Search Results (13,729)

Healing skin wounds is still difficult in many clinical situations, especially when the wounds are chronic or infected. These wounds often stay inflamed for long periods, and the risk of bacterial invasion is high. Oxidative stress tends to increase as well, while the formation of new blood vessels is often inadequate. Because of these factors, wound repair depends on the proper coordination of several biological events. These include basic antimicrobial activities, the control and resolution of inflammation, protection against oxidative damage, the rebuilding of collagen structures, and the development of new vascular networks. Traditional Chinese Medicine (TCM) provides many active compounds. These compounds work on many targets and through different pathways. They show good potential in wound treatment. But many TCM compounds have poor solubility in water. They are also unstable, have low bioavailability, and do not pass through the skin easily. These problems limit their use in clinical settings. Nanotechnology offers new ways to solve these problems. Nanodelivery systems can improve the solubility and stability of active compounds. They can also help the compounds enter the skin and stay in the wound area. Many types of nanocarriers have been developed, such as liposomes, polymer nanoparticles, nanogels, and inorganic nanomaterials. These systems can also provide controlled release or release that responds to the wound environment. This can make the treatment more accurate. In this review, we summarize how major TCM-derived compounds support wound repair and describe the biological mechanisms behind their effects. We also discuss recent nanodelivery approaches that aim to strengthen these therapeutic actions. These combinations can improve antibacterial performance, shape the immune response, reduce reactive oxygen species, and help the skin close more quickly. We also point out several challenges, such as concerns about material safety, the need for more consistent herbal extraction methods, gaps in mechanistic understanding, and the difficulty of producing these formulations on a large scale. Taken together, these points suggest that nanodelivery approaches using TCM-derived compounds still need more careful study and steady improvement before they can be used more widely in wound care. Full article

Introduction: Cystic fibrosis (CF) frequently presents prenatally with meconium ileus (MI), a condition associated with significant neonatal morbidity and long-term gastrointestinal complications. The advent of highly effective CFTR modulators, particularly elexacaftor/tezacaftor/ivacaftor (ETI), during pregnancy remains off-label, and their role as in utero therapy for affected fetuses of carrier mothers is still emerging. Methods: We conducted a narrative literature review using PubMed, Embase, and Scopus to identify published reports of in utero CFTR modulator therapy for MI between 2022 and 2026. Seven relevant studies were identified and qualitatively synthesized. Their findings were interpreted in comparison with the present case. Results: We describe the first Italian case of prenatal ETI therapy for fetal CF. At 32 weeks’ gestation, ultrasound (US) findings were suggestive of evolving MI. Both parents were carriers of F508del CFTR and subsequent testing confirmed fetal homozygosity. Following urgent multidisciplinary consultation and ethics committee approval, maternal ETI therapy was initiated at 33 weeks’ gestation. After 21 days of treatment, follow-up fetal US demonstrated improvement in bowel dilatation and hyperchogenity. The infant was delivered at 36 + 2, passed meconium spontaneously, and required no surgical intervention. Pharmacokinetic assessment showed substantial transplacental transfer of all three ETI components, with cord-to-maternal plasma ratios of 0.34 (elexacaftor), 2.48 (tezacaftor), and 0.58 (ivacaftor), and detectable concentrations in amniotic fluid. Postnatally, sweat chloride was elevated, and pancreatic function transitioned from initially preserved to pancreatic insufficiency within the first month of life. Conclusions: This case and literature review suggest that prenatal CFTR modulation may influence the early trajectory of CF, potentially by preventing MI and potentially delaying the progression to pancreatic insufficiency and potentially reducing later gastrointestinal complications. While evidence remains limited, these findings highlight a potential therapeutic window during fetal life and underscore the need for prospective data collection, structured registries, and harmonized clinical guidance in this evolving field. Full article

Generative Artificial Intelligence (GenAI), particularly Large Language Models (LLMs), is rapidly changing how higher education approaches teaching, learning, and assessment. In cybersecurity education, professional certification exams are key for measuring competence and helping professionals find better job offers, but there is little research on how GenAI systems perform in these exam settings. This study looks at how three popular LLMs, ChatGPT-5, Gemini-2.5 Pro, and Copilot-2.5 Pro, handle 183 practice questions from the CompTIA Security+ certification. The study used a two-phase evaluation: a domain-based assessment and a full-length practice exam that mirrors real certification tests. The researchers measured model performance with accuracy scores, chi-square tests for statistical differences, and an error taxonomy to spot patterns of mistakes important for education. All three GenAI systems scored above the passing mark, and there were no significant differences between them. Still, the error analysis showed ongoing conceptual and classification mistakes that did not show up in the overall accuracy scores. Our results show that GenAI systems can pass structured certification tests, but accuracy by itself does not fully measure professional skills. The study points out important issues for the reliability and validity of AI-based assessments in higher education and stresses the need for more realistic, concept-focused ways to evaluate GenAI in cybersecurity education. Full article

In fire emergency ventilation systems, EC (Electronically Commutated) internal-rotor axial fans are critical devices, but their high-speed operation generates aerodynamic noise often exceeding 90 dB (A). While struts are core structural components regulating flow field stability, their specific geometric impact on trailing-edge vortex shedding and noise generation mechanisms remains unclear. This study investigates three strut configurations: a hexagonal annular type, a hexagonal double-ring type, and a three-pronged type. A coupled numerical model was established using Large Eddy Simulation (LES) and the Ffowcs Williams and Hawkings (FW-H) acoustic analogy. The Q-criterion was employed to analyze vortical structures, with numerical predictions validated against experimental measurements in a semi-anechoic chamber. The results quantitatively demonstrate that optimizing the strut geometry significantly mitigates unsteady flow separation. The three-pronged strut (Model C) effectively dispersed high-velocity airflow, reducing the peak turbulent kinetic energy (TKE) at the inlet by 30% compared to the original design (Model a). Furthermore, Model C achieved a 6.7 dB reduction in the sound pressure level at the blade-passing frequency (BPF), alongside a 14.1% reduction in pressure pulsation amplitude near the blade tip. Structural optimization of struts enables synergistic control over turbulence distribution and pressure fluctuations. By disrupting the phase coherence of shed vortices, the optimized design fundamentally suppresses aerodynamic noise, advancing axial fan design toward precise quantitative aeroacoustic optimization. Full article

Sustainable ridge-based peanut production following winter wheat requires soil preparation technologies capable of simultaneously ensuring precise ridge formation, reduced energy consumption and efficient in situ utilisation of crop residues. This study aimed to develop and experimentally validate a combined soil preparation technology integrating shallow tillage, deep loosening and ridge formation within a single field pass, and to quantify its technological and biological performance. Field experiments were conducted using a prototype combined machine with analytically justified geometric parameters of the working tools, followed by multifactor optimisation and statistical modelling. Technological performance was assessed by soil fragmentation degree and draft resistance, while biological effects were evaluated using residue incorporation (Pz), biodegradation coefficient after 60 days (k₆₀) and dehydrogenase activity after 30 days (DHA₃₀). The results showed statistically significant nonlinear relationships between tool parameters and technological responses, with coefficients of determination exceeding 0.94 for soil fragmentation and 0.97 for draft resistance. The proposed technology increased residue incorporation efficiency by 15–20%, enhanced biodegradation intensity (k₆₀) by up to 18%, and reduced energy consumption due to single-pass operation compared with conventional multi-pass systems. A strong relationship between Pz and biological indicators confirmed the key role of residue placement in controlling microbial processes. These findings demonstrate that integrated control of soil processing and residue placement enables energy-efficient single-pass technologies for ridge-based peanut production systems. Full article

Background/Objective: Buccal delivery offers a potential route to circumvent gastrointestinal degradation and hepatic first-pass metabolism, but hydrophilic peptides typically exhibit limited mucosal permeation. Nanostructured lipid carriers (NLCs) have been proposed as delivery platforms capable of modulating interfacial interactions and improving mucosal transport. This study aimed to quantitatively evaluate the ex vivo buccal permeation of angiotensin II (Ang II), used as a hydrophilic peptide model, when associated with NLCs compared with free peptide under matched Franz diffusion cell conditions. Methods: Ang II-associated NLCs were prepared by melt emulsification combined with a low-energy injection technique. Particle size, polydispersity index, and zeta potential were determined by dynamic light scattering and laser Doppler electrophoresis. Association efficiency and drug loading were quantified by indirect spectrofluorometric analysis. Ex vivo permeation studies were conducted using porcine buccal mucosa mounted in Franz diffusion cells, and cumulative permeation, steady-state flux, and apparent permeability coefficients were calculated. Results: The NLCs exhibited nanometric size, moderate polydispersity, and association efficiency above 80%, and remained colloidally stable at 4 °C for 28 days. In ex vivo experiments, Ang II-associated NLCs showed measurable cumulative permeation, reaching approximately 9% after 2 h, whereas free Ang II was not detected in the receptor compartment under the tested conditions. Conclusions: This work provides a quantitative ex vivo buccal transport comparison of a hydrophilic peptide model delivered as NLC-associated versus free peptide under matched Franz cell conditions. The findings support further investigation of NLC-based approaches for buccal delivery of vasoactive peptides and provide a rational basis for future in vivo evaluation of mucosal delivery performance and systemic exposure. Full article

In semiconductor fabrication, abnormal behavior may first appear in a small subset of serial numbers before it is reflected in lot-level yield metrics. We present a monitoring framework that detects measurement item outliers using Z-scores, aggregates them into a serial-level cumulative-risk score, provides exploratory views of lot- and site-level trends, and ranks high-risk serials for follow-up. The approach is evaluated on an industrial semiconductor manufacturing dataset comprising 14,142 unique serials (${\mathrm{N}}_{\mathrm{s}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{a}\mathrm{l}}$ = 14,142). Because most TestResult labels are PASS, label-based yield shows little variation. In this setting, label-based yield alone is not informative enough for early monitoring, so we use outlier-based yield as the primary metric, defined as the proportion of serials with cumulative risk below the threshold ($\mathrm{R}\left(\mathrm{s}\right)<\mathrm{\tau }$, where $\mathrm{\tau }=10$). A sensitivity study of the outlier threshold $\mathrm{\kappa }$ ($\mathrm{\sigma }$-multiplier) shows that yield varies widely, from 61.66% at $\mathrm{\kappa }=3$ to above 99% at $\mathrm{\kappa }\ge 7$. This result shows the trade-off between detection sensitivity and inspection workload. Case studies of top-ranked serials show two recurring patterns: cumulative risk is driven either by isolated extreme deviations or by the accumulation of moderate deviations across multiple items. These results support the use of the proposed score for inspection prioritization. Full article

We analysed the formal inspection reports of 108 licensed British zoos covering three consecutive formal inspections, equivalent to a licensing period, under the Zoo Licensing Act 1981 (ZLA). We examined the compliance of zoos against animal welfare standards, animal escape protocols and engagement in conservation measures, as well as the effects of licence type, zoo association membership, and collection type. Of the 324 inspection reports analysed, 59 (18%) reported that the zoo had passed every assessed question. Failure to undertake the necessary number of escape drills was the most reported area of non-compliance in 134 (41%) of the reports. Across a total of 15,876 welfare assessment criteria, 14,067 (89%) were scored as compliant, but only 83 inspection reports (26%) recorded that the zoo had met all welfare standards. Zoos were commonly found to fall into one of three classes, which predicted their probability of participating in each of the five conservation measures within the ZLA. Farm parks were identified as the collection type performing least well across inspection categories. With British zoos being required to meet new standards from May 2027, we propose a number of changes which could aid inspection consistency and legislative enforcement and drive improvements. Full article

Vibration and noise generated by rail transit systems pose significant constraints on their environmental sustainability. Although extensive research has been conducted by scholars on vibration and noise in rail transit, quantitative studies specifically investigating the influence of train speed on the vibration and noise of elevated rail transit are scarce. Therefore, this study selected a typical elevated section of Wuhan Metro Line 21 and systematically performed field tests to measure the vibration and noise induced by trains passing at speeds of 20, 40, 60 and 80 km·h⁻¹. Based on the test results, the vibration characteristics of the rails, track slab, and bridge structure, as well as the radiation characteristics of wheel–rail noise and bridge structure-borne noise under different speeds, were investigated. The study further explored the impact of train speed variation on the vibration and noise of the elevated rail transit system. The results indicate that the vibration acceleration levels of both the outer and inner rails increase significantly with train speed. Each time the speed doubles, the vibration level rises by approximately 11.5 dB for the outer rail and 10.0 dB for the inner rail. The vibration of the track slab and bridge structure is notably lower than that of the rails. Each time the speed doubles, the vibration acceleration level at various measurement points increases by an average of about 8.5–9.0 dB. Wheel–rail noise is primarily concentrated in the frequency bands around 630 Hz and 3150 Hz. Each time the speed doubles, the trackside noise level increases by an average of approximately 7.2–7.6 dB(A). Noise measured under the bridge shows a distinct peak around 100 Hz, which aligns with the vibration frequency of the bottom slab. Due to the shielding effect of shrubs, noise in the 63–100 Hz frequency band is attenuated at measurement points above ground level. Each time the speed doubles, bridge structure-borne noise increases by about 4.5–5.0 dB(A), representing a lower growth rate compared to wheel–rail noise. The findings of this research are expected to contribute to vibration and noise reduction strategies and support the sustainable development of rail transit systems. Full article

Master–slave bilateral teleoperation systems face several practical challenges, including model uncertainties, time-varying communication delays, and environment-induced force disturbances. To address these issues, this paper proposes an adaptive super-twisting sliding-mode control scheme to achieve high-precision position tracking and real-time force-feedback synchronization. First, joint-space dynamic models are established for both the master and the slave manipulators, and a passive impedance model is adopted to characterize the interaction dynamics at the operator–master and environment–slave interfaces. Second, to attenuate measurement noise in the environment interaction force, a first-order low-pass filter is used to preprocess the raw force measurements, and a radial basis function neural network (RBFNN) is employed to approximate the environment torque online. Furthermore, a super-twisting sliding-mode controller is developed and combined with an adaptive law to compensate online for system uncertainties, including dynamic parameter variations and environment-induced force disturbances. The stability of the resulting closed-loop system is rigorously analyzed using Lyapunov stability theory. Finally, the effectiveness of the proposed method is validated through numerical simulations, virtual experiments conducted in the MuJoCo physics engine, and real-world hardware experiments. The results show that the proposed strategy achieves accurate position synchronization and force tracking while maintaining stable haptic interaction in the presence of bounded time-varying delays, parameter uncertainties, and external disturbances. Full article

Welded joints in API 5L X70 pipeline steel represent critical locations for pipelines intended for hydrogen service because welding can create microstructural inhomogeneity, stress concentrations, and uneven mechanical properties that can promote hydrogen-assisted degradation. In hydrogen-containing environments, these effects may manifest as reduced ductility, loss of fracture resistance, and increased cracking susceptibility, particularly in the weld metal and heat-affected zone. Therefore, welding procedures for X70 intended for hydrogen applications must be evaluated using systematic mechanical testing and microstructural characterization under defined hydrogen exposure conditions. The study investigates the detrimental effects of hydrogen on the mechanical integrity of pipeline materials, focusing on welded joints of the API 5L X70 steel, a candidate material for use in hydrogen-containing environments. The weldability and structural performance of the X70 pipeline steel joints in hydrogen environments, produced using automated multi-pass metal active gas (MAG) welding, was experimentally studied. Welding was performed on a DN800 pipe with precise control over welding parameters. Comprehensive analyses were conducted on the welded joints, including microstructure examinations, hardness measurements, slow strain rate testing in high-pressure gaseous H₂ with a N₂ baseline and fracture toughness testing. In high-pressure hydrogen SSRT showed a moderate reduction in ductility relative to nitrogen, with reduction of area decreasing from 81.2% (N₂) to 69.1 and 71.5% (H₂), while time-to-failure remained comparable (475 min in N₂ vs. 497 and 496 min in H₂) Ultimate tensile strength was not reduced (579 MPa in N₂ vs. 609 and 597 MPa in H₂). Secondary surface cracks were observed only on specimens tested in hydrogen. Fracture mechanics testing after hydrogen exposure yielded K_IH values of 58–59 MPa√m in the weld metal and 57–61 MPa√m in the HAZ, exceeding the 55 MPa√m acceptance threshold applied in this study. The results highlight the necessity of optimized welding techniques and targeted material analyses to ensure the safety and durability of pipelines in hydrogen-rich environments, thereby contributing to the development of reliable infrastructure for sustainable energy systems. Full article

Background and Clinical Significance: Mucopolysaccharidosis type VI is a rare lysosomal storage disorder due to arylsulfatase B enzyme deficiency, leading to progressive multisystem disease and complex airway. Acute respiratory infections can precipitate airway embarrassment. A structured treatment guideline is currently lacking. We present a 7-year-old MPS VI male with respiratory distress, highlighting the challenges in management. Case Presentation: Case review focusing on clinical presentation, imaging findings, and multidisciplinary decision-making during acute deterioration. A child diagnosed with MPS VI at the age of 3.5 years old, due to low arylsulfatase B enzyme activity and homozygous for c.275C>A p.(Thr92Lys) variant in the ARSB gene. At 7 years of age, he showed the signs of dyspnoea, increased respiratory effort with bilateral crepitations, and noisy breathing. Initial management included facemask oxygen, nebulised adrenaline, corticosteroids, and bronchodilators. Computer tomography scan of the neck and chest showed a complex upper airway, multiple tracheal narrowing, tortuosity, and an extra loop of truncus brachiocephalicus from the arch of the aorta. Potential interventions carried substantial risks due to abnormal airway and multisystem disease. Following extensive multidisciplinary discussion after careful consideration of the significant risks associated with invasive airway interventions, a shared decision was reached with the family to adopt a comfort-focused palliative care approach. Despite the best supportive care, the child unfortunately passed away after 3 months. The family was involved in every decision process and was fully supported. Conclusions: MPS VI is associated with complex airways and multisystem disease. Multidisciplinary decision-making with family is critical to safe and appropriate care. The rarity of the disease, lack of guidelines, complex airways, and multiple comorbidities make management challenging. Full article

In this study, a novel reverse friction stir processing (FSP) was adopted to investigate the effects of multi-pass reverse FSP on the microstructure, microhardness, bonding strength, and tribological properties of NiCrBSi coatings deposited on 6061-T6 aluminum alloy via atmospheric plasma spraying (APS). The results demonstrate that reverse FSP effectively eliminates pores, unmelted particles, and interlamellar defects in the as-sprayed coating without causing mechanical damage to the coating surface inside the processed zone. With an increase in processing passes, a micron-scale diffusion zone forms at the coating/substrate interface, transforming the bonding mechanism from mechanical interlocking to metallurgical bonding. Mechanical property tests reveal that compared with the as-sprayed state, the microhardness and tensile bonding strength of the three-pass FSPed coating are increased by 26.0% and 171.1%, respectively, indicating significantly improved mechanical properties. Tribological tests demonstrate that the main wear mechanism of the as-sprayed coating is severe abrasive wear. After multi-pass FSP, the wear mechanism of the coating transforms into a mixed wear mechanism. Among them, the FSP3 coating exhibits mild abrasive wear accompanied by local adhesive wear. Full article

Background: Artificial intelligence (AI) is increasingly incorporated into higher education. However, most empirical studies focus on technological adoption or learner satisfaction rather than on how pedagogical design, perceived learning impact, and student experience interact within AI-mediated learning environments. Understanding these relationships is essential to determine whether AI supports higher-order reasoning processes rather than merely increasing technological engagement. Objective: This preliminary study aimed to develop and evaluate a theory-driven AI-mediated pedagogical framework and examine relationships between pedagogical design, perceived learning impact, and student satisfaction in a university learning context. Methods: An observational educational evaluation was conducted during implementation of an AI-mediated instructional framework in an undergraduate physiotherapy course. The full academic cohort (n = 22) completed a 24-item questionnaire assessing seven pedagogical domains on a 5-point Likert scale. Descriptive statistics, Pearson correlations, exploratory regression modeling, and factor analysis were used to examine relationships among domains. Academic performance indicators were summarized descriptively. Results: Students reported high evaluations across all domains (means > 4.5/5). The strongest association with satisfaction was perceived learning impact (r = 0.79, p < 0.001). Moderate correlations were found for usability (r = 0.66), AI content quality (r = 0.61), pedagogical coherence (r = 0.58), critical thinking (r = 0.52), and ethical integration (r = 0.47). Academic pass rates exceeded 90%. Conclusions: Perceived learning impact emerged as the central mechanism linking AI-mediated instructional design to student satisfaction, suggesting that the educational value of AI depends on alignment with cognitively demanding learning processes. Full article

Construction sites implement various safety management activities, including toolbox meetings, risk assessments, and safety knowledge assessments, to reduce accidents. Multiple-choice question (MCQ)-based assessments are widely used to evaluate worker safety competencies. However, the effectiveness of MCQ assessments depends critically on distractor quality; incorrect options must be plausible enough to challenge uninformed respondents while remaining clearly distinguishable from knowledgeable ones. Manual distractor creation requires substantial expertise and is prone to inconsistency, whereas large language models (LLMs) often generate options that lack domain relevance. This paper proposes context-aware multipath adaptive safety scoring (CoMPASS), an algorithm that integrates construction safety domain knowledge with LLM capabilities for MCQ distractor generation. CoMPASS operates through two pathways: CoMPASS-H leverages a hierarchical hazard factor ontology for hazard identification questions, whereas CoMPASS-R uses hybrid retrieval-augmented generation (RAG) for risk control questions. An evaluation using 50 real construction accident cases with a robotic assessment test (RAT) using frontier LLMs as virtual examinees demonstrated that CoMPASS-R achieved a 90% quality pass rate, whereas all baseline methods failed to meet the composite quality criteria. The proposed framework provides a scalable approach to generating assessment content that supports effective safety management at construction sites. Full article