Search Results (1,451)

Lesbian, Gay, Bisexual, Transgender, Questioning, or Queer (LGBTQ) students with disabilities face unique challenges in the educational environment, and educators must provide support based on intersectionality. However, research on LGBTQ students in special needs education is limited, and the extent of educators’ awareness and support is not well documented. Therefore, this study explored the awareness, knowledge, and support practices of special needs school educators regarding LGBTQ students. We conducted a nationwide survey of educators in special needs schools in Japan, and 2024 valid responses were analyzed using multiple correspondence and cluster analyses. The results revealed that many educators lacked an understanding of basic LGBTQ terminology and may have been unaware of their discriminatory behaviors. Additionally, most educators had never encountered LGBTQ students with disabilities, potentially hindering these students’ opportunities to seek support. Furthermore, educators who had received LGBTQ training reported higher awareness and being more proactive in supporting LGBTQ students than those who had not. Thus, training may be associated with support-related attitudes. This highlights the need for ongoing training programs that address LGBTQ identity and disability, considering their intersectionality. These preliminary findings suggest the potential for creating an inclusive environment for LGBTQ students with disabilities; nevertheless, structural barriers remain. Full article

Background/Objectives: Historically, echocardiographic imaging of the right heart has been challenging because its abnormal geometry is not conducive to reproducible anatomical and functional assessment. With the development of advanced echocardiographic techniques, it is now possible to complete an integrated assessment of the right heart that has fewer assumptions, resulting in increased accuracy and precision. Echocardiography continues to be the first-line imaging modality for diagnostic analysis and the management of acute and chronic right heart failure because of its portability, versatility, and affordability compared to cardiac computed tomography, magnetic resonance imaging, nuclear scintigraphy, and positron emission tomography. Virtually all echocardiographic parameters have been well-validated and have demonstrated prognostic significance. The goal of this narrative review of the echocardiographic parameters of the right heart chambers and hemodynamic alterations associated with right ventricular dysfunction is to present information that must be acquired during each examination to deliver a comprehensive assessment of the right heart and to discuss their clinical significance in right heart failure. Methods: Using a literature search in the PubMed database from 1985 to 2025 and the Cochrane database, which included but was not limited to terminology that are descriptive of right heart anatomy and function, disease states involving acute and chronic right heart failure and pulmonary hypertension, and the application of conventional and advanced echocardiographic modalities that strive to elucidate the pathophysiology of right heart failure, we reviewed randomized control trials, observational retrospective and prospective cohort studies, societal guidelines, and systematic review articles. Conclusions: In addition to the conventional 2-dimensional echocardiography and color, spectral, and tissue Doppler measurements, a contemporary echocardiographic assessment of a patient with suspected or proven right heart failure must include 3-dimensional echocardiographic-derived measurements, speckle-tracking echocardiography strain analysis, and hemodynamics parameters to not only characterize the right heart anatomy but to also determine the underlying pathophysiology of right heart failure. Complete and point-of-care echocardiography is available in virtually all clinical settings for routine care, but this imaging tool is particularly indispensable in the emergency department, intensive care units, and operating room, where it can provide an immediate assessment of right ventricular function and associated hemodynamic changes to assist with real-time management decisions. Full article

The continuous advancement of fire protection technologies has necessitated the development of comprehensive safety standards, leading to an increasingly diversified and specialized regulatory landscape. This has made it difficult for fire protection professionals to quickly and accurately locate the required fire safety standard information. In addition, the lack of effective integration and knowledge organization concerning fire safety standard entities has led to the severe fragmentation of fire safety standard information and the absence of a comprehensive “one map”. To address this challenge, we introduce FT-FLAT, an innovative CNN–Transformer fusion architecture designed specifically for fire safety standard entity extraction. Unlike traditional methods that rely on rules or single-modality deep learning, our approach integrates TextCNN for local feature extraction and combines it with the Flat-Lattice Transformer for global dependency modeling. The key innovations include the following. (1) Relative Position Embedding (RPE) dynamically encodes the positional relationships between spans in fire safety texts, addressing the limitations of absolute positional encoding in hierarchical structures. (2) The Multi-Branch Prediction Head (MBPH) aggregates the outputs of TextCNN and the Transformer using Einstein summation, enhancing the feature learning capabilities and improving the robustness for domain-specific terminology. (3) Experiments conducted on the newly annotated Fire Safety Standard Entity Recognition Dataset (FSSERD) demonstrate state-of-the-art performance (94.24% accuracy, 83.20% precision). This work provides a scalable solution for constructing fire safety knowledge graphs and supports intelligent information retrieval in emergency situations. Full article

Cyber threat intelligence summarization plays a critical role in enhancing threat awareness and operational response in cybersecurity. However, existing summarization models often fail to capture essential threat elements due to the unstructured nature of cyber threat intelligence documents and the lack of domain-specific knowledge. This paper presents a knowledge-guided cyber threat intelligence summarization framework via term-oriented input construction, designed to improve summary fidelity, semantic relevance, and model robustness. The proposed approach consists of two key components: a hybrid term construction pipeline that combines unsupervised keyword extraction and supervised term generation with rule-based refinement, and a knowledge-injected input construction paradigm that explicitly incorporates structured terms into the model input. This strategy enhances the model’s understanding of critical threat semantics without altering its architecture. Extensive experiments conducted on cyber threat intelligence summarization benchmarks under both zero-shot and supervised settings demonstrate that the proposed method consistently improves summarization performance across different models, offering strong generalization and deployment flexibility. Full article

Background and Clinical Significance: Blue nevi are a dubious pigmented lesion. While somewhat common throughout the population, they are significantly less common than other melanocytic neoplasms, and both their morphology and development bring them closer to true hamartomas than neoplasms. An exceedingly rare occurrence is the development of melanoma from a preexisting blue nevus. This nosological unit, defined as melanoma arising in a blue nevus, also known as malignant blue nevus, blue naevus–like melanoma, melanoma ex-blue naevus, and melanoma mimicking cellular blue naevus, is required to either originate from an area of previously excised blue nevus or have a blue nevus remnant adjacent to it. Due to the spindle cell morphology of melanoma arising in blue nevus, the terminology is often misused by some authors to include spindle cell melanomas, which exhibit a distinct pathogenesis and, although morphologically similar, have differing molecular profiles as well. Case presentations: The following manuscript discusses comparative morphological features in a case series of blue nevi and melanoma arising in blue nevi. Discussion: Blue nevi present with unique morphological features, with melanomas originating from them having a unique molecular pathology profile, which significantly differs from other cutaneous melanomas and is closer to that of uveal melanomas. Full article

The need for systems that forecast and respond proactively to meteorological disasters is growing amid climate variability. Although the early warning system in South Korea includes countermeasure information, it remains limited in terms of data recency, granularity, and regional adaptability. Additionally, its closed architecture hinders interoperability with external systems. This study aims to redesign the countermeasure function as an independent cloud-based platform grounded in the common standard terminology framework in South Korea. A multi-dimensional data model was developed using attributes such as crop type, cultivation characteristics, growth stage, disaster type, and risk level. The platform incorporates user-specific customization features and history tracking capabilities, and it is structured using a microservices architecture to ensure modularity and scalability. The proposed system enables real-time management and dissemination of localized countermeasure suggestions tailored to various user types, including central and local governments and farmers. This study offers a practical model for enhancing the precision and applicability of agrometeorological response information. It is expected to serve as a scalable reference platform for future integration with external agricultural information systems. Full article

Healthy food service guidelines (HFSG) comprise food, nutrition, behavioral design, and other standards to guide the purchasing, preparation, and offering of foods and beverages in worksites and institutional food service. To date, there have been few attempts to synthesize evidence for HFSG effectiveness in non-K-12 or early childhood education sectors, particularly at worksites and institutional food services. We conducted a scoping review to achieve the following: (1) characterize the existing literature on the effectiveness of HFSG for improving the institution’s food environment, financial outcomes, and consumers’ diet quality and health, and (2) identify gaps in the literature. The initial search in PubMed and Web of Science retrieved 10,358 articles; after screening and snowball searching, 68 articles were included for analysis. Studies varied in terms of HFSG implementation settings, venues, and outcomes in both U.S. (n = 34) and non-U.S. (n = 34) contexts. The majority of HFSG interventions occurred in venues where food is sold (e.g., worksite cafeterias, vending machines). A diversity of HFSG terminology and measurement tools demonstrates the literature’s breadth. Literature gaps include quasi-experimental study designs, as well as interventions in settings that serve dependent populations (e.g., universities, elderly feeding programs, and prisons). Full article

As cyberattacks continue to rise in frequency and sophistication, extracting actionable Cyber Threat Intelligence (CTI) from diverse online sources has become critical for proactive threat detection and defense. However, accurately identifying complex entities from lengthy and heterogeneous threat reports remains challenging due to long-range dependencies and domain-specific terminology. To address this, we propose XLNet-CRF, a hybrid framework that combines permutation-based language modeling with structured prediction using Conditional Random Fields (CRF) to enhance Named Entity Recognition (NER) in cybersecurity contexts. XLNet-CRF directly addresses key challenges in CTI-NER by modeling bidirectional dependencies and capturing non-contiguous semantic patterns more effectively than traditional approaches. Comprehensive evaluations on two benchmark cybersecurity corpora validate the efficacy of our approach. On the CTI-Reports dataset, XLNet-CRF achieves a precision of 97.41% and an F1-score of 97.43%; on MalwareTextDB, it attains a precision of 85.33% and an F1-score of 88.65%—significantly surpassing strong BERT-based baselines in both accuracy and robustness. Full article

Modern heritage (MH) is a key component of our built environment; however, it currently lacks widespread recognition and a clear, universally accepted definition, placing it in an emerging phase. This category of heritage, understood within the context of modernisation processes and the changes characteristic of the late modern period, remains underrepresented and warrants further study. The objective of this article is to fill the identified research gap, thereby fostering awareness of MH, improving its accessibility and enhancing its visibility and appreciation. It offers a diagnostic analysis of the corpus on MH through the design and development of a concrete methodology, which is transferable to the other heritage categories. This study reveals insights into the present understanding of the term ‘Modern Heritage’ and its relevance within an international framework. This understanding prompts a reflection on the terminology used to describe this concept, which serves not only as a significant result in itself but also as a foundation for future research. Despite the close association of modern heritage with the 20th century, this research identifies a cross-cutting nature that needs to be recognised, encompassing a wide range of periods, themes and typologies in this category. Full article

Background: As part of different navigational bronchoscopy (NVB) modalities, radial-probe endobronchial ultrasound (rEBUS) is used to confirm the peribronchial localization of peripheral pulmonary nodules (PPNs) immediately before collecting samples for histopathological analysis. Methods: This retrospective case series study presents the results of en bloc cryobiopsy of PPNs using a flexible 1.1-mm cryoprobe with different NVB modalities. For PPNs classified as adjacent or eccentric lesions by rEBUS (ES-rEBUS), the cryoprobe’s position was adjusted by 90–180° in relation to the ultrasound image of the lesion during the first and second biopsies. Results: All patients with a final histopathologically confirmed diagnosis of PPNs had positive rEBUS findings, regardless of the navigation modality, eccentric (18/42 patients, 43%) and concentric (24/42 patients, 57%) rEBUS view. In 5 out of 6 patients without a histopathological diagnosis, PPNs were not visualized by radial ultrasound. In the (ES-rEBUS) group of patients, 4 out of 18 had fewer than three biopsy samples collected per procedure, which means only an adjusted probe position has been applied, although diagnostic outcomes were achieved. Common Terminology Criteria for Adverse Events (CTCAE) grade 2 complications were reported in 10.4% of the patients, and grade 3 complications in 2% of the patients. Conclusions: Confirming the localization of nodules by rEBUS and properly adjusting the cryoprobe immediately before cryobiopsy of PPNs resulted in a diagnostic yield meeting the literature standards. Full article

Medieval and modern readers of Johannes de Hauvilla’s late XII-century Latin poem Architrenius have proposed an array of discordant interpretations of the eponymous protagonist. This paper offers a historical profile of the critical reception of this peculiar fictional character, tracing responses from the Middle Ages to the present day. Given the poem’s limited dissemination and the modest critical attention it has received in modern times, it is possible to provide a nearly comprehensive overview of the reception history of the Architrenius. We analyze and classify the terminology and the argumentative strategies used by critics in constructing their portrait of the hero of Johannes’ poem and observe how these choices interact with the overall critical assessment of the Architrenius. Our analysis identifies two principal families of readers—both philologically and thematically—suggesting a dual trajectory in the reception of the poem throughout the centuries. Full article

The large language model (LLM) has significant potential for application in the field of electricity markets, but there are shortcomings in professional evaluation methods for LLM: single task, limited dataset coverage, and lack of depth. To this end, this article proposes the ELM-Bench framework for evaluating the LLM of the Chinese electricity market, which evaluates the model from 3 dimensions of understanding, generation, and safety through 7 tasks (such as common-sense Q&A and terminology explanations) with 2841 samples. At the same time, a specialized domain model QwenGOLD was fine-tuned based on the general LLM. The evaluation results show that the top-level general model performs well in general tasks due to high-quality pre-training, while QwenGOLD performs better in tasks such as prediction and decision-making in professional fields, verifying the effectiveness of domain fine-tuning. The study also found that fine-tuning has limited improvement on LLM’s basic abilities, but its score in professional prediction tasks is second only to Deepseek-V3, indicating that some general LLMs can handle domain data well without professional training. This can provide a basis for model selection in different scenarios, balancing performance and training costs. Full article

The lack of precise definitions in plastics-related terminology continues to hinder the development of coherent sustainability strategies across the materials value chain. This communication revisits current definitions of plastics, polymers, and bioplastics, distinguishing between source (bio-based vs. fossil-based), structure (synthetic vs. natural polymer), and degradation behaviour (persistent vs. compostable or biodegradable). It critiques ambiguous classifications promoted in policy and marketing discourse. It introduces the concept of “Zero-Trace Plastic” (ZTP) to refer to materials that are non-plastic substitutes intended for versatile plastic-like uses while guaranteeing no trace of synthetic plastics in their composition and no contribution to pollution across their lifecycle. The ZTPframework prioritises complete mineralisation without plastic or microplastics or chemical residues under real-world conditions. ZTP is proposed not as a replacement for existing biodegradability standards, but it helps distinguish between plastic and non-plastic biopolymers and works as a complementary benchmark for biodegradability that aligns with and extends them by incorporating environmental specificity and system-wide traceability. The paper proposes a harmonised terminology matrix and calls for coordinated efforts by international agencies and standardisation institutes, national bodies and industries to avoid using misleading terminologies like bioplastics, often used for greenwashing and to enhance circular material strategies. Full article

The growing number of daylighting metrics—often overlapping in scope or terminology—combined with the need for prior familiarization to interpret and apply them effectively, has created a barrier to their adoption beyond academic settings. Consequently, this study analyzes a representative set of established and emerging daylighting metrics to evaluate applicability, synergies, and limitations. Particular attention is given to their implications for occupant health, well-being, performance, and energy use, especially within the context of sensorless smart control systems. A virtual room model was simulated using DaySim 3.1 in two contrasting climates—Seville and London—with varying window-to-wall ratios, orientations, and occupancy schedules. The results show that no single metric provides a comprehensive daylighting assessment, highlighting the need for combined approaches. Daylighting Autonomy (DA) proved useful for task illumination, while Useful Daylight Illuminance (UDI) helped identify areas prone to excessive solar exposure. Spatial metrics such as Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE) offer an overview but lack necessary granularity. Circadian Stimulus Autonomy (CSA) appears promising for evaluating circadian entrainment, though its underlying models remain under refinement. Continuous Overcast Daylight Autonomy (DAo.con) shows the potential for sensorless lighting control when adjusted for orientation. A nuanced, multi-metric approach is therefore recommended. Full article

The growing demand for accurate and efficient Chest X-Ray (CXR) interpretation has prompted the development of AI-driven systems to alleviate radiologist workload and reduce diagnostic variability. This paper introduces the Intelligent Humanized Radiology Analysis System (IHRAS), a modular framework that automates the end-to-end process of CXR analysis and report generation. IHRAS integrates four core components: (i) deep convolutional neural networks for multi-label classification of 14 thoracic conditions; (ii) Grad-CAM for spatial visualization of pathologies; (iii) SAR-Net for anatomical segmentation; and (iv) a large language model (DeepSeek-R1) guided by the CRISPE prompt engineering framework to generate structured diagnostic reports using SNOMED CT terminology. Evaluated on the NIH ChestX-ray dataset, IHRAS demonstrates consistent diagnostic performance across diverse demographic and clinical subgroups, and produces high-fidelity, clinically relevant radiological reports with strong faithfulness, relevancy, and alignment scores. The system offers a transparent and scalable solution to support radiological workflows while highlighting the importance of interpretability and standardization in clinical Artificial Intelligence applications. Full article