Impact of modification of envelope proteins on the mechanical properties of HIV virus-like particles.

Ethical conditions for university students’ adoption of large language models in exam preparation contexts

Characterization of wheat starch-safflower seed oil complex and its effects on noodle quality and starch digestibility.

Armed conflicts are among the most disruptive forces acting on agro-landscapes, yet their impact on land-use systems and ecosystem services remains insufficiently integrated into landscape ecology and agroecological research. This paper aims to systematise the international body of knowledge on the mechanisms of war-induced impacts on agro-landscapes, to identify reproducible causal patterns of ecosystem service degradation, and to propose methodological priorities for comprehensive assessment and monitoring of agro-landscapes under active armed conflict and post-conflict recovery. The study is based on a bibliometric analysis of 1,502 publications (WoS/Scopus, 2000–2026) and a comparative analysis of five literature clusters reflecting the evolution of research paradigms from foundational ecological concepts to conflict-specific environmental impact studies. The synthesis shows that conflicts disrupt agro-landscapes through direct destruction, forced displacement, land abandonment, and institutional collapse, triggering cascading degradation of provisioning, regulating, supporting, and cultural ecosystem services. Resilience theory and socio-ecological systems frameworks are identified as essential but systematically underutilised analytical lenses. A pronounced geographic bias favouring East Africa and Latin America was detected, with Eastern Europe and the Middle East comparatively understudied — a gap being rapidly addressed by the Ukrainian case post-2022. Remote sensing has emerged as the dominant methodology for assessing conflict-induced land-use change, yet integration with socio-economic and institutional dimensions remains limited. The paper argues that the next priority is the development of coupled models — Earth observation + field validation + ecological-economic assessment + scenario analysis — capable of underpinning evidence-based agro-landscape recovery policy under conditions of prolonged uncertainty.

Impact of climate change-induced temperature and salinity fluctuations on mussel byssus production and attachment strength.

ABSTRACT Purpose This article examines whether social work has experienced a genuine “cultural turn” in its disciplinary knowledge production. Materials and Methods The study draws on a Web of Science and Scopus corpus of 41,713 social work articles published between 1979 and 2025, including a cultur-indexed subcorpus of 5,442 explicitly culture-focused studies. It combines longitudinal trend analysis, changepoint detection, lexical classification, topic modeling, co-occurrence mapping, and methodological profiling. Results Findings reveal a modest but stabilizing increase in culture-related terminology over time, with no evidence of a structural break in disciplinary trajectories. Cultural discourse is dominated by managerial and competence-based frameworks and remains structurally anchored to mental health, education, risk, and service-delivery regimes. Critical, decolonial, and epistemic-justice vocabularies and methods remain marginal. Discussion Even within explicitly culture-oriented scholarship, culture functions primarily as a technical adjustment variable rather than as a disruptive epistemic force. The persistence of instrumental and professionalized uses of culture indicates continuity rather than transformation in the field’s epistemic foundations. Conclusion The study concludes that social work has institutionalized and professionalized culture without undergoing an epistemic transformation. Rather than evidencing a cultural turn, the discipline exhibits a pattern of cultural accommodation, with implications for theory, education, research practice, and future decolonizing projects.

Purpose This article aims to explore how manufacturing organizations navigate digital transformation in the era of Industry 5.0, with particular attention to management and learning. By applying the frameworks of dynamic capabilities and dynamic managerial capabilities, the study seeks to uncover how organizations sense emerging opportunities, mobilize resources and adapt employee competencies for digital transformation. Design/methodology/approach A qualitative case study was conducted using focus group interviews with 26 top and middle managers from eight manufacturing firms. Data were analyzed through thematic analysis in iterative steps. Findings The study highlights the ongoing need for organizations to sense opportunities, mobilize resources and transform capabilities to adapt to digital disruption. Sustained competitiveness requires continuous digital strategy, learning and managerial readiness to lead change processes. Research limitations/implications The study is limited to eight companies and managerial perspectives. Broader organizational insights and a larger sample could enhance the findings. Practical implications While seizing capabilities are often addressed, many organizations fall short in reconfiguring and transforming resources for long-term adaptation. Recognizing and developing organizational and managerial dynamic capabilities remains a challenge. Social implications This study points out the need for digital transformation managers to apply a human-centric perspective, acknowledging the disruptive force of digital transformation affecting the entire organization. Originality/value The novelty of this study lies in combining the frameworks of dynamic capabilities and dynamic managerial capabilities, uncovering how manufacturing organizations adapt resources and how managers drive learning and transformation building manufacturing systems that are not only technologically advanced but also human-centric and resilient.

This paper examines representations of marginalised masculinity in the fiction of Mo Yan and Zhu Wen, showing how male subjectivity is reshaped by ideological residues of the socialist past and the socio-economic upheavals of post-Mao China. In the late 1990s, state-owned enterprise (SOE) reform and large-scale layoffs produced a precarious population of displaced workers, with employees in crisis-ridden or shuttered factories—both younger and middle-aged—among the hardest hit. Their lives were shaped simultaneously by the lingering legacies of Maoist collectivism and the disruptive forces of market reform. Post-Mao writers increasingly responded to these transformations through new narrative forms that foreground social insecurity, gender anxiety, and the destabilisation of masculine identity. Focusing on Mo Yan’s Shifu, You’ll Do Anything for a Laugh (1999) and Zhu Wen’s Ah, Xiao Xie (1999), this study addresses a gap in scholarship on Chinese masculinity by offering a gender-focused analysis of marginal male protagonists caught between obsolete socialist certainties and unstable market futures. Approaching these works from a gendered poststructuralist perspective, it explores how they portray men’s struggles, resilience, and failures under conditions of institutional decline and economic insecurity. Through detailed analysis and comparative reading, the paper demonstrates how Mo Yan and Zhu Wen critique the erosion of welfare, challenge dominant gender discourses, and represent masculinity as unstable and contested. In doing so, it contributes to a deeper understanding of marginality, gender crisis, and the broader cultural anxieties surrounding masculinity in post-Mao China.

Deepfake technology, powered by advances in artificial intelligence, has emerged as a transformative yet disruptive force in contemporary information ecosystems. While it offers innovative applications in entertainment, education, and digital communication, its capacity to fabricate highly realistic audio-visual content raises serious concerns for democratic governance. This paper examines the social impacts of deepfakes on democratic trust, focusing on their role in amplifying misinformation, undermining informational integrity, and eroding confidence in public institutions. It analyzes the technical foundations of deepfakes, the challenges associated with their detection, and their implications for electoral processes, media credibility, and civic engagement. The study further evaluates existing policy responses across jurisdictions, including regulatory measures, platform governance strategies, and international initiatives, highlighting both their potential and limitations. Emphasis is placed on the importance of media literacy, civil society engagement, and multi-stakeholder collaboration in mitigating the risks posed by synthetic media. The paper argues that safeguarding democratic trust requires a balanced approach that combines technological innovation, legal regulation, and ethical accountability, while avoiding excessive restrictions that could undermine freedom of expression. Ultimately, it concludes that resilient democratic systems must adapt to the realities of synthetic media by strengthening transparency, accountability, and public awareness. Keywords: Deepfakes; Democratic trust; Misinformation; Media literacy and Platform governance.

Byssus adhesion-based biofouling by invasive mussels poses threats to freshwater ecosystems and underwater facilities. Among existing antifouling strategies, high-temperature treatment, though effective, is limited by high energy consumption and potential surface damage. Low-temperature treatment offers a promising alternative, but its mechanisms remain poorly understood. Here, we used the invasive golden mussel (Limnoperna fortunei) as a model species to investigate the mechanisms by which low temperatures (15°C and 5°C) affect byssus adhesion. Our results showed low-temperature exposures significantly reduced adhesion rates, primarily by limiting byssus production and decreasing byssus breaking force. Staining analysis observed foot gland atrophy and thickened collagen, suggesting disrupted byssal protein secretion. Additionally, reduced levels of tyrosinase and polyphenol oxidase further suggested the decreased byssus structural integrity due to disrupted byssal protein cross-linking. Individual and integrated transcriptomic and metabolomic analyses confirmed downregulations of genes/pathways for byssal protein synthesis (such as Foot protein 15, Putative foot protein-2, and the Phenylalanine, tyrosine, and tryptophan biosynthesis pathway) and upregulations of metabolites (pretyrosine and genipin) linked to protein cross-linking disruption, which collectively restricted byssal protein synthesis, precursor availability, and cross-linking processes. Notably, integrated transcriptomic and metabolomic analyses also revealed that low-temperature exposures activated survival-prioritized responses, including antioxidant, cellular stress response, immune regulation, and anti-apoptosis, reallocating energy from byssus production to stress responses and contributing to the reduced byssus adhesion. These findings advance low-temperature treatment as a strategy for controlling freshwater mussel biofouling and provide a foundation for developing targeted, environmentally sustainable antifouling approaches.

Abstract Invasive species have been known to be a disruptive force ecologically, economically, and socio-politically. Determining the impacts invasive species may have after introduction and establishment can be burdensome and expensive, particularly for species with intricate life histories and unique adaptations. In these situations, there may be deficits in ecological risks assessments and management plans, requiring the need for research that exceeds the bounds of typical management frameworks. This perspective serves to highlight the application of outside-the-box invasive species research through a variety of themes, while demonstrating the need for its continued development to protect global biodiversity and conservation efforts.

Artificial intelligence (AI) has rapidly emerged as a disruptive force in higher education, transforming how knowledge is produced, disseminated, and validated within academic communities. In Latin America, however, this transformation unfolds within persistent structural inequalities, where digital modernization progresses unevenly and intersects with socio-economic, institutional, and technological disparities. This study examines the perception and use of AI at Universidad del Valle–Pacífico Campus (Colombia), serving as a representative case of emerging educational innovation in a context shaped by regional constraints. Adopting a mixed-methods approach, the research combines: (i) online surveys administered to faculty members (N = 64) and students (N = 416), analyzed using descriptive and inferential statistics (Pearson’s χ², p < 0.05); and (ii) a focus group with ten instructors, analyzed through text mining and semantic network techniques. The findings reveal widespread adoption of AI tools—particularly ChatGPT—among students (98%) and faculty (74%), primarily for information retrieval, content generation, and pedagogical support. High levels of perceived usefulness (80–90%) and motivation (75–87%) were reported, with affective responses such as curiosity and amazement playing a significant role in engagement. Despite these positive perceptions, concerns remain regarding response accuracy, plagiarism, and technological dependency, further exacerbated by limited formal training in AI (59–70%). Inferential analysis demonstrates statistically significant associations between sociodemographic variables, ethical orientations, and usage patterns, indicating heterogeneous adoption across the academic community. Qualitative findings further suggest that AI is perceived as a transformative agent capable of reshaping educational roles, pedagogical practices, and ethical frameworks. Overall, the study highlights the urgent need for Latin American universities to reconsider pedagogical models, update governance and ethical guidelines, and implement inclusive strategies that promote equitable access, protect academic integrity, and strengthen institutional resilience in the context of AI integration.

Automatic driving technology is a disruptive force to reshape the future travel and transportation system. Its development has undergone a fundamental transformation from a rule-based modular approach to a data-driven deep learning paradigm. This paper systematically summarizes the key role, frontier progress and core challenges of neural network as the core technology engine in the whole technology stack of automatic driving perception, decision-making, planning and control. Firstly, this paper summarizes the application foundation of convolutional neural network, cyclic neural network, transformer and graph neural network in the field of automatic driving; Then the representative work and implementation path in the core tasks of multi-sensor fusion 3D target detection, interactive behavior prediction, end-to-end driving are analyzed in detail. The analysis shows that although the neural network has greatly improved the performance ceiling of the system, its inherent black box characteristics, vulnerability to adversarial attacks, difficult to deal with the "long tail problem" and high computing costs are still the fundamental obstacles restricting its safe landing. Finally, this paper looks forward to the future research directions of multimodal large-scale model, causal reasoning, neural radiation field simulation and vehicle road coordination, aiming to provide a comprehensive and profound perspective of technology development for researchers in the field.

Artificial intelligence (AI) has rapidly emerged as a disruptive force in the pharmaceutical industry, offering transformative applications across the entire drug lifecycle. Traditional drug development is hampered by high costs, extended timelines, and high attrition rates, with only a small fraction of candidate molecules reaching the market. AI-driven approaches provide innovative solutions by harnessing big data, computational modeling, and predictive analytics to accelerate discovery and development while reducing risk. In early-stage discovery, AI facilitates target identification, molecular design, and drug repurposing through deep learning, generative chemistry, and protein structure prediction. Preclinical stages benefit from advanced silico absorption, distribution, metabolism, excretion, and toxicity (ADMET) models, as well as digital pathology tools for toxicity prediction and biomarker discovery. In clinical trials, AI improves patient recruitment, stratification, and monitoring through mining of electronic health records, wearable technologies, and adaptive trial design, while also enabling the creation of synthetic control arms. Regulatory science and pharmacovigilance are enhanced by AI-assisted review of submissions, automated detection of adverse drug reactions, and real-time post-marketing surveillance. Furthermore, AI-powered manufacturing and supply chain solutions enable predictive maintenance, process optimization, and efficient distribution. Despite these advancements, challenges remain, including data quality, model transparency, ethical concerns, and regulatory acceptance. Future integration of multimodal data, federated learning, explainable AI, and digital twins may further accelerate innovation. Overall, AI represents not only a supportive tool but a paradigm shift, holding the potential to make drug development faster, more affordable, and more patient centric.

This study aims to explore leadership strategies to address the paradox of success in high-performing educational institutions, where past achievements often create strategic and cognitive inertia that hinders future adaptation. Using a Systematic Literature Review (SLR) methodology, 48 recent articles (2021–2025) from reputable databases such as Scopus and Google Scholar were synthesized. The analysis reveals that inertia in high-performing organizations manifests as an invisible cage and status quo bias, preventing innovation and adaptation. The study identifies Critical Leadership as a key mechanism to overcome this inertia through executive curiosity, digital emancipation, and interim leadership. Furthermore, Maintenance Innovation is conceptualized as a dynamic capability carried out by agile teams, enabling organizations to adapt and innovate continuously. The contribution of this study lies in its systematic synthesis of research on critical leadership, organizational inertia, and maintenance innovation in educational settings, providing a unified framework for overcoming challenges in high-performing schools. The novelty of this research lies in redefining Maintenance Innovation as a dynamic process that sustains performance amid technological disruptions, in contrast to traditional views of innovation as routine. Additionally, the study introduces Critical Leadership as a transformative, disruptive force that shifts leadership roles from merely maintaining quality to fostering productive dissatisfaction to stimulate innovation. This research offers valuable insights for educational leaders and policymakers on how to manage change and innovation while maintaining quality. However, further empirical research using quantitative and mixed-methods approaches is needed to validate these findings and assess their application across diverse educational contexts.

This study aimed to evaluate the influence of microfluidization cycles and oil type on the physicochemical characteristics of nanoemulsions and the properties of alginate-based edible films. Two types of oil (1%), coconut oil and coconut testa oil, were used for nanoemulsion preparation with Tween 80 and Span 20 (3:2). The emulsions were processed using different numbers of microfluidization cycles (0, 1, 2, and 3) and subsequently mixed with 2% sodium alginate in a 1:1 ratio to obtain film-forming solutions. The film-forming solution containing testa oil showed a particle size of 135.60 ± 37.87 nm, zeta potential of -22.14 ± 3.09 mV, whiteness index of 79.92 ± 2.20, and a creaming index of 0%. These systems produced flexible edible films with significantly (p < 0.05) higher elongation at break (1.35 ± 0.17%) and puncture force (2.40 ± 0.32 N), as well as lower water vapor permeability (4.7 × 10-7 ± 0.56 × 10-7 g m-1 h-1 Pa-1). Fourier Transform Infrared (FTIR) spectroscopy and Scanning Electron Microscopy (SEM) analyses indicated that both the number of microfluidization cycles and the type of oil significantly (p < 0.05) influenced the structural and physicochemical characteristics of the resulting edible films.

The rapid acceleration of Artificial Intelligence (AI) within the global technological revolution has intensified longstanding debates about transformation in tertiary education. While AI is often positioned as a disruptive force capable of reshaping higher education, less attention has been given to a more fundamental question: who must change in response to this disruption? This paper critically examines whether transformation should primarily occur at the level of educators, learners, curriculum content, or teaching and learning approaches, with specific attention to tertiary institutions in Fiji and the wider Pacific region. Drawing on contemporary scholarship in AI in education, heutagogy, learning analytics, and digital transformation, the study argues that technological adoption alone is insufficient. Instead, meaningful change requires a systemic reimagining of educational roles and relationships. The paper contends that educators must transition from content transmitters to facilitators of capability development; learners must assume greater agency and responsibility as self-determined participants in knowledge construction; curriculum content must evolve from static disciplinary coverage toward adaptive, interdisciplinary, and problem-based learning; and pedagogical models must shift from traditional pedagogy to heutagogy, emphasizing autonomy, reflection, and lifelong learning competencies. Within the Pacific context, these shifts are shaped by distinctive socio-cultural, geographic, and infrastructural realities. AI presents opportunities to address geographic dispersion, resource limitations, and inequities in access to higher education. However, it simultaneously raises concerns related to digital divides, algorithmic bias, ethical governance, cultural alignment, and educator preparedness. The paper proposes a contextually grounded framework for AI-enabled transformation that balances innovation with ethical oversight, cultural responsiveness, and institutional capacity-building. Ultimately, this study argues that transformation in the age of AI is not the responsibility of a single actor but a shared, systemic evolution of educators, learners, content, and pedagogy. By situating this discussion within a Pacific perspective, the paper contributes to global debates on AI in higher education while foregrounding the importance of contextual adaptation, equity, and sustainability. It offers strategic insights for policymakers, institutional leaders, and academics seeking to navigate the technological revolution without losing sight of human agency, cultural integrity, and educational purpose.

This research examines and delves into Yasmin Zaher's novel," The Coin "(2024) through a psychoanalytic perspective to uncover the impact of buried memories on one's sense of self and mental well-being. Modern storytelling often delves into fractured identities and inner turmoil, making psychoanalysis a crucial tool for understanding how memories, trauma, and identity intertwine. Despite this, there has been little focus on how The Coin (2024) portrays suppressed memories as a disruptive force that unsettles the protagonist's self-perception. Our research seeks to unravel how unconscious repression, unresolved trauma, and fragmented memories contribute to conflicts within one's identity and inner chaos in The Coin (2024). By drawing on Sigmund Freud's theories of repression, the unconscious mind, and delayed memories, we examine how buried experiences resurface through anxiety, compulsive actions, and narrative disruptions. Additionally, we incorporate Lacan's concept of fragmented subjectivity and Cathy Caruth's idea of trauma's delayed impact to further enrich our Freudian analysis. Methodologically, our study employs a meticulous examination of the text, focusing on character development, narrative gaps, symbolic elements, and instances of psychological breakdown. Our discoveries unveil that the protagonist's identity in The Coin (2024) is in a constant state of flux, shaped by memories that resist conscious acknowledgment. These "swallowed memories" perpetuate a state of psychological imbalance, where past events intrude upon the present, leading to confusion, guilt, and emotional turmoil. By offering a concentrated Freudian interpretation of The Coin(2024), our study contributes to the field of psychoanalytic literary criticism, showcasing how memory repression serves as both a narrative device and a psychological phenomenon. Ultimately, our research underscores the novel's significance in illustrating the enduring influence of the unconscious mind on identity and chaos in contemporary literature.

Amyotrophic Lateral Sclerosis (ALS) is a rare, incurable neurodegenerative disease that leads to death within 5 years of diagnosis and greatly impacts patients' and caregivers' quality of life (QoL). Typically leading to death within 5 years, ALS underscores the need for emotional and psychological support. This study analyzes 118 testimonies from patients (n = 67), informal caregivers (n = 41), and formal caregivers (n = 10), with a gender-balanced sample (n = 67 women), using discourse analysis. Narratives reveal a complex emotional landscape of suffering and resilience, showing ALS as a disruptive force that prompts reevaluation of roles and life stories. Shared support is crucial within families and social settings. Many testimonies express a desire to raise awareness and fund research. Understanding ALS through these stories offers insights into the psychological, emotional, cultural, and social challenges, essential for developing tailored interventions to support psychological well-being.

ABSTRACT Virtual influencers have emerged as a disruptive force in digital marketing, blurring the boundaries between human and computer-generated personas. Despite their growing prominence, academic research on VIs remains fragmented. To address this gap, this study conducts a comprehensive bibliometric analysis of 209 peer-reviewed articles retrieved from the Scopus data base to map the intellectual landscape of VI research. Employing bibliometric techniques within the SPAR-4 SLR framework, using tools such as VOSviewer and Bibliometrix package in R. This study investigates dominant theoretical frameworks, recent developments, and the transfer of information across disciplines. The key findings reveal that parasocial interaction, anthropomorphism, and brand trust are the most frequently applied theoretical lenses, yet gaps exist in understanding consumer-brand relationships with VIs. This study contributes to the literature by identifying underexplored areas, highlighting research gaps, and offering future directions for VI studies.