Search Results (119)

The traditional graduate admission method is to evaluate students’ performance and interview results, but this method relies heavily on the subjective feelings of the evaluators, and these methods may not be able to comprehensively and objectively evaluate the qualifications and potential of the applicants. At present, artificial intelligence has played a key role in the reform of the education system, and the data processing function of artificial intelligence has greatly reduced the workload of screening work. Therefore, this study aims to optimize the graduate enrollment evaluation process by applying a new composite model, the random forest–improved sparrow search algorithm (RF–ISSA). The research used seven data sets including research, cumulative grade point average (CGPA), letter of recommendation (LOR), statement of purpose (SOP), university rating, TOEFL score, and graduate record examination (GRE) score, and carried out the necessary data pre-processing before the model construction. The experimental results show that the RMSE and R values of the composite model are 0.0543 and 0.9281, respectively. The predicted results of the model are very close to the actual data. In addition, the study found that the importance score of CGPA was significantly higher than other characteristics, and that this value has the most significant impact on the outcome of the graduate admissions assessment. Overall, this study shows that combining the integrated strategy sparrow search algorithm (ISSA) with hyperparameter optimization and focusing on the most influential features can significantly improve the predictive performance and applicability of graduate admissions models, providing a more scientific decision support tool for school admissions professionals. Full article

The engineering of pore structures has great significance in the development of high-performance carbon-based supercapacitor electrode materials. Herein, we have successfully transformed jujube pits into hierarchical porous carbon (HJPC-4) with excellent capacitive properties via a unique hydrothermal–carbonization–activation strategy. Hydrothermal pretreatment is essential to regulate the supermesoporous and macroporous structure of samples and their superior electrochemical performances. Owing to the large ion-accessible, remarkable supermesoporous and macroporous pore volume, HJPC-4 exhibited ultra-high specific capacitance (6 M KOH: 316 F g⁻¹ at 1 A g⁻¹; EMIMBF₄: 204 F g⁻¹ at 1 A g⁻¹), excellent rate performance (6 M KOH: 231 F g⁻¹ at 100 A g⁻¹; EMIMBF₄: 154 F g⁻¹ at 30 A g⁻¹), outstanding cycling stability (6 M KOH: the retention rate is 92.11% after 60,000 cycles at 10 A g⁻¹; EMIMBF₄: the retention rate is 80% after 10,000 cycles at 5 A g⁻¹), and ultimate energy/power density up to 91.09 Wh kg⁻¹/24.25 kW kg⁻¹ in EMIMBF₄ two-electrode systems. This work presents unique insights into the effect of the pore structure of carbon-based materials on their capacitive energy storage. Full article

Digital transformation has become a critical aspect of modern education, necessitating the development of digital skills among all students, including those with disabilities. Among these, blind students face unique challenges in acquiring the digital competencies needed for academic success and professional integration. This study aimed to enhance the digital transformation skills of blind postgraduate students by evaluating the effectiveness of a cloud-based learning management system, Moodle Cloud. Using a mixed methods approach, we combined descriptive and quasi-experimental designs to assess the impact of the intervention. The sample included 20 blind graduate students from Beni Suef University, equally divided into experimental and control groups. Pre- and post-assessments measured participants’ digital transformation skills through achievement tests and performance evaluations. The findings indicated significant improvements in the experimental group, with higher scores in both the achievement tests and performance assessments compared to the control group. The results suggest that the cloud-based learning management system played a vital role in enhancing digital skills, and no significant differences were found between remote and in-person applications of the intervention. The study emphasizes the importance of incorporating modern digital technologies into the education of blind students, aligning with Egypt’s Vision 2030 plan and ongoing educational reforms. Full article

Today, most of the world’s electric energy is generated by burning hydrocarbon fuels, which causes significant emissions of harmful substances into the atmosphere by thermal power plants. In world practice, flue gas cleaning systems for removing nitrogen oxides, sulfur, and ash are successfully used at power facilities but reducing carbon dioxide emissions at thermal power plants is still difficult for technical and economic reasons. Thus, the introduction of carbon dioxide capture systems at modern power plants is accompanied by a decrease in net efficiency by 8–12%, which determines the high relevance of developing methods for increasing the energy efficiency of modern environmentally friendly power units. This paper presents the results of the development and study of the process flow charts of binary and trinary combined-cycle gas turbines with minimal emissions of harmful substances into the atmosphere. This research revealed that the net efficiency rate of a binary CCGT with integrated post-combustion technology capture is 39.10%; for a binary CCGT with integrated pre-combustion technology capture it is 40.26%; a trinary CCGT with integrated post-combustion technology capture is 40.35%; and for a trinary combined-cycle gas turbine with integrated pre-combustion technology capture it is 41.62%. The highest efficiency of a trinary CCGT with integrated pre-combustion technology capture is due to a reduction in the energy costs for carbon dioxide capture by 5.67 MW—compared to combined-cycle plants with integrated post-combustion technology capture—as well as an increase in the efficiency of the steam–water circuit of the combined-cycle plant by 3.09% relative to binary cycles. Full article

This study demonstrates the significant advantages of integrating computational fluid dynamics (CFD) with artificial intelligence (AI)-based machine learning (ML) to optimize the pre-reforming process for reversible solid oxide cell (r-SOC) technologies. It places a distinct focus on the relationship between process variables, aiming to enhance the preparation of quality r-SOC-ready fuel, which is an indispensable element for successful operation. Evaluating the intricate thermochemistry of syngas-containing reforming processes involves employing an experimentally validated CFD model. The model serves as the foundation for gathering essential data, crucial for the development and training of AI-based machine learning models. The developed model forecasts and optimizes reforming processes across diverse fuel compositions, encompassing oxygen-containing syngas blends and controlled feedstock outlet process conditions. Impressively, the model’s predictions align closely with CFD outcomes with an error margin as low as 0.34%, underscoring its accuracy and reliability. This research significantly contributes to a deeper understanding and the qualitative enhancement of preparing high-quality syngas for SOC under improved process conditions. Enabling the early availability of valuable information drives forward sustainable research and ensures the safe, consistent operation assessment of r-SOC. Additionally, this strategic approach substantially reduces the need for resource-intensive experiments. Full article

The Saudi government’s educational reforms aim to align the system with market needs and promote economic opportunities. However, a lack of credible data makes assessing public sentiment towards these reforms challenging. This research develops a sentiment analysis application to analyze public emotional reactions to educational reforms in Saudi Arabia using AraBERT, an Arabic language model. We constructed a unique Arabic dataset of 216,858 tweets related to the reforms, with 2000 manually labeled for public sentiment. To establish a robust evaluation framework, we employed random forests, support vector machines, and logistic regression as baseline models alongside AraBERT. We also compared the fine-tuned AraBERT Sentiment Classification model with CAMeLBERT, MARBERT, and LLM (GPT) models. The fine-tuned AraBERT model had an F1 score of 0.89, which was above the baseline models by 5% and demonstrated a 4% improvement compared to other pre-trained transformer models applied to this task. This highlights the advantage of transformer models specifically trained for the target language and domain (Arabic). Arabic-specific sentiment analysis models outperform multilingual models for this task. Overall, this study demonstrates the effectiveness of AraBERT in analyzing Arabic sentiment on social media. This approach has the potential to inform educational reform evaluation in Saudi Arabia and potentially other Arabic-speaking regions. Full article

This study examines the transformation of the urban fabric by analyzing changes in both structural and numerical parameters of spatial organization, with a particular emphasis on the hierarchical relationships between streets, blocks, and buildings. The research utilizes Bursa, the former Ottoman capital in Turkey, as a case study to explore these dynamics. The elements of streets, blocks, and buildings are posited as fundamental components in conceptualizing cities as layered palimpsests, where successive historical layers coexist within the urban fabric. The research establishes a conceptual parallel between the methodologies and analytical tools of urban morphology, particularly through the shared notion of the palimpsest. In the case of Bursa, the architectural remains and urban form of the Early, Classical, and Late Ottoman periods and of the Republican period are superimposed. In particular, the late Ottoman reform era, the Tanzimat period of the 19th century, brought great change. Historical maps from this era serve as primary sources for comprehending the evolving character and spatial configuration of the city. This research presents a novel methodological contribution by extending the analytical framework of urban morphology to integrate both qualitative and quantitative data. It employs Geographic Information Systems (GISs) and statistical methods to quantify changes in the urban fabric, assessing both pre-modernization and post-modernization phases. Historical maps from the 19th century are utilized as primary sources to trace and compare transformations within the urban fabric, with clustering techniques further aiding this analysis. The findings provide a deeper understanding of the dynamic processes that shape the historic structure of cities, offering a dual approach to urban transformation that harmonizes historical continuity with modern development. Full article

With the unprecedented growth of the Internet, online evaluations of teaching have emerged as a pivotal tool in assessing the quality of university education. Leveraging data mining technology, we can extract invaluable insights from these evaluations, offering a robust scientific foundation for enhancing both teaching quality and administrative oversight. This study utilizes teaching evaluation data from a mathematics course at a university in Beijing to propose a comprehensive data mining framework covering both subjective and objective evaluations. The raw data are first cleaned, annotated, and preprocessed. Subsequently, for subjective evaluation data, a model combining Bidirectional Encoder Representations from Transformers (BERT) pre-trained models and Long Short-Term Memory (LSTM) networks is constructed to predict sentiment tendencies, achieving an accuracy of 92.76% and validating the model’s effectiveness. For objective evaluation data, the Apriori algorithm is employed to mine association rules, from which meaningful rules are selected for analysis. This research effectively explores teaching evaluation data, providing technical support for enhancing teaching quality and devising educational reform initiatives. Full article

This study was designed to examine the changes in emergency room visits in otolaryngology, head and neck surgery, during the COVID-19 pandemic. The study included 11,277 patients who presented to a tertiary care hospital (ER) and an emergency practice (EP) during on-call hours in the first half of 2018, 2019, and 2020. The epidemiologic parameters, diagnoses, and level of urgency were recorded using a four-step scale. A comparison was made between the pre-pandemic years and 2020. The findings revealed a significant decrease in the frequency of ER visits in the second quarter of 2020 compared to 2019 (ER: 30.8%, EP: 37.8%), mainly due to the fact that there were significantly fewer patients, with low levels of urgency. Certain diagnoses, such as epistaxis (−3.0%) and globus sensation (−3.2%), were made at similar frequencies to 2019, while inflammatory diseases like skin infections (−51.2%), tonsillitis (−55.6%), sinusitis (−59%), and otitis media (−70.4%) showed a significant reduction. The study concludes that patients with a low triage level were less likely to visit the ER during the early stages of the pandemic, but some diagnoses were still observed at comparable rates. This suggests a disparity in perception between patients and ER staff regarding urgency. Many of the issues discussed were also emphasized in the 2024 proposal by the German Ministry of Health to reform emergency care in Germany. Full article

The objective of this article is to shed light on the history of the Reformation in 17th-century Geneva. The lens through which this study is conducted is that of religious publishing activity, which was significantly managed by the Company of Pastors and Professors. The role of the Company in religious publishing is inextricably linked to the unique status of the Church of Geneva within the broader context of the Reformation. The Company’s institutional archives offer insight into the issues at stake in the printed book matters. This article focuses on the role of the Company in local censorship, which diminished over the period under study. The Company’s censorship function enabled it to exert concrete influence on the global scale of Reformed publishing. This influence was the consequence of the Company’s ecclesiastical and theological authority. This authority derived from the status of the Church of Geneva as the principal church and birthplace of the Reformation in the 16th century. An analysis of the metaphors signifying and symbolizing this role in the printed books themselves underlines the pre-eminence of the Church of Geneva in 17th-century Reformation. Full article

We explored the outcomes and challenges encountered during a 12-year collaborative development endeavor in Tanzania, focused on enhancing the healthcare system. The Health Promotion and System Strengthening (HPSS) project, supported by the Swiss Government and implemented by the Swiss Tropical and Public Health Institute (Swiss TPH) from 2011 to 2023, aimed to strengthen various aspects of Tanzania’s healthcare landscape. This included reforms in health insurance through the improved Community Health Fund (iCHF), the establishment of a public–private partnership to optimize the health commodity supply chain via a Prime Vendor System (Jazia PVS), the implementation of health technology management innovations, and the facilitation of participatory community and school health promotion initiatives. Operating in a multisectoral, interdisciplinary, and systemic manner, the HPSS project employed a variety of interconnected strategies, focusing on key entry points within the Tanzanian health system, starting from district level to national policies. These efforts followed a three-stages approach to reach a sustainable adoption of the innovations, going through the process of service and product innovation, integration into service delivery systems, and finally their adoption in the respective institutional policies. Each stage presented distinct frameworks and challenges, detailed in this article. The development of innovative concepts was complemented by capacity building through on-the-job training, establishment of new accredited training programs for pre-service trainings, and the development of new IT systems integrated into the governmental IT environment, as well as efforts to improve transparency, accountability, and governance. Activities in these fields were guided by operational research, following the translational approach of Swiss TPH to go from innovation and validation to application. The example of the HPSS project highlights the cycle of developing and testing innovations at the community and district level, followed by endeavoring national-level integration and policy adjustments, consequently resulting in improved service delivery at the district and community level. Full article

Recent research into sodium zirconate as a high-temperature CO₂ sorbent has been extensive, but detailed knowledge of the material’s crystal structure during synthesis and carbon dioxide uptake remains limited. This study employs neutron diffraction (ND), thermogravimetric analysis (TGA), and X-ray diffraction (XRD) to explore these aspects. An improved synthesis method, involving the pre-drying and ball milling of raw materials, produced pure samples with average crystal sizes of 37–48 nm in the monoclinic phase. However, using a slower heating rate (1 °C/min) decreased the purity. Despite this, the 1 °C/min rate resulted in the highest CO₂ uptake capacity (4.32 mmol CO₂/g Na₂ZrO₃) and CO₂ sorption rate (0.0017 mmol CO₂/g) after 5 min at 700 °C. This was attributed to a larger presence of microstructure defects that facilitate Na diffusion from the core to the shell of the particles. An ND analysis showed that the conversion of Na₂ZrO₃ was complete under the studied conditions and that CO₂ concentration significantly impacts the rate of CO₂ absorption. The TGA results indicated that the reaction rate during CO₂ sorption remained steady until full conversion due to the absorptive nature of the chemisorption process. During the sorbent reforming step, ND revealed the disappearance of Na₂O and ZrO₂ as the zirconate phase reformed. However, trace amounts of Na₂CO₃ and ZrO₂ remained after the cycles. Full article

The shadow economy’s size and impact remain subjects of extensive research and debate, holding significant implications for economic policy and social welfare. In Lebanon, the ongoing crisis since 2019 has exacerbated severe economic challenges, with the national currency’s collapse, bank crisis, and foreign reserve deficits. The World Bank reports Lebanon’s financial deficit surpassed $72 billion, three times the GDP in 2021. Despite a drastic decline in GDP, imports have surged to near-pre-crisis levels, exacerbating economic woes and indicating a constant outflow of foreign currencies. Considering such contracting facts, this paper aims to investigate global factors influencing the shadow economy and discern their manifestations in Lebanon during financial crises. Our methodology involves a comprehensive literature review, alongside a case study approach specific to Lebanon. This dual-method strategy ensures a detailed understanding of the shadow economy’s impact and the development of actionable insights for policy and economic reform. Through this approach, we seek to contribute to a nuanced understanding of Lebanon’s economic landscape and provide valuable guidance for policy decisions aimed at reducing corruption, promoting transparency, and fostering a robust formal economy. The increase in the shadow economy raises the formal economy risk, as resources and activities diverted to informal channels hinder the growth and stability of the official economic sector. Although focusing on Lebanon, this analysis deepens the comprehension of the economic landscape and provides valuable guidance for policymakers, researchers, and stakeholders, aiming to address the root causes of informal economic activities and promote sustainable growth in developing countries in general. Full article

Renewable energy, such as wind power and photovoltaic power, has uncertain and intermittent characteristics and zero marginal cost characteristics. The traditional power market mechanism is difficult to adapt to the new power system with a high proportion of renewable energy, and the original market system needs to be reformed. This paper discusses the application of a VCG auction mechanism in the electricity market, proposes a two-stage VCG market-clearing model based on the VCG mechanism, including the day-ahead market and the real-time market, and discusses the nature of the VCG mechanism. In order to address the discrepancy between the actual output of stochastic generator sets in the real-time market and their pre-scheduled output in the day-ahead market due to prediction deviations, a method for calculating punitive costs is proposed. A reallocation method based on market entities’ contributing factors to budget imbalance is proposed to address the issue of budget imbalance under the VCG mechanism, in order to achieve revenue and expenditure balance. Through an example, the incentive compatibility characteristics of the VCG mechanism are verified, the problems of the locational marginal pricing (LMP) mechanism in the stochastic electricity market with a high proportion of renewable energy are analyzed, the electricity prices of the LMP mechanism and the VCG mechanism under different renewable energy proportions are compared, and the redistribution of the budget imbalance of the VCG mechanism is analyzed. Full article

In this study, vermiculite was explored as a support material for nickel catalysts in two key processes in syngas production: dry reforming of methane with CO₂ and steam reforming of ethanol. The vermiculite underwent acid or base treatment, followed by the preparation of Ni catalysts through incipient wetness impregnation. Characterization was conducted using various techniques, including X-ray diffraction (XRD), SEM–EDS, FTIR, and temperature-programmed reduction (H₂-TPR). TG-TD analyses were performed to assess the formation of carbon deposits on spent catalysts. The Ni-based catalysts were used in reaction tests without a reduction pre-treatment. Initially, raw vermiculite-supported nickel showed limited catalytic activity in the dry reforming of methane. After acid (Ni/VTA) or base (Ni/VTB) treatment, vermiculite proved to be an effective support for nickel catalysts that displayed outstanding performance, achieving high methane conversion and hydrogen yield. The acidic treatment improved the reduction of nickel species and reduced carbon deposition, outperforming the Ni over alkali treated support. The prepared catalysts were also evaluated in ethanol steam reforming under various conditions including temperature, water/ethanol ratio, and space velocity, with acid-treated catalysts confirming the best performance. Full article