Search Results (247)

Avocado (Persea americana), originally from Mesoamerica, has emerged as a focus of intense scientific and industrial interest due to its unique combination of nutritional richness, bioactive potential, and technological versatility. Its pulp, widely consumed across the globe, is notably abundant in monounsaturated fatty acids, especially oleic acid, which can comprise over two-thirds of its lipid content. In addition, it provides significant levels of dietary fiber, fat-soluble vitamins such as A, D, E and K, carotenoids, tocopherols, and phytosterols like β-sitosterol. These constituents are consistently associated with antioxidant, anti-inflammatory, glycemic regulatory, and cardioprotective effects, supported by a growing body of experimental and clinical evidence. This review offers a comprehensive and critical synthesis of the chemical composition and functional properties of avocado, with particular emphasis on its lipid profile, phenolic compounds, and phytosterols. It also explores recent advances in environmentally sustainable extraction techniques, including ultrasound-assisted and microwave-assisted processes, as well as the application of natural deep eutectic solvents. These technologies have demonstrated improved efficiency in recovering bioactives while aligning with the principles of green chemistry. The use of avocado-derived ingredients in nanostructured delivery systems and their incorporation into functional foods, cosmetics, and health-promoting formulations is discussed in detail. Additionally, the potential of native cultivars and the application of precision nutrition strategies are identified as promising avenues for future innovation. Taken together, the findings underscore the avocado’s relevance as a high-value matrix for sustainable development. Future research should focus on optimizing extraction protocols, clarifying pharmacokinetic behavior, and ensuring long-term safety in diverse applications. Full article

This study evaluates machine learning-based methods for retrieving thin Arctic sea ice thickness (SIT) from L-band radiometry, using data from the European Space Agency’s (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite. In addition to the operational ESA product, three alternative approaches are assessed: a Random Forest (RF) algorithm, a Convolutional Neural Network (CNN) that incorporates spatial coherence, and a Long Short-Term Memory (LSTM) neural network designed to capture temporal coherence. Validation against in situ data from the Beaufort Gyre Exploration Project (BGEP) moorings and the ESA SMOSice campaign demonstrates that the RF algorithm achieves robust performance comparable to the ESA product, despite its simplicity and lack of explicit spatial or temporal modeling. The CNN exhibits a tendency to overestimate SIT and shows higher dispersion, suggesting limited added value when spatial coherence is already present in the input data. The LSTM approach does not improve retrieval accuracy, likely due to the mismatch between satellite resolution and the temporal variability of sea ice conditions. These results highlight the importance of L-band sea ice emission modeling over increasing algorithm complexity and suggest that simpler, adaptable methods such as RF offer a promising foundation for future SIT retrieval efforts. The findings are relevant for refining current methods used with SMOS and for developing upcoming satellite missions, such as ESA’s Copernicus Imaging Microwave Radiometer (CIMR). Full article

Snow plays a crucial role in global climate regulation, hydrological processes, and environmental change, making the accurate acquisition of snow depth data highly significant. In this study, we used Sentinel-1 radar data and employed a simulated annealing algorithm to select the optimal influencing factors from radar backscatter characteristics and spatiotemporal geographical parameters within the study area. Snow depth retrieval was subsequently performed using both random forest (RF) and Support Vector Machine (SVM) models. The retrieval results were validated against in situ measurements and compared with the long-term daily snow depth dataset of China for the period 2017–2019. The results indicate that the RF model achieves better agreement with the measured data than existing snow depth products. Specifically, in the Xinjiang region, the RF model demonstrates superior performance, with an R² of 0.92, a root mean square error (RMSE) of 2.61 cm, and a mean absolute error (MAE) of 1.42 cm. In contrast, the SVM regression model shows weaker agreement with the observations, with an R² lower than that of the existing snow depth product (0.51) in Xinjiang, and it performs poorly in other regions as well. Overall, the SVM model exhibits deficiencies in both predictive accuracy and spatial stability. This study provides a valuable reference for snow depth retrieval research based on active microwave remote sensing techniques. Full article

Quantifying long-term variations in the cloud liquid water path (LWP) is crucial to obtain a better understanding of the processes relevant to cloud–climate feedback. The 12-year (2013–2024) time series of LWP values obtained from ground-based measurements by the RPG-HATPRO radiometer near the Gulf of Finland is analysed, and the linear trends of the LWP for different sampling subsets of data are assessed. These subsets include all-hour, daytime, and night-time measurements. Two different approaches have been used for trend assessment, which produced similar results. Statistically significant linear trends have been detected for most data subsets. The most pronounced general trend over the period 2013–2024 has been detected for the daytime LWP, and it constitutes −0.0011 ± 0.00015 kg m⁻² yr⁻¹. This trend is driven mainly by the daytime LWP trend for the warm season (May–July, −0.0014 ± 0.00015 kg m⁻² yr⁻¹), which is considerably larger than the trend for the cold season (November–January, −0.00064 ± 0.00026 kg m⁻² yr⁻¹). Additionally, the analysis shows that the absolute number of clear-sky measurements decreased approximately by a factor of 4 if the years 2013 and 2024 are compared. Full article

We present the validation of the latest version F Geophysical Data Records (GDR-F) for the TOPEX/POSEIDON (T/P) altimetry satellite mission. The GDR-F products represent a major evolution with respect to the preceding version B Merged Geophysical Data Records (MGDR-B) that were released more than two decades ago. Specifically, the numerical retracking of the altimeter waveforms significantly mitigates long-standing issues in the TOPEX altimeter measurements, such as drifts and hemispherical biases in the altimeter range and significant wave height. Additionally, GDR-F incorporates updated geophysical model standards consistent with current altimeter missions, improved sea state bias corrections, end-of-mission calibration for the microwave radiometer, and refined orbit ephemeris solutions. These enhancements notably decrease the variance of the Sea Surface Height Anomaly (SSHA) measurements, with along-track SSHA variance reduced by 26 cm² compared to MGDR-B and crossover SSHA variance lowered by 1 cm². GDR-F products also demonstrate improved consistency with Jason-1 measurements during their tandem mission phase, reducing the standard deviation of differences from 6 cm to 4 cm when compared to Jason-1 GDR-E data. These results confirm that GDR-F products offer a more accurate and consistent T/P data record, enhancing the quality of long-term sea level studies and supporting inter-mission altimetry continuity. Full article

Measuring pH is a critical parameter in environmental monitoring, biomedical diagnostics, food safety, and industrial processes. Optical fiber sensors have proven highly effective for pH detection due to their exceptional sensitivity, rapid response, and resistance to electromagnetic interference, making them well suited for real-time monitoring. This review offers a comprehensive analysis of recent advances in optical fiber-based pH sensors, covering key techniques such as fluorescence-based, absorbance-based, evanescent wave, and interferometric methods. Innovations in Fiber Bragg Grating and Surface Plasmon Resonance technologies are also examined. The discussion extends to the impact of pH-sensitive coatings—ranging from nanomaterials and polymeric films to graphene-based compounds—on enhancing sensor performance. Recent advancements have also enabled automation in data analysis and improvements in remote sensing capabilities. The review further compares the economic viability of optical fiber sensors with traditional electrochemical methods, while acknowledging persistent issues such as temperature cross-sensitivity, long-term stability, and fabrication costs. Overall, recent developments have broadened the functionality and application scope of these sensors by improving efficiency, accuracy, and scalability. Future research directions are outlined, including advanced optical interrogation techniques, such as Addressed Fiber Bragg Structures (AFBSs), microwave photonic integration, and optimized material selection. These approaches aim to enhance performance, reduce costs, and enable the broader adoption of optical fiber pH sensors. Full article

Cigarette smoking exposes individuals to numerous toxic substances, including heavy metals. Smokers are at risk due to the accumulation of these substances in various tissues. Objective: To compare the concentrations of 41 elements in 11 brain regions, the spinal cord, the bronchial, the lungs, and the liver in smokers (n = 11) and non-smokers (n = 17). Elemental composition was determined by ICP-MS after wet digestion in a microwave system. The following toxic elements were detected at levels of µg/g w.w.: Al, Cd, Pb, Ba, As, Ni, and Tl. Significantly higher concentrations of Al were detected in bronchial and lung, and more Pb, Tl, and rare earth elements were detected in the liver of smokers compared to non-smokers. In addition, smokers had significantly lower concentrations of essential elements involved in antioxidant defense, such as Cu, in liver tissue (p = 0.033). The brain and spinal cord in smokers and non-smokers were similar in terms of chemical composition, except the insula, where smokers had greater Al accumulation (p = 0.030), the precentral gyrus, where higher amounts of As, Cd, and Mn were detected, and the septal nucleus accumbens, which preferentially accumulated Cd in smokers; however, the p-values indicate that these differences were not statistically significant. Most brain areas of smokers were characterized by higher Na content (p < 0.05). These findings prove the long-term effects of smoking, demonstrating the bioaccumulation of toxic elements, the increased levels of rare earth elements in the liver, decreased levels of elements involved in the body’s antioxidant defense, and disruption of sodium homeostasis in the brain of smokers. Full article

This study aimed to examine trace element concentrations in indoor dust and evaluate health risks in child development centers in haze and industrial areas of Thailand from November 2023 to April 2024. The samples were extracted using a microwave oven and analyzed via ICP-OES. The finding indicated that the levels of As, Cr, Pb, V, Fe, Mn, and Zn in the dust from child development centers in the industrial area were significantly higher than those in the haze area (p < 0.05). The presence of trace element contaminants in indoor dust is indicative of anthropogenic sources. Cd and Zn in both areas have shown significantly elevated risks, according to the probable ecological risk factor. Source apportionment identified traffic, road dust, and biomass combustion as the principal sources of pollution in the haze area, while traffic and combustion activities were significant in the industrial area. Non-carcinogenic risk assessments for children exposed to As, Pb, Cu, and Cr revealed potential health risks (HI > 1). Furthermore, the total cancer risk (TCR) linked to As, Cr, and Ni is considered acceptable within the criteria of 10⁻⁶ to 10⁻⁴. However, long-term exposure may increase the risk of cancer in children. Full article

As solid-state devices continue to advance, vacuum electron devices maintain critical importance due to their superior high-frequency power handling, long-term reliability, and operational efficiency. Among these, traveling-wave tubes (TWTs) excel in high-power microwave (HPM) applications, offering exceptional bandwidth and gain. However, developing THz-range TWT slow-wave structures (SWSs) presents significant design challenges. This work systematically outlines the SWS design methodology while addressing key obstacles and their solutions. As a demonstration, a staggered double vane (SDV) SWS operating at 1 THz (980–1080 GHz) achieves 650 mW output power, 23.35 dB gain, 0.14% electronic efficiency, and compact 21 mm length. Comparative analysis with deformed quasi-sine waveguide (D-QSWG) SWS confirms the SDV design’s superior performance for THz applications. Full article

This study evaluates the corrosion-inhibiting effects of the methanolic (P₁) and the hydroalcoholic (P₂) extracts of the Rhus typhina L. leaves on carbon steel (OL37) in 1 M HCl. Extracts were prepared with microwave-assisted extraction and characterized using HPLC and LC-MS. Electrochemical methods (OCP, EIS, PDP) and surface analyses (SEM, EDX) assessed the performance of both extracts. The results showed that the P₁ and P₂ extracts significantly reduced corrosion rates by forming protective layers on the metal surface, with inhibition efficiencies exceeding 90%, at 1000 ppm concentration, for P₁ (93%), for P₂ at 800 ppm (91%) and 1000 ppm (94%). The P₂ extract demonstrated superior long-term performance, maintaining protection after 96 h of immersion. The extracts function as mixed-type inhibitors, affecting both anodic and cathodic reactions, with physicochemical adsorption demonstrated by the Langmuir isotherm. Overall, the Rhus typhina leaf extracts, particularly the P₂ extract, offer a promising, eco-friendly approach to corrosion prevention in acidic environments. Full article

Active and abandoned mining sites are significant sources of heavy metals and metalloid pollution, leading to serious environmental issues. This study assessed the environmental risks posed by potentially toxic elements (PTEs), specifically arsenic (As) and antimony (Sb), in the Technosols (mining residues) of the former Pejão coal mine complex in Northern Portugal, a site impacted by forest wildfires in October 2017 that triggered underground combustion within the waste heaps. Our methodology involved determining the “pseudo-total” concentrations of As and Sb in the collected heap samples using microwave digestion with aqua regia (ISO 12914), followed by analysis using hydride generation-atomic absorption spectroscopy (HG-AAS). The concentrations of As an Sb ranging from 31.0 to 68.6 mg kg⁻¹ and 4.8 to 8.3 mg kg⁻¹, respectively, were found to be above the European background values reported in project FOREGS (11.6 mg kg⁻¹ for As and 1.04 mg kg⁻¹ for Sb) and Portuguese Environment Agency (APA) reference values for agricultural soils (11 mg kg⁻¹ for As and 7.5 mg kg⁻¹ for Sb), indicating significant enrichment of these PTEs. Based on average I_geo values, As contamination overall was classified as “unpolluted to moderately polluted” while Sb contamination was classified as “moderately polluted” in the waste pile samples and “unpolluted to moderately polluted” in the downhill soil samples. However, total PTE content alone is insufficient for a comprehensive environmental risk assessment. Therefore, further studies on As and Sb fractionation and speciation were conducted using the Shiowatana sequential extraction procedure (SEP). The results showed that As and Sb levels in the more mobile fractions were not significant. This suggests that the enrichment in the burned (BCW) and unburned (UCW) coal waste areas of the mine is likely due to the stockpiling of lithic fragments, primarily coals hosting arsenian pyrites and stibnite which largely traps these elements within its crystalline structure. The observed enrichment in downhill soils (DS) is attributed to mechanical weathering, rock fragment erosion, and transport processes. Given the strong association of these elements with solid phases, the risk of leaching into surface waters and aquifers is considered low. This work underscores the importance of a holistic approach to environmental risk assessment at former mining sites, contributing to the development of sustainable remediation strategies for long-term environmental protection. Full article

Pulverized coal mass concentration in the primary air pipe is one of the essential parameters for promoting furnace combustion efficiency. However, attaining accurate, real-time, and online detection for pulverized coal mass concentration remains challenging due to factors such as large pipe diameter and high flow rate. This study introduces a quasi-open microwave resonant cavity sensor. The principle and model were analyzed using the perturbation method, and the design and optimization were conducted with the simulation. A prototype and its test system were constructed, and the test results demonstrated good agreement between the simulations and experiments. The simulation revealed that the resonant frequency decreased monotonically from 861 to 644 MHz as mass concentration increased within 20%~80%, resulting in a change of about 3.62 MHz/1% under static mixture. The resonant frequency showed a drop from 21 MHz to 9 MHz with an increase in mass concentration under pulverized coal flow. Prediction models were developed and validated, showing the absolute values of the relative errors to be within 4% under operational scenarios. Additionally, the impact of the sensor on pulverized coal flow was evaluated, and it was found that the sensor structure had minimal impact on the flow in terms of velocity and the distribution of continuous flow. Finally, the long-term stability was assessed by examining the wear of the antennas and barriers. With inner barriers experiencing up to 2/3d wear, the resonant frequency drift ratio remained below 1.5%, corresponding to a mass concentration deviation of less than 3.2%. Full article

Soil moisture (SM) plays a fundamental role in the water cycle and is an important variable for all processes occurring at the lithosphere–atmosphere interface, which are strongly affected by climate change. Among the different fields of application, accurate SM measurements are becoming more relevant for all studies related to extreme event (e.g., floods, droughts, and landslides) mitigation and assessment. In this study, data acquired by the advanced microwave sounding unit (AMSU) onboard the European Meteorological Operational Satellite Program (MetOP) satellites were used for the first time to extract information on the variability of SM by implementing the original soil wetness index (SWI). Long-term monthly SWI time series collected for the Basilicata region (southern Italy) were analyzed for drought assessment during the period 2007–2021. The accuracy of the SWI product was tested through a comparison with SM products derived by the Advanced SCATterometer (ASCAT) over the 2013–2016 period, while the Standardized Precipitation-Evapotranspiration Index (SPEI) was used to assess the relevance of the long-term achievements in terms of drought analysis. The results indicate a satisfactory accuracy of the SWI, with the mean correlation coefficient values with ASCAT higher than 0.7 and a mean normalized root mean square error less than 0.155. A negative trend in SWI during the 15-year period was found using both the original and deseasonalized series (linear and Sen’s slope ~−0.00525), confirmed by SPEI (linear and Sen’s slope ~−0.00293), suggesting the occurrence of a marginal long-term dry phase in the region. Although further investigations are needed to better assess the intensity and main causes of the phenomena, this result indicates the contribution that satellite data/products can offer in supporting drought assessment. Full article

Intensive industrial activities have led to severe polycyclic aromatic hydrocarbon (PAH) contamination of adjacent lands. Remediating such contaminated soil is crucial for maintaining long-term ecological health and sustainable development. This study systematically assessed the performance of a microwave-activated persulfate (MW/PS) oxidation method in remediating pyrene-contaminated soil. Under conditions of 80 °C and a persulfate concentration of 23.8 mg/g, this system achieved 85.3% pyrene degradation within 30 min, significantly outperforming both single microwave and thermal-activated persulfate (TH/PS) systems. Key factors influencing the oxidation efficiency included the temperature, persulfate and pyrene concentrations, moisture, and humic acid content. An electron paramagnetic resonance analysis confirmed the generation of reactive oxygen species, including ^•OH, SO₄^•− and ¹O₂, in the MW/PS system, while O₂^•− was exclusive to the TH/PS system. However, further experiments revealed that ¹O₂ had a negligible impact on pyrene degradation, suggesting that its role may have been overestimated in previous studies. The high MW/PS performance was attributed to the synergistic effects of both thermal and non-thermal (molecular vibration) mechanisms. Based on these findings, the pathways of pyrene degradation were proposed, with intermediate products exhibiting reduced toxicity and bioaccumulation potential. This study provides valuable insights into the application of MW/PS systems in the remediation of PAH-contaminated soils. Full article

Rosa damascena Mill., widely recognized for its remarkable skincare benefits, is extensively used in the cosmeceutical industry. This study introduces a novel green approach to extract bioactive compounds from R. damascena for cosmeceutical applications while also evaluating its stability in terms of physical, chemical, and biological properties. R. damascena petals were extracted using deionized water instead of organic solvents, using various green extraction methods, including infusion, microwave, ultrasound, pulsed electric field, and micellar extraction. Their chemical composition was analyzed using high-performance liquid chromatography. The extract with the highest concentration of bioactive compounds was further evaluated for its cosmeceutical properties and stability and compared with its individual chemical components. Various factors influencing stability were evaluated, including pH level (5, 7, and 9), temperature (4 °C, 30 °C, and 45 °C), and light exposure. The findings indicate that the extract obtained through microwave-assisted extraction (MAE) contained the highest concentration of bioactive constituents, with corilagin being the most abundant, followed by cyanidin-3,5-O-diglucoside, gallic acid, ellagic acid, L-ascorbic acid, and rutin, respectively. Additionally, MAE exhibited excellent antioxidant, whitening, and anti-skin-aging effects, demonstrating significantly higher activities than both the positive control (L-ascorbic acid for antioxidant effects, kojic acid for anti-tyrosinase effects, and epigallocatechin gallate and oleanolic acid for anti-skin-aging effects) and the individual chemical constituents. However, the physico-chemical and biological stability of MAE was influenced by pH, temperature, and light exposure, and as such, light-protected and controlled temperature (not exceeding 30 °C) is essential to maintain the extract’s efficacy in skincare products, and optimal formulation strategies are strongly recommended to ensure long-term stability. Full article