Search Results (492)

Petrochemical complexes are spatially expansive and host diverse emission sources, making accurate monitoring of volatile organic compounds (VOCs) challenging using conventional two-dimensional methods. This study introduces Mobile-extraction Differential Optical Absorption Spectroscopy (Me-DOAS), a real-time, three-dimensional remote sensing technique for assessing benzene emissions in the Ulsan petrochemical complex, South Korea. A vehicle-mounted Me-DOAS system conducted monthly measurements throughout 2024, capturing data during four daily intervals to evaluate diurnal variation. Routes included perimeter loops and grid-based transects within core industrial zones. The highest benzene concentrations were observed in February (mean: 64.28 ± 194.69 µg/m³; geometric mean: 5.13 µg/m³), with exceedances of the national annual standard (5 µg/m³) in several months. Notably, nighttime and early morning sessions showed elevated levels, suggesting contributions from nocturnal operations and meteorological conditions such as atmospheric inversion. A total of 179 exceedances (≥30 µg/m³) were identified, predominantly in zones with benzene-handling activities. Correlation analysis revealed a significant relationship between high concentrations and specific emission sources. These results demonstrate the utility of Me-DOAS in capturing spatiotemporal emission dynamics and support its application in exposure risk assessment and industrial emission control. The findings provide a robust framework for targeted management strategies and call for integration with source apportionment and dispersion modeling tools. Full article

Background: Crystalline glucosamine sulfate (cGS) claims to be a stabilized form of glucosamine sulfate with a defined crystalline structure intended to enhance chemical stability. It is proposed to offer pharmacokinetic advantages over regular glucosamine sulfate (rGS) which is stabilized with potassium or sodium chloride. However, comparative human bioavailability data are limited. Since both forms dissociate in gastric fluid into constituent ions, the impact of cGS formulation on absorption remains uncertain. This pilot study aimed to compare the bioavailability of cGS and rGS using a randomized, double-blind, crossover design. Methods: Ten healthy adults received a single 1500 mg oral dose of either cGS or rGS with a 7-day washout between interventions. Capillary blood samples were collected over 24 h. Glucosamine and its metabolite concentrations were quantified by Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS), and pharmacokinetic parameters—including maximum concentration (C_max), time to reach C_max (T_max), and area under the curve (AUC)—were calculated. Results: Mean AUC_0–24, C_max, T_max, and T_½ values for glucosamine and glucosamine-6-sulfate (GlcN-6-S) were comparable between cGS and rGS. Although the AUC_0–24 for glucosamine was modestly higher with rGS (18,300 ng·h/mL) than with cGS (12,900 ng·h/mL), the difference was not statistically significant (p = 0.136). GlcN-6-S exposure was also similar between formulations (rGS: 50,700 ng·h/mL; cGS: 50,600 ng·h/mL), with a geometric mean ratio of 1.39, a delayed T_max (6–8 h) and longer half-life, consistent with its role as a downstream metabolite. N-acetylglucosamine levels remained stable, indicating potential homeostatic regulation. Conclusions: This pilot study found no significant pharmacokinetic advantage of cGS over rGS. These preliminary findings challenge claims of cGS’ pharmacokinetic superiority, although the small sample size limits definitive conclusions. Larger, adequately powered studies are needed to confirm these results. Full article

Soil available nitrogen (AN) is a critical nutrient for plant absorption and utilization. Accurately mapping its spatial distribution is essential for improving crop yields and advancing precision agriculture. In this study, 188 AN soil samples (0–20 cm) were collected at Heshan Farm, Nenjiang County, Heihe City, Heilongjiang Province, in 2023. The soil available nitrogen content ranged from 65.81 to 387.10 mg kg⁻¹, with a mean value of 213.85 ± 61.16 mg kg⁻¹. Sentinel-2 images and normalized vegetation index (NDVI) and enhanced vegetation index (EVI) time series data were acquired on the Google Earth Engine (GEE) platform in the study area during the bare soil period (April, May, and October) and the growth period (June–September). These remote sensing variables were combined with soil sample data, crop type information, and crop growth period data as predictive factors and input into a Random Forest (RF) model optimized using the Optuna hyperparameter tuning algorithm. The accuracy of different strategies was evaluated using 5-fold cross-validation. The research results indicate that (1) the introduction of growth information at different growth periods of soybean and maize has different effects on the accuracy of soil AN mapping. In soybean plantations, the introduction of EVI data during the pod setting period increased the mapping accuracy R² by 0.024–0.088 compared to other growth periods. In maize plantations, the introduction of EVI data during the grouting period increased R² by 0.004–0.033 compared to other growth periods, which is closely related to the nitrogen absorption intensity and spectral response characteristics during the reproductive growth period of crops. (2) Combining the crop types and their optimal period growth information could improve the mapping accuracy, compared with only using the bare soil period image (R² = 0.597)—the R² increased by 0.035, the root mean square error (RMSE) decreased by 0.504%, and the mapping accuracy of R² could be up to 0.632. (3) The mapping accuracy of the bare soil period image differed significantly among different months, with a higher mapping accuracy for the spring data than the fall, the R² value improved by 0.106 and 0.100 compared with that of the fall, and the month of April was the optimal window period of the bare soil period in the present study area. The study shows that when mapping the soil AN content in arable land, different crop types, data collection time, and crop growth differences should be considered comprehensively, and the combination of specific crop types and their optimal period growth information has a greater potential to improve the accuracy of mapping soil AN content. This method not only opens up a new technological path to improve the accuracy of remote sensing mapping of soil attributes but also lays a solid foundation for the research and development of precision agriculture and sustainability. Full article

Accurate and rapid aquatic organism recognition is a core technology for fisheries automation and aquatic organism statistical research. However, due to absorption and scattering effects, images of aquatic organisms often suffer from poor contrast and color distortion. Additionally, the clustering behavior of aquatic organisms often leads to occlusion, further complicating the identification task. This study proposes a lightweight object detection model, Mobile-YOLO, for the recognition of four representative aquatic organisms, namely holothurian, echinus, scallop, and starfish. Our model first utilizes the Mobile-Nano backbone network we proposed, which enhances feature perception while maintaining a lightweight design. Then, we propose a lightweight detection head, LDtect, which achieves a balance between lightweight structure and high accuracy. Additionally, we introduce Dysample (dynamic sampling) and HWD (Haar wavelet downsampling) modules, aiming to optimize the feature fusion structure and achieve lightweight goals by improving the processes of upsampling and downsampling. These modules also help compensate for the accuracy loss caused by the lightweight design of LDtect. Compared to the baseline model, our model reduces Params (parameters) by 32.2%, FLOPs (floating point operations) by 28.4%, and weights (model storage size) by 30.8%, while improving FPS (frames per second) by 95.2%. The improvement in mAP (mean average precision) can also lead to better accuracy in practical applications, such as marine species monitoring, conservation efforts, and biodiversity assessment. Furthermore, the model’s accuracy is enhanced, with the mAP increased by 1.6%, demonstrating the advanced nature of our approach. Compared with YOLO (You Only Look Once) series (YOLOv5-12), SSD (Single Shot MultiBox Detector), EfficientDet (Efficient Detection), RetinaNet, and RT-DETR (Real-Time Detection Transformer), our model achieves leading comprehensive performance in terms of both accuracy and lightweight design. The results indicate that our research provides technological support for precise and rapid aquatic organism recognition. Full article

Time-domain (TD) diffuse reflectance can be modeled using diffusion theory (DT) to non-invasively estimate optical transport coefficients of biological media, which serve as markers of tissue physiology. We employ an optimized N-layer DT solver in cylindrical geometry to reconstruct optical coefficients of bilayered media from TD reflectance generated via Monte Carlo (MC) simulations. Optical properties for 384 bilayered tissue models representing human head or limb tissues were obtained from the literature at three near-infrared wavelengths. MC data were fit using the layered DT model to simultaneously recover transport coefficients in both layers. Bottom-layer absorption was recovered with errors under 0.02 cm⁻¹, and top-layer scattering was retrieved within 3 cm⁻¹ of input values. In contrast, recovered bottom-layer scattering had mean errors exceeding 50%. Total hemoglobin concentration and oxygen saturation were reconstructed for the bottom layer to within 10 μM and 5%, respectively. Extracted transport coefficients were significantly more accurate when obtained using layered DT compared to the conventional, semi-infinite DT model. Our results suggest using improved theoretical modeling to analyze TD reflectance analysis significantly improves recovery of deep-layer absorption. Full article

Land surface emissivity (LSE) is the most critical factor affecting land surface temperature (LST) retrieval. Understanding its variation characteristics is essential, as this knowledge provides fundamental prior constraints for the LST retrieval process. This study utilizes thermal infrared emissivity and hyperspectral data collected from diverse underlying surfaces from 2017 to 2024 to analyze LSE variation characteristics across different surface types, spectral bands, and temporal scales. Key influencing factors are quantified to establish empirical relationships between LSE dynamics and environmental variables. Furthermore, the impact of LSE models on diurnal LST retrieval accuracy is systematically evaluated through comparative experiments, emphasizing the necessity of integrating time-dependent LSE corrections into radiative transfer equations. The results indicate that LSE in the 8–11 µm band is highly sensitive to surface composition, with distinct dual-valley absorption features observed between 8 and 9.5 µm across different soil types, highlighting spectral variability. The 9.6 µm LSE exhibits strong sensitivity to crop growth dynamics, characterized by pronounced absorption valleys linked to vegetation biochemical properties. Beyond soil composition, LSE is significantly influenced by soil moisture, temperature, and vegetation coverage, emphasizing the need for multi-factor parameterization. LSE demonstrates typical diurnal variations, with an amplitude reaching an order of magnitude of 0.01, driven by thermal inertia and environmental interactions. A diurnal LSE retrieval model, integrating time-averaged LSE and diurnal perturbations, was developed based on underlying surface characteristics. This model reduced the root mean square error (RMSE) of LST retrieved from geostationary satellites from 6.02 °C to 2.97 °C, significantly enhancing retrieval accuracy. These findings deepen the understanding of LSE characteristics and provide a scientific basis for refining LST/LSE separation algorithms in thermal infrared remote sensing and for optimizing LSE parameterization schemes in land surface process models for climate and hydrological simulations. Full article

Background: Silymarin, a flavonoid complex, and the main bioactive component of milk thistle (Silybum marianum), is known for its hepatoprotective properties but suffers from poor bioavailability due to its low solubility and extensive first-pass metabolism. Method: This study aimed to evaluate the pharmacokinetics and tolerability of a novel micellar milk thistle formulation designed to enhance silymarin absorption, compared to an unformulated/standard milk thistle product, in a small-scale human bioavailability trial. In a randomized, double-blinded, crossover study, 16 healthy participants received a single dose of either the micellar formulation (LipoMicel Milk Thistle; LMM) or the standard formulation (STD) at a total daily dose of 130 mg silymarin. Blood concentrations were measured over 24 h, and key pharmacokinetic parameters—maximum plasma concentration (C_max), time to reach maximum concentration (T_max), and area under the curve (AUC)—were calculated. Tolerability and safety were assessed through adverse event monitoring during the study period. Results: Results demonstrated a significant increase in bioavailability with the micellar formulation, with 18.9-fold higher C_max (95% CI: 1.9–30.7 ng/mL vs. 74.4–288.3 ng/mL; p = 0.007) and 11.4-fold higher AUC_0–24 (95% CI: 7.40–113.5 ng·h/mL vs. 178–612.5 ng·h/mL; p = 0.015). T_max was 0.5 (95% CI: 0.5–4.0) hours for the micellar formulation versus 2.5 (95% CI: 0.5–8.0) hours for the standard product (p = 0.015) indicating faster absorption of LMM. The standard formulation exhibited a significantly longer mean residence time compared to the LMM formulation (95% CI: 4.4–7.5 h vs. 2.8–4.2 h; p = 0.015). Conclusions: No adverse events or significant safety concerns were observed in either group. Compared to the standard, the micellar formulation showed superior pharmacokinetic outcomes, suggesting it may enhance silymarin’s clinical efficacy in liver health. Full article

In this paper, we experimentally investigated the excitation of spoof surface plasmon polaritons (SSPPs) supported by a 1D subwavelength grating with a rectangular profile in the terahertz (THz) frequency range. Using the attenuated total reflection technique and the THz radiation of the Novosibirsk free electron laser, we carried out detailed studies of both angular and gap spectra at several wavelengths. A shallow grating supporting a fundamental mode was fabricated by means of multibeam X-ray lithography and used as a test sample. The results indicated that we achieved 1-THz tunability of resonance in the frequency range from 1.51 to 2.54 THz on a single grating, which cannot be obtained with active tunable metamaterials. The Q factors of the resonances in the angular spectra were within the range of 19.4–37.6, while the resonances of the gap spectra had a Q factor lying within the 1.17–2.03 range. The gap adjustment capability of the setup shown in the work has great potential in modulation of the absorption efficiency, whereas the angular tuning and recording data from each point of the grating will enable real-time monitoring of changes in the surrounding medium. All of this is highly important for enhanced terahertz real-time absorption spectroscopy and imaging. Full article

Background/Objectives: Jaspine B, a synthetic analog of anhydrophytosphingosine, demonstrates significant anticancer activity; however, its clinical application is hindered by its poor oral bioavailability, resulting in suboptimal systemic exposure. This study aimed to enhance the pharmacokinetic properties of Jaspine B by developing a liposomal delivery system. Methods: Jaspine B-loaded liposomes were formulated using a microfluidic approach and characterized by transmission electron microscopy (TEM) to assess particle morphology and size distribution. A sensitive and selective LC-MS/MS assay was developed and fully validated to quantify Jaspine B in rat plasma. The assay revealed excellent linearity across a broad concentration range and high intra- and inter-day precision. A pharmacokinetic study was conducted in Sprague Dawley rats to evaluate the influence of liposomal encapsulation on the pharmacokinetic profile of Jaspine B. Results: The liposomal formulation accelerated the absorption of Jaspine B, reaching the maximum concentration (T_max) at 2 h as opposed to 6 h in plain Jaspine B. The half-life (t_1/2) increased significantly from 7.9 ± 2.3 h to 26.7 ± 7.3 h. The area under the curve (AUC_0–∞) increased over two-fold from 56.8 ± 12.3 ng.h/mL to 139.7 ± 27.2 ng.h/mL, suggesting increased systemic drug exposure. Similarly, the drug molecule’s mean residence time (MRT) increased over three-fold. Conclusions: These results indicate that liposomal formulation enhances the pharmacokinetics of Jaspine B, prolonging its body circulation and exposure, which explains the improved therapeutic outcomes we observed in our previous pharmacodynamic study. Full article

The SPICAV IR spectrometer aboard the Venus Express orbiter measured spectra of the 1.1 and 1.18 μm atmospheric transparency windows at the Venus night side in 2006–2014. The long-term measurements encompassed the major part of the Venus globe, including polar latitudes. For the first time, the H₂O volume mixing ratio in the deep Venus atmosphere at about 10–16 km has been retrieved for the entire SPICAV IR dataset using a radiative transfer model with multiple scattering. The retrieved H₂O volume mixing ratio is found to be sensitive to different approximations of the H₂O and CO₂ absorption lines’ far wings and assumed surface emissivity. The global average of the H₂O abundance retrieved for different parameters ranges from 23.6 ± 1.0 ppmv to 27.7 ± 1.2 ppmv. The obtained values are consistent with recent studies of water vapor below the cloud layer, showing the H₂O mixing ratio below 30 ppmv. Within the considered dataset, the zonal mean of the H₂O mixing ratio does not vary significantly from 60° S to 75° N, except for a 2 ppmv decrease noted at high latitudes. The H₂O local time distribution is also uniform. The 8-year observation period revealed no significant long-term trends or periodicities. Full article

In this study, a boron-doped diamond (BDD) sensor was used to study the electroanalytical behavior of emerging contaminants (ECs), such as caffeine, paracetamol and methyl orange. BDD shows strong resolving power for the superimposed voltammetric response of ECs in well-resolved peaks with increased peak current. Differential pulse voltammetry, which is an electroanalytical technique, was compared with two reference techniques including absorption spectrophotometry in the UV-vis region and high-performance liquid chromatography (HPLC) in the detection and quantification of ECs. The results obtained were satisfactory, as the complete removal of ECs was achieved in all applied processes. The detection limits were 0.69 mg L⁻¹, 0.84 mg L⁻¹ and 0.46 mg L⁻¹ for CAF, PAR and MO, respectively. The comparison of electroanalysis results with those obtained by UV-vis and HPLC established and confirmed the potential applicability of the technique for determining CAF, PAR and MO analytes in synthetic effluents and environmental water samples (tap water, groundwater and lagoon water). The electrochemical approach can therefore be highlighted for its low consumption of reagents, ease of operation, time of analysis and excellent precision and accuracy, because these are characteristics that enable the use of this technique as another means of determining analytes in effluents. Full article

Near-infrared (NIR) rhodamine dyes are pivotal for bioimaging due to the minimal tissue interference. Yet, their rational design is hindered by unreliable computational methods for excited-state property prediction. We benchmarked the time-dependent density functional theory (TDDFT) with the linear-response (LR) and state-specific (SS) solvation models across five functionals (CAM-B3LYP, M06-2X, ωB97X-D, B3LYP, MN15) and optimized the ground/excited states for 42 rhodamine derivatives. A robust linear calibration framework was established by connecting the computed and experimental wavelengths, which was rigorously validated through six-fold cross-validation. The key metrics included the mean absolute error (MAE) and R² to assess the prediction robustness. CAM-B3LYP combined with LR solvation achieved the highest accuracy (absorption: MAE = 6 nm, R² = 0.94; emission: MAE = 12 nm, R² = 0.72). By integrating the TDDFT with a calibrated linear-response solvation model, we achieved sub-12 nm accuracy in predicting the NIR fluorescence peaks. This framework enabled the rational design of nine novel rhodamine derivatives with emissions beyond 700 nm, offering a paradigm shift in bioimaging probe development. Full article

Recycling in the construction industry is a necessity, not just a fashionable trend in scientific research. The use of coal slag aggregates in concrete means a significant reduction in environmental footprint and should be a priority. For these reasons, this study presents tests of the physical and mechanical properties of high-performance concrete (HPC) with coal slag (CS) used as a replacement for natural coarse aggregate in the amounts of 10%, 20%, and 30% after a long curing time. The investigation determined the porosity, water absorption, density, compressive strength, flexural strength, tensile splitting strength, modulus of elasticity, and ultrasonic pulse velocity (UPV), and analyzed HPC microstructure at 28, 56 days, as well as 2 years of maturation. The use of coal slag resulted in significant increases in compressive strength, flexural strength, and tensile splitting strength compared to reference concrete. However, for HPC with CS, a slight decrease in the elastic modulus and UPV was obtained. The SEM analysis showed a very good adhesion of the cement paste to the slag aggregate. In general, research shows that it is possible to obtain durable high-performance concrete with a 30% replacement of natural aggregate by coal slag. Full article

Towards the bioremediation of toxic compounds from aquatic environments using living microalgae, Chlorella vulgaris has emerged as a promising candidate for the removal of heavy metals. The present study advances the scale-up of the microalga’s culture and investigates its efficiency in multi-metal removal (Cu, Cd, Ni, Pb, and Zn at 1 ppm each). Two aeration conditions were investigated: standard/conventional aeration (SA), and an innovative, custom-built micro-bubble aeration (MBA), which optimizes CO₂ residence time to enhance photosynthesis. Conducted in a pilot-scale 30 L photobioreactor (PBR) over a cultivation period of 7 days, control and multi-metal treated cultures were monitored for pH, cell population growth, and pigment content. Heavy metal removal efficiency was evaluated by means of atomic absorption spectroscopy (AAS) on Days 3 and 7 of cultivation. The comparative results reveal that MBA significantly enhances both the population and the photosynthetic pigment content of the cultures. Furthermore, the heavy metal removal efficiency under MBA reached up to 95% even by Day 3 of cultivation, remarkably higher than the 67% of the SA treated culture. These findings not only demonstrate Chlorella vulgaris’s effectiveness in multi-metal treated systems but also highlight the potential of advanced aeration systems to enhance bioremediation efficiency in larger-scale aquatic environments. Full article

Background/Objectives: This paper describes the use of physiologically based biopharmaceutics modelling (PBBM) to predict the effect of food on diclofenac and ibuprofen absorption from ultra-rapid-release Surge Dose^® tablets. Methods: Fasted-state diclofenac pharmacokinetics (PK) were used with published IV data and biorelevant dissolution data for the diclofenac tablets to develop a mechanistic PBBM model which could be used to predict absorption. Results: The resultant model that best fitted the PK data showed that, in vivo, the ultra-rapid-release tablets behaved like a solution with a median time to peak plasma concentration (T_max) of 20 min. Incorporating a well-established model for gastric emptying in the fed state, the fed T_max for these tablets was predicted to be 21 min, similar to that seen in fasted subjects. Use of a PBBM model to predict absorption of ibuprofen in the fasted and fed states again showed that ultra-rapid-release tablets produced fast and consistent absorption independent of the presence of food. Predicted mean T_max values were 31.8 and 35.4 min in the fasted and fed states, respectively. Conclusions: Therefore, even if Surge Dose^® formulations are taken after food, as frequently recommended for NSAIDs, the speed of absorption and subsequent onset of action should not be impacted. Full article