Search Results (106)

Background: Tests for a trend in location are appropriate when there is an ordered alternative such as, for example, when it is assumed that the effect does not decrease with increasing doses of a drug or fertilizer. Classical trend tests for normally distributed data as well as the nonparametric Jonckheere trend test can have inflated type I error rates when variances differ between groups. Here, different approaches suggested to handle heterogeneous variances are investigated in combination with the Williams trend test. Methods: A simulation study was performed to compare the Jonckheere trend test with competing tests. The different tests were investigated for normal and non-normal data and also applied to a data set on sizes of walnuts opened by birds in various stages of a winter. Results: With one exception, all investigated trend tests can have an inflated type I error rate when variances differ. Only a nonparametric multiple contrast test based on relative effects showed an acceptable type I error rate in all scenarios considered in the simulation. Conclusions: The Williams trend test in combination with the nonparametric multiple contrast test based on relative effects can be suggested for routine use. With this procedure, an increase in variance cannot cause a significant result in the test for trend. Full article

This paper evaluates a dense, total-variation-based optical flow method for retrieving wildfire smoke plume motion vectors from geostationary, deep-space, and airborne remote sensing imagery. Using multiple major fire events, we assess the robustness of the approach across a range of spatial resolutions and time intervals. The test cases include Geostationary Operational Environmental Satellite (GOES) observations of the 2025 Los Angeles Fires and the 2024 Park Fire, imagery from NASA’s Enhanced MODIS Airborne Simulator (eMAS) for the 2019 Sheridan and Williams Flats Fires, and a complementary Park Fire image pair from the Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR). Optical flow is computed directly on radiance fields, and smoke plumes are isolated using smoke masks derived from the Segmentation, Instance Tracking, and data Fusion Using multi-SEnsor imagery (SIT-FUSE) framework where available. Performance is evaluated by comparing the root mean square error (RMSE) between original image pairs and between the first image and the second image after warping with the retrieved motion field. RMSE is computed both globally and over smoke-only regions. Across GOES and eMAS cases, optical flow systematically reduces RMSE, often by more than a factor of two within smoke regions, indicating substantially improved frame-to-frame alignment of plume structures after motion correction. The DSCOVR/EPIC case, despite its coarser spatial resolution and longer temporal separation, also shows a marked reduction in global RMSE, demonstrating that the method remains informative under a broader range of observational conditions. For a selected subset of 10 consecutive GOES Park Fire pairs, we additionally compare the retrieved smoke motion vectors with collocated winds from the High-Resolution Rapid Refresh (HRRR) model and find the closest agreement in a broad lower-tropospheric layer centered near 875 hPa. These results show that dense optical flow can capture fine-scale plume evolution in high-temporal-resolution datasets while also providing useful motion estimates in coarser, global-view imagery. RMSE reduction is interpreted here as evidence of improved motion-compensated alignment, while the HRRR comparison provides initial physical context rather than independent validation. The resulting smoke motion vector fields provide a foundation for future comparison with model winds and for applications in plume analysis, fire hazard monitoring, and air quality studies. Full article

Banana pseudostem is an abundant lignocellulosic residue with potential for value-added applications. This study evaluated five banana varieties to determine their suitability for bioplastic production, with Williams showing the highest cellulose yield (26.99% ± 0.23). Cellulose extracted from this variety was combined with corn-starch (1:1 w/w) to synthesize a bioplastic through gelatinization and lyophilization. FTIR confirmed effective removal of lignin and hemicellulose from the pseudostem and evidenced new hydrogen-bond interactions between cellulose and starch through O–H band shifts (3335 → 3282 cm⁻¹). SEM revealed a porous laminar morphology with cellulose particles (40–52 µm) embedded within the starch matrix. DSC analysis showed that the bioplastic exhibits an intermediate thermal profile between its components, while mechanical compression increased the endothermic transition temperature (from 69 °C to 85 °C) and reduced molecular mobility. Tensile testing demonstrated that compression markedly improved mechanical performance, increasing tensile strength from 0.094 MPa to 0.69 MPa and density from 110 to 638.7 kg/m³. These findings indicate that cellulose–starch bioplastics derived from banana pseudostem possess favorable structural, thermal, and mechanical characteristics for short-use applications. The approach also contributes to the valorization of agricultural waste through biodegradable material development. Full article

In this study, bio-based polyurethanes (PUs) were synthesized using renewable polyols derived from sunflower seed oil, aiming to develop flexible yet robust polymeric films and scaffolds. Given their composition and favorable physico-chemical properties, these materials may represent promising candidates for the design and development of advanced biomedical systems. Two distinct oil polyols were prepared via glycerol transesterification (GM) and epoxidation (EPO) with hydrogen peroxide/glacial acetic acid, respectively. These polyols, in combination with poly(tetramethylene ether) glycol (PTMEG) and/or poly(ethylene glycol) (PEG), served as diol components in a one-step reaction with 1,6-hexamethylene diisocyanate (HDI). The structure of the polyol precursors was thoroughly characterized by MALDI-TOF MS and NMR spectroscopy, confirming successful functionalization. The resulting PU films exhibited excellent flexibility (885%) and mechanical properties (23 MPa), as evaluated by ATR-FTIR, Tensile test, DSC, DMA and SEM methods. The crosslink density of the order of 10⁻³ also contributes to the development of outstanding mechanical properties. Stress relaxation experiments were described using a stretched exponential (Kohlrausch–Williams–Watts) model to capture the viscoelastic behavior of the materials. In addition, stress vs. relative elongation curves revealing strain-hardening behavior were also analyzed and modeled mathematically to better describe the mechanical response under deformation. Furthermore, salt leaching techniques were employed to fabricate porous scaffolds. This work highlights the versatility of vegetable oil-based feedstocks in producing functional polyurethanes with tunable mechanical properties for applied polymer systems. Full article

The family name Hay (plus associated spelling variants) is a prominent Anglo-Norman-in-origin surname that has been well-documented as a Scottish noble lineage since the 12th century CE. Their historical significance, linked to the rise in the Anglo-Norman era (1093–1286 CE) in Scotland, and the historical complexities of surname adoption post-Norman conquest of England, justifies the need for a comprehensive understanding of the genetic history of the Hay noble lineage. This study focuses on examining the patterns of paternal inheritance in lineages with the Hay surname. We conducted a comprehensive analysis of Y-chromosome data that is publicly available on the Family Tree DNA (FTDNA) platform, and specific FTDNA surname projects, as well as looking in more detail at three well-documented male-line descendants of William II de la HAYA, 1st of Erroll (d. 1201) that have been verified to a high degree of confidence. Our results reveal that all descendants of William II de la HAYA, 1st of Erroll (d. 1201) derive from the multigenerational Y-SNPs R1a-YP6500 (plus equivalent SNPs BY33394/FT2017) and R1a-FTT161. Furthermore, subclades of R1a-FTT161 have been identified that confirm direct male-line descent from two of William II de la HAYA’s sons. Subclade R1a-BY199342 (plus equivalents) confirms direct male-line descent from David de la HAYA, 2nd of Erroll (d. 1241), and subclade R1a-FTA7312 confirms direct male-line descent from Robert de la HAYA of Erroll. The result also confirms that the Hay noble lineage shares the Y-SNP R1a-YP4138 (estimated to have occurred in 832 CE) with several non-Hay test takers that have surnames of Norman origin, therefore providing further evidence to support the Norman origin hypothesis for these surnames. In addition to the identification of multigenerational Y-SNPs associated with documented Hay noblemen, this study has observed significant Y-DNA haplogroup diversity among males with the surname Hay (plus associated spelling variants: Hays, Haye, Hayes, Hey and Haya). Our results show that only 22% of the men sampled (n = 109) with the surname Hay (plus associated spelling variation) are descended from the 12th-century progenitor of the noble Hay lineage of Scotland. Therefore, this confirms that a significant proportion of males with the surname Hay do not descend from the noble progenitor of the Scottish Hay lineage of Erroll. Full article

Cylindrical bodies generate flow-induced noise when exposed to external flows, which can be predicted numerically using Computational Fluid Dynamics (CFD) combined with the Ffowcs Williams–Hawkings (FW–H) Equation. Accurate prediction, however, requires turbulence models such as Detached Eddy Simulation (DES) with fine spatial resolution and small time steps, in addition to time-dependent surface pressure data and receiver arrangements. These requirements greatly increase computational costs and limit the applicability of such methods during the design stage. To address this challenge, a Deep Neural Network (DNN) model was developed to predict flow-induced noise around a cylinder. Training data were generated from CFD cases using cylinder geometry and inflow velocity as design variables, with multiple receivers arranged in a polar coordinate system. Acoustic signals were computed using Farassat’s Formulation 1A, the time-domain surface solution of the FW–H Equation. The DNN was trained with design variables, receiver coordinates, and octave-band center frequencies as inputs, while the Sound Pressure Level (SPL) served as the output. Model performance was evaluated using the adjusted coefficient of determination (${\mathrm{R}}_{\mathrm{adj}}^2$) and the root mean squared error (RMSE). In addition, interpolation capability was tested by varying receiver spacing to examine robustness under sparse data conditions. The results confirm that the proposed framework provides accurate and computationally efficient predictions suitable for early-stage design. Full article

In order to conveniently and efficiently determine the Permissible Exposure Limits (PELs) of organic chemicals in the workplace, this study employed Quantitative Structure–Activity Relationship (QSAR) modeling to predict properties related to occupational health and safety. The predictive study was conducted by correlating the PELs of 75 hydrocarbons and their oxygen-containing derivatives with the molecular structures of the organic compounds. Meanwhile, this study conducted a comprehensive and in-depth comparative analysis of the four developed predictive models. The sample set was partitioned using the Affinity Propagation (AP) clustering algorithm. Four characteristic molecular descriptors were selected by integrating the Genetic Algorithm (GA) with the variance inflation factor (VIF) value. Subsequently, the Multiple Linear Regression (MLR) model and two nonlinear models, namely the Support Vector Machine (SVM) and the Extreme Gradient Boosting (XGBoost), were developed and used for predictive comparison. Furthermore, the performance of the models was evaluated through both internal and external validation methods, and the Williams plots were constructed to define the model’s applicability domain. The results indicated that the XGBoost model achieved high performance, with a coefficient of determination (R²) of 0.9962 on the training set and 0.8892 on the testing set. The corresponding root mean square errors (RMSE) were 0.1012 and 0.6623 for the training and testing sets, respectively. The internal validation coefficient (Q²loo) was 0.8975, while the external validation coefficient (Q²ext) was 0.832. Moreover, the majority of the sample data (approximately 96%) fell within the application domain defined by ±3 times the standard residue-to-critical arm ratio, where h* = 0.2. This demonstrates that the XGBoost model exhibits excellent fitting capability, stability, and predictive power, thereby uncovering a significant nonlinear relationship between the molecular structure of compounds and the PELs. As outlined above, the utilization of the QSAR method for predicting the PELs of hydrocarbons and their oxygen-containing derivatives constitutes a highly effective approach. Full article

Background: Noonan syndrome (NS) is a genetically heterogeneous condition within the RASopathies spectrum, with distinctive craniofacial features, congenital heart defects, short stature, and variably present developmental delay. Most cases result from variants in genes regulating the RAS/MAPK pathway, with PTPN11 variants being the most frequent; the c.922A>G substitution being among the most commonly reported. Methods: This pilot study analyzed clinical and partial genetic features of NS in a cohort from Transylvania, evaluated in the Children’s Emergency Clinical Hospital in Cluj-Napoca. Thirty-one patients fulfilling the Van der Burgt diagnostic criteria (twenty-two males, nine females) were included. Clinical data were systematically reviewed, and targeted molecular testing for the PTPN11 c.922A>G variant was performed. Results: Congenital heart defects were highly prevalent, with pulmonary stenosis representing the most frequent anomaly (54.8%). Craniofacial dysmorphism was observed in 76.7% of cases, cryptorchidism in 50% of the males, and short stature below the third percentile was described in 77.4% of patients. Genetic screening identified the PTPN11 c.922A>G variant in two individuals (6.45%). Additional diagnoses included Williams–Beuren syndrome and a 17q11.2 deletion consistent with Neurofibromatosis–Noonan syndrome, underscoring the clinical and genetic heterogeneity of the cohort. Comparison with international reports highlighted variability in phenotype and variant frequency. Future research directions include Sanger sequencing of key PTPN11 exons and the application of next-generation sequencing targeting all RAS pathway genes. Conclusions: This is the first Romanian cohort study on patients with a clinical suspicion of NS, providing insight into their evaluation. The findings reinforce the need for comprehensive molecular approaches, facilitating diagnostic precision and counseling strategies. Full article

To address the challenge of low modulation recognition accuracy for Low Probability of Intercept (LPI) radar waveforms under low Signal-to-Noise Ratio (SNR) conditions—a critical limitation in current radar signal processing research—this study proposes a novel recognition framework anchored in an improved EfficientNet model. First, to generate time–frequency images, the radar signals are initially subjected to time–frequency analysis using the Choi–Williams Distribution (CWD). Second, the Mobile Inverted Bottle-neck Convolution (MBConv) structure incorporates the Simple Attention Module (SimAM) to improve the network’s capacity to extract features from time–frequency images. Specifically, the original serial mechanism within the MBConv structure is replaced with a parallel convolution and attention approach, further optimizing feature extraction efficiency. Third, the network’s loss function is upgraded to Focal Loss. This modification aims to mitigate the issue of low recognition rates for specific radar signal types during training: by dynamically adjusting the loss weights of hard-to-recognize samples, it effectively improves the classification accuracy of challenging categories. Simulation experiments were conducted on 13 distinct types of LPI radar signals. The results demonstrate that the improved model validates the effectiveness of the proposed approach for LPI waveform modulation recognition, achieving an overall recognition accuracy of 96.48% on the test set. Full article

In this study, we explored the evolution of mechanical properties in hydroxyl-terminated polybutadiene (HTPB) propellants under fatigue loading by performing fatigue tests with varying maximum stresses and cycle numbers, followed by uniaxial tensile tests on post-fatigue specimens. Residual elongation was used as a key parameter to characterize mechanical behavior, while scanning electron microscopy (SEM) provided insights into the mesostructural morphological changes that occur under different loading conditions, revealing the mechanisms responsible for variations in mechanical properties. The results show that, as the number of loading cycles increases, residual elongation decreases, with three distinct phases of decline—slow change, gradual decline, and rapid deterioration—depending on the stress levels. SEM analysis identified damage mechanisms such as “dewetting” and particle fragmentation at the mesostructural level, which compromise the material’s structural integrity, leading to reduced residual elongation. A novel aspect of this study is the application of Williams–Landel–Ferry (WLF) theory to construct a master curve describing residual elongation decay. This approach enabled the development of a generalized model to predict the material’s degradation under fatigue loading, with experimental validation of the fitted evolution model, offering a new and effective method for assessing the long-term performance of HTPB propellants. Full article

Cardiopulmonary bypass (CPB) is one of the most groundbreaking medical innovations in history, enabling safe and effective heart surgery by temporarily replacing the function of the heart and lungs. This review starts with ancient concepts of cardiopulmonary function and then traces the evolution of CPB through important physiological and anatomical discoveries, culminating in the development of the modern heart–lung machine. In addition to examining the contributions of significant figures like Galen, Ibn al-Nafis, William Harvey, and John Gibbon, we also examine the ethical and technical challenges faced in the early days of open heart surgery. Modern developments are also discussed, such as miniature extracorporeal systems, off-pump surgical techniques, and the increasing importance of extracorporeal membrane oxygenation (ECMO) and extracorporeal life support (ECLS), while the evolving role of perfusionists in diverse cardiac teams and the variations in global access to CPB technology are also given special attention. We look at recent advancements in CPB, including customized methods, nanotechnology, artificial intelligence-guided perfusion, and organ-on-chip testing, emphasizing CPB’s enduring significance as a technological milestone and a living example of the cooperation of science, medicine, and human inventiveness because it bridges the gap between the past and the future. Full article

Background/Objectives: Anxiety is a hallmark feature of Williams syndrome (WS), with very high prevalence rates of generalised anxiety disorder (GAD) and specific phobias in both school-aged children and adults, yet a relatively lower prevalence of social phobia. There is very limited research on anxiety in very young children with WS, and no study to date has examined the early prevalence and development of different anxiety disorders in WS. The present research provides a comprehensive assessment of the prevalence and longitudinal profile of anxiety symptomology in very young children with WS. Potential environmental and demographic correlates of anxiety symptomology were also explored. Methods: Participants included 19 young children with WS, aged between 2 and 5 years (at initial testing), who completed a comprehensive developmental assessment. Parents/guardians also completed the Spence Children’s Anxiety Scale (SCAS; Spence, 1997 & Spence et al., 2001), a standardised, psychometrically robust anxiety questionnaire (commonly utilised in research and clinical settings) that measures anxiety symptomology for various anxiety disorders present in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5; American Psychiatric Association, 2013). Results: The present research found anxiety symptomology to be highly prevalent in very young children with WS, particularly GAD and specific phobia. Moreover, the prevalence of anxiety symptomology increased with age and over time, with many children developing comorbid anxiety disorder symptoms approximately 3.5 years later, at Time 2. Chronological age, sex, and developmental/intellectual capabilities were also found to impact on the developmental trajectory of anxiety in young children with WS. Conclusions: The longitudinal findings provide evidence for the contribution of environmental factors on the nature, developmental course, and maintenance of anxiety. Considerable individual variability was apparent, confirming the importance of individual assessments and developing individualised treatment programmes for those with WS. Full article

Bi₆Fe₂Ti₃O₁₈ (BFTO) ceramics were synthesized via a solid-state reaction route using stoichiometric amounts of Bi₂O₃, TiO₂, and Fe₂O₃ powders. A thermal analysis of the powder mixture was conducted to optimize the heat treatment parameters. Energy-dispersive X-ray spectroscopy (EDS) confirmed the conservation of the chemical composition following calcination. Final densification was achieved through hot pressing. The crystal structure of the sintered samples, examined via X-ray diffraction at room temperature, revealed a tetragonal symmetry for BFTO ceramics sintered at 850 °C. Electron backscatter diffraction (EBSD) provided detailed insight into the crystallographic orientation and microstructure. Broadband dielectric spectroscopy (BBDS) was employed to investigate the dielectric response of BFTO ceramics over a frequency range of 10 mHz to 10 MHz and a temperature range of −30 °C to +200 °C. The temperature dependence of the relative permittivity (ε_r) and dielectric loss tangent (tan δ) were measured within a frequency range of 100 kHz to 900 kHz and a temperature range of 25 °C to 570 °C. The impedance data obtained from the BBDS measurements were validated using the Kramers–Kronig test and modeled using the Kohlrausch–Williams–Watts (KWW) function. The stretching parameter (β) ranged from ~0.72 to 0.82 in the impedance formalism within the temperature range from 200 °C to 20 °C. Full article

Isobaric vapor-liquid equilibrium (VLE) data for binary mixtures of biomass–derived ethyl levulinate and ethanol were measured using an apparatus comprising a modified Rose-Williams still and a condensation system. Measurements were taken at temperatures ranging from 329.58 K to 470.00 K and pressures of 40.0, 60.0 and 80.0 kPa. The thermodynamic consistency of the VLE data was evaluated using the Redlich-Kister area test, the Fredenslund test and the Van Ness point-to-point test. The data was correlated using three activity coefficient models: Wilson, NRTL and UNIQUAC. The Gibbs energy of mixing of the VLE data was analyzed to verify the suitability of the binary interaction parameters of these models. The activity coefficients and excess Gibbs free energy, calculated from the VLE experimental data and model correlation results, were analyzed to evaluate the models’ fit and the non–ideality of the binary system. The accuracy of the regression results was also assessed based on the root mean square deviation (RMSD) and average absolute deviation (AAD) for both temperature and the vapor phase mole fraction of ethyl levulinate. The results indicate that the NRTL model provided the best fit to the experimental data. Notably, the experimental data showed strong correlation with the predictions of all three models, suggesting their reliability for practical application. Full article

Addressing the urgent need for lightweight and reusable energy-absorbing materials in aviation impact resistance, this study introduces an innovative multi-directional braided metamaterial design enabled by 4D printing technology. This approach overcomes the dual challenges of intricate manufacturing processes and the limited functionality inherent to traditional textile preforms. Six distinct braided structural units (types 1–6) were devised based on periodic trigonometric functions (Y = A sin(12πX)), and integrated with shape memory polylactic acid (SMP-PLA), thereby achieving a synergistic combination of topological architecture and adaptive response characteristics. Compression tests reveal that reducing strip density to 50–25% (as in types 1–3) markedly enhances energy absorption performance, achieving a maximum specific energy absorption of 3.3 J/g. Three-point bending tests further demonstrate that the yarn amplitude parameter A is inversely correlated with load-bearing capacity; for instance, the type 1 structure (A = 3) withstands a maximum load stress of 8 MPa, representing a 100% increase compared to the type 2 structure (A = 4.5). A multi-branch viscoelastic constitutive model elucidates the temperature-dependent stress relaxation behavior during the glass–rubber phase transition and clarifies the relaxation time conversion mechanism governed by the Williams–Landel–Ferry (WLF) and Arrhenius equations. Experimental results further confirm the shape memory effect, with the type 3 structure fully recovering its original shape within 3 s under thermal stimulation at 80 °C, thus addressing the non-reusability issue of conventional energy-absorbing structures. This work establishes a new paradigm for the design of impact-resistant aviation components, particularly in the context of anti-collision structures and reusable energy absorption systems for eVTOL aircraft. Future research should further investigate the regulation of multi-stimulus response behaviors and microstructural optimization to advance the engineering application of smart textile metamaterials in aviation protection systems. Full article