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23 pages, 4240 KiB  
Article
Heliocentric Orbital Repositioning of a Sun-Facing Diffractive Sail with Controlled Binary Metamaterial Arrayed Grating
by Alessandro A. Quarta
Appl. Sci. 2025, 15(15), 8755; https://doi.org/10.3390/app15158755 (registering DOI) - 7 Aug 2025
Abstract
This paper investigates the performance of a spacecraft equipped with a diffractive sail in a heliocentric mission scenario that requires phasing along a prescribed elliptical orbit. The diffractive sail represents an evolution of the more traditional reflective solar sail, which converts solar radiation [...] Read more.
This paper investigates the performance of a spacecraft equipped with a diffractive sail in a heliocentric mission scenario that requires phasing along a prescribed elliptical orbit. The diffractive sail represents an evolution of the more traditional reflective solar sail, which converts solar radiation pressure into thrust using a large reflective surface typically coated with a thin metallic film. In contrast, the diffractive sail proposed by Swartzlander leverages the properties of an advanced metamaterial-based film to generate a net transverse thrust even when the sail is Sun-facing, i.e., in a configuration that can be passively maintained by a suitably designed spacecraft. Specifically, this study considers a sail membrane covered with a set of electro-optically controlled diffractive panels. These panels employ a (controlled) binary metamaterial arrayed grating to steer the direction of photons exiting the diffractive film. This control technique has recently been applied to achieve a circle-to-circle interplanetary transfer using a Sun-facing diffractive sail. In this work, an optimal control law is employed to execute a rapid phasing maneuver along an elliptical heliocentric orbit with specified characteristics, such as those of Earth and Mercury. The analysis also includes a limiting case involving a circular heliocentric orbit. For this latter scenario, a simplified and elegant control law is proposed based on a linearized form of the equations of motion to describe the heliocentric dynamics of the diffractive sail-based spacecraft during the phasing maneuver. Full article
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14 pages, 1194 KiB  
Article
A Benzimidazole-Based Fluorescent Probe for the Selective Recognition of Cobalt (II) Ions
by Jing Zhu, Hua-Fen Wang, Jia-Xiang Zhang, Man Wang, Yu-Wei Zhuang, Zhi-Guang Suo, Ye-Wu He, Yan-Chang Zhang, Min Wei and Hai-Yan Zhang
Molecules 2025, 30(15), 3309; https://doi.org/10.3390/molecules30153309 (registering DOI) - 7 Aug 2025
Abstract
Cobalt, a rare element in the Earth’s crust, is widely used in industries due to its hardness and antioxidant properties. It also plays a vital role in physiological functions, being a key component of vitamin B12. However, excessive cobalt intake can [...] Read more.
Cobalt, a rare element in the Earth’s crust, is widely used in industries due to its hardness and antioxidant properties. It also plays a vital role in physiological functions, being a key component of vitamin B12. However, excessive cobalt intake can cause health issues. Detecting cobalt ions, especially Co2+, in food is crucial due to potential contamination from various sources. Fluorescent probes offer high sensitivity, selectivity, a rapid response, and ease of use, making them ideal for the accurate and efficient recognition of Co2+ in complex samples. In this context, a highly selective fluorescent probe, 2,2′-((3-(1H-benzo[d]imidazol-2-yl)-1,2-phenylene) bis(oxy)) bis(N-(quinolin-8-yl) acetamide) (DQBM-B), was synthesized using chloroacetyl chloride, 8-aminoquinoline, 2,3-dihydroxybenzaldehyde, and benzidine as raw materials for the recognition of Co2+. Probe DQBM-B can exhibit fluorescence alone in DMF. However, as the concentration of Co2+ increased, Photoinduced Electron Transfer (PET) occurred, which quenched the original fluorescence of the probe. Probe DQBM-B shows better selectivity for Co2+ than other ions with high sensitivity (detection limit: 3.56 μmol L−1), and the reaction reaches equilibrium within 30 min. Full article
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23 pages, 14727 KiB  
Article
A Novel Method for Single-Station Lightning Distance Estimation Based on the Physical Time Reversal
by Yingcheng Zhao, Zheng Sun, Yantao Duan, Hailin Chen, Yicheng Liu and Lihua Shi
Remote Sens. 2025, 17(15), 2734; https://doi.org/10.3390/rs17152734 - 7 Aug 2025
Abstract
A single-station lightning location has the obvious advantages of low cost and convenience in lightning monitoring and warning. To address the critical challenge of distance estimation accuracy in this technology, we propose a novel physical time-reversal (PTR) method to utilize the full wave [...] Read more.
A single-station lightning location has the obvious advantages of low cost and convenience in lightning monitoring and warning. To address the critical challenge of distance estimation accuracy in this technology, we propose a novel physical time-reversal (PTR) method to utilize the full wave information of both the ground wave and the sky wave in the detected signal. First, we improved the numerical model for accurately calculating the lightning sferics signals in the complex propagation environment of the Earth–ionosphere waveguide using the measured International Reference Ionosphere 2020. Subsequently, the sferics signal with multipath effect is transformed by time reversal and back propagated in the numerical model. Furthermore, a broadening factor reflecting the waveform dispersion in the back propagation is defined as the single-station focusing criterion to determine the optimal lightning propagation distance, considering the multipath effect and the focus of the PTR process. The experimental results demonstrate that the average root mean square error (RMSE) and the mean relative error (MRE) of the PTR method for the lightning distance estimation in the numerical simulation within the range of 100–1200 km are 5.517 km and 1.21%, respectively, and the average RMSE and the MRE for the natural lightning strikes to the Canton Tower from the measured data in the range of 181.643–1152.834 km are 9.251 km and 2.07%, respectively. Moreover, the correlation coefficients of the detection results are all as high as 0.999. These results indicate that the PTR method significantly outperforms the traditional ionospheric reflection method, demonstrating that it is able to perform a more accurate single-station lightning distance estimation by utilizing the compensation mechanism of the multipath effect on the sferics. The implementation of the proposed method has significant application value for improving the accuracy of single-station lightning location. Full article
(This article belongs to the Section Atmospheric Remote Sensing)
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17 pages, 6476 KiB  
Article
Spatiotemporal Exposure to Heavy-Day Rainfall in the Western Himalaya Mapped with Remote Sensing, GIS, and Deep Learning
by Zahid Ahmad Dar, Saurabh Kumar Gupta, Shruti Kanga, Suraj Kumar Singh, Gowhar Meraj, Pankaj Kumar, Bhartendu Sajan, Bojan Đurin, Nikola Kranjčić and Dragana Dogančić
Geomatics 2025, 5(3), 37; https://doi.org/10.3390/geomatics5030037 - 7 Aug 2025
Abstract
Heavy rainfall events, characterized by extreme downpours that exceed 100 mm per day, pose an intensifying hazard to the densely settled valleys of the western Himalaya; however, their coupling with expanding urban land cover remains under-quantified. This study mapped the spatiotemporal exposure of [...] Read more.
Heavy rainfall events, characterized by extreme downpours that exceed 100 mm per day, pose an intensifying hazard to the densely settled valleys of the western Himalaya; however, their coupling with expanding urban land cover remains under-quantified. This study mapped the spatiotemporal exposure of built-up areas to heavy-day rainfall (HDR) across Jammu, Kashmir, and Ladakh and the adjoining areas by integrating daily Climate Hazards Group InfraRed Precipitation with Stations product (CHIRPS) precipitation (0.05°) with Global Human Settlement Layer (GHSL) built-up fractions within the Google Earth Engine (GEE). Given the limited sub-hourly observations, a daily threshold of ≥100 mm was adopted as a proxy for HDR, with sensitivity evaluated at alternative thresholds. The results showed that HDR is strongly clustered along the Kashmir Valley and the Pir Panjal flank, as demonstrated by the mean annual count of threshold-exceeding pixels increasing from 12 yr−1 (2000–2010) to 18 yr−1 (2011–2020), with two pixel-scale hotspots recurring southwest of Srinagar and near Baramulla regions. The cumulative high-intensity areas covered 31,555.26 km2, whereas 37,897.04 km2 of adjacent terrain registered no HDR events. Within this hazard belt, the exposed built-up area increased from 45 km2 in 2000 to 72 km2 in 2020, totaling 828 km2. The years with the most expansive rainfall footprints, 344 km2 (2010), 520 km2 (2012), and 650 km2 (2014), coincided with heavy Western Disturbances (WDs) and locally vigorous convection, producing the largest exposure increments. We also performed a forecast using a univariate long short-term memory (LSTM), outperforming Autoregressive Integrated Moving Average (ARIMA) and linear baselines on a 2017–2020 holdout (Root Mean Square Error, RMSE 0.82 km2; measure of errors, MAE 0.65 km2; R2 0.89), projecting the annual built-up area intersecting HDR to increase from ~320 km2 (2021) to ~420 km2 (2030); 95% prediction intervals widened from ±6 to ±11 km2 and remained above the historical median (~70 km2). In the absence of a long-term increase in total annual precipitation, the projected rise most likely reflects continued urban encroachment into recurrent high-intensity zones. The resulting spatial masks and exposure trajectories provide operational evidence to guide zoning, drainage design, and early warning protocols in the region. Full article
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23 pages, 11564 KiB  
Article
Cloud-Based Assessment of Flash Flood Susceptibility, Peak Runoff, and Peak Discharge on a National Scale with Google Earth Engine (GEE)
by Ivica Milevski, Bojana Aleksova, Aleksandar Valjarević and Pece Gorsevski
Atmosphere 2025, 16(8), 945; https://doi.org/10.3390/atmos16080945 - 7 Aug 2025
Abstract
Flash floods, exacerbated by climate change and land use alterations, are among the most destructive natural hazards globally, leading to significant damage and loss of life. In this context, the Flash Flood Potential Index (FFPI), which is a terrain and land surface-based model, [...] Read more.
Flash floods, exacerbated by climate change and land use alterations, are among the most destructive natural hazards globally, leading to significant damage and loss of life. In this context, the Flash Flood Potential Index (FFPI), which is a terrain and land surface-based model, and Google Earth Engine (GEE) were used to assess flood-prone zones across North Macedonia’s watersheds. The presented GEE-based assessment was accomplished by a custom script that automates the FFPI calculation process by integrating key factors derived from publicly available sources. These factors, which define susceptibility to torrential floods, include slope (Copernicus GLO-30 DEM), land cover (Copernicus GLO-30 DEM), soil type (SoilGrids), vegetation (ESA World Cover), and erodibility (CHIRPS). The spatial distribution of average FFPI values across 1396 small catchments (10–100 km2) revealed that a total of 45.4% of the area exhibited high to very high susceptibility, with notable spatial variability. The CHIRPS rainfall data (2000–2024) that combines satellite imagery and in situ measurements was used to estimate peak 24 h runoff and discharge. To improve the accuracy of CHIRPS, the data were adjusted by 30–50% to align with meteorological station records, along with normalized FFPI values as runoff coefficients. Validation against 328 historical river flood and flash flood records confirmed that 73.2% of events aligned with moderate to very high flash flood susceptibility catchments, underscoring the model’s reliability. Thus, the presented cloud-based scenario highlights the potential of the GEE’s efficacy in scalability and robustness for flash flood modeling and regional risk management at national scale. Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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20 pages, 12866 KiB  
Article
Integrating Spatial Autocorrelation and Greenest Images for Dynamic Analysis Urban Heat Islands Based on Google Earth Engine
by Dandan Yan, Yuqing Zhang, Peng Song, Xiaofang Zhang, Yu Wang, Wenyan Zhu and Qinghui Du
Sustainability 2025, 17(15), 7155; https://doi.org/10.3390/su17157155 - 7 Aug 2025
Abstract
With rapid global urbanization development, impermeable surface increase, urban population growth, building area expansion, and rising energy consumption, the urban heat island (UHI) effect is becoming increasingly serious. However, the spatial distribution of the UHI cannot be accurately extracted. Therefore, we focused on [...] Read more.
With rapid global urbanization development, impermeable surface increase, urban population growth, building area expansion, and rising energy consumption, the urban heat island (UHI) effect is becoming increasingly serious. However, the spatial distribution of the UHI cannot be accurately extracted. Therefore, we focused on Luoyang City as the research area and combined the Getis-Ord-Gi* statistic and the greenest image to extract the UHI based on the Google Earth Engine using land surface temperature–spatial autocorrelation characteristics and seasonal changes in vegetation. As bare land considerably influenced the UHI extraction results, we combined the greenest image with the initial extraction results and applied the maximum normalized difference vegetation index threshold method to remove this effect on UHI distribution extraction, thereby achieving improved UHI extraction accuracy. Our results showed that the UHI of Luoyang continuously expanded outward, increasing from 361.69 km2 in 2000 to 912.58 km2 in 2023, with a continuous expansion rate of 22.95 km2/year. Furthermore, the urban area had a higher UHI area growth rate than the county area. Analysis indicates that the UHI effect in Luoyang has increased in parallel with the expansion of the building area. Intensive urban construction is a primary driver of this growth, directly exacerbating the UHI effect. Additionally, rising temperatures, population growth, and gross domestic product accumulation have collectively contributed to the ongoing expansion of this phenomenon. This study provides scientific guidance for future urban planning through the accurate extraction of the UHI effect, which promotes the development of sustainable human settlements. Full article
(This article belongs to the Special Issue Sustainable Future of Ecohydrology: Climate Change and Land Use)
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22 pages, 15367 KiB  
Article
All-Weather Precipitable Water Vapor Retrieval over Land Using Integrated Near-Infrared and Microwave Satellite Observations
by Shipeng Song, Mengyao Zhu, Zexing Tao, Duanyang Xu, Sunxin Jiao, Wanqing Yang, Huaxuan Wang and Guodong Zhao
Remote Sens. 2025, 17(15), 2730; https://doi.org/10.3390/rs17152730 - 7 Aug 2025
Abstract
Precipitable water vapor (PWV) is a critical component of the Earth’s atmosphere, playing a pivotal role in weather systems, climate dynamics, and hydrological cycles. Accurate estimation of PWV is essential for numerical weather prediction, climate modeling, and atmospheric correction in remote sensing. Ground-based [...] Read more.
Precipitable water vapor (PWV) is a critical component of the Earth’s atmosphere, playing a pivotal role in weather systems, climate dynamics, and hydrological cycles. Accurate estimation of PWV is essential for numerical weather prediction, climate modeling, and atmospheric correction in remote sensing. Ground-based observation stations can only provide PWV measurements at discrete points, whereas spaceborne infrared remote sensing enables spatially continuous coverage, but its retrieval algorithm is restricted to clear-sky conditions. This study proposes an innovative approach that uses ensemble learning models to integrate infrared and microwave satellite data and other geographic features to achieve all-weather PWV retrieval. The proposed product shows strong consistency with IGRA radiosonde data, with correlation coefficients (R) of 0.96 for the ascending orbit and 0.95 for the descending orbit, and corresponding RMSE values of 5.65 and 5.68, respectively. Spatiotemporal analysis revealed that the retrieved PWV product exhibits a clear latitudinal gradient and seasonal variability, consistent with physical expectations. Unlike MODIS PWV products, which suffer from cloud-induced data gaps, the proposed method provides seamless spatial coverage, particularly in regions with frequent cloud cover, such as southern China. Temporal consistency was further validated across four east Asian climate zones, with correlation coefficients exceeding 0.88 and low error metrics. This algorithm establishes a novel all-weather approach for atmospheric water vapor retrieval that does not rely on ground-based PWV measurements for model training, thereby offering a new solution for estimating water vapor in regions lacking ground observation stations. Full article
(This article belongs to the Section Atmospheric Remote Sensing)
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17 pages, 216 KiB  
Article
Inference to the Only Explanation: The Case of the Cretaceous/Paleogene Extinction Controversies
by Keith M. Parsons
Philosophies 2025, 10(4), 89; https://doi.org/10.3390/philosophies10040089 - 7 Aug 2025
Abstract
In the sciences of the deep past, it is taken for granted that the hypothesis that offers the best explanation is the best confirmed. I examine in detail the debate over the K/Pg mass extinctions that began in 1980 with the publication of [...] Read more.
In the sciences of the deep past, it is taken for granted that the hypothesis that offers the best explanation is the best confirmed. I examine in detail the debate over the K/Pg mass extinctions that began in 1980 with the publication of the paper by Alvarez et al. that proposed the impact extinction hypothesis. I summarize this debate and show how the impact hypothesis eventually achieved consensus as the best explanation. I then consider the relevance of that case study to an evaluation of the employment of inference to the best explanation (IBE) in the earth sciences. I first reject a number of the standard objections to IBE and then strongly endorse John Norton’s claim that no form of ampliative inference can receive a priori justification. Nevertheless, drawing on the case study and other instances, we may identify four “abductive virtues” that characterize many of the most successful instances of IBE, making them attractive and even compelling. Full article
21 pages, 1788 KiB  
Article
Investigation, Prospects, and Economic Scenarios for the Use of Biochar in Small-Scale Agriculture in Tropical
by Vinicius John, Ana Rita de Oliveira Braga, Criscian Kellen Amaro de Oliveira Danielli, Heiriane Martins Sousa, Filipe Eduardo Danielli, Newton Paulo de Souza Falcão, João Guerra, Dimas José Lasmar and Cláudia S. C. Marques-dos-Santos
Agriculture 2025, 15(15), 1700; https://doi.org/10.3390/agriculture15151700 - 6 Aug 2025
Abstract
This study investigates the production and economic feasibility of biochar for smallholder and family farms in Central Amazonia, with potential implications for other tropical regions. The costs of construction of a prototype mobile kiln and biochar production were evaluated, using small-sized biomass from [...] Read more.
This study investigates the production and economic feasibility of biochar for smallholder and family farms in Central Amazonia, with potential implications for other tropical regions. The costs of construction of a prototype mobile kiln and biochar production were evaluated, using small-sized biomass from acai (Euterpe oleracea Mart.) agro-industrial residues as feedstock. The biochar produced was characterised in terms of its liming capacity (calcium carbonate equivalence, CaCO3eq), nutrient content via organic fertilisation methods, and ash analysis by ICP-OES. Field trials with cowpea assessed economic outcomes, as well scenarios of fractional biochar application and cost comparison between biochar production in the prototype kiln and a traditional earth-brick kiln. The prototype kiln showed production costs of USD 0.87–2.06 kg−1, whereas traditional kiln significantly reduced costs (USD 0.03–0.08 kg−1). Biochar application alone increased cowpea revenue by 34%, while combining biochar and lime raised cowpea revenues by up to 84.6%. Owing to high input costs and the low value of the crop, the control treatment generated greater net revenue compared to treatments using lime alone. Moreover, biochar produced in traditional kilns provided a 94% increase in net revenue compared to liming. The estimated externalities indicated that carbon credits represented the most significant potential source of income (USD 2217 ha−1). Finally, fractional biochar application in ten years can retain over 97% of soil carbon content, demonstrating potential for sustainable agriculture and carbon sequestration and a potential further motivation for farmers if integrated into carbon markets. Public policies and technological adaptations are essential for facilitating biochar adoption by small-scale tropical farmers. Full article
(This article belongs to the Special Issue Converting and Recycling of Agroforestry Residues)
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20 pages, 11969 KiB  
Article
Spatiotemporal Variability of Cloud Parameters and Their Climatic Impacts over Central Asia Based on Multi-Source Satellite and ERA5 Data
by Xinrui Xie, Liyun Ma, Junqiang Yao and Weiyi Mao
Remote Sens. 2025, 17(15), 2724; https://doi.org/10.3390/rs17152724 - 6 Aug 2025
Abstract
As key components of the climate system, clouds exert a significant influence on the Earth’s radiation budget and hydrological cycle. However, studies focusing on cloud properties over Central Asia are still limited, and the impacts of cloud variability on regional temperature and precipitation [...] Read more.
As key components of the climate system, clouds exert a significant influence on the Earth’s radiation budget and hydrological cycle. However, studies focusing on cloud properties over Central Asia are still limited, and the impacts of cloud variability on regional temperature and precipitation remain poorly understood. This study uses reanalysis and multi-source remote sensing datasets to investigate the spatiotemporal characteristics of clouds and their influence on regional climate. The cloud cover increases from the southwest to the northeast, with mid and low-level clouds predominating in high-altitude regions. All clouds have shown a declining trend during 1981–2020. According to satellite data, the sharpest decline in total cloud cover occurs in summer, while reanalysis data show a more significant reduction in spring. In addition, cloud cover changes influence the local climate through radiative forcing mechanisms. Specifically, the weakening of shortwave reflective cooling and the enhancement of longwave heating of clouds collectively exacerbate surface warming. Meanwhile, precipitation is positively correlated with cloud cover, and its spatial distribution aligns with the cloud water path. The cloud phase composition in Central Asia is dominated by liquid water, accounting for over 40%, a microphysical characteristic that further impacts the regional hydrological cycle. Full article
(This article belongs to the Section Atmospheric Remote Sensing)
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30 pages, 4444 KiB  
Article
Unveiling the Potential of Novel Ternary Chalcogenide SrHfSe3 for Eco-Friendly, Self-Powered, Near-Infrared Photodetectors: A SCAPS-1D Simulation Study
by Salah Abdo, Ambali Alade Odebowale, Amer Abdulghani, Khalil As’ham, Sanjida Akter, Haroldo Hattori, Nicholas Kanizaj and Andrey E. Miroshnichenko
Sci 2025, 7(3), 113; https://doi.org/10.3390/sci7030113 - 6 Aug 2025
Abstract
Ternary chalcogenide-based sulfide materials with distorted morphologies such as BaZrS3, CaZrS3, and SrZrS3, have recently gained much attention in optoelectronics and photovoltaics due to their high structural and thermal stability and compatibility with low-cost, earth-abundant synthesis routes. [...] Read more.
Ternary chalcogenide-based sulfide materials with distorted morphologies such as BaZrS3, CaZrS3, and SrZrS3, have recently gained much attention in optoelectronics and photovoltaics due to their high structural and thermal stability and compatibility with low-cost, earth-abundant synthesis routes. However, their relatively large bandgaps often limit their suitability for near-infrared (NIR) photodetectors. Here, we conducted a comprehensive investigation of SrHfSe3, a ternary chalcogenide with an orthorhombic crystal structure and distinctive needle-like morphology, as a promising candidate for NIR photodetection. SrHfSe3 exhibits a direct bandgap of 1.02 eV, placing it well within the NIR range. Its robust structure, high temperature stability, phase stability and natural abundance make it a compelling material for next-generation, self-powered NIR photodetectors. An in-depth analysis of the SrHfSe3-based photodetector was performed using SCAPS-1D simulations, focusing on key performance metrics such as J–V behavior, photoresponsivity, and specific detectivity. Device optimization was achieved by thoroughly altering each layer thickness, doping concentrations, and defect densities. Additionally, the influence of interface defects, absorber bandgap, and operating temperature was assessed to enhance the photoresponse. Under optimal conditions, the device achieved a short-circuit current density (Jsc) of 45.88 mA/cm2, an open-circuit voltage (Voc) of 0.7152 V, a peak photoresponsivity of 0.85 AW−1, and a detectivity of 2.26 × 1014 Jones at 1100 nm. A broad spectral response spanning 700–1200 nm confirms its efficacy in the NIR region. These results position SrHfSe3 as a strong contender for future NIR photodetectors and provide a foundation for experimental validation in advanced optoelectronic applications. Full article
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16 pages, 2868 KiB  
Article
The Biocorrosion of a Rare Earth Magnesium Alloy in Artificial Seawater Containing Chlorella vulgaris
by Xinran Yao, Qi Fu, Guang-Ling Song and Kai Wang
Materials 2025, 18(15), 3698; https://doi.org/10.3390/ma18153698 - 6 Aug 2025
Abstract
In the medical field, magnesium (Mg) alloys have been widely used due to their excellent antibacterial properties and biodegradability. However, in the marine environment, the antibacterial effect may be greatly attenuated, and consequently, microorganisms in the ocean are likely to adhere to the [...] Read more.
In the medical field, magnesium (Mg) alloys have been widely used due to their excellent antibacterial properties and biodegradability. However, in the marine environment, the antibacterial effect may be greatly attenuated, and consequently, microorganisms in the ocean are likely to adhere to the surface of Mg alloys, resulting in biocorrosion damage, which is really troublesome in the maritime industry and can even be disastrous to the navy. Currently, there is a lack of research on the biocorrosion of Mg alloys that may find important applications in marine engineering. In this paper, the biocorrosion mechanism of the Mg alloy Mg-3Nd-2Gd-Zn-Zr caused by Chlorella vulgaris (C. vulgaris), a typical marine microalga, was studied. The results showed that the biomineralization process in the artificial seawater containing a low concentration of C. vulgaris cells was accelerated compared with that in the abiotic artificial seawater, leading to the deposition of CaCO3 on the surface to inhibit the localized corrosion of the Mg alloy, whereas a high concentration of C. vulgaris cells produced a high content of organic acids at some sites through photosynthesis to significantly accelerate the surface film rupture at some sites and severe localized corrosion there, but meanwhile, it resulted in the formation of a more protective biomineralized film in the other areas to greatly alleviate the corrosion. The contradictory biocorrosion behaviors on the Mg-3Nd-2Gd-Zn-Zr alloy induced by C. vulgaris were finally explained by a mechanism proposed in the paper. Full article
(This article belongs to the Section Corrosion)
22 pages, 19937 KiB  
Article
Development and Evaluation of a Two-Dimensional Extension/Contraction-Driven Rover for Sideslip Suppression During Slope Traversal
by Kenta Sagara, Daisuke Fujiwara and Kojiro Iizuka
Aerospace 2025, 12(8), 699; https://doi.org/10.3390/aerospace12080699 - 6 Aug 2025
Abstract
Wheeled rovers are widely used in lunar and planetary exploration missions owing to their mechanical simplicity and energy efficiency. However, they face serious mobility challenges on sloped soft terrain, especially in terms of sideslip and loss of attitude angle when traversing across slopes. [...] Read more.
Wheeled rovers are widely used in lunar and planetary exploration missions owing to their mechanical simplicity and energy efficiency. However, they face serious mobility challenges on sloped soft terrain, especially in terms of sideslip and loss of attitude angle when traversing across slopes. Previous research proposed using wheelbase extension/contraction and intentionally sinking wheels into the ground, thereby increasing shear resistance and reducing sideslip. Building upon this concept, this study proposes a novel recovery method that integrates beam extension/contraction and Archimedean screw-shaped wheels to enable lateral movement without rotating the rover body. The beam mechanism allows for independent wheel movement, maintaining stability by anchoring stationary wheels during recovery. Meanwhile, the helical structure of the screw wheels helps reduce lateral earth pressure by scraping soil away from the sides, improving lateral drivability. Driving experiments on a sloped sandbox test bed confirmed that the proposed 2DPPL (two-dimensional push-pull locomotion) method significantly reduces sideslip and prevents a drop in attitude angle during slope traversal. Full article
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26 pages, 3314 KiB  
Article
Antenna Model with Pattern Optimization Based on Genetic Algorithm for Satellite-Based SAR Mission
by Saray Sánchez-Sevilleja, Marcos García-Rodríguez, José Luis Masa-Campos and Juan Manuel Cuerda-Muñoz
Sensors 2025, 25(15), 4835; https://doi.org/10.3390/s25154835 - 6 Aug 2025
Abstract
Synthetic aperture radar (SAR) systems are of paramount importance to remote sensing applications, including Earth observation and environmental monitoring. Accurate calibration of these systems is imperative to ensuring the accuracy and reliability of the acquired data. A central component of the calibration process [...] Read more.
Synthetic aperture radar (SAR) systems are of paramount importance to remote sensing applications, including Earth observation and environmental monitoring. Accurate calibration of these systems is imperative to ensuring the accuracy and reliability of the acquired data. A central component of the calibration process is the antenna model, which serves as a fundamental reference for characterizing the radiation pattern, gain, and overall performance of SAR systems. The present paper sets out to describe the implementation and validation of a phased-array antenna model for Synthetic Aperture Radar Systems (SARAS) in MATLAB R2024a. The antenna model was developed for utilization in the Spanish Earth observation missions PAZ and PRECURSOR-ECO. The antenna model incorporates a number of functions, which are divided into two primary modules: the first of these is the antenna pattern generation (APG) module, and the second is the antenna excitation generation (AEG) module. The present document focuses on the AEG, the function of which is to generate patterns for all required beams. These patterns are optimized and matched to specific calculated masks using an ad hoc genetic algorithm (GA). In consideration of the aforementioned factors, the AEG module generates a set of complex excitations corresponding to the required beam from different satellite operational beams, based on several radiometrically defined parameters.  Full article
(This article belongs to the Special Issue Recent Advances in Synthetic Aperture Radar (SAR) Remote Sensing)
28 pages, 4848 KiB  
Article
Mineralogical and Geochemical Features of Soil Developed on Rhyolites in the Dry Tropical Area of Cameroon
by Aubin Nzeugang Nzeukou, Désiré Tsozué, Estelle Lionelle Tamto Mamdem, Merlin Gountié Dedzo and Nathalie Fagel
Standards 2025, 5(3), 20; https://doi.org/10.3390/standards5030020 - 6 Aug 2025
Abstract
Petrological knowledge on weathering processes controlling the mobility of chemical elements is still limited in the dry tropical zone of Cameroon. This study aims to investigate the mobility of major and trace elements during rhyolite weathering and soil formation in Mobono by understanding [...] Read more.
Petrological knowledge on weathering processes controlling the mobility of chemical elements is still limited in the dry tropical zone of Cameroon. This study aims to investigate the mobility of major and trace elements during rhyolite weathering and soil formation in Mobono by understanding the mineralogical and elemental vertical variation. The studied soil was classified as Cambisols containing mainly quartz, K-feldspar, plagioclase, smectite, kaolinite, illite, calcite, lepidocrocite, goethite, sepiolite, and interstratified clay minerals. pH values ranging between 6.11 and 8.77 indicated that hydrolysis, superimposed on oxidation and carbonation, is the main process responsible for the formation of secondary minerals, leading to the formation of iron oxides and calcite. The bedrock was mainly constituted of SiO2, Al2O3, Na2O, Fe2O3, Ba, Zr, Sr, Y, Ga, and Rb. Ce and Eu anomalies, and chondrite-normalized La/Yb ratios were 0.98, 0.67, and 2.86, respectively. SiO2, Al2O3, Fe2O3, Na2O, and K2O were major elements in soil horizons. Trace elements revealed high levels of Ba (385 to 1320 mg kg−1), Zr (158 to 429 mg kg−1), Zn (61 to 151 mg kg−1), Sr (62 to 243 mg kg−1), Y (55 to 81 mg kg−1), Rb (1102 to 58 mg kg−1), and Ga (17.70 to 35 mg kg−1). LREEs were more abundant than HREEs, with LREE/HREE ratio ranging between 2.60 and 6.24. Ce and Eu anomalies ranged from 1.08 to 1.21 and 0.58 to 1.24 respectively. The rhyolite-normalized La/Yb ratios varied between 0.56 and 0.96. Mass balance revealed the depletion of Si, Ca, Na, Mn, Sr, Ta, W, U, La, Ce, Pr, Nd, Sm, Gd and Lu, and the accumulation of Al, Fe, K, Mg, P, Sc, V, Co, Ni, Cu, Zn, Ga, Ge, Rb, Y, Zr, Nb, Cs, Ba, Hf, Pb, Th, Eu, Tb, Dy, Ho, Er, Tm and Yb during weathering along the soil profile. Full article
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