Dynamics and drivers of mycorrhizal fungi after glacier retreat.

The development of terrestrial ecosystems depends greatly on plant mutualists such as mycorrhizal fungi. The global retreat of glaciers exposes nutrient-poor substrates in extreme environments and provides a unique opportunity to study early successions of mycorrhizal fungi by assessing their dynamics and drivers. We combined environmental DNA metabarcoding and measurements of local conditions to assess the succession of mycorrhizal communities during soil development in 46 glacier forelands around the globe, testing whether dynamics and drivers differ between mycorrhizal types. Mycorrhizal fungi colonized deglaciated areas very quickly (< 10 yr), with arbuscular mycorrhizal fungi tending to become more diverse through time compared to ectomycorrhizal fungi. Both alpha- and beta-diversity of arbuscular mycorrhizal fungi were significantly related to time since glacier retreat and plant communities, while microclimate and primary productivity were more important for ectomycorrhizal fungi. The richness and composition of mycorrhizal communities were also significantly explained by soil chemistry, highlighting the importance of microhabitat for community dynamics. The acceleration of ice melt and the modifications of microclimate forecasted by climate change scenarios are expected to impact the diversity of mycorrhizal partners. These changes could alter the interactions underlying biotic colonization and belowground-aboveground linkages, with multifaceted impacts on soil development and associated ecological processes.

Local climate modulates the development of soil nematode communities after glacier retreat.

The worldwide retreat of glaciers is causing a faster than ever increase in ice-free areas that are leading to the emergence of new ecosystems. Understanding the dynamics of these environments is critical to predicting the consequences of climate change on mountains and at high latitudes. Climatic differences between regions of the world could modulate the emergence of biodiversity and functionality after glacier retreat, yet global tests of this hypothesis are lacking. Nematodes are the most abundant soil animals, with keystone roles in ecosystem functioning, but the lack of global-scale studies limits our understanding of how the taxonomic and functional diversity of nematodes changes during the colonization of proglacial landscapes. We used environmental DNA metabarcoding to characterize nematode communities of 48 glacier forelands from five continents. We assessed how different facets of biodiversity change with the age of deglaciated terrains and tested the hypothesis that colonization patterns are different across forelands with different climatic conditions. Nematodes colonized ice-free areas almost immediately. Both taxonomic and functional richness quickly increased over time, but the increase in nematode diversity was modulated by climate, so that colonization started earlier in forelands with mild summer temperatures. Colder forelands initially hosted poor communities, but the colonization rate then accelerated, eventually leveling biodiversity differences between climatic regimes in the long term. Immediately after glacier retreat, communities were dominated by colonizer taxa with short generation time and r-ecological strategy but community composition shifted through time, with increased frequency of more persister taxa with K-ecological strategy. These changes mostly occurred through the addition of new traits instead of their replacement during succession. The effects of local climate on nematode colonization led to heterogeneous but predictable patterns around the world that likely affect soil communities and overall ecosystem development.

The importance of species addition 'versus' replacement varies over succession in plant communities after glacier retreat.

The mechanisms underlying plant succession remain highly debated. Due to the local scope of most studies, we lack a global quantification of the relative importance of species addition 'versus' replacement. We assessed the role of these processes in the variation (ß-diversity) of plant communities colonizing the forelands of 46 retreating glaciers worldwide, using both environmental DNA and traditional surveys. Our findings indicate that addition and replacement concur in determining community changes in deglaciated sites, but their relative importance varied over time. Taxa addition dominated immediately after glacier retreat, as expected in harsh environments, while replacement became more important for late-successional communities. These changes were aligned with total ß-diversity changes, which were more pronounced between early-successional communities than between late-successional communities (>50 yr since glacier retreat). Despite the complexity of community assembly during plant succession, the observed global pattern suggests a generalized shift from the dominance of facilitation and/or stochastic processes in early-successional communities to a predominance of competition later on.

Remanence Increase in SrFe12O19/Fe Exchange-Decoupled Hard-Soft Composite Magnets Owing to Dipolar Interactions.

In the search for improved permanent magnets, fueled by the geostrategic and environmental issues associated with rare-earth-based magnets, magnetically hard (high anisotropy)-soft (high magnetization) composite magnets hold promise as alternative magnets that could replace modern permanent magnets, such as rare-earth-based and ceramic magnets, in certain applications. However, so far, the magnetic properties reported for hard-soft composites have been underwhelming. Here, an attempt to further understand the correlation between magnetic and microstructural properties in strontium ferrite-based composites, hard SrFe12O19 (SFO) ceramics with different contents of Fe particles as soft phase, both in powder and in dense injection molded magnets, is presented. In addition, the influence of soft phase particle dimension, in the nano- and micron-sized regimes, on these properties is studied. While Fe and SFO are not exchange-coupled in our magnets, a remanence that is higher than expected is measured. In fact, in composite injection molded anisotropic (magnetically oriented) magnets, remanence is improved by 2.4% with respect to a pure ferrite identical magnet. The analysis of the experimental results in combination with micromagnetic simulations allows us to establish that the type of interaction between hard and soft phases is of a dipolar nature, and is responsible for the alignment of a fraction of the soft spins with the magnetization of the hard. The mechanism unraveled in this work has implications for the development of novel hard-soft permanent magnets.

Using small-angle scattering to guide functional magnetic nanoparticle design.

Magnetic nanoparticles offer unique potential for various technological, biomedical, or environmental applications thanks to the size-, shape- and material-dependent tunability of their magnetic properties. To optimize particles for a specific application, it is crucial to interrelate their performance with their structural and magnetic properties. This review presents the advantages of small-angle X-ray and neutron scattering techniques for achieving a detailed multiscale characterization of magnetic nanoparticles and their ensembles in a mesoscopic size range from 1 to a few hundred nanometers with nanometer resolution. Both X-rays and neutrons allow the ensemble-averaged determination of structural properties, such as particle morphology or particle arrangement in multilayers and 3D assemblies. Additionally, the magnetic scattering contributions enable retrieving the internal magnetization profile of the nanoparticles as well as the inter-particle moment correlations caused by interactions within dense assemblies. Most measurements are used to determine the time-averaged ensemble properties, in addition advanced small-angle scattering techniques exist that allow accessing particle and spin dynamics on various timescales. In this review, we focus on conventional small-angle X-ray and neutron scattering (SAXS and SANS), X-ray and neutron reflectometry, gracing-incidence SAXS and SANS, X-ray resonant magnetic scattering, and neutron spin-echo spectroscopy techniques. For each technique, we provide a general overview, present the latest scientific results, and discuss its strengths as well as sample requirements. Finally, we give our perspectives on how future small-angle scattering experiments, especially in combination with micromagnetic simulations, could help to optimize the performance of magnetic nanoparticles for specific applications.

On the Problem of Restoring and Classifying a 3D Object in Creating a Simulator of a Realistic Urban Environment.

Since the 20th century, a rapid process of motorization has begun. The main goal of researchers, engineers and technology companies is to increase the safety and optimality of the movement of vehicles, as well as to reduce the environmental damage caused by the automotive industry. The difficulty of managing traffic flows is that cars are driven by a person and their behavior, even in similar situations, is different and difficult to predict. To solve this problem, ground-based unmanned vehicles are increasingly being developed and implemented; however, like any other intelligent system, it is necessary to train different road scenarios. Currently, an engineer is driving an unmanned vehicle for training and thousands of kilometers are being driven for training. Of course, this approach to training unmanned vehicles is very long, and it is impossible to reproduce all the scenarios that can be found in real operations on a real road. Based on this, we offer a simulator of a realistic urban environment which allows you to reduce the training time and allows you to generate all kinds of events. To implement such a simulator, it is necessary to develop a method that would allow recreating a realistic world in one passage with cameras (monocular) installed on board the vehicle. Based on this, the purpose of this work is to develop an intelligent vehicle recognition system using convolutional neural networks, which allows you to create mesh objects for further placement in the simulator. It is important to note that the resulting objects should be optimal in size so as not to overload the system, since a large number of road infrastructure objects are stored there. Also, neural complexity should not be excessive. In this paper, the general concept and classification of convolutional neural networks are given, which allow solving the problem of recognizing 3D objects in images. Based on the analysis, the existing neural network architectures do not solve the problems mentioned above. In this connection, the authors first of all carried out the design of the system according to the methodology of modeling business processes, and also modified and developed the architecture of the neural network, which allows classifying objects with sufficient accuracy, obtaining optimized mesh objects and reducing computational complexity. The methods proposed in this paper are used in a simulator of a realistic urban environment, which reduces the time and computational costs when training unmanned transport systems.

Toward Understanding Complex Spin Textures in Nanoparticles by Magnetic Neutron Scattering.

In the quest to image the three-dimensional magnetization structure we show that the technique of magnetic small-angle neutron scattering (SANS) is highly sensitive to the details of the internal spin structure of nanoparticles. By combining SANS with numerical micromagnetic computations we study the transition from single-domain to multidomain behavior in nanoparticles and its implications for the ensuing magnetic SANS cross section. Above the critical single-domain size we find that the cross section and the related correlation function cannot be described anymore with the uniform particle model, resulting, e.g., in deviations from the well-known Guinier law. In the simulations we identify a clear signature for the occurrence of a vortexlike spin structure at remanence. The micromagnetic approach to magnetic SANS bears great potential for future investigations, since it provides fundamental insights into the mesoscale magnetization profile of nanoparticles.

Investigation of magnetically driven passage of magnetic nanoparticles through eye tissues for magnetic drug targeting.

This paper elucidates the feasibility of magnetic drug targeting to the eye by using magnetic nanoparticles (MNPs) to which pharmaceutical drugs can be linked. Numerical simulations revealed that a magnetic field gradient of 20 T m-1 seems to be promising for dragging magnetic multicore nanoparticles of about 50 nm into the eye. Thus, a targeting magnet system made of superconducting magnets with a magnetic field gradient at the eye of about 20 T m-1 was simulated. For the proof-of-concept tissue experiments presented here the required magnetic field gradient of 20 T m-1 was realized by a permanent magnet array. MNPs with an optimized multicore structure were selected for this application by evaluating their stability against agglomeration of MNPs with different coatings in water for injections, physiological sodium chloride solution and biological media such as artificial tear fluid. From these investigations, starch turned out to be the most promising coating material because of its stability in saline fluids due to its steric stabilization mechanism. To evaluate the passage of MNPs through the sclera and cornea of the eye tissues of domestic pigs (Sus scrofa domesticus), a three-dimensionally printed setup consisting of two chambers (reservoir and target chamber) separated by the eye tissue was developed. With the permanent magnet array emulating the magnetic field gradient of the superconducting setup, experiments on magnetically driven transport of the MNPs from the reservoir chamber into the target chamber via the tissue were performed. The resulting concentration of MNPs in the target chamber was determined by means of quantitative magnetic particle spectroscopy. It was found that none of the tested particles passed the cornea, but starch-coated particles could pass the sclera at a rate of about 5 ng mm-2 within 24 h. These results open the door for future magnetic drug targeting to the eye.

Putting the poorly documented 1998 GLOF disaster in Shakhimardan River valley (Alay Range, Kyrgyzstan/Uzbekistan) into perspective.

On July 8, 1998, the deadliest glacier lake outburst flood (GLOF) in Central Asia for at least the last 100 years occurred in the Shakhimardan catchment, Kyrgyzstan. Most of the >100 victims were, however, killed in the Uzbek enclave of Shakhimardan, i.e. in the downstream part of this transboundary catchment. No warnings were issued between the two countries. In addition, due to political tensions, access to the site was impossible and a detailed assessment of the disaster could not be realized until now. Using remote sensing, we show that the lake at the origin of the "Shakhimardan event" appeared in the 1960s and drained periodically, without, however, causing damage to downstream areas before it eventually disappeared in the late 1980s. Based on post-event videos, we conclude that the GLOF-producing depression was again filled with a lake, estimated at 20 ± 1.2 × 103 m2 in area, before the disaster. The lake burst was likely driven by the rapidly rising air temperatures and the melting of snow/ice in late June and early July. The GLOF first travelled as a debris flow for 17 km, then continued as a debris flood in the increasingly flatter channel for another 20 km. Interestingly, the mean weighted channel angle in the areas of erosion was extremely low at 6.7°. The flood continued further downstream for ~100 km from its source. Today, 32 lakes (total area ~300 × 103 m2 in 2018) exist in the catchment, with several of the larger lakes (>5 × 103 m2) showing signs of instability. We therefore call for a systematic monitoring of environments like the Shakhimardan catchment, as well as for the installation of early warning systems at critical sites, with exchange of data between the Kyrgyz and Uzbek disaster risk management units, so as to mitigate existing and evolving GLOF risks.

Towards understanding of magnetization reversal in Nd-Fe-B nanocomposites: analysis by high-throughput micromagnetic simulations.

We demonstrate how micromagnetic simulations can be employed in order to characterize and analyze the magnetic microstructure of nanocomposites. For the example of nanocrystalline Nd-Fe-B, which is a potential material for future permanent-magnet applications, we have compared three different models for the micromagnetic analysis of this material class: (i) a description of the nanocomposite microstructure in terms of Stoner-Wohlfarth particles with and without the magnetodipolar interaction; (ii) a model based on the core-shell representation of the nanograins; (iii) the latter model including a contribution of superparamagnetic clusters. The relevant parameter spaces have been systematically scanned with the aim to establish which micromagnetic approach can most adequately describe experimental data for this material. According to our results, only the last, most sophisticated model is able to provide an excellent agreement with the measured hysteresis loop. The presented methodology is generally applicable to multiphase magnetic nanocomposites and it highligths the complex interrelationship between the microstructure, magnetic interactions, and the macroscopic magnetic properties.