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Gradient sensing via cell communication
Experimental evidence lends support to the conjecture that cell-to-cell communication plays a role in the gradient sensing of chemical species by certain chains of cells. Models have been formulated to explore this idea. For cells with no identifiable sensing structure, Mugler et al. [Proc. Natl. Acad. Sci. (U.S.A.) 113, E689 (2016)] have defined a particular local excitation, global inhibition (LEGI) model that pits nearest-neighbor communication against local reactions in a noisy environment to suggest how this sensing capability might arise in a physical system. In this study, we generalize the nearest-neighbor communication mechanism in the aforementioned LEGI model in order to explore the extent to which the gradient sensing characteristics depend on the parametrization of the communication itself, as well as on the cell size, the radius of influence of neighboring cells, and the influence of the background noise. Using our generalization and a collection of particular candidate communication models, we find that the precision of gradient sensing is indeed sensitive to the particular communication model, and we derive physical and analytic explanations for these results. The framework established and the associated results should prove useful in understanding the appropriateness of particular cell-to-cell communication models in gradient sensing studies.
Status of structural analysis of 30 cm diameter ion optics
Three structural finite element programs are compared with theory, experimental data, and each other to evaluate their usefulness for modeling the thermomechanical deflection of ion engine electrodes. Two programs, NASTRAN and MARC, used a Cray XMP and the third, Algor, used an IBM compatible personal computer. The shape of the applied temperature gradient greatly affects off-axis displacement, implying that an accurate temperature distribution is required to analyze new designs. The use of bulk material constants to model the perforated electrodes was investigated. The stress and displacement predictions are shown to be sensitive to the temperature gradient and the Young's modulus, and insensitive to number of nodes, above some minimum value, and the Poisson ratio used. The models are shown to be useful tools for evaluating designs. Experimental measurement of temperatures and displacements was identified as the most critical area for further work.
Status of structural analysis of 30 cm diameter ion optics
Three structural finite element programs are compared with theory, experimental data, and each other to evaluate their usefulness for modeling the thermomechanical deflection of ion engine electrodes. Two programs, NASTRAN and MARC, used a Cray XMP and the third, Algor, used an IBM compatible personal computer. The shape of the applied temperature gradient greatly affects off-axis displacement, implying that an accurate temperature distribution is required to analyze new designs. The use of bulk material constants to model the perforated electrodes was investigated. The stress and displacement predictions are shown to be sensitive to the temperature gradient and the Young's modulus, and insensitive to number of nodes, above some minimum value, and the Poisson ratio used. The models are shown to be useful tools for evaluating designs. Experimental measurements of temperatures and displacements was identified as the most critical area.
Monsoon Depression Amplification by Horizontal Shear and Humidity Gradients: A Shallow Water Perspective
Transient, synoptic-scale vortices produce a large fraction of total rainfall in most monsoon regions and are often associated with extreme precipitation. However, the mechanism of their amplification remains a topic of active research. For monsoon depressions, which are the most prominent synoptic-scale vortex in the Asian–Australian monsoon, recent work has suggested that meridional gradients in zonal wind in the vortex environment may produce growth through barotropic instability, while meridional gradients in environmental humidity have also been proposed to cause amplification through coupling with precipitating convection. Here, a two-dimensional shallow water model on a sphere with parameterized precipitation is used to examine the relative role played by these two environmental gradients. By systematically varying the meridional moisture gradient and meridional wind shear for both weak, quasi-linear waves and finite-amplitude isolated vortices, we show that rotational winds in the initial vortex are amplified most strongly by meridional shear of the environmental zonal wind, while vortex precipitation rates are most sensitive to environmental moisture gradients. The growth rate in the presence of both gradients is less than the sum of growth rates in the presence of isolated gradients, as the phase relation between moisture and vorticity anomalies becomes distorted with increasing shear. In conclusion, these results suggest that background meridional gradients in both zonal wind and environmental humidity can contribute to the amplification of vortices to monsoon depression strength, but with some degree of decoupling of the dry rotational flow and the moist convection.
Computational assessment of smooth and rough parameter dependence of statistics in chaotic dynamical systems
An assumption of smooth response to small parameter changes, of statistics or long-time averages of a chaotic system, is generally made in the field of sensitivity analysis, and the parametric derivatives of statistical quantities are critically used in science and engineering. In this paper, we propose a numerical procedure to assess the differentiability of statistics with respect to parameters in chaotic systems. Here, we numerically show that the existence of the derivative depends on the Lebesgue integrability of a certain density gradient function, which we define as the derivative of logarithmic SRB density along the unstable manifold. We develop a recursive formula for the density gradient that can be efficiently computed along trajectories, and demonstrate its use in determining the differentiability of statistics. Our numerical procedure is illustrated on low-dimensional chaotic systems whose statistics exhibit both smooth and rough regions in parameter space.
Gravity surveys using a mobile atom interferometer
Mobile gravimetry is important in metrology, navigation, geodesy, and geophysics. Atomic gravimeters could be among the most accurate mobile gravimeters but are currently constrained by being complex and fragile. Here, we demonstrate a mobile atomic gravimeter, measuring tidal gravity variations in the laboratory and surveying gravity in the field. The tidal gravity measurements achieve a sensitivity of 37 μGal/ Hz (1 μGal = 10 nm/s 2 ) and a long-term stability of better than 2 μGal, revealing ocean tidal loading effects and recording several distant earthquakes. We survey gravity in the Berkeley Hills with an uncertainty of around 0.04 mGal and determine the density of the subsurface rocks from the vertical gravity gradient. With simplicity and sensitivity, our instrument paves the way for bringing atomic gravimeters to field applications.
Flow structure in continuous flow electrophoresis chambers
There are at least two ways that hydrodynamic processes can limit continiuous flow electrophoresis. One arises from the sensitivity of the flow to small temerature gradients, especially at low flow rates and power levels. This sensitivity can be suppressed, at least in principle, by providing a carefully tailored, stabilizing temperature gradient in the cooling system that surrounds the flow channel. At higher power levels another limitation arises due to a restructuring of the main flow. This restructuring is caused by buoyancy, which is in turn affected by the electro-osmotic crossflow. Approximate solutions to appropriate partial differential equations have been computed by finite difference methods. One set of results is described here to illustrate the strong coupling between the structure of the main (axial) flow and the electro-osmotic flow.
Files and scripts to support manuscript Needham et al. Canopy Gradients of Respiration
This dataset includes the parameter files, relevant output files, and scripts to perform analysis with Jupyter notebooks that support the manuscript Needham et al 2025 “Canopy Gradients of Respiration Drive Plant Carbon Budgets and Leaf Area Index.” We add functionality to the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) to allow flexible vertical gradients of leaf maintenance respiration (Rdark) and maximum carboxylation rate (Vcmax) through the canopy. We test the sensitivity of FATES to canopy gradients in Rdark, both in global simulations to assess broad scale impacts on leaf area index (LAI) and vegetation carbon, and in single site simulations where we assess impacts on plant functional type (PFT) competitive dynamics. Parameter files are netcdf files that can be converted to human readable .cdl files using NCO tools. Analysis scripts are Jupyter notebook files. These can be opened and run using the open source Jupyter notebook software. Model outputs are netcdf files.
Innovative design of composite structures: The use of curvilinear fiber format to improve buckling resistance of composite plates with central circular holes
The gains in buckling performance are explored that can be achieved by deviating from the conventional straightline fiber format and considering the situation whereby the fiber orientation in a layer, or a group of layers, can vary from point to point. The particular situation studied is a simply supported square plate with a centrally located hole loaded in compression. By using both a sensitivity analysis and a gradient-search technique, fiber orientation in a number of regions of the plate are selected so as to increase the buckling load relative to baseline straightline designs. The sensitivity analysis is used to determine which regions of the plate have the most influence on buckling load, and the gradient search is used to find the design that is believed to represent the absolute maximum buckling load for the conditions prescribed. Convergence studies and sensitivity of the final design are discussed. By examining the stress resultant contours, it is shown how the curvilinear fibers move the load away from the unsupported hole region of the plate to the supported edges, thus increasing the buckling capacity. The tensile capacity of the improved buckling design is investigated, and it is shown that both tensile capacity and buckling capacity can be improved with the curvilinear fiber concept.
The use of curvilinear fiber format to improve buckling resistance of composite plates with central circular holes
The gains in buckling performance are explored that can be achieved by deviating from the conventional straightline fiber format and considering the situation whereby the fiber orientation in a layer, or a group of layers, can vary from point to point. The particular situation studied is a simply supported square plate with a centrally located hole loaded in compression. By using both a sensitivity analysis and a gradient-search technique, fiber orientation in a number of regions of the plate are selected so as to increase the buckling load relative to baseline straightline designs. The sensitivity analysis is used to determine which regions of the plate have the most influence on buckling load, and the gradient search is used to find the design that is believed to represent the absolute maximum buckling load for the conditions prescribed. Convergence studies and sensitivity of the final design are discussed. By examining the stress resultant contours, it is shown how the curvilinear fibers move the load away from the unsupported hole region of the plate to the supported edges, thus increasing the buckling capacity. The tensile capacity of the improved buckling design is investigated, and it is shown that both tensile capacity and buckling capacity can be improved with the curvilinear fiber concept.
Relating Paleoclimate Data and Past Temperature Gradients: Some Suggestive Rules
Understanding tropical sensitivity is perhaps the major concern confronting researchers, for both past and future climate change issues. Tropical data has been beset by contradictions, and many techniques applicable to the extratropics are either unavailable or fraught with uncertainty when applied at low latitudes. Paleoclimate data, if interpreted within the context of the latitudinal temperature gradient data they imply, can be used to estimate what happened to tropical temperatures in the past, and provide a first guess for what might happen in the future. The approach is made possible by the modeling result that atmospheric dynamical changes, and the climate impacts they produce, respond primarily to temperature gradient changes. Here we review some "rules" obtained from GCM (General Circulation Model) experiments with different sea surface temperature gradients and different forcing, that can be used to relate paleoclimate reconstructions to the likely temperature gradient changes they suggest.
Effect of elevation, season and accelerated snowmelt on biogeochemical processes during isolated conifer needle litter decomposition
Increased drought and temperatures associated with climate change have implications for ecosystem stress with risk for enhanced carbon release in sensitive biomes. Litter decomposition is a key component of biogeochemical cycling in terrestrial ecosystems, but questions remain regarding the local response of decomposition processes to climate change. This is particularly complex in mountain ecosystems where the variable nature of the slope, aspect, soil type, and snowmelt dynamics play a role. Hence, the goal of this study was to determine the role of elevation, soil type, seasonal shifts in soil moisture, and snowmelt timing on litter decomposition processes. Experimental plots containing replicate deployments of harvested lodgepole and spruce needle litter alongside needle-free controls were established in open meadows at three elevations ranging from 2,800–3,500 m in Crested Butte, Colorado. Soil biogeochemistry variables including gas flux, porewater chemistry, and microbial ecology were monitored over three climatically variable years that shifted from high monsoon rains to drought. Results indicated that elevation and soil type influenced baseline soil biogeochemical indicators; however, needle mass loss and chemical composition were consistent across the 700 m elevation gradient. Rates of gas flux were analogously consistent across a 300 m elevation gradient. The additional variable of early snowmelt by 2–3 weeks had little impact on needle chemistry, microbial composition and gas flux; however, it did result in increased dissolved organic carbon in lodgepole porewater collections suggesting a potential for aqueous export. In contrast to elevation, needle presence and seasonal variability of soil moisture and temperature both played significant roles in soil carbon fluxes. Furthermore, during a pronounced period of lower moisture and higher temperatures, bacterial community diversity increased across elevation with new members supplanting more dominant taxa. Microbial ecological resilience was demonstrated with a return to pre-drought structure and abundance after snowmelt rewetting the following year. These results show similar decomposition processes across a 700 m elevation gradient and reveal the sensitivity but resilience of soil microbial ecology to low moisture conditions.
MITgcm-AD v2: Open source tangent linear and adjoint modeling framework for the oceans and atmosphere enabled by the Automatic Differentiation tool Tapenade
The Massachusetts Institute of Technology General Circulation Model (MITgcm) is widely used by the climate science community to simulate planetary atmosphere and ocean circulations. A defining feature of the MITgcm is that it has been developed to be compatible with an algorithmic differentiation (AD) tool, TAF, enabling the generation of tangent-linear and adjoint models. These provide gradient information which enables dynamics-based sensitivity and attribution studies, state and parameter estimation, and rigorous uncertainty quantification. Importantly, gradient information is essential for computing comprehensive sensitivities and performing efficient large-scale data assimilation, ensuring that observations collected from satellites and in-situ measuring instruments can be effectively used to optimize a large uncertain control space. As a result, the MITgcm forms the dynamical core of a key data assimilation product employed by the physical oceanography research community: Estimating the Circulation and Climate of the Ocean (ECCO) state estimate. Although MITgcm and ECCO are used extensively within the research community, the AD tool TAF is proprietary and hence inaccessible to a large proportion of these users. The new version 2 (MITgcm-AD v2) framework introduced here is based on the source-to-source AD tool Tapenade, which has recently been open-sourced. Another feature of Tapenade is that it stores required variables by default (instead of recomputing them) which simplifies the implementation of efficient, AD-compatible code. The framework has been integrated with the MITgcm model’s main branch and is now freely available.
On the numerical sensitivity of cellular automata grain structure predictions to large thermal gradients and cooling rates
Cellular automata (CA) models of as-solidified grain structure, originally developed and applied to casting, have become a common means of predicting grain structure resulting from Additive Manufacturing (AM) processes. The majority of these models are based on the decentered octahedron approach, which attempts to correct for the effect of grid anisotropy on the prediction of competitive solidification of dendritic grains. However, AM solidification occurs under cooling rates ($\dot{T}$) and thermal gradients (G) that are orders of magnitude larger than those encountered in casting, and no systematic investigation on the effect of the CA model cell size (Δx) and time step (Δt) on AM microstructure predictions has been performed. Here, in this study, such an investigation is first performed via simulation of individual grains of various crystallographic orientations with a fixed, unidirectional G, showing that CA prediction of the steady-state undercooling matched the expected values based on the interfacial response function at small G and deviated from the expected values at large G. Simulation of competitive growth of multiple grains showed a weakening of the predicted texture as G and Δx became large. Simulation of solidification under AM conditions, where G and $\dot{T}$ vary spatially across the melt pools, showed that not only does grain selection weaken and deviate from expectations at large Δx, but grains with crystallographic $\langle$100$\rangle$ aligned with the grid directions are more adversely affected by the temperature field discontinuities than grains with other crystallographic orientations. Despite the fact that the exact grain competition results depended on Δt, the overall texture development was notably less sensitive to Δt than Δx, provided that a reasonable value of Δt is selected based on the ratio of Δx to the maximum local solidification velocity in the simulation domain. Finally, from the directional solidification and AM simulation results, an analysis of computational cost compared to simulation resolution is performed based on an equation derived to quantify the relatively inaccuracy in grain selection based on the model and temperature field inputs. From this analysis, it is concluded that there is a need for algorithmic improvements to improve CA grain competition accuracy for large G processing conditions as sufficiently small Δx to resolve the necessary competition is intractable for many AM processing conditions.
Comparisons Between Array Derived Dynamic Strain Rate (ADDS) and Fiber‐Optic Distributed Acoustic Sensing (DAS) Strain Rate
Abstract Distributed acoustic sensing (DAS) strain rate and particle velocity can be compared through approximate scaling with medium velocity. We instead performed a direct comparison between array derived dynamic strain (ADDS) rate and DAS strain rate for six frequency bands. The PoroTomo project at Brady's Hot Springs, Nevada, deployed a 240‐geophone 3C array co‐located with fiber‐optic DAS system and 8.7 km of buried cable. We selected subsets of the geophone array to create four smaller arrays and computed ADDS. The horizontal components of the ADDS were rotated into the direction of the fiber‐optic cable and then compared with the observed DAS strain rates. From three example regional earthquakes of local magnitudes 2.9, 4.1, and 4.3, the ADDS are found to be coherent with DAS for frequencies ≤1 Hz. For frequencies >1‐Hz, this correlation decays quickly. Small differences between linear and areal dynamic strains at 1‐Hz suggest poor signal‐to‐noise or localized strain that is perturbed by shallow heterogeneities compare to the average strain propagating across the geophone array. The implication is that around 1‐Hz, straight fiber DAS is measuring axial strain along the fiber and can provide good approximations to translational particle motions. However, above 1‐Hz, DAS becomes more sensitive to shallow velocity gradients that can be beneficial for geophysical imaging yet becomes a limitation for traditional seismic analysis methods depending on absolute amplitude and phase from translational particle motions.
Advances in Kriging-Based Autonomous X-Ray Scattering Experiments
Autonomous experimentation is an emerging paradigm for scientific discovery, wherein measurement instruments are augmented with decision-making algorithms, allowing them to autonomously explore parameter spaces of interest. We have recently demonstrated a generalized approach to autonomous experimental control, based on generating a surrogate model to interpolate experimental data, and a corresponding uncertainty model, which are computed using a Gaussian process regression known as ordinary Kriging (OK). We demonstrated the successful application of this method to exploring materials science problems using x-ray scattering measurements at a synchrotron beamline. Here, we report several improvements to this methodology that overcome limitations of traditional Kriging methods. The variogram underlying OK is global and thus insensitive to local data variation. We augment the Kriging variance with model-based measures, for instance providing local sensitivity by including the gradient of the surrogate model. As with most statistical regression methods, OK minimizes the number of measurements required to achieve a particular model quality. However, in practice this may not be the most stringent experimental constraint; e.g. the goal may instead be to minimize experiment duration or material usage. We define an adaptive cost function, allowing the autonomous method to balance information gain against measured experimental cost. We provide synthetic and experimental demonstrations, validating that this improved algorithm yields more efficient autonomous data collection.
Seismic inversion of the solar entropy: setting a cat among the pigeons
The Sun is the most constrained and well-studied of all stars. As a consequence, the physical ingredients entering solar models are used as a reference to study all other stars observed in the Universe. However, our understanding of the solar structure is still imperfect, as illustrated by the current debate on the heavy element abundances in the Sun. Aims. We wish to provide additional information on the solar structure by carrying out structural inversions of a new physical quantity, a proxy of the entropy of the solar plasma which properties are very sensitive to the temperature gradient below the convective zone. Methods. We use new structural kernels to carry out direct inversions of an entropy proxy of the solar plasma and compare the solar structure to various standard solar models built using various opacity tables and chemical abundances. We also link our results to classical tests commonly found in the literature. Results. Our analysis allows us to probe more efficiently the uncertain regions of the solar models, just below the convective zone, paving the way for new in-depth analyses of the Sun taking into account additional physical uncertainties of solar models beyond the specific question of chemical abundances.