Distribution Of Time Scales Research Articles

Posterior parietal cortex regulates neural timescales and stimulus-driven attentional modulation in the prefrontal cortex.

Intrinsic neural timescales characterize the dynamics of endogenous fluctuations in neural activity. We measured the intrinsic timescales of prefrontal neurons and examined their changes during posterior parietal cortex (PPC) inactivation. Frontal eye field (FEF) neurons within the prefrontal cortex (PFC) exhibited a bimodal distribution of timescales: short-timescale neurons showed stronger transient visual responses, while long-timescale neurons exhibited stronger sustained modulation during stimulus-driven attention. PPC inactivation increased intrinsic timescales in both neuron types, with a 15-fold greater increase in short-timescale neurons. Additionally, it reduced visual and attentional modulation, particularly impairing attentional modulation in long-timescale neurons. Our results provide the first causal evidence that the intrinsic timescales of FEF neurons depend on PPC and suggest the presence of at least two network motifs with distinct timescales that contribute to neuronal dynamics and functional computations within FEF. The heterogeneity in these timescales may facilitate cognitive flexibility, allowing PFC to adapt to varying task demands.

Bayesian impedance deconvolution using timescale distribution for lithium-ion battery state estimation

The distribution of relaxation times (DRT) and distribution of diffusion times (DDT) are widely recognized as effective model-free methods for deconvolving the internal properties of complex electrochemical systems using electrochemical impedance spectroscopy (EIS) data. This study proposes an integrated framework that employs a Bayesian approach to accurately estimate both DRT and DDT and machine learning techniques to enhance capacity estimation, incorporating Gaussian process regression and transformer networks. These methods utilize the inferred DRT and DDT as inputs to predict the discharge capacity. In addition, we perform a peak analysis on the estimated DRT and DDT to extract additional physically meaningful features, which have also proven to be effective inputs for capacity prediction. The applicability of the proposed framework to the EIS experimental data of lithium-ion cells is demonstrated and compared with existing capacity estimation methods. The proposed framework demonstrates a mean absolute error in capacity prediction below 3.03% when using DRT and DDT directly and 2.71% when using extracted features, outperforming existing methods by approximately one to three percentage points. Our Bayesian approach, combined with peak analysis and the integration of machine learning techniques, enables a more robust diagnosis of the internal state of lithium-ion batteries through EIS measurements.

Valence can control the nonexponential viscoelastic relaxation of multivalent reversible gels.

Gels made of telechelic polymers connected by reversible cross-linkers are a versatile design platform for biocompatible viscoelastic materials. Their linear response to a step strain displays a fast, near-exponential relaxation when using low-valence cross-linkers, while larger supramolecular cross-linkers bring about much slower dynamics involving a wide distribution of timescales whose physical origin is still debated. Here, we propose a model where the relaxation of polymer gels in the dilute regime originates from elementary events in which the bonds connecting two neighboring cross-linkers all disconnect. Larger cross-linkers allow for a greater average number of bonds connecting them but also generate more heterogeneity. We characterize the resulting distribution of relaxation timescales analytically and accurately reproduce stress relaxation measurements on metal-coordinated hydrogels with a variety of cross-linker sizes including ions, metal-organic cages, and nanoparticles. Our approach is simple enough to be extended to any cross-linker size and could thus be harnessed for the rational design of complex viscoelastic materials.

Ocean Heat Convergence and North Atlantic multidecadal heat content variability

Abstract We construct an upper ocean (0-1000m) North Atlantic heat budget (26°-67°N) for the period 1950-2020 using multiple observational datasets and an eddy-permitting global ocean model. On multidecadal timescales ocean heat transport convergence controls ocean heat content (OHC) tendency in most regions of the North Atlantic with little role for diffusive processes. In the subpolar North Atlantic (45°N-67°N) heat transport convergence is explained by geostrophic currents whereas ageostrophic currents make a significant contribution in the subtropics (26°N-45°N). The geostrophic contribution in all regions is dominated by anomalous advection across the time-mean temperature gradient although other processes make a significant contribution particularly in the subtropics. The timescale and spatial distribution of the anomalous geostrophic currents are consistent with a simple model of basin scale thermal Rossby waves propagating westwards/northwestwards in the subpolar gyre and multidecadal variations in regional OHC are explained by geostrophic currents periodically coming into alignment with the mean temperature gradient as the Rossby wave passes through. The global ocean model simulation shows that multidecadal variations in the Atlantic Meridional Overturning Circulation are synchronized with the ocean heat transport convergence consistent with modulation of the west-east pressure gradient by the propagating Rossby wave.

Spatially resolved microlensing time-scale distributions across the Galactic bulge with the VVV survey

ABSTRACT We analyse 1602 microlensing events found in the VISTA Variables in the Via Lactea (VVV) near-infrared (NIR) survey data. We obtain spatially resolved, efficiency-corrected time-scale distributions across the Galactic bulge (|ℓ| < 10°, |b| < 5°), using a Bayesian hierarchical model. Spatially resolved peaks and means of the time-scale distributions, along with their marginal distributions in strips of longitude and latitude, are in agreement at a 1σ level with predictions based on the Besançon model of the Galaxy. We find that the event time-scales in the central bulge fields (|ℓ| < 5°) are on average shorter than the non-central (|ℓ| > 5°) fields, with the average peak of the lognormal time-scale distribution at 23.6 ± 1.9 d for the central fields and 29.0 ± 3.0 d for the non-central fields. Our ability to probe the structure of the bulge with this sample of NIR microlensing events is limited by the VVV survey’s sparse cadence and relatively small number of detected microlensing events compared to dedicated optical surveys. Looking forward to future surveys, we investigate the capability of the Roman telescope to detect spatially resolved asymmetries in the time-scale distributions. We propose two pairs of Roman fields, centred on (ℓ = ±9, 5°, b = −0.125°) and (ℓ = −5°, b = ±1.375°) as good targets to measure the asymmetry in longitude and latitude, respectively.

Understanding stress relaxation behavior of amorphous polystyrene based on microstructural heterogeneity

The relationship between stress relaxation behavior and inherent microstructural heterogeneity in amorphous polystyrene materials is studied in this work. Starting from the basic Maxwell viscoelastic model and extending to the three-parameter stretched exponential equation, the nature of the distribution of characteristic timescales and the segmental effects during polymer stress relaxation are discussed. The results indicate that the stress relaxation behavior of amorphous polymers exhibits non-exponential characteristics. Neither a single characteristic time with exponential decay nor a finite spectrum method with finite characteristic time can adequately describe the stress relaxation behavior of polystyrene due to the continuous distribution of characteristic timescales resulting from microstructural heterogeneity in amorphous polymers. In addition, the changes in stress relaxation behavior caused by physical aging are explored. Aging leads to a transition of the system towards a more stable energy state, making it difficult to activate the relaxation of the individual units, thus slowing down the stress relaxation process and increasing the characteristic time.

Exponential dynamics of DNA methylation with age

The association of DNA methylation with age has been extensively studied. Previous work has investigated the trajectories of methylation with age, and developed predictive biomarkers of age. However, we still have a limited understanding of the functional form of methylation-age dynamics. To address this we present a theoretical framework to model the dynamics of DNA methylation at single sites. We show that this model leads to convergence to a steady-state methylation level at an exponential rate. By fitting the model to a dataset that measures changes in DNA methylation in the brain from birth to old age, we show that the timescales of this exponential convergence are heterogeneous across sites. To model this heterogeneity we generated a simulation of CpG Methylation changes with time and investigated the functional form of the dynamics of methylation with age under the empirical distribution of timescales estimated from the dataset. The resulting dynamics of the average methylation of the system were characterized and were found to closely follow an exponential trajectory. We conclude that DNA methylation can be modeled as a system that starts out of equilibrium at birth and approaches equilibrium with age in an exponential fashion. These insights illustrate the importance of accounting for nonlinear dynamics when utilizing age associated DNA methylation changes for constructing biomarkers of aging. Thus DNA methylation, along with the exponentially increasing risk of mortality with age, further establishes the exponential nature of aging.

A reservoir of timescales emerges in recurrent circuits with heterogeneous neural assemblies.

The temporal activity of many physical and biological systems, from complex networks to neural circuits, exhibits fluctuations simultaneously varying over a large range of timescales. Long-tailed distributions of intrinsic timescales have been observed across neurons simultaneously recorded within the same cortical circuit. The mechanisms leading to this striking temporal heterogeneity are yet unknown. Here, we show that neural circuits, endowed with heterogeneous neural assemblies of different sizes, naturally generate multiple timescales of activity spanning several orders of magnitude. We develop an analytical theory using rate networks, supported by simulations of spiking networks with cell-type specific connectivity, to explain how neural timescales depend on assembly size and show that our model can naturally explain the long-tailed timescale distribution observed in the awake primate cortex. When driving recurrent networks of heterogeneous neural assemblies by a time-dependent broadband input, we found that large and small assemblies preferentially entrain slow and fast spectral components of the input, respectively. Our results suggest that heterogeneous assemblies can provide a biologically plausible mechanism for neural circuits to demix complex temporal input signals by transforming temporal into spatial neural codes via frequency-selective neural assemblies.

Exciton-polaron interactions in metal halide perovskite nanocrystals revealed via two-dimensional electronic spectroscopy.

Metal halide perovskite nanocrystals have been under intense investigation for their promise in optoelectronic devices due to their remarkable physics, such as liquid/solid duality. This liquid/solid duality may give rise to their defect tolerance and other such useful properties. This duality means that the electronic states are fluctuating in time, on a distribution of timescales from femtoseconds to picoseconds. Hence, these lattice induced energy fluctuations that are connected to polaron formation are also connected to exciton formation and dynamics. We observe these correlations and dynamics in metal halide perovskite nanocrystals of CsPbI3 and CsPbBr3 using two-dimensional electronic (2DE) spectroscopy, with its unique ability to resolve dynamics in heterogeneously broadened systems. The 2DE spectra immediately reveal a previously unobserved excitonic splitting in these 15nm NCs that may have a coarse excitonic structure. 2D lineshape dynamics reveal a glassy response on the 300fs timescale due to polaron formation. The lighter Br system shows larger amplitude and faster timescale fluctuations that give rise to dynamic line broadening. The 2DE signals enable 1D transient absorption analysis of exciton cooling dynamics. Exciton cooling within this doublet is shown to take place on a slower timescale than within the excitonic continuum. The energy dissipation rates are the same for the I and Br systems for incoherent exciton cooling but are very different for the coherent dynamics that give rise to line broadening. Exciton cooling is shown to take place on the same timescale as polaron formation, revealing both as coupled many-body excitation.

Phenomenology of the Prethermal Many-Body Localized Regime.

The dynamical phase diagram of interacting disordered systems has seen substantial revision over the past few years. Theory must now account for a large prethermal many-body localized regime in which thermalization is extremely slow, but not completely arrested. We derive a quantitative description of these dynamics in short-ranged one-dimensional systems using a model of successive many-body resonances. The model explains the decay timescale of mean autocorrelators, the functional form of the decay-a stretched exponential-and relates the value of the stretch exponent to the broad distribution of resonance timescales. The Jacobi method of matrix diagonalization provides numerical access to this distribution, as well as a conceptual framework for our analysis. The resonance model correctly predicts the stretch exponents for several models in the literature. Successive resonances may also underlie slow thermalization in strongly disordered systems in higher dimensions, or with long-range interactions.

Seasonal overturning variability in the eastern North Atlantic subpolar gyre: a Lagrangian perspective

Abstract. Both observations and ocean reanalyses show a pronounced seasonality in the strength of the Atlantic meridional overturning circulation (MOC) within the eastern North Atlantic subpolar gyre (eSPG). However, attributing this overturning seasonality to seasonal dense water formation remains challenging owing to the wide distribution of recirculation timescales within the Iceland and Irminger basins. Here, we investigate the nature of seasonal overturning variability using Lagrangian water parcel trajectories initialised across the Overturning in the Subpolar North Atlantic Program (OSNAP) East section within an eddy-permitting ocean sea ice hindcast. By adopting a Lagrangian perspective, we show that the seasonal minimum of the Eulerian overturning at OSNAP East in autumn results from a combination of enhanced stratification and increased southward transport within the upper East Greenland Current. This convergence of southward transport within the MOC upper limb is explained by decreasing water parcel recirculation times in the upper Irminger Sea, consistent with a gyre-scale response to seasonal wind forcing. To account for the diversity of recirculation times within the eSPG, we also quantify the Lagrangian overturning (LMOC) as the total dense water formation along water parcel trajectories. The majority of water parcels, sourced from the central and southern branches of the North Atlantic Current, fail to return to OSNAP East prior to experiencing wintertime diapycnal transformation into the lower limb, and thus they determine the mean strength of the LMOC within the eSPG (8.9 ± 2.2 Sv). The strong seasonality of the LMOC is explained by a small collection of upper-limb water parcels, circulating rapidly (≤ 8.5 months) in the upper Irminger and central Iceland basins, whose along-stream transformation is determined by their month of arrival at OSNAP East.

The brightest galaxies at cosmic dawn

ABSTRACT Recent JWST observations suggest an excess of z ≳ 10 galaxy candidates above most theoretical models. Here, we explore how the interplay between halo formation time-scales, star formation efficiency, and dust attenuation affects the properties and number densities of galaxies observed in the early Universe. To guide intuition, we calculate the theoretical upper limit on the UV luminosity function (LF), assuming star formation is 100 per cent efficient and all gas in haloes is converted into stars, and that galaxies are at the peak age for UV emission (∼10 Myr). This upper limit is ∼4 orders of magnitude greater than current observations, implying no formal tension with star formation in Lambda cold dark matter cosmology. In a more realistic model, we use the distribution of halo formation time-scales derived from extended Press–Schechter theory as a proxy for star formation rate (SFR). We predict that the galaxies observed so far at z ≳ 10 are dominated by those with the fastest formation time-scales, and thus most extreme SFRs and young ages. These galaxies can be upscattered by ∼1.5 mag compared to the median UV magnitude versus halo mass relation. This likely introduces a selection effect at high redshift whereby only the youngest (≲10 Myr), most highly star-forming galaxies (specific SFR$\gtrsim 30\, \mathrm{Gyr}^{-1}$) have been detected so far. Furthermore, our modelling suggests that redshift evolution at the bright end of the UV LF is substantially affected by the build-up of dust attenuation. We predict that deeper JWST observations (reaching m ∼ 30) will reveal more typical galaxies with relatively older ages (∼100 Myr) and less extreme specific SFRs ($\sim 10\, \mathrm{Gyr}^{-1}$ for a MUV ∼ −20 galaxy at z ∼ 10).

The Hydrogen-poor Superluminous Supernovae from the Zwicky Transient Facility Phase I Survey. I. Light Curves and Measurements

During the Zwicky Transient Facility (ZTF) Phase I operations, 78 hydrogen-poor superluminous supernovae (SLSNe-I) were discovered in less than 3 yr, constituting the largest sample from a single survey. This paper (Paper I) presents the data, including the optical/UV light curves and classification spectra, while Paper II in this series will focus on the detailed analysis of the light curves and modeling. Our photometry is primarily taken by ZTF in the g, r, and i bands, and with additional data from other ground-based facilities and Swift. The events of our sample cover a redshift range of z = 0.06 − 0.67, with a median and 1σ error (16% and 84% percentiles) of . The peak luminosity covers −22.8 mag ≤ M g,peak ≤ −19.8 mag, with a median value of mag. The light curves evolve slowly with a mean rest-frame rise time of t rise = 41.9 ± 17.8 days. The luminosity and timescale distributions suggest that low-luminosity SLSNe-I with a peak luminosity ∼−20 mag or extremely fast-rising events (<10 days) exist, but are rare. We confirm previous findings that slowly rising SLSNe-I also tend to fade slowly. The rest-frame color and temperature evolution show large scatters, suggesting that the SLSN-I population may have diverse spectral energy distributions. The peak rest-frame color shows a moderate correlation with the peak absolute magnitude, i.e., brighter SLSNe-I tend to have bluer colors. With optical and UV photometry, we construct the bolometric luminosity and derive a bolometric correction relation that is generally applicable for converting g, r-band photometry to the bolometric luminosity for SLSNe-I.

Viscoelastic behavior and fragility of Se-deficient chalcogenide liquids in As-P-Se system

The viscoelastic behavior of supercooled Se-deficient liquids in the series As x Se 100-x (40 ≤ x ≤ 60) and P x As 4–x Se 3 (0 ≤ x ≤ 2.8) are studied using parallel plate rheometry. The compositional variations in the viscosity and fragility of these liquids are shown to be consistent with the corresponding structural evolution. While the shear relaxation of As x Se 100-x liquids with 40 ≤ x ≤ 50 is associated with the dynamics of As Se bond scission/renewal, the As-rich liquids with x ≥ 55 are found to display an additional low-frequency process, which is related to a cooperative interconversion between molecular and network structural moieties. A similar behavior is also exhibited by the As-rich liquids in the P x As 4–x Se 3 series. In contrast, the P-rich liquids characterized by high molecule content display a power-law relaxation behavior resulting from a rather broad distribution of relaxation timescales associated with various dynamical modes of single molecules and molecular clusters.

Comparative analysis for commercial li-ion batteries degradation using the distribution of relaxation time method based on electrochemical impedance spectroscopy

As a non-destructive method for characterizing battery dynamic behavior, electrochemical impedance spectroscopy (EIS) is becoming increasingly important to analyze electrode process kinetics, electric double layers, and diffusion in the study of battery performance. However, overlapping features of the EIS semicircle of commercial batteries over the lifetime bring ambiguities concerning their physicochemical significance spectra in the timescale distribution. In this work, we analyze the impedance of kinetic processes and corresponding time constants in three types of commercial batteries at different aging stages via the optimized distribution of relaxation time (DRT) investigation which extracts evolution details of different time scales that could not be distinguished. Firstly, informative aging tests for battery LiNi0·8Co0·1Mn0·1O2 (NCM), LixFePO4 (LFP), and LiNixCoyAlzO2 (NCA) during the whole life cycle were designed to simulate different electric vehicles working conditions, followed by periodical EIS measurements. And then, the capacity retention, as well as the deconvolution of EIS for discriminating the electrochemical mechanisms of commercial LiBs during aging were compared. Gaussian process and ridge regression are dedicated to complex superposed impedance spectra to DRT. Combining both experimental measurements and multi-peak analysis for DRT, the analysis determined the impedance distribution characteristics of batteries with different materials during cycling, which facilitates rapid identification of aging mechanisms and further life prediction. Therefore, the peak characteristic analysis method based on the DRT analysis can be employed to diagnose and predict the impact of battery performance.

Molecular and Atomic Clouds Associated with the Gamma-Ray Supernova Remnant Puppis A

We have carried out a study of the interstellar medium (ISM) toward the shell-like supernova remnant (SNR) Puppis A using NANTEN CO and ATCA H i data. We synthesized a comprehensive picture of the SNR radiation by combining the ISM data with the gamma-ray and X-ray distributions. The ISM, both atomic and molecular gas, is dense and highly clumpy, and is distributed all around the SNR, but mainly in the northeast. The CO distribution revealed an enhanced line intensity ratio of CO(J = 2–1)/(J = 1–0) transitions as well as CO line broadening, which indicate shock heating/acceleration. The results support the assertion that Puppis A is located at 1.4 kpc, in the Local Arm. The ISM interacting with the SNR has a large mass of ∼104 M ⊙, which is dominated by H i, showing good spatial correspondence with the Fermi-LAT gamma-ray image. This favors a hadronic origin of the gamma-rays, while an additional contribution from a leptonic component is not excluded. The distribution of the X-ray ionization timescales within the shell suggests that the shock front ionized various parts of the ISM at epochs ranging over a few to ten thousand years. We therefore suggest that the age of the SNR is around 104 yr as given by the largest ionization timescale. We estimate the total cosmic-ray energy W p to be 1047 erg, which is well placed in the cosmic-ray escaping phase of an age–W p plot including more than ten SNRs.

Optical Monitoring and Variability Analyses of the FSRQ 3C 454.3

Based on the database monitored by the 1.26 m National Astronomical Observatory–Guangzhou University Infrared/Optical Telescope, we studied the optical variabilities of FSRQ 3C454.3. The monitoring period was from 2016 October 17 to 2018 December 14, and there were 6701 observations covering the g, r, and i bands (2196 at the g band, 2214 at the r band, and 2291 at the i band). (1) The maximum variabilities were Δm g = 2.806 ± 0.124 mag at the g band; Δm r = 2.365 ± 0.160 mag at the r band; and Δm i = 3.126 ± 0.070 mag at the i band. (2) Among the gri intraday lightcurves, there are 172 portions of the data sets showing intraday variability (IDV). The distributions of IDV timescales (ΔT) can be profiled by a three-order Gaussian function, with the center values ΔT 1 = 17.18 minutes, ΔT 2 = 34.91 minutes, and ΔT 3 = 68.92 minutes. These results imply that the origin of IDVs is very complicated. (3) Based on the IDV timescales, we obtained the emission size R ≤ 7.17 × 1015 cm, fixed the broad-line region and modeled the spectral energy distributions. (4) We used the Jurkevich method, red-noise fitting, and the weighted wavelet Z-transform to analyze the long-term variabilities and obtained indications of a possible period of P = 2.92 ± 0.85 yr, and used the binary black hole system to explain this period. Based on the long-term period, we can estimate the time until merger of the binary black hole, t merge = 6.69 × 103 yr, and the luminosity of gravitational waves, L G = 1.56 × 1048 erg s−1.

Oculomotor plant and neural dynamics suggest gaze control requires integration on distributed timescales.

A fundamental principle of biological motor control is that the neural commands driving movement must conform to the response properties of the motor plants they control. In the oculomotor system, characterizations of oculomotor plant dynamics traditionally supported models in which the plant responds to neural drive to extraocular muscles on exclusively short, subsecond timescales. These models predict that the stabilization of gaze during fixations between saccades requires neural drive that approximates eye position on longer timescales and is generated through the temporal integration of brief eye velocity-encoding signals that cause saccades. However, recent measurements of oculomotor plant behaviour have revealed responses on longer timescales. Furthermore, measurements of firing patterns in the oculomotor integrator have revealed a more complex encoding of eye movement dynamics. Yet, the link between these observations has remained unclear. Here we use measurements from the larval zebrafish to link dynamics in the oculomotor plant to dynamics in the neural integrator. The oculomotor plant in both anaesthetized and awake larval zebrafish was characterized by a broad distribution of response timescales, including those much longer than 1s. Analysis of the firing patterns of oculomotor integrator neurons, which exhibited a broadly distributed range of decay time constants, demonstrates the sufficiency of this activity for stabilizing gaze given an oculomotor plant with distributed response timescales. This work suggests that leaky integration on multiple, distributed timescales by the oculomotor integrator reflects an inverse model for generating oculomotor commands, and that multi-timescale dynamics may be a general feature of motor circuitry. KEY POINTS: Recent observations of oculomotor plant response properties and neural activity across the oculomotor system have called into question classical formulations of both the oculomotor plant and the oculomotor integrator. Here we use measurements from new and published experiments in the larval zebrafish together with modelling to reconcile recent oculomotor plant observations with oculomotor integrator function. We developed computational techniques to characterize oculomotor plant responses over several seconds in awake animals, demonstrating that long timescale responses seen in anaesthetized animals extend to the awake state. Analysis of firing patterns of oculomotor integrator neurons demonstrates the sufficiency of this activity for stabilizing gaze given an oculomotor plant with multiple, distributed response timescales. Our results support a formulation of gaze stabilization by the oculomotor system in which commands for stabilizing gaze are generated through integration on multiple, distributed timescales.

Rheology of supercooled P-Se glass-forming liquids: From networks to molecules and the emergence of power-law relaxation behavior.

The effect of the network-to-molecular structural transformation with increasing phosphorus content in PxSe100-x (30 ≤ x ≤ 67) supercooled liquids on their shear-mechanical response is investigated using oscillatory shear rheometry. While network liquids with 30 ≤ x ≤ 40 are characterized by shear relaxation via a network bond scission/renewal process, a Maxwell scaling of the storage (G') and loss (G″) shear moduli, and a frequency-independent viscosity at low frequencies, a new relaxation process emerges in liquids with intermediate compositions (45 ≤ x ≤ 50). This process is attributed to an interconversion between network and molecular structural moieties. Predominantly molecular liquids with x ≥ 63, on the other hand, are characterized by a departure from Maxwell behavior as the storage modulus shows a linear frequency scaling G'(ω) ∼ ω over nearly the entire frequency range below the G'-G″ crossover and a nearly constant ratio of G″/G' in the terminal region. Moreover, the dynamic viscosity of these rather fragile molecular liquids shows significant enhancement over that of network liquids at frequencies below the dynamical onset and does not reach a frequency-independent regime even at frequencies that are four orders of magnitude lower than that of the onset. Such power-law relaxation behavior of the molecular liquids is ascribed to an extremely broad distribution of relaxation timescales with the coexistence of rapid rotational motion of individual molecules and cooperative dynamics of transient molecular clusters, with the latter being significantly slower than the shear relaxation timescale.

A viscoelastic Timoshenko beam: Model development, analysis, and investigation

Vibrations are ubiquitous in mechanical or biological systems, and they are ruinous in numerous circumstances. We develop a viscoelastic Timoshenko beam model, which naturally captures distinctive power-law responses arising from a broad distribution of time-scales presented in the complex internal structures of viscoelastic materials and so provides a very competitive description of the mechanical responses of viscoelastic beams, thick beams, and beams subject to high-frequency excitations. We, then, prove the well-posedness and regularity of the viscoelastic Timoshenko beam model. We finally investigate the performance of the model, in comparison with the widely used Euler–Bernoulli and Timoshenko beam models, which shows the utility of the new model.