Slow Time Scale Research Articles

A multi-timescale framework for state monitoring and lifetime prognosis of lithium-ion batteries

Battery State-of-charge (SOC) estimation and lifetime prognosis play important roles in its fuel-gauging and predictive maintenance. However, the inevitable modeling biases and measurement noises caused by the complexity of battery dynamics in nonlinearity, temperature sensitivity, and degradation, still challenge the accuracy and robustness. To bridge this research gap, this paper presents a multi-timescale framework for SOC estimation and lifetime prediction of lithium-ion batteries. In the fast timescale, a recursive-least-square-based parameter identification algorithm is first employed to eliminate the effects of identification errors on SOC estimation and reduce the dimension of the SOC observer. Then, a robust observer and dual extended-Kalman-filter (DEKF) are combined to achieve simultaneous SOC and capacity estimation against bounded modeling errors. In the slow timescale, the battery lifetime is predicted through a particle-filtering based on the capacity. The effectiveness and superiority of the proposed method are demonstrated by both simulation and experimental results conducted on LiCoO2 cells. The results indicate that the root-mean-square-error of the SOC and capacity can be achieved within 3.5% and 0.5%, respectively, in the presence of the model mismatch. In addition, the lifetime prediction framework can also ensure accurate lifetime prediction.

Extraction of rapid kinetics from smFRET measurements using integrative detectors

SUMMARYHidden Markov models (HMMs) are used to learn single-molecule kinetics across a range of experimental techniques. By their construction, HMMs assume that single-molecule events occur on slower timescales than those of data acquisition. To move beyond that HMM limitation and allow for single-molecule events to occur on any timescale, we must treat single-molecule events in continuous time as they occur in nature. We propose a method to learn kinetic rates from single-molecule Förster resonance energy transfer (smFRET) data collected by integrative detectors, even if those rates exceed data acquisition rates. To achieve that, we exploit our recently proposed “hidden Markov jump process” (HMJP), with which we learn transition kinetics from parallel measurements in donor and acceptor channels. HMJPs generalize the HMM paradigm in two critical ways: (1) they deal with physical smFRET systems as they switch between conformational states in continuous time, and (2) they estimate transition rates between conformational states directly without having recourse to transition probabilities or assuming slow dynamics. Our continuous-time treatment learns the transition kinetics and photon emission rates for dynamic regimes that are inaccessible to HMMs, which treat system kinetics in discrete time. We validate our framework’s robustness on simulated data and demonstrate its performance on experimental data from FRET-labeled Holliday junctions.

Growth, death, and resource competition in sessile organisms

Population-level scaling in ecological systems arises from individual growth and death with competitive constraints. We build on a minimal dynamical model of metabolic growth where the tension between individual growth and mortality determines population size distribution. We then separately include resource competition based on shared capture area. By varying rates of growth, death, and competitive attrition, we connect regular and random spatial patterns across sessile organisms from forests to ants, termites, and fairy circles. Then, we consider transient temporal dynamics in the context of asymmetric competition, such as canopy shading or large colony dominance, whose effects primarily weaken the smaller of two competitors. When such competition couples slow timescales of growth to fast competitive death, it generates population shocks and demographic oscillations similar to those observed in forest data. Our minimal quantitative theory unifies spatiotemporal patterns across sessile organisms through local competition mediated by the laws of metabolic growth, which in turn, are the result of long-term evolutionary dynamics.

An Evaluation of Optical Absorbance Kinetics for the Detection of Micro-Porosity in Molecularly Doped Polymer Thin-Films

The use of optical absorbance kinetics to identify micro-porous regions in doped polymer films is evaluated. Data are presented for a series of hydrazone doped polymer films which are found to optically bleach upon exposure to an ultra violet (UV) radiation source. The UV absorbance kinetics are found to exhibit distinctive characteristics for the various polymers studied, with changes in film absorbance occurring either in a fast (<103 s) or slow (>104 s) timescale. An interpretation of these distinctive timescales based upon a cellular-automata model of the absorbance kinetics suggests that the underlying photo-oxidation of the hydrazone is highly sensitive to underlying micro-porosity in the films which controls the necessary supply of absorbed oxygen for photo-cyclic reaction.

Unraveling the Coupling between Conformational Changes and Ligand Binding in Ribose Binding Protein Using Multiscale Molecular Dynamics and Free-Energy Calculations.

Conformational changes of proteins upon ligand binding are usually explained in terms of several mechanisms including the induced fit, conformational selection, or their mixtures. Due to the slow time scales, conventional molecular dynamics (cMD) simulations based on the atomistic models cannot easily simulate the open-to-closed conformational transition in proteins. In our previous study, we have developed an enhanced sampling scheme (generalized replica exchange with solute tempering selected surface charged residues: gREST_SSCR) for multidomain proteins and applied it to ligand-mediated conformational changes in the G134R mutant of ribose-binding protein (RBPG134R) in solution. The free-energy landscape (FEL) of RBPG134R in the presence of a ribose at the binding site included the open and closed states and two intermediates, open-like and closed-like forms. Only the open and open-like forms existed in the FEL without a ribose. In the current study, the coupling between the conformational changes and ligand binding is further investigated using coarse-grained MD, multiple atomistic cMD, and free-energy calculations. The ribose is easily dissociated from the binding site of wild-type RBP and RBPG134R in the cMD simulations starting from the open and open-like forms. In contrast, it is stable at the binding site in the simulations from the closed and closed-like forms. The free-energy calculations provide the binding affinities of different structures, supporting the results of cMD simulations. Importantly, cMD simulations from the closed-like structures reveal transitions toward the closed one in the presence of a bound ribose. On the basis of the computational results, we propose a molecular mechanism in which conformational selection and induced fit happen in the first and second halves of the open-to-closed transition in RBP, respectively.

Adaptation of spontaneous activity in the developing visual cortex

Spontaneous activity drives the establishment of appropriate connectivity in different circuits during brain development. In the mouse primary visual cortex, two distinct patterns of spontaneous activity occur before vision onset: local low-synchronicity events originating in the retina and global high-synchronicity events originating in the cortex. We sought to determine the contribution of these activity patterns to jointly organize network connectivity through different activity-dependent plasticity rules. We postulated that local events shape cortical input selectivity and topography, while global events homeostatically regulate connection strength. However, to generate robust selectivity, we found that global events should adapt their amplitude to the history of preceding cortical activation. We confirmed this prediction by analyzing in vivo spontaneous cortical activity. The predicted adaptation leads to the sparsification of spontaneous activity on a slower timescale during development, demonstrating the remarkable capacity of the developing sensory cortex to acquire sensitivity to visual inputs after eye-opening.

Conformational dynamics in interleukin 17A and 17F functional complexes is a key determinant of receptor A affinity and specificity

The proinflammatory cytokines IL-17A and IL-17F have been identified as key drivers of a range of human inflammatory diseases, such as psoriasis, which has led to several therapeutic antibodies targeted at IL-17A. The two cytokines have been shown to tightly associate as functional homo and hetero dimers, which induce signalling via the formation of a cell surface signalling complex with a single copy of both IL-17RA and IL-17RC. Striking differences in affinity have been observed for IL-17RA binding to IL-17AA, IL-17AF and IL-17FF, however, the functional significance and molecular basis for this has remained unclear. We have obtained comprehensive backbone NMR assignments for full length IL-17AA (79%), IL-17AF (93%) and IL-17FF (89%), which show that the dimers adopt almost identical backbone topologies in solution to those observed in reported crystal structures. Analysis of the line widths and intensities of assigned backbone amide NMR signals has revealed striking differences in the conformational plasticity and dynamics of IL-17AA compared to both IL-17AF and IL-17FF. Our NMR data indicate that a number of regions of IL-17AA are interconverting between at least two distinct conformations on a relatively slow timescale. Such conformational heterogeneity has previously been shown to play an important role in the formation of many high affinity protein-protein complexes. The locations of the affected IL-17AA residues essentially coincides with the regions of both IL-17A and IL-17F previously shown to undergo significant structural changes on binding to IL-17RA. Substantially less conformational exchange was revealed by the NMR data for IL-17FF and IL-17AF. We propose that the markedly different conformational dynamic properties of the distinct functional IL-17 dimers plays a key role in determining their affinities for IL-17RA, with the more dynamic and plastic nature of IL-17AA contributing to the significantly tighter affinity observed for binding to IL-17RA. In contrast, the dynamic properties are expected to have little influence on the affinity of IL-17 dimers for IL-17RC, which has recently been shown to induce only small structural changes in IL-17FF upon binding.

Role of integrated noise in pathway-specific signal propagation in feed-forward loops

Cells impose optimal noise control mechanism in diverse situations to cope with distinct environmental cues. Sometimes, it is desirable for the cell to utilize fluctuations for noise-driven processes. In other cases, noise can be harmful to the cell to show optimal fitness. It is, therefore, important to unravel the noise propagation mechanism inside the cell. Such noise controlling mechanism is accomplished by using gene transcription regulatory networks. One such gene regulatory network is feed-forward loop, having three regulatory nodes S, X and Y. Here, we consider the most abundant type 1 of coherent and incoherent feed-forward loops with both OR and AND logic functions, forming four different architectures. In OR logic function, the functions representing S and X act additively for the regulation of Y, while in AND logic function, the same functions (S and X) act multiplicatively for the regulation of Y. Measurement of susceptibility of the signal at output Y is done using elasticity of each regulation in FFLs. Using susceptibility, we demonstrate the nature of pathway integration by which one-step and two-step pathways get overlapped. The integration type is competitive for motifs having OR gate, while it is noncompetitive for the same with AND gate. The pathway integration property explains the output noise behavior of the motifs properly but cannot infer about the mechanism by which the upstream noise propagates to output. To account this, the total output noise is decomposed, which results in integrated noise as an additional noise source along with pathway-specific noise components. The integrated noise is found to appear as a consequence of integration between the pathways and has different functional characteristics explaining noise amplification and noise attenuation property of coherent and incoherent feed-forward loops, respectively. The noise decomposition also quantifies the contribution of different noise sources toward total noise. Finally, the noise propagation is being tuned as a function of input signal noise and its time scale of fluctuations, which shows considerable intrinsic noise strength and relatively slow relaxation time scale causes a higher degree of noise propagation in FFLs.

Emergent robustness of bacterial quorum sensing in fluid flow

Bacteria use intercellular signaling, or quorum sensing (QS), to share information and respond collectively to aspects of their surroundings. The autoinducers that carry this information are exposed to the external environment; consequently, they are affected by factors such as removal through fluid flow, a ubiquitous feature of bacterial habitats ranging from the gut and lungs to lakes and oceans. To understand how QS genetic architectures in cells promote appropriate population-level phenotypes throughout the bacterial life cycle requires knowledge of how these architectures determine the QS response in realistic spatiotemporally varying flow conditions. Here we develop and apply a general theory that identifies and quantifies the conditions required for QS activation in fluid flow by systematically linking cell- and population-level genetic and physical processes. We predict that when a subset of the population meets these conditions, cell-level positive feedback promotes a robust collective response by overcoming flow-induced autoinducer concentration gradients. By accounting for a dynamic flow in our theory, we predict that positive feedback in cells acts as a low-pass filter at the population level in oscillatory flow, allowing a population to respond only to changes in flow that occur over slow enough timescales. Our theory is readily extendable and provides a framework for assessing the functional roles of diverse QS network architectures in realistic flow conditions.

Ventromedial Prefrontal Cortex Activity and Sympathetic Allostasis During Value-Based Ambivalence.

Anxiety is characterized by low confidence in daily decisions, coupled with high levels of phenomenological stress. Ventromedial prefrontal cortex (vmPFC) plays an integral role in maladaptive anxious behaviors via decreased sensitivity to threatening vs. non-threatening stimuli (fear generalization). vmPFC is also a key node in approach-avoidance decision making requiring two-dimensional integration of rewards and costs. More recently, vmPFC has been implicated as a key cortical input to the sympathetic branch of the autonomic nervous system. However, little is known about the role of this brain region in mediating rapid stress responses elicited by changes in confidence during decision making. We used an approach-avoidance task to examine the relationship between sympathetically mediated cardiac stress responses, vmPFC activity and choice behavior over long and short time-scales. To do this, we collected concurrent fMRI, EKG and impedance cardiography recordings of sympathetic drive while participants made approach-avoidance decisions about monetary rewards paired with painful electric shock stimuli. We observe first that increased sympathetic drive (shorter pre-ejection period) in states lasting minutes are associated with choices involving reduced decision ambivalence. Thus, on this slow time scale, sympathetic drive serves as a proxy for “mobilization” whereby participants are more likely to show consistent value-action mapping. In parallel, imaging analyses reveal that on shorter time scales (estimated with a trial-to-trial GLM), increased vmPFC activity, particularly during low-ambivalence decisions, is associated with decreased sympathetic state. Our findings support a role of sympathetic drive in resolving decision ambivalence across long time horizons and suggest a potential role of vmPFC in modulating this response on a moment-to-moment basis.

Summertime Transport Pathways From Different Northern Hemisphere Regions Into the Arctic

AbstractTrace gases and aerosols play an important role in Arctic chemistry and climate. As most Arctic tracers and aerosols are transported from midlatitude source regions, long‐range transport into the Arctic is one of the key factors to understand the current and future states of Arctic climate. While previous studies have investigated the airmass fraction and transit time distribution in the Arctic, the actual transport pathways and their underlying dynamics and efficiencies are yet to be understood. In this study, we implement a large ensemble of idealized tagged pulse passive tracers in the Whole Atmosphere Community Climate Model version 5 to identify and analyze summertime transport pathways from different Northern Hemisphere surface regions into the Arctic. Three different transport pathways are identified as those associated with fast, intermediate and slow time scales. Midlatitude tracers can be transported into the Arctic in the troposphere via the fast transport pathway (∼8 days), which moves tracers northward from the source region mainly through transient eddies. For the intermediate transport pathway, which happens on 1–3 weeks’ time scales, midlatitude tracers are first zonally transported by the jet stream, and then advected northward into the Arctic over Alaska and northern North Atlantic. Tropical and subtropical tracers are transported into the Arctic lower stratosphere via the slow transport pathway (1–3 months), as the tracers are lifted upward into the tropical and subtropical lower stratosphere, and then transported into the Arctic following the isentropic surfaces.

Inverted central auditory hierarchies for encoding local intervals and global temporal patterns

In sensory systems, representational features of increasing complexity emerge at successive stages of processing. In the mammalian auditory pathway, the clearest change from brainstem to cortex is defined by what is lost, not by what is gained, in that high-fidelity temporal coding becomes increasingly restricted to slower acoustic modulation rates.1,2 Here, we explore the idea that sluggish temporal processing is more than just an inability for fast processing, but instead reflects an emergent specialization for encoding sound features that unfold on very slow timescales.3,4 We performed simultaneous single unit ensemble recordings from three hierarchical stages of auditory processing in awake mice - the inferior colliculus (IC), medial geniculate body of the thalamus (MGB) and primary auditory cortex (A1). As expected, temporal coding of brief local intervals (0.001 - 0.1 s) separating consecutive noise bursts was robust in the IC and declined across MGB and A1. By contrast, slowly developing (∼1s period) global rhythmic patterns of inter-burst interval sequences strongly modulated A1 spiking, were weakly captured by MGB neurons, and not at all by IC neurons. Shifts in stimulus regularity were not represented by changes in A1 spike rates, but rather in how the spikes were arranged in time. These findings show that low-level auditory neurons with fast timescales encode isolated sound features but not the longer gestalt, while the extended timescales in higher-level areas can facilitate sensitivity to slower contextual changes in the sensory environment.

Multiscale and monolithic arbitrary Lagrangian–Eulerian finite element method for a hemodynamic fluid-structure interaction problem involving aneurysms

In this paper, a multiscale and monolithic arbitrary Lagrangian–Eulerian finite element method (ALE-FEM) is developed for a multiscale hemodynamic fluid-structure interaction (FSI) problem involving an aortic aneurysm growth to quantitatively predict the long-term aneurysm risk in the cardiovascular environment, where the blood fluid profile, the hyperelastic arterial wall, and the aneurysm pathophysiology are integrated into one hemodynamic FSI model, together with no-slip interface conditions between the blood fluid and the arterial wall. Additionally, two different time scales are involved: a fast time scale for the blood fluid-arterial wall interaction process in terms of seconds, and a slow time scale for the biological (abdominal aortic aneurysms (AAA) progression) process in terms of years. Two types of multiscale methods, the heterogeneous multiscale method (HMM) and the seamless multiscale method (SMM), are employed to tackle different time scales while the arbitrary Lagrangian–Eulerian (ALE) method is adopted to generate the moving blood fluid meshes that adapt to the deformation of the hyperelastic arterial wall all the time, based on which the variable time-stepping/mixed finite element method (FEM) is defined in the ALE frame to discretize the developed hemodynamic FSI model involving aneurysms. A two-dimensional schematic blood fluid-artery-aneurysm interaction example and a three-dimensional realistic cardiovascular FSI problem with an aortic aneurysm growth based upon the patients' CT scan data are simulated to validate the accuracy and the efficiency of our developed HMM(SMM)/ALE-FEM, and a medically reasonable long-term prediction is obtained for the aneurysm growth as well.

Singlet Exciton Fission and Associated Enthalpy Changes with a Covalently Linked Bichromophore Comprising TIPS-Pentacenes Held in an Open Conformation.

A covalently linked bichromophore, embracing 6,13-bis(triisopropylsilylethinyl)pentacene (TIPS-pentacene) terminals bridged by a rigid fluorene spacer, generates a relatively high yield (i.e., 65 ± 6%) of the spin-correlated, triplet biexciton upon illumination in toluene. Under the same conditions, the extent of fluorescence quenching relative to the parent TIPS-pentacene approaches 97% and is insensitive to temperature. The biexciton, having overall singlet spin multiplicity, undergoes internal conversion in competition to spin decorrelation. These latter processes occur on the relatively slow time scale of a hundred or so nanoseconds, possibly reflecting the restricted level of electronic communication between the terminals. Spin decorrelation leads to evolution of an independent triplet pair with an overall quantum yield of 0.50 ± 0.06 and a lifetime of 8 ± 2 μs in deaerated toluene. Photoacoustic calorimetry (PAC) indicates three separate enthalpy changes: a very fast step associated with intramolecular singlet exciton fission to form the correlated triplet biexciton, a fast step essentially reflecting spin decorrelation, and a slow step associated with relaxation of the independent triplet pair. Analysis of the PAC data, in conjunction with the transient absorption results, establishes excitation energies for both spin-correlated and independent triplet pairs. Polar solvent enhances both fluorescence quenching and triplet formation at the expense of radiationless decay while temperature effects have been recorded for all important intermediate species.

Multi-Timescale QoE Provisioning for Adaptive Video Streaming in Heterogeneous Deployments

This paper considers an optimization problem that maximizes an aggregate utility, formulated as the weighted geometric mean of the “in-context” suitability of a set of radio access technologies (RATs), to support adaptive video streaming subject to the existence of legacy data transfers. Motivated by the unfeasibility of solving the formulated problem centrally when the various RATs are loosely integrated (i.e., at core network (CN) level), a hybrid (i.e., network-assisted user-driven) strategy is devised to approximate its optimum solution. Unlike previous hybrid approaches, the proposed methodology exploits network assistance to ensure a friendly co-existence between adaptive video streaming clients and legacy users. It operates on different timescales, where the fastest timescale operation is performed on the video clients according to a policy that is tuned by the network on slower timescales. The user operation on the fastest timescale (i.e., tens of ms) enables to adapt video streaming depending on the perceived quality-of-experience (QoE) and local components of the context (e.g., remaining credit and battery level). A small-cell tuning on a slower timescale (i.e., hundreds of ms) enables to preempt the resources used by legacy users based on the operating conditions (e.g., load and type of scheduler). Finally, a tuning performed by the network on the slowest timescale (i.e., few seconds) offloads legacy data transfers to unlicensed bands whenever the amount of interference on licensed bands reaches critical levels, which helps to sustain good QoE for all video clients. A cost-benefit analysis reveals that the proposed methodology performs closely to its centralized counterpart with much less control overhead on the radio interface.

Strong convergence order for slow–fast McKean–Vlasov stochastic differential equations

In this paper, we consider the averaging principle for a class of McKean–Vlasov stochastic differential equations with slow and fast time-scales. Under some proper assumptions on the coefficients, we first prove that the slow component strongly converges to the solution of the corresponding averaged equation with convergence order 1/3 using the approach of time discretization. Furthermore, under stronger regularity conditions on the coefficients, we use the technique of Poisson equation to improve the order to 1/2, which is the optimal order of strong convergence in general.

Probing the Contributions to DNA Hybridization Dynamics with Time-Resolved Infrared Spectroscopy

DNA can undergo a diverse set of folding and hybridization transitions of which the energetics and dynamics are highly sensitive to the local solution environment as well as nucleobase chemical modifications. Such sensitivity is used to perform various biological functions and can fuel many nanotechnology applications. However, the physical properties of folding and hybridization reactions that underly these applications often remain poorly understood. DNA folding and hybridization is complicated by many fast structural motions, such as fraying and sliding, and therefore investigation of DNA folding and hybridization requires the ability to probe DNA structure across both fast (ns-µs) and slow (ms-s) timescales. infrared (IR) spectroscopy offers the capability to probe dynamics from ultrafast timescales to seconds with nucleobase-specific information. Along these lines our group has developed temperature-jump (T-jump) IR and two-dimensional IR (2D IR) methods that can monitor DNA interactions from nanoseconds to many seconds. We are investigating DNA unfolding and duplex dehybridization and how they are modulated by nucleobase sequence, chemical modifications, and nucleobase protonation using T-jump IR spectroscopy. Recently, we have found that the modified nucleobases 5-formyl- and 5-carboxylcytosine can alter DNA base pairing and hybridization with great sensitivity to solution pH. Our results provide insight into a complex interplay between sequence, chemical modification, and sequence that may tune DNA hybridization dynamics.

Molecular Mechanism of Force Generation by the Actin-Myosin Complex During Cardiac Muscle Contraction

Cardiac muscle contraction is performed by arrays of contractile proteins in the sarcomere. Serious heart diseases, such as cardiomyopathy, can often be results of mutations in myosin and actin, which slide along each other to generate force using the energy from ATP hydrolysis. All-atom molecular dynamics (MD) simulations have been growing its power in predicting protein structure-function relationships. However, such approaches are limited in the study of the myosin crossbridge cycle owing to the slow timescale as well as the lack of high-resolution structures of various intermediate states for the human cardiac myosin-actin complex. Here, combining comparative modeling and enhanced sampling MD simulations, we characterize how the myosin-actin interactions in human are influenced by the myosin functional states. By incorporating structural information from multiple templates, our comparative modeling provides conformational ensembles for different myosin-actin states, which enable us to efficiently sample the energy landscape using Gaussian accelerated MD simulations. Our results reveal novel interactions between key myosin loops and actin, which are consistent with recent cryo-EM density data. Furthermore, we find that the myosin cleft motion is impacted by the ATP binding site dynamics and that ADP release is coupled to the lever arm swing. Our approach demonstrates the potential to link genotype and molecular structures to the physical properties of the sarcomere.

Influence of ethylenediaminetetraacetic acid on the long-term oxidation state distribution of plutonium

Spectrophotometry was used to study the effect of EDTA on plutonium oxidation state distribution as a function of time, pH, and ligand-to-metal ratio (L/M) under anoxic conditions. Novel Pu(V)-EDTA absorption bands were identified at 571, 993, 1105, and 1150 nm with molar absorption coefficients of 15 ± 1, 6 ± 1, 10 ± 1, and 10 ± 1 cm−1M−1, respectively. Pu(V)-EDTA spectral changes occurred at L/M < 1, indicating only PuVO2(EDTA)3- formed with logK = 3.6 ± 0.3. Time-resolved experiments showed EDTA drastically increased the Pu(V/VI) reduction rate, which we propose is driven by amine lone-pair electron donation and the oxidative decarboxylation of EDTA. Oxidation of Pu(III)-EDTA to Pu(IV)-EDTA occurred on a slower time scale (110–237 days) than previously reported (<15 min) and is hypothesized to be radiolysis driven. Pu(V/VI)-EDTA and Pu(III)-EDTA both approached Pu(IV)-EDTA stabilization over time, yet Pu(V/VI)-EDTA solubility data was ≥ 1.0 log10 units higher than predicted by Pu(IV)-EDTA solubility models, indicating that current thermodynamic models are incomplete. Ultimately, the data show EDTA preferentially stabilizes Pu(IV) over time regardless of initial oxidation state, but Pu(V)-EDTA can persist under environmentally-relevant conditions, emphasizing the need to continue investigating redox reactions, speciation, and behavior of these complexes to support the transuranic waste disposal and surface remediation/containment efforts.

Kinetic equations in a third-generation spectral wave model

Abstract