Search Results (9,467)

The use of effect size estimates to complement visual analysis has become increasingly emphasized in single-case research design (SCRD) studies in special education. This review examined trends in SCRD publication and ES reporting practices across three major special education journals (i.e., Journal of Special Education, Exceptional Children, and Remedial and Special Education) from 2001 to 2025. A total of 1969 articles were screened, yielding 194 SCRD intervention studies and 124 SCRD systematic reviews/meta-analyses. Results indicated a sustained increase in the publication of SCRD studies over time, accompanied by a marked rise in ES reporting. Overall, 42.27% (n = 82) of SCRD intervention studies and 55.65% (n = 69) of SCRD systematic reviews reported at least one effect size estimate, with the highest rates observed in the most recent publication period (2001–2025). Across both intervention studies and systematic reviews, Percentage of Nonoverlapping Data and Tau-U were the most frequently reported ES metrics, although reliance on Percentage of Nonoverlapping Data declined over time while use of Tau-U increased. Findings highlight evolving effect size reporting practices and have implications for evidence synthesis and methodological standards in special education research. Full article

In her fiction, Joan Didion crafted female protagonists who embodied the strange stirrings documented by Betty Friedan in The Feminine Mystique, as common among mid-century White, educated women. Didion’s protagonists are all daughters, wives, and mothers who come to realize their lives are built on empty compromises. However, in her late 20th-century novels, their awareness leads to actual changes: the Didion Women who confront the void in Democracy and The Last Thing He Wanted find their lives impacted by the machinations of U.S. Cold War policies. These novels specifically trace the impact of American imperialism on wives and daughters at home—those that the policies claimed to protect. These protagonists, and their witnesses, refuse to be passive casualties. Their narration by an embedded professional female journalist adds weight to the journeys of these overlooked women. Through her protagonists of privilege, Didion unflinchingly documents the physical and psychological damages of patriarchy—both personal and political—presenting female models of awareness and resistance. This essay will examine Didion’s Democracy and The Last Thing He Wanted as the capstones of her woman-centered fiction, presenting detailed portraits of matrons who deliberately disentangle themselves from history. Full article

The media industry has undergone a myriad of challenges in recent years and in Ireland the impact of those challenges has been particularly acute in the regional print press. Changes in media consumption patterns, a shift from mainstream and digital media, advances in technology, reduced income from advertising and a decrease in newspaper circulation have all had a significant impact on the regional print press in Ireland. Semi-structured interviews were carried out with five owners and five editors of regional print newspapers. An overall negative view of the future of the industry, from a regional print perspective, was found. Survival is a priority and a lack of resources is a concern, as recruitment of staff—journalists and photojournalists—is limited or non-existent. All participants cited lack of revenue from advertising and struggles to generate any profit from online advertising as major concerns. While all maintained that editorial independence is a priority, in reality, the separation between newsrooms and commercial sections of media organisations has become less pronounced, amid commercial realities which are a source of disquiet. Full article

Background: Chronic heart failure (CHF) in older adults requires sustained self-management and close follow-up, yet day-to-day care is often carried out by families with support from primary healthcare nurses. In Saudi Arabia, where family caregiving is culturally normative, collaboration between nurses and patients’ families may be pivotal to effective CHF management, but remains insufficiently understood in primary healthcare contexts. Methods: A qualitative study informed by an interpretive phenomenological approach was conducted. Participants (n = 24; 12 nurses and 12 family caregivers) were recruited using purposive sampling from primary healthcare centers in Riyadh, Saudi Arabia. In-depth, semi-structured interviews were conducted in Arabic or English, audio-recorded, transcribed verbatim, and analyzed using reflexive thematic analysis following Braun and Clarke’s six-phase framework. Strategies to enhance trustworthiness included member checking, peer debriefing, maintenance of an audit trail, and reflexive journaling. Results: Twenty-four participants (12 nurses and 12 family caregivers) were interviewed. Four interrelated themes were generated from both nurses’ and family caregivers’ accounts. (1) “We Are Caring Together”: Collaboration was experienced as shared responsibility for daily CHF management, grounded in trust; (2) Navigating Roles and Boundaries: Participants described unclear expectations, role overlap, and tension between professional authority and family knowledge; (3) Communication as the Engine of Collaboration: Effective partnerships depended on clear information exchange, caregiver-tailored education, and continuity of contact, while communication gaps created uncertainty and delayed support-seeking; and (4) Cultural and System Constraints Shaping Collaboration: Strong family obligation motivated caregiving but also intensified moral pressure and limited help-seeking, while time pressure and fragmented services constrained meaningful engagement and continuity across settings. Conclusions: Nurse–family collaboration in CHF management is relational, shaped by trust, role negotiation, and communication, and constrained by cultural norms and system pressures. This study contributes to the literature by demonstrating how moral obligation, hierarchical professional norms, and system fragmentation distinctively shape collaboration in the Saudi primary care context, extending existing conceptualizations derived primarily from Western individualist settings. Strengthening collaboration requires explicit role clarification, health literacy–informed caregiver education, continuity of contact, and organizational supports. Findings are limited by purposive sampling, single-city context, and exclusion of patient perspectives. Full article

Phishing remains a major cybersecurity threat, yet the application of quantum machine learning (QML) to phishing detection is still at an early stage. This study presents a systematic literature review aimed at providing a concise overview of existing QML-based approaches for phishing detection, identifying methodological trends, limitations, and future research directions. A PRISMA-guided review protocol was applied to peer-reviewed journal and conference articles published between 2021 and 2025, retrieved from major scientific databases. Eligible studies were analyzed in terms of QML models, feature encoding strategies, experimental settings, evaluation metrics, and study quality using an adapted Newcastle–Ottawa Scale. The results indicate that current research is limited in volume and largely focuses on hybrid quantum–classical models, particularly quantum support vector machines and variational quantum classifiers. Reported performance is highly dependent on encoding methods, circuit depth, and simulator-based experimentation, with few studies evaluating real quantum hardware. Common challenges include small datasets, lack of external validation, hardware noise, scalability constraints, and the absence of standardized benchmarks. Overall, the review suggests that QML for phishing detection remains exploratory and is not yet competitive with mature classical approaches, but it holds potential as an experimental research direction, provided that future studies address robustness, reproducibility, and practical deployment constraints. Full article

The Cite Frequency Approach (CFA) is an accepted method for identifying potential factors influencing bid/no-bid decisions, yet no study has systematically validated its theoretical foundation. The aim of this study was to elucidate the theoretical basis of CFA and ascertain whether citation frequency truly reflects factor importance. Through rigorous screening undertaken using the PRISMA method, 24 journal articles with bid/no-bid decision (BNBD) factors’ RII were extracted for analysis. By constructing a 276-times pairwise comparisons of these articles, a matrix of 121 factors’ RII was built. Based on the matrix data, 2380 Spearman correlation coefficients (rhos) between cite frequency and RII were calculated. Significant level rhos of medium and high strength account for only 15.59%. This demonstrates that the cite frequencies of factors found in previous studies are not highly representative of their importance. Cite frequencies are therefore shown to be unreliable in identifying the potential factors affecting BNBD. Moreover, the Meta-Analyses approach (MAA) is proposed as a superior factor selection method (MAA), and this was verified to be more representative and effective than CFA. This study provides the first systematic and global validation of CFA’s core assumption supported by robust and generalizable findings. It enriches the methods for identifying potential factors affecting decisions, including but not limited to BNBD. Full article

This study aims to systematically analyze scholarly research on virtual reality (VR), augmented reality (AR), and the metaverse in the tourism and hospitality sectors, offering insights into publication patterns, key contributors, thematic evolution, and potential research directions from 2016 to mid-2025. It maps how the literature evolved in response to technological maturation and changing tourism constraints. A systematic literature review and comprehensive bibliometric analysis were conducted using the Scopus database. The analysis encompassed bibliographic metrics, thematic clustering, and content analysis techniques to identify influential journals, authors, and evolving research themes. The results reveal a pronounced acceleration in research activity post-2020, reflecting heightened interest due to the COVID-19 pandemic’s push towards digital and immersive solutions. Core journals identified include Tourism Management, Current Issues in Tourism, and Journal of Travel Research. Influential contributors such as Timothy H. Jung, M. Claudia tom Dieck, and Dimitrios Buhalis significantly shaped the field. The thematic trajectory demonstrates a shift from initial exploration and application of VR and AR technologies toward comprehensive integration into metaverse ecosystems, with emerging themes such as digital twins, synthetic experiences, immersive storytelling, and growing emphasis on ethical and sustainability considerations. By synthesizing nearly a decade of research, this study provides valuable insights into immersive technologies’ evolution in tourism and hospitality, identifying critical areas for future investigation aligned with enterprise information management strategies. Full article

Advances in Generative Artificial Intelligence have enabled the development of models capable of generating text, images, and audio that are similar to what humans can create. These models often have valuable general knowledge thanks to their training on large datasets. Through fine-tuning or prompt-based adaptation, this knowledge can be applied to specific tasks. In this work, we propose a modular approach to automated news generation using Large Language Models, composed of an information retrieval module and a text generation module. The proposed system leverages both publicly available (open-weight) and proprietary Large Language Models, enabling a comparative evaluation of their behavior within the proposed news generation pipeline. We describe the experiments carried out with a total of five representative Large Language Models spanning both categories, detailing their configurations and performance. The results demonstrate the feasibility of using Large Language Models to automate this task and identify systematic differences in behavior across model categories, as well as the problems that remain to be solved to enable fully autonomous news generation. Full article

Background/Objectives: Increasing evidence indicates that tumors interact functionally with the nervous system. Rather than being passively innervated, many cancers establish bidirectional communication with neurons, suggesting that neural activity may represent an additional regulatory layer of tumor biology. This review aims to synthesize current knowledge on the mechanisms and consequences of tumor innervation and to discuss its implications for cancer progression and therapy. Methods: We performed a narrative synthesis of recent experimental and translational studies (2015–2026), identified through PubMed and major peer-reviewed biomedical journals. The literature was analyzed to identify key mechanisms of neural influence on tumor biology, including axonogenesis, pseudo-synaptic communication, neurotransmitter signaling, and metabolic coupling. Results: Emerging evidence indicates that neural inputs can regulate multiple hallmarks of cancer, including proliferation, invasion, angiogenesis, metabolic plasticity, and immune evasion. Tumors can actively recruit nerve fibers through axonogenic signals and establish specialized neuron–cancer interfaces that enable activity-dependent oncogenic signaling. In addition, neuronal interactions can influence tumor metabolism and therapeutic resistance through mechanisms such as mitochondrial transfer and neurotransmitter-driven signaling pathways. Conclusions: Tumor innervation represents an important and increasingly recognized dimension of cancer biology. Understanding how neural circuits interact with tumor cells and the surrounding microenvironment may reveal new biomarkers and therapeutic strategies aimed at disrupting tumor–neuron communication. Full article

Higher education is undergoing a constant paradigm shift, transforming itself into a system of innovation for society. This study has explored and determined the relationship between educational innovation and research in university contexts in order to distinguish, compare, and establish dynamics of interaction. The contributions of scientific articles published in WoS-indexed journals between 2019 and 2025 in a total of 108 sources were analyzed using the PRISMA method and an analysis inspired by grounded theory with open coding and axial coding (mixed method). As a result, both functions have been conceptually differentiated while establishing these points of contact, productive interactions, and their relationship with university institutional management. It is concluded that higher education is facing a paradigm shift, transforming itself from a center of knowledge and professional training to the hub of innovation systems. The main contribution of this study is its exposition of how this profound change is taking place and the conditions of research–innovation interaction in the university setting. Full article

The rapid integration of renewable generation, distributed energy resources, and advanced monitoring infrastructures has increased the demand for data-driven methods in modern power systems. Artificial neural networks (ANNs) have become widely adopted for load forecasting, fault diagnosis, state estimation, stability assessment, and energy management. Despite substantial publication growth, large-scale operational deployment of ANN-based solutions remains limited. This study presents a bibliometric and engineering assessment of ANN applications in power systems between 2020 and 2024, based on 1511 SCI-Expanded journal articles retrieved from the Web of Science. Beyond conventional science mapping, the study integrates an engineering-oriented deployment-readiness evaluation that systematically links ANN architectures with core operational problem classes. The results reveal a significant imbalance between reported algorithmic performance and operational validation rigor. Forecasting and energy management applications demonstrate relatively higher readiness due to real-world dataset usage, whereas fault diagnosis and state estimation remain predominantly simulation-driven and lack explainability and robustness validation. A deployment-readiness matrix is applied to quantitatively evaluate dataset realism, interpretability integration, and reliability considerations across domains. The findings indicate that the primary barriers to ANN integration in power systems stem from insufficient validation protocols and resilience-oriented design rather than algorithmic limitations, highlighting key engineering priorities for reliable real-world implementation. Full article