Time Evolution Research Articles

Vibrational relaxation of HOD by collisions with Ar atoms.

Vibrational relaxation of HOD(v12, v3) molecules by collisions with Ar was studied at 298K (v12 denotes coupled bending, v2, and OD stretching, v1, vibrational modes and v3 denotes OH stretching mode). The vibrationally excited HOD molecules were generated by exothermic abstraction reactions of OD radicals with 13 different RH reactants and observed by infrared emission from a fast-flow reactor as a function of Ar pressure and reaction time. State-specific relaxation rate constants were obtained by comparison of the time evolution of the experimental vibrational distributions with numerical kinetic calculations for vibrational populations. The relaxation mechanism was based on the relaxation scheme of H2O studied earlier with the addition of specific channels for HOD(v12, v3). Unlike H2O, energy in stretching and bending vibrations of HOD cannot be separated due to close ν1 and 2ν2 energies, which leads to fast collisional equilibration between these Fermi-resonant levels. For relaxation of the only pure bending state (10), a rate constant of (1.5 ± 0.3) × 10-13cm3molecule-1s-1 was obtained. The relaxation rate of higher v12 states linearly increases with quantum number and very likely includes transfer of population from OD stretch levels, v1, to a lower energy bend level. The average rate constants for the loss of population from (01), (02), and (03) stretching states are (1.1 ± 0.3) × 10-14, (3.2 ± 1.0) × 10-14, and (5.6 ± 1.2) × 10-14cm3molecule-1s-1, respectively.

Dissecting Allosteric Mutations for Antibiotic Resistance by Time-Dependent Linear Response Theory.

We report a new approach that combines molecular dynamics trajectories with time-dependent linear response theory to compute the time evolution of residue fluctuation responses to force perturbations exerted at functional sites. Applying this new approach to TEM-1 beta-lactamase, we observe that the time-resolved response profiles of allosteric sites to perturbations of TEM-1 active sites are distinct from those of non-allosteric residues. Using Fourier transformations, we convert the time domain response profiles to the frequency domain and demonstrate that the frequency space representation of the perturbation response can capture the mutational behavior of each site when applied to deep sequencing mutational data. Furthermore, we show that classification models built on perturbation responses can accurately identify distal positions that regulate antibiotic resistance. These findings provide insights into the contributions of specific residues to resistance-encoded in time-resolved perturbation response behavior and highlight the importance of this new approach in identifying allosteric mutations, opening avenues for the potential characterization of additional allosteric positions without extensive computational simulations.

De-novo assembly of a reference genome for a critically threatened Aotearoa New Zealand tree species, Syzygium maire (Myrtaceae)

Aotearoa New Zealand’s swamp forests have experienced significant habitat loss in fewer than two hundred years. Many of the country’s tree species are endemic with sparse to no genetic information available to underpin conservation strategies. Syzygium maire, Aotearoa’s only endemic Syzygium species, is a culturally and ecologically important component of swamp forest habitats. Unfortunately, populations of S. maire have been greatly reduced, heavily fragmented and are susceptible to the emergent pathogen Austropuccinia psidii (myrtle rust), posing eminent danger of a further decline of the species. We sought to develop genomic resources to inform conservation management of S. maire. To this end, we used long read, high accuracy sequencing technology to produce a highly complete reference quality genome for S. maire. The genome sequence was named ‘Ngā Hua o te Ia Whenua’ by the local Māori tribe where the tree used for genome sequencing grows. We assess whether genome-level divergence with other Myrtaceae may have followed geographic isolation of the species. We detect conservation of large scale synteny between three Syzygium species and Eucalyptus grandis, providing support for the stability of Syzygium genomes across evolutionary time. We annotate genes implicated in fungal pathogen defence, identifying several hundred putative NLR genes, including putative homologs of previously identified Austropuccinia psidii resistance genes. Finally, we evaluate the genetic relationships of individuals of a small, isolated population of trees. We find evidence of high levels of kinship and inbreeding within small and isolated S. maire populations, informing local-scale conservation strategies for the species. Our findings enable practical conservation actions and provide resources for larger scale studies of S. maire and other Syzygium species in the future.

DISCOVERING SYMBOLIC LAWS DIRECTLY FROM TRAJECTORIES WITH HAMILTONIAN GRAPH NEURAL NETWORKS

Abstract The time evolution of physical systems is described by differential equations, which depend on abstract quantities like energy and force. Traditionally, these quantities are derived as functionals based on observables such as positions and velocities. Discovering these governing symbolic laws is the key to comprehending the interactions in nature. Here, we present a Hamiltonian graph neural network (HGNN), a physics-enforced GNN that learns the dynamics of systems directly from their trajectory. We demonstrate the performance of HGNN on n-springs, n-pendulums, gravitational systems, and binary Lennard Jones systems; HGNN learns the dynamics in excellent agreement with the ground truth from small amounts of data. We also evaluate the ability of HGNN to generalize to larger system sizes, and to a hybrid spring-pendulum system that is a combination of two original systems (spring and pendulum) on which the models are trained independently. Finally, employing symbolic regression on the learned HGNN, we infer the underlying equations relating to the energy functionals, even for complex systems such as the binary Lennard-Jones liquid. Our framework facilitates the interpretable discovery of interaction laws directly from physical system trajectories. Furthermore, this approach can be extended to other systems with topology-dependent dynamics, such as cells, polydisperse gels, or deformable bodies.

Damage evolution in Plasma Facing Materials by a sequential multiscale approach

Abstract Describing the time evolution of Plasma Facing Materials (PFMs),
meaning quantitative evaluation of erosion, roughness, and physical properties
degradation, is one of the difficult challenges to reach the goal of efficient energy
production by nuclear fusion.
To follow all the aging-connected physical and chemical phenomena through
their characteristic dimensional scale, and to estimate the PFM microstructural
transformation over time, we propose a predictive sequential multiscale methodology,
consisting of two database-provided coupled codes. The first is a time-dependent,
volume-averaged, plasma simulator which describes completely this system, in terms of
thermodynamics, composition and evaluation of the sheath potential. Plasma solutions
are geometrically rearranged by adding surface reactions and 3D geometric features.
To increase sensitivity, plasma information is provided to the second code as an initial
condition. Such a code is a 3D kinetic Monte Carlo (3D-KMC) in-cell algorithm
for nanoscale erosion describing the PFM interactions through an extendable set of
physical phenomena, such as sticking, sputtering, ion enhanced removals and ion
penetration.
In this paper, we perform simulations for the case of study of Hydrogen (H) plasmas
produced in linear devices, reaching the quasi-atomic detail of the plasma induced
material modification of tungsten (W) as PFM.

Measuring the Loschmidt Amplitude for Finite-Energy Properties of the Fermi-Hubbard Model on an Ion-Trap Quantum Computer

Calculating the equilibrium properties of condensed-matter systems is one of the promising applications of near-term quantum computing. Recently, hybrid quantum-classical time-series algorithms have been proposed to efficiently extract these properties from a measurement of the Loschmidt amplitude ⟨ψ|e−iH^t|ψ⟩ from initial states |ψ⟩ and a time evolution under the Hamiltonian H^ up to short times t. In this work, we study the operation of this algorithm on a present-day quantum computer. Specifically, we measure the Loschmidt amplitude for the Fermi-Hubbard model on a 16-site ladder geometry (32 orbitals) on the Quantinuum H2-1 trapped-ion device. We assess the effect of noise on the Loschmidt amplitude and implement algorithm-specific error-mitigation techniques. By using a thus-motivated error model, we numerically analyze the influence of noise on the full operation of the quantum-classical algorithm by measuring expectation values of local observables at finite energies. Finally, we estimate the resources needed for scaling up the algorithm. Published by the American Physical Society 2024

Particle transport in reduced turbulence neutral beam heated discharges at Wendelstein 7-X

Abstract A spontaneous reduction in anomalous particle transport in the plasma core is seen experimentally in reproducible, purely neutral beam heated plasma phases at Wendelstein 7-X (W7-X). Heating and fueling the plasma exclusively with the neutral beam injection (NBI) system for several seconds leads to continuously peaking plasma density profiles with strong gradients inside mid minor radius. A significant acceleration of the density peaking occurs after a certain onset time and is examined with a detailed particle transport analysis in several discharges. By invoking the particle continuity equation, the total experimental radial electron flux is deduced from the time evolution of the electron density profile and the radially resolved particle sources. Subtracting the modeled neoclassical particle flux contribution gives the anomalous particle flux. Exploiting the evolving plasma conditions, anomalous diffusion and convection coefficients are computed from the flux variation with density and density gradients. In several discharges a significant and consistent change of the anomalous transport coefficients is seen when crossing a specific normalized density gradient length.

Photonic cellular automaton simulation of relativistic quantum fields: Observation of Zitterbewegung

Quantum cellular automaton (QCA) is a model for universal quantum computation and a natural candidate for digital quantum simulation of relativistic quantum fields. Here we introduce the first photonic platform for implementing QCA simulation of a free relativistic Dirac quantum field in 1+1 dimension, through a Dirac quantum cellular automaton (DQCA). Encoding the field position degree of freedom in the orbital angular momentum (OAM) of single photons, our state-of-the-art setup experimentally realizes eight steps of a DQCA, with the possibility of having complete control over the input OAM state preparation and the output measurement making use of two spatial light modulators. Therefore, studying the distribution in the OAM space at each step, we were able to reproduce the time evolution of the free Dirac field observing the , an oscillatory movement extremely difficult to see in a real-case experimental scenario that is a signature of the interference of particle and antiparticle states. The accordance between the expected and measured oscillations certifies the simulator performances, paving the way towards the application of photonic platforms to the simulation of more complex relativistic effects. Published by the American Physical Society 2024

Exploring chaos and ergodic behavior of an inductorless circuit driven by stochastic parameters

AbstractThere exist extensive studies on periodic and random perturbations of various smooth maps investigating their dynamics. Unlike smooth maps, non-smooth maps are yet to be studied extensively under a stochastic regime. This paper presents a stochastic piecewise-smooth map derived from a simple inductorless switching circuit. The stochasticity is introduced in parameter values. The distribution of the parameter values is bounded and randomly selected from uniform and triangular distributions and ranges between high and low bifurcation parameter values of the deterministic map. Due to this inherent stochasticity in parameter values, the time evolution of the state variable cannot be predicted at a specific time instant. We observe that the state variable exhibits completely ergodic behavior when the minimum value of the parameter is the same as the minimum bifurcation parameter of the deterministic system. However, the ensemble average of the state variable converges to a fixed value. The system demonstrates nonchaotic behavior for a particular range of parameter values but the deterministic map in that bifurcation range shows interplay between chaos and periodic orbits. The values of Lyapunov exponents decrease monotonically with increased asymmetry of the distribution from which the bifurcation parameter values are chosen. We determine the probability density function of the stochastic map and verify its invariance under initial conditions. The most noteworthy result is the disappearance of chaotic behavior when the lower range of the distribution is varied while maintaining a fixed upper threshold for a particular distribution, even though the deterministic map exhibits an array of periodic and chaotic behaviors within the range. As the period-incrementing cascade with chaotic inclusion only occurs in nonsmooth maps, this paper numerically shows the stochasticity of a piecewise-smooth map obtained from a practical system for the first time where randomness is introduced in the parameter space.

CuO nanoparticles' effect on the photosynthetic performance in seed tissues of Inga laurina (Fabaceae).

Copper oxide nanoparticles (CuONPs) have been produced on a large scale because they can be applied across various fields, especially in nano-enabled healthcare and agricultural products. However, the increasing use of CuONPs leads to their release and accumulation into the environment. The CuONPs uptaken by seeds and their implications on germination behavior have been reported, but little is known or understood about their impact on photosynthesis in seed tissues. To fill knowledge gaps, this study evaluated the effects of CuONP concentrations (0-300mg L-1) on the photosynthetic activity of Inga laurina seeds. The microscopy data showed that CuONPs had an average size distribution of 57.5 ± 0.7nm. Copper ion release and production of reactive oxygen species (ROS) by CuONPs were also evaluated by dialysis and spectroscopy experiments, respectively. CuONPs were not able to intrinsically generate ROS and released a low content of Cu2⁺ ions (4.5%, w/w). Time evolution of chlorophyll fluorescence imaging and laser-induced fluorescence spectroscopy were used to monitor the seeds subjected to nanoparticles during 168h. The data demonstrate that CuONPs affected the steady-state maximum chlorophyll fluorescence ( ), the photochemical efficiency of photosystem II ( ), and non-photochemical quenching ( ) of Inga laurina seeds over time. Besides, the significantly increased at the seed development stage, near the root protrusion stage, probably due to energy dissipation at this germination step. Additionally, the results indicated that CuONPs can change the oscillatory rhythms of energy dissipation of the seeds, disturbing the circadian clock. In conclusion, the results indicate that CuONPs can affect the photosynthetic behavior of I. laurina seeds. These findings open opportunities for using chlorophyll fluorescence as a non-destructive tool to evaluate nanoparticle impact on photosynthetic activity in seed tissues.

Post-COVID-19 Condition: How Sociodemographic Factors, Physical Well-Being and Functionality Influence Quality of Life and Mental Health Symptoms

Background: Long COVID-19 syndrome remains a global public health problem, with more than 145 million people affected with multisystemic symptoms. Addressing the requirements of individuals impacted by a syndrome characterised by a complex and variable clinical presentation is of utmost importance. Identifying the variables that can exert influence and understanding their progression is essential for directing treatment strategies aimed at enhancing both independence and quality of life. Therefore, the aim of this study was to analyse the influence of sociodemographic and clinical variables on existence and their relationship with asthenia, anxiety symptoms and low mood. Methods: An analytical study secondary to an observational cross-sectional descriptive study. Results: Logistic regression showed significant univariate effects on asthenia [sex (p = 0.034); age (p = 0.042); Activities of Daily Living Questionnaire [ADQL (p = 0.002)] [physical functioning (p < 0.001) and general health (p = 0.014)] and multivariate [sex (p = 0.019), adult age (p = 0.01) and physical functioning (p = 0.04)]]; low mood [time of evolution (p = 0.028) and multivariate [time course (p = 0.007), ADLQ (p = 0.011), role physical (p = 0.013) and general health (p = 0.001)]] and anxiety [physical functioning (p = 0.046) and multivariate [physical functioning (p = 0.034), age (p = 0.011), time of evolution (p = 0.001) and ADQL (p = 0.011)]]. Conclusions: Increased age, gender and longer evolution time seem to favour the prevalence and occurrence of mental health symptoms; greater independence and good physical functioning are protective factors with respect to the occurrence of mental health-related symptoms in patients affected by post-COVID-19 condition.

Phylogenomic analyses of all species of swordtail fishes (genus Xiphophorus) show that hybridization preceded speciation

Hybridization has been recognized to play important roles in evolution, however studies of the genetic consequence are still lagging behind in vertebrates due to the lack of appropriate experimental systems. Fish of the genus Xiphophorus are proposed to have evolved with multiple ancient and ongoing hybridization events. They have served as an informative research model in evolutionary biology and in biomedical research on human disease for more than a century. Here, we provide the complete genomic resource including annotations for all described 26 Xiphophorus species and three undescribed taxa and resolve all uncertain phylogenetic relationships. We investigate the molecular evolution of genes related to cancers such as melanoma and for the genetic control of puberty timing, focusing on genes that are predicted to be involved in pre-and postzygotic isolation and thus affect hybridization. We discovered dramatic size-variation of some gene families. These persisted despite reticulate evolution, rapid speciation and short divergence time. Finally, we clarify the hybridization history in the entire genus settling disputed hybridization history of two Southern swordtails. Our comparative genomic analyses revealed hybridization ancestries that are manifested in the mosaic fused genomes and show that hybridization often preceded speciation.

Bio‐Based Foams to Function as Future Plastic Substitutes by Biomimicry: Inducing Hydrophobicity with Lignin

To replace common plastics, bio‐based alternatives are needed. Cellulose foams, as plant‐based materials, are the most attractive solution, being often biodegradable and inexpensive and having the potential for distributed production. Cellulose and its derivatives, as raw materials, present a fundamental challenge, as they are hydrophilic. Herein, this problem is solved by drawing inspiration from the hydrophobic barrier that lignin creates in wood and applying lignin to methylcellulose (MC) foams. The lignin (0.0–1.0 wt% being the range studied here) is applied directly to the suspension consisting of water and MC (1.8 wt%), which is then foamed and solidified to a dry 3D porous structure. By comparing different types of lignin and the resulting surface morphologies, it is shown that organosolv lignin (OL) most strongly self‐assembles to the air–foam interfaces, achieving area fractions up to 27%. Using different concentrations of OL, how hydrophobicity—described by the initial water contact angle and its time evolution—increases with increasing lignin concentration is then shown. Thus, significantly increased water resistance (up to 91 times higher compared to the pure MC foam), a crucial property for developing novel bio‐based materials that can compete with traditional plastics, is able to be achieved.

A piece-wise reconstruction of some mechanistic steps in Pickering emulsion polymerization: a semicontinuous styrene montmorillonite-supported process as a case example

AbstractBuilding on traditional emulsion polymerization research, which continues to yield results up to the present day, techniques have emerged to produce hybrid materials. One such technique is Pickering emulsion polymerization, with numerous industrial applications. Despite a growing interest in Pickering emulsion polymerization, the intrinsic mechanisms involved have been based mainly on the findings of classical emulsion polymerization. In this work, by relying on a minimum of assumptions and using a simple model and experimental data on conversion and particle size, we obtain information about the prevailing mechanisms. More specifically, we present four main findings based on data reported previously in the literature. First, in contrast to the three rate-of-reaction intervals reported in classical emulsion polymerization, the integro-differential method yielded only two rate-of-reaction intervals against conversion. Second, a master curve is constructed by plotting the reaction rate against overall conversion, showing a maximum of approximately 55% conversion. Third, despite having a semicontinuous process, monomer concentration inside the particles is not constant. Finally, particle density is a strong function of the Pickering agent concentration, where two fitting parameters (nucleation and coagulation) allowed an accurate description for the particle number time evolution. Both parameters showed a power-law dependence with clay concentration.

Anomalous quantum transport in fractal lattices

Fractal lattices are self-similar structures with repeated patterns on different scales. Quantum transport through such structures is subtle due to the possible co-existence of localized and extended states. Here, we study the dynamical properties of two fractal lattices, the Sierpiński gasket and the Sierpiński carpet. While the gasket exhibits sub-diffusive behavior, sub-ballistic transport occurs in the carpet. We show that the different dynamical behavior is in line with qualitative differences of the systems’ spectral properties. Specifically, in contrast to the Sierpiński carpet, the Sierpiński gasket exhibits an inverse power-law behavior of the level spacing distribution. As a possible technological application, we discuss a memory effect in the Sierpiński gasket which allows to read off the phase information of an initial state from the spatial distribution after long evolution times. We also show that interpolating between fractal and regular lattices allows for flexible tuning between different transport regimes.

Adaptive radiation without independent stages of trait evolution in a group of Caribbean anoles.

Adaptive radiation involves diversification along multiple trait axes, producing phenotypically diverse, species-rich lineages. Theory generally predicts that multi-trait evolution occurs via a 'stages' model, with some traits saturating early in a lineage's history, and others diversifying later. Despite its multidimensional nature, however, we know surprisingly little about how different suites of traits evolve during adaptive radiation. Here, we investigated the rate, pattern, and timing of morphological and physiological evolution in the anole lizard adaptive radiation from the Caribbean island of Hispaniola. Rates and patterns of morphological and physiological diversity are largely unaligned, corresponding to independent selective pressures associated with structural and thermal niches. Cold tolerance evolution reflects parapatric divergence across elevation, rather than niche partitioning within communities. Heat tolerance evolution and the preferred temperature evolve more slowly than cold tolerance, reflecting behavioral buffering, particularly in edge-habitat species (a pattern associated with the Bogert effect). In contrast to the nearby island of Puerto Rico, closely related anoles on Hispaniola do not sympatrically partition thermal niche space. Instead, allopatric and parapatric separation across biogeographic and environmental boundaries serves to keep morphologically similar close relatives apart. The phenotypic diversity of this island's adaptive radiation accumulated largely as a by-product of time, with surprisingly few exceptional pulses of trait evolution. A better understanding of the processes that guide multidimensional trait evolution (and nuance therein) will prove key in determining whether the stages model should be considered a common theme of adaptive radiation.

Surface micro-morphology model involved in grinding of GaN crystals driven by strain-rate and abrasive coupling effects

The complexity of the interaction between the workpiece and abrasives, the characterisation difficulty of the strain-rate effect, and the analytical difficulty of brittle-ductile coexistence removal pose significant challenges in surface micro-morphology modelling of brittle-solid grinding. To overcome these bottlenecks, a theoretical model of the normal scratching force driven by the strain-rate effect was developed to verify the strain-rate sensitivity coefficients of gallium nitride (GaN) crystals. Impact scratching tests with a single grit further emphasised that the brittle-to-ductile transition and subsurface damage behaviour of GaN crystals exhibited a distinct strain-rate dependence. Subsequently, a theoretical model of the surface micro-morphology involved in the grinding of GaN crystals was developed by comprehensively considering the strain rate, abrasive coupling effect, time evolution, abrasive randomness, and elastic-to-plastic and brittle-to-ductile transition depths. The simulated results of the model agreed well with the experimental results, with an average error of < 10%. The model indicated that the ground surface micro-morphology and roughness were insensitive to variations in the grinding depth. Under the allowable conditions of the grinder stiffness and dynamic balance, appropriately increasing the wheel speed and grinding depth, decreasing the feed speed, and refining the abrasive size could effectively improve the proportion of ductile removal during the grinding of brittle solids. The results not only enhance the understanding of the abrasive coupling effect on surface micro-morphological evolution, material removal, and damage accumulation, but also provide theoretical guidance for the parameter optimisation involved in the grinding of brittle solids.

Collisionless Relaxation from Near-equilibrium Configurations: Linear Theory and Application to Tidal Stripping

Placed slightly out of dynamical equilibrium, an isolated stellar system quickly returns toward a steady virialized state. We study this process of collisionless relaxation using the matrix method of linear response theory. We show that the full phase-space distribution of the final virialized state can be recovered directly from the disequilibrium initial conditions, without the need to compute the time evolution of the system. This shortcut allows us to determine the final virialized configuration with minimal computational effort. Complementing this result, we develop tools to model the system's full time evolution in the linear approximation. In particular, we show that moments of the velocity distribution can be efficiently computed using a generalized moment matrix. We apply our linear methods to study the relaxation of energy-truncated Hernquist spheres, mimicking the tidal stripping of a cuspy dark matter subhalo. Comparison of our linear predictions against controlled, isolated N-body simulations shows agreement at percent level for the parts of the system where a linear response to the perturbation is expected. We find that relaxation generates a tangential velocity anisotropy in the intermediate regions, despite the initial disequilibrium state having isotropic kinematics. Our results also strengthen the case for relaxation depleting the amplitude of the density cusp, without affecting its asymptotic slope. Finally, we compare the linear theory against an N-body simulation of tidal stripping on a radial orbit, confirming that the theory still accurately predicts density and velocity dispersion profiles for most of the system.

Editorial Comment: Cardiac CT and MRI Training-Redefining Competency in Times of Evolution and Need.

Editorial Comment: Cardiac CT and MRI Training-Redefining Competency in Times of Evolution and Need.

Analysis of a Resistive-Capacitive Shunted Josephson Junction with Topologically Nontrivial Barrier Coupledto a RLC Resonator

This paper presents the resistive-capacitive shunted Josephson junction (RCSJJ) with a topologically nontrivial barrier (TNB) coupled to a linear RLC resonator. The rate equations describing RCSJJ with TNB coupled to the linear RLC resonator are established via Kirchhoff’s current and voltage laws. The model exhibits four, two, or no equilibrium points depending on the external direct current (DC) source and the fractional parameter. The stability analysis of the equilibrium points with credit to the Routh-Hurwitz stability criterion reveals that the stability of equilibrium points depends on the DC source and the fractional parameter. Current-voltage characteristic reveals the presence of a birhythmicity zone which is sensitive to the fractional parameter m. As the fractional parameter increases, the coexistence of the resonant state is destroyed, which is followed simultaneously by the appearance of a new resonance state. Depending on initial conditions, birhythmic behaviour is characterized by the existence of a limit cycle. The projection of the phase space in the specific plane and the time evolution of charge is predicted in which the amplitude of attractors reported is sensitive to the parameter m. Lastly, with a defined fractional parameter, the amplitude of the branch locked to the resonator is greater than the unlocked branch.