stations' all-weather power generation capabilities.
The Necessity of Constructing Civil Air Defense Engineering in Residential Communities
With the rapid development of the national economy and the continuous improvement of people's living standards, residential communities in cities have gradually become an important part of the national civil air defense engineering construction system against the backdrop of social development and evolving international situations. In peacetime, civil air defense projects in various residential communities serve functions such as commercial development and recreational activities for the public. However, when war breaks out, these projects can be quickly transformed into civil air defense facilities, providing solid protection for people's basic lives and property. Therefore, civil air defense engineering in residential communities has become a vital military-civilian facility integrating peacetime and wartime functions. Civil air defense engineering in modern communities is also a key component of China's national defense security construction system. This paper first analyzes the current status of the civil air defense engineering construction system in urban residential communities in China, then elaborates on the importance of constructing such projects in communities. Finally, based on China's current actual situation and in light of the prominent problems existing in the existing civil air defense projects, corresponding countermeasures and suggestions are put forward.
The diversified development of pension financial products: a bank-centered exploration
Under the background of the acceleration of population ageing and the diversification of pension needs, the innovation of pension financial products has become the core proposition to deal with the challenges of the silver-haired economy. This paper takes the bank-dominated pension finance ecology as the entry point, and reconstructs the dynamic life cycle model and the theoretical framework of intertemporal utility optimization, an asset allocation strategy based on multi-dimensional demand clustering and an open product architecture design are proposed, which break through the limitation of single function of traditional financial products, it explores the innovation of technology-driven service models such as the construction of closed-loop medical health payment through API technology, integrated home care monitoring through the Internet of things, and evaluation of digital twin empowerment institutions, and build a two-dimensional prevention and control mechanism for full-cycle risk monitoring and consumer protection. The purpose of this paper is to provide theoretical support and practical path for the product iteration and service upgrading of commercial banks in the field of pension finance, and to help realize the precise allocation and sustainable development of pension resources.
An Analysis of Common Problems and Countermeasures in the Teaching of Civil Air Defense Engineering Architectural Design
Civil air defense engineering is an important national strategy, serving as a long-term national initiative to advance China's national defense strategic needs and the stable development of the economy. Against the backdrop of the intricate and complex international situation, which poses significant threats to China's stable and secure development, promoting the construction of civil air defense engineering has become crucial. In the construction process of civil air defense engineering, architectural design serves as the overall guideline and the fundamental reference for specific implementation. Therefore, the cultivation of professionals specialized in civil air defense engineering architecture is particularly important. Only by continuously optimizing the teaching link of civil air defense engineering architectural design can we boost the development of civil air defense engineering, and further advance the overall strategic layout of national defense and national development.
Research on the Mechanism Test and Spatial Optimization of Digital Economy driving the Improvement of New Quality Productivity in Hebei Province
At the critical moment of industrial structure transformation and the kinetic energy conversion, the new digital economy as the core engine to foster productivity can assign role increasingly highlighted. As a major industrial province in northern China, Hebei province needs to solve the development dilemma of high proportion of traditional industries and insufficient innovation capacity. Based on the panel data of 11 cities in Hebei Province from 2011 to 2023, this paper constructs a comprehensive evaluation system of digital economy and new quality productivity, and uses entropy method, panel data model, mediating effect model and spatial Durbin model to systematically explore the enabling effect, mechanism, regional heterogeneity and spatial characteristics of digital economy on new quality productivity. Based on this, this paper puts forward countermeasures and suggestions from the four dimensions of digital infrastructure improvement, regional collaborative development, mechanism innovation activation and policy system optimization, providing decision-making reference for Hebei Province to solve the problems of industrial transformation and cultivate new quality productivity with the help of digital economy.
A Brief Discussion on Construction Technology and Quality Control of Civil Air Defense Engineering
From the perspective of civil air defense engineering, the fundamental goal of construction is to realize social benefits and combat readiness benefits. In this regard, continuously improving the quality of civil air defense engineering and presenting excellent peacetime and wartime functions have become the top priority. This study conducts in-depth investigation and analysis on multiple civil air defense engineering projects in Guizhou Province, and finds that there are still many problems, which will directly affect the overall quality of civil air defense engineering and deviate to a certain extent from the combat readiness requirements of civil air defense engineering. Therefore, it is necessary to sort out and summarize the relevant problems, and formulate scientific and feasible solutions through discussion and research.
Towards Carbon Neutrality: The Development and Technological Pathways from Green Buildings and Passive Buildings to Zero-Carbon Buildings
Against the backdrop of global efforts to address climate change and China's steadfast advancement of the "dual carbon" strategic goals, the low-carbon transition in the building sector has become critical to achieving carbon neutrality. This paper examines the evolutionary pathway from green buildings and passive buildings to zero-carbon buildings, systematically analyzing the inherent logic and progressive development of these three building concepts in terms of their sustainability objectives, core principles, and technological systems. The study reveals that green buildings establish a comprehensive philosophy of lifecycle environmental friendliness, passive buildings minimize building energy demand through state-of-the-art energy efficiency technologies, while zero-carbon buildings build upon the solid foundations of the former two by integrating renewable energy and carbon management to ultimately achieve net-zero carbon balance in building operation and even across the entire lifecycle. The paper further analyzes the key technological pathways underpinning this evolution, including passive-first strategies ranging from integrated design to ultra-low energy consumption, as well as active renewable energy supply systems progressing from energy efficiency enhancement to energy generation integration. Ultimately, the paper aims to provide a clear theoretical framework and practical roadmap for the building industry to systematically and incrementally progress toward the goal of carbon neutrality.
人防工程电气设计常见问题与对策
随着我国城市发展水平的不断提高，人防工程越来越受到国家的重视。人防工程不仅为解决城市发展空间受限、防灾减灾等方面提供了很好的途径，而且为提升整座城市的防护及生存能力，提供了重要支撑。人防工程中的电气专业为人防工程运行提供了动力来源，显得尤为重要。