Search Results (6,973)

Monte Carlo Path Tracing (MCPT) provides highly realistic visualization of biomedical volumes, but its computational cost limits real-time interaction. The Advanced Realistic Rendering Technique (AR²T) adapts MCPT to enable interactive exploration through coarse images generated at low sample counts. This study explores the application of deep learning models for denoising in the early iterations of the AR²T to enable higher-quality interaction with biomedical data. We evaluate five deep learning architectures, both pre-trained and trained from scratch, in terms of denoising performance. A comprehensive evaluation framework, combining metrics such as PSNR and SSIM for image fidelity and tPSNR and LDR-FLIP for temporal and perceptual consistency, highlights that models trained from scratch on domain-specific data outperform pre-trained models. Our findings challenge the conventional reliance on large, diverse datasets and emphasize the importance of domain-specific training for biomedical imaging. Furthermore, subjective clinical assessments through expert evaluations underscore the significance of aligning objective metrics with clinical relevance, highlighting the potential of the proposed approach for improving interactive visualization for analysis of bones, joints, and vessels in clinical and research environments. Full article

Background: Chronic lung allograft dysfunction (CLAD) occurs in up to 50% of patients within the first five years after lung transplantation (LuTX) and represents the main complication and cause of death regarding this surgery. Alveolar septal widening in transbronchial biopsies has shown an association with acute humoral allograft rejection. We aimed to explore histological markers that could predict the development of CLAD before its clinical manifestation. Methods: We retrospectively analyzed transbronchial biopsies taken at three time points from 57 patients who underwent LuTX between February 2010 and July 2019, 26 of whom developed CLAD up to November 2022. The biopsies were analyzed by microscopic morphometry and quantitative reverse transcription PCR to identify predictors of CLAD. Results: CLAD development was associated with increased alveolar septal width (ASW) as early as the first year post-LuTX (5.46 ± 0.76 µm versus 4.59 ± 0.44 µm; p < 0.001). The ASW in later biopsy timepoints predicted survival in multivariate models (last timepoint: hazard ratio 1.885, 95% confidence interval 1.086–3.269). Collagen (COL1A1 and COL3A1) expression was significantly increased in samples from patients who developed CLAD compared with those who did not. The increase in ASW was paralleled by interstitial deposition of COL1A1 and COL3A1 and a decrease in both the carbon monoxide (DLCO) diffusing capacity of the lung and the DLCO/alveolar volume. Conclusions: We report a new histologic approach for early assessment of risk of CLAD in patients who have undergone LuTX. The ASW represents a pre-symptomatic, continuous, and widely distributed change within the lung parenchyma that is accessible to transbronchial biopsy. Full article

Blueberry (Vaccinium spp.) leaves, a residual biomass of pruning, are a rich source of polyphenols, fiber, and minerals. In this study, blueberry leaf powder (BBLP) was incorporated into wheat/soy flour-based cookies to develop antioxidant- and fiber-enriched bakery products. BBLP exhibited 8.2% protein, 44% dietary fiber (predominantly insoluble), and high antioxidant activity (2109 ± 20 mg gallic acid equivalents/100 g sample; 6251 ± 42 µmol Trolox equivalents/100 g). Four cookies’ formulations were prepared by replacing 0%, 2.5%, 5.0%, and 7.5% of the flour blend with BBLP. The total phenolic content, total antioxidant content, physical properties (weight, diameter, thickness, volume, hardness, and color), chemical composition (moisture, ash, minerals, protein, carbohydrate, fat, and fiber content), and sensory properties (taste, texture, aroma, and overall acceptability) were analyzed. All BBLP-enriched cookies qualified as a “source of fiber” according to Codex Alimentarius guidelines and EU Regulation (EC) No 1924/2006 on nutrition and health claims for foods. The addition of BBLP significantly affected the cookies’ diameter, thickness, volume, and hardness, likely due to its high insoluble fiber content. Moreover, as BBLP levels increased, the surface color darkened progressively, with increased redness and decreased yellowness attributed to the presence of anthocyanins. Accordingly, BBLP-enriched cookies showed increased antioxidant capacity, proportional to the amount of BBLP added, indicating good retention of the bioactive compounds after baking. Sensory evaluation using Quantitative Descriptive Analysis revealed that cookies with 2.5% BBLP were rated with the highest acceptability scores, whereas higher concentrations imparted noticeable herbal notes and a darker color, decreasing overall acceptability. In conclusion, BBLP can be effectively incorporated at 2.5% to enhance the nutritional quality and antioxidant potential of cookies without compromising sensory appeal, contributing to sustainable food innovation by valorizing residual agricultural biomass. Full article

The determination of uncertainty in porosity analysis based on X-ray computed tomography (XCT) images is currently the focus of research. This study aims to contribute to that by investigating the variation in porosity analysis resulting only from the segmentation and data analysis and by focusing on metal parts produced by different additive manufacturing processes, partially fabricated with intended porosity. Samples manufactured from aluminum, titanium alloy and nickel-chromium-based feedstock by liquid metal jetting (LMJ), laser-based powder bed fusion (PBF-LB) and directed energy deposition (DED) were scanned by XCT. The reconstructed volumes were distributed to four operators with different experience levels using Avizo, Dragonfly, Image J/Fiji, IPSDK Explorer, and VG Studio Max for porosity analysis. It was found that for all parts, the majority of operators chose a global manual threshold for image segmentation. Depending on the characteristics of the pores in the investigated samples, relative standard uncertainties up to 12% and 38% were observed for the LMJ and PBF-LB parts. For the part produced by DED, which showed the lowest overall porosity, relative standard uncertainties between 70% and 89% were observed for different image qualities; all were affected by the presence of artefacts investigated on purpose. Full article

We investigate the impact of dataset augmentation and synthetic generation techniques on the accuracy of supervised audio classification based on state-of-the-art neural networks used as classifiers. Dataset augmentation techniques are applied upon the raw sound and its transformed image format. Specifically, sound augmentation techniques are applied prior to spectral-based transformation and include time stretching, pitch shifting, noise addition, volume controlling, and time shifting. Image augmentation techniques are applied after the transformation of the sound into a scalogram, involving scaling, shearing, rotation, and translation. Synthetic sound generation is based on the AudioGen generative model, triggered through a series of customized prompts. Augmentation and synthetic generation are applied to three sound categories: (a) human sounds, (b) animal sounds, and (c) sounds of things, with each category containing ten sound classes with 20 samples retrieved from the ESC-50 dataset. Sound- and image-orientated neural network classifiers have been used to classify the augmented datasets and their synthetic additions. VGGish and YAMNet (sound classifiers) employ spectrograms, while ResNet50 and DarkNet53 (image classifiers) employ scalograms. The streamlined AI-based process of augmentation and synthetic generation, enhanced classifier fine-tuning and inference allowed for a consistent, multicriteria-comparison of the impact. Classification accuracy has increased for all augmentation and synthetic generation scenarios; however, the increase has not been uniform among the techniques, the sound types, and the percentage of the training set population increase. The average increase in classification accuracy ranged from 2.05% for ResNet50 to 9.05% for VGGish. Our findings reinforce the benefit of audio augmentation and synthetic generation, providing guidelines to avoid accuracy degradation due to overuse and distortion of key audio features. Full article

Sodium magadiite (Na-Mgd) was hydrothermally prepared and converted to its protonic (H-Mgd) form by reaction with hydrochloric (HCl) solution. The obtained products were studied as adsorbents for basic blue 41 (BB-41) removal from polluted aqueous solution. Na-Mgd and H-Mgd were characterized by different techniques. Powder X-ray (PXRD) diffraction data confirmed a pure Na-Mag phase and its conversion to acidic form (H-Mgd) with shift in d₀₀₁ value from 1.54 nm to 1.12 nm. X-ray fluorescence (XRF) data supported the exchange of Na cations by protons for H-Mag. ²⁹Si magic angle spinning nuclear magnetic resonance (MAS-NMR) indicated a change in the local environment of silicon nucleus when Na-Mgd was treated with HCl solution. The BB-41 removal dyes were investigated throughout the batch process. Effects of selected parameters, for example, the adsorbent dosage, pH of the BB-41 solution, pH of the H-Mag solid, and starting concentration, were explored. The equilibrium data were fitted to the Langmuir and Freundlich isotherm models. The maxima removal capacities of Na-Mgd and H-Mgd were 219 mg/g and 114 mg/g, respectively. The regeneration and reusability tests were performed using initial concentrations of 50 mg/L and 200 mg/L for seven cycles. The efficiency was maintained for 5 to 6 cycles with a decline of 10% using low initial concentration; however, a decline of efficiency to 30 to 50% was achieved when a higher initial concentration was employed after 3 to 4 regeneration tests for Na-Mgd and H-Mgd samples. Adsorber batch design using the Langmuir and Freundlich isotherm parameters was used to predict its performance for commercial usage. The predicted masses of H-Mgd were higher than those of Na-Mgd to treat different effluent volumes contaminated with 200 mg/L of BB-41 dyes at desired removal percentages. Full article

This study evaluates the physical, mechanical, durability, and environmental properties of geopolymer mortars (GMs) produced using waste tire steel fibers (WTSFs), hemp fibers (HFs), waste marble powder (WMP), and recycled fine aggregates (RFAs). Within the scope of this study, fibers were incorporated as single and hybrid types at 0.5% and 1% by volume. The addition of HFs generally reduced dry unit weight, as well as compressive and flexural strength but increased fracture energy by nearly three times. The addition of WTSFs improved compressive and flexural strengths by up to 42% and enhanced fracture energy by 840%. Hybrid fibers increased the strength values by 21% and the fracture energy by up to four times, demonstrating a clear synergistic effect between HFs and WTSFs in enhancing crack resistance and structural stability. In the durability tests conducted within the scope of this study, HFs burnt at 600 °C, while WTSFs showed signs of corrosion under freeze–thaw and acid conditions; however, hybrid fibers combined the benefits of both materials, resulting in an effective preservation of internal structure. The fact that the materials used in the production of GM samples were waste or recycled products reduced the total cost to 188 USD/m³, and thanks to these materials and the carbon-negative properties of HFs, CO₂ emissions were reduced to 338 kg CO₂/m³. The presented study demonstrates the potential of using recycled and waste materials to create sustainable building materials in the construction industry. Full article

Background/Objectives: Voice disorders caused by laryngeal hypertension can impact volume, quality, pitch, resonance, flexibility, and stamina. The laryngeal palpation is a tactile-perceptual assessment, which is one of a few examination methods to evaluate laryngeal hypertension. Laryngeal palpation is a manual examination of the extrinsic and paralaryngeal tissues of the larynx (e.g., lateral laryngeal mobility, thyrohyoid and cricothyroid spaces, vertical laryngeal position/mobility, and pain) through the examiner’s fingers. It can be performed during rest (static assessment) or during phonation (dynamic assessment) of the individual being evaluated. This study aimed to validate a novel laryngeal palpation tool with quantitative ordinal scores by assessing its reliability and diagnostic accuracy establishing preliminary clinical cut-off values, and examining its correlations with self-reported voice disorder symptoms. Methods: In a prospective, controlled validation study, 33 participants were selected to assess the validity and reliability of the novel diagnostic tool in a clinical sample and healthy controls. The clinical sample (n = 19) comprised individuals diagnosed with voice disorders, whereas the healthy control group (n = 14) included participants with no history or symptoms of voice pathology. The novel laryngeal palpation tool was employed by two independent examiners to assess both static and dynamic laryngeal function in all participants. In addition, each participant completed the following questionnaires: Voice Handicap Index (VHI-30) with the 30-item, Vocal Fatigue Index (VFI), and the Vocal Tract Discomfort Scale (VTD). Results: Static palpatory assessment of laryngeal tension demonstrated excellent discriminatory power between groups and tension levels (AROC = 0.979), along with high intra-rater (ICC = 0.966) and inter-rater reliability (ICC = 0.866). Significant correlations were revealed between the static palpation results and the VHI scores (r = 0.496; p < 0.01) and VFI (r = 0.514; p < 0.01). For the dynamic evaluation of the palpation tool, comparable results for the validity (AROC = 0.840) and reliability (inter-rater: ICC = 0.800, and intra-rater: ICC = 0.840) were revealed. However, no significant correlations were found between dynamic palpation and self-perceived questionnaires, although some were likely found with static palpation. The validity of the total score was found to be AROC = 0.992. Conclusions: The static and dynamic assessments using the novel laryngeal palpation tool demonstrated promising reliability and diagnostic accuracy, providing initial evidence to support its clinical utility. Further studies are needed to establish broader validation. Full article

Electroencephalography (EEG) is a non-invasive biosensing platform with a spatial-frequency content that is of significant relevance for a multitude of aspects in the neurosciences, ranging from optimal spatial sampling of the EEG to the design of spatial filters and source reconstruction. In the past, simplified spherical head models had to be used for this analysis. We propose a method for spatial frequency analysis in EEG for realistically shaped volume conductors, and we exemplify our method with a five-compartment Boundary Element Method (BEM) model of the head. We employ the recently developed technique for spatial harmonic analysis (Sphara), which allows for spatial Fourier analysis on arbitrarily shaped surfaces in space. We first validate and compare Sphara with the established method for spatial Fourier analysis on spherical surfaces, discrete spherical harmonics, using a spherical volume conductor. We provide uncertainty limits for Sphara. We derive relationships between the signal-to-noise ratio (SNR) and the required spatial sampling of the EEG. Our results demonstrate that conventional 10–20 sampling might misestimate EEG power by up to 50%, and even 64 electrodes might misestimate EEG power by up to 15%. Our results also provide insights into the targeting problem of transcranial electric stimulation. Full article

An electrochemical aptamer sensor for the sensitive detection of aflatoxin B₁ (AFB₁) in corn samples was developed using nanocomposites loaded with copper nanoparticles (CuNPs) on zeolitic imidazolate framework-8 (ZIF-8), which were modified on a glassy carbon electrode (GCE). The CuNPs@ZIF-8 nanocomposites served as modifying materials for electrodes, exhibiting a high specific surface area and excellent compatibility with aptamers, thereby enhancing the electron transfer rate and increasing the aptamer loading and immobilization efficiency. The electrochemical properties before and after modification were investigated and validated using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques, while the sensor’s performance was analyzed through quantitative detection via differential pulse voltammetry (DPV). Furthermore, various conditions, including the volume of ZIF-8 dispersion, electrodeposition time of copper nanoparticles, aptamer concentration, and AFB₁ incubation time, were optimized. The results indicated that the sensor exhibited a wide linear range (10.0 to 1.0 × 10⁶ pg/mL), with a lower limit of detection (LOD) of 1.13 pg/mL under optimized conditions, outperforming other reported aptamer sensors. The spiked recoveries in corn samples ranged from 96.663% to 105.72%. In conclusion, this sensor presents a novel solution for low-cost and high-sensitivity detection of AFB₁. Full article

Mediterranean rocky reef habitats are ecologically valuable yet increasingly degraded due to cumulative human pressures, necessitating efficient, large-scale ecological status assessments to inform management. Macroalgal communities are widely used as indicators of rocky reef conditions and are typically assessed via photoquadrat sampling. However, the manual annotation of benthic images remains time-consuming and costly. This study evaluates the performance of CoralNet (version 1.0), an AI-assisted image annotation platform, using a pre-annotated dataset of 2537 photoquadrat images from 89 rocky reef sites in the Aegean Sea, Greece, classified into 23 taxonomic and morphofunctional groups. Half of the dataset was used to iteratively train CoralNet classifiers, while the remainder was used to compute the reef-EBQI index and compare ecological status estimates with those derived from manual annotations. The classifier accuracy improved with training volume, reaching 67% using the entire dataset. Reef-EBQI scores derived from CoralNet showed 87% agreement with the manual classifications. Despite challenges and limitations, AI-assisted annotation proved effective in regional-scale ecological assessments based on broad taxonomic and morphofunctional categories. Automated tools like CoralNet can reduce post-processing bottlenecks and enable scalable, cost-effective monitoring, especially when integrated with standardized protocols and citizen science initiatives. Full article

Phosphogypsum represents a gypsum-based solid waste originating from phosphoric acid production, which can be exploited for road filling after cement modification. This study delved into the composition design of high-volume phosphogypsum road base materials, aiming to ascertain their feasibility for subgrade filling, and refine the mix ratio. The main content of phosphogypsum was set at three high-proportion intervals of 86%, 88% and 90%, while the total content of inorganic curing agent was fixed at 0.5% of the total material. Within such a total amount, the proportion of bentonite was preserved at 20%, whereas the proportion of waterproofing agent was configured at three gradients of 20%, 25% and 30%, with the remaining part supplemented by powdered sodium silicate. Merged with trace amounts of inorganic curing agents, particularly the waterproofing agent component, the composite cementitious system comprising cement and ground granulated blast-furnace slag (GGBS) was leveraged to augment the key road performance and water stability of high-volume phosphogypsum-based materials. Material strengths were observed to be distinguishable under an array of phosphogypsum contents, which could be explained by the varying proportions of cement, GGBS and waterproofing agent. The test samples and microscopic products were dissected via XRD and SEM, demonstrating that the hydration products of the materials were predominantly C-S-H gel and ettringite crystals. Full article

Polyhexamethylene guanidine phosphate (PHMG-p), a widely used disinfectant component in household humidifiers, has been implicated in various health issues, including pulmonary toxicity. Many people use humidifiers to improve dry eye disease (DED). The current study was performed to elucidate the effect of PHMG-p on eye dryness in a rat model using metabolomics. Male Sprague Dawley rats were exposed to PHMG-p (0.1% and 0.3%) following a previously established DED induction model using scopolamine hydrobromide and desiccation stress. Ocular surface damage was assessed using corneal fluorescein staining, tear volume measurement, and tear break-up time (TBUT). Plasma and urine samples were analyzed using ¹H-NMR-based metabolomics to identify metabolic alterations associated with PHMG-P-p exposure and DED pathogenesis. PHMG-p exposure exacerbated DED symptoms, as evidenced by a significant reduction in tear volume, shorter TBUT, and increased corneal damage compared to the control group. Metabolomic profiling identified distinct metabolic changes in PHMG-p-exposed groups, including alterations in glutamate, glycine, citrate, and succinate metabolism. These metabolic changes correlated with increased levels of inflammatory cytokines such as IL-1β, IL-6, and TNF-α in the corneal and lacrimal gland tissues. Our findings suggest that PHMG-p exposure contributes to DED pathophysiology by inducing metabolic disturbances and inflammatory responses in the ocular surface. This study highlights the need for further investigation into the potential risks of PHMG-p exposure on ocular health and provides novel insights into the metabolic underpinnings of DED. Full article

Lump charcoal is used in various applications, with combustion performance reliant on physical properties including apparent density. Currently, apparent density is measured by liquid displacement using Archimedes’ principle, which can yield inconsistent results for porous, irregular materials. This study investigates structure-from-motion (SfM) photogrammetry as a non-destructive alternative for estimating the apparent density of lump charcoal. Ninety fragments from 15 commercial samples were analyzed. Mass was measured using an analytical balance, and volume was estimated independently via Archimedes’ method and photogrammetry. Apparent density was calculated as the ratio of mass to volume. Results showed strong agreement between the two methods. Mean density values ranged from 284.2 to 751.6 kg/m³ for photogrammetry and from 267.2 to 765.7 kg/m³ for Archimedes. No significant differences were found (Wilcoxon test, p > 0.05), and a strong correlation was observed (Spearman’s ρ = 0.94, p < 0.001). Photogrammetry also demonstrated low estimation errors, with a mean absolute error of 38.8 kg/m³, a percentage error of 9.9%, and a root mean squared error of 50.2 kg/m³. Beyond methodological innovation, this approach strengthens sustainability by supporting accurate fuel properties control, allowing better use of the resource and maximizes combustion efficiency. In this way, it contributes to United Nations Sustainable Development Goal 7 (SDG7) on affordable, reliable, and sustainable energy. Full article

This work studies yellow pea flour (YPF) fermentation with kefir (1:1.5 mass ratio, incubated 30 h at 25 °C) for gluten-free breadmaking. Three samples were evaluated: untreated YPF, YPF mixed with kefir (UF), and fermented YPF (FF). Structural changes were minimal, but fermentation improved the flour functionality. Bulk density (g/mL) decreased from 0.54 ± 0.02 in YPF and 0.47 ± 0.01 in UF to 0.43 ± 0.01 in FF, while the water absorption capacity (g/g) increased from 1.20 ± 0.01 in YPF and 1.50 ± 0.05 in UF to 1.92 ± 0.02 in FF. YPF showed the lowest oil absorption capacity (0.90 ± 0.02 g/g), while higher values were obtained for FF and UF (averaging 1.54 g/g). The yellowness index showed a clear tendency: higher in UF (34.9 ± 0.2), intermediate in FF (32.869 ± 0.008), and lower in YPF (22.4 ± 0.1). In gluten-free bread, baking loss did not show significant differences between FF-B and UF-B (averaging 15.65%) but they were significantly lower than that of YPF-B (18.5 ± 0.5%). The highest specific volume (mL/g) was observed in FF-B (1.96 ± 0.02), followed by UF-B (1.33 ± 0.02) and YPF-B (1.08 ± 0.02). Significantly reduced “pea” sensory attributes were perceived in FF-B, while acidity perception increased. Hardness was similar among breads, although chewiness was higher in FF-B. These results suggest that kefir fermentation enhances YPF functionality in gluten-free breadmaking. Full article