Search Results (2,049)

Monitoring sediment concentration in water bodies is crucial for assessing water quality, ecosystems, and environmental health. However, physical sampling and sensor-based approaches are labor-intensive and unsuitable for large-scale, continuous monitoring. This study employs machine learning models to estimate suspended sediment concentration using images captured in natural light, named RGB, and near-infrared (NIR) conditions. A controlled dataset of approximately 1300 images with SSC values ranging from 1000 mg/L to 150,000 mg/L was developed, incorporating temperature, time of image capture, and solar irradiance as additional features. Random forest regression and gradient boosting regression were trained on mean RGB values, red reflectance, time of captured, and temperature for natural light images, achieving up to 72.96% accuracy within a 30% relative error. In contrast, NIR images leveraged gray-level co-occurrence matrix texture features and temperature, reaching 83.08% accuracy. Comparative analysis showed that ensemble models outperformed deep learning models like Convolutional Neural Networks and Multi-Layer Perceptrons, which struggled with high-dimensional feature extraction. These findings suggest that using machine learning models and RGB and NIR imagery offers a scalable, non-invasive, and cost-effective way of sediment monitoring in support of water quality assessment and environmental management. Full article

Background/Objectives: This study aimed to investigate the influence of shade and thickness on the polymerization of SDR^® flow+, a low-viscosity bulk-fill composite, by assessing its degree of conversion (DC). Methods: An in vitro study was conducted using SDR^® flow+ composite resin. Specimens were prepared at two thicknesses (2 mm and 4 mm) and four shades (Universal, A1, A2, A3). Polymerization was performed using a high-intensity LED curing unit. The DC was assessed using Fourier-transform infrared spectroscopy (ATR-FTIR). Results: Both shade and thickness significantly influenced DC. Thicker specimens (4 mm) exhibited reduced polymerization compared to thinner specimens (2 mm). Darker shades, particularly A3, demonstrated the lowest DC values due to their higher chroma, which limits light penetration. In contrast, the Universal shade achieved higher DC values, even at increased depths, likely due to its greater translucency. Conclusions: Shade and thickness play a critical role in the polymerization of bulk-fill composites. Ensuring adequate polymerization is essential for the longevity of pediatric restorations. Further in vivo research is needed to confirm these findings and assess their clinical implications. Full article

This study synthesizes and comparatively investigates two squaric acid-based phthalocyanine-like dyes, SNF and its long-chain alkylated derivative LNF, to systematically elucidate the influence of peripheral hydrophobic groups on their third-order nonlinear optical (NLO) properties. The NLO characteristics were comprehensively characterized using femtosecond Z-scan and I-scan techniques at both 800 nm and 900 nm. Both dyes exhibited strong saturable absorption (SA), confirming their potential as saturable absorbers. Critically, the comparative analysis revealed that SNF exhibits a significantly greater nonlinear absorption coefficient (β) compared to LNF under identical conditions. For instance, at 800 nm, the β of SNF was approximately 3–5 times larger than that of LNF. This result conclusively demonstrates that the introduction of long hydrophobic alkyl chains attenuates the NLO response. Furthermore, I-scan measurements revealed excellent SA performance, with high modulation depths (e.g., LNF: 43.0% at 900 nm) and low saturation intensities. This work not only clarifies the structure–property relationship in these D-A-D dyes but also presents a clear strategy for modulating the NLO properties of organic chromophores for applications in near-infrared pulsed lasers. Full article

Background/Objectives: To investigate acute caffeine (CAF: 375 mg, ≈4.8 mg/kg body mass) effects on energy expenditure (EE) and substrate kinetics during high-intensity interval exercise in individuals with high (HBAT) versus low (LBAT) brown adipose tissue activity using time-trend polynomial modeling. Methods: This is a randomized, double-blind crossover study in which 35 highly-trained males [HBAT-CAF, HBAT-PLA (Placebo), LBAT-CAF, LBAT-PLA] performed 30-min treadmill HIIE. Infrared thermography (IRT) assessed BAT activity by measuring supraclavicular skin temperature (SST). Breath-by-breath ergospirometry measured EE (kcal/min) and carbohydrate (CHO), lipid (LIP), and protein (PTN) oxidation. We applied second- and third-order polynomial regression models to depict the temporal trajectories of metabolic responses. Results: HBAT groups showed 25% higher sustained EE versus LBAT (p < 0.001), amplified by CAF. CHO oxidation exhibited biphasic kinetics: HBAT had 40% higher initial rates (0.75 ± 0.05 vs. 0.45 ± 0.04 g/min; p < 0.001) with accelerated decline (k = −0.21 vs. −0.15/min; p = 0.01). LIP oxidation peaked later in LBAT (40 vs. 20 min in HBAT), with CAF increasing oxidation by 18% in LBAT (p = 0.01). HBAT-CAF uniquely showed transient PTN catabolism (peak: 0.045 g/min at 10 min; k = −0.0033/min; p < 0.001). Conclusions: BAT status determines EE magnitude and substrate-specific kinetic patterns, while CAF exerts divergent modulation, potentiating early glycogenolysis in HBAT and lipolysis in LBAT. The HBAT-CAF synergy triggers acute proteolysis, revealing BAT-mediated metabolic switching. Full article

The article is focused on the quantitative assessment of the thermal impact of polar mesospheric clouds (PMCs) on the mesopause caused by the emission of absorbed solar and terrestrial infrared (IR) radiation by cloud particles. For this purpose, a parameterization of mesopause heating by PMC crystals has been developed, the main feature of which is to incorporate the thermal properties of ice and the interaction of cloud particles with the environment. Parametrization is based on PMCs zero-dimensional (0-D) model and uses temperature, pressure, and water vapor data in the 80–90 km altitude range retrieved from Solar Occultation for Ice Experiment (SOFIE) measurements. The calculations are made for 14 PMC seasons in both hemispheres with the summer solstice as the central date. The obtained results show that PMCs can make a significant contribution to the heat balance of the upper atmosphere, comparable to the heating caused, for example, by the dissipation of atmospheric gravity waves (GWs). The interhemispheric differences in heating are manifested mainly in the altitude structure: in the Southern Hemisphere (SH), the area of maximum heating values is 1–2 km higher than in the Northern Hemisphere (NH), while quantitatively they are of the same order. The most intensive heating is observed at the lower boundary of the minimum temperature layer (below 150 K) and gradually weakens with altitude. The NH heating median value is 5.86 K/day, while in the SH it is 5.24 K/day. The lowest values of heating are located above the maximum of cloud ice concentration in both hemispheres. The calculated heating rates are also examined in the context of the various factors of temperature variation in the observed atmospheric layers. It is shown in particular that the thermal impact of PMC is commensurate with the influence of dissipating gravity waves at heights of the mesosphere and lower thermosphere (MLT), which parameterizations are included in all modern numerical models of atmospheric circulation. Hence, the developed parameterization can be used in global atmospheric circulation models for further study of the peculiarities of the thermodynamic regime of the MLT. Full article

Selenium (Se) is an essential trace element involved in antioxidant redox regulation, thyroid hormone metabolism, and cancer prevention. Among its different forms, elemental selenium (Se⁰), particularly at the nanoscale, has gained growing attention in food, feed, and biomedical applications due to its lower toxicity and higher bioavailability compared to inorganic selenium species. However, the detection of Se⁰ in real samples remains challenging as current analytical methods are time-consuming, labour-intensive, and often unsuitable for rapid analysis. In this study, we developed a method for rapidly measuring Se⁰ using carbon nanodots (CNDs) produced from the Maillard reaction between glucose and glycine. The fabricated CNDs were water-dispersible and strongly fluorescent, with an average particle size of 3.90 ± 1.36 nm. Comprehensive characterisation by transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), fluorescence spectroscopy, and Raman spectroscopy confirmed their structural and optical properties. The CNDs were employed as fluorescent probes for the selective detection of Se⁰. The sensor showed a wide linear detection range (0–12.665 mmol L⁻¹), with a low detection limit (LOD) of 0.381 mmol L⁻¹ and a quantification limit (LOQ) of 0.465 mmol L⁻¹. Validation with spiked real samples—including ultra-pure water, tap water, and soft drinks—yielded high recoveries (98.6–108.1%) and low relative standard deviations (<3.4%). These results highlight the potential of CNDs as a simple, reliable, and environmentally friendly sensing platform for trace-level Se⁰ detection in complex food and beverage matrices. Full article

Objective: This study aimed to evaluate the in vitro efficacy of silver nanoparticles (AgNPs) synthesized by bioreduction using lemongrass (Cymbopogon citratus) essential oil against multidrug-resistant (MDR) bacteria isolated from an Intensive Care Unit (ICU). Methods: The essential oil was extracted and characterized by gas chromatography–mass spectrometry (GC-MS). Antioxidant activity was assessed using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay, the 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assay, and total phenolic content. AgNPs (3 mM and 6 mM silver nitrate) were characterized by UV-Vis spectroscopy, dynamic light scattering (DLS), zeta potential, transmission electron microscopy (TEM), and Fourier-transform infrared (FTIR) spectroscopy. Bacterial isolates were obtained from ICU surfaces and personal protective equipment (PPE). Results: The essential oil presented citral A, citral B, and β-myrcene as major components (97.5% of identified compounds). AgNPs at 3 mM showed smaller size (87 nm), lower Polydispersity Index (0.14), and higher colloidal stability (−23 mV). The 6 mM formulation (147 nm; PDI 0.91; −10 mV) was more effective against a strain of Enterococcus spp. resistant to all antibiotics tested. FTIR analysis indicated the presence of O–H, C=O, and C–O groups involved in nanoparticle stabilization. Discussion: The higher antimicrobial efficacy of the 6 mM formulation was attributed to the greater availability of active AgNPs. Conclusions: The green synthesis of AgNPs using C. citratus essential oil proved effective against MDR bacteria and represents a sustainable and promising alternative for microbiological control in healthcare environments. Full article

To enhance the survivability of armed helicopters in high-threat environments, integrated infrared (IR) suppressors are increasingly adopted to reduce thermal signatures. However, such integration significantly alters the exhaust flow field, which may in turn affect both the infrared and acoustic characteristics of the helicopter. This study investigates the aerodynamic, infrared, and acoustic impacts of an integrated IR suppressor through the comparative analysis of two helicopter configurations: a conventional design and a design equipped with an integrated IR suppressor. Full-scale models are used to analyze flow field and IR radiation characteristics, while scaled models are employed for aeroacoustic simulations. The results show that although the integrated IR suppressor increases flow resistance and reduces entrainment performance within the exhaust mixing duct, it significantly improves the thermal dissipation efficiency of the exhaust plume. The infrared radiation analysis reveals that the integrated suppressor effectively reduces radiation intensity in both the 3~5 μm and 8~14 μm bands, especially under cruise conditions where the exhaust is more efficiently cooled by ambient airflow. Equivalent radiation temperatures calculated along principal axes confirm lower IR signatures for the integrated configuration. Preliminary acoustic analyses suggest that the slit-type nozzle and integrated suppressor layout may also offer potential benefits in jet noise reduction. Overall, the integrated IR suppressor provides a clear advantage in lowering the infrared observability of armed helicopters, with acceptable aerodynamic and acoustic trade-offs. These findings offer valuable guidance for the future development of low-observable helicopter platforms. Full article

The objective of this study was to develop a novel sauce formulation in which egg yolk was substituted with pea and soy proteins, in addition to the incorporation of tomato pomace as a functional ingredient. Nine experimental samples (E1–E3, S1–S3, and P1–P3) and three control samples (E0, S0, and P0) were prepared, corresponding to three protein sources (E: egg yolk, S: soy, P: pea), with increasing concentrations of tomato pomace (0, 2, 4, and 6%). The formulations were adjusted proportionally in terms of water and oil to maintain the desired consistency. The analyses performed included: physico-chemical analysis of the sauce (fat content, peroxide value, and CIE L* a* b* color determination), quality assessment using Fourier Transform Infrared Spectroscopy (FT-IR, rheological measurements, and microstructural evaluation. The sample designated P2 demonstrated a notable correlation with favourable parameters, exhibiting intense colouration, elevated protein content, and consistent rheological properties. However, at higher levels of tomato pomace (notably 6%), microstructural instability was observed, which may limit the formulation’s robustness over time. These findings demonstrate that tomato pomace can enhance the functional and structural characteristics of sauce, while also highlighting the importance of optimizing concentration levels to avoid negative impacts on emulsion stability. Overall, the results support the use of tomato pomace and plant proteins in the formulation of sustainable and innovative food products. Full article

The inspection of encapsulated MEMS devices typically relies on destructive methods which compromise the structural integrity of samples. In this work, we present the concept and preliminary experimental validation of a laser scanning setup to non-destructively inspect silicon-encapsulated microstructures by measuring small variations of transmitted light intensity in the near-infrared spectrum. This method does not require any particular sample preparation or damage, and it is based on the higher degree of transparency of silicon in the near-infrared and the transmission contrast resulting from the Fresnel reflections observed at the interfaces between the different materials of the MEMS device layers. We characterise the small feature resolving performance of the laser scanning setup using standard targets, and experimentally demonstrate the inspection of a MEMS latching device enclosed within silicon covers, comparing the contrast measurements with theoretical predictions. Full article

Diffuse Optical Tomography (DOT) is a non-invasive medical imaging technique that makes use of Near-Infrared (NIR) light to recover the spatial distribution of optical coefficients in biological tissues for diagnostic purposes. Due to the intense scattering of light within tissues, the reconstruction process inherent to DOT is severely ill-posed. In this paper, we propose to tackle the ill-conditioning by learning a prior over the solution space using an autoencoder-type neural network. Specifically, the decoder part of the autoencoder is used as a generative model. It maps a latent code to estimated physical parameters given in input to the forward model. The latent code is itself the result of an optimization loop which minimizes the discrepancy of the solution computed by the forward model with available observations. The structure and interpretability of the latent space are enhanced by minimizing the rank of its covariance matrix, thereby promoting more effective utilization of its information-carrying capacity. The deep learning-based prior significantly enhances reconstruction capabilities in this challenging domain, demonstrating the potential of integrating advanced neural network techniques into DOT. Full article

This study evaluated birch and oak ash extracts as alternative extractants for isolating humic substances (HSs) from peat and lignite. The effects of ultrasound intensity, extraction time, and temperature were optimized using a Box–Behnken design and validated statistically. The highest HSs yields were obtained from peat with oak ash extract (pH 13.18), compared to birch ash extract (pH 12.09). Optimal process parameters varied by variant, falling within 309–391 mW∙cm⁻², 116–142 min, and 67–79 °C. HSs extracted under optimal conditions were fractionated into humic acids (HAs) and fulvic acids (FAs), and then analyzed by elemental analysis, Fourier Transform Infrared Spectroscopy (FTIR), and Cross-Polarization Magic Angle Spinning Carbon-13 Nuclear Magnetic Resonance Spectroscopy (CP/MAS ¹³C NMR). The main differences in HSs quality were influenced by raw material and fraction type. However, the use of birch ash extract consistently resulted in a higher proportion of carboxylic structures across all fractions. Overall, wood ash extract, especially from oak, offers a sustainable and effective alternative to conventional extractants, particularly for HSs isolation from lignite. Notably, HSs yield from lignite with oak ash extract (29.13%) was only slightly lower than that achieved with 0.5 M NaOH (31.02%), highlighting its practical potential in environmentally friendly extraction technologies. Full article

Asphalt–rubber binders (A-RBs) have a long and deep history of use; however, little is known regarding the interrelated chemical behaviors and miscibility of rubber with the asphalt fractions [saturates, aromatics, resins, and asphaltenes (SARA)]. This study comprehensively attempted to address this knowledge deficiency by employing Fourier transform infrared spectroscopy (FTIR) to investigate the chemical evolution of A-RBs. A-RB interacted at 190 °C and 3000 min⁻¹ for 8 h was deemed to have the optimal rheological performance. FTIR of the liquid fractions of A-RB 190–3000 showed a prominent chemical shift in the SARA fractions, with new peaks that showed rubber polybutadiene (PB) and polystyrene migration into asphaltenes. Meanwhile, decreases in peaks with C–H aromatic bending and S=O stretching for the A-RB 190–3000 saturates showed that the rubber absorbed low-molecular-weight maltenes during swelling. Peaks associated with C=C aromatic appeared in saturates and aromatics, respectively, emphasizing that unsaturated components migrated from the rubber into the asphalt. Thermal analysis showed that rubber dissolution for this sample reached 82%. While a PB peak existed in asphaltenes of A-RB 220–3000, its intensity was diminished by depolymerization, thus compromising the integrity of the migrated rubber structure and generating less rheological enhancement. This study concludes that FTIR characterization of SARA fractions offers valuable insights into the interactions between asphalt and rubber, and that regulated processing conditions are essential for enhancing binder performance. Full article

This work explores zinc oxide nanoparticle (ZnO NP) synthesis utilizing leaf extract of the Gaultheria fragrantissima plant that are useful in medicine, environmental remediation, and cosmetics due to their antibacterial activity, photocatalytic efficiency, and UV-blocking characteristics. Traditional synthesis methods involve energy-intensive procedures and hazardous chemicals, posing environmental and human health risks. To overcome these limitations, this research focuses on utilizing G. fragrantissima, rich in bioactive compounds such as phenolics and flavonoids, with the methyl salicylate previously reported in the literature for this species, which helps reduce and stabilize NPs. ZnO NPs were characterized through X-ray diffraction (XRD), UV–visible spectroscopy, Fourier transform infrared (FTIR) spectroscopy, field emission scanning electron microscopy (FESEM), and energy-dispersive spectroscopy (EDS). The ZnO NPs were found to have a well-defined crystalline structure, with their average crystallite size measured at around 8.26 nm. ZnO NPs exhibited moderate antimicrobial activity against selected microbial strains. These findings underscore the potential of G. fragrantissima-mediated synthesis as an environmentally sustainable and efficient method for producing ZnO NPs with multifunctional applications. This study provides a greener alternative to conventional synthesis approaches, demonstrating a method that is both eco-friendly and capable of yielding NPss with desirable properties. Full article