Search Results (935)

The aetiology of invasive candidiasis is undergoing substantial changes; traditionally, these mycoses have been considered to originate from endogenous reservoirs; however, the increasing prevalence of non-Candida albicans species, such as Candida parapsilosis and Candida auris (also named Candidozyma auris), is a cause of concern as they demonstrate significant exogenous transmission. This challenges the long-standing paradigm of endogenous origin in hospital settings. Unlike previous reviews primarily focused on clinical epidemiology, this work adopts a multidisciplinary perspective combining microbiological evidence with biomaterials science. We analyse how surface roughness, hydrophobicity, and polymer composition within the hospital “plastisphere” influence Candida adhesion and the formation of dry surface biofilms (DSBs). In this specific context, in contrast to C. albicans, primarily associated with mucosal colonisation, C. auris and C. parapsilosis exhibit distinctive adaptations that promote survival in healthcare environments, including pronounced cell surface hydrophobicity and the capacity to form dense cellular aggregates, which facilitate prolonged adherence to synthetic polymers used in medical devices. We also explore the biological mechanisms underlying this resilience, with particular emphasis on the development of dry surface biofilms and viable but non-culturable states. These phenotypic traits confer tolerance to desiccation and resistance to conventional disinfectants, raising concerns that standard hygiene and decontamination protocols may be inadequate to prevent transmission. Understanding these mechanisms is essential for designing effective infection control strategies and mitigating the risk of invasive disease caused by these highly persistent species. Full article

This research investigates the effects of corona plasma treatment on the mechanical properties of jute/epoxy-reinforced composites, particularly within biomedical application contexts. Plant Fibre Composites (PFCs) are attractive for medical devices and scaffolds due to their environmental friendliness, renewability, cost-effectiveness, low density, and high specific strength. However, their applications are often constrained by inferior mechanical performance arising from poor bonding between the plant fibre used as the reinforcement and the synthetic resin or polymer serving as the matrix. This study addresses the challenge of improving the weak interfacial bonding between plant fibre and synthetic resin in a 2/2 twill-weave-woven jute/epoxy composite material. The surface of the jute fibre is modified for better adhesion with the epoxy resin through plasma treatment, which exposes the jute fibre to controlled plasma energy and utilises dry air (plasma only), argon (Ar) (argon gas with plasma), and nitrogen (N₂) (nitrogen gas with plasma) at two different distances (25 mm and 35 mm) between the plasma nozzle and the fibre surface. In this context, “equilibrium” refers to the optimal combination of plasma power, treatment distance, and gas environment that collectively determines the degree of fibre surface modification. The results indicate that all plasma treatments improve the interlaminar shear strength in comparison to untreated samples, with treatments at 35 mm using N₂ gas showing a 35.4% increase in shear strength. Conversely, plasma treatment using dry air at 25 mm yields an 18.3% increase in tensile strength and a 35.7% increase in Young’s modulus. These findings highlight the importance of achieving an appropriate equilibrium among plasma intensity, treatment distance, and fibre–plasma interaction conditions to maximise the effectiveness of plasma treatment for jute/epoxy composites. This research advances sustainable innovation in biomedical materials, underscoring the potential for improved mechanical properties in environmentally friendly fibre-reinforced composites. Full article

A dew-point evaporative air cooler incorporating a novel segmented heat exchange design, demarcated according to the humidity state of moist air, is proposed. The system employs a porous fibrous material to create a wetted evaporative surface, which is continuously maintained in a moistened condition through a self-wicking water supply mechanism to enhance latent heat transfer. Circular fins are installed on the heat exchanger’s partition surface once the moist air reaches saturation, thereby improving sensible heat exchange between the dry and wet channels. The performance of a prototype was evaluated under controlled conditions in a standard enthalpy chamber. Experimental results indicate that, under typical summer conditions (inlet dry-bulb and wet-bulb temperatures of 33.8 °C and 25.4 °C, respectively), with an air mass flow ratio of 0.7 and an air velocity of 1.5 m/s, the wet-bulb effectiveness reaches 114.4% and the dew-point effectiveness achieves 84.8%. The maximum temperature reduction occurs in the sensible heat exchange section, reaching up to 6.1 °C, demonstrating its substantial sensible heat recovery capability. The device exhibits an energy efficiency ratio (EER) ranging from 9.1 to 31.8. The proposed compact configuration not only enhances energy efficiency but also reduces material costs by approximately 15.4%, providing a valuable reference for the future development of dew-point evaporative cooling systems in residential buildings. Full article

Projects integrating Science, Technology, Engineering, and Mathematics (STEM) are essential to interdisciplinary research. This study presents a STEM (Science, Technology, Engineering, and Mathematics) methodology with the primary objective of designing, constructing, and validating a functional cannabinoid extraction device. To inform the device’s drying parameters, the dehydration kinetics of female hemp buds or flowering buds (FHB) were first analyzed using infrared drying at 100 °C for different durations. The plants were cultivated and harvested in accordance with good agricultural practices using Dinamed CBD Autoflowering seeds. The FHB were harvested and prepared by manually separating them from the stems and leaves. Six 5 g samples were prepared, each with a slab geometry of varying surface area and thickness. Two of these samples were ground: one into a fine powder and the other into a coarse powder. Mathematical fits were obtained for each resulting curve using either an exponential decay model or the logarithmic equation $y\left(t\right)=A\left(e^{-kt}\right)+y_0$ calculate the equilibrium moisture (m_E). The Moisture Rate (MR) was calculated, and by modelling with the logarithmic equation, the constant k and the effective diffusivity (Deff) were determined with the analytical solution of Fick’s second law. The Deff values (ranging from 10⁻⁷ to 10⁻⁵) were higher than previously reported. The coarsely ground powder sample yielded the highest k and Deff values and was selected for oil extraction. The device was then designed using Quality Function Deployment (QFD), specifically the House of Quality (HoQ) matrix, to systematically translate user requirements into technical specifications. A 200 g sample of coarsely ground, dehydrated FHB was prepared for ethanol extraction. Chemical results obtained by Liquid Chromatography coupled with Photodiode Array Detection (LC-PDA) revealed the presence of THC, CBN, CBC, and CBG. The extraction device design was validated using previous results showing the presence of CBD and CBDA. The constructed device successfully extracted cannabinoids, including Δ9-THC, CBG, CBC, and CBN, from coarsely ground FHB, validating the integrated STEM approach. This work demonstrates a practical framework for developing accessible agro-technical devices through interdisciplinary collaboration. Full article

The inner spacer module, which profoundly affects the final performance of a device, is a critical component in GAA NSFET (Gate-all-around Nanosheet Field Effect Transistor) manufacturing and necessitates systematic optimization and fundamental innovation. This work aims to develop an advanced SiGe etching process with high selectivity, uniformity and low damage to achieve an ideal inner spacer structure for logic GAA NSFETs. For three distinct dry etching technologies, ICP (Inductively Coupled Plasma Technology), RPS (Remote Plasma Source) and Gas Etching, we evaluated their potential and comparative advantages for inner spacer cavity etching under the same experimental conditions. The experimental results demonstrated that Gas Etching technology possesses the uniquely high selectivity of the SiGe sacrificial layer, making it the most suitable approach for inner spacer cavity etching to reduce Si nanosheet damage. Based on the results, in the stacked structures, the SiGe/Si selectivity ratio exhibited in Gas Etching is ~9 times higher than ICP and ~2 times higher than RPS. Through systematic optimization of pre-clean conditions, temperature and chamber pressure control, we successfully achieved a remarkable performance target of cavity etching: the average SiGe/Si etching selectivity is ~56, the inner spacer shape index is 0.92 and the local etching distance variation is only 0.65 nm across different layers. These findings provide valuable guidance for equipment selection in highly selective SiGe etching and offer critical insights into key process module development for GAA NSFETs. Full article

Meibomian gland dysfunction (MGD) is a leading cause of dry eye disease, assessable through gland atrophy degree. While deep learning (DL) has advanced meibomian gland (MG) segmentation and MGD classification, existing methods treat these tasks independently and suffer from domain shift across multi-center imaging devices. We propose ADAM-Net, an attention-guided unsupervised domain adaptation multi-task framework that jointly models MG segmentation and MGD classification. Our model introduces structure-aware multi-task learning and anatomy-guided attention to enhance feature sharing, suppress background noise, and improve glandular region perception. For the cross-domain tasks MGD-1K→{K5M, CR-2, LV II}, this study systematically evaluates the overall performance of ADAM-Net from multiple perspectives. The experimental results show that ADAM-Net achieves classification accuracies of 77.93%, 74.86%, and 81.77% on the target domains, significantly outperforming current mainstream unsupervised domain adaptation (UDA) methods. The F1-score and the Matthews correlation coefficient (MCC-score) indicate that the model maintains robust discriminative capability even under class-imbalanced scenarios. t-SNE visualizations further validate its cross-domain feature alignment capability. These demonstrate that ADAM-Net exhibits strong robustness and interpretability in multi-center scenarios and provide an effective solution for automated MGD assessment. Full article

This study focused on developing and validating machine learning models to predict pavement marking retroreflectivity using Light Detection and Ranging (LiDAR) intensity data. The retroreflectivity data was collected using a Mobile Retroreflectometer Unit (MRU) due to its increasing acceptance among states as a compliant measurement device. A comprehensive dataset was assembled spanning more than 1000 miles of roadways, capturing diverse marking materials, colors, installation methods, pavement types, and vehicle speeds. The final dataset used for model development focused on dry condition measurements and roadway segments most relevant to state transportation agencies. A detailed synchronization process was implemented to ensure the accurate pairing of retroreflectivity and LiDAR intensity values. Using these data, several machine learning techniques were evaluated, and an ensemble of gradient boosting-based models emerged as the top performer, predicting pavement retroreflectivity with an R² of 0.94 on previously unseen data. The repeatability of the predicted retroreflectivity was tested and showed similar consistency as the MRU. The model’s accuracy was confirmed against independent field segments demonstrating the potential for LiDAR to serve as a practical, low-cost alternative for MRU measurements in routine roadway inspection and maintenance. The approach presented in this study enhances roadway safety by enabling more frequent, network-level assessments of pavement marking performance at lower cost, allowing agencies to detect and correct visibility problems sooner and helping to prevent nighttime and adverse weather crashes. Full article

The unique material properties of Cyperus esculentus L. seeds present challenges for precision seeding, as no specialized seed-metering device is currently available. In practice, general-purpose planters such as peanut seeders are often adapted for this crop. However, the dry seeds of C. esculentus exhibit an irregular shape, uneven surface texture, significant size variation, and poor flowability, leading to inadequate seed pickup and suboptimal seeding performance in conventional metering devices. To address these issues, two types of seed pickup devices—one with a V-shaped scoop and the other with an arc-shaped scoop—were designed to improve the seed-filling process and enhance seed agitation within the seed pool. A comparative analysis of the material properties of seeds before and after soaking was conducted, and key structural parameters of the scoops were determined based on the post-soaking characteristics. A mechanistic analysis was performed to clarify the operational principles and influencing factors of the scoop-based pickup mechanism. Using EDEM software (2022 version), the motion characteristics of seeds inside the metering device were observed, and the agitating speed of the seed population was compared with and without the scoop devices. Performance comparison experiments were carried out with two scoop types under varying conditions, including metering disc rotation speed, seed size grade (large, medium, and small), and seed moisture state (dry vs. soaked). Simulation results of seed disturbance indicated that the V-shaped scoop significantly enhanced agitation intensity, with a maximum movement velocity 15.8% higher than that of the arc-shaped scoop. The V-shaped scoop demonstrated superior stability and adaptability across different seed sizes, rotation speeds, and moisture conditions. Seed pickup success rates reached 96%, 96%, and 85% for large, medium, and small seeds, respectively. Under high-speed operation (40 r/min), the V-shaped scoop showed a 9% lower miss-seeding rate compared to the arc-shaped scoop. Full article

A portable and integrated monitoring device was developed to digitally assess both water levels and surrounding fire-related conditions in forest firefighting water buckets using multi-sensor fusion. The system integrates a hydrostatic liquid-level sensor with temperature–humidity and smoke sensors. Validation was performed through field-oriented experiments conducted under semi-controlled conditions. Water-level measurements were collected over a three-month period under simulated forest conditions and benchmarked against conventional steel-ruler readings. Early-stage fire monitoring experiments were carried out using dry wood and leaf litter under varying wind speeds, wind directions, and representative extreme weather conditions. The device achieved a mean water-level bias of −0.60%, a root-mean-square error of 0.64%, and an overall accuracy of 99.36%. Fire monitoring reached a maximum detection distance of 7.30 m under calm conditions and extended to 16.50 m under strong downwind conditions, with performance decreasing toward crosswind directions. Stable operation was observed during periods of strong winds associated with typhoon events, as well as prolonged high-temperature exposure. The primary novelty of this work lies in the conceptualization of a Collaborative Forest Resource–Hazard Monitoring Architecture. Unlike traditional isolated sensors, our proposed framework utilizes a dual-domain decision-making model that simultaneously assesses water-bucket storage stability and micro-scale fire threats. By implementing a robust ‘sensing–logic–alert’ framework tailored for rugged environments, this study offers a new methodological reference for the intelligent management of forest firefighting resources. Full article

This work focuses on testing and validating a prototype device for measuring mass transfer phenomena in biomass drying processes, patented by the Universitat Politècnica de València (UPV) and Escuela Politécnica del Litoral (ESPOL), WO2025/109237 A1. The first step involved evaluating and calibrating the sensors of the measuring device to ensure accurate and consistent measurements. Subsequently, extensive tests were conducted to validate the prototype’s functionality for obtaining mass diffusivity and the mass transfer coefficient by convection at the solid-air interface. Finally, the results obtained were compared with those provided by existing predictive theoretical models in the literature. Areas for improvement in the theoretical models were identified, and adjustments were made to optimize prediction. The study highlights that the theoretical Sherwood method for estimating the mass transfer coefficient shows discrepancies with experimental data, mainly due to the assumption that the transfer coefficient remains constant during drying, whereas it actually varies with the material’s moisture content. This leads to inaccuracies that affect the efficiency of industrial drying systems. The prototype proved effective in measuring both diffusivity and mass transfer coefficient, validating the method. Full article

In this study, a high-performance MoS₂-based strain-gauge pressure was sensor fabricated entirely below 80 °C, enabling direct integration onto flexible polyethylene terephthalate (PET) substrates. The sensor comprised a three-layer MoS₂ channel (~2 nm) patterned via dry transfer and O₂/Ar plasma etching, interfaced with Cr/Au electrodes. This wafer-scale and cost-effective fabrication route preserves the crystallinity of the film and prevents substrate degradation. The sensor achieved a gauge factor of ~104 under compression, representing a fifty-fold improvement over conventional metal foil gauges (~2), with a linear response across both compressive and tensile regimes. Mechanical robustness was confirmed through repeated bending and tape adhesion tests, with no degradation in electrical performance. When configured as a Wheatstone bridge, this device exhibits normalized sensitivity suitable for real-time monitoring, with response and recovery times below 200 ms. These results establish O₂/Ar-plasma-patterned MoS₂ architectures as a scalable, cost-effective platform for next-generation flexible sensors, outperforming metal-foil technology in applications including seat-occupancy detection, wearable physiological monitoring, and tactile interfaces for soft robotics. Full article

Appliance recognition from aggregate household measurements is challenging under real deployment conditions, where multiple devices operate concurrently and sensor data are affected by imperfections such as noise, missing samples, and nonlinear meter response. In contrast to many studies that rely on curated or idealized datasets, this work investigates appliance recognition using real multimodal utility data (electricity, water, gas) collected at the building entry point, in the presence of substantial uninstrumented background activity. We present a case study evaluating transparent, rule-based detectors designed to exploit characteristic temporal dependencies between modalities while remaining interpretable and robust to sensing imperfections. Four household appliances—washing machine, dishwasher, tumble dryer, and kettle—are analyzed over six weeks of data. The proposed approach achieves reliable detection for structured, water-related appliances (22/30 washing cycles, 19/21 dishwashing cycles, and 23/27 drying cycles), while highlighting the limitations encountered for short, high-power events such as kettle usage. The results illustrate both the potential and the limitations of conservative rule-based detection under realistic conditions and provide a well-documented baseline for future hybrid systems combining interpretable rules with data-driven adaptation. Full article

Pulmonary drug delivery represents a promising approach in the treatment of respiratory diseases, allowing for passive targeting and enhanced drug efficacy. Background/Objectives: The aim of the present study was to develop inhalable dry powders from lyophilized sildenafil citrate (SC)-loaded liposomes made from phosphatidylcholine and either cholesterol (CH) or resveratrol (RSV). Methods: Liposomes were prepared via a pH gradient method to increase drug entrapment efficiency and drug loading, and then the liposomes were lyophilized using different proportions of ethanol, mannitol, and lactose as excipients. The resulting dry cakes were converted into powders and evaluated for aerodynamic performance using a custom-designed air-blowing device. Notably, this is the first time that resveratrol has been used as a substitute for cholesterol in SC-loaded liposomes. Results: Our results demonstrate that RSV is a suitable liposome bilayer component and improves drug loading. Our findings prove that lyophilized cakes containing liposomes produce a dry powder that is suitable for aerosolization with potential application to pulmonary delivery of sildenafil citrate. The results suggest that RSV represents a potential alternative to traditional cholesterol-based liposomal formulations. Conclusions: This work presents a novel strategy for the pulmonary delivery of sildenafil, using biocompatible and FDA-approved mannitol and lactose for this administration route. Full article

Drowsy driving and sudden medical emergencies are major contributors to traffic accidents, necessitating continuous, non-intrusive driver monitoring. Since current technologies often struggle to balance accuracy with practicality, this study presents the design, fabrication, and validation of a smart steering wheel prototype. The device integrates dry-contact electrocardiogram (ECG), photoplethysmography (PPG), and inertial sensors to facilitate multimodal physiological monitoring. The system underwent a two-stage evaluation involving a single participant: laboratory validation benchmarking acquired signals against medical-grade equipment, followed by real-world testing in a custom electric research vehicle to assess performance under dynamic conditions. Laboratory results demonstrated that the prototype captured high-quality signals suitable for reliable heart rate variability analysis. Furthermore, on-road evaluation confirmed the system’s operational functionality; despite increased noise from motion artifacts, the ECG signal remained sufficiently robust for continuous R-peak detection. These findings confirm that the multimodal smart steering wheel is a feasible solution for unobtrusive driver monitoring. This integrated platform provides a solid foundation for developing sophisticated machine-learning algorithms to enhance road safety by predicting fatigue and detecting adverse health events. Full article

Dry Eye Disease (DED) is a highly characterised multifactorial disease resulting in the loss of tear film homeostasis and associated with a major impact on patient quality of life. DED affects up to half of the global population, with modern lifestyle factors playing a critical role in disease development, particularly excessive use of digital devices. The ultimate treatment goal is restoration of tear film homeostasis and breaking the ‘vicious circle’ of DED. Today, the use of tear substitutes represents the main option for the treatment of DED. These topical formulations aim to provide lubrication, reduce osmolarity, and improve tear clearance. However, they do not interact with the ocular surface epithelium nor modulate ocular inflammation, and do not fully restore natural tear function. T-LysYal is the first supramolecular ocular surface modulator for DED. Studies demonstrate that T-LysYal promotes tissue repair, improves tear breakup time, restores corneal epithelial cell damage, and modulates inflammation processes, significantly reducing the severity of DED symptoms in patients. In addition, T-LysYal provides stability that prolongs activity and favours cell adhesion. Through its 3D nanotube structure, movement of water in the eye is retained and improved, enhancing ocular hydrodynamics. This narrative review introduces T-LysYal for DED whilst highlighting both its in vitro activity and clinical profile against hyaluronic acid, a mainstay of disease management. Full article