Search Results (416)

Spam consists of unsolicited messages, and the posting of such irrelevant messages often presents significant challenges in technical forums. Two particular challenges are the dynamic nature of spamming tactics and the inadequacy of adaptable spam databases for automated classifiers. Our work addresses the need for a robust spam classification solution that can be seamlessly integrated with database, SQL, and APEX applications. We developed a labeled spam database by asking experts to categorize 1916 posts as spam or regular posts to ensure accurate classification and then created an SVM-based spam classification model that achieves an average validation accuracy of 90%. Our research enhances the current understanding of spam in technical forums and represents a solution for embedding spam classifiers into widely used platforms with an accuracy of 98.1%. Furthermore, we explore the incorporation of generative topics into our approach by integrating generative topic modeling techniques, such as latent Dirichlet allocation. In our work, the spam classifier is dynamically updated to account for emerging spam patterns and topics based on a generative approach that improves the robustness of the classifier against new spamming tactics and enables nuanced, context-aware filtering of messages. In addition, our experiments highlight the potential of text SVM classifiers for real-time applications through the fine-tuning of text features. Full article

The Hyakuzahōdan Kikigakishō (百座法談聞書抄, hereafter Hyakuza 百座), compiled in the late Heian period, is an important Buddhist document that records a hundred-day lecture series on the Lotus Sutra (法華経). While previous scholarship has recognized the constructed nature of the text as a kikigaki (聞書), it has predominantly focused on content analysis, implicitly treating the text as a transparent window into the actual preaching event. To move beyond this limitation, this study proposes the analytical framework of dual performativity and, drawing on Diana Taylor’s theory of the archive and the repertoire, reexamines the text’s generative logic and political implications. This study argues that the Hyakuza embodies two interrelated forms of performance: first, the performativity of the hōdan (法談) as a live ritual, understood as a repertoire performance that constructs immediate authority through body, voice, and situational dynamics; second, the performativity of the kikigaki as textual construction, understood as an archival performance that transforms the ephemeral oral event into an authoritative, transmissible text through formulaic rhetoric, localized adaptation, and systematic arrangement. Integrating methodologies from textual history, rhetorical analysis, ritual theory, and intellectual history, this study demonstrates that the Hyakuza is not a neutral transcript of sermons but a meticulous, intentional act of writing with two fundamental aims: on a cultural level, to hierarchically integrate shinbutsu shūgō (神仏習合) through narrative appropriation; on a social level, to symbolically bind Buddhist merit with the institutional identities of aristocrats such as naishinnō (内親王), ultimately serving the self-affirmation internal cohesion, and cultural demarcation of the elite community from the masses, while simultaneously contributing to the state’s project of constructing a unified ideology in the late Heian period. By examining both cross-civilizational universal logic and specific historical context, this study reveals how the Hyakuza’s dual performativity produces and categorizes knowledge narratives while embedding political power dynamics, offering a critical path for the study of kikigaki-genre literature from discourse analysis to politics of textuality. Full article

Diffusion models have emerged as a powerful class of generative models, demonstrating impressive results across visual domains such as image and video synthesis. This survey provides a comprehensive taxonomy of generative models, with a particular focus on diffusion models and their applications in enhancing visual fidelity for text-to-image and text-to-video generation. We discuss the theoretical foundations of diffusion models, including their formulation through stochastic differential equations, and analyze the forward noising and reverse denoising processes that enable stable training and high-quality generation. The survey further categorizes diffusion architectures, including pixel-space and latent-space models, and examines their design choices, training strategies, and trade-offs across different resolution regimes. In addition, we review noise characteristics in real-world imaging domains and discuss their implications for diffusion-based models. Denoising strategies are analyzed by distinguishing between in-model denoising mechanisms and external denoising techniques used in preprocessing and post-processing pipelines. The survey also summarizes commonly used datasets and evaluation metrics for generative modeling, providing a practical perspective on benchmarking and model comparison. Finally, we discuss current challenges, including computational efficiency, scalability, and robustness to diverse noise distributions, and outline potential directions for future research. This survey aims to provide a structured reference for understanding diffusion models and their applications in visual generation tasks. Full article

Geological hazard data exhibits high-volume and multi-type characteristics, specifically characterized by inherent complexity; measurement uncertainty; cross-source heterogeneity; underdeveloped semantic organization; and fragile inter-entity associations. Consequently, advanced modeling techniques coupled with robust extraction frameworks become imperative for effective unstructured data governance. To address this challenge, we propose a content–knowledge representation framework that decomposes and reconstructs disaster data using fine-grained content entities as base units. This approach allows for a unified description, objectification, ordering, hierarchical storage, and indexed categorization of unstructured information. Furthermore, we develop specialized text extraction algorithms tailored to document imagery and vector maps—facilitating the systematic application of information retrieval techniques while efficiently targeting specific thematic content. Our method outperforms two representative deep learning architectures (Fast CNN and FCN), demonstrating superior performance in segmenting target regions and precisely detecting textual elements, tables, and geographic features within complex datasets. By studying the modeling and extraction technology of unstructured geologic data, this paper establishes the value chain of geologic result data, which can provide strong support for digital management of geologic disaster data and improve work efficiency. Full article

Discretisation is a processing step often included in the preliminary data preparation. Typically, when the input features have continuous domains and their discrete forms are needed, all are translated into categorical type at the same time, before data mining takes place. However, proceeding this way is not always the most advantageous to performance. The paper presents results from the research where the discretisation transformations were carried out sequentially forward for variables, and their selection was based on their values and also importance of the attributes estimated by the constructed rankings. The experiments were executed on the datasets from the area of stylometric analysis of texts, the application domain focused on recognising authorship based on individual characteristics of writing styles. For the selected data mining techniques, the performance was studied in the context of transformed features. The observed trends indicate that along with enhanced understanding of the nature of the data, partial discretisation of feature sets could bring higher accuracy than transformation of entire input domain, showing the merits of the described research methodology. Full article

Text-to-video (T2V) generation has recently emerged as a transformative technology within the field of generative AI, enabling the creation of realistic, temporally coherent videos based on natural language descriptions. This paradigm provides significant added value in many domains such as creative media, human-computer interaction, immersive learning, and simulation. Despite its growing importance, systematic discussion of T2V is still limited compared with adjacent modalities such as text-to-image and image-to-video. To alleviate the scarcity of discussions in the T2V field, this paper provides a systematic review of works published from 2024 onward, consolidating fragmented contributions across the field. We survey and categorize the selected literature into three principal areas—namely, T2V methods, datasets, and evaluation practices—and further subdivide each area into subcategories that reflect recurring themes and methodological patterns in the literature. Emphasis is then placed on identifying key research opportunities and open challenges that need further investigation. Full article

Background: Cutaneous melanoma metastases (CMM) represent a clinically relevant manifestation of advanced melanoma and may constitute the first sign of disseminated disease. Their diagnosis is challenging because CMM shows highly variable clinical and dermoscopic presentations and frequently mimic other benign or malignant skin lesions. Although dermoscopy is routinely used to improve skin lesion assessment, dermoscopic criteria specific to CMM remain poorly defined and still non-standardized. Methods: We performed a narrative review of the literature to summarize dermoscopic features reported in CMM. MedLine (via PubMed) and Web of Science were searched up to 3 December 2025 using the keywords “dermoscopy” and “melanoma metastasis,” complemented by manual reference screening. Eligible studies were English-language full-text articles in peer-reviewed journals providing a complete dermoscopic description. Extracted data included patient demographics and major dermoscopic criteria, categorized as global patterns and focal dermoscopic and vascular structures. Due to heterogeneity, results were synthesized descriptively. Results: Twenty studies were included, comprising 774 patients. Dermoscopic findings were markedly heterogeneous. Globally, lesions frequently showed homogeneous pigmentation with variable colors and included amelanotic presentations. Commonly evaluated focal features included irregular dots and globules, crystalline structures, peripheral gray dots, and lacuna-like areas. Vascular patterns were prominent, particularly serpentine and corkscrew-like vessels. Conclusions: CMM dermoscopy is characterized by substantial heterogeneity and a lack of standardized criteria. Systematic classification of recurring dermoscopic features may improve diagnostic consistency and provide an interpretable framework for future artificial intelligence-based approaches supporting non-invasive recognition of melanoma metastases. Full article

Biportal endoscopic (BE) spine surgery has gained increasing attention as a minimally invasive alternative to conventional spinal procedures, yet the distribution of procedural applications and anatomic targets within influential BE-specific publications has not been clearly synthesized. This study aimed to synthesize influential publications on BE spine surgery to describe the evolution of procedural applications, anatomic focus, and clinically relevant themes reflected in the literature. A comprehensive search of the Web of Science database was performed using terms related to biportal and multiportal endoscopic spine techniques. Influential articles were identified using citation frequency as a screening criterion, and relevant study characteristics, including publication year, authorship, institutional affiliation, geographic region, journal, and spinal region addressed, were extracted. Full-text screening confirmed inclusion of true biportal endoscopic spinal procedures and categorized the anatomical region and surgical technique addressed. Publications spanned 1997 to 2023, with a marked increase after 2018 and peak productivity in 2022. Influential publications were most frequently published in World Neurosurgery, with substantial contributions originating from South Korea, including work by Dae-Jung Choi. Most studies focused on lumbar procedures, primarily decompression techniques and transforaminal lumbar interbody fusion. Overall, this review highlights the rapid clinical growth of BE spine surgery, with influential literature emphasizing lumbar applications and underscoring the need for further research on outcomes, learning curves, and broader international adoption. Full article

Rapid classification of social media content during humanitarian crises is essential for effective disaster relief; however, traditional approaches require extensive annotated training data, which are often unavailable during new disasters. This paper presents a training-free, multimodal classification framework that leverages zero-shot vision-language models to analyze disaster-related social media content without task-specific training. The framework employs a two-stage prompt-engineered pipeline using the locally deployable Mistral-Small-3.1-24B-Instruct model, performing binary informativeness detection followed by multiclass categorization into eight humanitarian categories through structured JSON output generation. Evaluation on the CrisisMMD dataset of 18,082 multimodal samples from seven natural disasters demonstrated binary F1 scores above 0.84 for both text and image informativeness detection and weighted F1 scores of 0.61 (text) and 0.72 (image) for humanitarian categorization. The framework generalizes consistently across all disaster types with minimal performance variance (standard deviation below 0.031) and operates entirely on local infrastructure without cloud dependencies, requiring only moderate GPU resources. By eliminating training data requirements, this approach enables immediate deployment during new disasters, demonstrating that zero-shot multimodal classification achieves practically relevant performance for real-time crisis response. Full article

Background/Objectives: Interest in Oral Kaposi’s sarcoma (OKS) has declined recently, potentially causing diagnostic errors due to physicians’ unfamiliarity with its presentation. This review describes clinical and demographic characteristics of OKS patients across epidemiological groups. Methods: A literature search of studies published from 1957 to December 2024 was conducted using PubMed, Web of Science, Cochrane Library, Scopus, and Google Scholar. Studies with confirmed oral Kaposi sarcoma were included, while those with incomplete data were excluded. Cases were grouped into classic, endemic, epidemic (AIDS-related), iatrogenic, and HIV-negative males who have sex with males. Sex distribution, mean age, clinical appearance, lesion topography, and cause-related information for iatrogenic forms were recorded. Results: A total of 1812 articles were identified through database search. During initial screening, 1162 articles were excluded as duplicates. Of the remaining 650 papers, 338 were dismissed based on title and abstract. Of the remaining 312 articles for full-text review, 93 could not be accessed, leaving 219 articles for analysis. After screening, 123 were excluded, resulting in 117 articles for review. These were categorized as: 16 classical KS, 7 endemic-African, 20 iatrogenic, 70 epidemic-HIV/AIDS-related, and four articles reporting cases among MSM not related to HIV infection. A total of 152 patients with OKS were analyzed. Mean age was 38.04 years (range, 2–86 years), and 75% were male. Of all cases, 64.4% were epidemic, 13.8% iatrogenic, 10.5% classical, and 4.6% endemic. The palate was most common (44.6% of lesions), followed by gingiva (25.3%). Nodular or papular presentations were most frequent. Conclusions. OKS occurs in all KS epidemiological forms, and since this tumor can mimic gingival and periodontal lesions, dentists and physicians must be alert to identify oral Kaposi’s sarcoma. Full article

Background/Objectives: The second victim phenomenon is increasingly recognized as a significant issue affecting nurses involved in adverse events resulting from clinical decisions or interventions. Although patients and families, considered the first victims, are directly impacted, nurses often undergo challenges as second victims. With the growing awareness of these effects, this study aimed to map recent evidence on the second victim phenomenon among nurses in Western countries. Methodology: A Scoping Review was conducted following the Joanna Briggs Institute methodology in September 2024 and updated in November 2025. Eligibility criteria were defined using the PCC (Population, Concept, Context) framework. Searches were performed in PubMed, CINAHL, SciELO, and Scopus. Two independent reviewers carried out study selection, data extraction, and synthesis. Rayyan^® supported screening, performed in two phases: title/abstract review and full-text analysis. Data extraction was conducted in Excel^®, and data were analyzed using descriptive statistics and categorized into thematic areas. The review followed PRISMA-ScR guidelines and was registered in the Open Science Framework. Results: Of the 111 articles retrieved, 39 met the inclusion criteria. Evidence shows that although several support programs exist for nurses as second victims, they are often perceived as inadequate or inconsistently implemented. Second victim experience is associated with physical (e.g., sleep disturbances), emotional (e.g., fear), and psychological (e.g., distress) symptoms, with consequences such as absenteeism, professional dissatisfaction, loss of meaning in life, and even suicide. Conclusion: Findings highlight the need for more comprehensive, accessible, and consistently implemented support strategies to meet the complex needs of nurses affected by the second victim phenomenon. Full article

Despite advancements in navigation apps for wheelchair users, there is no consensus on which environmental factors to prioritize for personalized accessible routes. This scoping review synthesizes factors influencing wheelchair mobility in urban settings, evaluates measurement methods, and assesses their integration into routing algorithms. Following Arksey and O’Malley’s framework and PRISMA-ScR guidelines, we analyzed six databases for English-language articles from 2005 to 2023, supplemented by an updated search covering 2023 to 2026. Two reviewers screened 6966 records and examined 79 full-text articles, with 24 meeting the inclusion criteria for data extraction. Environmental factors were categorized into static and dynamic factors affecting mobility. Key components included sidewalks (96%), ramps (63%), curb cuts (54%), stairs (50%), crosswalks (50%), and streets (38%). Common factors examined were length, slope, width, and surface properties. Data collection methods varied: 42% relied on measurements, 8% used user assessments and sensors, while 50% combined both approaches. Recent studies (2023–2026) demonstrate increasing adoption of AI and machine learning techniques, including crowdsourced smartphone data and generative AI for feature detection. This review identifies essential factors for wheelchair navigation and highlights significant gaps in dynamic factor assessment and real-time data integration. Full article

This study examines the Laozi Zhigui—a key text of Han dynasty Huang-Lao thought—and reconstructs the categorical status of qi to reassess received primordial qi-centered cosmological interpretations and clarify the text’s distinctive worldview. The Laozi Zhigui explains the relation between Dao and the myriad entities through four stages of wu (nothingness)—Dao, De, Spirit-Illumination, and Great Harmony—and previous studies, working within inherited qi-centered cosmological frameworks, have generally assimilated these stages to qi. A contextual reading of key passages on cosmology, mind–nature, and self-cultivation clarifies that in the Laozi Zhigui, qi does not belong to the same ontological category as these four stages of wu. Instead, it functions as a mediating substance through which the order of wu is carried over into you (somethingness). Furthermore, the four stages of wu are likewise not as the internal differentiation of qi but as a non-substantialist account of the “generation of order.” On this basis, the worldview of the Laozi Zhigui can be reconstructed as a triadic schema of wu–qi–you (nothingness–qi–somethingness), which yields a distinctive model of qi cosmology that, unlike Han dynasty primordial qi-centered accounts, does not presuppose the generation and fission of a single primordial qi. Full article

This research presents a large-scale thematic analysis of 66,002 Slovak university thesis abstracts, aimed at identifying, categorizing, and visualizing research trends across multiple academic disciplines. Using BERTopic for unsupervised topic modeling with K-Means clustering, 3000 distinct thematic clusters were extracted through rigorous coherence optimization, with each topic characterized by representative keywords derived from class-based TF-IDF weighting. Text embeddings were generated using SlovakBERT-STS, a domain-adapted Slovak BERT model fine-tuned for semantic textual similarity, producing 768-dimensional vectors that enable precise computation of cosine similarity between topics, resulting in a 3000 × 3000 topic similarity matrix. The optimal topic count was determined through systematic evaluation of K values ranging from 1000 to 10,000, with K = 3000 identified as the optimal configuration based on coherence elbow analysis, yielding a mean coherence score of 0.433. Thematic relationships were visualized through Multidimensional Scaling (MDS) projection to 3-D space, where convex hull geometries reveal semantic boundaries and topic separability. The methodology incorporates dynamic stopword filtering, Stanza-based lemmatization for Slovak morphology, and UMAP dimensionality reduction, achieving a balanced distribution of approximately 22 abstracts per topic. Results demonstrate that fine-grained topic models with 3000 clusters can extract meaningful semantic structure from multi-domain, morphologically complex Slovak academic corpora, despite inherent coherence constraints. The reproducible pipeline provides a framework for large-scale topic discovery, coherence-driven optimization, and geometric visualization of thematic relationships in academic text collections. Full article

Parental practices strongly influence offspring development, and parental alcohol use may affect parenting behavior. However, most studies have focused on child-related outcomes. This review instead examined associations between parental drinking and parenting practices. Following PRISMA guidelines, a systematic search in MEDLINE, PsycINFO, Embase, and Scopus identified 9053 articles. Of these, 222 full texts were screened by two reviewers, and 77 were included for critical appraisal. After quality assessment, 68 studies published between 1991 and 2026 were reviewed. Studies were included if they (i) measured parental alcohol use as a predictor and parenting practices as an outcome, (ii) involved offspring under 20 years, (iii) had a quantitative design, (iv) were peer-reviewed and published in English, and (v) excluded pregnancy measures and alcohol/parenting treatment interventions. Parenting factors (e.g., parent–child relationship, monitoring, communication, discipline, conflict, abuse) were categorized and grouped into general and alcohol-specific practices. Parental drinking was categorized into alcohol use disorders (AUD) and non-dependent alcohol use. Sixty-four studies reported at least one significant association between parental drinking and poorer parenting practices. Mixed results were observed for non-dependent drinking and alcohol-specific parenting. Some associations varied with parental gender. Overall, different drinking patterns appear to be linked to impaired parenting quality. Despite being the most common pattern of alcohol use, non-dependent drinking remains understudied in parenting research. The present review highlights several critical gaps in the literature, particularly regarding the relationship between non-dependent drinking, maternal AUD, and parenting practices. Moreover, contextual factors, such as socioeconomic status and gender differences, are insufficiently explored, limiting the understanding of heterogeneity in risk and outcomes. Future research would benefit from employing robust longitudinal designs and expanding geographical representation, in order to capture variation across sociocultural contexts and enhance the generalizability of findings. Full article