Explore the vast range of titles available.

A compact new X-ray reflectometer setup was realized, with a main design focus on mechanical stability and ruggedness, allowing in particular the change from a horizontal to a vertical scattering geometry, this way enabling polarization dependent experiments, and an easy transfer from one beamline to another. An additional mirror system was established, that allows to deflect the beam downwards to also render investigations of liquid sample surfaces possible. The layout of the reflectometer setup is described, and some representative grazing incidence EXAFS measurements outlining the experimental capabilities of the system are presented.

High-entropy and medium-entropy alloys are presumed to have a configurational entropy as high as that of an ideally mixed solid solution (SS) of multiple elements in near-equal proportions. However, enthalpic interactions inevitably render such chemically disordered SSs rare and metastable, except at very high temperatures. Here we highlight the wide variety of local chemical ordering (LCO) that sets these concentrated SSs apart from traditional solvent-solute ones. Using atomistic simulations, we reveal that the LCO of the multi-principal-element NiCoCr SS changes with alloy processing conditions, producing a wide range of generalized planar fault energies. We show that the LCO heightens the ruggedness of the energy landscape and raises activation barriers governing dislocation activities. This influences the selection of dislocation pathways in slip, faulting, and twinning, and increases the lattice friction to dislocation motion via a nanoscale segment detrapping mechanism. In contrast, severe plastic deformation reduces the LCO towards random SS. Multi-principal-element alloys have been assumed to have the configurational entropy of an ideal solution. Here, the authors use atomistic simulations to show that instead NiCoCr exhibits local chemical order, raising the activation barriers of dislocation activities to elevate mechanical strength.

Active metasurfaces promise reconfigurable optics with drastically improved compactness, ruggedness, manufacturability and functionality compared to their traditional bulk counterparts. Optical phase-change materials (PCMs) offer an appealing material solution for active metasurface devices with their large index contrast and non-volatile switching characteristics. Here we report a large-scale, electrically reconfigurable non-volatile metasurface platform based on optical PCMs. The optical PCM alloy used in the devices, Ge 2 Sb 2 Se 4 Te (GSST), uniquely combines giant non-volatile index modulation capability, broadband low optical loss and a large reversible switching volume, enabling notably enhanced light–matter interactions within the active optical PCM medium. Capitalizing on these favourable attributes, we demonstrated quasi-continuously tuneable active metasurfaces with record half-octave spectral tuning range and large optical contrast of over 400%. We further prototyped a polarization-insensitive phase-gradient metasurface to realize dynamic optical beam steering. An electrically reconfigurable optical metasurface using a Ge 2 Sb 2 Se 4 Te phase change material shows half an octave spectral tuning and promising performances for optical beam steering applications.

We study rough high-dimensional landscapes in which an increasingly stronger preference for a given configuration emerges. Such energy landscapes arise in glass physics and inference. In particular, we focus on random Gaussian functions and on the spiked-tensor model and generalizations. We thoroughly analyze the statistical properties of the corresponding landscapes and characterize the associated geometrical phase transitions. In order to perform our study, we develop a framework based on the Kac-Rice method that allows us to compute the complexity of the landscape, i.e., the logarithm of the typical number of stationary points and their Hessian. This approach generalizes the one used to compute rigorously the annealed complexity of mean-field glass models. We discuss its advantages with respect to previous frameworks, in particular, the thermodynamical replica method, which is shown to lead to partially incorrect predictions.

The genotype-phenotype map determines how genetic variation translates into traits, influencing evolutionary adaptability. While previous models often assume a static relationship, genetic architectures evolve dynamically in response to selective pressures. In this study, we investigate how epistasis and pleiotropy adapt under varying fitness landscape ruggedness (K) and environmental variability (V ) together, shaping genetic robustness and evolvability. Using the NK treadmill model, we systematically explore the independent effects of K and V on genetic complexity. Our findings reveal that increased ruggedness (K) reduces genetic interdependencies, favoring modular architectures that enhance mutational robustness. Conversely, higher environmental variability (V ) promotes interconnected genetic networks, increasing evolvability. Empirical validation using bacterial genomes supports these results, showing strong correlations between genetic complexity measures and mutational robustness, reinforcing the role of environmental pressures in shaping genetic architectures.

Terrain elevation variations (absolute and relative) play a special role in the organization of plain landscapes. They are most clearly observed in the form of zonal landscape vertical differentiation. Vertical relief transformation leads to formation of altitudinal landscape systems, which are dynamically and morphologically united groups of landscapes. They have a common altitudinal position and genesis under the influence of horizontal and vertical physiographic process. We have analyzed the influence of relative and absolute altitudes on morphometric parameters of the land surface as well as indicators of landscape-forming processes and textural terrain indicators, and so identified altitudinal landscape systems of different dimensions. A well-studied region in terms of landscape science, the Central Black Earth region, was the case study area. As a result of the study, we revealed spatial patterns in (i) the indicators of horizontal and vertical terrain ruggedness in relation to the absolute terrain altitudes at the level of landscape, and (ii) the morphometric indicators of terrain, landscape-forming processes and landscape shapes at the local level.

Living systems evolve one mutation at a time, but a single mutation can alter the effect of subsequent mutations. The underlying mechanistic determinants of such epistasis are unclear. Here, we demonstrate that the physical dynamics of a biological system can generically constrain epistasis. We analyze models and experimental data on proteins and regulatory networks. In each, we find that if the long-time physical dynamics is dominated by a slow, collective mode, then the dimensionality of mutational effects is reduced. Consequently, epistatic coefficients for different combinations of mutations are no longer independent, even if individually strong. Such epistasis can be summarized as resulting from a global nonlinearity applied to an underlying linear trait, that is, as global epistasis. This constraint, in turn, reduces the ruggedness of the sequence-to-function map. By providing a generic mechanistic origin for experimentally observed global epistasis, our work suggests that slow collective physical modes can make biological systems evolvable.

SRM is utilized in many industrial applications owing to its simple construction along with its ruggedness. While this feature is inherently present due to the robustness of SRM, it is not guaranteed a fail-safe and needs in-depth analysis for various operational circumstances. In rotating machines, one of the most general faults is Eccentricity which may lead to operational defects. A few end-users mistook this eccentricity as sloppy alignment, despite the essential need for it to diagnose and assess whether or not the motor’s left/right run-out is running true. This work reports simulations of the proposed model for comprehending SRM operational characteristics at low, medium and high severities under static, dynamic and mixed forms of eccentricity.

Soil pH is a key factor that controls soil nutrient availability, soil microbial activities, and crop growth and development. However, studies on the soil pH variations of cultivated lands in different horizons at the regional scale remain limited. In this work, 348 soil samples were collected from three soil horizons (A, B, and C) at 120 sites over the hilly region of Chongqing, southwestern China. Six topographic indicators, four climate parameters, and parent material were considered. Classification and regression trees (CARTs) were applied to investigate the relationships between soil pH and the variables in the A, B, and C horizons. Model performances were evaluated by root mean square error (RMSE), relative root mean square error (RRMSE), and coefficient of determination (R2). Results showed that soil pH increased obviously from the A to C horizons. Soil pH was predicted well by the forcing factors with the CART models in all horizons. RMSE, RRMSE, and R2 varied between 0.37 and 0.435, between 5.93 and 7.23%, and between 0.71 and 0.80, respectively. The relative importance of the studied variables to soil pH differed with the horizons. Annual temperature range (ATR), terrain wetness index (TWI), and Melton ruggedness number were critical factors that controlled soil pH variability in the A horizon. Parent material, precipitation of warmest quarter (PWQ), ATR, and TWI were important variables in the B horizon. Parent material, PWQ, ATR, and precipitation were key factors in the C horizon. The results are expected to provide valuable information for designing appropriate measurements for agricultural practices and preventing soil acidification.

Cervellini, M., Di Musciano, M., Zannini, P., Fattorini, S., Jiménez-Alfaro, B., Agrillo, E., Attorre, F., Angelini, P., Beierkuhnlein, C., Casella, L., Field, R., Fischer, J.-C., Genovesi, P., Hoffmann, S., Irl, S.D.H., Nascimbene, J., Rocchini, D., Steinbauer, M., Vetaas, O.R., Chiarucci, A.