Search Results (6,177)

Background: Present ACS risk stratification predominantly depends on LDL-C, yet its diagnostic accuracy for coronary plaque burden remains limited. We examined whether extensive lipid profiling, specifically the TG/HDL-C ratio, could function as a more effective diagnostic instrument for forecasting significant plaque burden in treatment-naïve first-time ACS patients. Methods: Among 722 ACS patients screened, 376 treatment-naïve patients undergoing PCI with complete lipid data were included. Exclusions (n = 346) were due to prior CAD, lipid-lowering therapy, renal/hepatic dysfunction, malignancy, pregnancy, or incomplete data. Coronary plaque burden was quantified by QCA, and patients were stratified by lesion count (0, 1, 2, 3, ≥4). The levels of lipids (LDL-C, HDL-C, TC, TG) and their ratios (LDL/HDL-C, TC/HDL-C, TG/HDL-C) were measured. Analyses included ANOVA (with Bonferroni correction), correlation, ordinal regression, and logistic regression (≥3 vs. <3 lesions). ROC analysis determined thresholds. Results: TG/HDL-C ratio increased progressively from 3.3 (0 lesions) to 5.3 (≥4 lesions). After Bonferroni correction, only TG/HDL-C retained significance (p = 0.009). Logistic regression confirmed TG/HDL-C as an independent predictor of high plaque burden (OR 1.25, 95% CI 1.09–1.42, p = 0.004), outperforming LDL-C. Conclusions: TG/HDL-C ratio is a superior diagnostic biomarker compared to LDL-C for identifying extensive coronary plaque burden. Integration into admission lipid profiling offers a cost-effective, actionable tool. Full article

Low-cost sensors have demonstrated their advances in acquiring hyper-localized data compared to traditional, high-maintenance air quality monitoring stations. The study aims to leverage the mobility of participants equipped with low-cost wearable monitors (LWMs) by comparing their exposure to particulate matter (PM) across indoor-home, outdoor-walking, and hybrid-commuting micro-environments. The LWMs would be calibrated first through field co-location and the multiple linear regression models. The coefficient of determination (R²) of PM_1.0 and PM_2.5 increased to over 0.85 after calibration, along with the reduced root mean square error of 2.25 and 3.46 , respectively. The 26-day PM data collection with geographic locations could identify individual exposure patterns, local source contributions, and hotspot maps. Commuting constituted a small fraction of daily time (4–8%) but contributed a disproportionate impact, accounting for 11% of individual PM exposure. Indoor-home PM_2.5 exposure varied significantly among the urban districts. Based on the PM_2.5 hotspot map, the elevated concentration was mainly concentrated in dense residential areas and historical industrial areas, as well as interchanges of major roads and the highway system. LWMs acting as non-regulatory instruments can complement monitoring stations to provide missing short-term and hyper-localized air pollution data. Future studies should integrate long-term monitoring and citizen science across seasons and geographical regions to address pollutant spatiotemporal variability for building and city sustainability. Full article

Significant time, money, and energy are invested in Continuing Professional Development (CPD) across Further Education (FE) colleges in England, with the aim of enhancing teaching strategies, sharing “best” practices, and improving educational quality. Despite these intentions, practitioner perceptions of CPD’s value remain mixed, highlighting concerns about the effectiveness of current approaches. CPD managers often face competing financial and operational demands, alongside pressure to comply with external requirements, resulting in CPD that is frequently instrumental, mandatory, and delivered through one-off events. These practices reflect a data-driven, prescriptive management culture that prioritizes measurable outcomes over meaningful educational experiences. Consequently, teachers are compelled to demonstrate compliance within a system where accountability is unevenly distributed. This medium-scale, multi-method practitioner research study investigates how such compliance-driven CPD practices divert attention and resources from genuine educational improvement. This study explores an alternative model of CPD rooted in teacher agency and enriched through engagement with the arts and aesthetic experiences. Drawing on surveys, semi-structured interviews, critical incidents, and narrative accounts, the findings suggest that this approach fosters more democratic, creative, and impactful professional development. In promoting teacher agency and challenging dominant power structures, this study offers a vision of CPD that supports meaningful educational transformation, with practical examples and recommendations for broader implementation. Full article

Biomechanical strategies of running gait were compared among healthy and recently injured pediatric and adult runners (N = 207). Spatiotemporal, kinematic, and kinetic parameters (ground reaction force [GRF], vertical average loading rate [VALR]) and leg stiffness (K_vert) were obtained during running on an instrumented treadmill with simultaneous 3D-motion capture. Significant age X injury interactions existed for cadence, peak GRF, and peak joint angles in stance. Cadence was fastest in healthy adults and 2–3% lower in other groups (p = 0.049). Injured adults exhibited higher variance in stance and swing time, whereas injured pediatric runners had lower variance in these measures (p < 0.05). Peak GRF was highest in non-injured adults (2.6–2.7 BW) and lowest in injured adults (2.4 BW; p < 0.05). VALRs (BW/s) were higher among pediatric groups, irrespective of injury (p < 0.05). The interaction for ankle dorsiflexion/plantarflexion moment was significant (p = 0.05). Healthy pediatric runners produced more plantarflexion than all other groups (p = 0.026). Pelvis rotation was highest in healthy pediatric runners and lowest in healthy adults (17.3° versus 12.0°; p = 0.036). Pediatric runners did not leverage force-dampening strategies, but reduced gait cycle time variance and controlled pelvic rotation. Injured adults had lower GRF and longer stance time, indicating a shift toward force mitigation during stance. Age-specific rehabilitation and gait retraining approaches may be warranted. Full article

Promoting sustainable and balanced economic growth remains a key challenge for developing countries. This study empirically investigates the impact of China’s Pilot Free Trade Zone (PFTZ) on regional economic growth from 2010 to 2023, offering important insights into how targeted policy instruments can contribute to sustainable economic growth. Employing a multiperiod difference-in-differences model and a capital–technology–marketization framework, this study finds that PFTZ implementation has a significant and direct influence on promoting provincial economic growth. The growth effects are primarily driven by improved capital flows and enhanced technological innovation. Notably, these positive effects are more pronounced in central and western Chinese provinces and regions with lagging economic development, indicating that PFTZs can serve as effective tools for reducing regional disparities. These findings provide new empirical evidence regarding the regional heterogeneity of PFTZ policy impacts and offer valuable insights into the design, timing, and spatial targeting of PFTZ initiatives in developing countries seeking to support inclusive and sustainable development across the country. Full article

Background: Fear of cancer recurrence (FCR) is a common, distressing concern among cancer survivors, with implications for psychological well-being and quality of life. Despite the proliferation of patient-reported outcome measures (PROMs) to assess FCR, consensus on the most valid and reliable instruments remains limited. Objective: To conduct a comprehensive psychometric evaluation of FCR PROMs developed or validated between 2011 and 2023, using the full COSMIN methodology. This review builds on earlier work by systematically appraising both newly developed and adapted instruments to inform evidence-based PROM selection for clinical and research use. Methods: This review followed the COSMIN 10-step procedure and PRISMA 2020 guidelines. Six databases were searched from January 2011 to December 2023. A search cut-off of 31 December 2023 was applied to align with COSMIN feasibility recommendations and ensure sufficient time and resources for full psychometric evaluation across all included PROMs. Eligible studies included adults diagnosed with cancer and reported on the psychometric evaluation of a self-reported, Likert-scale-based FCR PROM. PROMs were appraised across eight psychometric properties using COSMIN’s Risk of Bias checklist, criteria for good measurement properties, and modified Grading of Recommendations Assessment, Development, and Evaluation (GRADE) for evidence quality. Instruments were categorized as A, B, or C according to COSMIN’s recommendations. Results: Of the 34 PROMs evaluated across 32 studies, 28 achieved COSMIN Category A status, indicating sufficient psychometric quality for clinical or research use. Among the 19 FCRI and FoP-Q instruments validated in new cultural or population contexts, 15 received a Category A rating, reflecting strong cross-cultural performance. Short forms such as the FCRI-SF and FoP-Q-SF demonstrated consistent psychometric strength across French, English, Portuguese, and Asian-language versions. Of the 14 newly developed PROMs—including the CWS-6, FCR4/7, CARQ-4, and FCR-1—12 achieved Category A. The FCR-1 was the only single-item PROM to demonstrate responsiveness, supporting its use in both screening and longitudinal monitoring. For practical guidance, five PROMs (FCR-1, FCRI-SF, FoP-Q-SF, FCR-7, and CWS) emerged as the most strongly supported for clinical use. Conclusions: This review provides a comprehensive evaluation of contemporary FCR PROMs and highlights substantial progress in the development of valid, reliable, and culturally adaptable tools. The FCRI, FoP-Q-SF, and several newly developed short forms, such as FCR7, CWS, and particularly, the FCR-1, emerge as strong candidates for use in clinical screening and longitudinal assessment. These findings offer clear evidence-based guidance for instrument selection in research and survivorship care. PROSPERO registration: CRD42023453783. Full article

High-precision assembly plays a central role in aerospace, defense, and precision instrumentation, where errors in bolt preload or tightening sequences can directly degrade product reliability and lead to costly rework. Traditional finite element analysis (FEA) offers accuracy but is too computationally expensive for iterative or real-time optimization. Surrogate models are a promising alternative, yet conventional machine learning methods often neglect the sequential and constraint-aware nature of multi-bolt assembly. To overcome these limitations, this paper introduces an integrated framework that combines an Attention-based Bidirectional Long Short-Term Memory (AB-BiLSTM) surrogate with a stratified version of the Harris Hawks Optimizer (SEG-HHO). The AB-BiLSTM captures temporal dependencies in preload evolution while providing interpretability through attention–weight visualization, linking model focus to physical assembly dynamics. SEG-HHO employs an encoding–decoding mechanism to embed engineering constraints, enabling efficient search in complex and constrained design spaces. Validation on a gyroscope assembly task demonstrates that the framework achieves high predictive accuracy (Mean Absolute Error of 3.59 × 10⁻⁵), reduces optimization cost by orders of magnitude compared with FEA, and reveals physically meaningful patterns in bolt interactions. These results indicate a scalable and interpretable solution for precision assembly optimization. Full article

Many industries release untreated synthetic dye effluents into water bodies, harming ecosystems and human health. Therefore, an economical and sustainable solution for treating dye-contaminated water must be developed. In this study, mulberry leaves (Morus nigra L.), as a cost-effective and sustainable adsorbent, were prepared to remove Basic Yellow 28 (BY28) and Basic Blue 3 (BB3) cationic dyes from industrial dye wastewater using adsorption. Batch experiments with key variables such as initial dye concentration, adsorbent dosage, contact time, temperature, stirring speed, and pH were conducted to find optimal conditions. The effectiveness of mulberry leaves as an adsorbent after multiple regeneration cycles was examined. The adsorbent was characterized through various instrumental methods, including FTIR, SEM, XRD, and BET analysis. Adsorption performance was analyzed using the Langmuir and Freundlich isotherm models. The results showed that the mulberry leaf adsorbent best fits the Langmuir model, with R² values of 0.999 for BY28 and 0.973 for BB3. The maximum adsorption capacities were 0.15 mg/g for BY28 and 7.19 mg/g for BB3, indicating their upper limits for dye uptake. The optimal conditions achieving removal efficiencies of over 99% were 1.5 g, 50 mL, 15 min, 180 rpm, and 10 mg/L at 30 °C for BY28 in neutral pH (7) and 1.5 g, 50 mL, 45 min, 100 rpm, and 30 mg/L at 40 °C for BB3 in basic pH (10). The regeneration of mulberry leaves as an adsorbent through acid treatment with 0.1 M HCl and 0.1 M CH₃COOH solutions maintained a high performance, achieving up to 98% dye removal efficiency after two regeneration cycles. It has been observed that successful results can be achieved in terms of reusability. Additionally, the removals of BB3 and BY28 performed in an ultrasonic-bath-assisted environment successfully achieved removal efficiencies of 84.87% and 75.41%, respectively. According to the results, mulberry leaves can effectively be used in wastewater treatment to remove dyes, can be reused multiple times, and thus serve as an environmentally friendly and sustainable adsorbent. Full article

The assessment of physical quantity values, especially in case of sports-related activities, is critical to evaluate the performance and fitness level of athletes. In real-world applications, motion analysis tools are often employed to assess motor performance in subjects. In case the methods used to calculate a specific quantity of interest differ from each other, different values may be provided as output. Therefore, there is the need to get a coherent final measurement, giving the possibility to compare results homogeneously, combining the different methodologies used by the instruments. These tools vary in measurement capabilities and the physical principles underlying the measurement procedures. Emerging differences in results could lead to non-uniform evaluation metrics, thus making a fair comparison unpracticable. A possible solution to this problem is provided in this paper by implementing an iterative approach, working on two measurement time series acquired by two different instruments, specifically focused on jump height estimation. In the analyzed case study, two instruments estimate the jump height exploiting two different technologies: the inertial and the vision-based ones. In the first case, the measurement value depends on the movement of the center of gravity during jump activity, while, in the second case, the jump height is derived by estimating the maximum distance ground–foot during the jump action. These approaches clearly could lead to different values, also considering the same jump test, due to their observation point. The developed methodology can provide three different ways out: (i) mapping the inertial values towards the vision-based reference system; (ii) mapping the vision-based values towards the inertial reference system; (iii) determining a comprehensive measurement, incorporating both contributions, thus making measurements comparable in time (performance progression) and space (comparison among subjects), eventually adopting only one of the analyzed instruments and applying the transformation algorithm to get the final measurement value. Full article

Particulate matter (PM) is a significant air pollutant in modern egg production. However, high-quality PM data from commercial egg farms are still very limited. A 6-month study, covering both cold and hot seasons, measured PM₁₀ concentrations and emissions in a 140,000-hen commercial laying hen house in the Midwest USA. An advanced measurement system was implemented for continuous and real-time monitoring, collecting data from 67 online instruments and sensors. The study generated 4318 h of valid PM₁₀ data, with 97.8% data completeness. The average daily mean (ADM) PM₁₀ concentration in the house exhaust air, standardized to 20 °C and 1 atm, was 236 ± 162 (ADM ± standard deviation) µg m⁻³. The ADM net PM₁₀ emission was 18.9 ± 2.2 mg d⁻¹ hen⁻¹. Increasing outdoor temperatures were correlated with decreased indoor PM₁₀ concentrations but increased overall emissions. Comparison with the ADM emission of 12.4 ± 13.3 mg d⁻¹ hen⁻¹ from the same house during a previous six-month study in 2004–2005 revealed that artificial hen molting in this study increased PM₁₀ concentrations and emissions. Extrapolating the ADM PM₁₀ emission from the house, the ADM PM₁₀ emission from the entire egg farm was estimated at 35.6 ± 31.1 kg d⁻¹ (or 35.6 ± 4.5 kg d⁻¹ with a 95% confidence interval). This study provides valuable insights into air quality in animal agriculture and contributes high-quality and real-world data for use in data-driven approaches such as artificial intelligence, machine learning, data mining, and big data analytics. Full article

This paper examines the interconnection and wavelet coherence between the green cryptocurrency market and the green conventional market, utilizing daily data. The research period covers 1 July 2020 to 30 September 2024. Employing the time-varying parametric vector autoregression (TVP-VAR) model and wavelet coherence analysis, we capture both short- and long-term spillovers across markets. The results show that cryptocurrencies, particularly Binance and Litecoin, act as dominant transmitters of volatility and return shocks, while green conventional indices function mainly as receivers with strong self-dependence. Spillover intensity is highly time-varying, with peaks during periods of systemic stress, particularly during the COVID-19 pandemic, and troughs indicating diversification opportunities. These findings advance the literature on systemic risk and portfolio design by showing that crypto assets can simultaneously amplify vulnerabilities and enhance diversification when combined with green finance instruments. For policy, the results highlight the need for regulatory frameworks that integrate sustainability taxonomies, mandate environmental disclosures for digital assets, and incentivize energy-efficient blockchain adoption to align crypto markets with sustainable finance objectives. This research enhances our understanding of the interrelationship between green investments and cryptocurrencies, providing valuable insights for investors and policymakers on risk management and diversification strategies in an increasingly sustainable financial landscape. Full article

The increasing power demand in substations and the advancement of smart-grid technology point to optical voltage sensors (OVSs) based on the Pockels effect as an attractive solution to replace traditional coil instrument transformers, due to their advantageous characteristics of lower cost and installation space, absence of explosion risks, as well as nonlinear effects such as magnetic hysteresis. Regarding the measurement, our OVS presents excellent linearity, 3 kHz bandwidth, and high input impedance. The primary contribution of this paper is to demonstrate, for the first time, the efficiency of a versatile nonlinear digital controller, based on sliding mode theory, for the optical phase demodulation of an OVS. A simple proportional-integral feedback control is employed to prevent signal fading and generate the two quadrature signals required by the observer, which includes the nonlinear digital controller. Experimental results, for 60 Hz sinusoidal voltages with amplitudes exceeding the half-wave voltage of the OVS, prove that peak-to-peak relative errors remain below 0.8%, while total harmonic distortion (THD) relative errors are under 1.5% when compared to a commercial high-voltage probe used as a reference. These results confirm compliance with Class 1.0 of the UNE-EN 60044-7 standard and show strong potential for applications in power quality measurements. Full article

Gait recovery after stroke is a primary goal of rehabilitation, therefore it is imperative to develop technologies that accurately identify gait impairments after stroke. Markerless motion capture (MMC) is an emerging technology that has been validated in healthy individuals. Our study aims to evaluate the validity of MMC against an instrumented walkway system (IWS) commonly used to evaluate gait in stroke survivors. Nineteen participants performed three comfortable speed (CS) and three fastest speed (FS) walking trials simultaneously recorded with IWS and MMC system, KinaTrax (HumanVersion 8.2, KinaTrax Inc., Boca Raton, FL, USA). Pearson’s correlation coefficient and intraclass correlation coefficient (ICC (3,1), 95%CI) were used to evaluate the agreement and consistency between systems. Furthermore, Bland–Altman plots were used to estimate bias and Limits of Agreement (LoA). For both CS and FS, agreements between MMC and IWS were good to excellent in all parameters except for non-paretic single-limb support time (SLS), which revealed moderate agreement during CS. Additionally, stride width and paretic SLS showed poor agreement in both conditions. Biases eliminated systematic errors, with variable LoAs in all parameters during both conditions. Findings indicated high validity of MMC in measuring spatiotemporal gait parameters in stroke survivors. Further validity work is warranted. Full article

Rapid urbanization has intensified the systemic inequities of resources and infrastructure distribution in informal settlements, particularly in the Global South. Digital Twin Modeling (DTM), as an effective data-driven representation, enables real-time analysis, scenario simulation, and design optimization, making it a promising tool to support urban resilience. This study introduces the Integrated Modification Methodology (IMM), developed by Politecnico di Milano (Italy), to explore how DTM can be systematically structured and transformed into an active instrument, linking theories with practical application. Focusing on Paranoá (Brasília), a case study developed under the NBSouth project in collaboration with the Politecnico di Milano and the University of Brasília, this research integrates advanced spatial mapping with comprehensive key performance indicators (KPIs) analysis to address developmental and environmental challenges during the regeneration process. Key metrics—Green Space Diversity, Ecosystem Service Proximity, and Green Space Continuity—were analyzed by a Geographic Information System (GIS) platform on 30 m by 30 m sampling grids. Additional KPIs across urban structural, environmental, and mobility layers were calculated to support the decision-making process for strategic mapping. This study contributes to theoretical advancements in DTM and broader discourse on urban regeneration under climate stress, offering a systemic and practical approach for multi-dimensional digitalization of urban structure and performance, supporting a more adaptive, data-based, and transferable planning process in the Global South. Full article

pH-sensitive intelligent films offer a novel strategy for real-time monitoring of food freshness via visible color changes. This study valorizes onion peel powder (OPP), a polyphenol-rich agro-industrial by-product, by incorporating it into cassava starch-based films at three concentrations (1O, 2O, 3O). Increasing OPP content led to significantly higher total phenolic and flavonoid levels, enhancing the films’ antioxidant properties (p < 0.0001). While the films exhibited selective antibacterial effects, pronounced inhibition zones were observed against Pseudomonas aeruginosa and Escherichia coli, two relevant meat spoilage and pathogenic bacteria. The films displayed clear and gradual color shifts from light to dark brown across a wide pH range (1–13), confirming their suitability as pH indicators. When applied as labels in minced beef packaging stored at 4 °C, the films successfully tracked freshness over 13 days. Film color changes were strongly correlated with microbial load and pH variations, accurately flagging spoilage onset. These findings support the potential of cassava starch/OPP films as biodegradable, cost-effective intelligent packaging tools, contributing to food safety, waste reduction, and circular bioeconomy principles. The system provides a practical, non-invasive solution for meat freshness monitoring without requiring instrumentation. Full article