The MAJIS (Moons And Jupiter Imaging Spectrometer) instrument, part of the JUICE (JUpiter ICy moons Explorer) mission, is a crucial tool for investigating the composition and dynamics of Jupiter's atmosphere, and the surfaces and exospheres of its icy moons. To optimize observational planning and assess instrument performance, we have developed a radiometric simulator that accurately models MAJIS expected signal from various Jovian system targets. This simulator incorporates instrumental parameters, the spacecraft trajectory, observational constraints, and Jupiter's radiation environment. It provides essential outputs, including Signal-to-Noise Ratio (SNR) predictions and optimized instrument settings for different observational scenarios. By simulating both radiometric performance and de-spiking strategies to mitigate the impact of Jupiter radiation belt, the tool aids in refining observation strategies throughout the MAJIS operations. Several scientific applications demonstrate the simulator capabilities, from mapping the surfaces of Ganymede and Europa to detecting exospheric emissions and atmospheric composition on Jupiter. This simulator is a critical asset for maximizing MAJIS scientific return and ensuring optimal data acquisition during MAJIS exploration of the Jovian system. Study cases are presented for illustrating the capability of the simulator to model scenarios such as high-resolution mapping of Ganymede, exosphere characterization and hotspot detection on Io and Europa. These simulations confirm the potential of MAJIS for detecting key spectral features with high signal to noise ratio so as to provide major contributions to the main goals of the mission: habitability and compositional diversity in the Jovian system.

In the last decade, several studies have reported enrichments of the heavy isotopes of moderately volatile elements in lunar mare basalts. However, the mechanisms controlling the isotope fractionation are still debated and may differ for elements with variable geochemical behaviour. Here, we present a new comprehensive dataset of mass-dependent copper isotope compositions (delta 65Cu) of 30 mare basalts sampled during the Apollo missions. The new delta 65Cu data range from +0.14 %o to +1.28 %o (with the exception of two samples at 0.01 %o and -1.42 %o), significantly heavier than chondrites and the bulk silicate Earth. A comparison with mass fractions of major and trace elements and thermodynamic constraints reveals that Cu isotopic variations within different mare basalt suites are mostly unrelated to fractional crystallisation of silicates or oxides and late-stage magmatic degassing. Instead, we propose that the delta 65Cu average of each suite is representative of the composition of its respective mantle source. The observed differences across geographically and temporally distinct mare basalt suites, suggest that this variation relates to large-scale processes that formed isotopically distinct mantle sources. Based on a Cu isotope fractionation model during metal melt saturation in crystal mush zones of the lunar magma ocean, we propose that distinct delta 65Cu compositions and Cu abundances of mare basalt mantle sources reflect local metal melt-silicate melt equilibration and trapping of metal in mantle cumulates during lunar magma ocean solidification. Differences in delta 65Cu and mass fractions and ratios of siderophile elements between low- and high-Ti mare basalt sources reflect the evolving compositions of both metal and silicate melt during the late cooling stages of the lunar magma ocean.

This study investigated how soil properties affect levee erosion and foundation scouring by evaluating the behavior of loose and cohesive (mixed) soils beneath a rigid crest under overflow conditions and analyzing flow dynamics within the scoured hole to understand the scouring mechanism. Four cases were examined with varying overtopping depths (Od): LS-FS, LS-FM, and LM-FS, at Od = 2 cm, and LS-FM at Od = 3 cm, where 'L' stands for levee, 'F' for foundation, 'S' for sand (#8), and 'M' for mixed soil (20% silt + 80% sand #8). The results revealed distinct differences among the cases. Notably, erosion of the back slope in the LM-FS case was delayed fourfold compared to LS-FS. In the LS-FM case, breaching of the levee body was delayed by 1.6 times compared to the LS-FS case with a 2 cm overtopping depth. Moreover, different scour hole geometries with complex flow patterns occurred in different timespans. Particle image velocimetry (PIV) was utilized on two physical scoured hole models to analyze the flow behavior within these scoured holes. The PIV analysis revealed the formation of twin eddies, moving in opposite directions and shaped by the nappe flow jet, which was instrumental in the development of the scour holes. This study found that foundation cohesion is more essential than the levee body in delaying levee breaches under rigid crest. Additionally, it revealed the role of twin eddies, especially the levee-side eddy, in increasing the size of the scoured hole upstream and causing levee breaches.

Arbuscular mycorrhizal (AM) fungi are important plant symbionts that provide plants with nutrients and water as well as support plant defences against pests and disease. Consequently, they present a promising alternative to using environmentally damaging and costly fertilisers and pesticides in agricultural systems. However, our limited understanding of how agricultural practices impact AM fungal diversity and functions is a key impediment to using them effectively in agriculture. We assessed how organic and conventional agricultural management systems shaped AM fungal communities. We also investigated how AM fungal communities derived from these agricultural management systems affected crop biomass and development. Six soil samples from five organically and five conventionally managed agricultural sites were used to cultivate Sorghum bicolor. Plant growth, plant nutrient concentrations and AM fungal colonisation rates were analysed alongside DNA metabarcoding of community composition. We observed that soil from conventional agricultural fields resulted in a pronounced reduction in sorghum biomass (-53.6%) and a significant delay in flowering compared to plants grown without AM fungi. Sorghum biomass was also reduced with soil from the organic system, but to a lesser extent (-30%) and without a delay in flowering. Organic systems were associated with a large proportion of AM fungal taxa (50.5% of VTs) not found in conventional systems, including Diversispora (r(2) = 0.09, p < 0.001), Archaeospora (r(2) = 0.07, p < 0.001) and Glomus (r(2) = 0.25, p < 0.001) spp., but also shared a large proportion of taxa with conventional systems (42.3% of VTs). Conventional systems had relatively few unique taxa (7.2% of VTs). Our results suggest that conventional agricultural practices selected against AM fungi that were, in this context, more beneficial for host plants. In contrast, organic management practices mitigate this negative effect, likely due to the presence of specific key AM fungal taxa. However, this mitigation is only partial, as less beneficial AM fungal taxa still persist, probably due to abiotic factors associated with agricultural management and the sensitivity of AM fungi to these factors. This persistence explains why the effect is not entirely eradicated. Read the free Plain Language Summary for this article on the Journal blog.

Ongoing climate warming and increased human activities have led to significant permafrost degradation on the Qinghai-Tibet Plateau (QTP). Mapping the distribution of active layer thickness (ALT) can provide essential information for understanding this degradation. Over the past decade, InSAR (Interferometric synthetic aperture radar) technology has been utilized to estimate ALT based on remotely-sensed surface deformation information. However, these methods are generally limited by their ability to accurate extract seasonal deformation and model subsurface water content of active layer. In this paper, an ALT inversion method considering both seasonal deformation from InSAR and smoothly multilayer soil moisture from ERA5 is proposed. Firstly, we introduce a ground seasonal deformation extraction model combining RobustSTL and InSAR, and the deformation extraction accuracy by considering the deformation characteristics of permafrost are evaluated, proving the effectiveness of RobustSTL in extracting seasonal deformation of permafrost. Then, using ERA5 soil moisture products, a smoothed multilayer soil moisture model for ALT inversion is established. Finally, integrating the seasonal deformation and multilayer soil moisture, the ALT can be estimated. The proposed model is applied to the Yellow River source region (YRSR) with Sentinel-1A images acquired from 2017 to 2021, and the ALT retrieval accuracy is validated with measured data. Experimental results show that the vertical deformation rate of the study area generally ranges from -30 mm/year to 20 mm/year, with seasonal deformation amplitude ranging from 2 mm to 30 mm. The RobustSTL method has the highest accuracy in extracting seasonal deformation of permafrost, with an RMSE (root mean square error) of 0.69 mm, and is capable of capturing the freeze-thaw characteristics of the active layer. The estimated ALT of the YRSR ranges from 49 cm to 450 cm, with an average value of 145 cm. Compared to the measured data, the proposed method has an average error of 37.5 cm, which represents a 21 % improvement in accuracy over existing methods.

This paper provides a report on a test that was carried out over 20 years ago to demonstrate that two 3He gas proportional neutron sensors could survive a high-impact penetrator test. This test was carried out as part of a risk reduction effort for a proposed mission that would send multiple penetrators to landing locations within lunar permanently shaded regions (PSRs). After landing, the neutron sensors would carry out in situ measurements within the PSRs to quantify the hydrogen abundances within these regions. Two penetrator shots were successfully carried out with the neutron sensors enclosed in the penetrators. The deceleration value for the shots exceeded 1,400 G's over less than 20 milliseconds. Pre- and post-penetration measurements of the 3He sensors show that the sensors themselves suffered no degradation in performance; one non-spaceflight quality high-voltage connector did indicate performance degradation. These results provide confidence that these types of 3He neutron sensors could be successfully used in a future penetrator mission to a planetary body.

Accurate structural health monitoring (SHM) is crucial for ensuring safety and preventing catastrophic failures. However, conventional parameter identification methods often assume a fixed-base foundation, neglecting the significant influence of soil-structure interaction (SSI) on the dynamic response, leading to inaccurate damage assessments, especially under seismic loading. Therefore, we introduce a novel approach that explicitly incorporates SSI effects into parameter identification for frame structures, utilizing an optimized variational mode decomposition (VMD) technique. The core innovation is the application of the Subtraction Average-Based Optimizer (SABO) algorithm, coupled with permutation entropy as the fitness function, to optimize the critical VMD parameters. This SABO-VMD method was rigorously validated through a shaking table test on a 12-story frame structure on soft soil. Comparative analysis with EMD and conventional VMD demonstrated that SABO-VMD provides a superior time-frequency representation of the structural response, capturing non-stationary characteristics more effectively. A novel energy entropy index, derived from the SABO-VMD output with SSI, was developed for quantitative damage assessment. It revealed 8.1% lower degree of structural damage compared to the fixed-base assumption. The proposed SABO-VMD-based approach, by explicitly accounting for SSI, offers a substantial advancement in SHM of frame structures, leading to more reliable safety evaluations and improved seismic resilience.

The seismic effects of complex, deep, and inhomogeneous sites constitute a significant research topic. Utilizing geological borehole data from the Suzhou urban area, a refined 2D finite element model with nonuniform meshes of a stratigraphic crossing the Suzhou region was established. Within the ABAQUS/explicit framework, the spatial inhomogeneity of soils, including the spatial variation of S-wave velocity structures, was considered in detail. The nonlinear and hysteretic stress-strain relationship of soil was characterized using a non-Masing constitutive model. Ricker wavelets with varying peak times, peak frequencies (fp), and amplitudes were selected as input bedrock motions. The analysis revealed the spatial distribution characteristics of 2D nonlinear seismic effects on the surface of deep and complex sedimentary layers. The surface peak ground acceleration (PGA) amplification coefficients initially increased and then decreased as fp increases. The surface PGA amplification was most pronounced when the fp is close to the site fundamental frequency. Additionally, when fp = 0.1 Hz, the surface PGA amplification was found to depend solely on the level of bedrock seismic shaking, with amplification factors ranging from 1.20 to 1.40. Furthermore, the ensemble empirical mode decomposition components of seismic site responses can intuitively reveal the variations in time-frequency and time-energy characteristics of Ricker wavelets as they propagate upward from bedrock to surface.

The Arctic experiences rapid climate change, but our ability to predict how this will influence plant communities is hampered by a lack of data on the extent to which different species are associated with particular environmental conditions, how these conditions are interlinked, and how they will change in coming years. Increasing temperatures may negatively affect plants associated with cold areas due to increased competition with warm-adapted species, but less so if local temperature variability is larger than the expected increase. Here we studied the potential drivers of vegetation composition and species richness along coast to inland and altitudinal gradients by the Nuuk fjord in western Greenland using hierarchical modelling of species communities (HMSC) and linear mixed models. Community composition was more strongly associated with random variability at intermediate spatial scales (among plot groups 500 m apart) than with large-scale variability in summer temperature, altitude or soil moisture, and the variation in community composition along the fjord was small. Species richness was related to plant cover, altitude and slope steepness, which explained 42% of the variation, but not to summer temperature. Jointly, this suggests that the direct effect of climate change will be weak, and that many species are associated with microhabitat variability. However, species richness peaked at intermediate cover, suggesting that an increase in plant cover under warming climatic conditions may lead to decreasing plant diversity.

Excessive bromine, iodine and dyes can damage soil structure and aquatic ecosystems. Therefore, capturing toxic bromine, iodine and dyes from nuclear fuel waste and organic waste liquid is crucial for protecting the environment and human health. In this study, a tridentate imide acid monomer was synthesized with various functional groups and structures, including carboxyl (-COOH), amide (-CONH), and imide rings, to construct a new type of hyper-crosslinked poly (amide-imide) (PAI1-PAI4). Subsequently, porous carbons (PAI1-900-PAI4900) were prepared, and urea was doped during the secondary carbonization process. The ammonia gas (NH3) and carbon dioxide (CO2) generated from the high-temperature decomposition of urea can be trapped by the porous structure of the carbon-based derivatives, and these gases then react with the carbon in the porous carbon and the N-H/C-H in the amide groups, thus resulting in carbon-based materials (PAI1-U-900-PAI4-U-900) with multiple nitrogen and oxygen Lewis basic sites (C-N/N-O/C--O/-OH) and a moderate porosity. These materials enhanced the interactions between the adsorbent and bromine, iodine, and anionic dyes, and exhibited selective adsorption effects for bromide and Congo red (CR).