Search Results (6,569)

Background/Objectives: Workplace conflict and aggression pose significant psychosocial risks across diverse professional sectors. This protocol outlines a novel, university-based educational intervention. Developed by a multidisciplinary team from the University Hospital of Pisa, Italy, including occupational physicians and a psychiatrist specializing in work and organizational psychology, its primary purpose is to enhance conflict prevention and crisis management skills. While initially developed and tested within the veterinary sector due to its identified vulnerabilities, the intervention is inherently generalizable to any high-stress professional environment characterized by intense client, customer, or public interactions. Methods: The intervention integrates didactic instruction with active, immersive learning through tailored role-playing scenarios simulating real-world challenging encounters. This study protocol details the structured methodology for evaluating the immediate effectiveness of this training. We are using a specifically developed efficacy scale to assess outcomes. Results: The results demonstrate a significant improvement in all assessed skills from the pre-training to the post-training evaluation. For every item on the scale, the median scores increased, indicating a positive shift in overall group performance. The p-value for each item was <0.001, confirming that the observed improvements were statistically significant. These results demonstrate enhanced conflict resolution skills, improved communication, and an increased sense of self-efficacy among participants. Conclusions: This protocol offers a comprehensive and generalizable approach to addressing workplace psychosocial risks through an innovative educational intervention. A key future goal involves advancing this training methodology by integrating virtual reality (VR) environments with AI-driven avatars for role-playing, aiming to achieve a more realistic and impactful learning experience and sustained behavioral change. Full article

In complicated scenarios, due to the low precision of float solutions and poor reliability of fixed solutions, it is challenging to achieve a balance between accuracy and reliability of the integer least squares (ILS) estimation. To address this dilemma, the best integer equivariant (BIE) estimation, which makes a weighted sum of all possible candidates, has recently been attached great importance. The BIE solution approaches the float solution at a low ILS success rate, maintaining positioning reliability. As the success rate increases, it converges to the fixed solution, facilitating high-precision positioning. Furthermore, the posterior variance of BIE estimation provides the capability of reliability evaluation. However, in environments with a limited number or a deficient configuration of available satellites, there is a sharp decline in the strength of the GNSS precise positioning model. In this case, the exactness of weight allocation for integer candidates in BIE estimation will be severely compromised by unmodeled errors. When the ambiguity is incorrectly fixed, the wrongly determined optimal candidate is probably assigned an excessively high weight. Therefore, the BIE solution in a weak GNSS model always exhibits a significant positioning error consistent with the fixed solution. Moreover, the posterior variance of BIE estimation approximately resembles that of a fixed solution, losing error warning ability. Consequently, the BIE estimation may exhibit lower reliability compared to the ILS estimation employing a validation test with a loose acceptance threshold. To improve the positioning performance in weak GNSS models, a BIE ambiguity resolution (AR) method based on Tikhonov regularization is proposed in this paper. The method introduces Tikhonov regularization into the least squares (LS) estimation and the ILS ambiguity search, mitigating the serious impact of unmodeled errors on the BIE estimation under weak observation conditions. Meanwhile, the regularization factors are appropriately selected by utilizing an optimized approach established on the L-curve method. Simulation experiments and field tests have demonstrated that the method can significantly enhance the positioning accuracy and reliability in weak GNSS models. Compared to the traditional BIE estimation, the proposed method achieved accuracy improvements of 73.6% and 69.3% in the field tests with 10 km and 18 km baselines, respectively. Full article

This study aims to analyse the effect of partially clogged inlets on the behaviour of urban drainage systems at the city scale, particularly regarding intercepted volumes and flood depths. The main challenges were to represent the inlet network in detail at a rather large scale and to avoid the effect of sewer network surcharging on the draining capacity of inlets. This goal has been achieved through a 1D/2D coupled hydraulic model of the whole urban drainage system in La Almunia de Doña Godina (Zaragoza, Spain). The model focuses on the interaction between grated drain inlets and the sewer network under partial clogging conditions. The model is fed with data obtained on field surveys. These surveys identified 948 inlets, classified into 43 types based on geometry and grouped into 7 categories for modelling purposes. Clogging patterns were derived from field observations or estimated using progressive clogging trends. The hydrological model combines a semi-distributed approach for micro-catchments (buildings and courtyards) and a distributed “rain-on-grid” approach for public spaces (streets, squares). The model assesses the impact of inlet clogging on network performance and surface flooding during four rainfall scenarios. Results include inlet interception volumes, flooded surface areas, and flow hydrographs intercepted by single inlets. Specifically, the reduction in intercepted volume ranged from approximately 7% under a mild inlet clogging condition to nearly 50% under severe clogging conditions. Also, the model results show the significant influence of the 2D mesh detail on flood depths. For instance, a mesh with high resolution and break lines representing streets curbs showed a 38% increase in urban areas with flood depths above 1 cm compared to a scenario with a lower-resolution 2D mesh and no curbs. The findings highlight how inlet clogging significantly affects the efficiency of urban drainage systems and increases the surface flood hazard. Further novelties of this work are the extent of the analysis (city scale) and the approach to improve the 2D mesh to assess flood depth. Full article

Heat-related morbidity and mortality are increasing due to climate change, emphasizing the need to identify vulnerable areas and people exposed to extreme temperatures. To improve heat stress impact assessment, we developed a replicable machine learning model that integrates remote sensing, ground station, and geospatial data to estimate daily air temperature at a spatial resolution of 100 m × 100 m across the region of Tuscany, Italy. Using a two-stage approach, we first imputed missing land surface temperature data from MODIS using gradient-boosted trees and spatio-temporal predictors. Then, we modeled daily maximum and minimum air temperatures by incorporating monitoring station observations, satellite-derived data (MODIS, Landsat 8), topography, land cover, meteorological variables (ERA5-land), and vegetation indices (NDVI). The model achieved high predictive accuracy, with R² values of 0.95 for Tmax and 0.92 for Tmin, and root mean square errors (RMSE) of 1.95 °C and 1.96 °C, respectively. It effectively captured both temporal (R²: 0.95; 0.94) and spatial (R²: 0.92; 0.72) temperature variations, allowing for the creation of high-resolution maps. These results highlight the potential of integrating Earth Observation and machine learning to generate high-resolution temperature maps, offering valuable insights for urban planning, climate adaptation, and epidemiological studies on heat-related health effects. Full article

Background/Objectives: Sepsis is a high-mortality syndrome characterized by organ dysfunction resulting from a dysregulated host response to infection. This study aimed to evaluate the potential of growth differentiation factor 15 (GDF15), a stress-inducible cytokine, as a biomarker in patients diagnosed with urosepsis. Methods: A total of 13 patients diagnosed with urosepsis, based on an increase of ≥2 points in the Sequential Organ Failure Assessment (SOFA) score and positive urine culture, were included in the study. Daily blood samples were collected from patients for 10 days, and serum levels of GDF15, procalcitonin (PCT), and presepsin (P-SEP) were measured by ELISA. C-reactive protein (CRP), blood urea nitrogen (BUN), serum creatinine, estimated glomerular filtration rate (eGFR), hemoglobin, and neutrophil, lymphocyte, and platelet counts were determined using autoanalyzers. Temporal changes were analyzed using the Friedman test, and correlations were analyzed using Spearman’s test. Results: GDF15 levels began to decrease from Day 3, with a significant decline observed from Day 7 compared to Day 1 (p < 0.001). Similar decreasing trends were observed in CRP and PCT levels, whereas presepsin levels did not exhibit significant changes. Significant positive correlations were identified between GDF15 and CRP (r = 0.65, p = 0.015), BUN (r = 0.57, p = 0.041), and creatinine (r = 0.62, p = 0.024), and a significant negative correlation was observed with eGFR (r = −0.62, p = 0.024). No significant correlation was found between GDF15 and presepsin (p > 0.05). Conclusions: GDF15 is a biomarker sensitive to the resolution phase of inflammation and organ dysfunction in sepsis, demonstrating significant temporal changes. It holds potential as an indicator for monitoring clinical progression and assessing prognosis. Full article

The Haiyang-2B (HY-2B) satellite, launched on 25 October 2018, carries both active and passive microwave sensors, including a scanning microwave Radiometer (SMR), to deliver high-precision, all-weather global observations. Sea surface temperature (SST) is among its key products. We evaluated the HY-2B SMR Level-4A (L4A) SST (25 km resolution) over the North Pacific (0–60°N, 120°E–100°W) for the period 1 October 2023 to 31 March 2025 using the extended triple collocation (ETC) and dual-pairing methods. These comparisons were made against the Remote Sensing System (RSS) microwave and infrared (MWIR) fused SST product and the National Oceanic and Atmospheric Administration (NOAA) in situ SST Quality Monitor (iQuam) observations. Relative to iQuam, HY-2B SST has a mean bias of –0.002 °C and a root mean square error (RMSE) of 0.279 °C. Compared to the MWIR product, the mean bias is 0.009 °C with an RMSE of 0.270 °C, indicating high accuracy. ETC yields an equivalent standard deviation (ESD) of 0.163 °C for HY-2B, compared to 0.157 °C for iQuam and 0.196 °C for MWIR. Platform-specific ESDs are lowest for drifters (0.124 °C) and tropical moored buoys (0.088 °C) and highest for ship and coastal moored buoys (both 0.238 °C). Both the HY-2B and MWIR products exhibit increasing ESD and RMSE toward higher latitudes, primarily driven by stronger winds, higher columnar water vapor, and elevated cloud liquid water. Overall, HY-2B SST performs reliably under most conditions, but incurs larger errors under extreme environments. This analysis provides a robust basis for its application and future refinement. Full article

Background: Multiple sclerosis (MS) is an immune-mediated neuroinflammatory disorder with a multifactorial etiology involving genetic susceptibility, environmental triggers, and vascular contributions. Carotid intima–media thickness (CIMT) is a significant marker of endothelial dysfunction. Endothelial cell-specific molecule-1 (endocan) and hyaluronic acid, key components implicated in endothelial and vascular remodeling, may significantly contribute to the inflammatory and vascular pathologies observed in MS. We aimed to investigate the relationship between CIMT and endothelial biomarkers, such as endocan and hyaluronic acid, in patients with MS. Methods: In this cross-sectional study, 100 patients with relapsing–remitting MS and 56 healthy controls were included. Demographic, clinical, laboratory, and imaging data were documented. CIMT was measured bilaterally using high-resolution B-mode ultrasonography. Serum endocan and hyaluronic acid levels were quantified via enzyme-linked immunosorbent assays. Results: MS patients exhibited significantly higher CIMT and serum endocan levels compared with controls (p < 0.001). CIMT values were significantly elevated in MS patients, with longer disease duration, higher expanded disability status scale scores, and an older diagnosis age (p < 0.05). However, serum endocan and hyaluronic acid levels did not significantly differ between MS subgroups based on disease duration, disability severity, and diagnosis age. Additionally, there was no correlation between CIMT and serum endocan and hyaluronic acid levels in MS patients (p > 0.05). Conclusions: Increased CIMT and serum endocan levels in MS patients may indicate endothelial dysfunction suggesting vascular involvement in MS. The lack of a correlation between CIMT and endocan and hyaluronic acid levels reveals the complexity of vascular and immune interactions in MS, which needs further research. Full article

Herpes Simplex Virus (HSV) infections, caused primarily by HSV-1 and HSV-2, are among the most prevalent viral diseases worldwide, with recurrent manifestations that significantly affect quality of life. Therapeutic strategies include both topical and systemic interventions, each with distinct goals. This systematic review was conducted according to PRISMA guidelines. A comprehensive search of PubMed, Scopus, and Web of Science (2005–2025) identified studies evaluating topical or systemic treatments for HSV. Eligible studies included randomized controlled trials and observational studies reporting validated clinical outcomes. Topical treatments, including acyclovir cream, docosanol, and newer formulations, primarily reduce lesion duration and alleviate local symptoms when applied early. These interventions have limited systemic absorption and generally do not influence recurrence frequency. Novel delivery methods and combination strategies, such as acyclovir–hydrocortisone formulations or photodynamic therapy, may enhance local efficacy and symptom control. Systemic Therapies: Systemic antivirals, such as acyclovir, valacyclovir, and famciclovir, target both lesion resolution and recurrence prevention. Evidence from randomized trials supports their use for episodic and suppressive therapy, including short-course, high-dose regimens that improve adherence while controlling symptoms. Systemic therapy is particularly indicated for recurrent, disseminated, or high-risk infections. Topical and systemic therapies serve complementary roles in HSV management. Topical agents are useful for localized or initial episodes, while systemic therapy addresses broader clinical objectives, including recurrence reduction. Future research should focus on mechanism-based therapies, novel delivery systems, and standardized outcome measures to guide personalized treatment strategies. Emerging therapies targeting viral latency, immune modulation, and gene-editing technologies hold promise for long-term suppression and personalized management of HSV infections. Full article

Objectives: Connective tissue diseases (CTDs) include a diverse group of systemic autoimmune conditions, among which interstitial lung disease (ILD) is acknowledged as a major determinant of prognosis. High-resolution computed tomography (HRCT) is the gold standard for ILD assessment. The distribution of HRCT patterns across CTDs remain incompletely defined. The objective of this systematic review is to synthesize available evidence regarding the prevalence of specific radiological patterns within CTD-ILDs and to assess whether specific patterns occur at different frequencies among individual CTDs. Methods: The inclusion criteria encompassed original human studies published in English between 2015 and 2024, involving adult participants (≥18 years) with CTD-ILDs assessed primarily by HRCT and designed as retrospective, prospective, or cross-sectional trials with extractable data. We systematically searched PubMed, Scopus, and Web of Science (January 2025). Risk of bias was evaluated using the Newcastle–Ottawa Scale (NOS) for cohort and case–control studies, and the JBI Critical Appraisal Checklist for cross-sectional studies. Data were extracted and categorized by HRCT pattern for each CTD, and then summarized descriptively and statistically. Results: We analyzed 23 studies published between 2015 and 2024, which included 2020 patients with CTD-ILDs. The analysis revealed non-specific interstitial pneumonia (NSIP) as the most prevalent pattern overall (36.5%), followed by definite usual interstitial pneumonia (UIP) (24.8%), organizing pneumonia (OP) (9.8%) and lymphoid interstitial pneumonia (LIP) (1.25%). HRCT distribution varied by CTD: NSIP predominated in systemic sclerosis, idiopathic inflammatory myopathies, and mixed connective tissue disease; UIP was most frequent in rheumatoid arthritis; LIP was more common in Sjögren’s syndrome. While global differences were statistically significant, pairwise comparisons often lacked significance, likely due to sample size constraints. Discussion: Limitations include varying risk of bias across study designs, heterogeneity in HRCT reporting, small sample sizes, and inconsistent follow-up, which may reduce precision and generalizability. In addition to the quantitative synthesis, this review offers a detailed description of each radiologic pattern mentioned above, illustrated by representative examples to support the recognition in clinical settings. Furthermore, it includes a brief overview of the major CTDs associated with ILD, summarizing their epidemiological data, risk factors for ILD and clinical presentation and diagnostic recommendations. Conclusions: NSIP emerged as the most common HRCT pattern across CTD-ILDs, with UIP predominating in RA. Although inter-disease differences were observed, statistical significance was limited, likely reflecting sample size constraints. These findings emphasize the diagnostic and prognostic relevance of HRCT pattern recognition and highlight the need for larger, standardized studies. Full article

Background and Objectives: Chronic lung diseases act as multi-organ conditions in which systemic inflammation, vascular dysfunction, and fibrosis intersect. The pulmo-renal continuum—functional crosstalk between lungs and kidneys—remains poorly characterized. We compared year-long changes in endothelin-1 (ET-1), galectin-3 (Gal-3), renal indices (eGFR, ACR), and quantitative CT densitometry in COPD and systemic sclerosis-associated ILD (SSc-ILD). Materials and Methods: In this prospective observational study (January 2023–December 2024), 112 patients were consecutively enrolled (COPD, n = 58; SSc-ILD, n = 54). Assessments were performed at baseline and 12 months. ET-1 (ELISA) and Gal-3 (chemiluminescence) were measured in serum; eGFR was calculated by the creatinine-based CKD-EPI (2021) equation; ACR was photometric. High-resolution chest CT provided lung volume and parenchymal density (Hounsfield units) at six predefined axial levels per lung. Non-parametric statistics were applied: Wilcoxon signed-rank (within-group), Mann–Whitney U (between-group), and Spearman rank correlations for associations; results are reported with p-values (and 95% CIs). Results: Baseline eGFR was normal (COPD 90.37; SSc-ILD 92.4 mL/min/1.73 m²). eGFR declined by 6.76% in COPD (p = 0.001) and 3.16% in SSc-ILD (p = 0.029). ET-1 increased in both cohorts but more in COPD (+83.78%, p = 0.0002) than in SSc-ILD (+23.83%, p = 0.0001). Gal-3 rose significantly only in SSc-ILD (+10.2%, p = 0.043). FVC decreased in COPD (−4.01%, p = 0.01) and was unchanged in SSc-ILD. Total lung volume declined in SSc-ILD (−6.08%, p = 0.02) but not in COPD. CT density shifts were small: several slices in COPD and one slice (L6) in SSc-ILD reached statistical but not biological relevance. Conclusions: COPD exhibited larger vascular and renal biomarker shifts (ET-1 up, eGFR down, ACR up), suggesting systemic inflammation and early renal involvement. In SSc-ILD, biomarker and CT changes predominantly reflected pulmonary fibrosis progression with limited renal impact. Integrating biomarkers with quantitative CT may help delineate organ-specific trajectories along the pulmo-renal continuum; longer, larger studies are warranted. Limitations: This was a single-center cohort with a modest sample (58 COPD and 54 SSc-ILD) and a 12-month, two-time-point follow-up, which may not capture long-term trajectories and may limit it generalizability; larger multicenter studies with an extended follow-up are warranted. Full article

Laser-induced forward transfer (LIFT) bioprinting enables precise deposition of biological materials for advanced biomedical applications. This study presents a parametric analysis of the donor–receiver distances (1.0, 1.5, 2.0, 2.5, and 3.0 mm) in LIFT bioprinting, investigated through high-speed video and image analysis of 4 × 4 spot arrays. Droplet velocity was quantified and jet trajectory characterized, revealing that increased distances reduced spatial resolution, with significant shape deterioration observed beyond 2.0 mm. Thus, a maximum 2.0 mm donor–receiver gap was determined as optimal for acceptable printing resolution. As an application, a microfluidic device was fabricated using LCD 3D printing with a biocompatible resin and glass-bottomed configuration. The chamber height was matched to the validated 2.0 mm distance, ensuring compatibility with LIFT printing. Computational fluid dynamics simulations were conducted to model fluid flow conditions within the device. Subsequently, LLC cells were successfully printed inside the microfluidic chamber, cultured under continuous flow for 24 h, and demonstrated normal proliferation. This work highlights LIFT bioprinting’s viability and precision for integrating cells within microfluidic platforms, presenting promising potential for organ-on-chip applications and future biomedical advancements. Full article

This study presents the implementation and evaluation of a high-resolution operational forecasting system for the Tagus estuary (Portugal), focusing on inundation and water quality predictions to support estuarine management. Developed using the relocatable Water Information Forecast Framework (WIFF), the system integrates two implementations of SCHISM: a 2D barotropic model including wave–current interactions for flood-prone areas, and a 3D baroclinic model simulating salinity, temperature, and biogeochemical variables. Forecasts were assessed over six months using in situ and satellite near real-time observations. Results show that the operational models represent well water levels, waves, salinity, temperature, and water quality dynamics. Compared to a regional model, the local forecast system generally offers improved accuracy within the estuary due to higher spatial resolution and better representation of local dynamics. Several challenges remain, including uncertainties in oceanic and riverine boundary conditions and limited high-resolution near real-time observations to continuously assess and improve operational models. Furthermore, the absence of operational two-way coupling between regional and local models limits cross-scale integration of physical and biogeochemical processes. The forecasting system for the Tagus estuary demonstrates the potential of local high-resolution operational models as reliable, user-oriented tools for managing transitional water systems, and as core elements for coastal management. Full article

Visibility of the sea plays a significant role in shaping spatial perception, property value, and planning decisions in coastal areas. While traditional GIS-based viewshed analysis provides useful tools for modeling visibility, it remains limited by its 2.5D nature and simplified representations of terrain and vegetation. This study presents a 3D ray-tracing-based method for analyzing water surface visibility using high-resolution LIDAR data and physically based rendering techniques within a fully 3D environment. The methodology allows for realistic modeling of visibility from a human perspective, accounting for complex occlusions caused by buildings, terrain, and vegetation. Unlike conventional GIS tools, the proposed approach identifies visible areas beneath tree canopies and enables vertical exploration of visibility from different elevations and building floors. The method was applied in a case study of the coastal city of Świnoujście, Poland. The resulting viewshed was validated through photographic field verification from observer height (1.7 m), confirming the accuracy of visibility predictions. This research demonstrates the potential of ray-tracing methods in landscape and urban visibility analysis, offering a flexible and perceptually accurate alternative to traditional GIS-based approaches. Future work will focus on quantifying the visible extent of the water surface to support more detailed assessments of visual exposure in planning and conservation context. Full article

Current simulation training for pilots wearing night vision goggles (NVGs) (e.g., night landings and tactical reconnaissance) faces fidelity limitations from conventional displays. This study proposed a novel dynamic NIR-LED direct-view display system for authentic nighttime scene simulation. Through comparative characterization of NVG response across LED wavelengths under ultra-low-current conditions, 940 nm was identified as the optimal wavelength. Quantification of inherent nonlinear response in NVG observation enabled derivation of a mathematical model that provides the foundation for inverse gamma correction compensation. A prototype NIR-LED display was engineered with 1.25 mm pixel pitch and 1280 × 1024 resolution at 60 Hz refresh rate, achieving >90% uniformity and >2000:1 contrast. Subjective evaluations confirmed exceptional simulation fidelity. This system enables high-contrast, low-power NVG simulation for both full-flight simulators and urban low-altitude reconnaissance training systems, providing the first quantified analysis of NVG-LED nonlinear interactions and establishing the technical foundation for next-generation LED-based all-weather visual displays. Full article

Sea surface temperature (SST) is vital for climate monitoring and extreme weather forecasting. Existing global SST datasets are typically provided at daily to seasonal resolutions, while hourly data remain limited to regional scales. Polar-orbiting satellites offer global coverage but low temporal resolution, providing only 1–2 observations per day. Geostationary satellites provide high temporal resolution but cover only part of the region. These limitations create a gap in the availability of global, hourly SST data. To address this, we propose a Triple-Collocation (TC)-based fusion algorithm for generating accurate global hourly SST data through multi-source integration. The method includes data preprocessing (quality control and linear interpolation), merging five geostationary SST datasets into two global sets by priority, applying TC fusion to three polar-orbiting datasets, and finally combining all sources via multi-source TC fusion. Results show improved temporal resolution and increased spatial coverage to 32%. The fused dataset achieves high accuracy, with a daily mean Bias below 0.0427 °C, RMSE about 0.5938 °C to 0.6965 °C, and R² exceeding 0.9879. These outcomes demonstrate the method’s reliability and its potential for supporting climate and environmental research. Full article