Search Results (7,352)

Maieutics is a remarkable method for discovering new insights through deep dialogue. Defined as “relating to or resembling the Socratic method of eliciting new ideas from another”, the term originates from the Greek word for “midwifery”—as noted in the Merriam-Webster Dictionary. Recently, maieutics has gained renewed relevance in advanced discussions about artificial intelligence, the nature of the mind, and scientific inquiry. This contribution presents a real and extended dialogue, illustrating the power of the maieutic method in addressing key developments in the field of Automatic Control. Over the past 40 years, the authors have followed a unique intellectual path shaped by this method. Inspired by recent research, they have also applied maieutics in interaction with AI systems—particularly ChatGPT. This experiment aimed to replicate, in a condensed timeframe, the long intellectual journey taken over decades. The preliminary results suggest that although AI systems can retrieve historical information, they struggle to capture the deeper, guiding principles of this journey. The authors also identify a significant concern: while the maieutic approach with ChatGPT can serve as a valuable educational tool, it must be complemented by a strong knowledge of dynamical systems leading to innovative paradigms of learning. Full article

In developing countries, indoor air pollution in rural areas is often attributed to the use of solid biomass fuels for cooking. Such fuels generate particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO₂), polyaromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs). PM created from biomass combustion is a pollutant particularly damaging to health. This rigorous study employed a personal sampling device and multi-stage cascade impactor to collect airborne PM (including PM_2.5) and deposited ash from 20 real-world kitchen microenvironments. A robust analysis of the PM was undertaken using a range of morphological, physical, and chemical techniques, the results of which were then compared to a controlled burn experiment. Results revealed that airborne PM was predominantly carbon (~85%), with the OC/EC ratio varying between 1.17 and 11.5. Particles were primarily spherical nanoparticles (50–100 nm) capable of deep penetration into the human respiratory tract (HRT). This is the first systematic characterisation of biomass cooking emissions in authentic rural kitchen settings, linking particle morphology, chemistry and toxicology at health-relevant scales. Toxic heavy metals like Cr, Pb, Cd, Zn, and Hg were detected in PM, while ash was dominated by crustal elements such as Ca, Mg and P. VOCs comprised benzene derivatives, esters, ethers, ketones, tetramethysilanes (TMS), and nitrogen-, phosphorus- and sulphur-containing compounds. This research showcases a unique collection technique that gathered particles indicative of their potential for penetration and deposition in the HRT. Impact stems from the close link between the physico-chemical properties of particle emissions and their environmental and epidemiological effects. By providing a critical evidence base for exposure modelling, risk assessment and clean cooking interventions, this study delivers internationally significant insights. Our methodological innovation, capturing respirable nanoparticles under real-world conditions, offers a transferable framework for indoor air quality research across low- and middle-income countries. The findings therefore advance both fundamental understanding of combustion-derived nanoparticle behaviour and practical knowledge to inform public health, environmental policy, and the UN Sustainable Development Goals. Full article

Background/Objective: Oropouche virus (OROV—Orthobunyvirus oropoucheense) is a neglected arbovirus endemic to parts of Latin America, particularly the Brazilian Amazon. Despite its increasing epidemiological relevance, little is known about healthcare professionals’ awareness and preparedness regarding the virus. Methods: A cross-sectional, questionnaire-based study was conducted between February 2024 and March 2025 with 760 healthcare professionals across 21 Brazilian states. Participants represented various professional categories, including nursing, medicine, pharmacy, and biomedical sciences. The survey assessed knowledge on OROV epidemiology, clinical recognition, diagnostic practices, and compulsory notification. Results: Among participants, 37.4% had never heard of OROV, and 38.0% had heard of it but knew little about it. Most professionals first learned about the virus within the past year (31.8%). The majority (86.1%) reported not having received information about OROV during undergraduate education. Only 21.9% knew which diagnostic test to request, and 64.7% were aware that OROV is subject to mandatory notification. Notably, 71.2% were unaware of the virus’s potential neurological complications. Conclusions: These findings reveal a significant gap in the education and training of healthcare professionals regarding OROV, even in endemic areas. The results underscore the need for curricular reform, expanded continuing education, and stronger integration of OROV into national epidemiological surveillance efforts. Full article

As academic institutions expand, the proliferation of laboratories dealing with hazardous chemicals has risen. While the physicochemical characterization equipment employed in these academic chemical laboratories is widely recognized, its usage presents a notable risk to researchers at various levels. This paper presents a simplified approach for evaluating the effects of the implementation of prevention investments in regard to working with nanomaterials on a lab scale. The evaluation is based on modeling the benefits (avoided accident costs) and costs (safety training), as opposed to an alternative (not investing in safety training). Each scenario analyzed in the economic evaluation reflects a different level of risk. The novelty of this study lies in its objective to provide an economic assessment of the benefits and returns from safety investments—specifically training—in a chemical laboratory, using a framework that integrates qualitative insights to explore and define the context alongside quantitative data derived from a cost–benefit analysis. The Net Present Value (NPV) was evaluated. The results of the cost–benefit analysis demonstrated that the benefits exceed the cost of the investment. The findings from the sensitivity analysis highlight the significant influence of insurance benefits on safety investments in the specific case study. In this case study, the deterministic analysis yielded a Net Present Value (NPV) of €280,414.67, which aligns closely with the probabilistic results. The probabilistic NPV indicates 90% confidence that the investment will yield a positive NPV ranging from €283,053 to €337,356. The cost–benefit analysis results demonstrate that the benefits outweigh the costs, showing that with an 87% training success rate, this investment would generate benefits of approximately €6328 by preventing accidents in this study. To the best of the researchers’ knowledge, this is the first study to evaluate the influence of safety investment through an economic evaluation of laboratory accidents with small-angle X-ray scattering during the physicochemical characterization process of engineered nanomaterials. The proposed approach and framework are relevant not only to academic settings but also to industry. Full article

The European e-Competence Framework (e-CF) and the European Skills, Competences, Qualifications and Occupations (ESCO) classification are two key initiatives developed by the European Commission to support skills transparency, mobility, and interoperability across labour and education systems. While e-CF defines essential competences for ICT professionals through a structured framework, it provides only a limited number of illustrative skills and knowledge examples for each competence. In contrast, ESCO offers a rich, multilingual taxonomy of skills and knowledge, each accompanied by a detailed description, alternative labels, and links to relevant occupations. This paper explores the possibility of enriching the e-CF framework by linking it to relevant ESCO ICT skills using text embedding (MPNet) and cosine similarity. This approach allows the extension to 15–25 semantically aligned skills and knowledge items per competence in e-CF, all with full description and officially translated into all EU languages, instead of the present amount of 4–10 brief examples. This significantly improves the clarity, usability, and interpretability of e-CF competences for the various stakeholders. Furthermore, since ESCO terminology serves as the foundation for labour market analysis across the EU, establishing this linkage provides a valuable bridge between the e-CF competence model and real-time labour market intelligence, a connection not available now. The results of this study offer practical insights into the application of semantic technologies to the enhancement and mutual alignment of European ICT skills frameworks. Full article

Background and Clinical Significance: Triosephosphate isomerase (TPI) deficiency is a rare autosomal recessive metabolic disorder caused by a pathogenic variant in the TPI1 gene. It is characterised by chronic haemolytic anaemia, progressive neuromuscular dysfunction, and reduced life expectancy. Patients typically present with symptoms in the first few months of life, including muscle weakness, ataxia, and recurrent respiratory infections. Diagnosis is confirmed by genetic testing, and management is generally symptomatic as no treatment is available. Case Presentation: We describe the case of an infant diagnosed with TPI deficiency in the context of haemolytic anaemia with progressive neurological deterioration and respiratory failure. Conclusions: This case illustrates the complexity of the disease and highlights the importance of early diagnosis and contributes to the limited literature by providing a detailed clinical description and highlighting the diagnostic challenges associated with this condition. Beyond its clinical relevance, this report emphasises the potential role of personalised medicine in the management of TPI deficiency. Early identification of specific genotypes may inform prognosis and guide individualised supportive strategies. As knowledge of the molecular underpinnings of TPI deficiency expands, opportunities may emerge for targeted therapeutic approaches tailored to patient-specific characteristics. Full article

Sarcocystosis is a parasitic infection caused by obligate intracellular coccidia, which infect humans, domestic animals, and wildlife. More than 200 Sarcocystis species have already been identified, but for many of these, the life cycle, pathogenesis, and clinical signs remain unclear. The infection is cosmopolitan, with high prevalence in cattle herds worldwide. Although the clinical disease in definitive hosts is considered rare, the high number of sporocysts released by them drives the incidence in production animals. Furthermore, sarcocystosis has some One Health relevance due to its zoonotic potential, especially concerning species infecting primates. Few studies have reported on the epidemiology of sarcocystosis in Brazil. However, a high prevalence of the disease was found in areas where investigations of Sarcocystis species were conducted, which highlights the potential for foodborne transmission to humans. Therefore, it is relevant to study this parasitic disease so that control and prophylaxis measures can be adopted. This study aims to review the current state of knowledge on Sarcocystis spp. in farm animals in Brazil. Full article

With the increasing digitalization and connectivity of transportation systems, there are many opportunities for data-based approaches in transportation planning and management. In this context, data quality management has a special role to play, including the systematic quality assessment of data assets. Data quality is particularly crucial for emerging data that has not yet been widely researched from a quality perspective. Emerging data is often found in Smart Parking Systems (SPSs). Currently, it remains unclear how SPS-generated data can be exploited by potential data consumers, such as municipal parking managers. One reason is the lack of knowledge about the quality of available data sources and the data provided. This paper presents an approach to assessing and defining data quality in the field of on-street parking. It examines relevant quality issues in this field and consolidates the findings into relevant quality indicators. The methodology includes a cross-check analysis of data sources and an inductive taxonomy development. The cross-check analysis provided empirical findings through qualitative analyses of available parking data in Hamburg, Germany, considering various conventional and SPS-based data sources. Based on this, a set of relevant quality criteria and quality metrics was developed. Full article

Background: The craniofacial region is functionally unique, with close interaction between muscles and bones during mastication, speech, and facial expression. Although myokines, muscle-derived signaling molecules, are increasingly being studied in relation to bone metabolism, most studies have focused on limb muscles and long bones. Given the developmental and functional specificity of craniofacial structures, this article aims to map the current evidence on myokines involved in craniofacial bone metabolism and to identify gaps in order to guide future research. Methods: We conducted a literature search in PubMed and Scopus (January 2000–July 2025), combining both free-text keywords and MeSH terms to ensure comprehensive retrieval of relevant articles. Results: Nine articles from the extensive search were included in this review that adhered to the eligibility criteria. The myokines that were reported include interleukin-6, insulin like growth factor-1, and myostatin and irisin. Conclusions: Further research is required into the mechanism by which craniofacial muscle-derived myokines regulate local bone metabolism, as this knowledge could pave the way for novel therapeutic strategies that leverage myokine signaling, which could be applied in the context of orthodontic and orthognathic treatments, maxillofacial reconstruction, or age-related bone loss. Full article

Activated peroxymonosulfate (PMS) processes have emerged as a highly effective advanced oxidation technique for the removal of emerging organic contaminants in water. This study successfully converted δ-MnO₂ into α-MnO₂ through a crystal phase transformation method via the application of a mild water bath heating process, enhancing its catalytic properties. α-MnO₂ (k = 0.092 ± 0.0059 min⁻¹) exhibited significantly higher activity than δ-MnO₂ (k = 0.027 ± 0.0075 min⁻¹) in the PMS-activated degradation of sulfamethoxazole (SMX). Importantly, ¹O₂ was identified as the primary reactive oxygen species in the α-MnO₂ + PMS system for SMX degradation. XPS and O₂-TPD characterizations demonstrated that α-MnO₂ possesses a higher concentration of active lattice oxygen a and lower concentration of Mn(III) than δ-MnO₂. Further analysis reveals that both surface Mn(III) and active lattice oxygen in α-MnO₂ are crucial for PMS activation. Notably, ¹O₂ is predominantly generated through the interaction between PMS and reactive lattice oxygen. Moreover, a heterogeneous PMS activation mechanism toward α-MnO₂ was proposed. This research underscores the critical role of active lattice oxygen in MnO₂ for PMS activation, providing valuable insight relevant to the design of catalysts aimed at pollutant elimination in environmental applications. To the best of our knowledge, our study is the first to report a pathway for MnO₂ crystal phase transition under relatively mild conditions. Full article

The phosphoinositide 3-kinase (PI3K)/AKT signaling pathway is a crucial regulator of cellular metabolism, proliferation, and survival. It is frequently dysregulated in metabolic, cardiovascular, and neoplastic disorders. Despite the advancements in multi-omics technology, existing methods often fail to provide real-time, pathway-specific insights for precision medicine and drug repurposing. We offer Agentic RAG-Driven Multi-Omics Analysis (ARMOA), an autonomous, hypothesis-driven system that integrates retrieval-augmented generation (RAG), large language models (LLMs), and agentic AI to thoroughly analyze genomic, transcriptomic, proteomic, and metabolomic data. Through the use of graph neural networks (GNNs) to model complex interactions within the PI3K/AKT pathway, ARMOA enables the discovery of novel biomarkers, probable candidates for drug repurposing, and customized therapy responses to address the complexities of PI3K/AKT dysregulation in disease states. ARMOA dynamically gathers and synthesizes knowledge from multiple sources, including KEGG, TCGA, and DrugBank, to guarantee context-aware insights. Through adaptive reasoning, it gradually enhances predictions, achieving 91% accuracy in external testing and 92% accuracy in cross-validation. Case studies in breast cancer and type 2 diabetes demonstrate that ARMOA can identify synergistic drug combinations with high clinical relevance and predict therapeutic outcomes specific to each patient. The framework’s interpretability and scalability are greatly enhanced by its use of multi-omics data fusion and real-time hypothesis creation. ARMOA provides a cutting-edge example for precision medicine by integrating multi-omics data, clinical judgment, and AI agents. Its ability to provide valuable insights on its own makes it a powerful tool for advancing biomedical research and treatment development. Full article

LexTALE has emerged as a popular measure of language proficiency in research studies. While it has been widely validated for L2 learners across multiple languages, its applicability to heritage language learners (HLLs)—who often show distinct language development from L2ers—has not been established. Here, we evaluate the Spanish version of LexTALE (LexTALE-Esp) as a predictor of writing proficiency among college-aged HLLs in the United States. We show that LexTALE-Esp scores significantly correlate with ACTFL-rated functional writing levels and outperform self-assessment as a predictor of proficiency. Our results suggest that, despite concerns about HLLs’ limited experience with written texts in the heritage language, vocabulary-based tasks capture core aspects of written language ability. These findings indicate that vocabulary-based tests like LexTALE-Esp capture proficiency-relevant lexical knowledge across speaker profiles and may tap into dimensions of both core and extended language competence. Full article

With the ongoing electrification of vehicles and the resulting demand for higher power densities, drivetrain requirements are becoming increasingly stringent. Shaft-hub connections are particularly affected in terms of both quantity and design, making innovative solutions necessary. A key factor in meeting these requirements is knowledge of the stress state within the contact area. One promising approach is the application of a thin-film-based sensor system directly onto the shaft surface. This enables, for the first time, the direct measurement of contact pressure in the interface, allowing for more precise connection design. To fully exploit the potential of this sensor technology, its influence on the joining process of shaft-hub connections must be investigated. In this study, cylindrical interference-fits were coated with two thin-film systems relevant to the application, followed by joining tests. The resulting damage was analyzed to derive general recommendations for the joining of coated shaft-hub connections. The results show that shrink-fitting enables damage-free joining, provided specific parameters are met, as confirmed by experimental testing and microscopic examination. This not only preserves the integrity of the sensor system but also establishes the prerequisite for potential in situ measurements, thereby laying the foundation for the feasibility of direct load monitoring during operation. Full article

Natural cooling and ventilation have been fundamental principles in vernacular architecture for millennia, shaping sustainable building practices across diverse climatic regions. This paper examines the historical evolution, technological advancements, environmental benefits, and prospects of passive cooling strategies, with a particular focus on wind catchers. Originating in Mesopotamian, Egyptian, Caucasia, and Iranian architectural traditions, these structures have adapted over centuries to maximize air circulation, thermal regulation, and humidity control, ensuring comfortable indoor environments without reliance on mechanical ventilation. This study analyzes traditional wind catcher designs, highlighting their geometric configurations, airflow optimization, and integration with architectural elements such as courtyards and solar chimneys. Through a comparative assessment, this paper contrasts passive cooling systems with modern HVAC technologies, emphasizing their energy neutrality, low-carbon footprint, and long-term sustainability benefits. A SWOT analysis evaluates their strengths, limitations, opportunities for technological integration, and challenges posed by urbanization and regulatory constraints. This study adopts a comparative analytical method, integrating a literature-based approach with qualitative assessments and a SWOT analysis framework to evaluate passive cooling strategies against modern HVAC systems. Methodologically, the research combines historical review, typological classification, and sustainability-driven performance comparisons to derive actionable insights for climate-responsive design. The research is grounded in a comparative assessment of traditional and modern cooling strategies, supported by typological analysis and evaluative frameworks. Looking toward the future, the research explores hybrid adaptations incorporating solar energy, AI-driven airflow control, and retrofitting strategies for smart cities, reinforcing the enduring relevance of vernacular cooling techniques in contemporary architecture. By bridging historical knowledge with innovative solutions, this paper contributes to ongoing discussions on climate-responsive urban planning and sustainable architectural development. Full article

The aging population in Europe and other developed regions is accelerating the demand for adaptable domestic environments that support independent living and care at home. In this context, ontologies offer a promising approach to represent and manage knowledge about built environments, smart technologies, and user needs—especially within Ambient Assisted Living (AAL) systems. This paper presents a systematic literature review examining the role of ontologies in the reconfiguration of domestic living spaces, with a focus on their application in design processes and decision support systems. Following the PRISMA methodology, 14 relevant works published between 2000 and 2025 were identified and analyzed. The review explores key aspects such as ontology conceptualization, reuse, engineering methodologies, integration with CAD systems, and validation practices. The results show that research on this topic is fragmented yet growing, with the first contribution dated 2005 and peaks in 2016, 2018, and 2024. Most works (11) were conference papers, with Europe leading the contributions, particularly Italy. Half of the reviewed ontologies were developed “from scratch”, while the rest relied on conceptualizations such as BIM. Ontology reuse was inconsistent: only 50% of works reused existing models (e.g., SAREF, SOSA, BOT, ifcOWL), and few adopted Ontology Design Patterns. While 11 works followed ontology engineering methodologies—mostly custom or established methods such as Methontology or NeOn—stakeholder collaboration was reported in less than 36% of cases. Validation practices were weak: only six studies presented use cases or demonstrators. Integration with CAD systems remains at a prototypical stage, primarily through semantic enrichment and SWRL-based reasoning layers. Remaining gaps include poor ontology accessibility (few provide URLs or W3IDs), limited FAIR compliance, and scarce modeling of end-user needs, despite their relevance for AAL solutions. The review highlights opportunities for collaborative, human-centered ontology development aligned with architectural and medical standards to enable scalable, interoperable, and user-driven reconfiguration of domestic environments. Full article