Search Results (645)

Despite the significant volume of empirical research found in student-authored academic theses—particularly in the social sciences—these works are often poorly documented and difficult to discover within institutional repositories. A key reason for this is the lack of appropriate metadata frameworks that balance descriptive richness with usability. General standards such as Dublin Core are too simplistic to capture critical research details, while more robust models like the Data Documentation Initiative (DDI) are too complex for non-specialist users and not designed for use with student theses. This paper presents the design and validation of a lightweight, web-based metadata framework specifically tailored to document empirical research in academic theses. We are the first to adapt existing hybrid Dublin Core–DDI approaches specifically for thesis documentation, with a novel focus on cross-methodological research and non-expert usability. The model was developed through a structured analysis of actual student theses and refined to support intuitive, structured metadata entry without requiring technical expertise. The resulting system enhances the discoverability, classification, and reuse of empirical theses within institutional repositories, offering a scalable solution to elevate the visibility of the gray literature in higher education. Full article

This paper presents a critical and comprehensive review of the application of mining waste, specifically waste rock and tailings, in asphalt pavements, with the aim of synthesizing performance outcomes and identifying key research gaps. A systematic literature search yielded a final dataset of 41 peer-reviewed articles for detailed analysis. Bibliometric analysis indicates a notable upward trend in annual publications, reflecting growing academic and practical interest in this field. Performance-based evaluations demonstrate that mining wastes, particularly iron and copper tailings, have the potential to enhance the high-temperature performance (i.e., rutting resistance) of asphalt binders and mixtures when utilized as fillers or aggregates. However, their effects on fatigue life, low-temperature cracking, and moisture susceptibility are inconsistent, largely influenced by the physicochemical properties and dosage of the specific waste material. Despite promising results, critical knowledge gaps remain, particularly in relation to long-term durability, comprehensive environmental and economic Life-Cycle Assessments (LCA), and the inherent variability of waste materials. This review underscores the substantial potential of mining wastes as sustainable alternatives to conventional pavement materials, while emphasizing the need for further multidisciplinary research to support their broader implementation. Full article

The rubber industry is facing major socio-economic and environmental constraints. Rubber-based agroforestry systems represent a more sustainable solution through the diversification of income and the provision of greater ecosystem services than monoculture plantations. Participative approaches are known for their ability to co-construct solutions with stakeholders and to promote a positive impact on smallholders. This study therefore implemented a participatory research process with stakeholders in the natural rubber sector for the purpose of improving inclusion, relevance and impact. Facilitation training sessions were first organised with academic actors to prepare participatory workshops. A working group of stakeholder representatives was set up and participated in these workshops to share a common representation of the value chain and to identify problems and solutions for the sector in Indonesia. By fostering collective intelligence and systems thinking, the process is aimed at enabling the development of adaptive technical solutions and building capacity across the sector for future government replanting programmes. The resulting adaptive technical packages were then detailed and objectified by the academic consortium and are part of a participatory plant breeding approach adapted to the natural rubber industry. On-station and on-farm experimental plans have been set up to facilitate the drafting of projects for setting up field trials based on these outcomes. Research played a dual role as both knowledge provider and facilitator, guiding a co-learning process rooted in social inclusion, equity and ecological resilience. The initiative highlighted the potential of rubber cultivation to contribute to climate change mitigation and food sovereignty, provided that it can adapt through sustainable practices like agroforestry. Continued political and financial support is essential to sustain and scale these innovations. Full article

In this paper, preliminary gate reliability of p-GaN HEMTs under high positive gate bias is studied. Gate robustness is of great interest both from an academic and industrial point of view; in fact, different tests and models can be explored to estimate the device lifetime, which must meet some minimum product requirements, as specified by international standards (AEC Q101, JESD47, etc.). However, reliability characterizations are usually time-consuming and are performed in parallel on multiple packaged devices. Therefore, it would be useful to have a faster method to screen out weaker gate trials, already on-wafer, before reaching the packaging step. For this purpose, a room-temperature stress procedure is presented and described in detail. Then, this screening test is applied to devices with a reference gate process, and, as a result, high gate leakage degradation is observed. Afterwards, a different process implementing a dielectric layer between p-GaN and gate metal is evaluated, highlighting the improved behavior during the stress test. However, it is also observed that devices with this process suffer from very high drain leakage, and this effect is then studied and understood through TCAD (technology computer-aided design) simulations. Finally, the effect of a surface treatment performed on the p-GaN is analyzed, showing improved gate pre-reliability while maintaining low drain leakage. Full article

Two-wheeled self-balancing robots (TWSBRs) are underactuated, inherently nonlinear systems that exhibit unstable dynamics. Due to their structural simplicity and rich control challenges, TWSBRs have become a standard platform for validating and benchmarking various control algorithms. This paper presents a comprehensive and structured review of control strategies applied to TWSBRs, encompassing classical linear approaches such as PID and LQR, modern nonlinear methods including sliding mode control (SMC), model predictive control (MPC), and intelligent techniques such as fuzzy logic, neural networks, and reinforcement learning. Additionally, supporting techniques such as state estimation, observer design, and filtering are discussed in the context of their importance to control implementation. The evolution of control theory is analyzed, and a detailed taxonomy is proposed to classify existing works. Notably, a comparative analysis section is included, offering practical guidelines for selecting suitable control strategies based on system complexity, computational resources, and robustness requirements. This review aims to support both academic research and real-world applications by summarizing key methodologies, identifying open challenges, and highlighting promising directions for future development. Full article

Graphene oxide (GO) aerogels were discovered as lightweight, highly porous materials with exceptional mechanical, electrical, and thermal properties. These properties make them suitable for a wide range of advanced applications. This paper discusses GO aerogel synthesis processes, characterization, mechanical properties, applications, and future directions. The synthesis methods discussed include hydrothermal reduction, chemical reduction, crosslinking methods, and 3D printing, with major emphasis on their effects on the aerogel’s structural and functional attributes. A detailed analysis of mechanical characterization techniques is elaborated upon, along with highlighting the effects of parameters such as porosity, crosslinking, and graphene concentration on mechanical strength, elasticity, and stability. Research has been carried out to find GO aerogel applications in various sectors, such as energy storage, environmental remediation, sensors, and thermal management, showcasing their versatility and potential. Additionally, the combination of nanoparticles and doping strategies to improve specific properties is addressed. The review concludes by identifying current challenges in scalability, brittleness, and property optimization and proposes future directions for synthesis innovations. This work will be helpful for researchers and engineers exploring new possibilities for GO aerogels in both academic and industrial areas. Full article

Selective Mutism (SM) is a childhood anxiety disorder characterized by the persistent inability to speak in specific social settings while being able to speak freely in more comfortable environments, such as at home with family. This condition often leads to significant impairments in social, academic, and occupational functions. This article presents a novel treatment methodology that integrates the physiology of vocal production with pragmatic language instruction through teletherapy, administered to two adolescents diagnosed with selective mutism (SM). The frequency of speaking on the Selective Mutism Questionnaire increased from 35% to 86% and from 25% to 55% for the two children. Pragmatic language skills on the Social Communication Skills: Pragmatics Checklist improved from 47% to 96% and 13% to 40% after treatment. It is crucial to emphasize vocal control for speech initiation and pragmatic language for verbal expression. Detailed strategies, specific activities, and treatment outcomes are provided. Full article

Background/Objectives: This study examines the academic discourse surrounding Critical Incident Stress Debriefing (CISD) and Critical Incident Stress Management (CISM) for first responders using Latent Dirichlet Allocation (LDA) topic modeling. It aims to uncover latent topical structures in the literature and critically evaluate assumptions to identify gaps and limitations. Methods: A corpus of 214 research article abstracts related to CISD/M was gathered from the Web of Science Core Collection. After preprocessing, we used Orange Data Mining software’s LDA tool to analyze the corpus. We tested models ranging from 2 to 10 topics. To guide interpretation and labeling, we evaluated them using log perplexity, topic coherence, and LDAvis visualizations. A four-topic model offered the best balance of detail and interpretability. Results: Four topics emerged: (1) Critical Incident Stress Management in medical and emergency settings, (2) psychological and group-based interventions for PTSD and trauma, (3) peer support and experiences of emergency and military personnel, and (4) mental health interventions for first responders. Key gaps included limited focus on cumulative trauma, insufficient longitudinal research, and variability in procedural adherence affecting outcomes. Conclusions: The findings highlight the need for CISD/M protocols to move beyond event-specific interventions and address cumulative stressors. Recommendations include incorporating holistic, proactive mental health strategies and conducting longitudinal studies to evaluate long-term effectiveness. These insights can help refine CISD/M approaches and enhance their impact on first responders working in high-stress environments. Full article

Exploring the causes of the concave curved form of the roofs in traditional Chinese architecture is key to understanding its unique esthetics and structural logic. Regarding its causes, the academic community offers various explanations, including esthetics and function, but research that delves deeply into specific construction techniques and material limitations and systematically explains how they lead to the precise roof forms is relatively insufficient, which limits our comprehensive understanding of the deep generative logic of this unique form. This study aimed to bridge this gap by systematically exploring the causes of the concave curved form of roofs in traditional Chinese architecture (such as flying eaves, upturned corners, and Ju zhe) from the perspective of construction technology. Through a systematic review of historical literature (especially Yingzao fashi (Treatise on Architectural Methods)); the empirical investigation and analysis of typical architectural examples; detailed research on the structural practices, material properties (especially the creep behavior of timber), and construction techniques of key timber components such as flying rafters, hip rafters, and rafters; and mechanical principles and computational simulation, this study found that the concave curved forms of different parts of the roof, such as the eaves (flying rafters), corners (corner upturn), and main body (Ju zhe), are not purely esthetic choices but are, to a large extent, technical responses or inevitable results stemming from objective construction constraints of the time, including limitations on timber length, component connection methods, structural load distribution, and long-term deformation. Based on these findings, this study proposes the concept of “Passive Form” to summarize this form-generation mechanism, emphasizing that architectural forms are not solely determined by subjective will but are rooted in the adaptation and transformation of real constraints in construction, providing a technical perspective rooted in practice for understanding the forms of Chinese traditional architecture. Full article

Personal lifestyle choices contribute up to 75% of national emissions and yet the greenhouse gas (GHG) inventories included in the National Inventory Report (NIR) of Canada provide limited insight on these choices. Better insight can be found using carbon footprint calculators that estimate individual emissions; however, they vary in regard to their input parameters, output data, and calculation methods. This study assessed five calculators, which are popular with the public, or compatibility with the Canadian NIR. A quantitative scoring matrix was developed to assess the output depth, academic proficiency, and effectiveness of the calculators to inform lifestyle changes, alongside NIR alignment. The results showed that the calculator with the overall highest cumulative score across all the comparative criteria was the one offered by Carbon Footprint Ltd. The other calculators that scored highly include CoolClimate Calculator and Carbon Independent. The potential of the calculators in regard to informing low-carbon lifestyles can be improved through the incorporation of more depth in terms of capturing the purchase information of goods and services and providing detailed secondary information to users, including mitigation strategies and carbon offset options. The main driver of incompatibility between the calculator tools and the NIR was the different approaches taken to the emissions inventory, with the NIR using a territorial framework and the calculators being consumption driven. The outcomes of this study demonstrate a global need for the evolution of NIR structuring to increase its relatability with citizens and for the improved standardization of publicly available tools. Full article

The increasing demand for critical raw materials, such as antimony—a semimetal with strategic relevance in fire-retardant applications, electronic components, and national security—has made the identification of European sources essential for the European Union’s strategic autonomy. Remote sensing offers a valuable tool for detecting alteration minerals associated with subsurface gold and antimony deposits that reach the surface. However, the coarse spatial resolution of the most freely available satellite data remains a limiting factor. The PlanetScope satellite constellation presents a promising low-cost alternative for the academic community, providing 3 m spatial resolution and eight spectral bands. In this study, we evaluated PlanetScope’s capacity to detect Fe³⁺-bearing iron oxides—key indicators of hydrothermal alteration—by applying targeted band ratios (BRs) in northern Portugal. A comparative analysis was conducted to validate its performance using established BRs from Sentinel-2, ASTER, and Landsat 9. The results were assessed through relative comparison methods, enabling both quantitative and qualitative evaluation of the spectral similarity among sensors. Spatial patterns were analyzed, and points of interest were identified and subsequently validated through fieldwork. Our findings demonstrate that PlanetScope is a viable option for mineral exploration applications, capable of detecting iron oxide anomalies associated with alteration zones while offering finer spatial detail than most freely accessible satellites. Full article

Modern financial practices introduce complex risks, which in turn force financial institutions to rely increasingly on computational risk analytics (CRA). The purpose of our research is to attempt to systematically explore the evolution and intellectual structure of CRA in banking using a detailed bibliometric analysis of the literature sourced from Web of Science from 2000 to 2025. A comprehensive search in the Web of Science (WoS) Core Collection yielded 1083 peer-reviewed publications, which we analyzed using analytical tools like VOSviewer 1.6.20 and Bibliometrix (Biblioshiny 5.0) so as to examine the dataset and uncover bibliometric characteristics like citation patterns, keyword occurrences, and thematic clustering. Our initial analysis results uncover the presence of key research clusters focusing on bankruptcy prediction, AI integration in financial services, and advanced deep learning applications. Furthermore, our findings note a transition of CRA from an emerging to an expanding domain, especially after 2019, with terms like machine learning (ML), artificial intelligence (AI), and deep learning (DL) being identified as prominent keywords and a recent shift towards blockchain, explainability, and financial stability being present. We believe that this study tries to address the need for an updated mapping of CRA, providing valuable insights for future academic inquiry and practical financial risk management applications. Full article

This article presents an empirical evaluation of the technical and economic performance of a building-integrated photovoltaic (PV) system implemented at the Faculty of Architecture and Urbanism of the University of Cuenca, Ecuador. This study explores both stages of deployment, beginning with a 7.7 kWp pilot system and later scaling to a full 75.6 kWp configuration. This hourly monitoring of power exchanges with utility was conducted over several months using high-resolution instrumentation and cloud-based analytics platforms. A detailed comparison between projected energy output, recorded production, and real energy consumption was carried out, revealing how seasonal variability, cloud cover, and academic schedules influence system behavior. The findings also include a comparison between billed and actual electricity prices, as well as an analysis of the system’s payback period under different cost scenarios, including state-subsidized and real-cost frameworks. The results confirm that energy exports are frequent during weekends and that daily generation often exceeds on-site demand on non-working days. Although the university benefits from low electricity tariffs, the system demonstrates financial feasibility when broader public cost structures are considered. This study highlights operational outcomes under real-use conditions and provides insights for scaling distributed generation in institutional settings, with particular relevance for Andean urban contexts with similar solar profiles and tariff structures. Full article

Assessing building fire safety risks during the early design phase is vital for developing practical solutions to minimize loss of life and property. This study aims to identify research trends and provide a guiding framework for researchers by systematically reviewing the literature on integrating machine learning-based predictive methods into building fire safety design using bibliometric methods. This study evaluates machine learning applications in fire safety using a comprehensive approach that combines bibliometric and content analysis methods. For this purpose, as a result of the scan without any year limitation from the Web of Science Core Collection-Citation database, 250 publications, the first of which was published in 2001, and the number has increased since 2019, were reached, and sample analysis was performed. In order to evaluate the contribution of qualified publications to science more accurately, citation counts were analyzed using normalized citation counts that balanced differences in publication fields and publication years. Multiple regression analysis was applied to support this metric’s theoretical basis and determine the impact levels of variables affecting the metric’s value (such as total citation count, publication year, and number of articles). Thus, the statistical impact of factors influencing the formation of the normalized citation count was measured, and the validity of the approach used was tested. The research categories included evacuation and emergency management, fire detection, and early warning systems, fire dynamics and spread prediction, fire load, and material risk analysis, intelligent systems and cyber security, fire prediction, and risk assessment. Convolutional neural networks, artificial neural networks, support vector machines, deep neural networks, you only look once, deep learning, and decision trees were prominent as machine learning categories. As a result, detailed literature was presented to define the academic publication profile of the research area, determine research fronts, detect emerging trends, and reveal sub-themes. Full article

We introduce a novel technique for the sonification/auditory representation of a 12-lead electrocardiogram (ECG), the standard diagnostic method for the detection of ST elevation myocardial infarction (STEMI). Our approach to ST elevation sonification conveys the detailed variation of the ST segment to enable differentiated, correct interpretation and severity without consulting a visual display. We present a variety of novel sonification designs and discuss their benefits and limitations. As part of an emergency training program, a cohort of 44 medical students (5th academic year) participated in a classification study in which the diagnostic accuracy of the participants was determined with regard to audibly presented ECG sequences of different STEMI severity levels. Regarding the classification of sonified ECG sequences, the discrimination of isoelectricity (IE, the healthy class) from all other (STEMI) classes combined yielded a perfect classification of all 660 classification instances (sensitivity = specificity = 1). With respect to the individual classification of all five classes (IE, inferior/anterior, and moderate/severe STEMI), an overall accuracy of 0.82 (0.79, 0.85) and an intraclass coefficient of $\kappa =0.77$ were estimated. Full article