Search Results (3,147)

Osteochondral repair remains challenging due to cartilage’s limited self-healing capacity and the structural complexity of the osteochondral interface, particularly the hypertrophic layer anchoring cartilage to bone. We fabricated melt electrowritten (MEW) poly(L-lactic acid) (PLLA) scaffolds incorporating 1%, 5%, and 10% hydroxyapatite (HAp) to provide a precise fiber architecture (~200 μm pores) and bone-mimetic biochemical cues. Human nasal chondrocytes (hNCs), currently in clinical trials for knee cartilage repair, were selected for their phenotypic plasticity and established safety profile, facilitating translational potential. HAp–PLLA scaffolds, especially at higher HAp contents, enhanced hNC adhesion, proliferation, mineralization, and maintenance of cartilage-specific ECM compared to PLLA alone. This work demonstrates the first high-HAp MEW-printed PLLA scaffold for osteochondral repair, integrating architectural precision with bioactivity in a clinically relevant cell–material system. Full article

Background: Systemic lupus erythematosus (SLE) is reported to be the most common rheumatological disorder associated with catatonia. To date, reports on catatonia manifestations in SLE patients are uncommon in published literature, which has often favored a fragmented vision. We performed a narrative review with the aim of identifying all published reports of catatonia in SLE patients to ascertain—in a comprehensive view—its clinical characteristics and to provide useful insights for daily clinical practice. Methods: Comprehensive literature searches were carried out on 10 March 2025 (subsequently repeated ahead of draft on 6 June) in all main bibliographic databases: MEDLINE and EMBASE (OVID interface); PsycINFO (ProQuest); and PubMed, to capture within-text references. All searches combined controlled (MESH, Entree, and APA Headings) and free-text elements for both areas under observation: systemic lupus erythematosus (SLE) AND catatonia, with primary focus on case reports and series. Sets of findings were reviewed separately by the authors, and the full text of selected items was sourced. Further useful references were retrieved through citation lists. Results: 39 cases of patients with SLE and catatonia were identified (35 females and 4 males), with a mean age of 22.64 years (range 11–46). Only three patients were over the age of 40; a total of 10 had catatonia at the same time of SLE onset and 5 within a month of SLE diagnosis. Antiphospholipid and anti-ribosomal P protein antibodies were rarely identified. Almost all the patients improved following treatment with lorazepam and/or electroconvulsive therapy. Only one case of malignant catatonia was reported. Finally, a large number of patients were Asian or Afro-American, at least in the reports where ethnicity was specified. Conclusions: Catatonia can occur in patients with SLE, and it may be its first clinical manifestation, especially in young patients. Its prognosis is mostly favorable. Full article

The large-scale evaluation of multiple-choice tests is a challenging task from the perspective of image processing. A typical instrument is a multiple-choice question test that employs an answer sheet with circles or squares. Once students have finished the test, the answer sheets are digitized and sent to a processing center for scoring. Operators compute each exam score manually, but this task requires considerable time. While it is true that mature algorithms exist for detecting circles under controlled conditions, they may fail in real-life applications, even when using controlled conditions for image acquisition of the answer sheets. This paper proposes a desktop application for optical mark recognition (OMR) on the scanned multiple-choice question (MCQ) test answer sheets. First, we compiled a set of answer sheet images corresponding to 6029 exams (totaling 564,040 four-option answers) applied in 2024 in Tamaulipas, Mexico. Subsequently, we developed an image-processing module that extracts answers from the answer sheets and an interface for operators to perform analysis by selecting the folder containing the exams and generating results in a tabulated format. We evaluated the image-processing module, achieving a percentage of 96.15% of exams graded without error and 99.95% of 4-option answers classified correctly. We obtained these percentages by comparing the answers generated through our system with those generated by human operators, who took an average of 2 min to produce the answers for a single answer sheet, while the automated version took an average of 1.04 s. Full article

The present study showed that it is possible add value to eucalyptus harvest waste, obtained in large quantities, from the cellulose industries, without known economic use, for the production of an activated biochar. The biochar, produced from the impregnation of eucalyptus harvest waste with H₃PO₄, and subsequently pyrolyzed at 600 °C for 1 h, was successfully used as a bioadsorbent in the removal of paracetamol, an emerging pollutant present in wastewater. The biochar showed a high specific surface area with micro- and mesopores and functionalized surface. The optimal conditions for the removal of paracetamol achieve an efficiency around 88–93%. The Langmuir and the pseudo-first-order models best fit the experimental data, with a maximum adsorption capacity of approximately 27.8 mg g⁻¹, at 25 °C. The thermodynamic showed that adsorption occurred spontaneously, endothermally and randomly at the solid–liquid interface. In addition, the bioadsorbent showed excellent reusability and no significant difference in adsorption capacity was observed in more complex aqueous matrices. Thus, the activated biochar produced in this study proved to be an efficient, low-cost and environmentally friendly bioadsorbent, capable of removing paracetamol from contaminated water, with great potential for use in water treatment plants, on a large scale and economically, contributing to the improvement of water quality and minimizing residual biomass in the environment. Full article

Background: Skin cancer represents one of the most prevalent malignancies worldwide, with melanoma accounting for approximately 75% of skin cancer-related deaths despite comprising fewer than 5% of cases. Early detection dramatically improves survival rates from 14% to over 99%, highlighting the urgent need for accurate and accessible diagnostic tools. While deep learning has shown promise in dermatological diagnosis, existing approaches lack clinical explainability and deployable interfaces that bridge the gap between research innovation and practical healthcare applications. Methods: This study implemented a comprehensive multimodal deep learning framework using the HAM10000 dataset (10,015 dermatoscopic images across seven diagnostic categories). Three CNN architectures (DenseNet-121, EfficientNet-B3, ResNet-50) were systematically compared, integrating patient metadata, including age, sex, and anatomical location, with dermatoscopic image analysis. The first implementation of XRAI (eXplanation with Region-based Attribution for Images) explainability for skin lesion classification was developed, providing spatially coherent explanations aligned with clinical reasoning patterns. A deployable web-based clinical interface was created, featuring real-time inference, comprehensive safety protocols, risk stratification, and evidence-based cosmetic recommendations for benign conditions. Results: EfficientNet-B3 achieved superior performance with 89.09% test accuracy and 90.08% validation accuracy, significantly outperforming DenseNet-121 (82.83%) and ResNet-50 (78.78%). Test-time augmentation improved performance by 1.00 percentage point to 90.09%. The model demonstrated excellent performance for critical malignant conditions: melanoma (81.6% confidence), basal cell carcinoma (82.1% confidence), and actinic keratoses (88% confidence). XRAI analysis revealed clinically meaningful attention patterns focusing on irregular pigmentation for melanoma, ulcerated borders for basal cell carcinoma, and surface irregularities for precancerous lesions. Error analysis showed that misclassifications occurred primarily in visually ambiguous cases with high correlation (0.855–0.968) between model attention and ideal features. The web application successfully validated real-time diagnostic capabilities with appropriate emergency protocols for malignant conditions and comprehensive cosmetic guidance for benign lesions. Conclusions: This research successfully developed the first clinically deployable skin lesion classification system combining diagnostic accuracy with explainable AI and practical patient guidance. The integration of XRAI explainability provides essential transparency for clinical acceptance, while the web-based deployment democratizes access to advanced dermatological AI capabilities. Comprehensive validation establishes readiness for controlled clinical trials and potential integration into healthcare workflows, particularly benefiting underserved regions with limited specialist availability. This work bridges the critical gap between research-grade AI models and practical clinical utility, establishing a foundation for responsible AI integration in dermatological practice. Full article

Adverse pressure gradients are intrinsic to compressor flow behavior and are further intensified by secondary effects associated with rotor tip clearance flow interactions. Tip clearance generates leakage flow, which leads to the formation of tip leakage vortices, a major contributor to aerodynamic losses in axial compressors. These vortices significantly influence both compressor performance and operational stability. Extensive prior research has demonstrated that passive casing treatments, particularly axial slots, can substantially improve the stall margin in axial compressors. In this work, the performance of a new casing treatment geometry is investigated using the concept of recirculating flow within semi-circular axial slots. The proposed casing treatment geometry builds upon recent experimental findings involving single-rotor configurations. It was applied to the first rotor row of a three-and-a-half-stage (3.5-stage) axial compressor comprising an inlet guide vane followed by three rotor–stator stages. The numerical model incorporates axial slots with a novel periodic interface approach implemented in a multistage compressor simulation. Three-dimensional steady-state RANS (Reynolds Average Navier-Stokes) simulations were performed to investigate the aerodynamic effects of the casing treatment across various rotational speeds. The results for the casing treatment configuration were compared with those of a baseline smooth casing. The introduction of the new casing treatment produced noticeable modifications to the internal flow structure, particularly in the tip region, resulting in improved overall compressor stability within the operating range of 85 to 100% of design speed. Full article

The GaN-on-Si virtual substrate is now an indispensable platform for the application of GaN in the fields of power devices, radio frequency, light-emitting devices, etc. Such applications are still in need of more effective stress balancing techniques to achieve higher quality and stress balance in GaN-on-Si at a lower thickness. In this study, three promising practical prototypes of highly effective stress-balancing structures are proposed to realize the concept of an ideal AlN interlayer (AlN-IL) featuring a completely relaxed lower AlN/GaN interface and a fully strained upper GaN/AlN interface. The first is a single-layer AlN interlayer grown via precursor pulsed-injection (PI-AlN-IL). The second combines a low-temperature AlN (LT-AlN) underlayer with a PI-AlN-IL. The third integrates LT-AlN with a high-temperature AlN cap. Compared with optimal conventional single-layer AlN interlayer references, all these designs more effectively induced compressive stress and strain in overlying GaN layers. This study opens new technical paths to balancing stress in GaN-on-Si systems at a reduced thickness more efficiently. Full article

Wildfires pose severe threats to ecosystems and human settlements, making early detection and rapid response critical for minimizing damage. The adage—“You fight fire in the first second with a spoon of water, in the first minute with a bucket, and in the first hour with a truckload”—illustrates the importance of early intervention. Over recent decades, significant research efforts have been directed toward developing efficient systems capable of identifying wildfires in their initial stages, especially in remote forests and wildland–urban interfaces (WUIs). This review paper introduces the Special Issue of Fire and is dedicated to advanced approaches to wildfire detection, monitoring, and surveillance. It summarizes state-of-the-art technologies for smoke and flame detection, with a particular focus on their integration into broader wildfire management systems. Emphasis is placed on distinguishing wildfire monitoring (the passive collection of data using various sensors) from surveillance (active data analysis and action based on visual information). The paper is structured as follows: a historical and theoretical overview; a discussion of detection validation and available datasets; a review of current detection methods; integration with ICT tools and GIS systems; the identification of system gaps; and future directions and emerging technologies. Full article

Electrical resistivity tomography (ERT) is one of the most commonly used geophysical methods for imaging the distribution of electrical resistivity in the subsurface. It is often employed to characterise heterogeneity in karst regions and locate cavities and conduits below the surface. The resistivity contrast between the host rock and the cavity depends on the material filling the cavity. Air has a high electrical resistivity and should therefore produce strong reflections and refractions off cavity walls. However, cavities are not always easily detectable. A decrease in resistivity contrast at the interface between rock and air may result from different physical conditions relating to pore saturation, fracturing and stress near the cavity walls. Our first goal is to understand how extensive fracturing and hydrogeological conditions in the first subsurface layers can affect electric current flow in the presence of a karst tunnel. We use the commercial Res2Dmod software 3.0 to simulate an ERT on several ground models. The results, which are based on hydrogeological models, are presented for several conditions of a karst conduit: empty; full of water within a homogeneous background; and below the groundwater level in the presence of extensive fractures in the shallow layer above it. Full article

Composite materials have gained prominence in aerospace engineering due to their high strength-to-weight and stiffness-to-weight ratios. However, their susceptibility to interlaminar damage, particularly delamination, remains a significant concern, especially under compressive loads. This study presents a detailed numerical investigation into the buckling behavior and delamination propagation in flat and curved composite panels with centrally located circular delaminations. Four configurations were analyzed, differing by geometry (flat vs. curved) and delamination interface. The critical buckling load was first estimated through linear eigenvalue analysis, while post-buckling behavior and damage progression were studied using a nonlinear static analysis enhanced by the Smart-time XB (SMXB) tool. Numerical results, including out-of-plane displacements and delamination length evolution, were validated against experimental data from the literature. The findings confirm the accuracy of the adopted FEM approach and highlight the beneficial role of curvature in increasing buckling resistance and improving damage tolerance, offering valuable insights for the design of aerospace composite structures. Full article

Closing resistors in ultra-high-voltage (UHV) gas-insulated circuit breakers (GCBs) are critical components designed to suppress inrush currents and transient overvoltages during switching operations. However, in practical service, these resistors are subjected to repeated mechanical impacts and transient electrical stresses, leading to degradation of their electrical contact interfaces, fluctuating resistance values, and potential failure of the entire breaker assembly. Existing studies mostly simplify the closing resistor as a constant resistance element, neglecting the coupled electro-thermal–mechanical effects that occur during transient events. In this work, a comprehensive modeling framework is developed to investigate the dynamic electrical contact characteristics of a 750 kV GCB closing resistor under transient closing impacts. First, an electromagnetic transient model is built to calculate the combined inrush and power-frequency currents flowing through the resistor during its pre-insertion period. A full-scale mechanical test platform is then used to capture acceleration signals representing the mechanical shock imparted to the resistor stack. These measured signals are fed into a finite element model incorporating the Cooper–Mikic–Yovanovich (CMY) electrical contact correlation to simulate stress evolution, current density distribution, and temperature rise at the resistor interface. The simulation reveals pronounced skin effect and current crowding at resistor edges, leading to localized heating, while transient mechanical impacts cause contact pressure to fluctuate dynamically—resulting in a temporary decrease and subsequent recovery of contact resistance. These findings provide insight into the real-time behavior of closing resistors under operational conditions and offer a theoretical basis for design optimization and lifetime assessment of UHV GCBs. Full article

This work presents a proof of concept for a short-range high spectral resolution lidar (SR-HSRL) optimized for aerosol characterization in the first kilometer of the atmosphere. The system is based on a compact, high-repetition-rate diode-based fiber laser with a 300 MHz linewidth and 5 ns pulse duration, coupled with an iodine absorption cell. A central challenge in the instrument’s development was identifying a laser source that offered both sufficient spectral resolution for HSRL retrievals and nanosecond pulse durations for high spatiotemporal resolution, while also being compact, tunable, and cost-effective. To address this, we developed a methodology for complete spectral and temporal laser characterization. A two-day field campaign conducted in July 2024 in Tsukuba, Japan, validated the system’s performance. Despite the relatively broad laser linewidth, we successfully retrieved aerosol backscatter coefficient profiles from 50 to 1000 m, with a spatial resolution of 7.5 m and a temporal resolution of 6 s. The results demonstrate the feasibility of using SR-HSRL for detailed studies of aerosol layers, cloud interfaces, and aerosol–cloud interactions. Future developments will focus on extending the technique to ultra-short-range applications (<100 m) from ground-based and mobile platforms, to retrieve aerosol extinction coefficients and lidar ratios to improve the characterization of near-source aerosol properties and their radiative impacts. Full article

Late bilingual speakers immersed in a second language (L2) environment often experience the non-pathological attrition of their first language (L1), exhibiting selective and reversible changes in L1 processing and production. While attrition research has largely focused on long-term residents in anglophone countries, examining changes primarily within a single L1 domain, the present study employs a novel experimental design to investigate L1 attrition, alongside L2 acquisition, across three domains (i.e., the lexicon, syntax–pragmatics interface, and prosody) in two groups of L1-English L2-Italian late bilinguals: long-term residents in Italy vs. university students in the UK. A total of 112 participants completed online tasks assessing lexical retrieval, anaphora resolution, and sentence stress patterns in both languages. First, both bilingual groups showed comparable levels of semantic interference in lexical retrieval. Second, at the syntax–pragmatics interface, only residents in Italy showed signs of L1 attrition in real-time processing of anaphora, while resolution preferences were similar between groups; in the L2, both bilingual groups demonstrated target-like preferences, despite some slowdown in processing. Third, while both groups showed some evidence of target-like L2 prosody, with residents in Italy matching L1-Italian sentence stress patterns closely, prosodic attrition was only reported for residents in Italy in exploratory analyses. Overall, this study supports the notion of L1 attrition as a natural consequence of bilingualism—one that is domain- and experience-dependent, unfolds along a continuum, and involves a complex (and possibly inverse) relationship between L1 and L2 performance that warrants further investigation. Full article

Modeling ion transport through membrane channels is crucial for understanding cellular processes, and Poisson–Nernst–Planck (PNP) equations provide a fundamental continuum framework for such ionic fluxes. We investigate a quasi-one-dimensional steady-state PNP system for two oppositely charged ion species, focusing on how large permanent charges within the channel and realistic boundary conditions impact ion transport. In contrast to classical models that impose ideal electroneutrality at the channel ends (a simplification that eliminates boundary layers near the membrane interfaces), we adopt relaxed neutral boundary conditions that allow small charge imbalances at the boundaries. Using asymptotic analysis treating the large permanent charge as a singular perturbation, we derive explicit first-order expansions for each ionic flux, incorporating boundary layer parameters $(\sigma ,\rho )$ to quantify slight deviations from electroneutrality. This analysis enables a qualitative characterization of individual cation and anion flux behaviors. Notably, we identify two critical transmembrane potentials, $V_{1c}$ and $V_{2c}$, at which the cation and anion fluxes, respectively, vanish, signifying flux-reversal thresholds that delineate distinct monotonic regimes in the flux-voltage response; these critical values depend on the permanent charge magnitude and the boundary layer parameters. We further show that both ionic fluxes exhibit saturation: as the applied voltage becomes extreme, each flux approaches a finite limiting value, with the saturation level modulated by the degree of boundary charge imbalance. Moreover, allowing even small boundary charge deviations reveals non-intuitive discrepancies in flux behavior relative to the ideal electroneutral case. For example, in certain parameter regimes, a large permanent charge that enhances an ionic current under strict electroneutral conditions will instead suppress that current under relaxed-neutral conditions (and vice versa). This new analytical framework exposes subtle yet essential nonlinear dynamics that classical electroneutral assumptions would otherwise obscure. It provides deeper insight into the interplay between large fixed charges and boundary-layer effects, emphasizing the importance of incorporating such realistic boundary conditions to ensure accurate modeling of ion transport through membrane channels. Numerical simulations are performed to provide more intuitive illustrations of our analytical results. Full article

Printed flexible materials have garnered considerable attention as next-generation materials for bioelectronic applications, particularly hydrogels and elastomers, owing to their intrinsic softness, tissue-like mechanical compliance, and electrical conductivity. In contrast to conventional fabrication approaches, printing technologies enable precise spatial control, design versatility, and seamless integration with complex biological interfaces. This review provides a comprehensive overview of the progress in printable soft conductive materials, with a particular emphasis on the composition, processing, and functional roles of conductive hydrogels and elastomers. This review first introduces traditional fabrication methods for conductive materials and explains the motivation for using printing techniques. We then introduce two major classes of soft conductive materials, hydrogels and elastomers, and describe their applications in both in vitro systems, such as biosensors and soft stimulators, and in vivo settings, including neural interfaces and implantable devices. Finally, we discuss current challenges and propose future directions for advancing printed soft bioelectronics toward clinical translation. Full article