Search Results (229)

Background: This case report presents a 12-year-old male with vertically transmitted chronic hepatitis B virus (HBV) infection, exhibiting a rare pan-reactive serological profile (concurrent HBsAg, HBsAb, HBeAg, HBeAb, and HBcAb positivity) alongside fluctuating low-level viremia (HBV DNA: 1.06 × 10² IU/mL to undetectable). Rigorous exclusion of technical artifacts confirmed the authenticity of this atypical serologic pattern, observed in <0.001% of the general population. Methods: Liver biopsy and immunohistochemical staining were performed to evaluate hepatic inflammation and fibrosis. HBV serological markers and viral load were quantified using commercial diagnostic kits, with longitudinal monitoring for 18 months. Results: Liver biopsy revealed Grade 2 inflammation with focal HBsAg/HBcAg expression, supporting immune-active chronic hepatitis B (CHB) despite partial seroconversion. The patient’s clinical course highlights key challenges in pediatric HBV management: (1) delayed immune reconstitution (18-month longitudinal HBeAg/HBeAb dynamics), (2) non-linear virologic-ALT correlation, and (3) diagnostic ambiguity in pan-positive serology—potentially reflecting S-gene escape mutants or transitional immune responses. Initiation of tenofovir disoproxil fumarate (TDF) achieved sustained virologic suppression, underscoring the importance of early antiviral therapy in pediatric CHB with atypical markers. Conclusions: This case provides preliminary insights into the complex interplay between viral evolution and immature host immunity, advocating for refined monitoring protocols integrating high-sensitivity HBV DNA, quantitative serology, and non-invasive fibrosis assessment in pediatric HBV care. Full article

This study examined how distinct dimensions of grandiose narcissism shape responses to self-relevant video advertising framed as either recognition/validation or status challenge. Drawing on the Narcissistic Admiration and Rivalry Concept, we tested a dual-path process model in which two proximal mechanisms–perceived recognition and autonomy-related resistance (operationalized as perceived freedom threat and state reactance)–are associated with advertising-related outcomes. Community adults (N = 598) were randomly assigned to view one of two video advertisements and subsequently reported perceived recognition, resistance, and consumer responses. Recognition framing increased perceived recognition but did not directly influence consumer outcomes. Process analyses revealed distinct personality-linked patterns that were consistent with the proposed dual-path model. Narcissistic admiration was associated with more favorable attitudes toward the advertisement and brand, as well as stronger purchase intentions, indirectly through higher perceived recognition. In contrast, narcissistic rivalry showed contrasting indirect associations, with positive indirect associations through recognition alongside negative indirect associations through resistance. Moderated mediation by message framing was not supported. Overall, the findings are consistent with the view that self-relevant advertising can simultaneously activate affirmation-related and autonomy-protective processes that may partially offset one another at the aggregate level. Importantly, consumer responses appear to depend on whether the persuasive encounter is construed as authentic recognition or as an autonomy threat–an interpretive dynamic that is especially pronounced among individuals high in narcissistic rivalry. Full article

The Automated Essay Scoring (AES) systems confront two fundamental challenges: opaque “black-box” decision-making that limits educator trust, and insufficient validation across linguistically diverse educational contexts. This study proposes IRT-AESF, an innovative framework that bridges educational measurement theory and artificial intelligence by integrating item response theory (IRT) with deep learning. The framework generates three theoretically grounded psychometric parameters: student ability, item difficulty, and item discrimination, which provide transparent and interpretable explanations for scoring decisions. We rigorously evaluated IRT-AESF through 5-fold cross-validation on three large-scale datasets comprising 41,328 authentic essays from English and Chinese educational settings, including both classroom assessments and high-stakes examinations. Results demonstrate statistically significant improvements over competitive baseline models, achieving an 8.4% relative increase in quadratic weighted kappa while maintaining robust cross-lingual performance. This research advances the development of transparent, trustworthy automated assessment systems that deliver not only scores but meaningful diagnostic insights for educational practice. Full article

Unmanned Aerial Vehicles (UAVs) are increasingly integrated into critical applications ranging from logistics and agriculture to defence and security operations, surveillance and emergency response. At the core of these systems lies the communication link between the UAV and its ground control station (GCS), which serves as the backbone for command, control and data exchange. However, communications links remain highly vulnerable to cyber-threats, including eavesdropping, signal falsification, radio frequency interference (RFI) and hijacking. These risks highlight the urgent need for secure communication protocols and effective defence mechanisms capable of protecting data confidentiality, integrity, availability and authentication. This study performs a comprehensive survey of secure UAV-GCS communication protocols and artificial intelligence (AI)-driven intrusion detection techniques. Initially, we review widely used communication protocols, examining their security features, vulnerabilities and existing countermeasures. Accordingly, a taxonomy of UAV-GCS security threats is proposed, structured around confidentiality, integrity, availability and authentication and map these threats to relevant attacks and defences. In parallel, our study examines state-of-the-art intrusion detection systems for UAVs, while particular emphasis is placed on emerging methods such as deep learning, federated learning, tiny machine learning and explainable AI, which hold promise for lightweight and real-time threat detection. The survey concludes by identifying open challenges, including resource constraints, lack of standardised secure protocols, scarcity of UAV-specific datasets and the evolving sophistication of attackers. Finally, we outline research directions for next-generation UAV architectures that integrate secure communication protocols with AI-based anomaly detection to achieve resilient and intelligent drone ecosystems. Full article

Background: This exploratory study investigates whether STEM (science, technology, engineering, and mathematics) students’ increasing reliance on off-campus resources (e.g., online platforms, private tutors) reflects an authentic preference for autonomous learning or a compensatory response to perceived deficiencies in on-campus instruction. Methodology: Using a mixed-methods design, data were collected from 118 engineering and science students. A model was developed to examine the relationship between the intensity of student criticism and their declared preference for off-campus learning. Findings: The model revealed a significant negative relationship between the intensity of criticism and the preference for off-campus instruction. This suggests that for highly critical students, external resources function primarily as a compensatory mechanism for “needs frustration” rather than a preferred alternative. The results imply that these students continue to value the frontal model but find its current implementation insufficient to meet their pedagogical needs. Conclusion: These findings challenge the assumption that digital trends signify a voluntary abandonment of the classroom. Instead, reliance on external resources is positioned as a reactive, compensatory strategy. Higher education institutions should prioritize revitalizing frontal instruction through enhanced clarity and focus to reduce dependency on off-campus platforms and restore the value of the campus experience. Full article

Physical Unclonable Functions (PUFs) represent a highly promising hardware security primitive, yet they face constraints of insufficient reliability and threats from modeling attacks. This paper designs a novel Feed-Forward Crossbar Matrix Arbiter PUF (FC-MA PUF). It incorporates an inter-stage crossbar structure, a feed-forward control system, and a mechanism for selecting reliable challenge-response pairs. These features significantly enhance the structural non-linearity and stability, substantially improving security and adaptability to a wider range of operating environments. It provides a high-strength authentication solution with low resource overhead for lightweight security-demanding devices such as IoT devices. The proposed FC-MA PUF has been successfully implemented on a Field-Programmable Gate Array (FPGA) platform. Experimental results for the selected 4-stage FC-MA PUF configuration show a bias, inter-chip uniqueness, and bit error rate (BER) of 49.88%, 49.68%, and 0.018%, respectively. Furthermore, the structure allows for flexible configuration of the number of feed-forward modules based on practical application requirements: a greater number of feed-forward modules enhances security but also leads to an increased BER and a decreased proportion of stable challenge-response pairs. Experimental results based on a training set of 1,000,000 challenge-response pairs demonstrate that: with two feed-forward units, the stable (Challenge Response Pair)CRP ratio is 39.72% and the Covariance Matrix Adaptation Evolutionary Strategies (CMA-ES) attack prediction success rate is 58.20%; with three units, the ratio decreases to 29.12% and the prediction rate drops to 54.91%; with four units, these values further decline to 20.18% and 52.33% respectively. These results confirm that the proposed FC-MA PUF effectively resists multiple modeling attacks, including Logistic Regression (LR), Support Vector Machine (SVM), and CMA-ES. Full article

The rapid integration of generative artificial intelligence into scientific publishing is reshaping how academic text can be produced, revised, and scaled. While transparent and limited use of AI for language support may be acceptable, a new structural vulnerability may be emerging in medical publishing: the large-scale production of short, plausible, and weakly individualized correspondence across multiple specialties. In this viewpoint, we describe and conceptualize a pattern that may be termed synthetic authorship, defined not as undisclosed AI use alone, but as a reproducible mode of scholarly output structurally facilitated by automation. We focus particularly on letters to the editor, a format that combines brevity, rapid editorial handling, and formal indexation, and may therefore be especially exposed to this phenomenon. Based on recurring patterns observed in PubMed-indexed literature, including unusually high publication velocity, abrupt thematic dispersion, and stylistic uniformity across unrelated domains, we argue that such outputs may challenge the authenticity, epistemic value, and editorial function of scientific correspondence. We do not present empirical proof of misconduct, but rather outline a conceptual framework for understanding this emerging risk and propose proportionate editorial safeguards, including cross-domain pattern detection and contextual assessment of authorship coherence. As AI lowers the threshold for generating domain-plausible commentary at scale, scientific publishing must adapt its integrity frameworks accordingly. In this context, vigilance toward synthetic authorship may become an essential component of editorial responsibility and post-publication quality control. Full article

Targeting resource-constrained Internet of Things (IoT) devices, this paper proposes Stuck-at-Fault Physical Unclonable Function (SAF-PUF), a lightweight Resistive Random-Access Memory (RRAM)-based PUF that exploits the intrinsic addresses of manufacturing-induced SAF defects as a stable entropy source. By using the coordinates of Stuck-at-1 (SA1) cells to seed a 32-bit Linear Feedback Shift Register (LFSR), SAF-PUF generates robust, variable-length responses with zero Bit Error Rate (BER) across a wide temperature range from −40 °C to 125 °C, without any error-correction circuitry. Experimental results based on 100,000 Challenge–Response Pairs (CRPs) demonstrate strong resilience against machine learning (ML) attacks, with prediction accuracies of logistic regression (LR), support vector machines (SVM), neural networks (NN) and convolutional neural networks (CNNs) remaining close to 50%. Moreover, a “use-then-conceal” mechanism is introduced to enhance post-authentication security, enabling response obfuscation with minimal cell reconfiguration. These features make SAF-PUF a high-security, low-overhead hardware root of trust suitable for IoT applications. Full article

This study examined how pedagogical strategies can support student-coaches’ (SCs) empowerment and promote preservice teachers’ (PSTs) professional learning within Sport Education (SE) seasons. Sixty-seven tenth-grade students (aged 15–18) participated in SE units taught by three PSTs (two males, one female, aged 22–25) enrolled in a master’s degree program in Teaching of Physical Education in Primary and Secondary Education in northern Portugal. Data were collected through participant observation, informal and focus group interviews, and PSTs’ reflective diaries within a Collaborative Action Research (CAR) framework and analyzed thematically. Three CAR cycles addressed key challenges: (1) encouraging SCs to assume responsibility for their role, (2) fostering inclusive and supportive team interactions, (3) strengthening SCs’ sport-specific and instructional knowledge. Guided by a facilitator, PSTs implemented strategies including pre-lesson meetings, structured communication routines, task-modification and feedback cards, accountability systems, and visual identification of SCs. Findings suggest that SCs’ empowerment was progressively constructed through interconnected psychological, relational and pedagogical processes, supported by structured mediation and iterative reflection. Simultaneously, engagement in CAR cycles enabled PSTs to develop adaptive instructional decision-making and mediation strategies. The study highlights how empowerment in SE is shaped through relational and pedagogical conditions and illustrates how CAR can foster reciprocal learning between SCs and PSTs in authentic teacher education contexts. Full article

Authentic learning is widely recognised as critical for graduate employability, yet embedding it across curricula presents challenges, including resourcing, time for redevelopment, and managing large-scale cultural change. Scalable approaches require pilot studies to explore how authentic learning principles can be implemented and scaffolded effectively. This paper presents a case study of an Australian university’s co-created ‘Authentic Learning Blueprint’, designed to embed industry/community engaged learning throughout the learner’s experience. Phase one involved a team of educators, drawing on insights from learners, and employer feedback to co-develop the Blueprint. The Blueprint allows learners to progress through scaffolded stages, Novice, Associate, and Emerging Practitioner, gaining discipline-specific and industry-ready skills through real-world project briefs and work-integrated learning experiences. The Blueprint distributes teaching and learning responsibilities across learners, educators, and industry/community in a three-way partnership model. Learning experiences were designed to reflect knowledge and skills relevant to professional practice. In phase two, the proof-of-concept was applied to two design units, one undergraduate and one postgraduate, and we tested acceptance and scalability, with positive student feedback. Phase three showcases how the Blueprint then informed curriculum redesign within the design school’s flagship course, including trials of ungraded assessment to further support authentic learning. The findings demonstrate that a co-created, scaffolded approach integrating industry-engaged experiences from enrolment to graduation can bridge the gap between academia and professional practice. This study contributes a practical framework for embedding authentic learning at scale, offering insights for institutions seeking to enhance employability through curriculum innovation. Full article

This work proposes a lightweight biometric key-binding scheme that adapts a PUF-style challenge–response mechanism to face geometry: a two-factor password and session nonce generate random challenge points, Gray-coded Euclidean distances to facial landmarks form responses, and a random key is bound by discarding selected positions so only a reduced subset, the nonce, and a key hash are stored. At authentication, a fresh response set is compared to the subset with a Hamming-distance tolerance, and bounded local search corrects residual errors; each successful session rotates the nonce and refreshes the ephemeral key. We frame this as a conceptual exploration of an interpretable, on-device, controlled-capture design niche—a per-session nonce-driven cancelable biometric key-binding mechanism—and we quantify the resulting security–usability trade-offs. Empirically, the scheme works under stable capture conditions with carefully tuned thresholds, and it is naturally suited to tightly controlled deployments (e.g., access kiosks) where it can also incorporate user-driven micro-gestures as an extra behavioral factor. While the construction is fragile under broader variability and leans on the second factor for security, it offers an alternative to existing mechanisms and a clear niche, and we present it as a conceptual exploration showing how CRP mechanisms can inform cancelable biometrics with per-session revocability. Full article

This paper critically examines Charles Taylor’s analysis in A Secular Age, with a focus on the concepts of authenticity, fragilization and cross-pressure. I explore the ethic of authenticity in relation to the ontological instability produced by exclusive humanism and consider how fragilization and cross-pressure reflect the fragmentation of our relation to the spiritual. At the same time, I engage with critical responses to Taylor that challenge his claims about authenticity and question the coherence and universality of fragilization and cross-pressure as social and cultural phenomena. I conclude that Taylor’s account of authenticity is fundamentally ambivalent, as it reproduces the rigid distinction between immanence and transcendence that the ethic of authenticity itself seeks ostensibly to destabilize. Full article

Rural tourism is defined as a tourism activity in which the visitor’s experience is linked to agricultural activities, rural lifestyles, and traditional cultures. In many geographical contexts, especially in Europe, because the rural economy is so deeply tied to family farming, this form of tourism is referred to as “agritourism”, even though agrotourism is a specific subset of rural tourism defined by the integration of tourism with a working farm or agricultural operation. The entry delineates the transformative dynamics of rural tourism in the context of global shifts towards personalized, experiential travel. It examines how contemporary tourists increasingly seek authentic and immersive experiences as a response to the superficiality of mass tourism. This trend leads travellers to engage deeply with local cultures, thereby fostering connections with community life and prioritizing sustainability. Amidst challenges such as environmental degradation and overtourism, rural tourism emerges as a viable alternative, offering unique, less-congested destinations that cater to travellers’ desire for exclusivity and genuine discovery. The paper traces the historical evolution of rural tourism from its European origins in mid-20th-century agricultural practices to its current status as a vital component of rural development strategies. Through a comparative analysis of two distinct regional scenarios, Europe and Oceania, this article elucidates how local contexts shape tourism practices. The analysis highlights the pivotal role of gastronomy in enriching tourist experiences and emphasizes the need for digital literacy and eco-effectiveness in rural tourism operations. Although the entry does not provide a comprehensive global perspective on rural tourism or a quantitative environmental account of the sector’s impact, it ultimately conveys that rural tourism is a critical engine of regional vitality and sustainability, illustrating the juxtaposition of historical roots and contemporary trends that define this evolving sector. Full article

Accurate identification of dynamic parameters, specifically natural frequency and damping ratio, is critical for optimizing the disturbance rejection performance of laser level self-leveling mechanisms. However, traditional Finite Element Analysis (FEA) often struggles to quantify micro-friction damping, while contact measurement methods introduce added mass interference. To address these challenges, this paper proposes an integrated framework combining Pulse-Window Software Lock-in (PWSL) sensing with a data-driven model updating strategy. Initially, a rigid-body dynamic model theoretically predicted a natural frequency (f_sim) of 2.987 Hz and a damping ratio (ζ_sim) of 0.1255. To acquire authentic responses, a non-contact Position Sensitive Detector (PSD) system was developed. The custom PWSL algorithm leverages the laser’s 10 kHz carrier to extract high-fidelity displacement signals, effectively suppressing broadband noise despite embedded hardware limitations. Experimental results demonstrated that the measured frequency (f_exp = 2.861 Hz) aligned well with predictions (4.22% error). In contrast, the measured damping ratio (ζ_exp = 0.1435) exceeded the simulation value by 14.34%, quantitatively revealing the energy dissipation caused by unmodeled bearing friction. Based on this disparity, the FEA model was inversely updated by introducing an equivalent friction coefficient, successfully reducing the damping prediction error to 0.97%. This study establishes a high-fidelity updated model, providing a reliable basis for the refined design of precision pendulum instruments. Full article

It is well-known that GNSS high accuracy solutions are increasingly vulnerable to jamming and spoofing attacks, posing significant challenges to their reliability, security, and accuracy. In the past years, GNSS communities have witnessed an increase in the frequency and sophistication of these attacks, driven, among other factors, by the widespread availability of low-cost, off-the-shelf equipment capable of denying or even totally misleading GNSS-based positioning systems. On the one hand, jamming attacks aim at inhibiting signal reception by introducing high-power noise or interference, leading to degraded performance or complete failure in determining position. Jamming detection mechanisms need to be traced to GNSS receiver mitigation measures at signal processing level to analyze the radio frequency (RF) environment or receiver behavior. Signal-to-noise ratio (SNR) monitoring, power spectrum analysis, and signal power monitoring are commonly used to detect anomalies in signal characteristics. Jamming is often indicated with the presence of a combination of one or more dedicated indicators, opening space to characterize different levels of jamming attack allowing to optimize a response at user level. On the other hand, detecting spoofing attacks requires different advanced techniques to identify anomalies in satellite signals, receiver behavior, or consistency of computed position data. Indicators regarding internal consistency checks, as well as unexpected evolutions of GNSS signals, are typically suspicious behaviors to be analyzed as possible attacks. Additionally, ensuring trust in the received navigation information by including cryptographic authentication mechanisms is key to quickly detecting some kinds of spoofing. This paper presents the latest enhancements on jamming and spoofing detection and mitigation mechanisms for GMV GSharp^® high accuracy and safe positioning solution. This new method, based on fuzzy logic systems, allows us to distinguish between different levels of attack and adapt the reactions to reduce the impact on the final user as much as possible. Additionally, test results obtained from real GNSS attacks datasets will be shown. Full article