Search Results (248,706)

Against the backdrop of accelerating urbanization and population aging, urban parks have emerged as significant venues for enhancing the physical and mental well-being of older adults. The age-friendly quality of these spaces is directly linked to health equity and urban inclusiveness. Using the high-density historic district of Beilin in Xi’an as a case study, we developed an innovative assessment tool to evaluate the age-friendliness of park walking environments. Guided by the Health Impact Assessment (HIA) framework, this tool integrates subjective perceptions and objective data to diagnose environmental strengths and weaknesses across four dimensions: accessibility, safety, comfort, and health-related interactivity. Based on multi-source data and quantitative analysis, the study revealed key variations in the age-friendly attributes of different parks. Our field assessment focused on three representative park types: urban comprehensive, historic–cultural, and community leisure parks. The key findings are: (1) Safety was perceived by experts as the most critical dimension for older adults’ health experience, with a weight of 0.49, accounting for nearly half of the total. However, significant variations exist in safety quality across different types of parks. (2) Age-friendly performance differed profoundly among park types. Benefiting from systematic management, the urban comprehensive park achieved balanced performance and a total score of 84.87. In contrast, the historic–cultural park, constrained by its linear morphology and historical functions, scored the lowest at 66.03, exhibiting notable deficits in safety and comfort. The community leisure park, while vibrant in community activity, attained an intermediate score of 74.76 due to insufficient attention to safety details. (3) The assessment outcomes highlight the association of park typology, site selection, and design sophistication with the lived experience and potential health benefits for older adults. This study provides a refined evaluation tool and tailored optimization strategies for the age-friendly renovation of diverse park types. Full article

Tiltable quadrotors have the ability of independent control of position and attitude, which can be more flexible in complex task scenarios. However, the inherent unmodeled dynamics, model uncertainties, and external disturbances pose significant challenges to the control system design. Aiming at the the control problem of tiltable quadrotors, this paper proposes a hierarchical adaptive coupling/disturbance utilization control strategy. First, an error-dynamics model is developed, explicitly incorporating coupling effects and lumped disturbances. Then, hierarchical adaptive coupling/disturbance utilization mechanisms are designed to adaptively exploit coupling and disturbances to improve system performance. Subsequently, super-twisting higher-order sliding-mode observers and robust tracking control laws are synthesized to estimate lumped disturbances and guarantee system robustness. Finally, through theoretical analysis, the stability of the closed-loop system and the role of hierarchical adaptive coupling/disturbance utilization mechanisms are elucidated. The effectiveness of the proposed control strategy is validated through simulations and flight experiments. Full article

The intelligent detection of asphalt pavement cracks has become increasingly important for ensuring service performance of road infrastructure. Traditional manual detection has significant safety hazards and insufficient accuracy. Furthermore, existing deep learning models still face challenges, including missed detection, false alarms, and poor performance in small target detection under complex conditions. This investigation adopts unmanned aerial vehicles (UAVs) to acquire pavement distress information and develops an intelligent detection approach for asphalt pavement crack based on improved YOLOv8s. First, the Spatial Pyramid Pooling Fast (SPPF) module is replaced with the Spatial Pyramid Pooling Fast with Cross Stage Partial Connections (SPPFCSPC) module in the backbone network to enhance the multi-scale feature fusion capability. Secondly, the Convolutional Block Attention Module (CBAM) module is introduced to the neck network to optimize the feature weights in both channel and spatial attention. Meanwhile, the Efficient Intersection over Union (EIoU) loss is adopted to improve accuracy. Finally, the Crack_Dataset is established, and the ablation experiments are conducted to verify the reliability of the detection model. The research indicates that the improved model achieves Precision, Recall, and mAP@0.5 of 83.9%, 79.6%, and 83.9%, respectively, representing increases of 1.5%, 1.3%, and 1.4%, compared with the baseline model. In comparison with mainstream object detection algorithms such as YOLOv5s and YOLOv8s, the proposed method attains an F1-score, mAP@0.5, and mAP@[0.5–0.95] of 0.82, 83.9%, and 46.6%, respectively, demonstrating a performance improvement. Based on the improved detection model, a pavement crack detection system was designed and implemented using PyQt5. This system supports image, video, and real-time camera input and detection. Full article

Accurate prediction of shipping freight indices, represented by the Baltic Dry Index (BDI), is crucial for operational decision-making and risk management in the shipping industry. Existing models mainly rely on historical time-series data and often overlook the influence of unstructured information such as market sentiment. To address this limitation, this study proposes a dynamic freight rate prediction framework integrating a shipping text sentiment index. First, a shipping news sentiment index is constructed using a RoBERTa-based pre-trained model to quantify the impact of market sentiment on freight rate fluctuations. Second, the BDI series is decomposed and reconstructed through Variational Mode Decomposition (VMD) and Fuzzy C-Means (FCM) clustering to extract multiscale features. Finally, a deep learning based multi-step prediction model is developed by incorporating the sentiment index into the forecasting process. Empirical results show that the proposed model significantly outperforms benchmark models without sentiment information in terms of MAE, RMSE, and R², and demonstrates greater robustness under extreme market conditions. These findings provide a novel methodological framework for improving freight rate forecasting accuracy and offer practical decision support for shipping enterprises. Full article

Cardiometabolic abnormalities, which are common in diabetes patients, can be alleviated through exercise. We examined the specific effects of walking (4–5 METS) on diabetic patients’ cardiac function in a randomized study. Patients with type 2 diabetes (metformin-, insulin-, and diet-controlled; n = 32) were randomized to a 12-week walking intervention (40 min, three times/week; n = 16) or standard care (control group, n = 16). We prospectively compared metabolic, anthropometric, cardiac function and cardiorespiratory fitness parameters between the two groups via linear regression. Compared with that of the control group, the postintervention global strain of the walking group improved significantly (−19.0 (±3.0) vs. −20.9 (±2.6), Diff = −1.92 (CI = −2.61–−1.24), p < 0.001; control: −18.7 (±3.2) vs. −18.9 (±3.6), Diff = −0.19 (CI = −1.00–0.63), p = 0.650), with a pre/post between-group estimated mean difference of ~−1.73 (CI = −2.78–−0.69; p < 0.001). Abdominal circumference (−3 cm (CI = −4.41–−1.59), p < 0.001)), resting heart rate/bpm (−6.50 (CI = −9.69–−3.31, p < 0.001)) and body fat percentage (−2.74 (CI = −4.71–−0.76, p < 0.007)) changed significantly only in the walking group. Spiroergometric data revealed improved oxygen uptake in the walking group vs. the control group: abs_VO2max/L·min⁻¹ (0.19 (0.05–0.33), p < 0.008); rel_VO2max/mL·kg⁻¹·min⁻¹ (2.43 (1.03–3.83), p < 0.001). This first randomized intervention study of supervised walking in patients with type 2 diabetes demonstrated that even moderate-intensity physical activity (such as walking) can improve cardiac function and body composition, reduced waist circumference, and increased oxygen uptake, making it a cost-effective treatment with significant preventive and restorative benefits for cardiac function and body composition in these patients. Full article

During hemorrhagic procedures, autotransfusion is one of the main strategies for patient blood management. While conventional cell savers only concentrate red blood cells due to the centrifugation method, the innovative same™ autotransfusion medical device (i-SEP, Nantes, France), based on a hollow-fiber filtration technology, has the ability to preserve red blood cells along with the majority of platelets. Background/Objectives: The present study aimed at comparing the functionality of preserved platelets in the clot formation by using Quantra^® and/or ROTEM^® Point-Of-Care coagulation tests, after blood treatment for autotransfusion with either a standard centrifugation-based system (Xtra^® device, LivaNova, London, UK), or the filtration-based same™ device. Methods: First, coagulation was assessed in an in vitro experiment, where human blood samples were used to obtain ten treated blood products by each autotransfusion device that were evaluated with or without supplementation of plasma poor or rich in platelets. Then, to confirm the potential clinical benefit of the platelet preservation in a surgical context, coagulation was studied in vivo using a massive surgical hemorrhagic model on eight minipigs per device. Samples were collected after reinfusion steps and during a 6 h post-operative follow-up. Results: Both in vitro and in vivo, the same™ device consistently retained more platelets compared to the Xtra^® device. This enhanced preservation resulted in significantly stronger clot formation, likely due to higher platelet concentration and superior functional integrity. Conclusions: These findings highlight the potential clinical benefit of same™-recovered platelets for improving hemostasis during hemorrhagic surgery. Full article

Eye-tracking methodology represents a young but rapidly growing approach in tourism research, offering a direct window into the cognitive processes driving tourism stakeholders’ behaviour. However, a critical gap remains between the rapid adoption of this tool and the methodological rigour required to interpret its neurophysiological data. This critical review synthesizes 23 empirical studies (2020–2025) from the destination marketing and branding domain to diagnose eye-tracking’s state-of-the-art application. Adopting the SALSA framework (Search, Appraisal, Synthesis, Analysis) augmented by PRISMA 2020 guidelines, this study systematically searched Web of Science and Scopus databases. Studies were appraised using an eight-dimensional quality rubric, assessing from theoretical grounding to experimental design to statistical rigour. Findings revealed a “tool-first” exploratory phenomenon, where the majority of studies relied on basic fixation metrics to infer complex psychological states such as “interest”, when they could imply other cognitive states. Furthermore, most reviewed studies failed to control for stimulus-level confounds (e.g., luminance, AOI size) and utilized inappropriate data-handling procedures and methods, such as the absence of data cleaning and treating count and binary data as continuous data. These, coupled with transparency deficits, undermined the validity of their conclusions. Hence, a Checklist for Eye-Tracking Rigour (CETR) and a methodological decision tree were developed to guide researchers towards confirmatory and neurobiologically grounded research. Findings also provided a framework for managers/practitioners to more accurately interpret eye-tracking studies. Full article

Rapid access to building intelligence is critical for emergency response, yet paper fire safety instructions (FSi) often provide limited utility under stress. This structured narrative review addresses the “information gap” between unit arrival and decision-making by analyzing the legal admissibility, technological requirements, and security risks of digital FSi across Poland, Germany, France, Belgium, and Hungary. While no explicit prohibition of digital forms was identified, enforcement practices prioritize paper as the evidentiary master. Consequently, we propose a hybrid model: a paper master for compliance and redundancy, supplemented by a digital operational overlay accessed via “zero-install” offline-first progressive web apps (PWA). The review defines a minimum operational dataset (MOD)—prioritizing critical data like utility shut-offs and hazards over full documentation—and addresses cybersecurity threats, specifically QR-phishing (“quishing”). We conclude that the hybrid model minimizes legal and operational risks while significantly reducing time-to-information, provided that strict content identity and change management protocols are maintained. Full article

Background/Objectives: Preterm infants with respiratory distress syndrome (RDS) require mechanical ventilation but risk lung injury This study compared neurally adjusted ventilatory assist (NAVA) with conventional modes regarding respiratory mechanics and clinical outcomes. Methods: We analyzed data from 79 preterm infants born at <32 weeks gestation who were invasively ventilated for RDS and classified into three groups: NAVA (n = 26), volume-targeted (VT; n = 29), and pressure-controlled (PC; n = 24). Respiratory parameters for 6 h post-surfactant administration and clinical outcomes were evaluated. Results: Baseline characteristics were similar across groups. The NAVA group demonstrated the most rapid reduction in peak inspiratory pressure over 6 h (F = 4.125, p = 0.023) and the fastest increase in dynamic compliance during the first 4 h (F = 3.273, p = 0.048). Respiratory rates were significantly lower with NAVA than with VT or PC modes, while tidal volumes were significantly higher in PC than in NAVA or VT modes. Invasive mechanical ventilation duration was shorter in NAVA (3.0 [0.9–4.9] days) than in PC modes (15.1 [0.3–38.5] days, p = 0.031), whereas not significantly different from that in VT modes (3.8 [0.9–13.4] days). While bronchopulmonary dysplasia or death was lower in NAVA (19.2%) than in PC modes (41.7%), the difference was not statistically significant (p = 0.092). Conclusions: NAVA resulted in the fastest reduction in ventilator-delivered pressure and earlier improvement in dynamic compliance while maintaining respiratory rates within physiological ranges and was associated with shorter ventilation duration than PC modes. However, VT modes achieved comparable respiratory parameters and ventilation durations to those achieved using NAVA. Full article

Background: Glabridin, a natural compound derived from Glycyrrhiza glabra L., possesses skin-lightening effects. This study aims to further elucidate the depigmentation mechanism of glabridin by investigating its effects on melanogenesis and melanin transfer. Methods: We initially confirmed the anti-melanogenic effects of glabridin in MNT-1 human melanoma cells. Then, we investigated the mechanism of its anti-melanogenic effect by evaluating the protein expression of β-catenin and MITF via Western blot. To investigate melanin transfer, we compared glabridin’s efficacy with that of niacinamide, a recognized inhibitor of melanosome transfer and employed two complementary experimental models: (1) α-melanocyte-stimulating hormone (α-MSH)-stimulated MNT-1 cells to analyze dendrite formation, and (2) a UVB-irradiated co-culture system of MNT-1 cells and HaCaT keratinocytes to evaluate melanin transfer. Results: By measuring glabridin’s effects on melanin content, tyrosinase activity, and melanogenesis-related protein expression confirmed its inhibition of melanin synthesis. Further investigation demonstrated that glabridin suppresses melanogenesis by downregulating β-catenin and MITF, indicating inhibition of the Wnt/β-catenin pathway. Furthermore, in α-MSH-treated MNT-1 cells, both glabridin and niacinamide were found to suppress dendrite formation and elongation. In a UVB-exposed co-culture system, both glabridin and niacinamide inhibited melanin transfer to keratinocytes. Mechanistically, these effects were linked to the regulation of Rho GTPases (Rac1, RhoA, Cdc42) and suppression of F-actin reorganization. Conclusions: This study provides, for the first time, evidence that the skin-lightening effect of glabridin involves two complementary mechanisms: inhibition of melanogenesis through suppression of the Wnt/β-catenin pathway, and attenuation of both dendricity and melanin transfer via the influence of Rho family GTPases expression. Full article

Children and young people with a parent in contact with the justice system rarely receive the support they need; many are judged and stigmatised. Child Impact Assessments were developed by the Prison Reform Trust in collaboration with 28 children and young people from across the United Kingdom with experience of parental imprisonment, who said in interviews, focus groups, and an online survey that they want to be seen, listened to, and considered at all stages of a parent’s journey through the justice system: arrest, court, and sentencing, prison or community sentence, and prior to a parent’s release. They want to be supported, and they want to be included in decisions about that support. This paper lays out why Child Impact Assessments are needed; what they are; and crucially how they can be used in practice to ensure the right support is offered to meet a child’s needs at the earliest opportunity. The paper will provide evidence of how Child Impact Assessments can improve children’s wellbeing and will give an overview of recent developments to the resources. The authors will also explore future developments, including adapting the resources to understand the impact on unborn babies, babies, and very young children (the first 1001 days) when a pregnant woman or mother is in contact with the justice system. Full article

Multichannel synthetic aperture radar (SAR) achieves high-resolution imaging while significantly enhancing the spatial freedom of the SAR system. As SAR hardware performance continues to improve, observed scenes often transition from simple to complex scenes. The increasingly complex clutter components introduced by complex scenes make clutter suppression increasingly challenging. Traditional multichannel clutter suppression algorithms usually assume that the observed scene, as a whole, satisfies the independent and identical distribution (IID) condition. However, in actual complex scenes, this assumption often proves difficult to uphold. Therefore, how to achieve more effective clutter suppression for complex scenes is a challenge for SAR. In this paper, we propose a knowledge-aided (KA) multichannel SAR clutter suppression algorithm for complex scenes. First, the single-channel image is processed at the superpixel level and a superpixel fusion algorithm is proposed, which adaptively realizes the refined classification of the complex scene. Then, a two-step clutter suppression processing method with multi-strategy clutter suppression preprocessing and sparse Bayesian residual clutter suppression is proposed. This method not only provides effective classification information for complex scenes but also achieves more efficient clutter suppression in complex scenes based on this classification information. Finally, the clutter suppression performance of this algorithm in complex scenes was validated through measured data. Full article

PCB surface defect detection plays a critical role in ensuring electronics manufacturing quality. To address the challenges of small target defect detection, this study proposes PCB-YOLO, an enhanced lightweight detector based on YOLOv8n. PCB-YOLO introduces three key improvements. First, a RepViT-EMA Fusion Architecture (REFA) module is designed for deep backbone layers to strengthen feature extraction while suppressing background interference from complex circuit patterns. Second, a Multi-Scale Grouped Aggregation (MSGA) module is developed to reduce feature redundancy and improve spatial-semantic information extraction for multi-scale defects. Third, a Pixel-level Intersection over Union (PIoU) loss function is proposed to enable pixel-level IoU calculation with enhanced angular and area constraints for more precise localization. Extensive experiments on the PKU-Market-PCB dataset demonstrate that PCB-YOLO achieves 98.4% mAP@0.5, 97.4% recall, and 96.1% precision with only 2.4 M parameters, 6.9 G FLOPs, and an inference speed of 224 FPS, outperforming multiple state-of-the-art methods while maintaining real-time capability. Additional experiments on the DeepPCB dataset yield 99.0% mAP@0.5 and 80.4% mAP@0.5:0.95, confirming the cross-dataset generalization ability of the proposed method. Full article

Background/Objectives: Insomnia disorder is highly prevalent and disabling, yet access to cognitive behavioural therapy for insomnia (CBT-I), the recommended first-line treatment, remains limited. Digital CBT-I (dCBT-I) offers scalable alternative; however, treatment outcomes vary according to intervention format and delivery context. This study evaluated whether delivering dCBT-I within a structured, medically supervised crenotherapy context improved insomnia symptom severity compared with stand-alone dCBT-I. Methods: In this multicentre proof-of-concept randomised controlled trial, 66 adults with insomnia disorder were allocated to receive either stand-alone dCBT-I (n = 38) or dCBT-I delivered within a 3-week standardised crenotherapy programme (medically supervised thermal spa treatment; n = 28). The primary outcome was change in Insomnia Severity Index (ISI) scores from pre- to post-treatment. Secondary outcomes included subjective sleep parameters (e.g., sleep efficiency and sleep onset latency), sleep-related functioning, pre-sleep arousal, anxiety and depressive symptoms. Engagement and satisfaction were assessed as additional descriptive outcomes. Results: Both groups showed significant improvements in insomnia severity, sleep parameters, and psychological symptoms. However, the primary between-group comparison did not demonstrate a statistically significant additive effect of crenotherapy on insomnia severity. ISI outcomes did not differ between the crenotherapy-delivered and stand-alone dCBT-I groups. Nevertheless, post hoc exploratory subgroup analyses suggested that, among participants younger than 60, delivery of dCBT-I within a crenotherapy care setting was associated with greater improvements in insomnia symptoms compared with stand-alone dCBT-I (mean ISI change: 10.4 vs. 5.4, p = 0.030). In a separate subgroup analysis, among participants with baseline anxiety symptoms, dCBT-I delivered within a crenotherapy care setting was associated with a greater reduction in anxiety compared with stand-alone dCBT-I (p = 0.030). Engagement and satisfaction were high in both groups, with no significant differences. Conclusions: Delivering dCBT-I within a crenotherapy context appears feasible and may offer specific benefits for specific subpopulations, particularly younger individuals and those with comorbid anxiety. These findings support further investigation of context-sensitive digital models to improve personalisation and accessibility of insomnia treatment. Full article