Intermediate Scale Research Articles

Lipid Membrane Domains Control Actin Network Viscoelasticity.

The mammalian cell membrane is embedded with biomolecular condensates of protein and lipid clusters, which interact with an underlying viscoelastic cytoskeleton network to organize the cell surface and mechanically interact with the extracellular environment. However, the mechanical and thermodynamic interplay between the viscoelastic network and liquid-liquid phase separation of 2-dimensional (2D) lipid condensates remains poorly understood. Here, we engineer materials composed of 2D lipid membrane condensates embedded within a thin viscoelastic actin network. The network generates localized anisotropic stresses that deform lipid condensates into triangular morphologies with sharp edges and corners, shapes unseen in many 3D composite gels. Kinetic coarsening of phase-separating lipid condensates accelerates the viscoelastic relaxation of the network, leading to an effectively softer composite material over intermediate time scales. We dynamically manipulate the membrane composition to control the elastic-to-viscous crossover of the network. Such viscoelastic composite membranes may enable the development of coatings, catalytic surfaces, separation membranes, and other interfaces with tunable spatial organization and plasticity mechanisms.

Mechanism of transition from subdiffusive transport to normal diffusion for passive tracers in a plane periodical flow induced by Gaussian noise

The known analytical solution describing a two-dimensional viscous flow with vortices under a driving force is generalized. It is shown that a periodic pattern of asymmetric vortices arises when the force amplitude exceeds a critical value. The transport of an ensemble of passive particles through the resulting structure has been studied. The envelope of each vortex contains a stagnation point, and the tracer motion along it without noise is infinitely long. It is shown that the macroscopic transport of an ensemble of tracers is extremely slow in the noise-free case. The latter leads to the mixing of the tracer ensemble. We study the peculiarities of such transport using a special flow model. Such a model has the form of a series of recurrence mappings. The recurrence mappings are constructed for the ensemble transport through a unit cell using the numerical solution of the Langevin equations in the presence of random particle displacements caused by molecular diffusion. The presence of diffusion allows particles to penetrate into the vortex, which leads to an additional slowing down of transport. The effect of noise on the variance of the tracer ensemble is investigated. It is shown that the growth of the standard deviation with time can be described by a power law. On an intermediate time scale, which grows exponentially long, as the noise strength tends to zero, a subdiffusive behavior is observed. The dependence of the subdiffusion exponent on the molecular diffusivity is obtained.

Spatial pattern of woody plant species richness and composition in primary warm temperate evergreen forest in Kasugayama Hill, Japan

Plant species richness and composition are influenced by complex interactions between biotic and abiotic factors that operate on different spatial scales. Since spatial scales vary continuously in nature, it is expected that multiple factors simultaneously affect species richness and composition at an intermediate spatial scale (i.e., the mesoscale landscape level). Previous studies have shown that local topography and elevation are important factors for shaping intermediate spatial scale plant species richness; however, the relative importance of these factors has rarely been examined. Here, we used spatially explicit woody plant data to examine the factors that characterize the spatial pattern of primary evergreen forest biodiversity at the intermediate spatial scale. We found that the spatial pattern of species diversity in a predominantly warm temperate evergreen forest at the landscape level is mainly characterized by shifts in species composition along the elevation gradient. Our study also found that compositional shift along the elevational gradient was mainly caused by habitat specialization among congeneric species, suggesting that niche partitioning among closely-related species is a fundamentally important feature of the intermediate spatial scale species richness pattern. Furthermore, we found that specialization in a habitat of closely-related species can be established even within a limited environmental gradient. This suggests that biotic interactions among closely-related species may be an important factor driving habitat specialization, and biotic interactions may play an important role in shaping landscape-scale biodiversity patterns.

Modelling of high-velocity free-surface flows: a revised interfacial area approach

The specific interface area transport equation is derived from first principles, and a closure model for turbulent flow is proposed. The flow is modelled by a two-phase method providing velocities of both phases at the bubbly, spray and the intermediate large scale interface (LSI) regimes. The interface area is transported by the interface velocity – a linear combination of corresponding phase velocities and a turbulent drift velocity. The resulting equation includes the source terms due to the bubble (droplet) breakup and coalescence, and turbulent splashes at the interface. A model is proposed for the source term in the LSI regime. The model is implemented in the developer's version of the Simcenter STAR-CCM+ ® CFD code. The new model is applied to self-aerating water flows down stepped chutes; the results are in reasonable agreement with the experimental data.

Intermediate scale testing for ORS

Intermediate scale testing for ORS

Indicators of Cultural Ecosystem Services for Peri-Urban Agricultural and Natural Areas at an Intermediate Scale: A Case Study of Arequipa, Peru

The evaluation of management in peri-urban agricultural and natural areas (PANAs) constitutes a complex topic, particularly when considering its scale in cities where landscape planning is a priority. Therefore, indicators are required to assess the non-material well-being, biodiversity, and quality of life of society, which are criteria of cultural ecosystem services (CESs). This research develops identification and subclassification CESs and tangible and intangible indicators that facilitate the management of the PANA landscape, using the city of Arequipa as a case study—a dynamic cultural city with a declared cultural heritage, in turn located in an artificial oasis in the Atacama Desert. Therefore, the results will enable the selection of indicators that are practically applicable to planning instruments, serving as support systems for decision-making regarding interventions in PANAs. The methodology began with a systematic and meta-analytic (PRISMA) review, identifying 25 articles containing 230 indicators across 19 subclassifications. Using the Multiscale Indicators Framework (MSIF), the literature was integrated with a participatory workshop to validate these findings. The level of impact was assessed for 115 indicators across 13 subclassifications, applying criteria such as diversity, sustainable management, quality of life, and scalability—factors necessary to comply with urban sustainability policies.

Using eDNA to Supplement Population Genetic Analyses for Cryptic Marine Species: Identifying Population Boundaries for Alaska Harbour Porpoises.

Isolation by distance and biogeographical boundaries define patterns of population genetic structure for harbour porpoise along the Pacific coast from California to British Columbia. Until recently, inadequate sample sizes in many regions constrained efforts to characterise population genetic structure throughout the coastal waters of Alaska. Here, tissue samples from beachcast strandings and fisheries bycatch were supplemented with targeted environmental DNA (eDNA) samples in key regions of Alaska coastal and inland waters. Using a geographically explicit, hierarchical approach, we examined the genetic structure of Alaska harbour porpoises, using both mitochondrial DNA (mtDNA) sequence data and multilocus SNP genotypes. Despite a lack of evidence of genetic differentiation from nuclear SNP loci, patterns of relatedness and genetic differentiation from mtDNA suggest natal philopatry at multiple geographic scales, with limited gene flow among sites possibly mediated by male dispersal. A priori clustering of sampled areas at an intermediate scale (eastern and western Bering Sea, Gulf of Alaska and Southeast Alaska) best explained the genetic variance (12.37%) among regions. In addition, mtDNA differentiation between the Gulf of Alaska and eastern Bering Sea, and among regions within the Gulf of Alaska, indicated significant genetic structuring of harbour porpoise populations in Southeast Alaska. The targeted collection of eDNA samples from strata within Southeast Alaska was key for elevating the statistical power of our mtDNA dataset, and findings indicate limited dispersal between neighbouring strata within coastal and inland waters. These results provide evidence supporting a population boundary within the currently recognised Southeast Alaska Stock. Together, these findings will prove useful for ongoing management efforts to reduce fisheries conflict and conserve genetic diversity in this iconic coastal species.

Changing Your Martini Can Still Give You a Hangover.

The Martini 3.0 coarse-grained force field, which was parametrized to better capture transferability in top-down coarse-grained models, is analyzed to assess its accuracy in representing thermodynamic and structural properties with respect to the underlying atomistic representation of the system. These results are compared to those obtained following the principles of statistical mechanics that start from the same underlying atomistic system. To this end, the potentials of mean force for lateral association in Martini 3.0 binary lipid bilayers are decomposed into their entropic and enthalpic components and compared to those of corresponding atomistic bilayers that have been projected onto equivalent coarse-grained mappings but evolved under the fully atomistic forces. This is accomplished by applying the reversible work theorem to lateral pair correlation functions between coarse-grained lipid beads taken at a range of different temperatures. The entropy-enthalpy decompositions provide a metric by which the underlying statistical mechanical properties of Martini can be investigated. Overall, Martini 3.0 is found to fail to properly partition entropy and enthalpy for the PMFs compared to the mapped all-atom results, despite changes made to the force field from the Martini 2.0 version. This outcome points to the fact that the development of more accurate top-down coarse-grained models such as Martini will likely necessitate temperature-dependent terms in the corresponding CG force-field; although necessary, this may not be sufficient to improve Martini. In addition to the entropy-enthalpy decompositions, Martini 3.0 produces an incorrect undulation spectrum, in particular at intermediate length scales of biophysical pertinence.

Scale dependence of local shearing motion in decaying turbulence generated by multiple-jet interaction

Scale dependence of local shearing motion is investigated experimentally in decaying homogeneous isotropic turbulence generated through multiple-jet interaction. The turbulent Reynolds number, based on the Taylor microscale, is between approximately 900 and 400. Velocity fields, measured using particle image velocimetry, are analysed through the triple decomposition of a low-pass filtered velocity gradient tensor, which quantifies the intensities of shear and rigid-body rotation at a given scale. These motions manifest predominantly as layer and tubular vortical structures, respectively. The scale dependence of the moments of velocity increments, associated with shear and rigid-body rotation, exhibits power-law behaviours. The scaling exponents for shear are in quantitative alignment with the anomalous scaling of the velocity structure functions, suggesting that velocity increments are influenced predominantly by shearing motion. In contrast, the exponents for rigid-body rotation are markedly smaller than those predicted by Kolmogorov scaling, reflecting the high intermittency of rigid-body rotation. The mean flow structure associated with shear at intermediate scales is investigated with conditional averages around locally intense shear regions in the filtered velocity field. The averaged flow field exhibits a shear layer structure with aspect ratio approximately 4.5, surrounded by rotating motion. The analysis at different scales reveals the existence of self-similar structures of shearing motion across various scales. The mean velocity jump across the shear layer increases with the layer thickness. This relationship is well predicted by Kolmogorov's second similarity hypothesis, which is useful in predicting the mean characteristics of shear layers across a wide range of scales.

Turbulent cascade arrests and the formation of intermediate-scale condensates.

Energy cascades lie at the heart of the dynamics of turbulent flows. In a recent study of turbulence in fluids with odd viscosity X.M. de Wit et al. [Nature (London) 627, 515 (2024)0028-083610.1038/s41586-024-07074-z], the two dimensionalization of the flow at small scales leads to the arrest of the energy cascade and selection of an intermediate scale, between the forcing and the viscous scales. To demonstrate the generality of the phenomenon and its existence for a wide class of turbulent systems, we study a shell model that is carefully constructed to have three-dimensional turbulent dynamics at small wave numbers and two-dimensional turbulent dynamics at large wave numbers. The large scale separation that we can achieve in our shell model allows us to examine clearly the interplay between these dynamics, which leads to an arrest of the energy cascade at a transitional wave number and an associated accumulation of energy at the same scale. Such pile-up of energy around the transitional wave number is reminiscent of the formation of condensates in two-dimensional turbulence, but, in contrast, it occurs at intermediate wave numbers instead of the smallest wave number.

1-arcsecond imaging of the ELAIS-N1 field at 144MHz using the LoTSS survey with the international LOFAR telescope

We present the first wide area ($2.5 deg ^2$) LOFAR high band antenna image at a resolution of $1.2 with a median noise of $ Jy beam $. It was made from an 8-hour International LOFAR Telescope (ILT) observation of the ELAIS-N1 field at frequencies ranging from 120 to 168\,MHz with the most up-to-date ILT imaging methods. This intermediate resolution falls between the highest possible resolution (0.3 achievable by using all ILT baselines and the standard 6-arcsecond resolution in the LOFAR Two-meter Sky Survey (LoTSS) image products utilising the LOFAR Dutch baselines only. This is the first demonstration of the feasibility of imaging using the ILT at a resolution of sim 1 which provides unique information on source morphology at scales that fall below the surface brightness limits at higher resolutions. The total calibration and imaging computational time is approximately 52,000 core hours, which is nearly five times more than required to produce a $6 resolution image. We also present a radio source catalogue containing 2263 sources detected over the $2.5 deg ^2$ image of the ELAIS-N1 field, with a peak intensity threshold of $5.5 The catalogue has been cross-matched with the LoTSS deep ELAIS-N1 field radio catalogue, and its flux density and positional accuracy have been investigated and corrected accordingly. We find that sim 80<!PCT!> of sources that we expect to be detectable based on their peak brightness in the LoTSS $6 resolution image are detected in this image, which is approximately a factor of two higher than for $0.3 resolution imaging in the Lockman Hole, implying there is a wealth of information on these intermediate scales.

Flow patterns and energy spectra in forced quasi-two-dimensional turbulence: effect of system size and damping rate

An experimental investigation is conducted to study the flow patterns, spectral properties and energy fluxes in thin-layer turbulence with varying system sizes and damping rates. It is found that although a system-size vortex (an indicator of spectral condensation) occurs for small system sizes and does not for large ones, the spectra for different system sizes consistently exhibit a scaling close to $k^{-3}$ in inverse cascade (another indicator of spectral condensation). On the other hand, under a fixed system size larger than the friction-dominated length scale, the energy spectrum in the inverse cascade range changes from $k^{-3}$ to $k^{-5/3}$ as the damping rate increases, suggesting that the friction-dominated length scale may not be a suitable parameter for predicting spectral transition. At lower damping rates and large system sizes, turbulent structures grow larger via inverse cascade, manifesting as long streamers, and the small-scale vortices are suppressed. This suppression leads to a reduction of energy flux at intermediate scales and a change in the spectral shape. The dimensionless Taylor microscale is found to exhibit a monotonic dependence on the damping rate. With the reduction in the damping rate, the Taylor microscale increases to become comparable with the forcing scale, and the spectrum in inverse cascade transits to a steeper scaling, $k^{-3}$ , indicating that the dimensionless Taylor microscale may be used as a diagnostic parameter for spectral transition.

Rugged magneto-hydrodynamic invariants in weakly collisional plasma turbulence: Two-dimensional hybrid simulation results

Aims. We investigated plasma turbulence in the context of solar wind. We concentrated on properties of ideal second-order magneto-hydrodynamic (MHD) and Hall MHD invariants. Methods. We studied the results of a two-dimensional hybrid simulation of decaying plasma turbulence with an initial large cross helicity and a negligible magnetic helicity. We investigated the evolution of the combined energy and the cross, kinetic, mixed, and magnetic helicities. For the combined (kinetic plus magnetic) energy and the cross, kinetic, and mixed helicities, we analysed the corresponding Kármán-Howarth-Monin (KHM) equation in the hybrid (kinetic proton and fluid electron) approximation. Results. The KHM analysis shows that the combined energy decays at large scales. At intermediate scales, this energy cascades (from large to small scales) via the MHD non-linearity and this cascade partly continues via Hall coupling to sub-ion scales. The cascading combined energy is transferred (dissipated) to the internal energy at small scales via the resistive dissipation and the pressure-strain effect. The Hall term couples the cross helicity with the kinetic one, suggesting that the coupled invariant, referred to here as the mixed helicity, is a relevant turbulence quantity. However, when analysed using the KHM equations, the kinetic and mixed helicities exhibit very dissimilar behaviours to that of the combined energy. On the other hand, the cross helicity, in analogy to the energy, decays at large scales, cascades from large to small scales via the MHD+Hall non-linearity, and is dissipated at small scales via the resistive dissipation and the cross-helicity equivalent of the pressure-strain effect. In contrast to the combined energy, the Hall term is important for the cross helicity over a wide range of scales (even well above ion scales). In contrast, the magnetic helicity is scantily generated through the resistive term and does not exhibit any cascade.

Probing the physics of star formation (ProPStar)

Context. Turbulence is a key component of molecular cloud structure. It is usually described by a cascade of energy down to the dissipation scale. The power spectrum for subsonic incompressible turbulence is ∝k−5/3, while for supersonic turbulence it is ∝k−2. Aims. We determine the power spectrum in an actively star-forming molecular cloud, from parsec scales down to the expected magnetohydrodynamic (MHD) wave cutoff (dissipation scale). Methods. We analyzed observations of the nearby NGC 1333 star-forming region in three different tracers to cover the different scales from ∼10 pc down to 20 mpc. The largest scales are covered with the low-density gas tracer 13CO (1–0) obtained with a single dish, the intermediate scales are covered with single-dish observations of the C18O (3–2) line, while the smallest scales are covered in H13CO+ (1–0) and HNC (1–0) with a combination of NOEMA interferometer and IRAM 30m single-dish observations. The complementarity of these observations enables us to generate a combined power spectrum covering more than two orders of magnitude in spatial scale. Results. We derive the power spectrum in an active star-forming region spanning more than 2 decades of spatial scales. The power spectrum of the intensity maps shows a single power-law behavior, with an exponent of 2.9 ± 0.1 and no evidence of dissipation. Moreover, there is evidence that the power spectrum of the ions to have more power at smaller scales than the neutrals, which is opposite to the theoretical expectations. Conclusions. We show new possibilities for studying the dissipation of energy at small scales in star-forming regions provided by interferometric observations.

The universal multiplicity function: counting haloes and voids

We present a novel combination of the excursion-set approach with the peak theory formalism in Lagrangian space and provide accurate predictions for halo and void statistics over a wide range of scales. The set-up is based on an effective moving barrier. Besides deriving the corresponding numerical multiplicity function, we introduce a new analytical formula reaching the percent level agreement with the exact numerical solution obtained via Monte Carlo realisations down to small scales, ∼ 1012 h -1M⊙. In the void case, we derive the dependence of the effective moving barrier on the void formation threshold, δ v, by comparison against the Lagrangian void size function measured in the DEMNUni simulations. We discuss the mapping from Lagrangian to Eulerian space for both haloes and voids; adopting the spherical symmetry approximation, we obtain a strong agreement at intermediate and large scales. Finally, using the effective moving barrier, we derive Lagrangian void density profiles accurately matching measurements from cosmological simulations, a major achievement towards using void profiles for precision cosmology with the next generation of galaxy surveys.

The epidemiological footprint of contact structures in models with two levels of mixing.

Models with several levels of mixing (households, workplaces), as well as various corresponding formulations for , have been proposed in the literature. However, little attention has been paid to the impact of the distribution of the population size within social structures, effect that can help plan effective interventions. We focus on the influence on the model outcomes of teleworking strategies, consisting in reshaping the distribution of workplace sizes. We consider a stochastic SIR model with two levels of mixing, accounting for a uniformly mixing general population, each individual belonging also to a household and a workplace. The variance of the workplace size distribution appears to be a good proxy for the impact of this distribution on key outcomes of the epidemic, such as epidemic size and peak. In particular, our findings suggest that strategies where the proportion of individuals teleworking depends sublinearly on the size of the workplace outperform the strategy with linear dependence. Besides, one drawback of the model with multiple levels of mixing is its complexity, raising interest in a reduced model. We propose a homogeneously mixing SIR ODE-based model, whose infection rate is chosen as to observe the growth rate of the initial model. This reduced model yields a generally satisfying approximation of the epidemic. These results, robust to various changes in model structure, are very promising from the perspective of implementing effective strategies based on social distancing of specific contacts. Furthermore, they contribute to the effort of building relevant approximations of individual based models at intermediate scales.

Emergent time scales of epistasis in protein evolution

We introduce a data-driven epistatic model of protein evolution, capable of generating evolutionary trajectories spanning very different time scales reaching from individual mutations to diverged homologs. Our in silico evolution encompasses random nucleotide mutations, insertions and deletions, and models selection using a fitness landscape, which is inferred via a generative probabilistic model for protein families. We show that the proposed framework accurately reproduces the sequence statistics of both short-time (experimental) and long-time (natural) protein evolution, suggesting applicability also to relatively data-poor intermediate evolutionary time scales, which are currently inaccessible to evolution experiments. Our model uncovers a highly collective nature of epistasis, gradually changing the fitness effect of mutations in a diverging sequence context, rather than acting via strong interactions between individual mutations. This collective nature triggers the emergence of a long evolutionary time scale, separating fast mutational processes inside a given sequence context, from the slow evolution of the context itself. The model quantitatively reproduces epistatic phenomena such as contingency and entrenchment, as well as the loss of predictability in protein evolution observed in deep mutational scanning experiments of distant homologs. It thereby deepens our understanding of the interplay between mutation and selection in shaping protein diversity and functions, allows one to statistically forecast evolution, and challenges the prevailing independent-site models of protein evolution, which are unable to capture the fundamental importance of epistasis.

Continuous Space-Time Video Super-Resolution with Multi-Stage Motion Information Reorganization

Space-time video super-resolution (ST-VSR) aims to simultaneously expand a given source video to a higher frame rate and resolution. However, most existing schemes either consider fixed intermediate time and scale or fail to exploit long-range temporal information due to model design or inefficient motion estimation and compensation. To address these problems, we propose a continuous ST-VSR method to convert the given video to any frame rate and spatial resolution with Multi- s tage M otion information r eorganization (MsMr). To achieve time-arbitrary interpolation, we propose a forward warping guided frame synthesis module and an optical flow-guided context consistency loss to better approximate extreme motion and preserve similar structures among input and prediction frames. To realize continuous spatial upsampling, we design a memory-friendly cascading depth-to-space module. Meanwhile, with the sophisticated reorganization of optical flow, MsMr realizes more efficient motion estimation and motion compensation, making it possible to propagate information from long-range neighboring frames and achieve better reconstruction quality. Extensive experiments show that the proposed algorithm is flexible and performs better on various datasets than the state-of-the-art methods. The code will be available at https://github.com/hahazh/LD-STVSR .

Quantum Tunneling: From Theory to Error‐Mitigated Quantum Simulation

AbstractEver since the discussions about a possible quantum computer arised, quantum simulations have been at the forefront of possible utilities, with the task of quantum simulations being one that promises quantum advantage. Recently, advancements have made it feasible to simulate complex molecules using Variational Quantum Eigensolvers or study the dynamics of many‐body spin Hamiltonians. These simulations have the potential to yield valuable outcomes through the application of error mitigation techniques. Simulating smaller models carries a great amount of importance as well and currently, in the Noisy Intermediate Scale Quantum era, is more feasible since it is less prone to errors. The objective of this work is to examine the theoretical background and the circuit implementation of a quantum tunneling simulation, with an emphasis on hardware considerations. This study presents the theoretical background required for such implementation and highlights the main stages of its development. By building on classic approaches of quantum tunneling simulations, this study aims at improving the result of such simulations by employing error mitigation techniques, Zero Noise Extrapolation, and Readout Error Mitigation and uses them in conjunction with multiprogramming of the quantum chip, a technique used for solving the hardware under‐utilization problem that arises in such contexts.

Elastic Modulus Measurement at High Temperatures for Miniature Ceramic Samples Using Laser Micro-Machining and Thermal Mechanical Analyzer.

In this paper, we demonstrate a method of measuring the flexural elastic modulus of ceramics at an intermediate (~millimeter) scale at high temperatures. We used a picosecond laser to precisely cut microbeams from the location of interest in a bulk ceramic. They had a cross-section of approximately 100 μm × 300 μm and a length of ~1 cm. They were then tested in a thermal mechanical analyzer at room temperature, 500 °C, 800 °C, and 1100 °C using the four-point flexural testing method. We compared the elastic moduli of high-purity Al2O3 and AlN measured by our method with the reported values in the literature and found that the difference was less than 5% for both materials. This paper provides a new and accurate method of characterizing the high-temperature elastic modulus of miniature samples extracted from representative/selected areas of bulk materials.