Search Results (67)

This study presents an innovative approach by combining magnetized water (MW) with Bacillus megaterium to improve the sustainability of concrete under various curing conditions. These enhancements contribute directly to reduced cement use and improved durability, both essential factors in sustainable construction. An experimental program with 27 distinct mixes analyzed variables such as the type of water (tap water/TW and two magnetization sequences/MW1 and MW2), bacterial dosage (0%, 2.5%, and 5% relative to cement weight), and curing methods (traditional water curing/C1, thermal shock/C2, freeze–thaw/C3). The primary discovery is a synergistic relationship between MW and bacteria: the MW1 treatment (1.5 T followed by 0.9 T) paired with a 2.5% bacterial dosage significantly improved the mechanical and self-healing properties of the concrete. This combination led to significant improvements in workability and compressive strength, achieving an increase of as much as 46.5% compared to the control. There was also an impressive recovery of strength in pre-cracked specimens, particularly under thermal shock curing (C2), where some healed cubes exceeded the strength of the uncracked ones. On the other hand, a 5% bacterial dosage was less effective, often resulting in reduced returns due to variations in microstructure. SEM and XRD analyses confirmed a more compact matrix and increased calcite precipitation with 2.5% bacteria, illustrating the combined effects of microbial activity and microwave treatment for sustainable concrete. Full article

Sea ice concentration (SIC) is crucial to the global climate. In this study, a new single-channel SIC retrieval algorithm utilizing spaceborne L-band brightness temperature (TB) measurements is developed based on a microwave radiative transfer model. Additionally, its four uncertainties are quantified and constrained: (1) variations in seawater reference TB under warm water conditions, (2) variations in sea ice reference TB under extremely low-temperature conditions, (3) the freeze–thaw dynamics of sea ice captured by Diurnal Amplitude Variation (DAV) signals, and (4) Land mask imperfections. It is found that DAV has the most pronounced effect: eliminating its influence reduces RMSE from 10.51% to 8.43%, increases R from 0.92 to 0.94, and minimizes Bias from -0.68 to 0.13. Suppressing all four uncertainties lowers RMSE to 7.42% (a 3% improvement). Furthermore, the algorithm exhibits robust agreement with the seasonal variability of SSM/I SIC, with R mostly exceeding 0.9, RMSE mostly below 10%, and Biases mostly within 5% throughout the year. Compared to ship-based and SAR SIC data, the new L-band algorithm’s Bias and RMSE are only 2% and 2% (ship-based)/2% and 1% (SAR) higher, respectively, than those of the SSM/I product. Future algorithms can integrate the DAV signal more effectively to better understand sea ice freeze–thaw processes and ice-atmosphere interactions. Full article

Microwave heating is a method with a uniform heating effect and environmental friendliness in in-place hot recycling, but the microwave absorption capacity of traditional asphalt mixtures is still insufficient. As an excellent microwave-absorbing material, magnetite powder has the characteristics of high temperature resistance, corrosion resistance, and good thermodynamic stability. This study selects it as the microwave-absorbing material, prepares AC (Asphalt Concrete) type and SMA (Stone Mastic Asphalt) type microwave asphalt mixtures by adjusting its content, and investigates its influence on the microwave-heating characteristics and pavement performance of the mixtures. Simulations of the microwave-heating process of AC-type mixtures using COMSOL software (COMSOL Multiphysics 6.2) show that magnetite powder achieves optimal performance in terms of heating effect and economic efficiency when its content is 0.5%. Subsequently, laboratory tests are conducted to study the wave absorption and temperature rise performance of AC and SMA microwave asphalt mixtures; combined with economic factors, the optimal contents of magnetite powder for the two types of mixtures are determined to be 0.5% and 1%, respectively, and at the same time, these results are explained based on multiple physical theories. Furthermore, pavement performance is investigated through laboratory tests, including high-temperature rutting tests, low-temperature bending tests, immersed Marshall tests, and freeze–thaw cycle durability tests, and the results indicate that the high-temperature performance, low-temperature performance, and water stability of the microwave asphalt mixtures all meet the specification requirements for pavement performance. Subsequently, after 15 freeze–thaw cycles, the splitting tensile strength retention rate and stiffness modulus of the two types of mixtures show minimal differences from those of ordinary mixtures, and there is no durability degradation caused by the incorporation of magnetite powder. Finally, outdoor environment verification is carried out, and the results show that under complex conditions such as environmental factors, the wave absorption and temperature rise rates of AC and SMA mixtures at optimal contents are 52.2% and 14.6% higher than those of ordinary AC and SMA asphalt mixtures, respectively. In addition, these microwave asphalt mixtures have the advantages of both sustainability and reduced carbon emissions. By combining simulation methods and experimental verification, this study finally prepared two types of microwave asphalt mixtures with excellent performance, not only improving the microwave absorption and heating performance of asphalt mixtures, but also reducing environmental pollution and energy consumption, which conforms to the development of green transportation. Full article

Food waste is a global challenge, with broccoli stalks (~58% of the head’s mass) often discarded despite being rich in fiber, fatty acids, organic acids, sugars, phenolic compounds, and glucosinolates. Pretreatments like microwaving are gaining interest for enhancing nutrient availability and microbial activity by modifying biomass structure and improving fermentation. This study explores microwave pretreatment (2, 4, 6, 9 W/g for 4–7 min) to enhance 24 h fermentation of pasteurized ground broccoli stalks using Lactiplantibacillus plantarum. Analyses included reducing sugars, total phenolics, microbial growth, Cryo-FESEM, and FTIR. Optimal microbial proliferation and preservation of key compounds were achieved at 4 W/g for 5 min. This condition was then compared to pasteurization, freezing/thawing, and autoclaving over a 96 h fermentation. pH, microbial population, and antioxidant properties were measured at 24 h intervals. Pasteurization, with or without microwaving, resulted in faster acidification and microbial growth. Microwaved samples retained the highest phenolic content, while autoclaved ones exhibited the highest flavonoid levels and antioxidant activity. Fermentation did not enhance antioxidant properties; phenolics and DPPH activity decreased after 24 h, while flavonoids and ABTS remained stable. Overall, pretreatments significantly influenced fermentation outcomes of broccoli stalks; microwaving post-pasteurization favored phenolic preservation and microbial proliferation, whereas autoclaving enhanced flavonoids and antioxidant potential. Full article

Spent hops from the supercritical extraction process represent a valuable source of xanthohumol (XN), a prenylated flavonoid with demonstrated anticancer, antidiabetic, antibacterial, and anti-inflammatory properties. However, XN is thermally sensitive and readily isomerizes into the less bioactive iso-XN at elevated temperatures, necessitating mild extraction conditions. Previous studies have shown that the pretreatment of plant biomass can enhance the extraction efficiency of bioactive compounds. In this study, various pretreatment methods—including physical (freeze–thaw, ultrasound, and microwave), chemical (acid and base hydrolysis), and enzymatic approaches—were applied to spent hops prior to extraction, and XN yields were compared to those obtained from untreated samples. The experiments, performed in triplicate, yielded meaningful results which helped understand the raw material’s behavior in applied conditions. Due to the compound’s high thermal sensitivity, ultrasound and microwave pretreatments require precise control to prevent excessive temperature increases, making low-temperature methods more suitable. Additionally, exposure to elevated pH adversely affected XN extraction efficiency, limiting the applicability of strong alkaline pretreatments. Among the evaluated methods, freeze–thaw pretreatment proved to be a simple and effective strategy, enhancing XN extraction yields by up to 10.7 ± 0.7% through the optimization of soaking time, the solid-to-liquid ratio, and the thawing temperature. Identifying an inexpensive and efficient pretreatment method could reduce extraction time while improving yield, contributing to the sustainable utilization of spent hops as an XN source. Full article

Marine microalgae are emerging as promising sources of polyphenols, renowned for their health-promoting benefits. Recovering polyphenols from microalgae requires suitable treatment and extraction techniques to ensure their release from the biomass and analytical methodologies to assess their efficiency. This review provides a comprehensive comparison of traditional and cutting-edge extraction and analytical procedures applied for polyphenolic characterization in marine microalgae over the past 26 years, with a unique perspective on optimizing their recovery and identification. It addresses (I) cell disruption techniques, including bead milling, high-speed homogenization, pulsed electric field, ultrasonication, microwave, freeze-thawing, and enzymatic/chemical hydrolysis; (II) extraction techniques, such as solid–liquid extraction, ultrasound and microwave-assisted extraction, pressurized-liquid extraction, and supercritical CO₂; (III) analytical methods, including total phenolic and flavonoid content assays and advanced chromatographic techniques like GC-MS, HPLC-DAD, and HPLC-MS. Key findings showed bead milling and chemical hydrolysis as effective cell disruption techniques, pressurized-liquid extraction and microwave-assisted extraction as promising efficient extraction methods, and HPLC-MS as the finest alternative for precise phenolic characterization. Unlike previous reviews, this study uniquely integrates both extractive and analytical approaches in one work, focusing exclusively on marine microalgae, a relatively underexplored area compared to freshwater species, offering actionable insights to guide future research and industrial applications. Full article

This study investigated the effects of microwave-assisted freezing on the quality attributes of button mushrooms (Agaricus bisporus). Four levels of microwave power (0, 10, 20, 30%) were applied to the mushroom samples during freezing. The quality attributes of the frozen and thawed mushrooms were then evaluated. The results suggested that higher microwave power produced the smaller and more uniform ice crystals. Moreover, the browning index of the mushroom samples increased with increasing microwave power. The textural properties (hardness) of the mushrooms were also affected by the microwave power, showing higher values as the power increased. Furthermore, the ratio of the microwave operating system’s power to the freezer power was low and approximately 20% at the highest power level. Therefore, these findings confirm the potential of microwave-assisted freezing for reducing freeze damage to mushroom tissue and, thus, provide frozen mushroom with a better texture. Full article

Soil freeze-thaw (FT) cycles over agricultural lands are of great importance due to their vital role in controlling soil moisture distribution, nutrient availability, health of microbial communities, and water partitioning during flood events. Active microwave sensors such as C-band Sentinel-1 synthetic aperture radar (SAR) can serve as powerful tools to detect field-scale soil FT state. Using Sentinel-1 SAR observations, this study compares the performance of two FT detection approaches, a commonly used seasonal threshold approach (STA) and a computationally inexpensive general threshold approach (GTA) at an agricultural field in New Hampshire, US. It also explores the applicability of an interferometric coherence approach (ICA) for FT detection. STA and GTA achieved 85% and 78% accuracy, respectively, using VH polarization. We find a marginal degradation in the performance of STA (82%) and GTA (76%) when employing VV-polarized data. While there was approximately a 6 percentage point difference between STA’s and GTA‘s overall accuracy, we recommend GTA for FT detection using SAR images at sub-field-scale over extended regions because of its higher computational efficiency. Our analysis shows that interferometric coherence is not suitable for detecting FT transitions under mild and highly dynamic winter conditions. We hypothesize that the relatively mild winter conditions and therefore the subtle FT transitions are not able to significantly reduce the correlation between the phase values. Also, the ephemeral nature of snowpack in our study area, further compounded by frequent rainfall, could cause decorrelation of SAR images even in the absence of a FT transition. We conclude that despite Sentinel-1’s ~80% mapping accuracy at a mid-latitude site, understanding the cause of misclassification remains challenging, even when detailed ground data are readily available and employed in error attribution efforts. Full article

GNSS-Reflectometry, a technique that harnesses the power of microwave remote sensing, is poised to revolutionize our ability to detect and monitor near-surface soil freeze/thaw processes. This technique’s theoretical underpinnings are deeply rooted in the comprehensive explanation of the Zhang–Zhao dielectric constant model, which provides crucial insights into the behavior of frozen and thawed soils. The model elucidates how the dielectric properties of soil change as it transitions between frozen and thawed states, offering a scientific basis for understanding reflectivity variations. Furthermore, the theoretical framework includes a set of formulas that are instrumental in calculating reflectivity at Lower Right (LR) polarization and in deriving Dual-Polarization Differential Observables (DDMs). These calculations are pivotal for interpreting the signals captured by GNSS-R sensors, allowing for the detection of subtle changes in the soil’s surface conditions. The evolution of GNSS-R as a tool for detecting freeze/thaw phenomena has been substantiated through qualitative analyses involving multiple satellite missions, such as SMAP-R, TDS-1, and CYGNSS. These analyses have provided empirical evidence of the technique’s effectiveness, illustrating its capacity to capture the dynamics of soil freezing and thawing processes. In addition to these qualitative assessments, the application of a discriminant retrieval algorithm using data from CYGNSS and F3E GNOS-R has further solidified the technique’s potential. This algorithm contributes to refining the accuracy of freeze/thaw detection by distinguishing between frozen and thawed soil states with greater precision. The deployment of space-borne GNSS-R for monitoring near-surface freeze/thaw cycles has yielded commendable results, exhibiting robust consistency and delivering relatively precise retrieval outcomes. These achievements stand as testaments to the technique’s viability and its growing significance in the field of remote sensing. However, it is imperative to recognize and actively address certain limitations that have been highlighted in this review. These limitations serve as critical focal points for future research endeavors, directing the efforts toward enhancing the technique’s overall performance and applicability. Addressing these challenges will be essential for leveraging the full potential of GNSS-R to advance our understanding and management of near-surface soil freeze/thaw processes. Full article

Over the past decades, the cryosphere has changed significantly in High Mountain Asia (HMA), leading to multiple natural hazards such as rock–ice avalanches, glacier collapse, debris flows, landslides, and glacial lake outburst floods (GLOFs). Monitoring cryosphere change and evaluating its hydrological effects are essential for studying climate change, the hydrological cycle, water resource management, and natural disaster mitigation and prevention. However, knowledge gaps, data uncertainties, and other substantial challenges limit comprehensive research in climate–cryosphere–hydrology–hazard systems. To address this, we provide an up-to-date, comprehensive, multidisciplinary review of remote sensing techniques in cryosphere studies, demonstrating primary methodologies for delineating glaciers and measuring geodetic glacier mass balance change, glacier thickness, glacier motion or ice velocity, snow extent and water equivalent, frozen ground or frozen soil, lake ice, and glacier-related hazards. The principal results and data achievements are summarized, including URL links for available products and related data platforms. We then describe the main challenges for cryosphere monitoring using satellite-based datasets. Among these challenges, the most significant limitations in accurate data inversion from remotely sensed data are attributed to the high uncertainties and inconsistent estimations due to rough terrain, the various techniques employed, data variability across the same regions (e.g., glacier mass balance change, snow depth retrieval, and the active layer thickness of frozen ground), and poor-quality optical images due to cloudy weather. The paucity of ground observations and validations with few long-term, continuous datasets also limits the utilization of satellite-based cryosphere studies and large-scale hydrological models. Lastly, we address potential breakthroughs in future studies, i.e., (1) outlining debris-covered glacier margins explicitly involving glacier areas in rough mountain shadows, (2) developing highly accurate snow depth retrieval methods by establishing a microwave emission model of snowpack in mountainous regions, (3) advancing techniques for subsurface complex freeze–thaw process observations from space, (4) filling knowledge gaps on scattering mechanisms varying with surface features (e.g., lake ice thickness and varying snow features on lake ice), and (5) improving and cross-verifying the data retrieval accuracy by combining different remote sensing techniques and physical models using machine learning methods and assimilation of multiple high-temporal-resolution datasets from multiple platforms. This comprehensive, multidisciplinary review highlights cryospheric studies incorporating spaceborne observations and hydrological models from diversified techniques/methodologies (e.g., multi-spectral optical data with thermal bands, SAR, InSAR, passive microwave, and altimetry), providing a valuable reference for what scientists have achieved in cryosphere change research and its hydrological effects on the Third Pole. Full article

Amphioctopus neglectus is a species of octopus that is favored by consumers due to its rich nutrient profile. To investigate the influence of different thawing methods on the quality of octopus meat, we employed four distinct thawing methods: air thawing (AT), hydrostatic thawing (HT), flowing water thawing (FWT), and microwave thawing (MT). We then explored the differences in texture, color, water retention, pH, total volatile basic nitrogen (TVB–N), total sulfhydryl content, Ca²⁺–ATPase activity, and myofibrillar protein, among other quality indicators in response to these methods, and used a low-field nuclear magnetic resonance analyzer to assess the water migration that occurred during the thawing process. The results revealed that AT had the longest thawing time, leading to oxidation-induced protein denaturation, myofibrillar protein damage, and a significant decrease in water retention. Additionally, when this method was utilized, the content of TVB–N was significantly higher than in the other three groups. HT, to a certain extent, isolated the oxygen in the meat and thus alleviated protein oxidation, allowing higher levels of Ca²⁺–ATPase activity, sulfhydryl content, and springiness to be maintained. However, HT had a longer duration: 2.95 times that of FWT, resulting in a 9.84% higher cooking loss and a 28.21% higher TVB–N content compared to FWT. MT had the shortest thawing time, yielding the lowest content of TVB–N. However, uneven heating and in some cases overcooking occurred, severely damaging the protein structure, with a concurrent increase in thawing loss, W value, hardness, and shear force. Meanwhile, FWT improved the L^*, W^* and b^* values of octopus meat, enhancing its color and water retention. The myofibrillar protein (MP) concentration was also the highest after FWT, with clearer subunit bands in SDS-PAGE electrophoresis, indicating that less degradation occurred and allowing greater springiness, increased Ca²⁺–ATPase activity, and a higher sulfhydryl content to be maintained. This suggests that FWT has an inhibitory effect on oxidation, alleviating protein oxidation degradation and preserving the quality of the meat. In conclusion, FWT outperformed the other three thawing methods, effectively minimizing adverse changes during thawing and successfully maintaining the quality of octopus meat. Full article

Surface freezing and thawing processes pose significant influences on surface water and energy balances, which, in turn, affect vegetation growth, soil moisture, carbon cycling, and terrestrial ecosystems. At present, the changes in surface freezing and thawing states are hotspots of ecological research, but the variations of surface frozen days (SFDs) are less studied, especially in the permafrost areas covered with boreal forest, and the influence of the environmental factors on the SFDs is not clear. Utilizing the Advanced Microwave Scanning Radiometer for EOS (AMSRE) and Microwave Scanning Radiometer 2 (AMSR2) brightness temperature data, this study applies the Freeze–Thaw Discriminant Function Algorithm (DFA) to explore the spatiotemporal variability features of SFDs in the Northeast China Permafrost Zone (NCPZ) and the relationship between the permafrost distribution and the spatial variability characteristics of SFDs; additionally, the Optimal Parameters-based Geographical Detector is employed to determine the factors that affect SFDs. The results showed that the SFDs in the NCPZ decreased with a rate of −0.43 d/a from 2002 to 2021 and significantly decreased on the eastern and western slopes of the Greater Khingan Mountains. Meanwhile, the degree of spatial fluctuation of SFDs increased gradually with a decreasing continuity of permafrost. Snow cover and air temperature were the two most important factors influencing SFD variability in the NCPZ, accounting for 83.9% and 74.8% of the spatial variation, respectively, and SFDs increased gradually with increasing snow cover and decreasing air temperature. The strongest explanatory power of SFD spatial variability was found to be the combination of air temperature and precipitation, which had a coefficient of 94.2%. Moreover, the combination of any two environmental factors increased this power. The findings of this study can be used to design ecological environmental conservation and engineer construction policies in high-latitude permafrost zones with forest cover. Full article

Microwave maintenance technology, as a new development trend, can realize the environmentally noninvasive and rapid repair of asphalt pavement and gradually replace traditional maintenance methods. Iron tailings were used as a self-healing material in this study to investigate the temperature response matching of microwave maintenance technology. Firstly, the physical properties and the mechanism of iron tailings were elaborated through macroscopic physical index testing and microscopic X-ray diffraction (XRD) analysis. Secondly, the applicability of aggregates to microwave heating was demonstrated by analyzing the temperature rise characteristics of the granules using infrared imaging. Then, the temperature field variation rules of the iron tailing asphalt mixture were summarized by microwave heating Marshall specimens. Finally, the road performance was assessed by conducting high-temperature dynamic stability, low-temperature tensile, water immersion Marshall, and freeze-thaw splitting tests. The experimental results showed that the iron tailings can be used as an aggregate for high-grade asphalt pavement and as the preferred aggregate for microwave maintenance technology. The iron tailings temperature field was radial from the inside out to provide different temperature response states for different pavement diseases, so the asphalt was dissolved and precipitated in a short time. The particle size of iron tailings was inversely proportional to the wave-absorbing heating rate, and the heating efficiency of the small particle size (0–4.75 mm) was the highest. The specimens doped with 4.75–13.2 mm iron tailings showed the best heating performance and road performance, with the average surface temperature of the specimens reaching 126.0 °C within 2 min. In summary, according to different disease types and construction needs, iron tailings can be used as an aggregate for asphalt pavement, providing an appropriate temperature field and improving the efficiency of the microwave maintenance of asphalt pavements. Full article

Lake ice phenology (LIP), hiding information about lake energy and material exchange, serves as an important indicator of climate change. Utilizing an efficient technique to swiftly extract lake ice information is crucial in the field of lake ice research. The Bayesian ensemble change detection (BECD) algorithm stands out as a powerful tool, requiring no threshold compared to other algorithms and, instead, utilizing the probability of abrupt changes to detect positions. This method is predominantly employed by automatically extracting change points from time series data, showcasing its efficiency and accuracy, especially in revealing phenological and seasonal characteristics. This paper focuses on Bosten Lake (BL) and employs PMRS data in conjunction with the Bayesian change detection algorithm. It introduces an automated method for extracting LIP information based on the Bayesian change detection algorithm. In this study, the BECD algorithm was employed to extract lake ice phenology information from passive microwave remote sensing data on Bosten Lake. The reliability of the passive microwave remote sensing data was further investigated through cross-validation with MOD10A1 data. Additionally, the Mann–Kendall non-parametric test was applied to analyze the trends in lake ice phenology changes in Bosten Lake. Spatial variations were examined using MOD09GQ data. The results indicate: (1) The Bayesian change detection algorithm (BCDA), in conjunction with PMRS data, offers a high level of accuracy and reliability in extracting the lake ice freezing and thawing processes. It accurately captures the phenological parameters of BL’s ice. (2) The average start date of lake ice freezing is in mid-December, lasting for about three months, and the start date of ice thawing is usually in mid-March. The freezing duration (FD) of lake ice is relatively short, shortening each year, while the thawing speed is faster. The stability of the lake ice complete ice cover duration is poor, averaging 84 days. (3) The dynamic evolution of BL ice is rapid and regionally distinct, with the lake center, southwest, and southeast regions being the earliest areas for ice formation and thawing, while the northwest coastal and Huang Shui Gou areas experience later ice formation. (4) Since 1978, BL’s ice has exhibited noticeable trends: the onset of freezing, the commencement of thawing, complete thawing, and full freezing have progressively advanced in regard to dates. The periods of full ice coverage, ice presence, thawing, and freezing have all shown a tendency toward shorter durations. This study introduces an innovative method for LIP extraction, opening up new prospects for the study of lake ecosystem and strategy formulation, which is worthy of further exploration and application in other lakes and regions. Full article

In this study, the effects of frozen storage time, thawing treatments, and their interaction on the rheological properties of non-fermented dough were evaluated. Texture profile analysis (TPA), rheological measurements, including strain/frequency sweep, and creep-recovery measurement were applied to the dough. Compared with unfrozen fresh dough, the frozen storage time (S) and thawing treatment (T) influenced almost all indicators significantly, and their mutual effects (S × T) mainly affected the hardness and springiness. Frozen time was the main factor resulting in the destruction of non-fermented dough during the thawing treatments. Moreover, refrigerator thawing (4 °C) produced a dough with minimal changes in the rheological properties, regardless of the frozen storage time. Meanwhile, microwave thawing resulted in lower G′ and lower zero shear viscosity (η₀) values, as well as higher maximum creep compliance (J_max) and hardness values. Moreover, the difference between the three thawing treatments was exacerbated after 30 days of frozen storage. SEM images also showed that long-term frozen storage combined with microwave thawing seriously destroyed the rheological properties, structural stability, and inner microstructure of the dough. Full article