Search Results (938)

Zero-Touch Network (ZTN) represents a cornerstone approach of Next Generation Networks (NGNs), enabling fully automated and AI-driven network and service management. However, their distributed and multi-domain nature introduces critical security challenges, particularly regarding service identity and data integrity. This paper proposes a novel blockchain-based framework to enhance the security of ZTN through two complementary mechanisms: decentralized digital identity management and oracle-assisted network monitoring. First, a Decentralized Identity Management framework aligned with Zero-Trust Architecture principles is introduced to ensure tamper-proof authentication and authorization in a trustless environment among network components. By leveraging decentralized identifiers, verifiable credentials, and zero-knowledge proofs, the proposed Decentralized Authentication and Authorization component eliminates reliance on centralized authorities, while preserving privacy and interoperability across domains. Second, the paper investigates blockchain oracle mechanisms as a means to extend data integrity guarantees beyond the blockchain, enabling secure monitoring of Network Services and validation of Service-Level Agreements. We propose a four-dimensional framework for oracle design, based on qualitative comparison of oracle types—decentralized, compute-enabled, and consensus-based—to identify their suitability for NGN scenarios. This work proposes an architectural and design framework for Zero-Touch Networks, focusing on system integration and security-aware orchestration rather than large-scale experimental evaluation. The outcome of our study highlights the potential of integrating blockchain-based identity and oracle solutions to achieve resilient, transparent, and self-managed network ecosystems. This research bridges the gap between theory and implementation by offering a holistic approach that unifies identity security and data integrity in ZTNs, paving the way towards trustworthy and autonomous 6G infrastructures. Full article

This study evaluated the feasibility, image quality, and referral accuracy of a patient-operated optical coherence tomography (OCT) device (SightSync) compared with technician-acquired Heidelberg OCT. This study was conducted in a Veterans Affairs retina clinic (Cleveland, Ohio), resulting in a predominantly male (98%) study population representative of the local veteran demographics. One hundred patients attempted self-administered OCT imaging after brief instruction, yielding 118 successful scans (59% of eyes) with no significant association between scan success and age, visual acuity, or diagnosis. Quantitative analysis of 142 paired images showed that SightSync produced interpretable scans with comparable sharpness to Heidelberg OCT, though signal- and intensity-based metrics (signal-to-noise ratio; SNR, contrast-to-noise ratio; CNR, entropy, pixel intensity; p90) were lower, consistent with hardware differences between a compact patient-operated prototype and a clinical-grade system. Among 121 high-quality SightSync scans, referral decisions demonstrated strong agreement with Heidelberg OCT, with a sensitivity of 83.9%, specificity of 75.6%, and a negative predictive value of 93.2%, indicating reliable exclusion of clinically significant pathology. These findings demonstrate that patients can independently acquire clinically interpretable OCT images and that SightSync provides safe, conservative triage performance—supporting its potential as a scalable community-based retinal imaging solution—while a review of unsuccessful scans has identified prototype modifications expected to further improve device feasibility. Full article

Superhydrophobic surfaces have gained considerable attention due to their ability to repel water and reduce surface adhesion, and they are now widely applied for self-cleaning, anti-fouling, anti-icing, and corrosion resistance purposes. In this study, either a computer numerical control (CNC) machine or photolithographic techniques were employed to fabricate molds with microwells, followed by soft lithography to obtain a polydimethylsiloxane (PDMS) micropillar array. An etching process was then carried out. It was found that, as etching time increased, the diameters of micropillars decreased, leading to a decrease in the solid fraction of the composite surface and increases in contact angles. When the ratios of spacing to diameter (W/D) and of height to diameter (H/D) both exceeded 1.5, the contact angle was found to exceed 150° and the original PDMS micropillar surface with a contact angle of around 135° became superhydrophobic. A drastic decrease in sliding angle was also observed at this threshold. Changes in contact angles with different W/D values were in good agreement with values calculated using the Cassie–Baxter equation, and the droplet state was verified by a pressure balance model. Meanwhile, the PDMS etching rate when using acetone as the solvent was approximately 6–8 times faster than that when using 1-Methyl-2-pyrrolidone (NMP), a result which is comparable to data in the literature. Full article

Early spring frost is a major meteorological hazard during the Apple Flowering period. To improve frost event prediction, this study proposes a hybrid 1D-CNN-BiLSTM-Attention model, with its core novelty lying in the integrated dual attention mechanism (Self-attention and Cross-variable Attention) and hybrid architecture. The 1D-CNN extracts extreme points and mutation features from meteorological factors, while BiLSTM captures long-term patterns such as cold wave accumulation. The dual attention mechanisms dynamically weight key frost precursors (low temperature, high humidity, calm wind), aiming to enhance the model’s focus on critical information. Using 1997–2016 data from Luochuan (four variables: Ground Surface Temperature (GST), Air Temperature (TEM), Wind Speed (WS), Relative Humidity (RH)), a segmented interpolation method increased temporal resolution to 4 h, and an adaptive Savitzky–Golay Filter reduced noise. For frost classification, Recall, Precision, and F1-score were higher than those of baseline models, and the model showed good agreement with the actual frost events in Luochuan on 6, 9, and 10 April 2013. The 4 h lead time could provide growers with timely guidance to take mitigation measures, alleviating potential losses. This research may offer modest technical references for frost prediction during the Apple Flowering period in similar regions. Full article

Materials with nonlinear conductivity are promising for electric field grading in various electrical and electronic devices because of their self-adaptability. In this study, we reported a nonlinear mechanism in fluorinated multi-wall carbon nanotube (F-MWCNT) clusters based on partial discharge in their porous structure. Excellent nonlinear conductivity featuring a low threshold electric field of around 2 kV/mm and a wide range of switching fields was observed after loading an ultra-low F-MWCNT loading ratio of 0.5 wt% into the UV-cured resin. Both experimental and theoretical analyses were performed to explain the underlying nonlinear mechanism. The improved electric field mitigation effect of the composite with F-MWCNT compared with the conventional inorganic fillers like SiC was validated by a flashover test in compressed SF₆ gas. Simulations were also conducted to explain the flashover threshold improvement considering the generation of seed electrons for ionization, which was in agreement with the experimental results. Full article

Background/Objectives: Children with inflammatory bowel disease (IBD) are managed with multi-modal treatment strategies, including non-clinical components such as the development of self-management skills. Assessment tools have been developed to quantify such traits, and parents may be asked to provide proxy reports on behalf of their child. The aim of this study was for child/parent dyads to complete a self-management skills assessment tool [IBD-STAR] to assess the agreement level between reports. Methods: Children aged ≥10 years with IBD, and one parent/caregiver, were recruited from three tertiary care centers in New Zealand, Australia, and Italy [translated version]. IBD-STAR is scored as completing skills independently [score = 2], with help [score = 1], or not at all [score = 0]. Individual agreement was assessed as a proportion of the maximum agreement on items, category agreement as inter-rater reliability using Gwets AC1 coefficient, and aggregate agreement as a Bland–Altman plot and correlations between child/parent percentage scores. Results: Fifty child/parent dyads participated; child mean age of 14.5 years (±2.4), 31 (62%) female, and 31 (62%) had Crohn’s disease and 19 (38%) ulcerative colitis. At the individual level, the mean proportional agreement was 0.70 (±0.15), equating to complete agreement on ≥12 IBD-STAR items. Category agreement was in the range of 44–94% for items, parents were more likely to underestimate self-management skills, and inter-rater reliability ranged from poor to very good for items, and ‘good’ overall. Aggregate agreement showed high correlation between child/parent % scores (R 0.77, p < 0.001, CI 0.63 to 0.87), and 47 (94%) of the pairs had % scores within two standard deviations of each other. No level of agreement was associated with any independent variable. Conclusions: Parental proxy reports of self-management skills using IBD-STAR had acceptable agreement. The trend towards parental underestimation should be considered when child self-report cannot be assessed. Full article

(1) Background: Pain assessment still relies primarily on subjective self-report. To address these limitations, we developed Piq, an EEG-based index derived from beta-band brain activity (Piq_β) aimed at providing objective pain identification and quantification. (2) Methods: The study combined cross-sectional and longitudinal designs. Resting-state brain activity was recorded for five minutes, and EEG signals were preprocessed using a dedicated algorithm. Piq_β performance was assessed by identifying an optimal cutoff to discriminate pain from no pain, evaluating its association with VNRS, and estimating agreement using a modified concordance criterion (exact match or ±1 category). A graded scale was also established to classify pain into distinct categories, according to intensity. (3) Results: An optimal cutoff of 10% for Piq_β yielded 97.8% sensitivity and 88.2% specificity. Piq_β correlated with self-reported scores (ρ = 0.60, p < 0.0001) with acceptable agreement (mean bias −1.02), accounting for clinically acceptable discrepancies. Five levels of pain were proposed, and Piq_β demonstrated the ability to track intra-individual fluctuations over time, accounting for clinically acceptable discrepancies. (4) Conclusions: These findings provide strong evidence to support the Piq_β index as a valuable complement to subjective pain ratings. Full article

This study attempted to develop and validate a data-driven simulation model that integrates field-measured data to assess the power requirement and fuel consumption characteristics of a self-propelled collector. The collector is a hydrostatic transmission-based, crawler-type platform designed for garlic and onion harvesting, equipped with multiple hydraulic subsystems for collection and sorting. During field experiments, the power requirements of each subsystem and fuel flow rate were recorded, and Willans line method was applied to estimate engine power and subsystem power transmission efficiencies. Because many small agricultural machines do not support electronically instrumented engines (e.g., CAN-bus/ECU-based measurements), the proposed model was formulated as a data-driven, low-order representation derived from on-site measurements rather than a full physics-based model. Using the identified parameters, the simulation framework predicts engine power and fuel efficiency under various operating conditions. The simulation results exhibited high agreement with field data, achieving R² and mean absolute percentage error values of 0.935–0.981 and 1.79–4.18%, respectively, confirming reliable reproduction of real field performance. A comprehensive analysis of the simulation results revealed that both engine speed and travel speed significantly influence power distribution and fuel rate, while also indicating that hydraulic working power is the dominant contributor to total power demand at higher engine speeds. These findings provide practical guidance for improving the fuel efficiency of compact self-propelled collectors. Full article

Effective upper-extremity rehabilitation requires intensive and precise movement training, yet conventional therapies lack accurate motion tracking. Robotic exoskeletons address this limitation but are often hindered by ergonomic misalignment and limited adaptability. The AssistOn-Arm, a novel self-aligning exoskeleton, integrates ergonomic design and back-drivable actuation to enhance comfort and facilitate natural user interaction. This study aimed to assess the usability and ergonomics of the device in healthy participants and to conduct a pilot clinical evaluation in individuals with upper-extremity impairments. Thirty healthy participants and twelve patients with shoulder impairments performed predefined tasks under participant-active and device-active conditions. Kinematic data captured concurrently with AssistOn-Arm and Xsens MVN demonstrated strong agreement between conditions. Quantitative analysis revealed no significant differences (p > 0.05) in flexion, elevation, abduction–adduction, and external rotation, indicating reliable alignment with natural joint axes. Significant differences (p < 0.05) were observed only in sagittal hyperextension and internal rotation, reflecting device mechanical constraints. The study confirms the clinical feasibility of AssistOn-Arm as a sensor-driven, self-aligning exoskeleton that bridges engineering innovation and precision rehabilitation, paving the way for its integration into clinical practice. Full article

Monitoring the health of power lines (PL) is essential for ensuring reliable power delivery, facilitating predictive maintenance, and maintaining a resilient grid infrastructure. Given the extensive length of PL networks, large numbers of wireless sensor nodes must be deployed, often in remote and harsh environments where battery replacement is costly and impractical. To address these limitations, this work proposes a hybrid energy-harvesting approach that combines piezoelectric and photovoltaic (PV) technologies to enable long-term, battery-free PL monitoring. The primary energy source is a compact, tunable, magnetically coupled piezoelectric vibrational energy harvester (VEH) that exploits local magnetic field distribution, inducing mechanical excitation of a cantilever and enabling the harvesting of vibrational energy near the PL at a frequency of 50 Hz. A complementary PV harvester is integrated to ensure operation during power outages or conditions where the piezoelectric excitation is reduced, thereby enhancing system robustness. Electromechanical characterization and a lumped-parameter model show good agreement with experimental results of the proposed VEH. The system is validated both on a PL test bench (5 A–10 A) and through inertial excitation using an electrodynamic shaker, demonstrating stable performance across a wide range of operating conditions. The combined hybrid architecture highlights a promising pathway toward self-sustaining, maintenance-free sensor nodes for next-generation power line monitoring. Finally, we demonstrate the feasibility of using such system for powering a WSN node by comparing the power produced by the proposed system with the power consumption of a potential application. Full article

Illustrated digital picture books are widely used for second-language reading and vocabulary growth. We ask how close current generative AI (GenAI) tools are to producing such books on demand for specific learners. Using the ChatGPT-based Learning And Reading (C-LARA) platform with GPT-5 for text/annotation and GPT-Image-1 for illustration, we ran three pilot studies. Study 1 used six AI-generated English books glossed into Chinese, French, and Ukrainian and evaluated them using page-level and whole-book Likert questionnaires completed by teachers and students. Study 2 created six English books targeted at low-intermediate East-Asian adults who had recently arrived in Adelaide and gathered student and teacher ratings. Study 3 piloted an individually tailored German mini-course for one anglophone learner, with judgements from the learner and two germanophone teachers. Images and Chinese glossing were consistently strong; French glossing was good but showed issues with gender agreement, register, and naturalness of phrasing; and Ukrainian glossing underperformed, with morphosyntax and idiom errors. Students rated tailored English texts positively, while teachers requested tighter briefs and curricular alignment. The German pilot was engaging and largely usable, with minor image-consistency and cultural-detail issues. We conclude that for well-supported language pairs (in particular, English–Chinese), the workflow is close to classroom/self-study usability, while other language pairs need improved multi-word expression handling and glossing. All resources are reproducible on the open-source platform. We adopt an interdisciplinary stance which combines aspects taken from computer science, linguistics, and language education. Full article

Background: Accurate deformity classification and fusion-level planning are essential in adolescent idiopathic scoliosis (AIS) surgery and are traditionally guided by Cobb angle measurement and the Lenke system. Multimodal large language models (LLMs) (e.g., ChatGPT-4.0; Claude 3.7 Sonnet, Gemini 2.5 Pro, DeepSeek-R1-0528 Chat) are increasingly used for image interpretation despite limited validation for radiographic decision-making. This study evaluated the agreement and reproducibility of contemporary multimodal LLMs for AIS assessment compared with expert spine surgeons. Methods: This single-center retrospective study included 125 AIS patients (94 females, 31 males; mean age 14.8 ± 1.9 years) who underwent posterior instrumentation (2020–2024). Two experienced spine surgeons independently performed Lenke classification (including lumbar and sagittal modifiers) and selected fusion levels (UIV–LIV) on standing AP, lateral, and side-bending radiographs; discrepancies were resolved by consensus to establish the reference standard. The same radiographs were analyzed by four paid multimodal LLMs using standardized zero-shot prompts. Because LLMs showed inconsistent end-vertebra selection, LLM-derived Cobb angles lacked a common anatomical reference frame and were excluded from quantitative analysis. Agreement with expert consensus and test–retest reproducibility (repeat analyses one week apart) were assessed using Cohen’s κ. Evaluation times were recorded. Results: Surgeon agreement was high for Lenke classification (92.0%, κ = 0.913) and fusion-level selection (88.8%, κ = 0.879). All LLMs demonstrated chance-level test–retest reproducibility and very low agreement with expert consensus (Lenke: 1.6–10.2%, κ = 0.001–0.036; fusion: 0.8–12.0%, κ = 0.003–0.053). Claude produced missing outputs in 17 Lenke and 29 fusion-level cases. Although LLMs completed assessments far faster than surgeons (seconds vs. ~11–12 min), speed did not translate into clinically acceptable reliability. Conclusions: Current general-purpose multimodal LLMs do not provide reliable Lenke classification or fusion-level planning in AIS. Their poor agreement with expert surgeons and marked internal inconsistency indicate that LLM-generated interpretations should not be used for surgical decision-making or patient self-assessment without task-specific validation. Full article

Fascia research suffers from definitional fragmentation, with no universal agreement about what fascia actually is, why it matters, or how to define it. Researchers often pursue lines of inquiry based on their existing expertise, yet traditional and newer approaches that might resolve these issues frequently conflict. To address this challenge, the authors use a hermeneutic framework to integrate their combined half century of anatomical experience with a narrative literature synthesis. They propose that fascia functions as a stochastic morphogenetic field rather than a discrete anatomical system, a stochastic process displaying opportunistic dynamics at atomic, molecular, and cellular scales that produces deterministic mechanical properties at macroscopic tissue levels. Four key conclusions emerge: (1) anatomical “virtual spaces” are hyaluronic acid (HA)–tissue manifolds tightly coupled with calcium coordination; (2) fascia functions as a stochastic morphogenetic field where clinically and educationally relevant deterministic patterns emerge; (3) a conceptual framework for context-flexible fascial nomenclature; (4) hermeneutic approaches enable synthesis across theoretical domains. The conclusions support the understanding of HA-mediated EMT/MET plasticity and its “Go or Grow” phenotypes as central conduits for both healing and cancer progression. Understanding the stochastic nature of fascia is thus essential for physicians as well as clinicians in the allied health setting. Optimal fascia-aware movement and manual therapy interventions are those that recognize fascia as a self-adapting morphogenetic field. Full article

Background/Objectives: Traditional dietary monitoring methods such as 24 h recalls rely on self-report, leading to recall bias and underreporting. Similarly, dietary control approaches, including portion control and calorie restriction, depend on user accuracy and consistency. Augmented reality (AR) offers a promising alternative for improving dietary monitoring and control by enhancing engagement, feedback accuracy, and user learning. This systematic review aimed to examine how AR technologies are implemented to support dietary monitoring and control and to evaluate their usability and effectiveness among adults. Methods: A systematic search of PubMed, CINAHL, and Embase identified studies published between 2000 and 2025 that evaluated augmented reality for dietary monitoring and control among adults. Eligible studies included peer-reviewed and gray literature in English. Data extraction focused on study design, AR system type, usability, and effectiveness outcomes. Risk of bias was assessed using the Cochrane RoB 2 tool for randomized controlled trials and ROBINS-I for non-randomized studies. Results: Thirteen studies met inclusion criteria. Since the evidence based was heterogeneous in design, outcomes, and measurement, findings were synthesized qualitatively rather than pooled. Most studies utilized smartphone-based AR systems for portion size estimation, nutrition education, and behavior modification. Usability and satisfaction varied by study: One study found that 80% of participants (N = 15) were satisfied or extremely satisfied with the AR tool. Another reported that 100% of users (N = 26) rated the app easy to use, and a separate study observed a 72.5% agreement rate on ease of use among participants (N = 40). Several studies also examined portion size estimation, with one reporting a 12.2% improvement in estimation accuracy and another showing −6% estimation, though a 12.7% overestimation in energy intake persisted. Additional outcomes related to behavior, dietary knowledge, and physiological or psychological effects were also identified across the review. Common limitations included difficulty aligning markers, overestimation of amorphous foods, and short intervention durations. Despite these promising findings, the existing evidence is limited by small sample sizes, heterogeneity in intervention and device design, short study durations, and variability in usability and accuracy measures. The limitations of this review warrant cautious interpretation of findings. Conclusions: AR technologies show promise for improving dietary monitoring and control by enhancing accuracy, engagement, and behavior change. Future research should focus on longitudinal designs, diverse populations, and integration with multimodal sensors and artificial intelligence. Full article

Background/Objectives: Glaucoma affects over 70 million people worldwide and is a major cause of irreversible blindness, with elevated intraocular pressure (IOP) as the only modifiable risk factor. Conventional techniques like Goldmann applanation tonometry (GAT) are widely used but cannot provide continuous or nocturnal monitoring, limiting the detection of pressure peaks relevant to disease progression. Emerging technologies, including home-based devices, wearable sensors, such as contact lens-based sensors (CLBS), and implantable biomedical microelectromechanical systems (bioMEMS), offer more comprehensive and continuous assessment of IOP patterns. Thus, this scoping review aimed to map the available evidence on technologies for continuous IOP monitoring, summarizing their performance and agreement with traditional tonometry. Methods: A systematic search of electronic databases was conducted to identify studies published in the last 10 years evaluating self-tonometry devices, CLBS, or implantable systems designed for continuous IOP monitoring. Two reviewers independently screened articles, applied eligibility criteria, charted relevant data, including device characteristics and agreement with GAT, and reported clinical applications. Results: Self-tonometry devices demonstrated generally good agreement with GAT while enabling patients to monitor IOP outside clinical settings. These devices provided valuable information on diurnal and nocturnal IOP fluctuations, especially in individuals with rapid progression or those undergoing postoperative follow-up. BioMEMS-based wearable and implantable sensors showed promise for continuous long-term monitoring and revealed previously unrecognized fluctuation patterns, including activity-related changes. Conclusions: Emerging IOP-monitoring technologies appear to complement standard clinical methods by offering more detailed IOP profiles. Their integration into clinical practice may support individualized risk assessment and improved management of glaucoma progression. Full article