Glasses are traditionally characterized by their rugged landscape of disordered low-energy states and their slow relaxation towards thermodynamic equilibrium. Far from equilibrium, dynamical forms of glassy behavior with anomalous algebraic relaxation have also been noted, for example, in networks of coupled oscillators. Due to their disordered and high-dimensional nature, such systems have been difficult to study theoretically, but data-driven methods are emerging as a promising alternative that may aid in their analysis. Here, we characterize glassy dynamics using the dynamic mode decomposition, a data-driven spectral computation that approximates the Koopman spectrum. We show that the gap between oscillatory and decaying modes in the Koopman spectrum vanishes in systems exhibiting algebraic relaxation, and thus, we propose a model-agnostic signature for robustly detecting and analyzing glassy dynamics. We demonstrate the utility of our approach through both a minimal example of a one-dimensional ODE and a high-dimensional example of coupled oscillators.
Although light nuclear clusters are known to form abundantly in warm and dilute nuclear matter, their role in hot and dense nuclear matter remains unclear due to the lack of experimental indication for their modifications by the Mott effect under such conditions. To address this issue, we resort to intermediate-energy heavy-ion collisions, where light clusters are mainly produced in the transiently formed hot and dense matter. A kinetic approach, which includes dynamically the formation and dissociation of light clusters, is employed to deduce the strength of the Mott effect and the α-particle fraction in hot and dense nuclear matter from the light-nuclei yields measured by the FOPI Collaboration in central Au+Au collisions at energies of 0.25A to 0.6A  GeV. We find an unexpectedly abundant α clustering in this environment, which will have profound implications for modeling the nuclear equation of state and describing supernovae and neutron star mergers.
暂无摘要（点击查看详情）
Nsp15 is an endoribonuclease, highly conserved among coronaviruses, that helps the virus evade detection in host cells by cleaving uridine-rich viral RNA sequences. Those sequences would otherwise trigger immune response pathways. Its essential role in pathogenesis and highly conserved nature make Nsp15 an attractive target for therapeutic intervention. While its crystal structure and uridine specificity are well-established, the influence of RNA structural dynamics and divalent cations on Nsp15 activity remains less understood. Leveraging single-molecule Pulsed Interleaved Excitation (PIE)-FRET and Fluorescence Correlation Spectroscopy (FCS) in combination, we developed an assay to track RNA cleavage by Nsp15 variants in real time and monitor the conformational dynamics of hybrid RNA/DNA substrates. Using our methodology and analysis strategies, we obtained clear indicators of RNA cleavage with both PIE-FRET and FCS data analysis. Our assay also revealed signatures of unique dynamic behavior in uridine-containing RNA substrates, indicating that divalent cations enhance substrate flexibility, which is associated with a faster observed reaction rate of RNA cleavage by Nsp15 in the presence of Mn2+. We propose that divalent cations induce a conformation that may be more favorable for cleavage in single-stranded RNA substrates that mediate the efficient nuclease activity of Nsp15.
We review the key observations and theories relevant to the origin and evolution of the Galilean satellites. Key observations include: the potentially undifferentiated nature of Callisto; the increasing ice fraction with semi-major axis; the present-day existence of the Laplace resonance; the potential resurfacing of Ganymede mid-way through its evolution; and the metal-enriched nature of Jupiter's envelope. The most widely accepted theory for the formation of the satellites is the so-called "starved disk" model, although newer alternatives including decretion disks and pebble accretion have also been proposed. Models that allow slow satellite formation in a cold disk are preferred, based on the density progression and Callisto's apparent differentiation state. Major model uncertainties include the angular momentum distribution of the material infalling to the circumplanetary disk, the source of the solids, and the thermal and viscosity structure of the disk. We identify six outstanding questions, some of which will be answered by JUICE, Europa Clipper and Tianwen-4. A major difficulty in answering some questions is overprinting of primordial characteristics by later events.
Silk protein ionomer-based layer-by-layer (LBL) nanocoating strategy was utilized to preserve the viability, metabolic activity and differentiation potential of human mesenchymal stem cells (hMSCs) in an in vitro inflamed osteoarthritis (OA) tissue niche. These temporary ionomer coatings for cell protection were functionalized with cytokines to impart immune-modulatory behavior. The cytokine-functionalized ionomer nanocoatings polarized neutral M0 macrophages into M1 and M2 subtypes, depending on the specific cytokine used, thereby reducing synovial inflammation in an in vitro setup. This approach would potentially abrogate the need for ex vivo polarization before transplantation during immunotherapy. The modular nature of these silk ionomer nanocoatings in tailoring cell surface stability was further validated by extending the cell coatings to 3D spheroids and also by introducing tyramine to the cationic silk ionomer to facilitate covalent crosslinking in addition to the electrostatic interactions between the cell surface and the ionomers. These results demonstrate the versatile and modular nature of silk-based ionomer cell nanocoatings, allowing control at material, cellular, and spheroid levels to tune coating stability and inflammatory responses. These systems uniquely impart immunomodulatory function, providing a biomaterial platform for cell-based immune-regenerative therapy, such as for OA and other inflammatory diseases.
The study of dense matter has been greatly advanced by progress in theoretical high-energy simulations and modern observational astronomy. Neutron stars serve as natural laboratories for probing matter under extreme density and strong gravitational fields. While polytropic equations of state are widely employed, conventional models based on a single polytropic index cannot adequately represent the stratified, layered nature of realistic compact-star interiors. To address this limitation, we develop a composite relativistic polytropic model in which the polytropic index varies smoothly with radius. By coupling the Einstein field equations with a generalized composite polytropic equation of state, we derive the composite Tolman-Oppenheimer-Volkoff (CTOV) system. The resulting nonlinear equations are solved using a Monte Carlo-based numerical integration method, which efficiently handles stiffness while enabling probabilistic exploration of the parameter space and natural uncertainty quantification. Our results demonstrate that increasing the relativistic parameter σ significantly reduces both the Emden function and the enclosed mass function, producing more compact stellar configurations. Sharper core-envelope transitions (ε = 0.01) yield systematically higher compactness than smoother transitions (ε = 0.03). The derived mass-radius relations reproduce the observed diversity of neutron stars, successfully matching both low-mass, large-radius systems such as PSR J0030 + 0451 and high-mass compact pulsars such as PSR J1614-2230. Importantly, the maximum-mass analysis shows that stiff composite configurations (nc = 1, ne = 2, xc = 0.7) can support gravitational masses up to Mmax ≈ 3.47 M[Formula: see text] for ε = 0.01 and Mmax ≈ 2.71 M[Formula: see text] for ε = 0.03, with corresponding minimum radii in the range Rmin ≈ 10.6-13.2 km, consistent with current observational constraints. These findings confirm that composite polytropes provide a flexible, physically motivated framework for modeling stratified compact stars and for constraining the dense-matter equation of state.
We present the first experimental evidence for in-ice Askaryan radiation-coherent charge-excess radio emission-from high-energy particle cascades developing in the Antarctic ice sheet. In 208 days of data recorded with the phased array instrument of the Askaryan Radio Array, a previous analysis has incidentally identified 13 events with impulsive radio frequency signals originating from below the ice surface. We here present a detailed reanalysis of these events. The observed event rate, radiation arrival directions, signal shape, spectral content, and electric field polarization are consistent with in-ice Askaryan radiation from cosmic ray air shower cores impacting the ice sheet. For the brightest events, the angular radiation pattern favors an extended cascadelike emitter over a pointlike source. An origin from the geomagnetic separation of charges in cosmic ray air showers is disfavored by the arrival directions and polarization. Considering the arrival angles, timing properties, and impulsive nature of the passing events, the event rate is inconsistent with the estimation of the combined background from thermal noise events and on-surface events at the level of 5.1σ.
Interstellar objects provide the only directly observable samples of icy planetesimals formed around other stars, and can therefore provide insight into the diversity of physical and chemical conditions occurring during exoplanet formation1-3. Here we report isotopic measurements of the interstellar comet 3I/ATLAS, which reveal an elemental composition unlike any Solar System body. The water in 3I/ATLAS is enriched in deuterium, at a level of D/H = (0.98 ± 0.06)%, which is more than an order of magnitude higher than in known comets, while its range of 12C/13C ratios (141-191 for CO2 and 123-172 for CO) exceeds typical values found in the Solar System, as well as nearby interstellar clouds and protoplanetary disks. Such extreme isotopic signatures indicate formation at temperatures  ≲ 30 K in a relatively metal-poor environment. When interpreted with respect to models for Galactic chemical evolution, the carbon isotopic composition implies that 3I/ATLAS may have accreted as long ago as 12 billion years, following a period of intense, early star formation. 3I/ATLAS thus represents a preserved fragment of an ancient planetary system.
Light beams possessing orbital angular momentum (OAM) have gained significant interest in areas such as optical manipulation, quantum entanglement, and super-resolved imaging. The OAM per photon of such beams, typically Laguerre-Gaussian beams, is directly proportional to the azimuthal index l. This index is continuous in nature and a non-trivial parameter to measure. In this study, Laguerre-Gaussian beams of differing l are generated through mode conversion using microscopic spiral phase plates. The value of l depends on the refractive index of the medium surrounding the spiral phase plates. Utilising laser speckle, we demonstrate an ultra-precise measurement of the azimuthal index of the generated beams to a precision of 2 × 10-5. In turn, this enables an ultra-precise measurement of the refractive index of the medium surrounding the spiral phase plates, with a best measured precision of 6.4  ×  10-7 refractive index units. Our study interrogates samples of sucrose and haemoglobin, only 300 pL in volume, within a microfluidic channel.
Plant cytochrome P450 enzymes are central to natural product biosynthesis, but remain difficult to express in microbial hosts due to their transmembrane nature. Lysate-based, cell-free expression systems allow supplementation with artificial membranes to support the expression and translocation of transmembrane proteins. We developed a framework to systematically test liposomal membrane compositions to enhance the plant P450 expression yield. Adjustments to common phospholipid ratios or the addition of plant galactolipids had minimal impact on expression. In contrast, blended liposomes containing Egg PC, sterol-conjugated phospholipids, and PEGylated lipids produced concentration-dependent increases in expression. Expression of an Escherichia coli mechanosensitive channel and three plant P450s improved more than 2-fold, with some P450s showing up to 14-fold enhancement. These findings highlight membrane composition as a key determinant of the P450 expression yield in cell-free expression systems. While P450 activity was not measured, these findings provide a framework for future workflows toward achieving functional plant transmembrane enzymes for the bioproduction of natural products.
Spin glasses are magnetic materials exhibiting numerous magnetization patterns, that randomly vary both in real space and in time. To date, it is still not well understood what the nature of these spatiotemporal dynamics is, namely if they are completely random or if there are relevant and correlated length and time scales. Here, we demonstrate dynamic heterogeneity in the aging dynamics of elemental neodymium. We used spin-polarized scanning tunneling microscopy in combination with atomistic spin dynamics simulations to image the locally ordered magnetic patterns in the self-induced spin glass state and tracked the induced spatiotemporal dynamics in response to external perturbations. We observed that the real-space magnetization exhibited a coexistence of slow and fast dynamics coinciding with particular length scales. We adapted a wavelet paradigm to identify and correlate local spatial order with its dynamical evolution. These results provide a platform to study dynamics in spin glasses beyond the mean-field limit, linking to a generalized picture of glasses.
Solar radio bursts exhibit complex fine structures that reveal intricate coronal plasma dynamics. Here, we report detection of spike-like repeating burst pairs, characterized by two short-lived (0.1-2 s), narrowband components separated by about 4 s at frequencies 30-50 MHz. Using high-resolution dynamic spectra and spectroscopic imaging, we analyzed 613 burst pairs, measuring their durations, bandwidths, drift rates, flux densities, and spatial characteristics. Imaging links sources to an active region, with earlier components spatially concentrated above the region while delayed components are displaced and exhibit reduced drift rates. Radio-wave propagation simulations support the delayed bursts as turbulent echoes of harmonic emission in anisotropic coronal plasma. The location of the burst sources high in the corona suggests ongoing magnetic reconnection and electron acceleration well above typical flare heights. Our findings offer new insights into coronal turbulence effects while advancing diagnostics of coronal plasma and the elusive nature of solar radio echoes from ground-based transmitters.
The advent of van der Waals (vdW) heterostructures has enabled formation of bespoke materials with atomic precision, where numerous quantum and topological phenomena have already been discovered. This atomic-layer tunability, however, comes at a cost: individual 2D layers must be picked up, moved, and placed in a deterministic manner while keeping their interfaces atomically clean. Recent advances in machine learning and robotics place even stronger emphasis on the deterministic aspect of vdW assembly. Current polymer-based transfer methods satisfy neither the determinism nor cleanliness requirements. To this end, solutions are needed where adhesion can be dynamically and deterministically controlled without leaving organic contamination. Here, we present a polymer-free transfer technique employing thin muscovite (mica) crystals. Temperature control over mica adhesion enables deterministic pick-up, stacking, and release of 2D materials, while their crystalline, inorganic nature ensures pristine interfaces and suppresses strain. Fully compatible with existing fabrication workflows, this approach enables the assembly of demanding vdW heterostructures, including those with exposed conductive layers, moiré superlattices and suspended membranes. Our method represents a promising strategy for vdW heterostructure fabrication toward its automatisation.
Continuous-variable (CV) quantum key distribution (QKD) allows for quantum secure communication with the benefit of being close to classical coherent communication. In recent years, CV QKD protocols using a discrete number of displaced coherent states have been studied intensively as the modulation can be directly implemented with real devices with finite resolution. Until now, experiments only calculated key rates in the asymptotic regime. Here, we present a CV QKD system using discrete modulation that is especially designed for atmospheric channels. We use polarization encoding to exploit the nonbirefringent nature of the turbulent atmosphere. This allows to expand CV QKD networks beyond the existing fiber backbone. In a laboratory demonstration with a static 3-decibel loss channel, we implemented a recently developed security proof allowing to calculate composable finite-size key rates against independently and identically distributed collective attacks. We applied the full QKD protocol including a quantum random number generator, error correction, and privacy amplification to extract secret keys.
Structural frustration is believed to play a key role in suppressing crystallization and promoting glass formation, yet experimentally quantifying and understanding the structural frustration in glasses remains highly challenging. Here, we systematically investigate the structural evolution of a prototypical metallic glass-former, Cu46Zr42Al7Y5, during its glass transition and crystallization upon heating, using in-situ high-temperature high-energy synchrotron x-ray diffraction in combination with conventional and ultrafast differential scanning calorimetry. By probing the kinetic interplay between glass transition and crystallization over a broad range of heating rates, we identify a heating-rate-dependent crossover in the nature of the first exothermic process: at high rates it is associated with conventional-like crystallization, whereas at low rates it corresponds to a polyamorphic-like amorphous-amorphous transition. Quantitative analysis of the evolving medium- and short-range order reveals that these structural evolution pathways are governed by the competition between locally favored ordering and extended crystal-like ordering, providing direct experimental evidence that such structural competition can frustrate crystallization and stabilize the glassy state. These findings provide fundamental insights into the intricate relationship between structural frustration and structural stability in metallic glasses.
Accurate simulation of fluid flow in porous media is a challenging task due to the complexity of pore-space geometries and the computational cost of solving the Navier-Stokes equations. Traditional numerical solvers rely on carefully constructed meshes, often requiring manual intervention, and typically exhibit slow convergence. This difficulty is particularly pronounced in porous media, where the diffusive nature of momentum transport is hindered by intricate solid boundaries. These challenges limit the efficiency of numerical simulations, particularly when repeated evaluations are required. We present a neural-network-based framework for predicting pore-scale velocity fields directly from sample geometry. The method is based on a convolutional encoder-decoder architecture with skip connections, designed to preserve fine-grained structural information. Physical consistency is encouraged through a custom loss function composed of multiple terms: incompressibility, no-flow conditions within solids, periodicity constraints, and agreement with the global tortuosity index. We systematically analyze the influence of weight selection for these loss terms, quantifying their individual contributions to prediction accuracy. Several architectural variants inspired by computer vision are evaluated to identify one providing the best performance and robustness. The generalization ability of the trained network is assessed on samples outside the training distribution, including variations in boundary conditions, obstacle geometry, and porosity. Finally, we demonstrate additional practical applications in which network predictions are used to initialize the Lattice-Boltzmann simulations, a standard fluid dynamics solver, often used in complex boundary problems like porous media and used by us to train the network. We have used network-generated velocity field as a starting point and found that this significantly accelerates LBM solver convergence, achieving improvements in over 90% of cases.
Proteins perform diverse functions in biological systems, including catalysis, signaling, transport, and various mechanical roles. The growing efforts to integrate proteins' unique functionalities into synthetic environments have stimulated research on protein behaviors in non-native, synthetic environments, such as in organic solvents or plastics. This study bridges the understanding of protein mechanics in nature with their application in synthetic environments. We used all-atom molecular dynamics simulations to study the unfolding of de novo helix repeat proteins in organic solvents at different hydration ratios under mechanical force. The results show that proteins in organic solvents require higher unfolding forces than in aqueous media and display distinct unfolding pathways. Detailed analysis revealed that sufficient replenishment of hydrogen bonding between protein and water favors helix unraveling, whereas the reduced hydrophobic effect in organic solvents encourages the breakdown of tertiary structure. These findings contribute critical insights into the rational design of proteins as unique mechanosensitive elements in synthetic materials, highlighting the importance of considering environmental context when repurposing proteins for such environments.
Scroll waves in three-dimensional excitable media rotate around singular filaments, which are topological defects analogous to phase singularities in two dimensions. Methods for precise localization of these filaments are essential for studies of filament dynamics in modeling and experimental studies. Practical applications of these methods include understanding the mechanisms of cardiac arrhythmias, most of which have recently been shown to have a three-dimensional nature. In this study, we propose a novel Jacobian-determinant vector method for filament identification based on the topological current theory. We define a Jacobian-determinant vector field, which we construct so that its magnitude peaks at filament locations, while its direction shows the local filament orientation, guiding further filament detection. We validate the method using the Aliev-Panfilov model across complex filament configurations, including Hopf links and trefoil knots, and demonstrate better performance compared to convolution-based and zero-normal-velocity methods, particularly under noisy and slightly fibrotic environments. This method, thus, provides a useful tool for studying scroll-wave dynamics in both theoretical and applied contexts.
The rapid increase in global plastic production over the past century has led to a severe environmental crisis, characterized by widespread contamination of terrestrial, freshwater, and marine ecosystems. Recently, microbial and enzymatic degradation has emerged as a promising alternative to conventional plastic waste management owing to its environmentally friendly nature and mild operational conditions. However, this approach still faces several critical challenges, including overinterpretation of degradation evidence, incomplete mechanistic understanding, and limited validation of true biodegradation. This review adopts a critical perspective to evaluate whether reported biodegradation is experimentally reliable and biologically meaningful. We synthesize recent advances in the biodegradation of both hydrolysable and non-hydrolysable plastics polymers, with specific emphasis on polymer-specific degradation mechanisms, analytical limitations, and methodological strategies for distinguishing genuine degradation from apparent surface deterioration. We further discuss emerging issues that determine practical relevance, including effects of contaminants in real plastic waste and divergent biodegradation behaviors of macroplastics and microplastics. By integrating mechanistic insights with rigorous evaluation criteria, this review provides a framework for advancing plastic biodegradation research from descriptive screening toward reliable validation and practical application.