Search Results (46,387)

Contactless monitoring of vital signs such as heart rate (HR) and respiratory rate (RR) has gained significant attention, with vibration-based sensors like geophones showing promise for accurate, non-invasive monitoring. However, most existing systems are developed with healthy subjects and may not generalize well to extreme physiological ranges, such as those observed in infants or patients with arrhythmia. Moreover, the underlying mechanisms of cardiorespiratory vibration dynamics remain insufficiently understood, limiting clinical adoption of these systems. To address these challenges, we present a programmable cardiorespiratory testbed capable of generating realistic HR and RR signals across a wide range (HR: 40–240 bpm, RR: 8–40 bpm). Our system uses a voice coil motor that acts as the vibration source, driven by a Raspberry Pi-based control circuit. Unlike similar systems that use separate modules for heart and lung signals, our setup generates both signals using a single motor. The synthetic signals exhibit a strong correlation of 0.85 compared with data from 75 human subjects. We use this system to design signal processing-based algorithms for vital signs monitoring and demonstrate their robustness for extreme physiological ranges. The proposed system enhances the understanding of cardiorespiratory vibration dynamics while significantly reducing the time and effort required to collect real-world data. Full article

This experimental review discusses evolutionarily approved, naturally pre-designed skeletal architectures of marine keratosan sponges in the form of 3D scaffolds, which have garnered increasing interest in the fields of structural and functional biomimetics as well as in tissue engineering. It has been demonstrated that these renewable, ready-to-use natural scaffolds can undergo further modifications through specialized treatments such as metallization and carbonization, enabling the creation of functional biomaterials while maintaining the species-specific hierarchical 3D structure. The study presented remarkable findings, including the demonstration of the unique shape-memory behavior of these scaffolds even after two months of exposure to high mechanical pressure at temperatures exceeding 100 °C. Additionally, the cytocompatibility and biological performance of natural and carbonized (1200 °C) spongin scaffolds, derived from selected bath sponges, were comparatively investigated with respect to growth and proliferation of human MG-63 osteoblastic cells. Understanding whether carbonization universally enhances osteogenic capabilities or selectively amplifies the inherent architectural advantages remains to be critical for the rational design of sponge-derived scaffolds in bone and structural tissue engineering applications. Full article

As global climate change intensifies and extreme weather events become more frequent, understanding the historical spatial distribution of vegetation is of critical importance. However, most vegetation studies are temporally limited to the post-1980 period due to satellite data constraints. To bridge this gap, we integrated tree-ring width chronologies from the International Tree-Ring Databank with Landsat-derived Enhanced Vegetation Index (EVI) data and evaluated three machine learning models—Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN)—to reconstruct annual, spatially explicit EVI for the period 1850–1985 in Diqing, Yunnan, China. RF regression was the best among the three with highest adjusted R² (0.90) and lowest Root Mean Square Error (0.032). The RF-based reconstruction indicated a consistent increase in regional EVI from 1991 to 2005. Breakpoint analysis identified three distinct sub-periods, each with unique spatiotemporal variation patterns. In current times, the EVI value shows a significant positive correlation with average temperatures in June, July, August, and December. In the contemporary period, it also correlates significantly and positively with winter average temperatures, March average precipitation, and spring average precipitation. The spatial pattern for the past 100 years reflects the succession of the local vegetation ecosystem and provides an insight into the influences of natural disturbances (low-temperature damages and droughts) on vegetation growth. This study demonstrates the feasibility of reconstructing high-resolution, long-term vegetation spatial dynamics using tree-ring proxies and machine learning. Full article

Background: Yoga has gained popularity worldwide and is generally considered a safe physical activity. However, injuries associated with yoga practice are increasingly reported, while data on cases requiring emergency care remain limited. Methods: A retrospective single-center study was conducted, analyzing cases of yoga-related injuries treated at a Swiss emergency department between 2013 and 2023. Medical records of 67 adult patients (aged ≥16 years) were reviewed for demographics, injury characteristics, management, and clinical outcomes. The study population consisted predominantly of females (76.1%), with a median age of 35 years. Results: Most injuries were musculoskeletal in nature and predominantly affected a single body region (95.5%). The most frequently involved areas were the head (29.9%), lower extremities (25.4%), and spine (19.4%). Soft tissue injuries, particularly muscle and tendon strains as well as contusions, were most common. Injury patterns differed across subgroups: older patients were more likely to sustain head injuries, whereas younger individuals more frequently presented with extremity injuries, including the rare cases of fractures and dislocations. Conservative treatment was sufficient in 94% of cases, although 20.9% of patients required hospitalization. Conclusion: Yoga-related injuries presenting to emergency care are generally minor and mainly involve soft tissues; however, injury patterns vary across demographic subgroups. Older adults appear more susceptible to balance-related and head injuries, while younger practitioners are more prone to acute extremity trauma. Recognizing these population-specific differences may support targeted prevention strategies and safer yoga practice. Full article

The effect of sinusoidal Extremely Low-Frequency Electromagnetic Fields (ELF-EMFs) on gynecological (HeLa, ES-2) and urological (DU-145) cancer cells was investigated. ELF-EMFs with a frequency of 50 Hz and a magnetic flux density of 1.3 mT were applied for 15 and 30 min. The experiment was conceptualized to investigate the in vitro short-term effects of ELF-EMFs on cell reactive oxygen species (ROS) formation, the levels of genes and proteins involved in DNA damage response, and epigenetic modifications. Here, we found that ELF-EMFs treatment leads to an elevation in the ROS levels that contribute to distinct scenarios in the studied cancer cells. The most prominent changes in the studied factors were found in ES-2 and DU-145 cells exposed to 30 min of ELF-EMFs. ES-2 cells exhibited upregulation of XRCC5 gene expression and elevated levels of several proteins: TNF-α, RAD51, APE1, XRCC1, and NSUN2. Diminished levels of BCL-2, HSP90, RAD51, and TNF-α, as well as overexpression of VIM and METTL3, were observed in DU-145 cells. In summary, we postulate that short-term exposure to 50 Hz ELF-EMFs may be a promising treatment strategy for gynecological and urological cancer cells. Full article

The accurate prediction of extreme dynamic amplification factor (DAF) values is significantly important to ensure a long-term safety assessment of bridges under stochastic vehicular loading. However, predicting extreme DAFs is challenging due to traffic randomness, road roughness variability, and nonlinear vehicle–bridge interaction (VBI) effects. This study presents an integrated framework for extreme DAF prediction for simply supported bridges by combining stochastic traffic–bridge interaction simulations with Bayesian updating and a Peaks-Over-Threshold–Generalized Pareto Distribution (POT–GPD) model. A coupled VBI model is developed, incorporating cellular automaton-based traffic flow, multi-axle nonlinear vehicle dynamics, finite-element bridge modeling, and stochastic road roughness profiles. A new DAF definition based on dynamic displacement difference is proposed to better represent dynamic effects. DAF samples obtained from VBI simulations under different road roughness levels are analyzed using the POT method, with GPD parameters estimated through maximum likelihood and Bayesian inference. Extreme DAFs corresponding to different return periods are then determined. The results indicate that extreme DAF values increase with worsening road roughness and longer return periods and that the Bayesian POT–GPD approach effectively captures tail behavior while providing reliable uncertainty quantification for extreme DAF prediction. Full article

One of the key artefacts of epigraphy in Southeast Asia is the Singapore Stone inscription, which is, unfortunately, in a poor condition. There are huge spaces that separate the readable characters, rendering the text incomplete. This renders a traditional reconstruction and interpretation by philologists extremely challenging. We consider epigraphic restoration as a data-restoration task in this paper. We represent the inscription as a system of categorical symbols, in keeping with the original spatial disposition of characters and spaces. Our model is trained in a conservative, data-driven manner using the observed symbols to learn the local transition statistics, and it takes advantage of this information to make plausible predictions of the most likely characters in missing sequences that are short and well-constrained. The procedure generates a probabilistic hypothesis of restoration, which can be audited, as opposed to one definitive reading. The validation of masked-character recovery demonstrates that the model has a mean top-one error of 53.3%, which represents a significantly worse performance compared with simple baseline methods. The process is focused on interaction and transparency with experts. It relies upon assurance scores and prioritised alternative completions of each proposed reconstruction, as a useful means to produce hypotheses in computational epigraphy and the digital humanities. Full article

This research focused on the systematic engineering of processing parameters to obtain novel hydrocolloids from cassava (Manihot esculenta), specifically investigating how extraction pH controls their functional and physicochemical properties. Hydrocolloids were obtained across a range of pH conditions, followed by rigorous analysis of their chemical composition, flow behavior, viscoelasticity, and technological capacity, including water and oil holding capacity (WHC and OHC). The study established that hydrocolloids yield can be decoupled from extreme pH constraints, as high yields were successfully attained in both acidic and alkaline environments, thereby identifying a critical and flexible processing window for scalable production. Compositionally, the extracts confirmed their potential as functional additives due to a high carbohydrate content and minimal fat. Crucially, the extracted hydrocolloids exhibited strong structural performance, displaying high water and oil retention capacity—metrics essential for emulsion stability and shelf life—while consistently confirming desirable shear-thinning behavior across all effective extraction conditions. In conclusion, these results demonstrate that hydrocolloids derived from cassava are versatile stabilizers whose robust structural performance is maintained across varying processing pH levels, positioning them as promising, cost-effective alternatives for developing resilient, stable food matrices. Full article

Interest in wind energy systems of different power ratings has increased significantly in recent years; however, low-power wind turbines are particularly sensitive to wind gust disturbances, which strongly affect their power electronic systems. In this work, a control strategy is proposed for regulating the output voltage of a buck converter integrated into a small wind turbine. To this end, a symmetric variable gain is incorporated into the classical sliding mode control framework, enabling the controller to dynamically adjust the control effort according to the operating conditions. The main objective of the proposed approach is to mitigate output voltage fluctuations induced by Extreme Operating Gusts (EOGs), which have a more pronounced impact on low-power wind turbines. The effectiveness of the proposed controller is validated through both simulation and experimental results. Full article

This study presents an operational approach to atmospheric wind profiling using a purpose-built meteorological uncrewed aerial vehicle (UAV) and an orientation-based wind estimation method that does not rely on dedicated onboard anemometers. The quadrotor platform, designed and developed by our team, has a maximum take-off mass of 2.45 kg and is capable of acquiring vertical atmospheric profiles up to 3000 m under a wide range of weather conditions. Within the framework of the World Meteorological Organization’s (WMO) global demonstration campaign for evaluating the use of uncrewed aircraft systems in operational meteorology and associated field activities, twelve vertical wind profiles were collected in parallel with radiosonde observations. UAV-based wind estimates were evaluated against radiosonde data using the WMO OSCAR (Observing Systems Capability Analysis and Review) performance framework. Across most wind speed regimes, the central 50% of UAV–radiosonde wind speed differences remain within OSCAR threshold requirements, indicating operationally relevant accuracy. Systematic deviations are physically interpretable and arise primarily in strongly sheared boundary-layer flows. A representative low-level jet case is used as a stress test, demonstrating that the UAV system remains safe and that wind estimates remain reliable even under extreme wind conditions, supporting robust performance in less demanding regimes. These results establish UAV-based wind profiling as a viable and complementary observing technique in the lower atmosphere and provide a practical pathway toward high-resolution, operational boundary-layer wind measurements. Full article

Despite extensive research on blast-resistant concrete structures, a clear scientific deficiency remains in the quantitative understanding of how fiber-reinforced concrete slabs behave under blast loading, particularly when experimental and numerical investigations are not conducted together under identical loading conditions. Existing studies often focus on either conventional reinforced concrete or isolated material systems, providing limited validation of comparative blast performance across different fiber-reinforced concretes. This study addresses this gap by investigating the blast resistance performance of four types of reinforced concrete slabs: normal concrete (NC), ultra-high-performance fiber-reinforced concrete (UHPFRC), organic fiber-reinforced high-performance concrete (O-HPC), and basalt FRP-sheet-strengthened slurry-infiltrated fiber concrete (F-SIFCON), using full-scale blast experiments and validated numerical simulations conducted with ANSYS Explicit Dynamics. Blast tests were performed to obtain time histories of reflected pressure, displacement, acceleration, reaction force, and internal energy. The influence of different fiber systems and FRP strengthening on dynamic response and failure mechanisms was systematically analyzed. The numerical models showed good agreement with experimental measurements, confirming their reliability. The results indicate that the normal concrete slab exhibited brittle failure and poor blast resistance, whereas the F-SIFCON slab demonstrated the best overall performance. Compared with the normal concrete slab, the F-SIFCON slab achieved approximately a 47% reduction in maximum displacement, a 56% increase in peak reaction force, and the highest internal energy absorption of 236 kJ. The UHPFRC and O-HPC slabs also showed improved blast resistance, although with different post-peak response characteristics. These findings demonstrate that hybrid fiber reinforcement combined with FRP strengthening can significantly enhance the blast resistance of concrete slabs and that coupled experimental–numerical approaches provide a robust framework for evaluating structural performance under extreme dynamic loading. Full article

Recent developments in unmanned aerial vehicle (UAV) activity highlight the need for advanced electromagnetic spectrum monitoring systems that can detect drones operating near sensitive or restricted areas. Such systems can identify emissions from drones even under frequency-hopping conditions, providing an early warning system and enabling a timely response to protect critical infrastructure and ensure secure operations. In this context, the present work proposes the development of a high-performance multichannel broadband monitoring system with real-time analysis capabilities, designed on an SDR architecture based on USRP with three acquisition channels: two broadband (160 MHz and 80 MHz) and one narrowband (1 MHz) channel, for simultaneous, of extended spectrum segments, aligned with current requirements for analyzing emissions from drones in the 2.4 GHz and 5.8 GHz ISM bands. The processing system was configured to support cumulative bandwidths of over 200 MHz through a high-performance hardware platform (powerful CPU, fast storage, GPU acceleration) and fiber optic interconnection, ensuring stable and lossless transfer of large volumes of data. The proposed spectrum monitoring system proved to be extremely sensitive, flexible, and extensible, achieving a reception sensitivity of −130 dBm, thus exceeding the values commonly reported in the literature. Additionally, the parallel multichannel architecture facilitates real-time detection of signals from different frequency ranges and provides a foundation for advanced signal classification. Its reconfigurable design enables rapid adaptation to various signal types beyond unmanned aerial systems. Full article

Climate change increasingly affects the sustainability and reliability of urban water and wastewater infrastructure. This study analyzes the relationship between climatic variables and the frequency of failures in water and sewage networks in northeastern Poland, using operational data from the Mrągowo system (2020–2023) and meteorological records from 1966 to 2023. Statistical analyses and trend assessments were employed to identify climate-related failure patterns and infrastructure vulnerabilities. Climatic parameters—including temperature extremes, precipitation, snow cover, and sunshine duration—were analyzed in relation to infrastructure reliability. The results indicate rising temperatures, reduced snowfall, and altered precipitation regimes. Although extreme cold corresponded with increased sewage network failures, no significant association was found for high temperatures. Precipitation and snow cover showed weak correlations, except during heavy rainfall events. The study highlights the need to integrate climate resilience into water infrastructure management through preventive maintenance, smart monitoring, and nature-based solutions. Findings contribute to sustainable urban development strategies by demonstrating how climate variability directly affects service reliability. By identifying climate-sensitive failure thresholds, the study supports sustainable infrastructure management by enabling risk-informed adaptation strategies that reduce service disruptions, resource losses, and environmental impacts. This case study offers methodological insights and empirical evidence that may support the assessment of climate-related vulnerability of water and wastewater infrastructure in similar urban contexts. Full article

In the extreme high-temperature (up to 150 °C) and high-pressure (up to 140 MPa) conditions of deep in situ condition-preserved coring devices, high-strength epoxy resin was selected as the insulation layer. The non-isothermal DSC method was employed at heating rates of 2.5, 5, 10, 15, and 20 °C/min, revealing that increasing the heating rate elevates curing temperatures, expands the curing range, and enhances curing rate and heat release. The curing kinetics were modeled using n-order and autocatalytic approaches, with the latter accurately describing the behavior. Optimized integration process conditions (80 °C/4 h + 150 °C/2 h + 180 °C/3 h) yielded epoxy with compressive strength of 204.47 MPa, initial thermal decomposition temperature of 345.9 °C, thermal conductivity of 0.246 W/m·K, and T_g of 193.04 °C (storage modulus 2.41 GPa at 150 °C). As insulation, it reduces rock core heat loss by 32.38% (8.78 × 10⁴ J) and active heating demand by 44 W, enhancing system stability for in situ temperature preservation. Full article

Green Infrastructure (GI) is crucial for urban climate adaptation, providing ecosystem services like mitigating the urban heat island effect and enhancing stormwater management, alongside benefits for public health and biodiversity. Effective GI implementation remains challenging, particularly in dense, rapidly urbanized mid-Adriatic coastal cities, classified as climate hotspots like other Mediterranean contexts. This paper presents a replicable applied trans-scalar methodology for detailed GI design scenarios, developed through the EU-funded LIFE+ A_GreeNet project to bridge the theory–practice gap and enable pilot implementations in multiple Italian mid-Adriatic coastal municipalities. The research details a comprehensive, multi-disciplinary, five-phase process applied to the Sant’Antonio district of San Benedetto del Tronto—a dense, trafficked urban area projected to face “extremely strong heat stress” by 2050. Design interventions included spatial optimization, strategic species replacement, the creation of vegetated bioretention basins, and systematic pavement de-sealing. The application of the model demonstrated significant improvements: a substantial increase in permeable surface area (+194%), a measurable reduction in the UTCI index (average ENVI-MET simulated reduction of 1.17 °C by 2030), and a series of benefits resulting from increased green space and enhanced meteorological water management. This research offers local authorities a tangible model to accelerate climate-adaptive solutions, showing how precise GI design creates resilient, comfortable, and human-centered urban spaces. Full article