Search Results (74)

Background: In healthcare education, understanding and managing cognitive load is crucial for enhancing learning outcomes for students, healthcare professionals, patients, and the general public. Despite numerous studies developing cognitive load classification models, there is a lack of comprehensive guidelines on how to effectively utilize these models in healthcare education. This study reviews cognitive load classification models using physiological data to provide insights and guidelines for their development in healthcare contexts. Methods: A scoping review was conducted on studies published between 2015 and 2024, identified through databases including Scopus, Web of Science, PubMed, EMBASE, and PsycINFO. The search terms included “cognitive load,” “physiology,” “data,” and “classification.” Inclusion criteria were peer-reviewed journal articles in English, focused on the healthcare context, utilizing experimental physiological data, and developing classification models. After screening 351 articles, ten studies met the inclusion criteria and were analyzed in detail. Results: Task design predominantly focused on measuring intrinsic cognitive load by adjusting task difficulty. Data collection mainly utilized EEG (electroencephalogram) and body movement data. SVM (support vector machine) algorithms were the most frequently used for model development, with cross-validation and feature selection employed to prevent overfitting. This study derived the importance of clearly defining cognitive load types, designing appropriate tasks, establishing reliable ground truths with multiple indicators, and selecting contextually relevant data. Conclusions: This study provides a comprehensive analysis of cognitive load classification models using physiological data in healthcare education, offering valuable guidelines for their development. Despite the study’s limitations, including a small number of analyzed papers and limited diversity in educational contexts, it offers critical insights for using and developing cognitive load classification in healthcare education. Future research should explore the applicability of these models across diverse educational settings and populations, aiming to enhance the effectiveness of healthcare education and ultimately improve learning and healthcare outcomes. Full article

This paper examines the philosophy of language in The Platform Sutra of the Sixth Patriarch (六祖壇經), demonstrating its centrality to Zen Buddhism and Buddhist sinicization. The sutra emphasizes the ineffability of ultimate truth (至道無言) and the principle that words falter in encapsulating the Dao (言語道斷), framing language as a provisional “raft” (筏) that must be instrumentalized yet transcended through a dialectic of employing and abandoning (用離辯證). It ontologically grounds this view in Buddha-nature’s (佛性) pre-linguistic essence, advocating transcending reliance on words and letters (不假文字) while strategically deploying language to dismantle its own authority. Historically, this constituted a revolt against Tang scholasticism’s textual fetishism. The text adopts a dynamic dialectic, neither clinging to nor rejecting language, exemplified by Huineng’s awakening through the Diamond Sutra, where recitation catalyzes internal insight. Operationally, it utilizes negational discourse, the “Two Paths Mutually Condition” method (二道相因) embedded in the “Twelve Pairs of Dharmic Forms” (法相語言十二對) in particular, to systematically deconstruct dualisms, while promoting embodied unity of speech, mind, and action (口念心行) to critique empty recitation. Ultimately, the sutra orchestrates language as a self-subverting medium: balancing acknowledgment of its limitations with pragmatic instrumentality, it presents an Eastern paradigm where language actively disrupts conceptual fetters to facilitate direct insight into Buddha-nature, reframing it as a dynamic catalyst for “illuminating the mind and seeing one’s nature” (明心見性). Full article

This article explores the transformative changes in Catholic liturgy during the twentieth century and their implications for the stability of religious meaning and cultural identity in the West. In critical dialogue with Chantal Delsol’s diagnosis of the decline of Christianitas, this study argues that the reform of ritual following the Second Vatican Council, rather than political entanglements, played a decisive role in weakening the public credibility of Catholic truth claims. Drawing on Roy A. Rappaport’s theory of ritual as a stabilizer of cultural meaning, the author analyzes how this postconciliar liturgical reform altered the semiotic structure of Catholic worship—shifting communication from indexical to symbolic forms and reorienting the liturgy from a vertical–concentric order to a more decentralized horizontal dynamic. The chosen method combines theoretical reflection with liturgical anthropology to assess how changes in the Roman Missal, ritual posture, and spatial arrangement disrupted the transmission of canonical messages. The conclusion suggests that this semiotic transformation undermined the liturgy’s capacity to ritually confirm the truths of faith, contributing to the broader civilizational disintegration observed by Delsol. Ultimately, this article contends that any future revitalization of Catholic culture will depend less on political influence and more on recovering the liturgy’s ritual capacity to sustain belief in transcendent truth. Full article

The prediction of anthropometric measurements from 2D body images, particularly for children, remains an under-explored area despite its potential applications in healthcare, fashion, and fitness. While pose estimation and body shape classification have garnered extensive attention, estimating body measurements and body mass index (BMI) from images presents unique challenges and opportunities. This paper provides a comprehensive review of the current methodologies, focusing on deep-learning approaches, both standalone and in combination with traditional machine-learning techniques, for inferring body measurements from facial and full-body images. We discuss the strengths and limitations of commonly used datasets, proposing the need for more inclusive and diverse collections to improve model performance. Our findings indicate that deep-learning models, especially when combined with traditional machine-learning techniques, offer the most accurate predictions. We further highlight the promise of vision transformers in advancing the field while stressing the importance of addressing model explainability. Finally, we evaluate the current state of the field, comparing recent results and focusing on the deviations from ground truth, ultimately providing recommendations for future research directions. Full article

This article examines the contributions of Turkish screenwriter Ayşe Şasa (1941–2014) to Turkish cinema and visual culture through her engagement with Sufism and metaphysical themes. It explores how Şasa draws on esoteric Sufi concepts such as the oneness of being (waḥdat al-wujūd), asceticism (zuhd), and inspiration (ilhām), using cinema as a vehicle for spiritual inquiry and the quest for truth (ḥaqīqa). Her films—including Hear the Reed (Dinle Neyden), The Night That Never Was (Hiçbir Gece), and My Friend the Devil (Arkadaşım Şeytan)—are explored through thematic and interpretive approaches that uncover their Sufi dimensions. The methodological approach combines Gillian Rose’s visual methodology, Klaus Krippendorff’s content analysis, and Arthur Asa Berger’s interpretive model. Rose’s framework facilitates an exploration of symbolic narrative in Şasa’s films and writings, while Krippendorff’s methods identify recurring metaphysical motifs. Berger’s approach uncovers layered meanings in visual and narrative elements. Through narrative structure, symbolic imagery, color, setting, costume, light, and sound, Şasa constructs a spiritually resonant cinematic esthetic that challenges the secular paradigms of modern cinema. Ultimately, this article argues that Şasa develops a distinct cinematic language grounded in Sufi metaphysics, enriching Turkish visual culture with a profound spiritual and moral sensibility. Full article

This paper aims to juxtapose bodhisattvas, awakened beings recognized in various Buddhist traditions and contemporary philosophies, as viewed through different lenses: as personified symbols, idealistic visions, mystical manifestations, naturalized sentient beings, and integral visions. Specific attention is given to the contrasting bodhisattva motivations and ideals articulated in Theravāda and Mahāyāna Buddhism as well as secularized psychospiritual–philosophical Western conceptions in neurophysicalism (naturalized bodhisattva) and participatory spirituality and theory (integral bodhisattva). The paradox of the traditional bodhisattva is to liberate oneself and all sentient beings by ending suffering and to act compassionately while realizing emptiness (Skt., śūnyatā), though with different conceptions undergirding ultimate realization. The paradoxical nature of bodhisattvas is discussed in regard to illusional ideation, moral agency, mystical nature, idealized devotion, and naturalized form. The ethical underpinnings of the traditional Buddhist bodhisattva notions and non-Buddhist ethics of Western bodhisattva conceptions are critically examined. Finally, the Buddhist and secular morals of bodhisattvas are discussed in the context of the moral relativism of the Post-Truth culture in the United States. Full article

Pneumothorax is a critical condition that requires rapid and accurate diagnosis from standard chest radiographs. Identifying and segmenting the location of the pneumothorax are essential for developing an effective treatment plan. nnUNet is a self-configuring, deep learning-based framework for medical image segmentation. Despite adjusting its parameters automatically through data-driven optimization strategies and offering robust feature extraction and segmentation capabilities across diverse datasets, our initial experiments revealed that nnUNet alone struggled to achieve consistently accurate segmentation for pneumothorax, particularly in challenging scenarios where subtle intensity variations and anatomical noise obscure the target regions. This study aims to enhance the accuracy and robustness of pneumothorax segmentation in low-contrast chest radiographs by integrating spatial prior information and attention mechanism into the nnUNet framework. In this study, we introduce the spatial prior contrast adapter (SPCA)-enhanced nnUNet by implementing two modules. First, we integrate an SPCA utilizing the MedSAM foundation model to incorporate spatial prior information of the lung region, effectively guiding the segmentation network to focus on anatomically relevant areas. In the meantime, a probabilistic atlas, which shows the probability of an area prone to pneumothorax, is generated based on the ground truth masks. Both the lung segmentation results and the probabilistic atlas are used as attention maps in nnUNet. Second, we combine the two attention maps as additional input into nnUNet and integrate an attention mechanism into standard nnUNet by using a convolutional block attention module (CBAM). We validate our method by experimenting on the dataset CANDID-PTX, a benchmark dataset representing 19,237 chest radiographs. By introducing spatial awareness and intensity adjustments, the model reduces false positives and improves the precision of boundary delineations, ultimately overcoming many of the limitations associated with low-contrast radiographs. Compared with standard nnUNet, SPCA-enhanced nnUNet achieves an average Dice coefficient of 0.81, which indicates an improvement of standard nnUNet by 15%. This study provides a novel approach toward enhancing the segmentation performance of pneumothorax with low contrast in chest X-ray radiographs. Full article

This paper explores how sound design in the Harry Potter film series shapes the symbolic significance of written words within the magical world. Sound mediates between language and meaning; while characters gain knowledge by reading and seeing, viewers are guided emotionally and thematically by how these written texts are framed through sound. For example, Harry’s magical identity is signalled to viewers through the score long before he fully understands himself—first through music when he speaks to a snake, then more explicitly when he receives his letter from Hogwarts. Throughout the series, characters engage with a wide array of written media—textbooks, letters, newspapers, diaries, maps, and inscriptions—that gradually shift in narrative function, from static props to dynamic, multi-sensory agents of transformation. Using a close analysis of selected scenes to examine layers of utterances, diegetic sounds, underscore, and sound design, this study draws on metaphor theory and adaptation theory to examine how sound design gives writing a metaphorical voice, sometimes framing it as character, landscape, or moral authority. As the series progresses, becoming more autonomous from the literary source, written words take on greater symbolic significance, and sound increasingly determines which texts are granted narrative power, whose voices are trusted, and how viewers interpret truth and agency across media. Ultimately, written words in the films are animated through sound into agents of growth, memory, resistance, and transformation. Thus, the audio-visual treatment of written magic reveals not just what is written, but what matters. Full article

Radiomics, an emerging discipline integrating imaging science, computational biology, and clinical oncology, enables the extraction of quantitative biomarkers from medical images for improved diagnosis and prognosis. However, variability in imaging protocols and insufficient validation studies hinder the clinical reliability of these biomarkers, limiting their integration into precision medicine. This study addresses these challenges by proposing an RW-ensemble method for extracting and validating radiomic features from segmented lung nodules. Using the Lung CT-Diagnosis dataset, which comprises CT images of 61 patients with segmentation annotations, nearly 38 radiomic features were extracted, incorporating texture-based features from the Grey-Level Co-occurrence Matrix (GLCM) and Grey-Level Run Length Matrix (GLRLM), as well as histogram-based features. The extracted features were validated against ground-truth data using Spearman’s correlation coefficient (SCC), demonstrating moderate to strong correlations. These findings confirm the robustness of the RW-ensemble segmentation and reinforce the potential of radiomics in enhancing diagnostic accuracy and guiding therapeutic decisions in precision oncology. Establishing the reliability and reproducibility of these features is crucial for their seamless clinical integration, ultimately advancing the role of radiomics in the diagnosis and treatment of lung adenocarcinoma. Full article

The philosophy of the Huayan school is founded on the dharmadhātu (法界) as its fundamental ontology, embodying the boundless truth of the cosmos and human existence. It seamlessly integrates the philosophical doctrine of the “perfect interpenetration and non-obstruction of Buddhist teachings”, while expounding the vast tenets of “principle (理), phenomena (事), wisdom (智), and practice (行),” all of which are encompassed within the comprehensive framework of the “four stages of faith–understanding–practice–realization (信解行证)”. The idea of “four dharmadhātus” (四法界), which was first systematically formulated by Master Chengguan, is considered one of the core doctrines of Huayan thought. However, contemporary scholarship has yet to provide a thorough elucidation of the relationship between the one true dharmadhātu (一真法界) and the four dharmadhātus, nor has it sufficiently addressed the notion that the four dharmadhātus are not merely a theoretical construct but also a genuine realization—a stage in the practice of spiritual cultivation. This study first explicates the conceptual significance of the four dharmadhātus, then analyzes the Huayan patriarchs’ interpretations of the one true dharmadhātu and the four dharmadhātus. It further explores the path to awakening through the interpenetration and non-obstruction of the four dharmadhātus and highlights the integration between the empirical world and the ideal world of Buddhist teachings. Ultimately, it argues that every realm and every stage within the dharmadhātu is perfectly complete and seamlessly interconnected. Full article

The question of whether ethics is possible without God is a non-issue. While many believe that without God, morality collapses, I contend that the existence or non-existence of God has no bearing on whether ethics is possible, whether moral truths exist, or whether ethical inquiry is viable. Ethics is no more secure within a theistic framework than an atheistic one. I establish this by critically examining Divine Command Theory (DCT) and its variants, including Divine Nature Theory, demonstrating that they fail to provide truthmakers for moral statements, explain moral truths, generate moral knowledge, or serve as a practical guide for ethical decision making. If one seeks a way to justify ethical principles or resolve moral dilemmas, appealing to God does not improve the situation; supernatural explanations, including those invoking divine commands or nature, fail to meet the criteria of explanatory adequacy. I conclude by suggesting a secular approach to ethics—drawing from Ted Schick’s inference to the best action—that does not depend on God’s existence. Ultimately, if moral nihilism is a concern, God’s existence offers no solution. If ethics is possible at all, it is possible regardless of whether God exists. Full article

Vehicle-to-Vehicle (V2V) communications technology offers enhanced road safety, traffic efficiency, and connectivity. In V2V, vehicles cooperate by broadcasting safety messages to quickly detect and avoid dangerous situations on time or to avoid and reduce congestion. However, vehicles might misbehave, creating false information and sharing it with neighboring vehicles, such as, for example, failing to report an observed accident or falsely reporting one when none exists. If other vehicles detect such misbehavior, they can report it. However, false accusations also constitute misbehavior. In disconnected areas with limited infrastructure, the potential for misbehavior increases due to the scarcity of Roadside Units (RSUs) necessary for verifying the truthfulness of communications. In such a situation, identifying malicious behavior using a standard misbehaving management system is ineffective in areas with limited connectivity. This paper presents a novel mechanism, Distributed Reputation for Accurate Misbehavior Reporting (DRAMBR), offering a fully integrated reputation solution that utilizes reputation to enhance the accuracy of the reporting system by identifying misbehavior in rural networks. The system operates in two phases: offline, using the Local Misbehavior Detection Mechanism (LMDM), where vehicles detect misbehavior and store reports locally, and online, where these reports are sent to a central reputation server. DRAMBR aggregates the reports and integrates DBSCAN for clustering spatial and temporal misbehavior reports, Isolation Forest for anomaly detection, and Gaussian Mixture Models for probabilistic classification of reports. Additionally, Random Forest and XGBoost models are combined to improve decision accuracy. DRAMBR distinguishes between honest mistakes, intentional deception, and malicious reporting. Using an existing mechanism, the updated reputation is available even in an offline environment. Through simulations, we evaluate our proposed reputation system’s performance, demonstrating its effectiveness in achieving a reporting accuracy of approximately 98%. The findings highlight the potential of reputation-based strategies to minimize misbehavior and improve the reliability and security of V2V communications, particularly in rural areas with limited infrastructure, ultimately contributing to safer and more reliable transportation systems. Full article

Background: Medical errors are common, and in particular, medication errors are one of the leading causes of morbidity and mortality in healthcare. Nurses must disclose errors to build trust and ensure patient safety despite communication barriers and fear of reprisals. Truthful documentation and better collaboration can improve patient outcomes. Aim: The aim of this study was to assess barriers to error disclosure among nurses in the Kingdom of Saudi Arabia. Methods: A descriptive cross-sectional survey was conducted in the months of June and August 2024 using a convenience sample of 255 nurses at King Fahad Hospital (KFH), Hofuf. A self-administered questionnaire that contained socio-demographic questions, as well as the Barriers to Error Disclosure Assessment (BEDA) tool, was deployed. Results: The majority of the sample were female (92.2%) and Bachelor’s degree holders (80.8%) who had 1–5 or 6–10 years of experience, representing 45.5% and 29.0% of the sample, respectively. When medical errors occur, only 18% of the nurses disclosed them to patients and their families, and 34.5% of the respondents disclosed medical errors to another team of healthcare professionals. The types of barriers to error disclosure were identified as relating to confidence and knowledge barriers, institutional barriers, psychological barriers, and financial concern barriers. The overall barrier score had an average of 63%. The barriers with the highest scores were those relating to psychological barriers (68.2%), followed by institutional barriers (66.5%) and financial concern barriers (64.5%). Conclusions: Targeted interventions are required for addressing the identified specific needs to support healthcare providers, specifically nurses. New regulations and policy changes are crucial for training programs implementation, enhancing safety culture, and tackling job-related insecurities to minimize barriers to error disclosure and ultimately provide better patient care quality. Further investigations may include a different approach, and it is recommended to provide deeper insights into nurse experiences. Full article

As described in several recent studies, the appropriation of the concept “religion 宗教” in modern Japan made “Buddhism 仏教” enter a transformation process that led, ultimately, to the reimagining of its very content; according to historian of religions Isomae Junichi, one of these elements was, for instance, an emphasis on “belief” to the detriment of “practice”. However, in terms of Buddhism’s reframing into the category of “religion”, we should also pay attention to the construction of the idea of “superstition 迷信”, which appears during this time as a concept relative to “belief” or “faith”. Often considered the epitome of this belief-centered version of the dharma, the so-called New Buddhism movement (shinbukkyō undō 新仏教運動) that occurred in the turn of the 20th century played a fundamental role in establishing the concept of “superstition”. This paper focuses on Sakaino Kōyō (境野黄洋 1871–1933), a pioneer of Chinese Buddhist studies in modern Japan and one of the main leaders of the movement. In order to explore the intellectual context that gave birth to such reformist efforts, I explore his ideas during the later 1890s, a period in which he was dedicated to differentiating “belief” from “superstition”. During this time, he emphasized the eradication of “superstition”, arguing that it constituted an unsound element both socially and intellectually. Sakaino offered the idea of “poetical Buddhism” (shiteki bukkyō 詩的仏教), a method for interpreting scripture in general, and segments thereof contemporarily regarded as “superstitious” specifically. This paper situates Sakaino’s contributions to Buddhist reform—analyzed through historical and hermeneutical methods and influenced by liberal Christian theology—within the global discourse on religion and science, while critically examining how his reinterpretations navigated tensions between modern rationality and the preservation of Buddhist truth in Meiji Japan. Full article

Kant’s philosophy of history is one of the best examples to trace the remains of certain theological concepts that emerged during the Christian tradition, which are secularized in order to shape a philosophical history. This process of secularization involves hidden causes through the weakening of the doctrinal truths of Christianism. These threats come from two antithetical poles whose attempts to demolish the Christian faith have been noticeable since its beginnings: Gnosticism and Ebionism. This article seeks to trace the influence of both doctrines in Kant’s philosophy of history. Based on his reinterpretation of certain theological concepts, it offers an adequate frame to understand the backgrounds that sustain Kant’s hope when regarding history. His great hesitation between an ultimate, intra-historical consummation and an infinite aspiration never fulfilled on Earth can be explained well from the opposite Ebionite and Gnostic perspectives. In conclusion, the article proposes that the tension that inspires Kant’s philosophy of history emerges from an unstable synthesis between Gnosticism and Ebionism. Full article