Search Results (337)

This paper advances the development of Extrinsic Fabry–Pérot interferometry (EFPI) for high-precision pressure sensing. Presented is an EFPI featuring a diameter of 800 μ$\mathrm{m}$ with a 7.4 μ$\mathrm{m}$ diaphragm thickness, demonstrating a resolution of 3.35 $\mathrm{mPa}$ and a sensitivity of 149 $\mathrm{n}\mathrm{m}/\mathrm{kPa}$ positioning it amongst the most sensitive fibre optic pressure sensors ever developed, establishing a new benchmark for EFPI pressure-based systems. Numerous fabrication methods, including resin bonding, fusion splicing, and additive manufacturing, are investigated. In conjunction with this, multiple diaphragm reduction techniques such as manual polishing, automated polishing, and hydrofluoric acid etching are explored. The reason why we have not seen development of large core/diameter silica EFPI sensors, with advantages in sensitivity and resolution, is that the construction technique is difficult and unknown. The design construction, testing, and development of said large-diameter sensor is novel. This sub-Pascal resolution opens new possibilities for applications in microfluidics, atmospheric monitoring, and medical diagnostics where detecting minute pressure variations is critical. Finally, a comparative analysis of the sensor construction and diaphragm reduction methods provides insight into the future development of these high-performance EFPI sensors. Full article

Against the backdrop of increasing demands for the safety and longevity of the bridge infrastructure, this review synthesizes the recent advances in structural health monitoring (SHM) sensing systems. Carbon nanotube (CNT), piezoelectric, RFID, wireless, fiber optic, and computer-vision-based sensing are thoroughly explored and elucidated in the existing literature survey that distills their working principles, documented deployments, and anticipated research directions. CNT sensors detect minute resistance variations for strain and crack surveillance; piezoelectric devices transduce mechanical stimuli into high-resolution electrical signals; RFID tags combine location tracking with modular sensing and wireless data relay; and wireless sensing technology integrates sensor nodes with microprocessors and communication modules, which can facilitate efficient data processing and autonomous management. Fiber optic sensing technology, known for precision and interference resistance, is ideal for high-precision monitoring under strong electromagnetic interference conditions, and vision-based systems emulate human perception to extract geometric descriptors via image analytics. The comparative analysis reveals complementary strengths that guide practitioners in selecting optimal sensor suites for specific bridge conditions. The findings underscore the transformative role of these technologies in enhancing SHM reliability and suggest that synergistic integration with robotics and emerging materials will further advance future resilient monitoring frameworks. Full article

This study proposes a machine learning-based framework for classifying occupational stress levels among nurses using physiological time-series data collected from wearable sensors. The dataset comprises multimodal signals including electrodermal activity (EDA), heart rate (HR), skin temperature (TEMP), and tri-axial accelerometer measurements (X, Y, Z), which are labeled into three categorical stress levels: low (0), medium (1), and high (2). To enhance the usability of the raw data, a resampling process was performed to aggregate the measurements into one-minute intervals, followed by the application of the Synthetic Minority Over-sampling Technique (SMOTE) to mitigate severe class imbalance. Subsequently, a comparative classification analysis was conducted using four supervised learning algorithms: Random Forest, XGBoost, k-Nearest Neighbors (k-NN), and LightGBM. Model performances were evaluated based on accuracy, weighted F1-score, and confusion matrices to ensure robustness across imbalanced class distributions. Additionally, temporal pattern analyses by the day of the week and the hour of the day revealed significant trends in stress variation, underscoring the influence of circadian and organizational factors. Among the models tested, ensemble-based methods, particularly Random Forest and XGBoost with optimized hyperparameters, demonstrated a superior predictive performance. These findings highlight the feasibility of integrating real-time, sensor-driven stress monitoring systems into healthcare environments to support proactive workforce management and improve care quality. Full article

Polymer viscoelasticity is crucial for mechanical performance, but conventional low-frequency methods struggle to isolate viscous loss—a key viscosity indicator. This study introduces a high-frequency ultrasonic method to differentiate the polymer viscous dissipation index by analyzing acoustic phase shifts. We employ ultrasonic phase-shift thermometry to measure localized temperature increases resulting from minute variations in sound velocity during controlled heating. This allows for the quantification of viscous loss, which is then used to distinguish between different polymer formulations. Experimental and simulation results on a series of polyurethane specimens with varying Shore hardness levels demonstrate that decawatt-range (10–20 W) ultrasonic irradiation enables sensitive and precise differentiation. Notably, the Shore A70 polyurethane sample exhibited a significantly higher viscous dissipation index, evidenced by the largest temperature rise (27.5 °C) and the highest proportion of viscous heating to total power dissipation (93.1%) under 17 W acoustic irradiation. While this study focuses on commercially available polymers, the method can be extended to evaluate key performance parameters, such as tensile modulus and glass transition temperature, in polymers fabricated under various processing conditions, thereby offering a powerful tool for material quality assessment. Full article

This study presents a detailed experimental comparison of the rotordynamic and thermal performance of automotive turbochargers supported by two distinct hydrodynamic bearing configurations: fully floating ring bearings (FFRBs) and semi-floating ring bearings (SFRBs). While both designs are widely used in commercial turbochargers, they exhibit significantly different dynamic behaviors due to differences in ring motion and fluid film interaction. A cold air-driven test rig was employed to assess vibration and temperature characteristics across a range of controlled lubricant conditions. The test matrix included oil supply pressures from 2 bar (g) to 4 bar (g) and temperatures between 30 °C and 70 °C. Rotor speeds reached up to 200 krpm (thousands of revolutions per minute), and data were collected using a high-speed data acquisition system, triaxial accelerometers, and infrared (IR) thermal imaging. Rotor vibration was characterized through waterfall and Bode plots, while jump speeds and thermal profiles were analyzed to evaluate the onset and severity of instability. The results demonstrate that the FFRB configuration is highly sensitive to oil supply parameters, exhibiting strong subsynchronous instabilities and hysteresis during acceleration–deceleration cycles. In contrast, the SFRB configuration consistently provided superior vibrational stability and reduced sensitivity to lubricant conditions. Changes in lubricant supply conditions induced a jump speed variation in floating ring bearing (FRB) turbochargers that was approximately 3.47 times larger than that experienced by semi-floating ring bearing (SFRB) turbochargers. Furthermore, IR images and oil outlet temperature data confirm that the FFRB system experiences greater heat generation and thermal gradients, consistent with higher energy dissipation through viscous shear. This study provides a comprehensive assessment of both bearing types under realistic high-speed conditions and highlights the advantages of the SFRB configuration in improving turbocharger reliability, thermal performance, and noise suppression. The findings support the application of SFRBs in high-performance automotive systems where mechanical stability and reduced frictional losses are critical. Full article

Fish coloration plays an important role in reproduction and camouflage, yet capturing color variation under field conditions remains challenging. We present a standardized, semi-automated protocol for measuring body coloration in the popular model fish threespine stickleback (Gasterosteus aculeatus). Individuals are photographed in a controlled light box within minutes of capture, and color is sampled from eight anatomically defined standard sites in human-perception-based CIELAB space. Analyses combine univariate color metrics, multivariate statistics, and the ΔE* perceptual difference index to detect subtle shifts in hue and brightness. Validation on pre-spawning fish shows the method reliably distinguishes males and females well before full breeding colors develop. Although it currently omits ultraviolet signals and fine-scale patterning, the approach scales efficiently to large sample sizes and varying lighting conditions, making it well suited for population-level surveys of camouflage dynamics, sexual dimorphism, and environmental influences on coloration in sticklebacks. Full article

Background/Objectives: The Pleth Variability Index (PVI) is a non-invasive parameter used to guide fluid management by reflecting respiratory-induced variations in the plethysmographic waveform. While PVI’s reliability in various positions has been studied, data on its behavior in geriatric patients undergoing transurethral resection of the prostate (TUR-P) in the lithotomy position remain limited. This study aimed to evaluate the effect of the lithotomy position on PVI in geriatric versus non-geriatric patients under spinal anesthesia. Methods: This prospective observational study included 90 patients undergoing elective TUR-P in the lithotomy position under spinal anesthesia. Patients were divided into geriatric (≥65 years, n = 48) and non-geriatric (<65 years, n = 42) groups. PVI and Perfusion Index (PI) were recorded at baseline, in the supine position, and in the lithotomy position. Fluid and vasopressor requirements, along with hemodynamic parameters, were also analyzed. Results: PVI values at the 5th minute in the lithotomy position were significantly higher in the geriatric group compared to the non-geriatric group (p = 0.019). No significant differences were observed in PI values or intraoperative hypotension rates between the groups. Neurological comorbidities were more prevalent in the geriatric group (p = 0.025). Conclusions: PVI appears to be a more sensitive indicator of fluid responsiveness in elderly patients under spinal anesthesia in the lithotomy position. Its age-dependent variability suggests clinical utility in guiding fluid management in geriatric populations, while the stable hypotension rates support the effectiveness of PVI-guided goal-directed therapy. Full article

Global warming is driving significant changes in aquatic ecosystems, where temperature fluctuations influence biological processes across multiple levels of organisation. As ectothermic organisms, fish are particularly susceptible, with even minor thermal shifts affecting their metabolism, behaviour, and overall fitness. Understanding these responses is essential for evaluating the ecological and evolutionary consequences of climate change. This study investigates the effects of acute (4-day) and chronic (21-day) exposure to three temperature regimes—18 °C (low), 26 °C (control), and 34 °C (high)—on the spatio-temporal shoaling behaviour of adult zebrafish (Danio rerio). Groups of four fish were tested for six minutes in water maintained at the same temperature as their prior acclimation. Shoaling behaviour was assessed by analysing shoal structure—encompassing shoal dimensions and cohesion—as well as spatial positioning. Parameters measured included inter-fish distance, shoal volume, shoal area, homogeneity index, distance to the centroid, and the shoal’s vertical and horizontal distribution. Results revealed complex behavioural changes influenced by both temperature and duration of exposure. At 18 °C, zebrafish showed a marked preference for the bottom zone and exhibited no significant temporal modulation in exploratory behaviour—patterns indicative of heightened anxiety-like responses. In contrast, exposure to 34 °C resulted in increased shoal cohesion, particularly under chronic conditions, and a progressive increase in environmental exploration over the six-minute test period. This enhancement in exploratory activity was especially evident when compared to the first minute of the test and was characterised by greater vertical movement—reflected in the increased use of the upper zone—and broader horizontal exploration, including more frequent occupation of peripheral areas. These findings align with previous research linking thermal variation to neurobiological and proteomic alterations in zebrafish. By elucidating how temperature modulates social behaviour in ectotherms, this study offers valuable insights into the potential behavioural impacts of climate change on aquatic ecosystems. Full article

Background/Objectives: In the context of active ageing, functional assessment is key to preserving autonomy in older women. The six-minute walk test (6MWT) is a practical tool for estimating general health, but its results can be influenced by various factors. This study analysed cardiorespiratory variations during the 6MWT in older women according to their physical activity level and age-related variables such as pain, sarcopenia, frailty, and motivation to exercise. Methods: A total of 163 older women with musculoskeletal pain, but without cardiac or respiratory conditions, were classified into groups with high (HPA), moderate (MPA), and low (LPA) physical activity. During the 6MWT, heart rate (HR), dyspnoea, and oxygen saturation (SpO₂) were recorded. Pain, sarcopenia, frailty, and motivation to exercise were also assessed. A repeated-measures multivariate analysis of (co)variance (RM-MANCOVA) was performed. Results: The results showed differences in HR depending on the level of physical activity, conditioned by sarcopenia (p < 0.05) and walked distance (p < 0.001), and in dyspnoea conditioned by pain perception (p < 0.01) and social (p < 0.001) and psychological (p < 0.05) motivation to exercise. There were also differences in SpO₂ depending on the level of physical activity (p < 0.0001). There were differences between the HPA group and both the MPA and LPA group, which had higher HR, higher dyspnoea, and lower SpO₂ when undergoing the 6MWT test. Conclusions: To accurately interpret 6MWT results in older adult women, it is essential to consider physical activity level, perceived pain, sarcopenia, and motivation to exercise, as these factors influence HR, dyspnoea, and SpO₂. These variables should guide physical activity recommendations for healthy ageing. Full article

The development of multifunctional lubricant additives is critical for enhancing the performance and longevity of internal combustion engines. This study investigates the influence of oil additive, containing an atomic metal conditioner (AMC), a two-dimensional sliding agent, and a patented revitalizer on lubricating properties of engine oil 5W-30 and on surface wear characteristics. The experimental testing involved comparative tribological evaluation using the 4-ball test. Pure commercial engine oil (PEO) 5W-30 and oil mixed with the revitalizer additive (OMA) were used. The changes in friction torque (FTq), temperature, and wear scars were analyzed. FTq evolution showed a distinct behavior across the different test cases: PEO exhibited fluctuating FTq in the initial minute and thereafter, but its value was lower, and the wear scars were smaller compared to OMA. Long-duration tests revealed that OMA resulted in significantly larger wear scars, large FTq values, and less variations emerging later in the test. When switching from PEO (1 h) to OMA (1 h) mid-test, the wear increased compared to 2 h PEO. Across all conditions, oil temperature had a strong relationship with FTq. Although some frictional improvements were observed, no definitive evidence of revitalizer-induced surface regeneration was detected, suggesting adhesive wear remained predominant under the studied conditions. Full article

As climate change alters subarctic ecosystems and human activities in Alaska, ecological baselines are critical for long-term conservation. We applied an ecoacoustic approach to characterize the ecological conditions of a rapidly deglaciating region in Kenai Fjords National Park, Alaska. Using automated recording units deployed at increasing distances from a road, we collected over 120,000 one-minute audio samples during the tourist seasons of 2021 and 2022. Ecoacoustic indices—Sonic Heterogeneity Index (SHI_tf), Spectral Sonic Signature (SSS), Weighted Proportion of Occupied Frequencies (wPOF), and Normalized Difference Sonic Heterogeneity Index (NDSHI)—were used to measure spatio-temporal patterns of the sonoscape. Results revealed higher sonic heterogeneity near the road attributed to technophony (vehicles) and geophony (wind) that spanned across the frequency spectrum, masking mid-high frequency biophony. Seasonal phenology and diel variations reflected ecological and human rhythms, including biophony from the dawn chorus from May–June, technophony from vehicle-based tourism from July–September, and decreased sonic activity in the form of geophonic ambience in October. Low-frequency geophonies were prevalent throughout the sonoscape with more natural sounds at greater distances from the road. Our findings demonstrate the benefits of using ecoacoustic methods to assess ecosystem dynamics for establishing ecological baselines useful for future comparisons in rapidly changing environments. Full article

Buprenorphine has gained widespread popularity for use in rabbits, while much less is known about methadone. Our aim was to compare sedative, analgesic, and respiratory effects of methadone and buprenorphine as part of balanced anaesthesia. Forty-eight female New Zealand white rabbits undergoing calvaria defects were randomly equally assigned to receive either 0.03 mg kg⁻¹ of buprenorphine (group B) or 0.3 mg kg⁻¹ of methadone (group M) in combination with 15 mg kg⁻¹ of ketamine and 0.1 mg kg⁻¹ of dexmedetomidine SC. Fifteen minutes later, sedation was scored. A laryngeal mask was placed, and inhalational anaesthesia started. Rescue intraoperative analgesia was administered based on autonomic variations. Arterial blood gases were analysed intra- and postoperatively. Postoperative analgesia was administered if the Rabbit Grimace Scale (RbtGS) score was ≥4. The Mann–Whitney test, t-test, and relative risk followed by chi-square test were used to compare the treatment groups. Deeper sedation was observed in rabbits of group M than in those of group B. Rescue analgesia was administered intraoperatively to seven animals in group B and five in group M (p = 0.739) and postoperatively to three in group B and twelve in group M (p = 0.013). Rabbits of both groups showed short-term respiratory acidosis. RbtGS scores indicated better and longer analgesia in group B compared to group M. Full article

As renewable energy penetration and extreme weather events increase, accurately predicting power system behavior is essential for reducing risks and enabling timely interventions. This study presents a physics-informed learning approach to forecast transient voltage angles in power systems with integrated wind energy under gusty wind conditions. We developed a simulation framework that generates wind power profiles with significant gust-induced variations over a one-minute period. We evaluated the effectiveness of physics-informed neural networks (PINNs) by integrating them with LSTM (long short-term memory) and GRU (gated recurrent unit) architectures and compared their performance to standard LSTM and GRU models trained using only mean squared error (MSE) loss. The models were tested under three wind energy penetration scenarios—20%, 40%, and 60%. Results show that the predictive accuracy of PINN-based models improves as wind penetration increases, and the best-performing model varies depending on the penetration level. Overall, this study highlights the value of physics-informed learning for dynamic prediction under extreme weather conditions and provides practical guidance for selecting appropriate models based on renewable energy integration levels. Full article

Monitoring respiratory parameters is essential in pediatric intensive care units (PICUs), yet bedside tidal volume (Vt) measurement is rarely performed due to the need for invasive airflow sensors. We present a real-time, non-contact respiratory monitoring system using the Azure Kinect DK (Microsoft, Redmond, WA, USA) depth camera, specifically designed for use in the PICU. The system automatically tracks thoracic volume variations to derive a comprehensive set of ventilator equivalent parameters: tidal volume, respiratory rate, minute ventilation, inspiratory/expiratory times, I:E ratio, and peak flows. Results are displayed via an ergonomic web interface for clinical use. This system introduces several innovations: real-time estimation of a complete set of respiratory parameters, a novel infrared-based region-of-interest detection method using YOLO-OBBs, enabling robust operation regardless of lighting conditions, even in total darkness, making it ideal for continuous monitoring of sleeping patients, and a pixel-wise 3D volume computation method that achieves a mean absolute error under 5% on tidal volume. The system was evaluated on both a healthy adult (compared to spirometry) and a critically ill child (compared to ventilator data). To our knowledge, this is the first study to validate such a contactless respiratory monitoring system on a non-intubated child in the PICU. Further clinical validation is ongoing. Full article

This study investigates the relationship between methane emissions and physiological, behavioural, and haematological parameters in dairy cows during the transition period. Methane emissions were monitored alongside variations in rumination, feeding behaviour, and blood markers three weeks before calving, on calving day, and three weeks post-calving. Cows were retrospectively classified into low, medium, and high rumination groups according to their average daily rumination duration to investigate the effects of behavioural influences. During the prepartum period, the methane concentration was moderately positively correlated with drinking time (r = 0.41, p < 0.01) and weakly negatively correlated with chews per minute (r = −0.358, p < 0.05). Significant negative correlations were noted with chloride (r = −0.42, p < 0.01) and glucose levels (r = −0.41, p < 0.01). Following calving, methane emissions showed a positive correlation with haematocrit (r = 0.41, p < 0.01) and a negative correlation with haemoglobin (r = −0.47, p < 0.01). A haematological analysis revealed a notable negative correlation with platelets during calving (r = −0.64, p < 0.05). Individual dry matter intake (DMI) was recorded for each period, showing a significant drop on calving day. This intake fluctuation coincided with a significant rise in methane yield on calving day (p < 0.001). In the low rumination time group, methane was moderately negatively correlated with rumination chews (r = −0.52, p < 0.05), while in the high rumination group, a moderate negative correlation was observed with drinking gulps (r = −0.42, p < 0.05), and a weak negative correlation was observed with bolus events (r = −0.37, p < 0.05). Despite behavioural variations, methane emissions showed no substantial differences among groups with low, medium, and high rumination times, suggesting a minimal direct influence on rumination duration. These findings emphasise the complex interactions between feed intake, metabolism, and methane emissions, underscoring the importance of integrating behavioural and physiological indicators to develop targeted strategies for enteric methane mitigation while providing baseline data from healthy cows that could guide future research on methane emissions in cows undergoing postpartum metabolic disorders. Full article