Search Results (81)

Background and Clinical Significance: Primary cutaneous anaplastic large cell lymphoma (C-ALCL) is a CD30-positive T-cell lymphoproliferative disorder that can clinically resemble various non-melanoma skin cancers, making diagnosis challenging. Although histopathology remains the diagnostic gold standard, non-invasive imaging modalities such as dermoscopy and reflectance confocal microscopy (RCM) are increasingly used as complementary tools to support the differential diagnosis. To date, no data on RCM features of C-ALCL have been described. Case Presentation: We report the case of an 80-year-old man presenting with a rapidly enlarging nodule on the lateral aspect of his right eyelid, providing a detailed account of dermoscopic and RCM findings integrated with clinicopathological correlation. Dermoscopy revealed a red-orange homogeneous background with white streaks, and polymorphic vascular structures, while subsequent RCM (Vivascope 3000 probe) demonstrated marked architectural disarray of the epidermis and dermoepidemal junction, with prominent epidermal involvement characterized by aggregates of highly reflective cells. In the absence of alternative diagnostic patterns, these features raised suspicion for a cutaneous lymphoproliferative disorder, which was later confirmed by histopathological and immunohistochemical analyses. Conclusions: Our findings support the value of RCM as a practical tool in guiding differential diagnosis and biopsy, particularly for rapidly growing lesions located in anatomically sensitive areas. Full article

Background/Objectives: Depression among older adults with disabilities represents a significant public health concern, with well-documented socioeconomic disparities. However, the mechanisms through which socioeconomic status (SES) is associated with depression in this population remain insufficiently specified. Guided by the Reserve Capacity Model (RCM), this study examines whether social support is statistically associated with the SES–depression relationship and whether this association varies according to psychosocial and structural resources. Methods: Data were drawn from the 18th wave (2023) of the Korea Welfare Panel Study (KoWePS) and its supplementary disability survey (N = 845). Moderated mediation analyses were conducted using the PROCESS macro with 5000 bootstrap samples to estimate indirect and conditional associations. Results: SES was negatively associated with depressive symptoms and positively associated with social support. Social support demonstrated a statistically significant indirect association between SES and depression, consistent with a partial mediation pattern, although the direct association remained significant. Self-esteem did not significantly moderate the indirect association. In contrast, public service utilization significantly moderated the association between social support and depression, such that the indirect association between SES and depression was attenuated at higher levels of service utilization. Conclusions: The findings indicate that depression among older adults with disabilities is associated with both socioeconomic disadvantage and variations in social and structural resources. These results underscore the relevance of considering both psychosocial and structural dimensions of resources when examining mental health disparities. Full article

In ceramic cup manufacturing, manual inspection is prone to missed detections and false positives, particularly for small surface defects. To address these challenges, this study presents an effective and efficient YOLOv11m-based detection framework, termed CEL-YOLOv11m, for precise identification of small-scale defects on ceramic surfaces. Specifically, a multi-scale convolution module (EMSC) is introduced to enhance the backbone feature extraction structure. By integrating convolution kernels of varying sizes, the module improves multi-scale feature representation, while grouped convolution is employed to reduce computational overhead. In the feature aggregation stage, a CRGseg-based structure is incorporated, and a refinement component (RCM) is designed to strengthen fine-grained information for small targets. Additionally, a cross-scale feature fusion strategy is applied to improve contextual representation across different resolutions. For the detection stage, a Layer-shared Detail-Enhanced Convolutional Detection Head (LSDECD) is adopted to improve fine-grained localization while improving computational efficiency through parameter sharing. Experiments conducted on a self-constructed ceramic defect dataset and the VisDrone2019 benchmark show that the proposed framework achieves competitive performance compared with representative methods. The model attains an mAP@50(%) of 54.8% with an inference speed of 89.9 FPS, providing a favorable trade-off between detection accuracy and computational efficiency while maintaining strong precision in small defect detection. Full article

The impact of climate change on rainfall extremes has become increasingly obvious in many climatic regions including arid regions where extreme precipitation events are thought to have augmented or at least intensified. Driven by global factors such as greenhouse gas emissions, deforestation, and industrialization, climate change has augmented hydrological variability, thus making traditional stationary models inadequate for the estimation of extreme rainfall at various return periods. Extreme value analyses, which were traditionally derived under the assumption of stationarity (i.e., constant statistical properties over time) and typically do not account for temporal variability or external climatic drivers (e.g., temperature or large-scale climate indices), may lead to inaccurate estimation of rainfall quantiles under changing climate conditions. This paper presents a structured review of applied methodologies for quantifying the influence of climate change on extreme rainfall events, with special attention to how non-stationarity is addressed in arid regions applications, which was not a major focus in previous review papers. Relevant statistical techniques, extreme value theory, machine learning models, and high-resolution climate simulations are reviewed. From an initial pool of over 340 studies, 91 were selected based on their relevance to quantify rainfall extremes induced by climate change in arid regions. Based on the reviewed studies, the analysis revealed a strong reliance on trend analysis of downscaled Global Climate Models (GCMs) and Regional Climate Models (RCMs) within a stationary framework, with limited integration of covariates, other than time, in non-stationary frequency analysis to estimate the climate change-related value. This review identifies the research gaps in the scientific literature related to climate change impact assessment on extreme rainfall in arid regions. It emphasizes the necessity for adopting more robust hybrid approaches, adopting statistical distributions more suitable to arid conditions, careful treatment of outliers, conducting regional analyses to better understand the overall climate behavior of the region, addressing the impact on short-duration rainfall, integrating key climatic drivers through the incorporation of additional climate covariates and the impact of climate change on sub-daily rainfall patterns. Full article

The increasing deployment of collaborative and industrial robots in manufacturing systems places high demands on equipment reliability, availability, and maintenance efficiency. Robotic workcells, in which multiple automated subsystems operate in tightly coordinated cycles, are particularly sensitive to unplanned downtime, as failures of individual components can disrupt the entire production process. Traditional time-based preventive maintenance is often insufficient under such conditions, as it does not adequately reflect actual operating loads or component degradation. This paper proposes a structured framework for the design of an integrated maintenance concept for a multi-robot packaging workcell. The framework systematically combines component identification, criticality assessment, and the selection of appropriate maintenance strategies, including preventive, predictive, corrective, proactive, and reactive approaches. Preventive maintenance is complemented by condition-based monitoring and trend analysis of selected diagnostic parameters, enabling predictive decision-making for critical components. The proposed methodology further integrates maintenance planning and performance evaluation through a computerized maintenance management system (CMMS), supporting the coordination of maintenance activities and the assessment of key performance indicators. The novelty of the proposed framework lies primarily in the dynamic allocation of maintenance strategies based on semi-quantified component criticality and in the structured integration of predictive diagnostic information with CMMS-supported maintenance planning. Unlike traditional RCM-based or single-strategy maintenance approaches, the framework enables coordinated preventive, predictive, corrective, proactive, and reactive actions within a unified decision-making architecture, supporting proactive continuous improvement of maintenance performance through a closed-loop feedback mechanism that updates component criticality based on real-time operational data. The framework is demonstrated on a robotic workcell comprising a collaborative robot, an industrial robot, pneumatic subsystems, and a centralized control architecture. The results suggest that the integrated approach may provide a coherent basis for reducing reactive maintenance actions, improving system availability, and supporting data-driven maintenance planning. As a conceptual framework with partial (pilot) practical implementation within the context of this paper, the proposed approach establishes a foundation for future broader implementation, experimental validation and the integration of advanced diagnostic and prognostic methods, mainly in the context of multi-Robot workcell and production process maintenance. Full article

To address the durability deficiencies and limited service life of concrete structures exposed to complex service environments such as chloride attack in marine and underground engineering, this study employs fly ash (FA) and ground granulated blast-furnace slag (GGBS), typical eco-friendly materials, as functional mineral admixtures to systematically investigate the effects of their combined incorporation on the mechanical properties, durability, drying shrinkage, and microstructural characteristics of concrete. The objective is to develop a concrete material that achieves high durability while maintaining structural safety and service performance, with the additional benefit of improved resource utilization efficiency. Single-factor tests were first conducted to determine the sensitivity ranges of FA and GGBS within 10–30% for slump, compressive strength, chloride migration coefficient (RCM), and drying shrinkage. Subsequently, response surface methodology (RSM) was employed to establish quadratic regression models using FA and GGBS as independent variables and compressive strength, RCM, and drying shrinkage as response indicators. The models exhibited high fitting accuracy, and their reliability was validated through analysis of variance (ANOVA), residual analysis, and predictive performance indices. Multi-objective optimization based on the desirability function identified the optimal mix proportion as FA = 14.8% and SL = 29.3%, yielding predicted values of 56.2 MPa for 28-day compressive strength, 6.03 × 10⁻¹² m²/s for RCM, and 639 με for 90-day drying shrinkage. Microstructural analysis using SEM and MIP further revealed that the binary-blended system promotes the formation of a dense C–S–H/C–A–S–H gel network, refines pore-size distribution, and reduces pore connectivity, thereby improving long-term mechanical and durability performance. The findings provide quantitative guidance for designing high-durability, environmentally friendly concrete suitable for marine and underground engineering applications. Full article

Hyperspectral images (HSIs) from the lunar polar regions are frequently compromised by low signal-to-noise ratio (SNR) under adverse illumination, limiting their utility for scientific analysis. Existing spectral-only compensation approaches operate without spatial context, leading to speckle-like artifacts that degrade spatial consistency and constrain subsequent applications. To address this limitation, we propose SSF-3DSC, a spatial–spectral fusion 3D signal-compensation framework tailored for lunar HSIs to simultaneously restore spectral fidelity and spatial consistency under extreme low-illumination conditions. To the best of our knowledge, this represents the first deep learning framework specifically engineered for joint spatial–spectral restoration in the photon-starved regime. SSF-3DSC integrates three specialized components: a spectral compensation module (SCM) for restoring spectral fidelity, a multi-scale spatial attention (MSA) module for capturing hierarchical spatial patterns, and a cascaded 3D residual convolutional module (C3D-RCM) for refining spatial–spectral representations. Trained on paired low- and high-SNR Moon Mineralogy Mapper (M3) data cubes from the lunar south polar region, SSF-3DSC employs synergistic spatial–spectral fusion to achieve high-fidelity reconstruction, significantly outperforming a spectral-only lunar baseline (Paired-CycleGAN). Regional-scale experiments demonstrate its ability to recover both spatially coherent geological structures and spectrally reliable mineral abundance maps. By establishing a new benchmark for lunar HSI restoration under low-illumination conditions, this work enhances the scientific utility of low-signal M3 data and enables robust quantitative investigations into the Moon’s challenging polar regions. Full article

The periocular region represents a highly sensitive anatomical area due to its functional relevance and aesthetic importance. It is frequently affected by a broad spectrum of cutaneous tumors, due to chronic exposure to ultraviolet radiation, hence an accurate diagnosis and lesion margin assessment is essential to guide appropriate treatment. Herein we summarize the current evidence on the use of reflectance confocal microscopy (RCM), optical coherence tomography (OCT), and line-field confocal optical coherence tomography (LC-OCT) for the assessment of periocular skin tumors. A comprehensive literature search was conducted in the main databases following PRISMA 2020 guidelines. Studies published between 2015 and 2025 evaluating the application of RCM, OCT, and LC-OCT in skin tumors of this area were included. RCM was the most extensively studied modality, demonstrating utility in the characterization of pigmented and non-pigmented periocular lesions and in the identification of basal cell carcinoma-specific features. OCT provided complementary information by enabling visualization of deeper tissue structures, particularly in non-melanoma skin cancers; LC-OCT showed high concordance with histopathology providing practical advantages in this area. As a conclusion, non-invasive imaging techniques represent valuable tools in the evaluation of periocular skin tumors, as they may enhance diagnostic confidence and support clinical decision-making. Full article

This study aims to assess how climate change will affect the intensity of soil erosion in the Vistula River basin by the mid-21st century. A simulation framework based on the SWAT–MUSLE model was applied, calibrated, and validated against observed streamflow data and driven by climatic forcings from the EURO-CORDEX ensemble (the RACMO22E, HIRHAM5, and RCA4 models forced by EC-EARTH GCM) under the RCP 4.5 and RCP 8.5 scenarios. Simulations were conducted at a daily time step for the years 2021–2050 and compared to the reference period 2013–2018. The analysis included the decadal and seasonal aggregation of the sediment yield (SYLD, t ha⁻¹ yr⁻¹). The results indicate that, relative to the baseline value (~1.84 t ha⁻¹ yr⁻¹), the SYLD increases under both scenarios. In RCP 4.5, the rise culminates during 2031–2040 and then stabilizes in 2041–2050. Under RCP 8.5, a continuous upward trend is observed, with the highest values projected for 2041–2050, particularly for the HIRHAM5 realization. The largest relative increases occur in summer (JJA) and, in the final decade, also in autumn (SON); in the early horizon, autumn may locally exhibit declines that later shift to increases. The spread among RCM realizations remains significant and should be interpreted as an expression of projection uncertainty. The practical implications include prioritizing soil protection measures in sub-catchments with high LS factors and soils susceptible to water erosion, strengthening runoff and sediment control in summer, and planning maintenance of small-scale retention infrastructure. Study limitations arise from the inherent structure of the MUSLE model, bias correction procedures for climate data, and the representation of extreme events. Therefore, greater emphasis is placed on the direction and seasonality of changes rather than absolute numerical values. Full article

This study investigates FLNC mutations in Chinese cardiomyopathy patients. Background: Inherited cardiomyopathies, including dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), restrictive cardiomyopathy (RCM), and arrhythmogenic right ventricular cardiomyopathy (ARVC) are major heart failure causes. FLNC, critical for muscle structure, is implicated in myofibrillar myopathy and isolated DCM (3–4% cases) with ventricular arrhythmias. Missense variants are linked to HCM and protein aggregation. A cohort of 25 patients with pathogenic/likely pathogenic FLNC mutations (2022–2025, Beijing Anzhen Hospital) underwent whole-exome sequencing (WES) using IDT kit 1.0/Hiseq 4000. Variants were classified via the American College of Medical Genetics and Genomics (ACMG) guidelines. Clinical data (echocardiography, CMR, labs) and follow-up data (prognosis, meds, and family history) were collected. The statistics used SPSS (p < 0.05). The mean age was 38 ± 14.6 years (13 males). There were 25 FLNC mutations: 12 single nucleotide polymorphisms (SNPs), 5 deletions, 2 duplications, and 3 deletion-insertions, classified as 6 pathogenic, 16 likely pathogenic, and 3 variants of uncertain significance (VUS). Diagnoses: 24% dilated cardiomyopathy (DCM), 8% hypertrophic cardiomyopathy (HCM), and 4% left ventricular non-compaction. Nonsense mutation carriers exhibited significantly higher tricuspid regurgitation prevalence compared to frameshift mutation carriers (6/9 vs. 2/10; p = 0.04). Echocardiography revealed reduced left ventricular ejection fraction (LVEF) (41.5 ± 14.1%), with statistically significant differences in fractional shortening (p = 0.024) and aortic root diameter (p = 0.028). Pedigree analysis confirmed that a frameshift mutation (LP) co-segregated with familial DCM and was associated with severe phenotypes, including sudden cardiac death. Furthermore, nonsense FLNC mutations correlated with increased tricuspid regurgitation severity, smaller aortic root dimensions, and reduced pulmonary artery flow velocity. Full article

Background: Eczematous dermatitis refers to a group of inflammatory skin disorders—including seborrheic, atopic, and contact dermatitis—characterized by epidermal barrier dysfunction and chronic inflammation. Disrupting the itch–scratch cycle and reversing microscopic skin changes are key to improving patient outcomes and quality of life. Aims: This study aimed to assess the clinical and microscopic effects of a topical medical device containing N-butanoyl glutathione (GSH-C4) and hyaluronic acid in patients with inflammatory eczematous dermatitis, combining clinical scores with in vivo confocal and OCT imaging. Methods: A prospective clinical trial enrolled 30 patients with active eczematous lesions. Participants applied a GSH-C4/hyaluronic acid-based product (GSEBA^®) for 28 days. Clinical improvement was evaluated at baseline, day 14, and day 28 using the Investigator’s Global Assessment (IGA), a Visual Analog Scale (VAS) for itching, and a self-reported index of disease impact on quality of life (IDL). Microscopic changes were assessed using optical coherence tomography (OCT) and reflectance confocal microscopy (RCM). Results: After 28 days, the mean IGA score improved from 2.48 to 0.18 (p < 0.001), VAS itching score decreased from 4.52 to 0.32 (p < 0.001), and IDL dropped from 4.86 to 0.79 (p < 0.001). RCM analysis showed significant reductions in key inflammatory features such as spongiosis, vesiculation, and inflammatory infiltrate. OCT revealed a significant decrease in vascularization at 150 μm depth, with no change in collagen density. Conclusions: The GSH-C4/hyaluronic acid-based mousse (GSEBA^®) demonstrated strong clinical efficacy and excellent tolerability in managing eczematous dermatitis. It effectively reduced both symptoms and microscopic markers of inflammation without compromising dermal structure. Full article

Normal concrete exhibits poor resistance to chloride penetration, often leading to reinforcement corrosion and premature structural failure. In contrast, ultra-high-performance concrete (UHPC) demonstrates superior resistance to corrosion caused by chloride salts. The chloride diffusion behaviour of UHPC was investigated via long-term immersion (LTI) and rapid chloride migration (RCM) tests. Additionally, this study presents the first development of a time-dependent diffusion model for UHPC under chloride corrosion, as well as the proposal of a performance-based design method for calculating the protective layer thickness. Results show that the incorporation of steel fibers reduced the chloride diffusion coefficient ($D$) by 37.9%. The free chloride content (FCC) in UHPC increased by 92.0% at 2 mm after 300 d of the action of LTI. $D$ decreased by up to 91.0%, whereas the surface chloride concentration ($C_{\mathrm{s}}$) increased by up to 92.5% under the action of LTI. The time-dependent models of $D$ and $C_{\mathrm{s}}$ followed power and logarithmic functions, respectively. An increase in UHPC surface temperature, relative humidity, and tensile stress ratio significantly diminishes the chloride resistance of UHPC. The minimum UHPC protective layer thicknesses required for UHPC-HPC composite beams with design service lives of 100 years, 150 years, and 200 years are 30 mm, 37 mm, and 43 mm, respectively. Full article

Background: In recent decades, dermatological diagnostics have undergone a profound transformation, driven by the integration of new technologies alongside traditional methods. Classic techniques such as the Tzanck smear, potassium hydroxide (KOH) preparation, and Wood’s lamp examination remain fundamental in everyday clinical practice due to their simplicity, speed, and accessibility. At the same time, the development of non-invasive imaging technologies and the application of artificial intelligence (AI) have opened new frontiers in the early detection and monitoring of both neoplastic and inflammatory skin diseases. Methods: This review aims to provide a comprehensive overview of how conventional and emerging diagnostic tools can be integrated into dermatologic practice. Results: We examined a broad spectrum of diagnostic methods currently used in dermatology, ranging from traditional techniques to advanced approaches such as digital dermoscopy, reflectance confocal microscopy (RCM), optical coherence tomography (OCT), line-field confocal OCT (LC-OCT), 3D total body imaging systems with AI integration, mobile applications, electrical impedance spectroscopy (EIS), and multispectral imaging. Each method is discussed in terms of diagnostic accuracy, clinical applications, and potential limitations. While traditional methods continue to play a crucial role—especially in resource-limited settings or for immediate bedside decision-making—modern tools significantly enhance diagnostic precision. Dermoscopy and its digital evolution have improved the accuracy of melanoma and basal cell carcinoma detection. RCM and LC-OCT allow near-histological visualization of skin structures, reducing the need for invasive procedures. AI-powered platforms support lesion tracking and risk stratification, though their routine implementation requires further clinical validation and regulatory oversight. Tools like EIS and multispectral imaging may offer additional value in diagnostically challenging cases. An effective diagnostic approach in dermatology should rely on a thoughtful combination of methods, selected based on clinical suspicion and guided by Bayesian reasoning. Conclusions: Rather than replacing traditional tools, advanced technologies should complement them—optimizing diagnostic accuracy, improving patient outcomes, and supporting more individualized, evidence-based care. Full article

Background: Keratinocyte carcinomas (KCs), including basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs), are the most prevalent malignancies globally, particularly affecting sun-exposed facial areas. Achieving clear surgical margins in these regions is essential to ensure oncologic control while preserving cosmetic outcomes. Reflectance confocal microscopy (RCM) is a noninvasive imaging technique that enables real-time, high-resolution visualization of skin structures and may aid in margin assessment during KC surgery. This systematic review aims to evaluate the role of in vivo RCM in the surgical treatment of KCs. Methods: This review followed PRISMA guidelines. A comprehensive search of PubMed, Scopus, Web of Science, Medline, and EBSCO databases was conducted for studies published between January 1992 and December 2024. Inclusion criteria focused on clinical studies utilizing in vivo RCM for diagnostic or surgical applications in KC management. Results: Eighteen studies involving 1112 patients were included. RCM was used preoperatively in 5 studies and intraoperatively in another 5. Nine studies assessed margin delineation, while eight focused on diagnostic accuracy. RCM improved diagnostic confidence and allowed for more precise margin assessment, potentially reducing the extent of surgical excision in cosmetically sensitive areas. However, its broader clinical adoption is limited by operator dependency, procedural complexity, and lack of standardization. Conclusions: RCM shows promise as a supportive tool in KC surgery, particularly for preoperative planning. While its diagnostic utility is well established, its intraoperative role requires further validation. Larger, standardized, and cost-effective studies are needed to confirm its impact on surgical outcomes and patient quality of life. Full article

This study quantifies the uncertainty in monthly streamflow predictions under future climate scenarios in two periods (near and far future) for the Riu Mannu di Narcao basin in Sardinia, Italy. The sources of uncertainty include the hydrological model structure, model parameters, and variability in climatic inputs derived from global and regional climate models (GCM-RCM coupling) and representative concentration pathways (RCPs). Three conceptual and lumped hydrological models (GR3M, ABCD, and IHACRES) were combined with four climate models and two RCPs (RCP 4.5 and RCP 8.5) to assess future streamflow. Monte Carlo simulations were performed to evaluate parameter uncertainty, and the analysis of variance (ANOVA) method was applied to quantify the different sources of uncertainty. The results reveal that, as a single source, GCM-RCM coupling is the largest contributor, accounting for 47.32% (54.64%) of total near (far) future monthly streamflow projection uncertainties, followed by the hydrological model structure at 16.02% (21.09%), RCP scenarios at 15.35% (8.54%), and parameter uncertainty at 0.79% (1.39%). A consistent decline in median monthly streamflow is projected, especially during winter months (December to February), raising a concern about water availability in the region. Our study quantified different sources of uncertainty in monthly streamflow predictions under climate change, disentangling the roles of the hydrological model, model parameters, climate model, and climate scenario for reliable future streamflow projections. Full article