High Temporal Accuracy Research Articles

Modulation of Neuronal Potassium Channels During Auditory Processing.

The extraction and localization of an auditory stimulus of interest from among multiple other sounds, as in the ‘cocktail-party’ situation, requires neurons in auditory brainstem nuclei to encode the timing, frequency, and intensity of sounds with high fidelity, and to compare inputs coming from the two cochleae. Accurate localization of sounds requires certain neurons to fire at high rates with high temporal accuracy, a process that depends heavily on their intrinsic electrical properties. Studies have shown that the membrane properties of auditory brainstem neurons, particularly their potassium currents, are not fixed but are modulated in response to changes in the auditory environment. Here, we review work focusing on how such modulation of potassium channels is critical to shaping the firing pattern and accuracy of these neurons. We describe how insights into the role of specific channels have come from human gene mutations that impair localization of sounds in space. We also review how short-term and long-term modulation of these channels maximizes the extraction of auditory information, and how errors in the regulation of these channels contribute to deficits in decoding complex auditory information.

Using High Sample Rate Lidar to Measure Debris-Flow Velocity and Surface Geometry

ABSTRACT Debris flows evolve in both time and space in complex ways, commonly starting as coherent failures but then quickly developing structures such as roll waves and surges. These processes are readily observed but difficult to study or quantify because of the speed at which they evolve. Many methods for studying debris flows consist of point measurements (e.g., flow height or basal stresses), which are inherently limited in spatial coverage and cannot fully characterize the spatiotemporal evolution of a flow. In this study, we use terrestrial lidar to measure debris-flow profiles at high sampling rates to examine debris-flow movement with high temporal and spatial precision and accuracy. We acquired measurements during gate-release experiments at the U.S. Geological Survey debris-flow flume, a unique experimental facility where debris flows can be artificially generated at a large scale. A lidar scanner was used to record repeat topographic profiles of the moving debris flows along the length of the flume with a narrow swath width (∼1 mm) at a rate of 60 Hz. The high-resolution lidar profiles enabled us to quantify flow front velocity of the debris flows and provided an unprecedented record of the development and evolution of the flow structure with a sub-second time resolution. The findings of this study demonstrate how to obtain quantitative measurements of debris-flow movement. In addition, the data help us to quantitatively define the development of a saltating debris-flow front and roll waves behind the debris-flow front. Such measurements may help constrain future modeling efforts.

High order semi-Lagrangian discontinuous Galerkin method coupled with Runge-Kutta exponential integrators for nonlinear Vlasov dynamics

In this paper, we propose a semi-Lagrangian discontinuous Galerkin method coupled with Runge-Kutta exponential integrators (SLDG-RKEI) for nonlinear Vlasov dynamics. The commutator-free Runge-Kutta (RK) exponential integrators (EI) were proposed by Celledoni, et al. (FGCS, 2003). In the nonlinear transport setting, the RKEI can be used to decompose the evolution of the nonlinear transport into a composition of a sequence of linearized dynamics. The resulting linearized transport equations can be solved by the semi-Lagrangian (SL) discontinuous Galerkin (DG) method proposed in Cai, et al. (JSC, 2017). The proposed method can achieve high order spatial accuracy via the SLDG framework, and high order temporal accuracy via the RK EI. Due to the SL nature, the proposed SLDG-RKEI method is not subject to the CFL condition, thus they have the potential in using larger time-stepping sizes than those in the Eulerian approach. Inheriting advantages from the SLDG method, the proposed SLDG-RKEI schemes are mass conservative, positivity-preserving, have no dimensional splitting error, perform well in resolving complex solution structures, and can be evolved with adaptive time stepping sizes. We show the performance of the SLDG-RKEI algorithm by classical test problems for the nonlinear Vlasov-Poisson system, as well as the Guiding center Vlasov model. Though that it is not our focus of this paper to explore the SLDG-RKEI scheme for nonlinear hyperbolic conservation laws that develop shocks, we show some preliminary results on schemes' performance on the Burgers' equation.

A comprehensive characterization of MODIS daily burned area mapping accuracy across fire sizes in tropical savannas

Daily global burned area mapping of Earth from remotely sensed data is of considerable interest and indicates a clear user need, despite well-known accuracy limitations. Many studies report global and regional indicators of spatial and temporal accuracy to evaluate the quality of burned area products, but tend to rely on relatively sparse validation data. In this paper, an extensive validation data set covering 223 million ha over the Brazilian Cerrado for the 2015 fire season is used to thoroughly evaluate how the accuracy of burned area products relying on distinct spectral channels (SWIR+NIR versus NIR) and spatial resolution (250 m, 500 m, and both) depends on fire size.Toward this end, we consider publicly available burned area products MCD64A1 (v006) at 500 m and FireCCI51 at 250 m and use a recently proposed graph-based patch algorithm, which is flexible enough to combine 250–500 m bands.The trade-off between spatial resolution and spectral channels for the problem at hand reveals that better spatial resolution (NIR at 250 m) is preferable to a broader range of spectral channels (NIR + SWIR at 500 m) for small burns (<250 ha), but that this relation is not preserved for large burns (>1000 ha). Also, this study shows that combining both spectral indices into a single classifier leads to the most accurate burned area map. The analysis by land cover type indicates that overall accuracy is highest for grasslands and savannas, with grasslands benefiting the most from the use of SWIR bands. Results also indicate that burned areas can be classified with accuracy measured by the Dice Coefficient close to 80% for fire sizes larger than 500 ha, which corresponds to 60% of the total burned area, but accuracy lower than 36% for fire sizes smaller than 250 ha. In particular, our analysis suggests that the validation of burned area products always should be linked to the description of fire size distribution since it is a fundamental driver of accuracy.Results show that MODIS daily burned area mapping at 250–500 m spatial resolution can exhibit high temporal accuracy, with almost unbiased estimates and standard deviation close to 1.5 days, indicating an accurate characterization of the spread of large fires.

Optimizing orthogonal-octahedron finite-difference scheme for 3D acoustic wave modeling by combination of Taylor-series expansion and Remez exchange method

Using orthogonal-octahedron finite-difference (FD) stencils, even-order accuracy for temporal and spatial derivatives can be reached for 3D acoustic wave equation modelling. However, the required length of FD operator is still long for high accuracy modelling. To tackle this issue, we have developed an optimization method using a combination of Taylor-series expansion plus Remez exchange methods. The Taylor-series expansion for the octahedron-shaped operator ensures high temporal accuracy and the Remez exchange for axial operator further improves the spatial accuracy. The comparison between our method, exisiting 3D temporal high order method and space domain least-square opimization method validates the efficiency and accuracy superiority of the new method.

Crank-Nicholson Scheme of the Zeroth-Order Approximate Deconvolution Model of Turbulence Based On a Mixed Formulation

This report presents a method with high spatial and temporal accuracy for estimating solutions of Navier-Stokes equations at high Reynolds number. It employs Crank-Nicolson time discretization along with the zeroth-order ap-proximate deconvolution model of turbulence to regularize the flow prob-lem; solves a deviation of the Navier Stokes equation instead. Both theoreti-cal and computational findings of this report illustrate that the model pro-duces a high order of accuracy and stability. Furthermore, measurements of the drag and lift coefficients of a benchmark problem verify the potential of the model in this kind of computations.

An argo‐based experiment providing near‐real‐time subsurface oceanic environmental information for fishery data

AbstractA better understanding of the relationships between oceanic environments and fishing conditions could make the utilization of fish more efficient, profitable, and sustainable. The current lack of high‐precision subsurface seawater information has long been a constraint on fishery research. Using near‐real‐time Argo observations, this paper presents a new approach called gradient‐dependent optimal interpolation. This approach provides daily subsurface oceanic environmental information according to fishery dates and locations. An experiment was conducted in the western and central Pacific Ocean using yellowfin tuna (YFT) catch data in August 2017. The results of seawater temperature and salinity represented differences of less than ±0.5°C and ±0.05, respectively, according to verification of error analysis and truth‐finding comparisons. After applying the constructed temperature and salinity profiles, we described the relationship between subsurface information and yellowfin tuna catch distribution. Statistical analysis revealed that yellowfin tuna were more adapted to warmer and saltier seawater. At the near‐surface (&lt;5 m), the most suitable temperature was 28–29°C, although yellowfin tuna can endure a temperature range from 11 to 12°C at a depth of 300 m. The corresponding upper boundary of the thermocline was approximately 75 m, with a mean strength of 0.074°C/m, and the most suitable salinity for yellowfin tuna was 34.5–36.0 at depths shallower than 300 m. These results indicated that the constructed subsurface information was very close to the true values and they had high spatial and temporal accuracy.

Viscoelastic Wave Simulation with High Temporal Accuracy Using Frequency-Dependent Complex Velocity

In recent decades, the study of seismic attenuation has received more and more concerns because it can stimulate the development of wave propagation simulation and improve the accuracy of structure imaging and reservoir prediction. In this paper, we review the attenuation theory and the development of high temporal accuracy wave simulation. The conventional mathematical models to describe the characteristics of viscoelastic are based on constant-Q model or standard linear solids theory. However, these approaches possess some noticeable shortcomings. Therefore, we introduce a frequency-dependent complex velocity to derive the novel viscoelastic wave equations with decoupled amplitude dissipation and phase dispersion. To obtain high temporal accuracy viscoelastic wave simulation, we adopt the normalized pseudo-Laplacian to compensate for the temporal dispersion errors caused by the second-order finite-difference discretization in the time domain. During the implementation, we incorporate the normalized pseudo-Laplacian into the optimized staggered-grid finite-difference coefficients. Therefore, it can greatly reduce the times of low-rank decomposition and Fourier transform and largely improve the computational efficiency. Based on this strategy, we can implement the high temporal accuracy viscoelastic wavefield extrapolation by comprehensively exploiting the staggered-grid finite-difference scheme, pseudo-spectral method and low-rank decomposition algorithm. Meanwhile, a linear velocity model is employed to evaluate the accuracy of low-rank approximation. Furthermore, we use several numerical examples to carry out the comparison between our scheme and other conventional methods. The numerical results reveal that our proposed scheme can effectively compensate for temporal dispersion errors and help generate high temporal accuracy viscoelastic wave solutions.

Low-Noise Magnetic Coil System for Recording 3-Dimensional Eye Movements.

Vestibular and oculomotor research often requires measurement of 3-dimensional (3D) eye orientation and movement with high spatial and temporal precision and accuracy. We describe the design, implementation, validation and use of a new magnetic coil system optimized for recording 3D eye movements using small scleral coils in animals. Like older systems, the system design uses off-the-shelf components to drive three mutually orthogonal alternating magnetic fields at different frequencies. The scleral coil voltage induced by those fields is decomposed into 3 signals, each related to the coil's orientation relative to the axis of one field component. Unlike older systems based on analog demodulation and filtering, this system uses a field-programmable gate array (FPGA) to oversample each induced scleral coil voltage (at 25 Msamples/s), demodulate in the digital domain, and average over 25 ksamples per data point to generate 1 ksamples/s output in real time. Noise floor is <0.036° peak-to-peak and linearity error is < 0.1° during 345° rotations in all three dimensions. This FPGA-based design, which is both reprogrammable and freely available upon request, delivers sufficient performance to record eye movements at high spatial and temporal precision and accuracy using coils small enough for use with small animals.

Optical tweezers-based velocimetry: a method to measure microscale unsteady flows

In the study of micro-scale biological flows, velocimetry methods based on passive tracers, such as micro-PIV and micro-PTV, are well established to characterize steady flows. However, these methods become inappropriate for measuring unsteady flows of small amplitude, because, on these scales, the motion of passive tracers cannot be distinguished from Brownian motion. In this study, we use optical tweezers (OTs) in combination with Kalman filtering, to measure unsteady microscopic flows with high temporal accuracy. This method is referred to as optical tweezers-based velocimetry (OTV). The OTV method measures the nanometric displacements of a trapped bead, and predicts the instantaneous velocity of the flow by employing a Kalman filter. We discuss the accuracy of OTV in measuring unsteady flows with 1.5–70 upmum s^{-1} amplitudes and 10–90 Hz frequencies. We quantify how the bead size and the laser power affect the velocimetry accuracy, and specify the optimal choices for the bead size and laser power to measure different unsteady flows. OTV accurately measures unsteady flows with amplitudes as small as 3–6 upmum s^{-1}. We compare the accuracy of OTV and micro-PTV, and characterize the flow regime for which OTV outperforms micro-PTV. We also demonstrate the robustness of OTV by measuring the unsteady flow created by the cilia of green alga Chlamydomonas reinhardtii, and comparing with numerical predictions based on Stokes equations. An open-source implementation of the OTV software in Matlab is available through the 4TU.Centre for Research Data.Graphic abstract

REMOTE ATTITUDE SENSING BASED ON HIGH-SPEED MUELLER MATRIX ELLIPSOMETRY

Abstract. The attitude metrology of moving objects has always been a hot topic in engineering applications. In this article, a novel optical method based on the high-speed Mueller matrix ellipsometry (MME) is proposed for real-time remote attitude sensing. With the help of an electric level, all the attitude angles of a free-moving object with a birefringent waveplate attached can be simultaneously extracted in real time. Compared with existing ellipsometry-based attitude metrology that can only be used in the transmission mode, the proposed method with the advantages of the high-speed MME can expand the application to both the transmission and reflection modes while maintaining higher accuracy and robustness in an ultra-large measurement range. The basic principle is presented via theoretical derivation, and the change in the Mueller matrix of the birefringent waveplate versus the attitude angles is explored in the simulated experiments. In a series of the dynamic experiments, with the extremely high temporal resolution and accuracy of the high-speed MME, an angular resolution up to 0.00022° and an angular accuracy better than 0.01° are achieved in the real-time attitude tracking of the free-moving object. As an additional benefit, the real-time angular velocity and acceleration of all the attitude angles can be obtained simultaneously. These experimental results demonstrate that the proposed attitude metrology is ready to be applied to the real-time remote attitude sensing with high angular resolution and accuracy.

Stimuli-Responsive Biomaterials for Vaccines and Immunotherapeutic Applications.

The immune system is the key target for vaccines and immunotherapeutic approaches aimed at blunting infectious diseases, cancer, autoimmunity, and implant rejection. However, systemwide immunomodulation is undesirable due to the severe side effects that typically accompany such strategies. In order to circumvent these undesired, harmful effects, scientists have turned to tailorable biomaterials that can achieve localized, potent release of immune‐modulating agents. Specifically, “stimuli‐responsive” biomaterials hold a strong promise for delivery of immunotherapeutic agents to the disease site or disease‐relevant tissues with high spatial and temporal accuracy. This review provides an overview of stimuli‐responsive biomaterials used for targeted immunomodulation. Stimuli‐responsive or “environmentally responsive” materials are customized to specifically react to changes in pH, temperature, enzymes, redox environment, photo‐stimulation, molecule‐binding, magnetic fields, ultrasound‐stimulation, and electric fields. Moreover, the latest generation of this class of materials incorporates elements that allow for response to multiple stimuli. These developments, and other stimuli‐responsive materials that are on the horizon, are discussed in the context of controlling immune responses.

Light Modulation of Brain and Development of Relevant Equipment.

Light modulation plays an important role in understanding the pathology of brain disorders and improving brain function. Optogenetic techniques can activate or silence targeted neurons with high temporal and spatial accuracy and provide precise control, and have recently become a method for quick manipulation of genetically identified types of neurons. Photobiomodulation (PBM) is light therapy that utilizes non-ionizing light sources, including lasers, light emitting diodes, or broadband light. It provides a safe means of modulating brain activity without any irreversible damage and has established optimal treatment parameters in clinical practice. This manuscript reviews 1) how optogenetic approaches have been used to dissect neural circuits in animal models of Alzheimer's disease, Parkinson's disease, and depression, and 2) how low level transcranial lasers and LED stimulation in humans improves brain activity patterns in these diseases. State-of-the-art brain machine interfaces that can record neural activity and stimulate neurons with light have good prospects in the future.

Plant phenological responses to the warm island effect in the lake group region of the Badain Jaran Desert, northwestern China

Plant phenology is a commonly used indicator representing the impacts on vegetation by the climate and other environmental factors. The use of repeated digital photography provides an opportunity to conduct long-term monitoring of plant phenology and to extract phenological transition dates. Here, we tracked the phenological changes in the flowering tree, Elaeagnus angustifolia L., in the Cherigele (CRGL) of the Badain Jaran Desert (BJD) and the nearby Lianggejing (LGJ); using one-year near-surface digital repeat photography and meteorological data, the phenological difference between the two sites was revealed. We found that the use of digital cameras allowed for the monitoring of plant phenology with high temporal and spatial accuracy in these dryland ecosystems. Furthermore, in the lake group region of BJD, the onset of greening occurred 23 days earlier, the onset of dormancy began 13 days later and the growing season was 36 days longer, compared to those of the surrounding area. This difference is partly related to the higher altitude in the LGJ; however, it is dominantly related to the warm island effect in the lake group region. This effect resulted in the mean annual temperature in the CRGL being ~1.6 °C higher than in the LGJ.

Evaluating Binding Affinities of Dimerization of Bar Proteins in Solution and on Membrane Surface

Membrane remodeling is a crucial process for various cellular pathways like signaling, viral assembly and clathrin-mediated endocytosis. This process is governed by a network of protein-protein interactions that perform specific tasks with high spatial and temporal accuracy. An important type of these proteins is the BAR domain family, proteins of which, self-assemble on the membrane surface and induce curvature. The localization of proteins to the 2D membrane surface from 3D solution reduces their search space, and our lab has shown how proteins can exploit this dimensionality reduction to trigger self-assembly. Further, the dimerization of BAR proteins, which is crucial in mediating protein-protein and protein-lipid interactions, is poorly understood from a quantitative perspective. We address this gap by applying Molecular Dynamics simulations to investigate the thermodynamics of binding in solution and on membrane surface. We employ metadynamics to evaluate the free energy of protein dimerization and obtain the binding affinity (KD). In addition, we aim to deconvolute the energetic and entropic contributions to the binding process and characterize the intermediate pathways of dimerization. Our results would quantify the role of dimensionality reduction on the binding affinity and also contribute to the theoretical framework of our reaction-diffusion software, NERDSS, that enables self-assembly simulations of a broad range of biological systems.

Optogenetic Control of Microtubule Dynamics.

Light can be controlled with high spatial and temporal accuracy. Therefore, optogenetics is an attractive experimental approach to modulate intracellular cytoskeleton dynamics at much faster timescales than by genetic modification. For example, in mammalian cells, microtubules (MTs) grow tens of micrometers per minute and many intracellular MT functions are mediated by a complex of +TIP proteins that dynamically associate with growing MT plus ends. EB1 is a central component of this +TIP protein network, and we recently developed a photo-inactivated π-EB1 by inserting a blue light-sensitive LOV2/Zdk1 module between the EB1 MT-binding domain and the +TIP adaptor domain. Blue light-induced π-EB1 photodissociation results in disassembly of the +TIP complex and strongly attenuates MT growth in mammalian cells.In this chapter, we discuss theoretical and practical aspects of how to perform high-resolution live-cell microscopy in combination with π-EB1 photodissociation. However, these techniques are broadly applicable to other LOV2-based and likely other blue light-sensitive optogenetics. In addition to being a tool to investigate +TIP functions acutely and with subcellular resolution, because of its dramatic and rapid change in intracellular localization, π-EB1 can serve as a powerful tool to test and characterize optogenetic illumination setups. We describe protocols on how to achieve micrometer-scale intracellular control of π-EB1 activity using patterned illumination, and we introduce a do-it-yourself LED cube design compatible with transmitted light microscopy in multiwell plates.

Time adaptive conservative finite volume method

Finite volume methods for time dependent problems typically employ time integration schemes with constant time step sizes. The latter, in order to ensure stability and time accurate solutions, have to be chosen small enough, such that the Courant-Friedrichs-Lewy (CFL) number stays below a critical value everywhere. In many cases, however, this time step size limitation leads to huge numbers of very small time steps, which renders simulations very expensive. Motivated by this drawback of conventional time stepping schemes, various sub-time stepping algorithms have been proposed. However, most of them are inherently asynchronous, require small local CFL numbers or are not strictly conservative. In this paper a new adaptive time integration scheme for finite volume methods, which is conservative, of high spatial and temporal order, robust and easy to implement is presented. It relies on local sub-time steps which are fractions of a global time step by powers of two, i.e., the grid cells proceed asynchronously in the order of their termination time, but since they all synchronize at the end of each global time step, it is possible to guarantee continuity of the mean fluxes and thus strict conservation at the global time step resolution. Numerical experiments with 1D and 2D test cases demonstrate that the adaptive conservative time integration (ACTI) scheme can achieve extreme speed-up factors over conventional time integration, while still maintaining high spatial and temporal accuracy.

Modeling 3D elastic VTI wave propagation using an optimal k-space operator-based temporal high-accuracy staggered-grid finite-difference scheme

It is difficult to extend the present time-space-domain or temporal high-order finite-difference (FD) stencils to model anisotropic wave equations owing to anisotropy parameters and spatial derivatives are mutually coupled. Thus, high-order spatial and second-order temporal FDs are commonly used to discretize anisotropic wave equations. To improve temporal modeling accuracy, we develop an efficient temporal high-accuracy staggered-grid FD (SG-FD) scheme to solve the first-order elastic wave equations in 3D vertical transversely isotropic (VTI) media. Through combining the spatial dispersion relation of the original SG-FD stencil with the first-order k (wavenumber)-space operator, we construct a modified SG-FD dispersion relation and determine FD coefficients using least-squares (LS). We adopt the modified LS-based SG-FD scheme using k-space operator compensation to simulate 3D elastic VTI wave propagation. Dispersion analysis and numerical examples demonstrate that our optimal k-space operator-based SG-FD scheme can achieve high temporal accuracy without compromising spatial accuracy compared with the traditionally uncompensated Taylor-series expansion- and LS-based SG-FD methods. Moreover, the stability of our proposed FD scheme is superior to the conventional ones.

Optogenomic Interfaces: Bridging Biological Networks With the Electronic Digital World

The development of optical nano-bio interfaces is a fundamental step toward connecting biological networks and traditional electronic computing systems. Compared to conventional chemical and electrical nano-bio interfaces, the use of light as a mediator enables new type of interfaces with unprecedented spatial and temporal resolutions. In this paper, the state of the art and future research directions in optogenomic interfaces are discussed. Optogenomic interfaces are light-mediated nano-bio interfaces that allow the control of the genome, i.e., the genes and their interactions in the cell nucleus (and, thus, of all the cell functionalities) with (sub) cellular resolution and high temporal accuracy. Given its fundamental role in the process of cell development, the study is focused on the interactions with the fibroblast growth factor receptor 1 (FGFR1) gene and the integrative nuclear FGFR1 signaling (INFS) module in stem cells and in neuronal cells, whose control opens the door to transformative applications, including reconstructive medicine and cancer therapy. Three stages of optogenomic interfaces are described, ranging from already experimentally validated interfaces activating broad cellular responses and expressing individual genes to more advanced interfaces able to regulate and correct DNA topology, chromatin structure, and cellular development.

Conceptualizing and characterizing micro-urbanization: A new perspective applied to Africa

Sustainable Development Goals (SDG) require sustainable urban development and management for better human life quality. Small urban settlements—those with fewer than 500,000 people—are home to 26.5% of the world’s population. Yet, relatively little research attention has been paid to understanding the structure and dynamics of these smaller cities. In this paper, we propose a new concept, micro-urbanization, to fill this knowledge gap, and develop a methodology to characterize and map it using dense remote sensing time series data and landscape pattern metrics. We define micro-urbanization as a process of urban land change that has five primary characteristics: small, patchy, far from main urban areas, with limited geographic connection with existing urban areas and low urban intensity. We apply the method to two rapidly urbanizing countries in Africa, Nigeria and the Democratic Republic of the Congo. Results show that the methodology is capable of detecting micro-urbanization with relatively high spatial and temporal accuracy.