Search Results (4,529)

Between 51% and 72% of a bituminous roofing membrane used for structural waterproofing consists of organic material, predominantly bitumen—a derivative of crude oil refining—highlighting the strong dependence of this product on fossil resources. Considering that several tonnes of these membranes must be replaced every 30 to 50 years, substantial potential exists for emission reduction through the establishment of circular material systems. This study investigates this potential by analysing 26 Environmental Product Declarations (EPDs) and life cycle datasets from across Europe covering the period from 2007 to 2023. To ensure comparability, all data were normalised to a declared unit of 1 kg of roofing membrane. The reinforcement layers were categorised into glass and polyester & glass composites, and their differences were examined using Welch’s t-tests. Correlative analyses and linear as well as multiple regression models were then applied to explore relationships between environmental indicators and the shares of organic and mineral mass fractions. The findings reveal that renewable energy sources, although currently representing only a small share of total production energy, provide a major lever for reducing nearly all environmental impact categories. The type of reinforcement layer was also found to influence the demand for fossil resources, both materially and energetically. For most environmental indicators, only multiple regression models can explain at least 30% of the variance based on the proportions of organic and mineral inputs. Overall, the study underscores the crucial importance of high-quality, transparently documented product data for accurately assessing the sustainability of building products. It further demonstrates that substituting fossil energy carriers with renewable sources and optimising material efficiency can substantially reduce environmental burdens, provided that methodological consistency and clarity of indicator definitions are maintained. Full article

The contemporary healthcare environment is characterized by high stress and emotional burden, contributing to increasing rates of professional burnout among clinicians. Exposure to patient death represents one of the most emotionally taxing experiences in medicine, particularly in obstetrics and gynecology (OB/GYN), where loss of life stands in stark contrast to the life-giving nature of the field. Despite extensive research on burnout in oncology and intensive care, the impact of patient death and death perception on OB/GYN clinicians remains underexplored. Objective: This study aimed to examine the relationships between exposure to patient death, perceptions of death, professional burnout, and professional fulfillment among OB/GYN clinicians. A secondary aim was to explore whether participation in emotional regulation training was associated with these variables. Methods: A cross-sectional study was conducted among 138 OB/GYN clinicians. An author-developed questionnaire was used, comprising scales measuring professional burnout, positive and negative death perception, professional fulfillment, professional development, and a global death-impact index. Statistical analyses included Pearson’s correlation and the Mann–Whitney U test to compare clinicians who had attended emotional regulation training with those who had not. Results: Significant positive correlations were observed between burnout and the death-impact index (r = 0.90, p < 0.001) and between burnout and negative death perception (r = 0.23, p = 0.007). Professional fulfillment strongly correlated with professional development (r = 0.94, p < 0.001) and positively with positive death perception (r = 0.30, p < 0.001). No significant group differences were found regarding emotional regulation training participation. Conclusions: Exposure to patient death in OB/GYN is strongly associated with professional burnout and negative perceptions of death. Conversely, professional fulfillment and development function as factors promoting resilience and meaning. Further research should validate the applied measurement tools and examine the effectiveness of emotional regulation interventions in reducing occupational distress. Full article

The rapid growth of technology has introduced robots into daily life, necessitating navigation frameworks that enable safe, human-friendly movement while accounting for social aspects. Such methods must also scale to situations with multiple humans and robots moving simultaneously. Recent advances in Deep Reinforcement Learning (DRL) have enabled policies that incorporate these norms into navigation. This work presents a socially aware navigation framework for mobile robots operating in environments shared with humans and other robots. The approach, based on single-agent DRL, models all interaction types between the ego robot, humans, and other robots. Training uses a reward function balancing task completion, collision avoidance, and maintaining comfortable distances from humans. An attention mechanism enables the framework to extract knowledge about the relative importance of surrounding agents, guiding safer and more efficient navigation. Our approach is tested in both dynamic and static obstacle environments. To improve training efficiency and promote socially appropriate behaviors, Imitation Learning is employed. Comparative evaluations with state-of-the-art methods highlight the advantages of our approach, especially in enhancing safety by reducing collisions and preserving comfort distances. Results confirm the effectiveness of our learned policy and its ability to extract socially relevant knowledge in human–robot environments where social compliance is essential for deployment. Full article

Internal defects commonly occur during the 3D printing process of Polylactic Acid (PLA), and significant challenges remain in detecting and extracting these defects, as well as understanding the relationship between defects and material fatigue life. This research proposes the Chroma-YOLO Enhanced Integrated Framework, an improved YOLOv11n-based model that integrates HSV defect extraction module and a random forest prediction model. Comprehensive ablation experiments demonstrate that the Chroma-YOLO model achieves significant improvements of 6.9% and 7.3% for mAP50 and mAP50-95 metrics, respectively, compared to the baseline YOLOv11n model, confirming substantial enhancements in feature extraction capability and target localization accuracy. Furthermore, this framework establishes a comprehensive model from defect detection to fatigue life prediction by combining the HSV color space-based defect detection technique with the random forest machine learning algorithm. The random forest-based predictive model achieves a remarkable accuracy of 96.25% and 99.09%for the test and validation set, respectively, for fatigue life prediction of 3D-printed PLA, which shows significant improvement compared to the conventional prediction methodologies. Full article

Spasticity after stroke impairs motor control, delays recovery, and reduces quality of life. Botulinum toxin type A is the first-line treatment, but it is often administered in the chronic phase, potentially limiting its impact on rehabilitation. Emerging evidence suggests that earlier treatment may enhance recovery, though functional benefits remain uncertain. We conducted a secondary analysis of a multicenter, open-label, longitudinal cohort study to investigate whether the timing of the first botulinum toxin type A injection influences outcomes in post-stroke patients naïve to this treatment. All participants received botulinum toxin injections combined with conventional rehabilitation. Assessments were performed at baseline and at 4, 12, and 24 weeks post-injection. The primary outcome was muscle tone; secondary outcomes included motor strength, sensorimotor recovery, and global disability. Statistical analyses used mixed-effects models and trend tests. Patients treated within 90 days of stroke onset showed greater reductions in spasticity at 4 and 12 weeks compared with later treatment. Despite having more severe baseline impairments, early treated patients demonstrated faster and more pronounced improvements in upper-limb strength, sensorimotor recovery, and global disability. Early toxin administration is associated with enhanced reduction in spasticity and improved motor recovery, particularly in patients with severe initial deficits. Full article

Background/Objectives: This study aimed to describe how adolescents with attention-deficit/hyperactivity disorder (ADHD) perceive their diagnosis identity and examine its correlation with executive functions (EFs), self-management abilities, and quality of life (QoL). Methods: A total of 66 adolescents with ADHD, aged 12 to 18 years (M = 15.21, SD = 1.84), completed self-report questionnaires, including the Illness Identity Questionnaire, Behavior Rating Inventory of Executive Function, Self-Control and Self-Management Scale, and Pediatric QoL Inventory. We used ANOVA with Bonferroni post hoc tests to assess differences in diagnosis identity domains and Pearson correlations to examine correlations between diagnosis identity, EFs, self-management, and QoL. Results: Adolescents reported significantly higher ADHD Acceptance feelings compared to Rejection, Engulfment, and Enrichment, F (2.38, 149.89) = 32.41, p < 0.001. Total diagnosis identity score was strongly associated with self-management (r = 0.61, p < 0.001). While no significant correlations were found with overall EF or QoL, significant associations did emerge with their sub-scores. Regression analyses indicated that self-monitoring, social QoL, and self-evaluation together explained 45% of the variance in diagnosis identity. The Engulfment dimension of identity was a significant negative predictor of executive functioning (R² = 0.15), self-management (R² = 0.35), and QoL (R² = 0.17). Conclusions: Promoting a positive diagnosis identity may improve functional and emotional outcomes in adolescents with ADHD. In turn, better functional and emotional outcomes may help them embrace a diagnosis identity that is more positive. Full article

The fabrication of a steel structure facility in the aerospace sector was executed through the implementation of welding techniques. In order to reduce the effects of environmental corrosion and extend its service life, it is typically coated with a protective layer. Nevertheless, conventional non-destructive testing (NDT) techniques generally necessitate preliminary procedures, such as coating removal and surface grinding, prior to inspection, leading to elevated costs and diminished efficiency. Consequently, the investigation into NDT methodologies for welds encased under coatings is of considerable practical significance. The objective of this paper is to comprehensively review and thoroughly analyze the latest research progress in NDT techniques for detecting defects in coated steel welds, seeking feasible approaches for achieving NDT on coated steel structures. Firstly, the paper examines the hazards of common weld defects and the challenges coatings pose to NDT operations. The text then proceeds to expound upon the principles, research advancements, and application scenarios of multiple NDT methods currently available for detecting defects beneath coatings. A comparative summary of these methods is provided, focusing on detection capabilities, coating penetration abilities, key advantages, and limitations. In conclusion, the paper provides insights into future development trends. Full article

Introduction: Evaluating cardiovascular function is crucial in the care of critically ill patients. Recent advancements in continuous cardiac output (CO) monitoring have led to the emergence of several arterial pulse contour devices. To effectively compare the accuracy of these devices, a comprehensive assessment is necessary. However, no experimental studies were found that have evaluated these devices in a controlled setting. Methods: In this innovative bench study, we used a Donovan mock circulatory system in conjunction with a total artificial heart (TAH-t) to simultaneously generate several comparable arterial waveforms and compared CO estimates from three different pulse contour devices: FloTrac™ (Vigileo™, v1.8 4th generation, Edwards LifeSciences, Irvine, CA, USA), proAQT™ (PulsioFlex™, Pulsion Medical Systems, Munich, Germany), and LiDCO™ Plus (LiDCO™, LidCO Ltd., Cambridge, UK). These devices underwent several hemodynamic challenges (HCs), including decreased preload, decreased afterload, and increased heart rate. To evaluate the degree of agreement between the devices, we performed a Bland–Altman analysis for the paired devices. The interclass comparison, error percentage, and variation coefficient for each device were also assessed. Results: The present study first tested the comparability between the three additional arterial line waveforms, and the arterial control line was simultaneously generated with the hemodynamic simulation bench. Comparing the reference values of the dP/dt and sAUC pulse pressure, we found no clinically significant difference between the simultaneously generated arterial waveforms. The different pulse contour devices were then each connected to the arterial lines, with the performance of HCs. HC1 with a decreased preload revealed that CO estimates significantly decreased compared to the baseline values: 3.2 ± 0.06 L.min⁻¹, 4.7 ± 0.05, 4.3 ± 0.07, and 4.0 ± 0.05 for reference methods FloTrac™, PulsioFlex™, and LiDCO™, respectively. HC2 with an increased heart rate revealed CO estimates with FloTrac™, PulsioFlex™, and LiDCO™—6.0 ± 0.03, 6.6 ± 0.06, and 6.0 ± 0.05 L.min⁻¹, respectively—when the CO estimate was 5.6 ± 0.2. HC3 with a decreased afterload that significantly increased CO estimates compared to the baseline with FloTrac™, PulsioFlex™, and LiDCO™—7.0 ± 0.18, 6.6 ± 0.15, and 7.1 ± 0.30 L.min⁻¹, respectively—when the CO estimate with the reference method did not change significantly (from 5.90 ± 0.13 to 5.94 ± 0.11 p = 0.26). The devices’ degree of agreement was estimated with Bland–Altman analysis. Conclusions: The Donovan Mock Circulatory System with SynCardia TAH-t can be used as an innovative experimental hemodynamic simulation bench. It was proven to be stable, accurate, and reliable in generating several controlled pulse pressure waveforms, while many parameters could be changed, such as the preload, heart rate, or afterload. This enables a simultaneous evaluation of different pulse contour devices submitted to several HCs. This is of interest for clinicians to better understand the underlying principles and realistically compare the performance and potentially inherent limitations of pulse contour devices experimentally in a controlled simulated environment. Full article

The objective of this study was to investigate electron beam hardening (EBH) technology and compare its performance with laser beam hardening (LBH) in the context of manufacturing components such as gears, which increasingly employ submicron bainitic steels. Given the stringent demands for durability and fatigue resistance of gear teeth, identifying an optimal surface hardening method is essential for extending service life. Comprehensive analyses, including light and electron microscopy, hardness testing, tribocorrosion testing, and X-ray diffraction for phase composition, were conducted. The EBH-treated layer exhibited a slightly higher hardness (by 26 HV) compared to the LBH-treated layer (average 654 HV), while the base material measured 393 HV. The EBH process produced a uniform hardness distribution with a subsurface zone of reduced hardness. In contrast, LBH resulted in a surface oxide layer absent in EBH due to its vacuum environment. Both techniques reduced the residual austenite content in the surface layer from 22.5% to approximately 1.3%–1.4%. Notably, EBH achieved comparable hardening effects with nearly half the energy input of LBH, demonstrating superior energy efficiency and industrial feasibility. Application of the developed EBH process to an actual gear component confirmed its practical potential for modern gear manufacturing. Full article

This research examined the mechanical, physical, thermal, and durability properties of plastic-based composites made from MSW, namely ultra-high-temperature (UHT) cartons, plastic bags, aluminum foil, and foil bags under both unweathered and accelerated weathering conditions to evaluate their potential as paving slab materials. Composite samples with varying mixing ratios were fabricated and tested based on an experimental design. Statistical analyses using one-way ANOVA confirmed the significant effects of composition on material performance (p < 0.05). The results demonstrated that the mixing ratio markedly influenced mechanical properties. The composite containing 50 wt% UHT carton and 50 wt% foil bags (U50F50) achieved the highest modulus of rupture (121.20 MPa) and modulus of elasticity (2.98 GPa), as well as compressive strength (28.56 MPa), compressive modulus (2.12 GPa), screw withdrawal resistance (54.25 MPa), and hardness (66.25). Under accelerated weathering, all of the composites showed moderate reductions in strength (10 to 30%) due to plastic degradation and surface cracking. In contrast, the composites containing high paperboard fractions (U80P15A5) exhibited greater WA (3.55%) and TS (3.04%), attributed to the hydrophilic nature of cellulose. The inclusion of foil bags effectively reduced WA and TS by limiting moisture penetration. Density measurements demonstrated a gradual increase (0.99 to 1.05 g/cm³) with higher foil content, while accelerated weathering induced an average 10% density reduction. Abrasion resistance improved in foil-rich composites, with U50F50 showing the lowest weight loss (8.56 to 14.02%), confirming its superior structural integrity under mechanical wear. Thermal analysis indicated low conductivity values (0.136 to 0.189 W/m·K), demonstrating favorable insulation performance compared to conventional paving materials. However, higher foil bag fractions enhanced heat conduction, balancing mechanical strength with thermal functionality. Overall, MSW-derived composites containing 30 to 50 wt% foil bags exhibited optimal mechanical durability, abrasion resistance, and thermal stability, making them promising candidates for sustainable paving slab production with low environmental impact and enhanced service life. Full article

The fatigue of wood is becoming increasingly important in modern engineering, as the safety of the structure must be guaranteed and the use of materials must be optimized at the same time. Predicting the fatigue behavior of wood remains a challenge for many researchers. Interest and the number of studies in this field have increased, highlighting the need for a comprehensive overview of the current state of knowledge on wood fatigue. In this paper, we focus on the study of the fatigue of wood-based materials to understand the similarities and peculiarities of fatigue behavior compared to other engineering materials and to identify opportunities for new research. We present the influence of physical and mechanical properties on fatigue life and identify similarities in the fatigue behavior of wood, polymeric materials and steel. The basic properties that differentiate the fatigue life of wood from that of other materials are heterogeneity, orthotropy, viscoelasticity, hygroscopicity, mechanosorptivity and the lack of a clear threshold value for fatigue strength. The differences in fatigue life between solid wood and laminated wood are not uniformly defined by researchers. We provide an overview of the measurement methods used to monitor the fatigue state, the models used to predict fatigue life and the simulations of the stress–strain response to cyclic loading. We identify areas where wood is subject to fatigue and determine which areas are most critical under cyclic loading. We make suggestions for further research that would contribute significantly to a better understanding and management of wood fatigue. Due to the wide variety of wood species used in the studies, it is impossible to compare the results. In order to obtain a comprehensive overview of the response of wood to fatigue under different test conditions, the test methods need to be standardized. Full article

Polyethylene terephthalate (PET) is one of the most widely used plastics globally, and its poor post-consumer management poses serious risks to the environment and human health. Tackling this issue requires innovative strategies that combine recycling and sustainable manufacturing with the principles of the circular economy. This study addresses this challenge by investigating the use of recycled PET, along with reverse logistics, to produce a cell phone holder through additive manufacturing (AM). Characterization was performed using differential scanning calorimetry, thermogravimetric analysis, intrinsic viscosity measurements, and mechanical tensile tests. Environmental and circular performance were evaluated using Life Cycle Assessment (LCA) and the Material Circularity Indicator (MCI), comparing production with 100% virgin PET resin and 100% recycled PET resin. The results showed that the recycled route achieved a tensile strength of 37.7 MPa, with 7.6% strain before rupture, and thermal analysis confirmed its stability during processing. The LCA revealed a 12% reduction in overall environmental impacts when recycled PET replaced virgin resin, with electricity consumption identified as the main critical point. The circularity assessment suggested potential savings of up to 70% if recycled PET products are reprocessed at the end of their life cycles. These findings demonstrate that combining open-loop recycling with additive manufacturing (AM) can effectively turn waste into high-quality, value-added products, advancing circularity and sustainable material innovation. Full article

Forests sustain high levels of biodiversity and essential ecosystem services, yet the impact of management practices on below-ground functioning remains difficult to assess. A comprehensive evaluation of ectomycorrhizal (ECM) fungal diversity is, therefore, required to better understand ecosystem dynamics. This study, conducted within the SelpiBioLife project, examined ECM community structure in two Pinus nigra J.F. Arnold forests in central Italy by integrating above- and below-ground sampling. Across 108 plots, ECM fruiting bodies (EMFb) were recorded during one fruiting season, and 54 soil cores were collected to characterize ECM root tips (EMRt) through morpho-anatomical analyses and ITS sequencing. Species richness and community composition were compared using rarefaction, PERMANOVA, NMDS, Mantel tests, and SIMPER analysis. A total of 70 EMFb species and 54 EMRt morphotypes were identified, displaying significant differences between sites and sampling types. EMFb surveys revealed greater richness, whereas EMRt reached sampling saturation only at one site, suggesting additional hidden diversity. Distinct community patterns were detected in ordination space, and weak correlations emerged between EMFb and EMRt dissimilarities, indicating complementary ecological information. These findings show that single-method monitoring underrepresents ECM diversity. Combined above- and below-ground investigations provide a more accurate basis for evaluating silvicultural impacts and maintaining forest ecosystem resilience. Full article

The rapid increase in retired lithium-ion batteries (LIBs) from electric vehicles (EVs) highlights the urgent need for accurate and automated end-of-life (EOL) assessment. This study proposes an AI-integrated smart grading system that combines hardware diagnostics and deep learning-based evaluation to classify the residual usability of retired batteries. The system incorporates a bidirectional charger/discharger, a CAN-enabled battery management system (BMS), and a GUI-based human–machine interface (HMI) for synchronized real-time data acquisition and control. Four diagnostic indicators—State of Health (SOH), Direct Current Internal Resistance (DCIR), temperature deviation, and voltage deviation—are processed through a deep neural network (DNN) that outputs categorical grades (A: reusable, B: repurposable, C: recyclable). Experimental validation shows that the proposed AI-assisted model improves grading accuracy by 18% and reduces total testing time by 30% compared to rule-based methods. The integration of adaptive correction models further enhances robustness under varying thermal and aging conditions. Overall, this system provides a scalable framework for automated, explainable, and sustainable battery reuse and recycling, contributing to the circular economy of energy storage. Full article

Silica fume (SF) is extensively utilized for enhancing concrete properties. This study examines the impact of SF dosage on concrete frost resistance. Specimens were produced by replacing cement with SF at 5%, 10%, 20%, and 30% ratios. Mechanical testing and microscopic characterization measured variations in mass loss, relative dynamic elastic modulus, flexural strength, hydration products, and pore structure. Digital image correlation tracked failure development during flexural tests. Results indicated that SF-modified concrete showed lower mass loss, better elastic modulus retention, and improved flexural strength maintenance compared to plain concrete after identical freeze–thaw (F-T) cycles. Additionally, SF-modified concrete demonstrated reduced crack widths and slower crack expansion during bending. The 10% SF mixture, after 300 cycles, achieved optimal results characterized by 2.83% mass loss, 88.1% relative dynamic modulus, and only a 17% flexural strength reduction. Microscopic studies confirm that SF addition increases calcium silicate hydrate formation, decreases calcium hydroxide levels, and refines pore structure with higher density. These modifications enhance frost resistance. A service-life prediction model using gray model approach methodology projected that 10% SF concrete would last 2.01 times longer than unmodified concrete under F-T exposure. Full article