Search Results (16,574)

Background: Rotating and night-including shifts disrupt circadian alignment, impair sleep, and may reduce nurses’ physiological recovery. Objectives: This study aimed (1) to compare sleep quality and physical well-being across four shift schedules among hospital nurses and (2) to examine whether the association between rotating shifts and physical well-being was statistically consistent with an indirect association via sleep quality. Methods: In this cross-sectional study, 173 nurses from a tertiary hospital in Zagreb, Croatia, completed validated measures of sleep quality and physical well-being. Four shift patterns were analyzed—fixed morning, morning–afternoon, extended 12-h, and rotating three-shift—using Welch ANOVA and regression models. A bootstrapped mediation analysis (10,000 resamples; BCa method), interpreted as a statistical decomposition, estimated an indirect association consistent with sleep quality. Results: Rotating-shift nurses reported the poorest sleep (PSQI = 10.2 ± 2.6; p = 0.003). Physical well-being did not differ significantly across shift types (p = 0.08), although rotating-shift nurses had the lowest mean physical scores (24.3 ± 4.4). The rotating-shift subgroup was small (n = 16), limiting precision. The mediation analysis was statistically consistent with an indirect association between rotating shifts and physical well-being via sleep quality (ACME = −1.85, 95% CI −3.05 to −0.88; p < 0.001), while the proportion of the total association was imprecisely estimated. Conclusions: In this single-site cross-sectional sample, rotating night shifts were associated with poorer sleep and, on average, lower physical well-being; patterns were statistically consistent with an indirect association via sleep quality. Because exposure, mediator, and outcome were measured concurrently, these findings are hypothesis-generating and do not establish causality. Full article

Psoriasis is a chronic inflammatory disorder with immunological, metabolic, and environmental components. It affects not only the skin but also the nails, joints, and vascular system. A total of 50 patients with psoriasis and 28 healthy controls took part in this study. Serum samples were gathered both from the psoriatic group and the control group. Serum zyxin concentrations were measured via enzyme-linked immunosorbent assay (ELISA). Our results revealed that serum zyxin amounts were significantly higher in patients with psoriasis compared with the controls. However, no statistically significant correlations were found between serum zyxin levels and inflammatory or metabolic parameters in the psoriasis group. Similarly, there was no significant correlation between zyxin level and disease severity as assessed by the Psoriasis Area and Severity Index (PASI) score. To sum up, our study demonstrates that serum zyxin levels are significantly elevated in patients with psoriasis compared with controls. Nevertheless, the precise role of zyxin in the aetiology of psoriasis remains unclear. Further research is needed to clarify the function of this protein in the disease process and to explore its potential as a therapeutic target. Full article

Background: Computer-guided static implant surgery (CGSIS) is widely adopted to enhance the precision of dental implant placement. However, significant heterogeneity in reported accuracy values complicates evidence-based clinical decision-making. This variance is likely attributable to a fundamental lack of standardization in the methodologies used to assess dimensional accuracy. Objective: This scoping review aimed to systematically map, synthesize, and analyze the clinical methodologies used to quantify the dimensional accuracy of CGSIS. Methods: The review was conducted in accordance with the PRISMA-ScR guidelines. A systematic search of PubMed/MEDLINE, Scopus, and Embase was performed from inception to October 2025. Clinical studies quantitatively comparing planned versus achieved implant positions in human patients were included. Data were charted on study design, guide support type, data acquisition methods, reference systems for superimposition, measurement software, and accuracy metrics. Results: The analysis of 21 included studies revealed extensive methodological heterogeneity. Key findings included the predominant use of two distinct reference systems: post-operative CBCT (n = 12) and intraoral scanning with scan bodies (n = 6). A variety of proprietary and third-party software packages (e.g., coDiagnostiX, Geomagic, Mimics) were employed for superimposition, utilizing different alignment algorithms. Critically, this heterogeneity in measurement approach directly manifests in widely varying reported values for core accuracy metrics. In addition, the definitions and reporting of core accuracy metrics—specifically global coronal deviation (range of reported means: 0.55–1.70 mm), global apical deviation (0.76–2.50 mm), and angular deviation (2.11–7.14°)—were inconsistent. For example, these metrics were also reported using different statistical summaries (e.g., means with standard deviations or medians with interquartile ranges). Conclusions: The comparability and synthesis of evidence on CGSIS accuracy are significantly limited by non-standardized measurement approaches. The reported ranges of deviation values are a direct consequence of this methodological heterogeneity, not a comparison of implant system performance. Our findings highlight an urgent need for a consensus-based minimum reporting standard for future clinical research in this field to ensure reliable and translatable evidence. Full article

The flexible micro-structured surface found in biological skins exhibits remarkable drag reduction properties, inspiring applications in the aerospace industry, underwater exploration, and pipeline transportation. To address the challenge of efficiently replicating such structures, this study presents a composite flexible polymer film with a bio-inspired micro-dimple array, fabricated via an integrated process of precision milling, polishing, and micro-injection molding using thermoplastic polyurethane (TPU). We systematically investigated the influence of key injection parameters on the shape accuracy and surface quality of the film. The experimental results show that polishing technology can significantly reduce mold core surface roughness, thereby enhancing film replication accuracy. Among the parameters, melt temperature and holding time exerted the most significant effects on shape precision PV and bottom roughness R_a, while injection speed showed the least influence. Under optimized conditions of a melt temperature of 180 °C, injection speed of 60 mm/s, holding pressure of 7 MPa, and holding time of 13 s, the film achieved a micro-structure shape accuracy of 13.502 μm and bottom roughness of 0.033 μm. Numerical simulation predicted a maximum drag reduction rate of 10.26%, attributable to vortex cushion effects within the dimples. This performance was experimentally validated in a flow velocity range of 0.6–2 m/s, with the discrepancy between simulated and measured drag reduction kept within 5%, demonstrating the efficacy of the proposed manufacturing route for flexible bio-inspired drag reduction film. Full article

Optical frequency domain reflectometry (OFDR) is a widely used method for measuring optical lengths to backscattering points in optical fibers and integrated optical chips. However, its application for measuring absolute distances in other media, including free space, remains insufficiently studied. This work aims to solve two main challenges in developing a free-space distance measurement method based on OFDR. The first one is the adaptation of the standard OFDR method to air-based measurements, considering the complex and/or atypical composition of the optical line, including the combination of fiber and air, as well as differing chromatic dispersion. The second task is the calibration of the reflectometer to ensure high measurement accuracy. The article proposes a mathematical framework for eliminating the influence of chromatic dispersion, based on signal transformation and the introduction of an equivalent phase of the reference interferometer. The method was verified experimentally. The experimental setup included an OFDR system, a collimator, and a corner reflector movable along a 2-m rail. An important result is the development and testing of a dispersion compensation method, which eliminated peak broadening in the trace as the distance increased, maintaining its width at a level of tens of microns. Through calibration using an interferometric fringe-counting method, a frequency-to-distance conversion coefficient was determined, ensuring measurement accuracy up to 2 μm. Thus, the study demonstrates the feasibility of adapting OFDR for precise distributed distance measurements in free space and in complex or otherwise non-standard structured environments, significantly expanding the application scope of the technology. Full article

Background: Neurofibromatosis type 1 (NF1) is an autosomal dominant disorder characterized by cutaneous and subcutaneous neurofibromas, which impact quality of life. Dermoscopy-guided high-frequency ultrasound (DG-HFUS) integrates dermoscopy with 33 MHz ultrasound, enabling precise lesion localization and reproducible measurements. Objective: To characterize neurofibromas in NF1 patients using DG-HFUS and identify imaging parameters for diagnosis, monitoring, and treatment planning. Methods: 14 genetically confirmed NF1 patients underwent DG-HFUS imaging (Dermus SkinScanner). 100 neurofibromas were assessed for size, location, shape, contours, surface, echogenicity, global echogenicity, and posterior acoustic features. Results: Lesions were dermal (79%) or subcutaneous (21%), round (28%), ovoid (63%), or spiked (9%). Mean vertical and lateral diameters were 5.37 ± 2.66 mm and 2.28 ± 1.39 mm. All were hypoechoic; 62% homogeneous, 38% heterogeneous. Margins were well-defined in 57% and poorly defined in 43%. Posterior enhancement occurred in 3% and shadowing in 10%. Conclusions: DG-HFUS provides a detailed, reproducible assessment of neurofibromas, supporting differential diagnosis, surgical planning, and longitudinal monitoring. The evaluated imaging parameters offer objective insights for optimizing NF1 management. Future developments, including 3D reconstruction and AI-assisted analysis, may further enhance its clinical utility. Full article

Concrete structures suffering from Mg²⁺ environments may suffer severe damage, which mainly has something to do with the coupled effect among Cl⁻, SO₄²⁻, and Mg²⁺. Based on a systematic review of Web of Science and Scopus database (2000–2025), we first summarized the migration behavior, reaction paths, and interaction mechanism of Cl⁻, SO₄²⁻, and Mg²⁺ in cementitious matrices. Secondly, from the perspective of Cl⁻ cyclic adsorption–desorption breaking the passivation film of steel bars, SO₄²⁻ generating expansion products leads to crack expansion, then Mg²⁺ decalcifies C-S-H and transforms into M-S-H; we analyzed the main damage mechanisms, respectively. In addition, under the coexistence conditions of three kinds of ions, the “fixation–substitution–redissolution” process and “crack–transport” coupling positive feedback mechanism further increase the development rate of damage. Then, some anti-corrosion measures, such as mineral admixtures, functional chemical admixtures, fiber reinforcements, surface coatings, and new binder systems, are summarized, and the pros and cons of different anti-corrosion technologies are compared and evaluated. Lastly, from two aspects of simulation prediction for the coupled corrosion damage mechanism and service life prediction, respectively, we have critically evaluated the advances and problems existing in the current research on the aspects of ion migration-reaction coupled models, multi-physics coupled frameworks, phase-field methods, etc. We found that there is still much work to be conducted in three respects: deepening mechanism understanding, improving prediction precision, and strengthening the connection between laboratory test results and actual projects, so as to provide theoretical basis and technical support for the durability design and anti-corrosion strategies of concrete in complex Mg²⁺ environments. Full article

Quick Quantitative (QQ) immunoassays have been increasingly applied for the measurement of enrofloxacin (ENR) and ciprofloxacin (CIP) residues in aquaculture due to their speed and convenience. However, their quantitative reliability remains limited because measurement uncertainty (MU) is rarely considered during field testing. To enhance the metrological reliability of QQ-based residue analysis, we developed AquaUncertainty Pal, a mobile application that embeds real-time MU computation into the QQ workflow. The software automatically evaluates uncertainty sources during sampling and pipetting, visualizes the uncertainty budget, and guides users through optimized operations. The framework was validated against ISO/IEC 17025–accredited LC–MS/MS and assessed through a user study involving 20 frontline technicians. With the integrated software, pipetting precision (RSD) at 100 μL improved from 4.1% to 1.79%, the inter-operator variability (CV) decreased by 52%, and conformity assessment accuracy for samples near the maximum residue limit (MRL) increased from 25% to 70%. This suggests that real-time MU visualization effectively guided technicians toward consistent pipetting and interpretation behavior. These results demonstrate that integrating MU into the QQ workflow is both feasible and effective, substantially improving reliability and providing a replicable digital framework for uncertainty-informed residue monitoring in aquaculture. Full article

The single-step Rydberg excitation of cesium atoms requires a 319 nm ultraviolet laser with a narrow laser linewidth, high frequency stability, and high output power. To meet these requirements, in this work, we construct a high-power, single-frequency UV laser system at this wavelength. In this system, the frequency stabilization of the 1560.492 nm seed laser is critical to the performance of the ultraviolet laser. We employ nonlinear frequency conversion technology, the 1560.492 nm laser is frequency-doubled to 780.246 nm via a single pass through a PPLN crystal, and function integration is realized based on the modular parameter adjustment interface provided by the PyRPL software. Subsequently, the 1560.492 nm laser is stabilized to the $D_2$ hyperfine transition line of Rb-87 atoms using polarization spectroscopy (PS) and radio-frequency-modulated saturation absorption spectroscopy (RF-SAS). A comparative study of these two techniques shows that RF-SAS achieves superior stabilization performance, with the residual frequency fluctuation of the frequency-doubled laser being 1.07 MHz over 30 min. According to frequency doubling theory, the actual residual frequency fluctuation of the 1560.492 nm fundamental-frequency laser can be calculated as 0.535 MHz. Compared with our earlier scheme that utilized an ultra-low-expansion (ULE) optical cavity as a frequency reference, the present scheme eliminates the long-term drift induced by environmental factors. In contrast to frequency stabilization relying on discrete instruments, this integrated scheme significantly reduces the cost, simplifies the system architecture, saves space, and greatly enhances the flexibility and controllability of the system. It therefore provides a reliable and cost-effective solution to ensure the portability and practicability of high-performance UV laser sources. This high-precision frequency stabilization scheme directly guarantees the performance of the 319 nm UV laser, suppressing its linewidth below 10 kHz. Thus, it fully meets the stringent laser linewidth and frequency stability requirements for the single-step Rydberg excitation of cesium atoms and provides a reliable light source foundation for subsequent precision spectroscopic measurements. Full article

Mobile Global Positioning System (GPS) data offer a promising approach to inferring mental health status through behavioural analysis. Whilst previous research has explored location-based behavioural indicators including location clusters, entropy, and variance, persistent GPS measurement errors have compromised data reliability, limiting the practical deployment of smartphone-based digital phenotyping systems. This study develops and validates an algorithmic preprocessing method designed to mitigate inherent GPS measurement limitations in mobile health applications. We conducted comprehensive evaluation through controlled experimental protocols and naturalistic field assessments involving 38 participants over a seven-day period, capturing GPS data across diverse environmental contexts on both Android and iOS platforms. The proposed preprocessing algorithm demonstrated exceptional precision, consistently detecting major activity centres within an average 50-metre margin of error across both platforms. In naturalistic settings, the algorithm yielded robust location detection capabilities, producing spatial patterns that reflected plausible and behaviourally meaningful traits at the individual level. Cross-platform analysis revealed consistent performance regardless of operating system, with no significant differences in accuracy metrics between Android and iOS devices. These findings substantiate the potential of mobile GPS data as a reliable, objective source of behavioural information for mental health monitoring systems, contingent upon implementing sophisticated error-mitigation techniques. The validated algorithm addresses a critical technical barrier to the practical implementation of GPS-based digital phenotyping, enabling the more accurate assessment of mobility-related behavioural markers across diverse mental health conditions. This research contributes to the growing field of mobile health technology by providing a robust algorithmic framework for leveraging smartphone sensing capabilities in healthcare applications. Full article

Conventional RC snubber design relies on oscillation frequency-based estimation, which is often influenced by uncontrolled parasitic elements and can therefore limit the accuracy of surge voltage prediction in GaN HEMT flyback converters. To overcome this limitation, a drain-voltage assessment-based design approach is introduced, in which the snubber parameters are extracted directly from the measured voltage characteristics during the turn off transition. This method allows the surge voltage to be modeled more precisely and enables the snubber capacitance to be selected without unnecessary oversizing. Simulation results using the GaN Systems GS66516T device show that the proposed approach reduces the total power loss by 27.67% and 21.84% relative to two empirical design methods and achieves up to 53.64% lower loss compared with other RC combinations in the explored design space. The method suppresses the surge voltage from 877 V to 556 V, which closely aligns with the design target of 550 V, whereas the empirical methods result in maximum voltages of 637 V and 603 V. Finally, the thermal feasibility of the snubber resistor is analytically assessed, indicating that the estimated temperature rise remains within the safe operating range of commercial components. Full article

Ray tracing (RT) has become an important method for train-to-ground (T2G) wireless channel modeling due to its physical interpretability. In rail transit scenarios, RT suffers from modeling errors that arise due to environmental reconstruction and uncertainties in electromagnetic parameters, as well as dynamic phase errors caused by coherent multi-path superposition that is further triggered by such modeling errors. Phase errors significantly affect both the calibration accuracy and prediction precision of RT. Therefore, this paper proposes an intelligent RT calibration method based on local phase errors. The method builds a phase error distribution model and uses constraints from limited measurements to explicitly estimate and correct phase errors in RT-generated channel responses. Firstly, the method applies the Variational Expectation–Maximization (VEM) algorithm to optimize the phase error model, where the expectation step derives an approximate posterior distribution and the maximization step updates parameters conditioned on this posterior. Secondly, experiments are conducted using differentiable RT implemented in the Sionna library, which explicitly provides gradients of environmental and link parameters with respect to channel frequency responses, enabling end-to-end calibration. Finally, experimental results show that in railway scenarios, compared with calibration methods based on phase error-oblivious and uniform phase error, the proposed approach achieves average gains of about 10 dB at SNR = 0 dB and 20 dB at SNR = 30 dB. Full article

Background: Artificial intelligence (AI) is rapidly transforming clinical medicine by enabling earlier disease detection, personalized risk stratification, precision diagnostics, and optimized therapeutic decision-making across multiple specialties. Methods: This narrative review synthesizes the most recent evidence from prospective randomized controlled trials, large cohort studies, and real-world implementations of AI in cardiology, pulmonology, neurology, hepatology, pancreatic diseases, and other key areas of internal medicine. Studies were selected based on clinical impact, external validation, and regulatory approval status where applicable. Results: AI systems now outperform traditional clinical tools in numerous high-stakes applications: >88% freedom from atrial fibrillation at 1 year with AI-guided ablation, noninferior stent optimization versus OCT guidance, >95% sensitivity for atrial fibrillation and low ejection fraction detection on single-lead ECG, substantial increases in adenoma detection rate and melanoma triage accuracy, automated pancreatic cancer detection on routine CT with 89–90% sensitivity, and significant improvements in palliative care consultation rates and post-PCI outcomes using AI-supported telemedicine. Over 850 FDA-cleared AI devices exist as of November 2025, with cardiology and radiology dominating clinical adoption. Conclusions: AI has transitioned from experimental to clinically indispensable in multiple specialties, delivering measurable reductions in mortality, morbidity, hospitalizations, and healthcare resource utilization. Remaining challenges include external validation gaps, bias mitigation, and the need for large-scale prospective trials before universal implementation. Full article

Amphibious light sport aircraft (LSA) combine the versatility of land and water operations but suffer aerodynamic penalties from their inherent design requirements, limiting cruise performance. This study investigates two drag reduction features for a proposed high-performance amphibious LSA developed by Altavia Aerospace. The concept targets a cruise speed of 140 KTAS, using retractable wingtip pontoons and a novel retractable hull step fairing. A 1/5-scale flying model was built and flight tested to assess the aerodynamic benefits of these features and evaluate sub-scale flight testing as a tool for drag measurement. Estimated propulsive power and GPS-based speed data corrected for wind were used to compute an estimated 17% reduction in drag coefficient by retracting the pontoons. The hull step fairing showed no measurable gains, likely due to inconsistent battery voltage, despite literature indicating potential 5% drag savings. Drag measurement precision of 7–9% was achieved using the power-based method, with potential precision better than 3% achievable if the designed thrust data system were fully validated and an autopilot integrated. A performance estimation for Altavia Aerospace’s concept predicts a cruise speed of 134 KTAS at 10,000 ft. Achieving the target of 140 KTAS may require further aerodynamic refinement, with investigation of a tandem seating configuration to reduce frontal area recommended. The study provides an initial drag assessment of retractable wingtip pontoons and demonstrates the potential of sub-scale flight testing for comparative drag analysis—two novel contributions to the field. Full article

Ruminant livestock production faces increasing pressure to reduce environmental impacts while maintaining productivity and food security. This comprehensive review examines current strategies and emerging technologies for enhancing environmental sustainability in ruminant systems. The review synthesizes recent advances across four interconnected domains: genetic and genomic approaches for breeding environmentally efficient animals, rumen microbiome manipulation, nutritional strategies for emission reduction, and precision management practices. Specifically, genetic and genomic strategies demonstrate significant potential for long-term sustainability improvements through selective breeding for feed efficiency, methane reduction, and enhanced longevity. Understanding host–microbe interactions and developing targeted interventions have also shown promising effects on optimizing fermentation efficiency and reducing methane production. Key nutritional interventions include dietary optimization strategies that improve feed efficiency, feed additives, and precision feeding systems that minimize nutrient waste. Furthermore, management approaches encompass precision livestock farming technologies including sensor-based monitoring systems, automated feeding platforms, and real-time emission measurement tools that enable data-driven decision making. Integration of these approaches through system-based frameworks offers the greatest potential for achieving substantial environmental improvements while maintaining economic viability. In addition, this review identifies key research gaps including the need for standardized measurement protocols, long-term sustainability assessments, and economic evaluation frameworks. Future directions emphasize the importance of interdisciplinary collaboration, policy support, and technology transfer to accelerate adoption of sustainable practices across diverse production systems. Full article