Search Results (99)

Accurate reservoir inflow forecasting is vital for effective water resource management. Reliable forecasts enable operators to optimize storage and release strategies to meet competing sectoral demands—such as water supply, irrigation, and hydropower scheduling—while also mitigating flood and drought risks. To address this need, in this study, we propose a novel time-variant encoder–decoder (ED) model designed specifically to improve multi-step reservoir inflow forecasting, enabling accurate predictions of reservoir inflows up to seven days ahead. Unlike conventional ED-LSTM and recursive ED-LSTM models, which use fixed encoder parameters or recursively propagate predictions, our model incorporates an adaptive encoder structure that dynamically adjusts to evolving conditions at each forecast horizon. Additionally, we introduce the Expected Baseline Integrated Gradients (EB-IGs) method for variable importance analysis, enhancing interpretability of inflow by incorporating multiple baselines to capture a broader range of hydrometeorological conditions. The proposed methods are demonstrated at several diverse reservoirs across the United States. Our results show that they outperform traditional methods, particularly at longer lead times, while also offering insights into the key drivers of inflow forecasting. These advancements contribute to enhanced reservoir management through improved forecasting accuracy and practical decision-making insights under complex hydroclimatic conditions. Full article

Thickness inspection of thermal barrier coatings is crucial to safeguard the reliability of high-temperature components of aero-engines, but traditional destructive inspection methods are difficult to meet the demand for rapid assessment in the field. In this study, a new non-destructive testing method integrating terahertz time-domain spectroscopy and machine learning algorithms is proposed to systematically study the thickness inspection of 8YSZ coatings prepared by two processes, namely atmospheric plasma spraying (APS) and electron beam physical vapor deposition (EB-PVD). By optimizing the preparation process parameters, 620 sets of specimens with thicknesses of 100–400 μm are prepared, and three types of characteristic parameters, namely, time delay Δt, frequency shift Δf, and energy decay η, are extracted by combining wavelet threshold denoising and time-frequency joint analysis. A CNN-RF cascade model is constructed to realize coating process classification, and an attention-LSTM and SVR weighted fusion model is developed for thickness regression prediction. The results show that the multimodal feature fusion reduces the root-mean-square error of thickness prediction to 8.9 μm, which further improves the accuracy over the single feature model. The classification accuracy reaches 96.8%, of which the feature importance of time delay Δt accounts for 62%. The hierarchical modeling strategy reduces the detection mean absolute error from 6.2 μm to 4.1 μm. the method provides a high-precision solution for intelligent quality assessment of thermal barrier coatings, which is of great significance in promoting the progress of intelligent manufacturing technology for high-end equipment. Full article

Inherited epidermolysis bullosa (EB) comprises a group of genetic disorders characterized by fragile skin that blisters easily. Targeted therapies for EB necessitate personalized approaches, underscoring the importance of precise diagnostics through genetic analysis and skin biopsy using transmission electron microscopy and/or immunohistochemistry. This study highlights the application of whole-exome sequencing (WES) to identify key pathogenic variants associated with EB. Most identified variants were associated with the recessive form of dystrophic EB, including four novel COL7A1 mutations: p.Leu1488ArgfsTer222, c.7759-3C>G, p.Gln1886Ter, and c.6501+6T>C, as well as recurrent variants p.Lys142Arg and p.Gly2049Glu. Additionally, variants were detected in KRT5 (c.971T>C, p.Val324Ala), associated with EB simplex, and in LAMB3 (c.2500C>T, p.Gln834Ter) in the homozygous state, associated with junctional EB. In silico splice prediction tools suggested disrupted splicing in both cases. One patient received topical gentamicin therapy targeting the nonsense mutation p.Gln1886Ter. These findings underscore the utility of WES in EB diagnostics, broaden the mutation spectrum, and contribute to the understanding of genotype–phenotype correlations in adult patients with EB. Full article

This study develops a novel physics-informed neural network (PINN) framework for predicting steady-state dynamic responses of infinite Euler–Bernoulli (E–B) beams on foundations under moving loads. By combining localized PINN modeling with transfer learning techniques, our approach achieves high-fidelity predictions across broad parameter ranges while significantly reducing data requirements. Numerical results show that the method maintains accuracy with less than half the training data of conventional PINN models (15 target domains) and remains effective with just four domains for approximate solutions. Key findings demonstrate that optimal spatial distribution—rather than quantity—of target domains ensures robustness against noise and parameter variations. The framework advances data-efficient surrogate modeling, enabling reliable predictions in data-scarce scenarios with applications to complex engineering systems where experimental data are limited. Full article

Kindler Epidermolysis bullosa (KEB; OMIM 173650) is a rare autosomal recessive genodermatosis characterized by bullous poikiloderma and photosensitivity. Additional presentations include blistering, poor wound healing, skin atrophy, and increased risk of skin cancer. Most cases of KEB result from aberrations in the FERMT1 (Fermitin family member 1) gene encoding kindlin-1 and include nonsense, frameshift, splicing, and missense variants. Large deletion variants have been reported in nine cases to date. Most variants are predicted to lead to premature termination of translation and to loss of kindlin-1 function. In this study, we report on a 33-year-old male patient who presented with typical clinical manifestations of KEB. As routine molecular testing failed to obtain a diagnosis, Next Generation Sequencing (NGS) of an Epidermolysis Bullosa (EB)-specific panel was carried out followed by the determination of the deletion breakpoints and verification at the mRNA and protein levels. This approach revealed a new large homozygous deletion of ~9.4 kb in the FERMT1 gene involving exons 7 to 9. Finally, we performed a literature review on large FERMT1 deletions. The deletion is predicted to skip exons 7 to 9 within the mRNA, which results in a frameshift. The patient’s phenotype is likely caused by the resulting truncated and non-functioning protein. Our report further enriches the spectrum of FERMT1 gene variants to improve genotype–phenotype correlations. Full article

In the pursuit of sustainable urban transportation, electric buses (EBs) have emerged as a promising solution to reduce emissions. The increasing adoption of EBs highlights the critical need for accurate energy consumption prediction. This study presents a comprehensive methodology integrating traction modeling with a Light Gradient Boosting Machine (LightGBM)-based trip-level energy consumption prediction framework to address challenges in power system efficiency and passenger load estimation. The proposed approach combines transmission system efficiency evaluation with dynamic passenger load estimation, incorporating temporal, weather, and driving pattern features. The LightGBM model, hyperparameter tuned through Bayesian Optimization (BO), achieved a mean absolute percentage error (MAPE) of 3.92% and root mean square error (RMSE) of 1.398 kWh, outperforming traditional methods. SHAP analysis revealed crucial feature impacts on trip-level energy consumption predictions, providing valuable insights for operational optimization. The model’s computational efficiency makes it suitable for real-time IoT applications while establishing precise parameters for future optimization strategies, contributing to more sustainable urban transit systems. Full article

In 2020, BDS-3 began broadcasting high-precision positioning correction products through B2b signals, effectively addressing the limitations of ground-based augmentation. However, challenges such as the “south wall effect” from geostationary orbit (GEO) satellites, issues of data (IOD) mismatch, and signal priority conflicts often result in interruptions and anomalies during real-time positioning with the B2b service. This paper proposes a continuous B2b-PPP (B2b signal-based Precise Point Positioning) model that incorporates signal-in-space range error (SISRE) residuals and predictions for B2b orbits and clock corrections to achieve seamless, high-precision continuous positioning. In our experiments, we first analyze the characteristics of B2b SISRE for both BDS-3 and GPS. We then evaluate the positioning accuracy of several models, B2b-PPP, EB2b-PPP, PB2b-PPP, EB2bS-PPP, and PB2bS-PPP, through simulated and real dynamic experiments. Here, ‘E’ indicates the direct utilization of the previous observation corrections from B2b before the signal interruption, ‘P’ represents B2b prediction products, and ‘S’ signifies the incorporation of the SISRE residuals. The results show that EB2b-PPP exhibits significant deviations as early as 10 min into a B2b signal interruption. Both PB2b-PPP and EB2bS-PPP demonstrate comparable performances, with PB2bS-PPP emerging as the most effective method. Notably, in real dynamic experiments, PB2bS-PPP maintains positioning accuracy in the E/N directions like B2b-PPP, even after 40 min of signal interruption, ensuring continuous and stable positioning upon signal restoration. This achievement significantly enhances the capability for high-precision continuous positioning based on B2b signals. Full article

This paper presents the results of an experimental study involving 20 tests performed on elliptical concrete columns confined with externally bonded carbon fiber-reinforced polymer (EB-CFRP) laminates. The study aimed to evaluate the effects of elliptical aspect ratio (A/B) as well as confinement rigidity (number of EB-FRP layers) on confinement effectiveness. The experimental program consisted of one series of control concrete columns (unstrengthened) and three additional series, each one strengthened with one, two and three layers of EB-CFRP sheets, respectively. Furthermore, each series considered five elliptical aspect ratios (A/B) ranging from 1.0 to 1.6. Following compressive concentric tests until failure, the results were analyzed to characterize the confinement level with an increasing number of EB-CFRP layers as a function of the elliptical aspect ratio. The results show considerable enhancements in compressive strength and in the ductility of the confined columns. Furthermore, this improvement is amplified as the number of EB-CFRP layers increases, indicating a proportional relationship between the compressive strength and the number of CFRP layers. It is found that the ultimate strength of EB-CFRP-confined columns with three layers reached up to 130% compared to the control specimens. However, increasing the elliptical aspect ratio reduced the compressive strength and ductility of confined columns. This study investigated the relation between the CFRP hoop and axial strains and the elliptical aspect ratios. Moreover, through comparison, the results reveal that the prediction models proposed by the Canadian standards S806-12 and S6-19 do not capture the negative effect of the elliptical aspect ratio in confined concrete columns. Full article

Background/Objective: Eating behaviors (EB) correlate with weight loss after bariatric surgery (BS). Therefore, the investigation of EB could guide interventions to prevent insufficient weight outcomes. Method: A prospective cohort of 85 patients undergoing Roux-en-Y Gastric Bypass (RYGB; 84.7% female, mean age 44.7 ± 9.3 years) was included. Six months after undergoing RYGB, EB patterns, including cognitive restraint (CR), uncontrolled (UE), and emotional eating (EE), were assessed using the Three-Factor Eating Questionnaire R21 (TFEQ-R21). History, physical examination, and anthropometric assessments were collected pre- and 12 months postoperative. Patients were divided based on the percentage of excess weight loss (%EWL < 80% or ≥80%) and EB patterns were correlated with weight outcomes at 12 months. Results: The %EWL ≥ 80% group demonstrated significantly higher scores in CR and EE compared to %EWL < 80% (p < 0.001 and p = 0.01, respectively). UE scores were similar between groups (p = 0.41). At 12 months postoperative, the %EWL ≥ 80% group had negative correlations between CR and BMI and positive correlations between CR and EWL (rho = −0.33 and rho = 0.29; p = 0.04). Multiple logistic regression considering %EWL ≥ 80% as the aim outcome revealed that CR had a significant influence (OR = 1.037; p = 0.058), while age (OR = 0.962; p = 0.145), sex (OR = 2.984; p = 0.135), UE (OR = 0.995; p = 0.736), and EE (OR = 1.017; p = 0.296) did not. Conclusions: EBs influence outcomes after BS, and a model using TFEQ-R21 predicted them. CR six months post-surgery was the strongest predictor of higher EWL at 12 months. Further research is needed to understand the relationship between restrictive EB and BS outcomes, possibly identifying strategies to prevent disordered EB in patients with higher scores. Full article

Wasp venom allergy can trigger severe allergic reactions, and predicting these acute responses remains challenging. This study evaluates the utility of immune system indexes, particularly the eosinophil–basophil/lymphocyte (EB/LR) and eosinophil–basophil–platelet/lymphocyte (EBP/LR) ratios, in assessing the severity of allergic reactions in patients with wasp venom allergy. A total of 61 patients with confirmed wasp venom allergy were categorized according to the Mueller scale, which classifies the severity of allergic reactions. Blood samples were analyzed for total and specific IgE levels alongside a range of hematological and biochemical parameters. This study found significant differences in the EB/LR and EBP/LR indexes between patients with mild (Mueller I–II) and severe (Mueller III–IV) allergic reactions, with higher values indicating more severe responses. However, no significant differences were observed in other immune indexes, such as the platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, systemic immune-inflammation index, and systemic inflammatory response index, as well as in additional blood parameters. These findings suggest that the EB/LR and EBP/LR ratios may serve as useful markers for predicting the severity of allergic reactions in patients with wasp venom allergy. This is the first study to establish such a link, although further research with larger cohorts is necessary to confirm these results and their potential application in clinical settings. Full article

Environmental and energy sustainability concerns have catalyzed a global transition toward renewable biofuel alternatives. Among these, biodiesel stands out as a promising substitute for conventional diesel in compression-ignition engines, providing compatibility without requiring modifications to engine design. A comprehensive understanding of biodiesel’s physical properties is crucial for accurately modeling fuel spray, atomization, combustion, and emissions in diesel engines. This study focuses on predicting the physical properties of PODL20 and EB100, including liquid viscosity, density, vapor pressure, latent heat of vaporization, thermal conductivity, gas diffusion coefficients, and surface tension, all integrated into the CONVERGE CFD fuel library for improved combustion simulations. Subsequently, numerical simulations were conducted using the predicted properties of the biodiesels, validated by experimental in-cylinder pressure data. The prediction models demonstrated excellent alignment with the experimental results, confirming their accuracy in simulating spray dynamics, combustion processes, turbulence, ignition, and emissions. Notably, significant improvements in key combustion parameters, such as cylinder pressure and heat release rate, were recorded with the use of biodiesels. Specifically, the heat release rates for PODL20 and EB100 reached 165.74 J/CA and 140.08 J/CA, respectively, compared to 60.2 J/CA for conventional diesel fuel. Furthermore, when evaluating both soot and NO_x emissions, EB100 displayed a more balanced performance, achieving a significant reduction in soot emissions of 34.21% alongside a moderate increase in NO_x emissions of 45.5% compared to diesel fuel. In comparison to PODL20, reductions of 20.4% in soot emissions and 3% in NO_x emissions were also noted. Full article

Automakers are focusing on lightweight vehicles to address fuel economy and emission challenges and are using high-performance materials such as 2K PU-based joints as alternatives to cast iron, steel, and other metals. This study was conducted with the aim of expanding the application of 2K PU and enhancing its compatibility with steel substrates, which are commonly used in the automotive manufacturing industry, through the use of O-I hybrid nanoparticles containing alkoxysilane groups as additives in the 2K PU formulation. At the same time, the simplified process introduced and examined in this study demonstrates its feasibility for industrial-scale applications; the process offers notable advantages in reducing workload and curing time by eliminating cumbersome surface pretreatment steps before applying the 2K PU layer. Two types of commercial SB PU and EB PU were selected to study the mechanism by which O-I hybrid NPs enhance adhesion when integrated directly into the 2K PU formulation. We optimized various input parameters through practical work and modeling using the response surface method. These parameters included the amounts of AFAP precursor, APTES, and butylene glycol (BG) and the mixing ratio of O-I hybrid NPs in the formulations of two commercial PUs. The results show that O-I hybrid NPs significantly enhance adhesion, increasing performance on stainless surfaces by up to 2.35 times compared to pristine EB and SB PU. Notably, the SB PU’s performance can improve up to 2.5 times according to the RSM predictions, highlighting the substantial impact of O-I hybrid NPs. Full article

This paper describes the process of producing chemosensors based on hybrid nanostructures obtained from Al₂O₃, as well as ZnO ceramic nanotubes and the following conducting polymers: poly(3-hexylthiophene), polyaniline emeraldine-base (PANI-EB), and poly(3, 4-ethylenedioxythiophene)-polystyrene sulfonate. The process for creating ceramic nanotubes involves three steps: creating polymer fiber nets using poly(methyl methacrylate), depositing ceramic films onto the nanofiber nets using magnetron deposition, and heating the nanotubes to 600 °C to burn off the polymer support completely. The technology for obtaining hybrid nanostructures from ceramic nanotubes and conducting polymers is drop-casting. AFM analysis emphasized a higher roughness, mainly in the case of PANI-EB, for both nanotube types, with a much larger grain size dimension of over 5 μm. The values of the parameter Rku were close or slightly above 3, indicating, in all cases, the formation of layers predominantly characterized by peaks and not by depressions, with a Gaussian distribution. An ink-jet printer was used to generate chemiresistors from ceramic nanotubes and PANI-EB structures, and the metallization was made with commercial copper ink for printed electronics. Calibration curves were experimentally generated for both sensing structures across a wider range of NH₃ concentrations in air, reaching up to 5 ppm. A 0.5 ppm detection limit was established. The curve for the ZnO:PANI-EB structure presented high linearity and lower resistance values. The sensor could be used in medical diagnosis for the analysis of breath ammonia and biomarkers for predicting CKD in stages higher than 1. The threshold value of 1 ppm represents a feasible value for the presented sensor, which can be defined as a simple, low-value and robust device for individual use, beneficial at the patient level. Full article

Epidermolysis bullosa (EB) is a clinically and genetically heterogeneous group of mechanobullous diseases characterized by non-scarring blisters and erosions on the skin and mucous membranes upon mechanical trauma. The simplex form (EBS) is characterized by recurrent blister formation within the basal layer of the epidermis. It most often results from dominant mutations in the genes coding for keratin (K) 5 or 14 proteins (KRT5 and KRT14). A disruptive mutation in KRT5 or KRT14 will not only structurally impair the cytoskeleton, but it will also activate a cascade of biochemical mechanisms contributing to EBS. Skin lesions are painful and disfiguring and have a significant impact on life quality. Several gene expression studies were accomplished on mouse model and human keratinocytes to define the gene expression signature of EBS. Several key genes associated with EBS were identified as specific immunological mediators, keratins, and cell junction components. These data deepened the understanding of the EBS pathophysiology and revealed important functional biological processes, particularly inflammation. This review emphasizes the three EBS subtypes caused by dominant mutations on either KRT5 or KRT14 (localized, intermediate, and severe). It aims to summarize current knowledge about the EBS expression profiling pattern and predicted molecular mechanisms involved and to outline progress in therapy. Full article

Background: Bronchiectasis (BE) has been traditionally associated with neutrophilic inflammation, but eosinophilic bronchiectasis (EB) has recently emerged. Data about prevalence, clinical features, and disease severity are lacking. This study aimed to assess the EB prevalence, compare EB with non-EB, evaluate the Type-2 (T2) high endotype in BE (T2-high EB) versus non-T2-high EB, and identify EB predictors. Methods: We conducted a prospective study involving 153 BE patients. The data collected included clinical, radiological, and microbiological findings. BE severity was assessed using the bronchiectasis severity index (BSI), FACED and E-FACED scores, and the bronchiectasis etiology and comorbidity index (BACI). EB was defined as a blood eosinophil count (BEC) ≥ 300 cells/μL, and T2-high EB as BEC ≥ 300 cells/μL with fractional exhaled nitric oxide (FeNO) ≥ 25 ppb. Results: Prevalence was 27% for EB and 20% for T2-high EB. EB patients exhibited poorer lung function and more severe radiologic features, with significantly higher severity scores [BSI, FACED, E-FACED, BACI (p < 0.05)], and a higher median exacerbation rate [4 (2–5) in EB vs. 2 (1–4) in non-EB, p = 0.0002], compared with non-EB patients. T2-high EB patients showed higher severity scores [BSI, FACED, E-FACED (p < 0.05)], as well as worse lung function parameters [FEV₁%, FVC%, FEF _25–75% (p < 0.05)] compared with non-T2-high EB patients. In our study, patients with EB exhibited notably worsened lung function and higher BE severity scores compared with their non-EB counterparts, with exacerbations playing a major role in these differences. We found statistically significant positive correlations between BEC and disease severity scores, such as BSI, FACED, and mMRC, as well as an inverse relationship with pulmonary function. The likelihood of EB being present was significantly higher in association with mMRC ≥ 1 (OR = 2.53; 95% CI, 1.26–5.64), exacerbations/year ≥ 1 (OR = 1.27; 95% CI, 1.0–1.63), and chronic PA colonization (OR = 3.9; 95% CI, 1.08–15.8). Conclusions: EB is a distinct endotype. Dyspnea, exacerbations, and PA colonization may be predictive of EB, emphasizing the importance of early detection for improved outcomes. BEC could serve as a useful biomarker of disease severity to consider when diagnosing EB. Full article