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Time-resolved imaging of the cellular structure of methane and natural gas detonations
No full textWe present experimental observations of the density field and reaction structure of methane and natural gas detonation waves propagating in a narrow channel. Simultaneous time-resolved schlieren and CH∗ chemiluminescence images are used to describe the structure of the unstable front. Nitrogen dilution concentration is varied, and the effect of increasing dilution is to increase the instability level and cell size and decrease the chemiluminescence intensity. Comparison is made between methane- and natural gas-fueled detonations. The effect of the higher hydrocarbons present in natural gas, primarily ethane, is to increase the fine-scale structure of the detonation front and create a more continuous reaction front. Utilizing the simultaneous images, observations are made about the formation and dissipation of the material separated across the shear layer behind the front
Space-time duality between quantum chaos and non-Hermitian boundary effect
No full textQuantum chaos in Hermitian systems concerns the sensitivity of long-time dynamical evolution to initial conditions. The skin effect discovered recently in non-Hermitian systems reveals the sensitivity to the spatial boundary condition even deep in the bulk. In this Letter, we show that these two seemingly different phenomena can be unified through the space-time duality. The intuition is that the space-time duality maps unitary dynamics to nonunitary dynamics and exchanges the temporal direction and spatial direction. Therefore, the space-time duality can establish the connection between the sensitivity to the initial condition in the temporal direction and the sensitivity to the boundary condition in the spatial direction. Here, we demonstrate this connection by studying the space-time duality of the out-of-time-ordered correlator in a concrete chaotic Hermitian model. We show that the out-of-time-ordered correlator is mapped to a special two-point correlator of a non-Hermitian system in the dual picture. For comparison, we show that the sensitivity disappears when the non-Hermiticity is removed in the dual picture
A general Bayesian nonlinear estimation method using resampled Smooth Particle Hydrodynamics solutions of the underlying Fokker–Planck Equation
No full textThe effectiveness of nonlinear filters depends on many factors, but one of the most important is how accurately the filter is able to predict the state dynamics of the underlying system between measurements. For a wide class of Gaussian white noise driven nonlinear systems the Bayesian optimal prior can be obtained by solving the system’s corresponding Fokker–Planck Equation (FPE). Unfortunately the Fokker–Planck Equation is a partial differential equation with dimension equal to the number of states in the underlying dynamical system, making it extremely difficult to solve for realistic systems due to Curse of Dimensionality scaling issues. As a result it has been and still largely remains computationally impractical to simulate higher dimensional Fokker–Planck equations, at least while obtaining very high accuracy across the entire transient probability density function. This paper presents a general nonlinear filter based on solving the transient Fokker–Planck equation via Smooth Particle Hydrodynamics (SPH) at lower resolution, which turns out to still allow for accurate state estimation. The filter is enabled by an efficient heuristic resampling scheme of the SPH solution also presented here. The FPE-SPH Filter is able to replicate the accuracy of the Particle Filter and Extended Kalman filter (EKF) for lower-dimensional systems, while also being more robust than the EKF on certain classes of system
Attributing differences of solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationships between two C4 crops: corn and miscanthus
No full textThere remains limited information to characterize the solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationship in C4 cropping systems. The annual C4 crop corn and perennial C4 crop miscanthus differ in phenology, canopy structure and leaf physiology. Investigating the SIF-GPP relationships in these species could deepen our understanding of SIF-GPP relationships within C4 crops. Using in situ canopy SIF and GPP measurements for both species along with leaf-level measurements, we found considerable differences in the SIF-GPP relationships between corn and miscanthus, with a stronger SIF-GPP relationship and higher slope of SIF-GPP observed in corn compared to miscanthus. These differences were mainly caused by leaf physiology. For miscanthus, high non-photochemical quenching (NPQ) under high light, temperature and water vapor deficit (VPD) conditions caused a large decline of fluorescence yield (Φ_F), which further led to a SIF midday depression and weakened the SIF-GPP relationship. The larger slope in corn than miscanthus was mainly due to its higher GPP in mid-summer, largely attributed to the higher leaf photosynthesis and less NPQ. Our results demonstrated variation of the SIF-GPP relationship within C4 crops and highlighted the importance of leaf physiology in determining canopy SIF behaviors and SIF-GPP relationships
A multi-phase field model for mesoscopic interface dynamics with large bulk driving forces
No full textWe develop a multi-phase field model for diffuse interface dynamics with large bulk chemical driving forces for phase transformation using the double-obstacle potential. We show how the classical prefactor functions for the bulk driving force significantly overestimate the velocity of multi-order-parameter junctions. We introduce a novel prefactor that properly distributes the forces for phase transformation among an arbitrary number of coexisting thermodynamic phases and order-parameters (i.e., melt patches and solid grains). The accuracy of the model is examined and we describe techniques to ensure accuracy for use with and without large bulk driving forces, including interface correction procedures that prevent profile deformation, and a recursive predictor–corrector technique for inter-parameter transfer at junctions. We explore the predictions of our models for a number of two-dimensional model configurations, including the shrinking circle, the moving tri-junction, and a shrinking circular crystal embedded in a fine-grained polycrystalline medium. The predictions for a moving tri-junction under increasingly large bulk driving forces (or length scales) are particularly notable, as the steady-state geometry of junctions deviate systematically from Young’s law for a given length scale. We provide an ansatz for the junction geometry in the case where a single-order-parameter phase (e.g., melt) consumes a multi-order-parameter phase (e.g., polycrystalline solid); an accurate solution for the opposite case remains elusive at present
Disrupting cellular memory to overcome drug resistance
No full textPlasticity enables cells to change their gene expression state in the absence of a genetic change. At the single-cell level, these gene expression states can persist for different lengths of time which is a quantitative measurement referred to as gene expression memory. Because plasticity is not encoded by genetic changes, these cell states can be reversible, and therefore, are amenable to modulation by disrupting gene expression memory. However, we currently do not have robust methods to find the regulators of memory or to track state switching in plastic cell populations. Here, we developed a lineage tracing-based technique to quantify gene expression memory and to identify single cells as they undergo cell state transitions. Applied to human melanoma cells, we quantified long-lived fluctuations in gene expression that underlie resistance to targeted therapy. Further, we identified the PI3K and TGF-β pathways as modulators of these state dynamics. Applying the gene expression signatures derived from this technique, we find that these expression states are generalizable to in vivo models and present in scRNA-seq from patient tumors. Leveraging the PI3K and TGF-β pathways as dials on memory between plastic states, we propose a “ pretreatment” model in which we first use a PI3K inhibitor to modulate the expression states of the cell population and then apply targeted therapy. This plasticity informed dosing scheme ultimately yields fewer resistant colonies than targeted therapy alone. Taken together, we describe a technique to find modulators of gene expression memory and then apply this knowledge to alter plastic cell states and their connected cell fates
Carbon isotope fractionation by an ancestral rubisco suggests biological proxies for CO₂ through geologic time should be re-evaluated
No full textThe history of Earth's carbon cycle reflects trends in atmospheric composition convolved with the evolution of photosynthesis. Fortunately, key parts of the carbon cycle have been recorded in the carbon isotope ratios of sedimentary rocks. The dominant model used to interpret this record as a proxy for ancient atmospheric CO₂ is based on carbon isotope fractionations of modern photoautotrophs, and longstanding questions remain about how their evolution might have impacted the record. We tested the intersection of environment and evolution by measuring both biomass (ϵₚ) and enzymatic (ϵRubisco) carbon isotope fractionations of a cyanobacterial strain (Synechococcus elongatus PCC 7942) solely expressing a putative ancestral Form 1B rubisco dating to ≫1 Ga. This strain, nicknamed ANC, grows in ambient pCO₂ and displays larger ϵₚ values than WT, despite having a much smaller ϵ_(Rubisco) (17.23 ± 0.61‰ vs. 25.18 ± 0.31‰, respectively). Measuring both enzymatic and biomass fractionation revealed a surprising result -- ANC ϵₚ exceeded ANC ϵRubisco in all conditions tested, contradicting prevailing models of cyanobacterial carbon isotope fractionation. However, these models were corrected by accounting for cyanobacterial physiology, notably the CO₂ concentrating mechanism (CCM). Our model suggested that additional fractionating processes like powered inorganic carbon uptake systems contribute to ϵₚ, and this effect is exacerbated in ANC. Understanding the evolution of rubisco and the CCM is therefore critical for interpreting the carbon isotope record. Large fluctuations in that record may reflect the evolving efficiency of carbon fixing metabolisms in addition to changes in atmospheric CO₂
Stable allocations in discrete economies
No full textWe study discrete allocation problems, as in the textbook notion of an exchange economy, but with indivisible goods. The problem is well-known to be difficult. The model is rich enough to encode some of the most pathological bargaining configurations in game theory, like the roommate problem. Our contribution is to show the existence of stable allocations (outcomes in the weak core, or in the bargaining set) under different sets of assumptions. Specifically, we consider dichotomous preferences, categorical economies, and discrete TU markets. The paper uses varied techniques, from Scarf's balanced games to a generalization of the TTC algorithm by means of Tarski fixed points
Efficiency in Random Resource Allocation and Social Choice
No full textWe study efficiency in general collective choice problems when agents have ordinal preferences and randomization is allowed. We establish the equivalence between welfare maximization and ex-ante efficiency for general domains. We relate ex-ante efficiency with ex-post efficiency, characterizing when the two notions coincide. Our results have implications for well-studied mechanisms including random serial dictatorship and a number of specific environments, including the dichotomous, single-peaked, and social choice domains
Transcranial photoacoustic computed tomography of human brain function
No full textHerein we report the first in-human transcranial imaging of brain function using photoacoustic computed tomography. Functional responses to benchmark motor tasks were imaged on both the skull-less and the skull-intact hemispheres of a hemicraniectomy patient. The observed brain responses in these preliminary results demonstrate the potential of photoacoustic computed tomography for achieving transcranial functional imaging