Estimation of Ordinary Differential Equation Parameters Using Constrained Local Polynomial Regression.

PubMed

Ding, A Adam; Wu, Hulin

2014-10-01

We propose a new method to use a constrained local polynomial regression to estimate the unknown parameters in ordinary differential equation models with a goal of improving the smoothing-based two-stage pseudo-least squares estimate. The equation constraints are derived from the differential equation model and are incorporated into the local polynomial regression in order to estimate the unknown parameters in the differential equation model. We also derive the asymptotic bias and variance of the proposed estimator. Our simulation studies show that our new estimator is clearly better than the pseudo-least squares estimator in estimation accuracy with a small price of computational cost. An application example on immune cell kinetics and trafficking for influenza infection further illustrates the benefits of the proposed new method.

Estimation of Ordinary Differential Equation Parameters Using Constrained Local Polynomial Regression

PubMed Central

Ding, A. Adam; Wu, Hulin

2015-01-01

We propose a new method to use a constrained local polynomial regression to estimate the unknown parameters in ordinary differential equation models with a goal of improving the smoothing-based two-stage pseudo-least squares estimate. The equation constraints are derived from the differential equation model and are incorporated into the local polynomial regression in order to estimate the unknown parameters in the differential equation model. We also derive the asymptotic bias and variance of the proposed estimator. Our simulation studies show that our new estimator is clearly better than the pseudo-least squares estimator in estimation accuracy with a small price of computational cost. An application example on immune cell kinetics and trafficking for influenza infection further illustrates the benefits of the proposed new method. PMID:26401093

High pressure cosmochemistry applied to major planetary interiors: Experimental studies

NASA Technical Reports Server (NTRS)

Nicol, M. F.; Johnson, M.; Koumvakalis, A. S.

1984-01-01

Progress is reported on a project to determine the properties and boundaries of high pressure phases of the H2-He-H2O-NH3-CH4 system that are needed to constrain theoretical models of the interiors of the major planets. This project is one of the first attempts to measure phase equilibria in binary fluid-solid systems in diamond anvil cells. Vibrational spectroscopy, direct visual observations, and X-ray diffraction crystallography of materials confined in externally heated cells are the primary experimental probes. Adiabats of these materials are also measured in order to constrain models of heat flow in these bodies and to detect phase transitions by thermal anomalies. Initial efforts involve the NH3-H2O binary. This system is especially relevant to models for surface reconstruction of the icy satellites of Jupiter and Saturn. Thermal analysis experiments were completed for the P-X space, p4GPa:0 or = 0.50, near room temperature. The cryostat, sample handling equipment, and optics needed to extend the optical P-T-X work below room temperature was completed.

Simultaneous inhibition of key growth pathways in melanoma cells and tumor regression by a designed bidentate constrained helical peptide.

PubMed

Dhar, Amlanjyoti; Mallick, Shampa; Ghosh, Piya; Maiti, Atanu; Ahmed, Israr; Bhattacharya, Seemana; Mandal, Tapashi; Manna, Asit; Roy, Koushik; Singh, Sandeep; Nayak, Dipak Kumar; Wilder, Paul T; Markowitz, Joseph; Weber, David; Ghosh, Mrinal K; Chattopadhyay, Samit; Guha, Rajdeep; Konar, Aditya; Bandyopadhyay, Santu; Roy, Siddhartha

2014-07-01

Protein-protein interactions are part of a large number of signaling networks and potential targets for drug development. However, discovering molecules that can specifically inhibit such interactions is a major challenge. S100B, a calcium-regulated protein, plays a crucial role in the proliferation of melanoma cells through protein-protein interactions. In this article, we report the design and development of a bidentate conformationally constrained peptide against dimeric S100B based on a natural tight-binding peptide, TRTK-12. The helical conformation of the peptide was constrained by the substitution of α-amino isobutyric acid--an amino acid having high helical propensity--in positions which do not interact with S100B. A branched bidentate version of the peptide was bound to S100B tightly with a dissociation constant of 8 nM. When conjugated to a cell-penetrating peptide, it caused growth inhibition and rapid apoptosis in melanoma cells. The molecule exerts antiproliferative action through simultaneous inhibition of key growth pathways, including reactivation of wild-type p53 and inhibition of Akt and STAT3 phosphorylation. The apoptosis induced by the bidentate constrained helix is caused by direct migration of p53 to mitochondria. At moderate intravenous dose, the peptide completely inhibits melanoma growth in a mouse model without any significant observable toxicity. The specificity was shown by lack of ability of a double mutant peptide to cause tumor regression at the same dose level. The methodology described here for direct protein-protein interaction inhibition may be effective for rapid development of inhibitors against relatively weak protein-protein interactions for de novo drug development. © 2014 Wiley Periodicals, Inc.

A novel phenomenological multi-physics model of Li-ion battery cells

NASA Astrophysics Data System (ADS)

Oh, Ki-Yong; Samad, Nassim A.; Kim, Youngki; Siegel, Jason B.; Stefanopoulou, Anna G.; Epureanu, Bogdan I.

2016-09-01

A novel phenomenological multi-physics model of Lithium-ion battery cells is developed for control and state estimation purposes. The model can capture electrical, thermal, and mechanical behaviors of battery cells under constrained conditions, e.g., battery pack conditions. Specifically, the proposed model predicts the core and surface temperatures and reaction force induced from the volume change of battery cells because of electrochemically- and thermally-induced swelling. Moreover, the model incorporates the influences of changes in preload and ambient temperature on the force considering severe environmental conditions electrified vehicles face. Intensive experimental validation demonstrates that the proposed multi-physics model accurately predicts the surface temperature and reaction force for a wide operational range of preload and ambient temperature. This high fidelity model can be useful for more accurate and robust state of charge estimation considering the complex dynamic behaviors of the battery cell. Furthermore, the inherent simplicity of the mechanical measurements offers distinct advantages to improve the existing power and thermal management strategies for battery management.

Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xavier, MA; Trimboli, MS

This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggestmore » significant performance improvements might be achieved by extending the result to electrochemical models. (C) 2015 Elsevier B.V. All rights reserved.« less

Theories and models on the biological of cells in space

NASA Technical Reports Server (NTRS)

Todd, P.; Klaus, D. M.

1996-01-01

A wide variety of observations on cells in space, admittedly made under constraining and unnatural conditions in may cases, have led to experimental results that were surprising or unexpected. Reproducibility, freedom from artifacts, and plausibility must be considered in all cases, even when results are not surprising. The papers in symposium on 'Theories and Models on the Biology of Cells in Space' are dedicated to the subject of the plausibility of cellular responses to gravity -- inertial accelerations between 0 and 9.8 m/sq s and higher. The mechanical phenomena inside the cell, the gravitactic locomotion of single eukaryotic and prokaryotic cells, and the effects of inertial unloading on cellular physiology are addressed in theoretical and experimental studies.

Structure of neutron star crusts from new Skyrme effective interactions constrained by chiral effective field theory

NASA Astrophysics Data System (ADS)

Lim, Yeunhwan; Holt, Jeremy W.

2017-06-01

We investigate the structure of neutron star crusts, including the crust-core boundary, based on new Skyrme mean field models constrained by the bulk-matter equation of state from chiral effective field theory and the ground-state energies of doubly-magic nuclei. Nuclear pasta phases are studied using both the liquid drop model as well as the Thomas-Fermi approximation. We compare the energy per nucleon for each geometry (spherical nuclei, cylindrical nuclei, nuclear slabs, cylindrical holes, and spherical holes) to obtain the ground state phase as a function of density. We find that the size of the Wigner-Seitz cell depends strongly on the model parameters, especially the coefficients of the density gradient interaction terms. We employ also the thermodynamic instability method to check the validity of the numerical solutions based on energy comparisons.

Modelling cell motility and chemotaxis with evolving surface finite elements

PubMed Central

Elliott, Charles M.; Stinner, Björn; Venkataraman, Chandrasekhar

2012-01-01

We present a mathematical and a computational framework for the modelling of cell motility. The cell membrane is represented by an evolving surface, with the movement of the cell determined by the interaction of various forces that act normal to the surface. We consider external forces such as those that may arise owing to inhomogeneities in the medium and a pressure that constrains the enclosed volume, as well as internal forces that arise from the reaction of the cells' surface to stretching and bending. We also consider a protrusive force associated with a reaction–diffusion system (RDS) posed on the cell membrane, with cell polarization modelled by this surface RDS. The computational method is based on an evolving surface finite-element method. The general method can account for the large deformations that arise in cell motility and allows the simulation of cell migration in three dimensions. We illustrate applications of the proposed modelling framework and numerical method by reporting on numerical simulations of a model for eukaryotic chemotaxis and a model for the persistent movement of keratocytes in two and three space dimensions. Movies of the simulated cells can be obtained from http://homepages.warwick.ac.uk/∼maskae/CV_Warwick/Chemotaxis.html. PMID:22675164

Modeling the Morphogenesis of Epidermal Tissues on the Surface of a 3D Last

NASA Astrophysics Data System (ADS)

McCleery, W. Tyler; Crews, Sarah M.; Mashburn, David N.; Veldhuis, Jim; Brodland, G. Wayne; Hutson, M. Shane

2014-03-01

Embryogenesis in the fruit fly Drosophila melanogaster is coordinated by the interaction of cells in adjacent tissues. For some events of embryogenesis, e.g., dorsal closure, two-dimensional models have been sufficient to elucidate the relevant cell and tissue mechanics. Here, we describe a new three-dimensional cell-level finite element model for investigating germ band retraction - a morphogenetic event where one epidermal tissue, the germ band, initially wraps around the posterior end of the ellipsoidal embryo. This tissue then retracts with a mechanical assist from contraction of cells in a second epidermal tissue, the amnioserosa. To speed simulation run times and focus on the relevant tissues, we only model epidermal tissue interactions. Epidermal cells are defined as polygons constrained to lie on the surface of the ellipsoidal last, but have adjustable parameters such as edge tensions and cell pressures. Tissue movements are simulated by balancing these dynamic cell-level forces with viscous resistance and allowing cells to exchange neighbors. Our choice of modeling parameters is informed by in vivo measurements of cell-level forces using laser microsurgery. We use this model to investigate the multicellular stress fields in normal and aberrant development.

Automatic Cell Segmentation Using a Shape-Classification Model in Immunohistochemically Stained Cytological Images

NASA Astrophysics Data System (ADS)

Shah, Shishir

This paper presents a segmentation method for detecting cells in immunohistochemically stained cytological images. A two-phase approach to segmentation is used where an unsupervised clustering approach coupled with cluster merging based on a fitness function is used as the first phase to obtain a first approximation of the cell locations. A joint segmentation-classification approach incorporating ellipse as a shape model is used as the second phase to detect the final cell contour. The segmentation model estimates a multivariate density function of low-level image features from training samples and uses it as a measure of how likely each image pixel is to be a cell. This estimate is constrained by the zero level set, which is obtained as a solution to an implicit representation of an ellipse. Results of segmentation are presented and compared to ground truth measurements.

Nonlinear Recurrent Neural Network Predictive Control for Energy Distribution of a Fuel Cell Powered Robot

PubMed Central

Chen, Qihong; Long, Rong; Quan, Shuhai

2014-01-01

This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell. PMID:24707206

Cooperativity and redundancy in the mechanics of compositely crosslinked branched anisotropic cytoskeletal networks

NASA Astrophysics Data System (ADS)

Schwarz, J. M.; Zhang, Tao; Das, Moumita

2013-03-01

At the leading edge of a crawling cell, the actin cytoskeleton extends itself in a particular direction via a branched crosslinked network of actin filaments with some overall alignment. This network is known as the lamellipodium. Branching via the complex Arp2/3 occurs at a reasonably well-defined angle of 70 degrees from the plus end of the mother filament such that Arp2/3 can be modeled as an angle-constraining crosslinker. Freely-rotating crosslinkers, such as alpha-actinin, are also present in lamellipodia. Therefore, we study the interplay between these two types of crosslinkers, angle-constraining and free-rotating, both analytically and numerically, to begin to quantify the mechanics of lamellipodia. We also investigate how the orientational ordering of the filaments affects this interplay. Finally, while role of Arp2/3 as a nucleator for filaments along the leading edge of a crawling cell has been studied intensely, much less is known about its mechanical contribution. Our work seeks to fill in this important gap in modeling the mechanics of lamellipodia.

A mathematical model for predicting the life of polymer electrolyte fuel cell membranes subjected to hydration cycling

NASA Astrophysics Data System (ADS)

Burlatsky, S. F.; Gummalla, M.; O'Neill, J.; Atrazhev, V. V.; Varyukhin, A. N.; Dmitriev, D. V.; Erikhman, N. S.

2012-10-01

Under typical Polymer Electrolyte Membrane Fuel Cell (PEMFC) fuel cell operating conditions, part of the membrane electrode assembly is subjected to humidity cycling due to variation of inlet gas RH and/or flow rate. Cyclic membrane hydration/dehydration would cause cyclic swelling/shrinking of the unconstrained membrane. In a constrained membrane, it causes cyclic stress resulting in mechanical failure in the area adjacent to the gas inlet. A mathematical modeling framework for prediction of the lifetime of a PEMFC membrane subjected to hydration cycling is developed in this paper. The model predicts membrane lifetime as a function of RH cycling amplitude and membrane mechanical properties. The modeling framework consists of three model components: a fuel cell RH distribution model, a hydration/dehydration induced stress model that predicts stress distribution in the membrane, and a damage accrual model that predicts membrane lifetime. Short descriptions of the model components along with overall framework are presented in the paper. The model was used for lifetime prediction of a GORE-SELECT membrane.

Anomalous dynamics of intruders in a crowded environment of mobile obstacles

PubMed Central

Sentjabrskaja, Tatjana; Zaccarelli, Emanuela; De Michele, Cristiano; Sciortino, Francesco; Tartaglia, Piero; Voigtmann, Thomas; Egelhaaf, Stefan U.; Laurati, Marco

2016-01-01

Many natural and industrial processes rely on constrained transport, such as proteins moving through cells, particles confined in nanocomposite materials or gels, individuals in highly dense collectives and vehicular traffic conditions. These are examples of motion through crowded environments, in which the host matrix may retain some glass-like dynamics. Here we investigate constrained transport in a colloidal model system, in which dilute small spheres move in a slowly rearranging, glassy matrix of large spheres. Using confocal differential dynamic microscopy and simulations, here we discover a critical size asymmetry, at which anomalous collective transport of the small particles appears, manifested as a logarithmic decay of the density autocorrelation functions. We demonstrate that the matrix mobility is central for the observed anomalous behaviour. These results, crucially depending on size-induced dynamic asymmetry, are of relevance for a wide range of phenomena ranging from glassy systems to cell biology. PMID:27041068

Groundwater management under uncertainty using a stochastic multi-cell model

NASA Astrophysics Data System (ADS)

Joodavi, Ata; Zare, Mohammad; Ziaei, Ali Naghi; Ferré, Ty P. A.

2017-08-01

The optimization of spatially complex groundwater management models over long time horizons requires the use of computationally efficient groundwater flow models. This paper presents a new stochastic multi-cell lumped-parameter aquifer model that explicitly considers uncertainty in groundwater recharge. To achieve this, the multi-cell model is combined with the constrained-state formulation method. In this method, the lower and upper bounds of groundwater heads are incorporated into the mass balance equation using indicator functions. This provides expressions for the means, variances and covariances of the groundwater heads, which can be included in the constraint set in an optimization model. This method was used to formulate two separate stochastic models: (i) groundwater flow in a two-cell aquifer model with normal and non-normal distributions of groundwater recharge; and (ii) groundwater management in a multiple cell aquifer in which the differences between groundwater abstractions and water demands are minimized. The comparison between the results obtained from the proposed modeling technique with those from Monte Carlo simulation demonstrates the capability of the proposed models to approximate the means, variances and covariances. Significantly, considering covariances between the heads of adjacent cells allows a more accurate estimate of the variances of the groundwater heads. Moreover, this modeling technique requires no discretization of state variables, thus offering an efficient alternative to computationally demanding methods.

A unified wall function for compressible turbulence modelling

NASA Astrophysics Data System (ADS)

Ong, K. C.; Chan, A.

2018-05-01

Turbulence modelling near the wall often requires a high mesh density clustered around the wall and the first cells adjacent to the wall to be placed in the viscous sublayer. As a result, the numerical stability is constrained by the smallest cell size and hence requires high computational overhead. In the present study, a unified wall function is developed which is valid for viscous sublayer, buffer sublayer and inertial sublayer, as well as including effects of compressibility, heat transfer and pressure gradient. The resulting wall function applies to compressible turbulence modelling for both isothermal and adiabatic wall boundary conditions with the non-zero pressure gradient. Two simple wall function algorithms are implemented for practical computation of isothermal and adiabatic wall boundary conditions. The numerical results show that the wall function evaluates the wall shear stress and turbulent quantities of wall adjacent cells at wide range of non-dimensional wall distance and alleviate the number and size of cells required.

Contact enhancement of locomotion in spreading cell colonies

NASA Astrophysics Data System (ADS)

D'Alessandro, Joseph; Solon, Alexandre P.; Hayakawa, Yoshinori; Anjard, Christophe; Detcheverry, François; Rieu, Jean-Paul; Rivière, Charlotte

2017-10-01

The dispersal of cells from an initially constrained location is a crucial aspect of many physiological phenomena, ranging from morphogenesis to tumour spreading. In such processes, cell-cell interactions may deeply alter the motion of single cells, and in turn the collective dynamics. While contact phenomena like contact inhibition of locomotion are known to come into play at high densities, here we focus on the little explored case of non-cohesive cells at moderate densities. We fully characterize the spreading of micropatterned colonies of Dictyostelium discoideum cells from the complete set of individual trajectories. From data analysis and simulation of an elementary model, we demonstrate that contact interactions act to speed up the early population spreading by promoting individual cells to a state of higher persistence, which constitutes an as-yet unreported contact enhancement of locomotion. Our findings also suggest that the current modelling paradigm of memoryless active particles may need to be extended to account for the history-dependent internal state of motile cells.

Reconstruction of a yeast cell from x-ray diffraction data

DOE PAGES

Thibault, Pierre; Elser, Veit; Jacobsen, Chris; ...

2006-06-21

We provide details of the algorithm used for the reconstruction of yeast cell images in the recent demonstration of diffraction microscopy by Shapiro, Thibault, Beetz, Elser, Howells, Jacobsen, Kirz, Lima, Miao, Nieman & Sayre. Two refinements of the iterative constraint-based scheme are developed to address the current experimental realities of this imaging technique, which include missing central data and noise. A constrained power operator is defined whose eigenmodes allow the identification of a small number of degrees of freedom in the reconstruction that are negligibly constrained as a result of the missing data. To achieve reproducibility in the algorithm's output,more » a special intervention is required for these modes. Weak incompatibility of the constraints caused by noise in both direct and Fourier space leads to residual phase fluctuations. This problem is addressed by supplementing the algorithm with an averaging method. The effect of averaging may be interpreted in terms of an effective modulation transfer function, as used in optics, to quantify the resolution. The reconstruction details are prefaced with simulations of wave propagation through a model yeast cell. These show that the yeast cell is a strong-phase-contrast object for the conditions in the experiment.« less

Simultaneous travel time tomography for updating both velocity and reflector geometry in triangular/tetrahedral cell model

NASA Astrophysics Data System (ADS)

Bai, Chao-ying; He, Lei-yu; Li, Xing-wang; Sun, Jia-yu

2018-05-01

To conduct forward and simultaneous inversion in a complex geological model, including an irregular topography (or irregular reflector or velocity anomaly), we in this paper combined our previous multiphase arrival tracking method (referred as triangular shortest-path method, TSPM) in triangular (2D) or tetrahedral (3D) cell model and a linearized inversion solver (referred to as damped minimum norms and constrained least squares problem solved using the conjugate gradient method, DMNCLS-CG) to formulate a simultaneous travel time inversion method for updating both velocity and reflector geometry by using multiphase arrival times. In the triangular/tetrahedral cells, we deduced the partial derivative of velocity variation with respective to the depth change of reflector. The numerical simulation results show that the computational accuracy can be tuned to a high precision in forward modeling and the irregular velocity anomaly and reflector geometry can be accurately captured in the simultaneous inversion, because the triangular/tetrahedral cell can be easily used to stitch the irregular topography or subsurface interface.

Simultaneous travel time tomography for updating both velocity and reflector geometry in triangular/tetrahedral cell model

NASA Astrophysics Data System (ADS)

Bai, Chao-ying; He, Lei-yu; Li, Xing-wang; Sun, Jia-yu

2017-12-01

To conduct forward and simultaneous inversion in a complex geological model, including an irregular topography (or irregular reflector or velocity anomaly), we in this paper combined our previous multiphase arrival tracking method (referred as triangular shortest-path method, TSPM) in triangular (2D) or tetrahedral (3D) cell model and a linearized inversion solver (referred to as damped minimum norms and constrained least squares problem solved using the conjugate gradient method, DMNCLS-CG) to formulate a simultaneous travel time inversion method for updating both velocity and reflector geometry by using multiphase arrival times. In the triangular/tetrahedral cells, we deduced the partial derivative of velocity variation with respective to the depth change of reflector. The numerical simulation results show that the computational accuracy can be tuned to a high precision in forward modeling and the irregular velocity anomaly and reflector geometry can be accurately captured in the simultaneous inversion, because the triangular/tetrahedral cell can be easily used to stitch the irregular topography or subsurface interface.

Modelling carotid artery adaptations to dynamic alterations in pressure and flow over the cardiac cycle

PubMed Central

Cardamone, L.; Valentín, A.; Eberth, J. F.; Humphrey, J. D.

2010-01-01

Motivated by recent clinical and laboratory findings of important effects of pulsatile pressure and flow on arterial adaptations, we employ and extend an established constrained mixture framework of growth (change in mass) and remodelling (change in structure) to include such dynamical effects. New descriptors of cell and tissue behavior (constitutive relations) are postulated and refined based on new experimental data from a transverse aortic arch banding model in the mouse that increases pulsatile pressure and flow in one carotid artery. In particular, it is shown that there was a need to refine constitutive relations for the active stress generated by smooth muscle, to include both stress- and stress rate-mediated control of the turnover of cells and matrix and to account for a cyclic stress-mediated loss of elastic fibre integrity and decrease in collagen stiffness in order to capture the reported evolution, over 8 weeks, of luminal radius, wall thickness, axial force and in vivo axial stretch of the hypertensive mouse carotid artery. We submit, therefore, that complex aspects of adaptation by elastic arteries can be predicted by constrained mixture models wherein individual constituents are produced or removed at individual rates and to individual extents depending on changes in both stress and stress rate from normal values. PMID:20484365

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Noise effect in metabolic networks

NASA Astrophysics Data System (ADS)

Li, Zheng-Yan; Xie, Zheng-Wei; Chen, Tong; Ouyang, Qi

2009-12-01

Constraint-based models such as flux balance analysis (FBA) are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term 'noise', and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.

CD8+ T-cell immunosurveillance constrains lymphoid pre-metastatic myeloid cell accumulation

PubMed Central

Li, Wenzhao; Deng, Jiehui; Herrmann, Andreas; Priceman, Saul J.; Liang, Wei; Shen, Shudan; Pal, Sumanta K.; Hoon, Dave S.B.; Yu, Hua

2014-01-01

Increasing evidence suggests that pre-metastatic niches, consisting mainly of myeloid cells, provide microenvironment critical for cancer cell recruitment and survival to facilitate metastasis. While CD8+ T cells exert immunosurveillance in primary human tumors, whether they can exert similar effects on myeloid cells in the pre-metastatic environment is unknown. Here, we show that CD8+ T cells are capable of constraining pre-metastatic myeloid cell accumulation by inducing myeloid cell apoptosis in C57BL/6 mice. Antigen-specific CD8+ T-cell cytotoxicity against myeloid cells in pre-metastatic lymph nodes is compromised by Stat3. We demonstrate here that Stat3 ablation in myeloid cells leads to CD8+ T-cell activation and increased levels of IFN-γ and granzyme B in the pre-metastatic environment. Furthermore, Stat3 negatively regulates soluble antigen cross-presentation by myeloid cells to CD8+ T cells in the pre-metastatic niche. Importantly, in tumor-free lymph nodes of melanoma patients, infiltration of activated CD8+ T cells inversely correlates with STAT3 activity, which is associated with a decrease in number of myeloid cells. Our study suggested a novel role for CD8+ T cells in constraining myeloid cell activity through direct killing in the pre-metastatic environment, and the therapeutic potential by targeting Stat3 in myeloid cells to improve CD8+ T-cell immunosurveillance against metastasis. PMID:25310972

Reflected stochastic differential equation models for constrained animal movement

USGS Publications Warehouse

Hanks, Ephraim M.; Johnson, Devin S.; Hooten, Mevin B.

2017-01-01

Movement for many animal species is constrained in space by barriers such as rivers, shorelines, or impassable cliffs. We develop an approach for modeling animal movement constrained in space by considering a class of constrained stochastic processes, reflected stochastic differential equations. Our approach generalizes existing methods for modeling unconstrained animal movement. We present methods for simulation and inference based on augmenting the constrained movement path with a latent unconstrained path and illustrate this augmentation with a simulation example and an analysis of telemetry data from a Steller sea lion (Eumatopias jubatus) in southeast Alaska.

Comparisons of a Constrained Least Squares Model versus Human-in-the-Loop for Spectral Unmixing to Determine Material Type of GEO Debris

NASA Technical Reports Server (NTRS)

Abercromby, Kira J.; Rapp, Jason; Bedard, Donald; Seitzer, Patrick; Cardona, Tommaso; Cowardin, Heather; Barker, Ed; Lederer, Susan

2013-01-01

Spectral reflectance data through the visible regime was collected at Las Campanas Observatory in Chile using an imaging spectrograph on one of the twin 6.5-m Magellan telescopes. The data were obtained on 1-2 May 2012 on the 'Landon Clay' telescope with the LDSS3 (Low Dispersion Survey Spectrograph 3). Five pieces of Geosynchronous Orbit (GEO) or near-GEO debris were identified and observed with an exposure time of 30 seconds on average. In addition, laboratory spectral reflectance data was collected using an Analytical Spectral Device (ASD) field spectrometer at California Polytechnic State University (Cal Poly) in San Luis Obispo on several typical common spacecraft materials including solar cells, circuit boards, various Kapton materials used for multi-layer insulation, and various paints. The remotely collected data and the laboratory-acquired data were then incorporated in a newly developed model that uses a constrained least squares method to unmix the spectrum in specific material components. The results of this model are compared to the previous method of a human-in-the-loop (considered here the traditional method) that identifies possible material components by varying the materials and percentages until a spectral match is obtained. The traditional model was found to match the remotely collected spectral data after it had been divided by the continuum to remove the space weathering effects, or a reddening of the materials. The constrained least-squares model also used the de-reddened spectra as inputs and the results were consistent with those obtained through the traditional method. For comparison, a first-order examination of including reddening effects into the constrained least-squares model will be explored and comparisons to the remotely collected data will be examined. The identification of each object s suspected material component will be discussed herein.

Comparisons of a Constrained Least Squares Model Versus Human-in-the-Loop for Spectral Unmixing to Determine Material Type of GEO Debris

NASA Technical Reports Server (NTRS)

Rapp, Jason; Abercromby, Kira J.; Bedard, Donald; Seitzer, Patrick; Cardona, Tommaso; Cowardin, Heather; Barker, Ed; Lederer, Susan

2012-01-01

Spectral reflectance data through the visible regime was collected at Las Campanas Observatory in Chile using an imaging spectrograph on one of the twin 6.5-m Magellan telescopes. The data were obtained on 1-2 May 2012 on the 'Landon Clay' telescope with the LDSS3 (Low Dispersion Survey Spectrograph 3). Five pieces of Geosynchronous Orbit (GEO) or near-GEO debris were identified and observed with an exposure time of 30 seconds on average. In addition, laboratory spectral reflectance data was collected using an Analytical Spectral Device (ASD) field spectrometer at California Polytechnic State University in San Luis Obispo on several typical common spacecraft materials including solar cells, circuit boards, various Kapton materials used for multi-layer insulation, and various paints. The remotely collected data and the laboratory-acquired data were then incorporated in a newly developed model that uses a constrained least squares method to unmix the spectrum in specific material components. The results of this model are compared to the previous method of a human-in-the-loop (considered here the traditional method) that identifies possible material components by varying the materials and percentages until a spectral match is obtained. The traditional model was found to match the remotely collected spectral data after it had been divided by the continuum to remove the space weathering effects, or a "reddening" of the materials. The constrained least-squares model also used the de-reddened spectra as inputs and the results were consistent with those obtained through the traditional method. For comparison, a first-order examination of including reddening effects into the constrained least-squares model will be explored and comparisons to the remotely collected data will be examined. The identification of each object's suspected material component will be discussed herein.

T-COMP—A suite of programs for extracting transmissivity from MODFLOW models

USGS Publications Warehouse

Halford, Keith J.

2016-02-12

Simulated transmissivities are constrained poorly by assigning permissible ranges of hydraulic conductivities from aquifer-test results to hydrogeologic units in groundwater-flow models. These wide ranges are derived from interpretations of many aquifer tests that are categorized by hydrogeologic unit. Uncertainty is added where contributing thicknesses differ between field estimates and numerical models. Wide ranges of hydraulic conductivities and discordant thicknesses result in simulated transmissivities that frequently are much greater than aquifer-test results. Multiple orders of magnitude differences frequently occur between simulated and observed transmissivities where observed transmissivities are less than 1,000 feet squared per day.Transmissivity observations from individual aquifer tests can constrain model calibration as head and flow observations do. This approach is superior to diluting aquifer-test results into generalized ranges of hydraulic conductivities. Observed and simulated transmissivities can be compared directly with T-COMP, a suite of three FORTRAN programs. Transmissivity observations require that simulated hydraulic conductivities and thicknesses in the volume investigated by an aquifer test be extracted and integrated into a simulated transmissivity. Transmissivities of MODFLOW model cells are sampled within the volume affected by an aquifer test as defined by a well-specific, radial-flow model of each aquifer test. Sampled transmissivities of model cells are averaged within a layer and summed across layers. Accuracy of the approach was tested with hypothetical, multiple-aquifer models where specified transmissivities ranged between 250 and 20,000 feet squared per day. More than 90 percent of simulated transmissivities were within a factor of 2 of specified transmissivities.

Directional control of lamellipodia extension by constraining cell shape and orienting cell tractional forces

NASA Technical Reports Server (NTRS)

Parker, Kevin Kit; Brock, Amy Lepre; Brangwynne, Cliff; Mannix, Robert J.; Wang, Ning; Ostuni, Emanuele; Geisse, Nicholas A.; Adams, Josephine C.; Whitesides, George M.; Ingber, Donald E.

2002-01-01

Directed cell migration is critical for tissue morphogenesis and wound healing, but the mechanism of directional control is poorly understood. Here we show that the direction in which cells extend their leading edge can be controlled by constraining cell shape using micrometer-sized extracellular matrix (ECM) islands. When cultured on square ECM islands in the presence of motility factors, cells preferentially extended lamellipodia, filopodia, and microspikes from their corners. Square cells reoriented their stress fibers and focal adhesions so that tractional forces were concentrated in these corner regions. When cell tension was dissipated, lamellipodia extension ceased. Mechanical interactions between cells and ECM that modulate cytoskeletal tension may therefore play a key role in the control of directional cell motility.

Prioritizing CD4 Count Monitoring in Response to ART in Resource-Constrained Settings: A Retrospective Application of Prediction-Based Classification

PubMed Central

Liu, Yan; Li, Xiaohong; Johnson, Margaret; Smith, Collette; Kamarulzaman, Adeeba bte; Montaner, Julio; Mounzer, Karam; Saag, Michael; Cahn, Pedro; Cesar, Carina; Krolewiecki, Alejandro; Sanne, Ian; Montaner, Luis J.

2012-01-01

Background Global programs of anti-HIV treatment depend on sustained laboratory capacity to assess treatment initiation thresholds and treatment response over time. Currently, there is no valid alternative to CD4 count testing for monitoring immunologic responses to treatment, but laboratory cost and capacity limit access to CD4 testing in resource-constrained settings. Thus, methods to prioritize patients for CD4 count testing could improve treatment monitoring by optimizing resource allocation. Methods and Findings Using a prospective cohort of HIV-infected patients (n = 1,956) monitored upon antiretroviral therapy initiation in seven clinical sites with distinct geographical and socio-economic settings, we retrospectively apply a novel prediction-based classification (PBC) modeling method. The model uses repeatedly measured biomarkers (white blood cell count and lymphocyte percent) to predict CD4+ T cell outcome through first-stage modeling and subsequent classification based on clinically relevant thresholds (CD4+ T cell count of 200 or 350 cells/µl). The algorithm correctly classified 90% (cross-validation estimate = 91.5%, standard deviation [SD] = 4.5%) of CD4 count measurements <200 cells/µl in the first year of follow-up; if laboratory testing is applied only to patients predicted to be below the 200-cells/µl threshold, we estimate a potential savings of 54.3% (SD = 4.2%) in CD4 testing capacity. A capacity savings of 34% (SD = 3.9%) is predicted using a CD4 threshold of 350 cells/µl. Similar results were obtained over the 3 y of follow-up available (n = 619). Limitations include a need for future economic healthcare outcome analysis, a need for assessment of extensibility beyond the 3-y observation time, and the need to assign a false positive threshold. Conclusions Our results support the use of PBC modeling as a triage point at the laboratory, lessening the need for laboratory-based CD4+ T cell count testing; implementation of this tool could help optimize the use of laboratory resources, directing CD4 testing towards higher-risk patients. However, further prospective studies and economic analyses are needed to demonstrate that the PBC model can be effectively applied in clinical settings. Please see later in the article for the Editors' Summary PMID:22529752

Modeling a space-variant cortical representation for apparent motion.

PubMed

Wurbs, Jeremy; Mingolla, Ennio; Yazdanbakhsh, Arash

2013-08-06

Receptive field sizes of neurons in early primate visual areas increase with eccentricity, as does temporal processing speed. The fovea is evidently specialized for slow, fine movements while the periphery is suited for fast, coarse movements. In either the fovea or periphery discrete flashes can produce motion percepts. Grossberg and Rudd (1989) used traveling Gaussian activity profiles to model long-range apparent motion percepts. We propose a neural model constrained by physiological data to explain how signals from retinal ganglion cells to V1 affect the perception of motion as a function of eccentricity. Our model incorporates cortical magnification, receptive field overlap and scatter, and spatial and temporal response characteristics of retinal ganglion cells for cortical processing of motion. Consistent with the finding of Baker and Braddick (1985), in our model the maximum flash distance that is perceived as an apparent motion (Dmax) increases linearly as a function of eccentricity. Baker and Braddick (1985) made qualitative predictions about the functional significance of both stimulus and visual system parameters that constrain motion perception, such as an increase in the range of detectable motions as a function of eccentricity and the likely role of higher visual processes in determining Dmax. We generate corresponding quantitative predictions for those functional dependencies for individual aspects of motion processing. Simulation results indicate that the early visual pathway can explain the qualitative linear increase of Dmax data without reliance on extrastriate areas, but that those higher visual areas may serve as a modulatory influence on the exact Dmax increase.

Constrained optimization via simulation models for new product innovation

NASA Astrophysics Data System (ADS)

Pujowidianto, Nugroho A.

2017-11-01

We consider the problem of constrained optimization where the decision makers aim to optimize the primary performance measure while constraining the secondary performance measures. This paper provides a brief overview of stochastically constrained optimization via discrete event simulation. Most review papers tend to be methodology-based. This review attempts to be problem-based as decision makers may have already decided on the problem formulation. We consider constrained optimization models as there are usually constraints on secondary performance measures as trade-off in new product development. It starts by laying out different possible methods and the reasons using constrained optimization via simulation models. It is then followed by the review of different simulation optimization approach to address constrained optimization depending on the number of decision variables, the type of constraints, and the risk preferences of the decision makers in handling uncertainties.

Cholangiocytes derived from human induced pluripotent stem cells for disease modeling and drug validation.

PubMed

Sampaziotis, Fotios; de Brito, Miguel Cardoso; Madrigal, Pedro; Bertero, Alessandro; Saeb-Parsy, Kourosh; Soares, Filipa A C; Schrumpf, Elisabeth; Melum, Espen; Karlsen, Tom H; Bradley, J Andrew; Gelson, William Th; Davies, Susan; Baker, Alastair; Kaser, Arthur; Alexander, Graeme J; Hannan, Nicholas R F; Vallier, Ludovic

2015-08-01

The study of biliary disease has been constrained by a lack of primary human cholangiocytes. Here we present an efficient, serum-free protocol for directed differentiation of human induced pluripotent stem cells into cholangiocyte-like cells (CLCs). CLCs show functional characteristics of cholangiocytes, including bile acids transfer, alkaline phosphatase activity, γ-glutamyl-transpeptidase activity and physiological responses to secretin, somatostatin and vascular endothelial growth factor. We use CLCs to model in vitro key features of Alagille syndrome, polycystic liver disease and cystic fibrosis (CF)-associated cholangiopathy. Furthermore, we use CLCs generated from healthy individuals and patients with polycystic liver disease to reproduce the effects of the drugs verapamil and octreotide, and we show that the experimental CF drug VX809 rescues the disease phenotype of CF cholangiopathy in vitro. Our differentiation protocol will facilitate the study of biological mechanisms controlling biliary development, as well as disease modeling and drug screening.

Upregulation of CYP 450s expression of immortalized hepatocyte-like cells derived from mesenchymal stem cells by enzyme inducers

PubMed Central

2011-01-01

Background The strenuous procurement of cultured human hepatocytes and their short lives have constrained the cell culture model of cytochrome P450 (CYP450) induction, xenobiotic biotransformation, and hepatotoxicity. The development of continuous non-tumorous cell line steadily containing hepatocyte phenotypes would substitute the primary hepatocytes for these studies. Results The hepatocyte-like cells have been developed from hTERT plus Bmi-1-immortalized human mesenchymal stem cells to substitute the primary hepatocytes. The hepatocyte-like cells had polygonal morphology and steadily produced albumin, glycogen, urea and UGT1A1 beyond 6 months while maintaining proliferative capacity. Although these hepatocyte-like cells had low basal expression of CYP450 isotypes, their expressions could be extensively up regulated to 80 folds upon the exposure to enzyme inducers. Their inducibility outperformed the classical HepG2 cells. Conclusion The hepatocyte-like cells contained the markers of hepatocytes including CYP450 isotypes. The high inducibility of CYP450 transcripts could serve as a sensitive model for profiling xenobiotic-induced expression of CYP450. PMID:21961524

Perspectives for computational modeling of cell replacement for neurological disorders

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aimone, James B.; Weick, Jason P.

In mathematical modeling of anatomically-constrained neural networks we provide significant insights regarding the response of networks to neurological disorders or injury. Furthermore, a logical extension of these models is to incorporate treatment regimens to investigate network responses to intervention. The addition of nascent neurons from stem cell precursors into damaged or diseased tissue has been used as a successful therapeutic tool in recent decades. Interestingly, models have been developed to examine the incorporation of new neurons into intact adult structures, particularly the dentate granule neurons of the hippocampus. These studies suggest that the unique properties of maturing neurons, can impactmore » circuit behavior in unanticipated ways. In this perspective, we review the current status of models used to examine damaged CNS structures with particular focus on cortical damage due to stroke. Secondly, we suggest that computational modeling of cell replacement therapies can be made feasible by implementing approaches taken by current models of adult neurogenesis. The development of these models is critical for generating hypotheses regarding transplant therapies and improving outcomes by tailoring transplants to desired effects.« less

Perspectives for computational modeling of cell replacement for neurological disorders

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aimone, James B.; Weick, Jason P.

Mathematical modeling of anatomically-constrained neural networks has provided significant insights regarding the response of networks to neurological disorders or injury. A logical extension of these models is to incorporate treatment regimens to investigate network responses to intervention. The addition of nascent neurons from stem cell precursors into damaged or diseased tissue has been used as a successful therapeutic tool in recent decades. Interestingly, models have been developed to examine the incorporation of new neurons into intact adult structures, particularly the dentate granule neurons of the hippocampus. These studies suggest that the unique properties of maturing neurons, can impact circuit behaviormore » in unanticipated ways. In this perspective, we review the current status of models used to examine damaged CNS structures with particular focus on cortical damage due to stroke. Secondly, we suggest that computational modeling of cell replacement therapies can be made feasible by implementing approaches taken by current models of adult neurogenesis. The development of these models is critical for generating hypotheses regarding transplant therapies and improving outcomes by tailoring transplants to desired effects.« less

Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble

PubMed Central

Jolivet, Renaud; Coggan, Jay S.; Allaman, Igor; Magistretti, Pierre J.

2015-01-01

Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain’s metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging. PMID:25719367

Multi-timescale modeling of activity-dependent metabolic coupling in the neuron-glia-vasculature ensemble.

PubMed

Jolivet, Renaud; Coggan, Jay S; Allaman, Igor; Magistretti, Pierre J

2015-02-01

Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain's metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging.

(R-X-R)4 -Motif Peptides Containing Conformationally Constrained Cyclohexane-Derived Spacers: Effect on Cellular Uptake.

PubMed

Bhosle, Govind S; Fernandes, Moneesha

2017-11-08

Arginine-rich peptides having the (R-X-R) n motif are among the most effective cell-penetrating peptides (CPPs). Herein we report a several-fold increase in the efficacy of such CPPs if the linear flexible spacer (-X-) in the (R-X-R) motif is replaced by constrained cyclic 1,4-substituted-cyclohexane-derived spacers. Internalization of these oligomers in mammalian cell lines was found to be an energy-dependent process. Incorporation of these constrained, non-proteinogenic amino acid spacers in the CPPs is shown to enhance their proteolytic stability. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Training Signaling Pathway Maps to Biochemical Data with Constrained Fuzzy Logic: Quantitative Analysis of Liver Cell Responses to Inflammatory Stimuli

PubMed Central

Morris, Melody K.; Saez-Rodriguez, Julio; Clarke, David C.; Sorger, Peter K.; Lauffenburger, Douglas A.

2011-01-01

Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL), converts a prior knowledge network (obtained from literature or interactome databases) into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a) generating experimentally testable biological hypotheses concerning pathway crosstalk, (b) establishing capability for quantitative prediction of protein activity, and (c) prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone. PMID:21408212

Cell Surface Mechanochemistry and the Determinants of Bleb Formation, Healing, and Travel Velocity

PubMed Central

Manakova, Kathryn; Yan, Huaming; Lowengrub, John; Allard, Jun

2016-01-01

Blebs are pressure-driven cell protrusions implicated in cellular functions such as cell division, apoptosis, and cell motility, including motility of protease-inhibited cancer cells. Because of their mechanical nature, blebs inform us about general cell-surface mechanics, including membrane dynamics, pressure propagation throughout the cytoplasm, and the architecture and dynamics of the actin cortex. Mathematical models including detailed fluid dynamics have previously been used to understand bleb expansion. Here, we develop mathematical models in two and three dimensions on longer timescales that recapitulate the full bleb life cycle, including both expansion and healing by cortex reformation, in terms of experimentally accessible biophysical parameters such as myosin contractility, osmotic pressure, and turnover of actin and ezrin. The model provides conditions under which blebbing occurs, and naturally gives rise to traveling blebs. The model predicts conditions under which blebs travel or remain stationary, as well as the bleb traveling velocity, a quantity that has remained elusive in previous models. As previous studies have used blebs as reporters of membrane tension and pressure dynamics within the cell, we have used our system to investigate various pressure equilibration models and dynamic, nonuniform membrane tension to account for the shape of a traveling bleb. We also find that traveling blebs tend to expand in all directions unless otherwise constrained. One possible constraint could be provided by spatial heterogeneity in, for example, adhesion density. PMID:27074688

Constrained reduced-order models based on proper orthogonal decomposition

DOE PAGES

Reddy, Sohail R.; Freno, Brian Andrew; Cizmas, Paul G. A.; ...

2017-04-09

A novel approach is presented to constrain reduced-order models (ROM) based on proper orthogonal decomposition (POD). The Karush–Kuhn–Tucker (KKT) conditions were applied to the traditional reduced-order model to constrain the solution to user-defined bounds. The constrained reduced-order model (C-ROM) was applied and validated against the analytical solution to the first-order wave equation. C-ROM was also applied to the analysis of fluidized beds. Lastly, it was shown that the ROM and C-ROM produced accurate results and that C-ROM was less sensitive to error propagation through time than the ROM.

An Anatomically Constrained Model for Path Integration in the Bee Brain.

PubMed

Stone, Thomas; Webb, Barbara; Adden, Andrea; Weddig, Nicolai Ben; Honkanen, Anna; Templin, Rachel; Wcislo, William; Scimeca, Luca; Warrant, Eric; Heinze, Stanley

2017-10-23

Path integration is a widespread navigational strategy in which directional changes and distance covered are continuously integrated on an outward journey, enabling a straight-line return to home. Bees use vision for this task-a celestial-cue-based visual compass and an optic-flow-based visual odometer-but the underlying neural integration mechanisms are unknown. Using intracellular electrophysiology, we show that polarized-light-based compass neurons and optic-flow-based speed-encoding neurons converge in the central complex of the bee brain, and through block-face electron microscopy, we identify potential integrator cells. Based on plausible output targets for these cells, we propose a complete circuit for path integration and steering in the central complex, with anatomically identified neurons suggested for each processing step. The resulting model circuit is thus fully constrained biologically and provides a functional interpretation for many previously unexplained architectural features of the central complex. Moreover, we show that the receptive fields of the newly discovered speed neurons can support path integration for the holonomic motion (i.e., a ground velocity that is not precisely aligned with body orientation) typical of bee flight, a feature not captured in any previously proposed model of path integration. In a broader context, the model circuit presented provides a general mechanism for producing steering signals by comparing current and desired headings-suggesting a more basic function for central complex connectivity, from which path integration may have evolved. Copyright © 2017 Elsevier Ltd. All rights reserved.

Digital Image Restoration Under a Regression Model - The Unconstrained, Linear Equality and Inequality Constrained Approaches

DTIC Science & Technology

1974-01-01

REGRESSION MODEL - THE UNCONSTRAINED, LINEAR EQUALITY AND INEQUALITY CONSTRAINED APPROACHES January 1974 Nelson Delfino d’Avila Mascarenha;? Image...Report 520 DIGITAL IMAGE RESTORATION UNDER A REGRESSION MODEL THE UNCONSTRAINED, LINEAR EQUALITY AND INEQUALITY CONSTRAINED APPROACHES January...a two- dimensional form adequately describes the linear model . A dis- cretization is performed by using quadrature methods. By trans

A phenomenological force model of Li-ion battery packs for enhanced performance and health management

NASA Astrophysics Data System (ADS)

Oh, Ki-Yong; Epureanu, Bogdan I.

2017-10-01

A 1-D phenomenological force model of a Li-ion battery pack is proposed to enhance the control performance of Li-ion battery cells in pack conditions for efficient performance and health management. The force model accounts for multiple swelling sources under the operational environment of electric vehicles to predict swelling-induced forces in pack conditions, i.e. mechanically constrained. The proposed force model not only incorporates structural nonlinearities due to Li-ion intercalation swelling, but also separates the overall range of states of charge into three ranges to account for phase transitions. Moreover, an approach to study cell-to-cell variations in pack conditions is proposed with serial and parallel combinations of linear and nonlinear stiffness, which account for battery cells and other components in the battery pack. The model is shown not only to accurately estimate the reaction force caused by swelling as a function of the state of charge, battery temperature and environmental temperature, but also to account for cell-to-cell variations due to temperature variations, SOC differences, and local degradation in a wide range of operational conditions of electric vehicles. Considering that the force model of Li-ion battery packs can account for many possible situations in actual operation, the proposed approach and model offer potential utility for the enhancement of current battery management systems and power management strategies.

Does Aspartic Acid Racemization Constrain the Depth Limit of the Subsurface Biosphere?

NASA Technical Reports Server (NTRS)

Onstott, T C.; Magnabosco, C.; Aubrey, A. D.; Burton, A. S.; Dworkin, J. P.; Elsila, J. E.; Grunsfeld, S.; Cao, B. H.; Hein, J. E.; Glavin, D. P.;

Does aspartic acid racemization constrain the depth limit of the subsurface biosphere?

PubMed

Onstott, T C; Magnabosco, C; Aubrey, A D; Burton, A S; Dworkin, J P; Elsila, J E; Grunsfeld, S; Cao, B H; Hein, J E; Glavin, D P; Kieft, T L; Silver, B J; Phelps, T J; van Heerden, E; Opperman, D J; Bada, J L

2014-01-01

Previous studies of the subsurface biosphere have deduced average cellular doubling times of hundreds to thousands of years based upon geochemical models. We have directly constrained the in situ average cellular protein turnover or doubling times for metabolically active micro-organisms based on cellular amino acid abundances, D/L values of cellular aspartic acid, and the in vivo aspartic acid racemization rate. Application of this method to planktonic microbial communities collected from deep fractures in South Africa yielded maximum cellular amino acid turnover times of ~89 years for 1 km depth and 27 °C and 1-2 years for 3 km depth and 54 °C. The latter turnover times are much shorter than previously estimated cellular turnover times based upon geochemical arguments. The aspartic acid racemization rate at higher temperatures yields cellular protein doubling times that are consistent with the survival times of hyperthermophilic strains and predicts that at temperatures of 85 °C, cells must replace proteins every couple of days to maintain enzymatic activity. Such a high maintenance requirement may be the principal limit on the abundance of living micro-organisms in the deep, hot subsurface biosphere, as well as a potential limit on their activity. The measurement of the D/L of aspartic acid in biological samples is a potentially powerful tool for deep, fractured continental and oceanic crustal settings where geochemical models of carbon turnover times are poorly constrained. Experimental observations on the racemization rates of aspartic acid in living thermophiles and hyperthermophiles could test this hypothesis. The development of corrections for cell wall peptides and spores will be required, however, to improve the accuracy of these estimates for environmental samples. © 2013 John Wiley & Sons Ltd.

Statistical Properties of Cell Topology and Geometry in a Tissue-Growth Model

NASA Astrophysics Data System (ADS)

Sahlin, Patrik; Hamant, Olivier; Jönsson, Henrik

Statistical properties of cell topologies in two-dimensional tissues have recently been suggested to be a consequence of cell divisions. Different rules for the positioning of new walls in plants have been proposed, where e.g. Errara’s rule state that new walls are added with the shortest possible path dividing the mother cell’s volume into two equal parts. Here, we show that for an isotropically growing tissue Errara’s rule results in the correct distributions of number of cell neighbors as well as cellular geometries, in contrast to a random division rule. Further we show that wall mechanics constrain the isotropic growth such that the resulting cell shape distributions more closely agree with experimental data extracted from the shoot apex of Arabidopsis thaliana.

Functionality, Complexity, and Approaches to Assessment of Resilience Under Constrained Energy and Information

DTIC Science & Technology

2015-03-26

albeit powerful , method available for exploring CAS. As discussed above, there are many useful mathematical tools appropriate for CAS modeling. Agent-based...cells, tele- phone calls, and sexual contacts approach power -law distributions. [48] Networks in general are robust against random failures, but...targeted failures can have powerful effects – provided the targeter has a good understanding of the network structure. Some argue (convincingly) that all

Flexible C : N ratio enhances metabolism of large phytoplankton when resource supply is intermittent

NASA Astrophysics Data System (ADS)

Talmy, D.; Blackford, J.; Hardman-Mountford, N. J.; Polimene, L.; Follows, M. J.; Geider, R. J.

2014-04-01

Phytoplankton cell size influences particle sinking rate, food web interactions and biogeographical distributions. We present a model in which the uptake, storage and assimilation of nitrogen and carbon are explicitly resolved in different sized phytoplankton cells. In the model, metabolism and cellular C : N ratio are influenced by accumulation of carbon polymers such as carbohydrate and lipid, which is greatest when cells are nutrient starved, or exposed to high light. Allometric relations and empirical datasets are used to constrain the range of possible C : N, and indicate larger cells can accumulate significantly more carbon storage compounds than smaller cells. When forced with extended periods of darkness combined with brief exposure to saturating irradiance, the model predicts organisms large enough to accumulate significant carbon reserves may on average synthesize protein and other functional apparatus up to five times faster than smaller organisms. The advantage of storage in terms of average daily protein synthesis rate is greatest when modeled organisms were previously nutrient starved, and carbon storage reservoirs saturated. Small organisms may therefore be at a disadvantage in terms of average daily growth rate in environments that involve prolonged periods of darkness and intermittent nutrient limitation. We suggest this mechanism is a significant constraint on phytoplankton C : N variability and cell size distribution in different oceanic regimes.

Modeling the Epithelial Morphogenesis of Germ Band Retraction in Three Dimensions

NASA Astrophysics Data System (ADS)

McCleery, W. Tyler; Veldhuis, Jim; Brodland, G. Wayne; Crews, Sarah M.; Hutson, M. Shane

2015-03-01

Embryogenesis of higher-order organisms is driven by an intricate coordination of cellular mechanics. Mechanical analysis of certain developmental events, e.g., dorsal closure in the fruit fly D. melanogaster, has been sufficiently described using two-dimensional models. Here, we present a three-dimensional modeling technique to investigate germ band retraction (GBR) - a whole-embryo, irreducibly 3D morphogenetic event. At the start of GBR, the epithelial tissue known as the germ band is initially wrapped around the posterior end of an ellipsoidal fly embryo. This tissue then retracts as an adjacent epithelial tissue, the amnioserosa, simultaneously contracts. We hypothesize that proper GBR requires maintenance of cell-cell connectivity in the amnioserosa, as well as both cell and tissue topology on the embryo's ellipsoidal surface. The exact interfacial tensions are less important. We test the dynamic interactions between these two tissues on a 3D ellipsoidal last. To speed simulation run times and focus on the relevant tissues, epithelial cells are defined as polygons constrained to lie on the surface of the ellipsoidal last. These cells have adjustable parameters such as edge tensions and cell pressures. Tissue movements are simulated by balancing these dynamic cell-level forces with viscous resistance and allowing cells to exchange neighbors. This modeling approach helps elucidate the multicellular stress fields in normal and aberrant development, providing deeper insight into the mechanical interdependence of developing tissues.

Symmetry structure in discrete models of biochemical systems: natural subsystems and the weak control hierarchy in a new model of computation driven by interactions.

PubMed

Nehaniv, Chrystopher L; Rhodes, John; Egri-Nagy, Attila; Dini, Paolo; Morris, Eric Rothstein; Horváth, Gábor; Karimi, Fariba; Schreckling, Daniel; Schilstra, Maria J

2015-07-28

Interaction computing is inspired by the observation that cell metabolic/regulatory systems construct order dynamically, through constrained interactions between their components and based on a wide range of possible inputs and environmental conditions. The goals of this work are to (i) identify and understand mathematically the natural subsystems and hierarchical relations in natural systems enabling this and (ii) use the resulting insights to define a new model of computation based on interactions that is useful for both biology and computation. The dynamical characteristics of the cellular pathways studied in systems biology relate, mathematically, to the computational characteristics of automata derived from them, and their internal symmetry structures to computational power. Finite discrete automata models of biological systems such as the lac operon, the Krebs cycle and p53-mdm2 genetic regulation constructed from systems biology models have canonically associated algebraic structures (their transformation semigroups). These contain permutation groups (local substructures exhibiting symmetry) that correspond to 'pools of reversibility'. These natural subsystems are related to one another in a hierarchical manner by the notion of 'weak control'. We present natural subsystems arising from several biological examples and their weak control hierarchies in detail. Finite simple non-Abelian groups are found in biological examples and can be harnessed to realize finitary universal computation. This allows ensembles of cells to achieve any desired finitary computational transformation, depending on external inputs, via suitably constrained interactions. Based on this, interaction machines that grow and change their structure recursively are introduced and applied, providing a natural model of computation driven by interactions.

Vibration control of multiferroic fibrous composite plates using active constrained layer damping

NASA Astrophysics Data System (ADS)

Kattimani, S. C.; Ray, M. C.

2018-06-01

Geometrically nonlinear vibration control of fiber reinforced magneto-electro-elastic or multiferroic fibrous composite plates using active constrained layer damping treatment has been investigated. The piezoelectric (BaTiO3) fibers are embedded in the magnetostrictive (CoFe2O4) matrix forming magneto-electro-elastic or multiferroic smart composite. A three-dimensional finite element model of such fiber reinforced magneto-electro-elastic plates integrated with the active constrained layer damping patches is developed. Influence of electro-elastic, magneto-elastic and electromagnetic coupled fields on the vibration has been studied. The Golla-Hughes-McTavish method in time domain is employed for modeling a constrained viscoelastic layer of the active constrained layer damping treatment. The von Kármán type nonlinear strain-displacement relations are incorporated for developing a three-dimensional finite element model. Effect of fiber volume fraction, fiber orientation and boundary conditions on the control of geometrically nonlinear vibration of the fiber reinforced magneto-electro-elastic plates is investigated. The performance of the active constrained layer damping treatment due to the variation of piezoelectric fiber orientation angle in the 1-3 Piezoelectric constraining layer of the active constrained layer damping treatment has also been emphasized.

A Model-Data Fusion Approach for Constraining Modeled GPP at Global Scales Using GOME2 SIF Data

NASA Astrophysics Data System (ADS)

MacBean, N.; Maignan, F.; Lewis, P.; Guanter, L.; Koehler, P.; Bacour, C.; Peylin, P.; Gomez-Dans, J.; Disney, M.; Chevallier, F.

2015-12-01

Predicting the fate of the ecosystem carbon, C, stocks and their sensitivity to climate change relies heavily on our ability to accurately model the gross carbon fluxes, i.e. photosynthesis and respiration. However, there are large differences in the Gross Primary Productivity (GPP) simulated by different land surface models (LSMs), not only in terms of mean value, but also in terms of phase and amplitude when compared to independent data-based estimates. This strongly limits our ability to provide accurate predictions of carbon-climate feedbacks. One possible source of this uncertainty is from inaccurate parameter values resulting from incomplete model calibration. Solar Induced Fluorescence (SIF) has been shown to have a linear relationship with GPP at the typical spatio-temporal scales used in LSMs (Guanter et al., 2011). New satellite-derived SIF datasets have the potential to constrain LSM parameters related to C uptake at global scales due to their coverage. Here we use SIF data derived from the GOME2 instrument (Köhler et al., 2014) to optimize parameters related to photosynthesis and leaf phenology of the ORCHIDEE LSM, as well as the linear relationship between SIF and GPP. We use a multi-site approach that combines many model grid cells covering a wide spatial distribution within the same optimization (e.g. Kuppel et al., 2014). The parameters are constrained per Plant Functional type as the linear relationship described above varies depending on vegetation structural properties. The relative skill of the optimization is compared to a case where only satellite-derived vegetation index data are used to constrain the model, and to a case where both data streams are used. We evaluate the results using an independent data-driven estimate derived from FLUXNET data (Jung et al., 2011) and with a new atmospheric tracer, Carbonyl sulphide (OCS) following the approach of Launois et al. (ACPD, in review). We show that the optimization reduces the strong positive bias of the ORCHIDEE model and increases the correlation compared to independent estimates. Differences in spatial patterns and gradients between simulated GPP and observed SIF remain largely unchanged however, suggesting that the underlying representation of vegetation type and/or structure and functioning in the model requires further investigation.

A Fluorescent Protein Scaffold for Presenting Structurally Constrained Peptides Provides an Effective Screening System to Identify High Affinity Target-Binding Peptides

PubMed Central

Kadonosono, Tetsuya; Yabe, Etsuri; Furuta, Tadaomi; Yamano, Akihiro; Tsubaki, Takuya; Sekine, Takuya; Kuchimaru, Takahiro; Sakurai, Minoru; Kizaka-Kondoh, Shinae

2014-01-01

Peptides that have high affinity for target molecules on the surface of cancer cells are crucial for the development of targeted cancer therapies. However, unstructured peptides often fail to bind their target molecules with high affinity. To efficiently identify high-affinity target-binding peptides, we have constructed a fluorescent protein scaffold, designated gFPS, in which structurally constrained peptides are integrated at residues K131–L137 of superfolder green fluorescent protein. Molecular dynamics simulation supported the suitability of this site for presentation of exogenous peptides with a constrained structure. gFPS can present 4 to 12 exogenous amino acids without a loss of fluorescence. When gFPSs presenting human epidermal growth factor receptor type 2 (HER2)-targeting peptides were added to the culture medium of HER2-expressing cells, we could easily identify the peptides with high HER2-affinity and -specificity based on gFPS fluorescence. In addition, gFPS could be expressed on the yeast cell surface and applied for a high-throughput screening. These results demonstrate that gFPS has the potential to serve as a powerful tool to improve screening of structurally constrained peptides that have a high target affinity, and suggest that it could expedite the one-step identification of clinically applicable cancer cell-binding peptides. PMID:25084350

Myosin-II controls cellular branching morphogenesis and migration in 3D by minimizing cell surface curvature

PubMed Central

Elliott, Hunter; Fischer, Robert A.; Myers, Kenneth A.; Desai, Ravi A.; Gao, Lin; Chen, Christopher S.; Adelstein, Robert; Waterman, Clare M.; Danuser, Gaudenz

2014-01-01

In many cases cell function is intimately linked to cell shape control. We utilized endothelial cell branching morphogenesis as a model to understand the role of myosin-II in shape control of invasive cells migrating in 3D collagen gels. We applied principles of differential geometry and mathematical morphology to 3D image sets to parameterize cell branch structure and local cell surface curvature. We find that Rho/ROCK-stimulated myosin-II contractility minimizes cell-scale branching by recognizing and minimizing local cell surface curvature. Utilizing micro-fabrication to constrain cell shape identifies a positive feedback mechanism in which low curvature stabilizes myosin-II cortical association, where it acts to maintain minimal curvature. The feedback between myosin-II regulation by and control of curvature drives cycles of localized cortical myosin-II assembly and disassembly. These cycles in turn mediate alternating phases of directionally biased branch initiation and retraction to guide 3D cell migration. PMID:25621949

Coupling Poisson rectangular pulse and multiplicative microcanonical random cascade models to generate sub-daily precipitation timeseries

NASA Astrophysics Data System (ADS)

Pohle, Ina; Niebisch, Michael; Müller, Hannes; Schümberg, Sabine; Zha, Tingting; Maurer, Thomas; Hinz, Christoph

2018-07-01

To simulate the impacts of within-storm rainfall variabilities on fast hydrological processes, long precipitation time series with high temporal resolution are required. Due to limited availability of observed data such time series are typically obtained from stochastic models. However, most existing rainfall models are limited in their ability to conserve rainfall event statistics which are relevant for hydrological processes. Poisson rectangular pulse models are widely applied to generate long time series of alternating precipitation events durations and mean intensities as well as interstorm period durations. Multiplicative microcanonical random cascade (MRC) models are used to disaggregate precipitation time series from coarse to fine temporal resolution. To overcome the inconsistencies between the temporal structure of the Poisson rectangular pulse model and the MRC model, we developed a new coupling approach by introducing two modifications to the MRC model. These modifications comprise (a) a modified cascade model ("constrained cascade") which preserves the event durations generated by the Poisson rectangular model by constraining the first and last interval of a precipitation event to contain precipitation and (b) continuous sigmoid functions of the multiplicative weights to consider the scale-dependency in the disaggregation of precipitation events of different durations. The constrained cascade model was evaluated in its ability to disaggregate observed precipitation events in comparison to existing MRC models. For that, we used a 20-year record of hourly precipitation at six stations across Germany. The constrained cascade model showed a pronounced better agreement with the observed data in terms of both the temporal pattern of the precipitation time series (e.g. the dry and wet spell durations and autocorrelations) and event characteristics (e.g. intra-event intermittency and intensity fluctuation within events). The constrained cascade model also slightly outperformed the other MRC models with respect to the intensity-frequency relationship. To assess the performance of the coupled Poisson rectangular pulse and constrained cascade model, precipitation events were stochastically generated by the Poisson rectangular pulse model and then disaggregated by the constrained cascade model. We found that the coupled model performs satisfactorily in terms of the temporal pattern of the precipitation time series, event characteristics and the intensity-frequency relationship.

One-Dimensional Fast Transient Simulator for Modeling Cadmium Sulfide/Cadmium Telluride Solar Cells

NASA Astrophysics Data System (ADS)

Guo, Da

Solar energy, including solar heating, solar architecture, solar thermal electricity and solar photovoltaics, is one of the primary alternative energy sources to fossil fuel. Being one of the most important techniques, significant research has been conducted in solar cell efficiency improvement. Simulation of various structures and materials of solar cells provides a deeper understanding of device operation and ways to improve their efficiency. Over the last two decades, polycrystalline thin-film Cadmium-Sulfide and Cadmium-Telluride (CdS/CdTe) solar cells fabricated on glass substrates have been considered as one of the most promising candidate in the photovoltaic technologies, for their similar efficiency and low costs when compared to traditional silicon-based solar cells. In this work a fast one dimensional time-dependent/steady-state drift-diffusion simulator, accelerated by adaptive non-uniform mesh and automatic time-step control, for modeling solar cells has been developed and has been used to simulate a CdS/CdTe solar cell. These models are used to reproduce transients of carrier transport in response to step-function signals of different bias and varied light intensity. The time-step control models are also used to help convergence in steady-state simulations where constrained material constants, such as carrier lifetimes in the order of nanosecond and carrier mobility in the order of 100 cm2/Vs, must be applied.

Triple point temperature of neon isotopes: Dependence on nitrogen impurity and sealed-cell model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pavese, F.; Steur, P. P. M.; Giraudi, D.

2013-09-11

This paper illustrates a study conducted at INRIM, to further check how some quantities influence the value of the triple point temperature of the neon high-purity isotopes {sup 20}Ne and {sup 22}Ne. The influence of nitrogen as a chemical impurity in neon is critical with regard to the present best total uncertainty achieved in the measurement of these triple points, but only one determination is available in the literature. Checks are reported, performed on two different samples of {sup 22}Ne known to contain a N{sub 2} amount of 157⋅10{sup −6}, using two different models of sealed cells. The model ofmore » the cell can, in principle, have some effects on the shape of the melting plateau or on the triple point temperature observed for the sample sealed in it. This can be due to cell thermal parameters, or because the INRIM cell element mod. c contains many copper wires closely packed, which can, in principle, constrain the interface and induce a premelting-like effect. The reported results on a cell mod. Bter show no evident effect from the cell model and provide a value for the effect of N{sub 2} in Ne liquidus point of 8.6(1.9) μK ppm N{sub 2}{sup −1}, only slightly different from the literature datum.« less

A Brain Unfixed: Unlimited Neurogenesis and Regeneration of the Adult Planarian Nervous System

PubMed Central

Brown, David D. R.; Pearson, Bret J.

2017-01-01

Powerful genetic tools in classical laboratory models have been fundamental to our understanding of how stem cells give rise to complex neural tissues during embryonic development. In contrast, adult neurogenesis in our model systems, if present, is typically constrained to one or a few zones of the adult brain to produce a limited subset of neurons leading to the dogma that the brain is primarily fixed post-development. The freshwater planarian (flatworm) is an invertebrate model system that challenges this dogma. The planarian possesses a brain containing several thousand neurons with very high rates of cell turnover (homeostasis), which can also be fully regenerated de novo from injury in just 7 days. Both homeostasis and regeneration depend on the activity of a large population of adult stem cells, called neoblasts, throughout the planarian body. Thus, much effort has been put forth to understand how the flatworm can continually give rise to the diversity of cell types found in the adult brain. Here we focus on work using single-cell genomics and functional analyses to unravel the cellular hierarchies from stem cell to neuron. In addition, we will review what is known about how planarians utilize developmental signaling to maintain proper tissue patterning, homeostasis, and cell-type diversity in their brains. Together, planarians are a powerful emerging model system to study the dynamics of adult neurogenesis and regeneration. PMID:28588444

The mathematics of tanning

PubMed Central

Thingnes, Josef; Øyehaug, Leiv; Hovig, Eivind; Omholt, Stig W

2009-01-01

Background The pigment melanin is produced by specialized cells, called melanocytes. In healthy skin, melanocytes are sparsely spread among the other cell types in the basal layer of the epidermis. Sun tanning results from an UV-induced increase in the release of melanin to neighbouring keratinocytes, the major cell type component of the epidermis as well as redistribution of melanin among these cells. Here we provide a mathematical conceptualization of our current knowledge of the tanning response, in terms of a dynamic model. The resolution level of the model is tuned to available data, and its primary focus is to describe the tanning response following UV exposure. Results The model appears capable of accounting for available experimental data on the tanning response in different skin and photo types. It predicts that the thickness of the epidermal layer and how far the melanocyte dendrites grow out in the epidermal layers after UV exposure influence the tanning response substantially. Conclusion Despite the paucity of experimental validation data the model is constrained enough to serve as a foundation for the establishment of a theoretical-experimental research programme aimed at elucidating the more fine-grained regulatory anatomy underlying the tanning response. PMID:19505344

Conformationally constrained peptides target the allosteric kinase dimer interface and inhibit EGFR activation.

PubMed

Fulton, Melody D; Hanold, Laura E; Ruan, Zheng; Patel, Sneha; Beedle, Aaron M; Kannan, Natarajan; Kennedy, Eileen J

2018-03-15

Although EGFR is a highly sought-after drug target, inhibitor resistance remains a challenge. As an alternative strategy for kinase inhibition, we sought to explore whether allosteric activation mechanisms could effectively be disrupted. The kinase domain of EGFR forms an atypical asymmetric dimer via head-to-tail interactions and serves as a requisite for kinase activation. The kinase dimer interface is primarily formed by the H-helix derived from one kinase monomer and the small lobe of the second monomer. We hypothesized that a peptide designed to resemble the binding surface of the H-helix may serve as an effective disruptor of EGFR dimerization and activation. A library of constrained peptides was designed to mimic the H-helix of the kinase domain and interface side chains were optimized using molecular modeling. Peptides were constrained using peptide "stapling" to structurally reinforce an alpha-helical conformation. Peptide stapling was demonstrated to notably enhance cell permeation of an H-helix derived peptide termed EHBI2. Using cell-based assays, EHBI2 was further shown to significantly reduce EGFR activity as measured by EGFR phosphorylation and phosphorylation of the downstream signaling substrate Akt. To our knowledge, this is the first H-helix-based compound targeting the asymmetric interface of the kinase domain that can successfully inhibit EGFR activation and signaling. This study presents a novel, alternative targeting site for allosteric inhibition of EGFR. Copyright © 2017 Elsevier Ltd. All rights reserved.

A predictive parameter estimation approach for the thermodynamically constrained averaging theory applied to diffusion in porous media

NASA Astrophysics Data System (ADS)

Valdes-Parada, F. J.; Ostvar, S.; Wood, B. D.; Miller, C. T.

2017-12-01

Modeling of hierarchical systems such as porous media can be performed by different approaches that bridge microscale physics to the macroscale. Among the several alternatives available in the literature, the thermodynamically constrained averaging theory (TCAT) has emerged as a robust modeling approach that provides macroscale models that are consistent across scales. For specific closure relation forms, TCAT models are expressed in terms of parameters that depend upon the physical system under study. These parameters are usually obtained from inverse modeling based upon either experimental data or direct numerical simulation at the pore scale. Other upscaling approaches, such as the method of volume averaging, involve an a priori scheme for parameter estimation for certain microscale and transport conditions. In this work, we show how such a predictive scheme can be implemented in TCAT by studying the simple problem of single-phase passive diffusion in rigid and homogeneous porous media. The components of the effective diffusivity tensor are predicted for several porous media by solving ancillary boundary-value problems in periodic unit cells. The results are validated through a comparison with data from direct numerical simulation. This extension of TCAT constitutes a useful advance for certain classes of problems amenable to this estimation approach.

Immune Tolerance Maintained by Cooperative Interactions between T Cells and Antigen Presenting Cells Shapes a Diverse TCR Repertoire

PubMed Central

Best, Katharine; Chain, Benny; Watkins, Chris

2015-01-01

The T cell population in an individual needs to avoid harmful activation by self peptides while maintaining the ability to respond to an unknown set of foreign peptides. This property is acquired by a combination of thymic and extra-thymic mechanisms. We extend current models for the development of self/non-self discrimination to consider the acquisition of self-tolerance as an emergent system level property of the overall T cell receptor repertoire. We propose that tolerance is established at the level of the antigen presenting cell/T cell cluster, which facilitates and integrates cooperative interactions between T cells of different specificities. The threshold for self-reactivity is therefore imposed at a population level, and not at the level of the individual T cell/antigen encounter. Mathematically, the model can be formulated as a linear programing optimization problem that can be implemented as a multiplicative update algorithm, which shows a rapid convergence to a stable state. The model constrains self-reactivity within a predefined threshold, but maintains repertoire diversity and cross reactivity which are key characteristics of human T cell immunity. We show further that the size of individual clones in the model repertoire becomes heterogeneous, and that new clones can establish themselves even when the repertoire has stabilized. Our study combines the salient features of the “danger” model of self/non-self discrimination with the concepts of quorum sensing, and extends repertoire generation models to encompass the establishment of tolerance. Furthermore, the dynamic and continuous repertoire reshaping, which underlies tolerance in this model, suggests opportunities for therapeutic intervention to achieve long-term tolerance following transplantation. PMID:26300880

nbCNV: a multi-constrained optimization model for discovering copy number variants in single-cell sequencing data.

PubMed

Zhang, Changsheng; Cai, Hongmin; Huang, Jingying; Song, Yan

2016-09-17

Variations in DNA copy number have an important contribution to the development of several diseases, including autism, schizophrenia and cancer. Single-cell sequencing technology allows the dissection of genomic heterogeneity at the single-cell level, thereby providing important evolutionary information about cancer cells. In contrast to traditional bulk sequencing, single-cell sequencing requires the amplification of the whole genome of a single cell to accumulate enough samples for sequencing. However, the amplification process inevitably introduces amplification bias, resulting in an over-dispersing portion of the sequencing data. Recent study has manifested that the over-dispersed portion of the single-cell sequencing data could be well modelled by negative binomial distributions. We developed a read-depth based method, nbCNV to detect the copy number variants (CNVs). The nbCNV method uses two constraints-sparsity and smoothness to fit the CNV patterns under the assumption that the read signals are negatively binomially distributed. The problem of CNV detection was formulated as a quadratic optimization problem, and was solved by an efficient numerical solution based on the classical alternating direction minimization method. Extensive experiments to compare nbCNV with existing benchmark models were conducted on both simulated data and empirical single-cell sequencing data. The results of those experiments demonstrate that nbCNV achieves superior performance and high robustness for the detection of CNVs in single-cell sequencing data.

Development of Cell-Permeable, Non-Helical Constrained Peptides to Target a Key Protein-Protein Interaction in Ovarian Cancer.

PubMed

Wiedmann, Mareike M; Tan, Yaw Sing; Wu, Yuteng; Aibara, Shintaro; Xu, Wenshu; Sore, Hannah F; Verma, Chandra S; Itzhaki, Laura; Stewart, Murray; Brenton, James D; Spring, David R

2017-01-09

There is a lack of current treatment options for ovarian clear cell carcinoma (CCC) and the cancer is often resistant to platinum-based chemotherapy. Hence there is an urgent need for novel therapeutics. The transcription factor hepatocyte nuclear factor 1β (HNF1β) is ubiquitously overexpressed in CCC and is seen as an attractive therapeutic target. This was validated through shRNA-mediated knockdown of the target protein, HNF1β, in five high- and low-HNF1β-expressing CCC lines. To inhibit the protein function, cell-permeable, non-helical constrained proteomimetics to target the HNF1β-importin α protein-protein interaction were designed, guided by X-ray crystallographic data and molecular dynamics simulations. In this way, we developed the first reported series of constrained peptide nuclear import inhibitors. Importantly, this general approach may be extended to other transcription factors. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Astrophysical Model Selection in Gravitational Wave Astronomy

NASA Technical Reports Server (NTRS)

Adams, Matthew R.; Cornish, Neil J.; Littenberg, Tyson B.

2012-01-01

Theoretical studies in gravitational wave astronomy have mostly focused on the information that can be extracted from individual detections, such as the mass of a binary system and its location in space. Here we consider how the information from multiple detections can be used to constrain astrophysical population models. This seemingly simple problem is made challenging by the high dimensionality and high degree of correlation in the parameter spaces that describe the signals, and by the complexity of the astrophysical models, which can also depend on a large number of parameters, some of which might not be directly constrained by the observations. We present a method for constraining population models using a hierarchical Bayesian modeling approach which simultaneously infers the source parameters and population model and provides the joint probability distributions for both. We illustrate this approach by considering the constraints that can be placed on population models for galactic white dwarf binaries using a future space-based gravitational wave detector. We find that a mission that is able to resolve approximately 5000 of the shortest period binaries will be able to constrain the population model parameters, including the chirp mass distribution and a characteristic galaxy disk radius to within a few percent. This compares favorably to existing bounds, where electromagnetic observations of stars in the galaxy constrain disk radii to within 20%.

Steroids are required for epidermal cell fate establishment in Arabidopsis roots.

PubMed

Kuppusamy, Kavitha T; Chen, Andrew Y; Nemhauser, Jennifer L

2009-05-12

The simple structure of Arabidopsis roots provides an excellent model system to study epidermal cell fate specification. Epidermal cells in contact with 2 underlying cortical cells differentiate into hair cells (H cells; trichoblasts), whereas cells that contact only a single cortical cell differentiate into mature hairless cells (N cells; atrichoblasts). This position-dependent patterning, in combination with the constrained orientation of cell divisions, results in hair and nonhair cell files running longitudinally along the root epidermis. Here, we present strong evidence that steroid hormones called brassinosteroids (BRs) are required to maintain position-dependent fate specification in roots. We show that BRs are required for normal expression levels and patterns of WEREWOLF (WER) and GLABRA2 (GL2), master regulators of epidermal patterning. Loss of BR signaling results in loss of hair cells in H positions, likely as a consequence of reduced expression of CAPRICE (CPC), a direct downstream target of WER. Our observations demonstrate that in addition to their well-known role in cell expansion, BRs play an essential role in directing cell fate.

Steroids are required for epidermal cell fate establishment in Arabidopsis roots

PubMed Central

Kuppusamy, Kavitha T.; Chen, Andrew Y.; Nemhauser, Jennifer L.

2009-01-01

The simple structure of Arabidopsis roots provides an excellent model system to study epidermal cell fate specification. Epidermal cells in contact with 2 underlying cortical cells differentiate into hair cells (H cells; trichoblasts), whereas cells that contact only a single cortical cell differentiate into mature hairless cells (N cells; atrichoblasts). This position-dependent patterning, in combination with the constrained orientation of cell divisions, results in hair and nonhair cell files running longitudinally along the root epidermis. Here, we present strong evidence that steroid hormones called brassinosteroids (BRs) are required to maintain position-dependent fate specification in roots. We show that BRs are required for normal expression levels and patterns of WEREWOLF (WER) and GLABRA2 (GL2), master regulators of epidermal patterning. Loss of BR signaling results in loss of hair cells in H positions, likely as a consequence of reduced expression of CAPRICE (CPC), a direct downstream target of WER. Our observations demonstrate that in addition to their well-known role in cell expansion, BRs play an essential role in directing cell fate. PMID:19416891

Flexible C : N ratio enhances metabolism of large phytoplankton when resource supply is intermittent

NASA Astrophysics Data System (ADS)

Talmy, D.; Blackford, J.; Hardman-Mountford, N. J.; Polimene, L.; Follows, M. J.; Geider, R. J.

2014-09-01

Phytoplankton cell size influences particle sinking rate, food web interactions and biogeographical distributions. We present a model in which the uptake, storage and assimilation of nitrogen and carbon are explicitly resolved in different-sized phytoplankton cells. In the model, metabolism and cellular C : N ratio are influenced by the accumulation of carbon polymers such as carbohydrate and lipid, which is greatest when cells are nutrient starved, or exposed to high light. Allometric relations and empirical data sets are used to constrain the range of possible C : N, and indicate that larger cells can accumulate significantly more carbon storage compounds than smaller cells. When forced with extended periods of darkness combined with brief exposure to saturating irradiance, the model predicts organisms large enough to accumulate significant carbon reserves may on average synthesize protein and other functional apparatus up to five times faster than smaller organisms. The advantage of storage in terms of average daily protein synthesis rate is greatest when modeled organisms were previously nutrient starved, and carbon storage reservoirs saturated. Small organisms may therefore be at a disadvantage in terms of average daily growth rate in environments that involve prolonged periods of darkness and intermittent nutrient limitation. We suggest this mechanism is a significant constraint on phytoplankton C : N variability and cell size distribution in different oceanic regimes.

Describing litho-constrained layout by a high-resolution model filter

NASA Astrophysics Data System (ADS)

Tsai, Min-Chun

2008-05-01

A novel high-resolution model (HRM) filtering technique was proposed to describe litho-constrained layouts. Litho-constrained layouts are layouts that have difficulties to pattern or are highly sensitive to process-fluctuations under current lithography technologies. HRM applies a short-wavelength (or high NA) model simulation directly on the pre-OPC, original design layout to filter out low spatial-frequency regions, and retain high spatial-frequency components which are litho-constrained. Since no OPC neither mask-synthesis steps are involved, this new technique is highly efficient in run time and can be used in design stage to detect and fix litho-constrained patterns. This method has successfully captured all the hot-spots with less than 15% overshoots on a realistic 80 mm2 full-chip M1 layout in 65nm technology node. A step by step derivation of this HRM technique is presented in this paper.

CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms.

PubMed

Terfve, Camille; Cokelaer, Thomas; Henriques, David; MacNamara, Aidan; Goncalves, Emanuel; Morris, Melody K; van Iersel, Martijn; Lauffenburger, Douglas A; Saez-Rodriguez, Julio

2012-10-18

Cells process signals using complex and dynamic networks. Studying how this is performed in a context and cell type specific way is essential to understand signaling both in physiological and diseased situations. Context-specific medium/high throughput proteomic data measured upon perturbation is now relatively easy to obtain but formalisms that can take advantage of these features to build models of signaling are still comparatively scarce. Here we present CellNOptR, an open-source R software package for building predictive logic models of signaling networks by training networks derived from prior knowledge to signaling (typically phosphoproteomic) data. CellNOptR features different logic formalisms, from Boolean models to differential equations, in a common framework. These different logic model representations accommodate state and time values with increasing levels of detail. We provide in addition an interface via Cytoscape (CytoCopteR) to facilitate use and integration with Cytoscape network-based capabilities. Models generated with this pipeline have two key features. First, they are constrained by prior knowledge about the network but trained to data. They are therefore context and cell line specific, which results in enhanced predictive and mechanistic insights. Second, they can be built using different logic formalisms depending on the richness of the available data. Models built with CellNOptR are useful tools to understand how signals are processed by cells and how this is altered in disease. They can be used to predict the effect of perturbations (individual or in combinations), and potentially to engineer therapies that have differential effects/side effects depending on the cell type or context.

CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms

PubMed Central

2012-01-01

Background Cells process signals using complex and dynamic networks. Studying how this is performed in a context and cell type specific way is essential to understand signaling both in physiological and diseased situations. Context-specific medium/high throughput proteomic data measured upon perturbation is now relatively easy to obtain but formalisms that can take advantage of these features to build models of signaling are still comparatively scarce. Results Here we present CellNOptR, an open-source R software package for building predictive logic models of signaling networks by training networks derived from prior knowledge to signaling (typically phosphoproteomic) data. CellNOptR features different logic formalisms, from Boolean models to differential equations, in a common framework. These different logic model representations accommodate state and time values with increasing levels of detail. We provide in addition an interface via Cytoscape (CytoCopteR) to facilitate use and integration with Cytoscape network-based capabilities. Conclusions Models generated with this pipeline have two key features. First, they are constrained by prior knowledge about the network but trained to data. They are therefore context and cell line specific, which results in enhanced predictive and mechanistic insights. Second, they can be built using different logic formalisms depending on the richness of the available data. Models built with CellNOptR are useful tools to understand how signals are processed by cells and how this is altered in disease. They can be used to predict the effect of perturbations (individual or in combinations), and potentially to engineer therapies that have differential effects/side effects depending on the cell type or context. PMID:23079107

OCO-2 Column Carbon Dioxide and Biometric Data Jointly Constrain Parameterization and Projection of a Global Land Model

NASA Astrophysics Data System (ADS)

Shi, Z.; Crowell, S.; Luo, Y.; Rayner, P. J.; Moore, B., III

2015-12-01

Uncertainty in predicted carbon-climate feedback largely stems from poor parameterization of global land models. However, calibration of global land models with observations has been extremely challenging at least for two reasons. First we lack global data products from systematical measurements of land surface processes. Second, computational demand is insurmountable for estimation of model parameter due to complexity of global land models. In this project, we will use OCO-2 retrievals of dry air mole fraction XCO2 and solar induced fluorescence (SIF) to independently constrain estimation of net ecosystem exchange (NEE) and gross primary production (GPP). The constrained NEE and GPP will be combined with data products of global standing biomass, soil organic carbon and soil respiration to improve the community land model version 4.5 (CLM4.5). Specifically, we will first develop a high fidelity emulator of CLM4.5 according to the matrix representation of the terrestrial carbon cycle. It has been shown that the emulator fully represents the original model and can be effectively used for data assimilation to constrain parameter estimation. We will focus on calibrating those key model parameters (e.g., maximum carboxylation rate, turnover time and transfer coefficients of soil carbon pools, and temperature sensitivity of respiration) for carbon cycle. The Bayesian Markov chain Monte Carlo method (MCMC) will be used to assimilate the global databases into the high fidelity emulator to constrain the model parameters, which will be incorporated back to the original CLM4.5. The calibrated CLM4.5 will be used to make scenario-based projections. In addition, we will conduct observing system simulation experiments (OSSEs) to evaluate how the sampling frequency and length could affect the model constraining and prediction.

Constrained and Unconstrained Partial Adjacent Category Logit Models for Ordinal Response Variables

ERIC Educational Resources Information Center

Fullerton, Andrew S.; Xu, Jun

2018-01-01

Adjacent category logit models are ordered regression models that focus on comparisons of adjacent categories. These models are particularly useful for ordinal response variables with categories that are of substantive interest. In this article, we consider unconstrained and constrained versions of the partial adjacent category logit model, which…

Multiscale Cues Drive Collective Cell Migration

NASA Astrophysics Data System (ADS)

Nam, Ki-Hwan; Kim, Peter; Wood, David K.; Kwon, Sunghoon; Provenzano, Paolo P.; Kim, Deok-Ho

2016-07-01

To investigate complex biophysical relationships driving directed cell migration, we developed a biomimetic platform that allows perturbation of microscale geometric constraints with concomitant nanoscale contact guidance architectures. This permits us to elucidate the influence, and parse out the relative contribution, of multiscale features, and define how these physical inputs are jointly processed with oncogenic signaling. We demonstrate that collective cell migration is profoundly enhanced by the addition of contract guidance cues when not otherwise constrained. However, while nanoscale cues promoted migration in all cases, microscale directed migration cues are dominant as the geometric constraint narrows, a behavior that is well explained by stochastic diffusion anisotropy modeling. Further, oncogene activation (i.e. mutant PIK3CA) resulted in profoundly increased migration where extracellular multiscale directed migration cues and intrinsic signaling synergistically conspire to greatly outperform normal cells or any extracellular guidance cues in isolation.

Optimal vibration control of a rotating plate with self-sensing active constrained layer damping

NASA Astrophysics Data System (ADS)

Xie, Zhengchao; Wong, Pak Kin; Lo, Kin Heng

2012-04-01

This paper proposes a finite element model for optimally controlled constrained layer damped (CLD) rotating plate with self-sensing technique and frequency-dependent material property in both the time and frequency domain. Constrained layer damping with viscoelastic material can effectively reduce the vibration in rotating structures. However, most existing research models use complex modulus approach to model viscoelastic material, and an additional iterative approach which is only available in frequency domain has to be used to include the material's frequency dependency. It is meaningful to model the viscoelastic damping layer in rotating part by using the anelastic displacement fields (ADF) in order to include the frequency dependency in both the time and frequency domain. Also, unlike previous ones, this finite element model treats all three layers as having the both shear and extension strains, so all types of damping are taken into account. Thus, in this work, a single layer finite element is adopted to model a three-layer active constrained layer damped rotating plate in which the constraining layer is made of piezoelectric material to work as both the self-sensing sensor and actuator under an linear quadratic regulation (LQR) controller. After being compared with verified data, this newly proposed finite element model is validated and could be used for future research.

Cell cycle stage-specific differential expression of topoisomerase I in tobacco BY-2 cells and its ectopic overexpression and knockdown unravels its crucial role in plant morphogenesis and development.

PubMed

Singh, Badri Nath; Mudgil, Yashwanti; John, Riffat; Achary, V Mohan Murali; Tripathy, Manas Kumar; Sopory, Sudhir K; Reddy, Malireddy K; Kaul, Tanushri

2015-11-01

DNA topoisomerases catalyze the inter-conversion of different topological forms of DNA. Cell cycle coupled differential accumulation of topoisomerase I (Topo I) revealed biphasic expression maximum at S-phase and M/G1-phase of cultured synchronized tobacco BY-2 cells. This suggested its active role in resolving topological constrains during DNA replication (S-phase) and chromosome decondensation (M/G1 phase). Immuno-localization revealed high concentrations of Topo I in nucleolus. Propidium iodide staining and Br-UTP incorporation patterns revealed direct correlation between immunofluorescence intensity and rRNA transcription activity within nucleolus. Immuno-stained chromosomes during metaphase and anaphase suggested possible role of Topo I in resolving topological constrains during mitotic chromosome condensation. Inhibitor studies showed that in comparison to Topo I, Topo II was essential in resolving topological constrains during chromosome condensation. Probably, Topo II substituted Topo I functioning to certain extent during chromosome condensation, but not vice-versa. Transgenic Topo I tobacco lines revealed morphological abnormalities and highlighted its crucial role in plant morphogenesis and development. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Anisotropic forces from spatially constrained focal adhesions mediate contact guidance directed cell migration

PubMed Central

Ray, Arja; Lee, Oscar; Win, Zaw; Edwards, Rachel M.; Alford, Patrick W.; Kim, Deok-Ho; Provenzano, Paolo P.

2017-01-01

Directed migration by contact guidance is a poorly understood yet vital phenomenon, particularly for carcinoma cell invasion on aligned collagen fibres. We demonstrate that for single cells, aligned architectures providing contact guidance cues induce constrained focal adhesion maturation and associated F-actin alignment, consequently orchestrating anisotropic traction stresses that drive cell orientation and directional migration. Consistent with this understanding, relaxing spatial constraints to adhesion maturation either through reduction in substrate alignment density or reduction in adhesion size diminishes the contact guidance response. While such interactions allow single mesenchymal-like cells to spontaneously ‘sense' and follow topographic alignment, intercellular interactions within epithelial clusters temper anisotropic cell–substratum forces, resulting in substantially lower directional response. Overall, these results point to the control of contact guidance by a balance of cell–substratum and cell–cell interactions, modulated by cell phenotype-specific cytoskeletal arrangements. Thus, our findings elucidate how phenotypically diverse cells perceive ECM alignment at the molecular level. PMID:28401884

Microbial processing of carbon in hydrothermal systems (Invited)

NASA Astrophysics Data System (ADS)

LaRowe, D.; Amend, J. P.

2013-12-01

Microorganisms are known to be active in hydrothermal systems. They catalyze reactions that consume and produce carbon compounds as a result of their efforts to gain energy, grow and replace biomass. However, the rates of these processes, as well as the size of the active component of microbial populations, are poorly constrained in hydrothermal environments. In order to better characterize biogeochemical processes in these settings, a quantitative relationship between rates of microbial catalysis, energy supply and demand and population size is presented. Within this formulation, rates of biomass change are determined as a function of the proportion of catabolic power that is converted into biomass - either new microorganisms or the replacement of existing cell components - and the amount of energy that is required to synthesize biomass. The constraints that hydrothermal conditions place on power supply and demand are explicitly taken into account. The chemical composition, including the concentrations of organic compounds, of diffuse and focused flow hydrothermal fluids, hydrothermally influenced sediment pore water and fluids from the oceanic lithosphere are used in conjunction with cell count data and the model described above to constrain the rates of microbial processes that influence the carbon cycle in the Juan de Fuca hydrothermal system.

Improved image decompression for reduced transform coding artifacts

NASA Technical Reports Server (NTRS)

Orourke, Thomas P.; Stevenson, Robert L.

1994-01-01

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

Oxygen consumption by bovine granulosa cells with prediction of oxygen transport in preantral follicles.

PubMed

Li, Dongxing; Redding, Gabe P; Bronlund, John E

2013-01-01

The rate of oxygen consumption by granulosa cells is a key parameter in mathematical models that describe oxygen transport across ovarian follicles. This work measured the oxygen consumption rate of bovine granulosa cells in vitro to be in the range 2.1-3.3×10⁻¹⁶ mol cell⁻¹ s⁻¹ (0.16-0.25 mol m⁻³ s⁻¹). The implications of the rates for oxygen transport in large bovine preantral follicles were examined using a mathematical model. The results indicate that oocyte oxygenation becomes increasingly constrained as preantral follicles grow, reaching hypoxic levels near the point of antrum formation. Beyond a preantral follicle radius of 134 µm, oxygen cannot reach the oocyte surface at typical values of model parameters. Since reported sizes of large bovine preantral follicles range from 58 to 145 µm in radius, this suggests that oocyte oxygenation is possible in all but the largest preantral follicles, which are on the verge of antrum formation. In preantral bovine follicles, the oxygen consumption rate of granulosa cells and fluid voidage will be the key determinants of oxygen levels across the follicle.

A Multidimensional Item Response Model: Constrained Latent Class Analysis Using the Gibbs Sampler and Posterior Predictive Checks.

ERIC Educational Resources Information Center

Hoijtink, Herbert; Molenaar, Ivo W.

1997-01-01

This paper shows that a certain class of constrained latent class models may be interpreted as a special case of nonparametric multidimensional item response models. Parameters of this latent class model are estimated using an application of the Gibbs sampler, and model fit is investigated using posterior predictive checks. (SLD)

Dynamic Modeling, Model-Based Control, and Optimization of Solid Oxide Fuel Cells

NASA Astrophysics Data System (ADS)

Spivey, Benjamin James

2011-07-01

Solid oxide fuel cells are a promising option for distributed stationary power generation that offers efficiencies ranging from 50% in stand-alone applications to greater than 80% in cogeneration. To advance SOFC technology for widespread market penetration, the SOFC should demonstrate improved cell lifetime and load-following capability. This work seeks to improve lifetime through dynamic analysis of critical lifetime variables and advanced control algorithms that permit load-following while remaining in a safe operating zone based on stress analysis. Control algorithms typically have addressed SOFC lifetime operability objectives using unconstrained, single-input-single-output control algorithms that minimize thermal transients. Existing SOFC controls research has not considered maximum radial thermal gradients or limits on absolute temperatures in the SOFC. In particular, as stress analysis demonstrates, the minimum cell temperature is the primary thermal stress driver in tubular SOFCs. This dissertation presents a dynamic, quasi-two-dimensional model for a high-temperature tubular SOFC combined with ejector and prereformer models. The model captures dynamics of critical thermal stress drivers and is used as the physical plant for closed-loop control simulations. A constrained, MIMO model predictive control algorithm is developed and applied to control the SOFC. Closed-loop control simulation results demonstrate effective load-following, constraint satisfaction for critical lifetime variables, and disturbance rejection. Nonlinear programming is applied to find the optimal SOFC size and steady-state operating conditions to minimize total system costs.

On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid

NASA Astrophysics Data System (ADS)

Velarde, P.; Valverde, L.; Maestre, J. M.; Ocampo-Martinez, C.; Bordons, C.

2017-03-01

In this paper, a performance comparison among three well-known stochastic model predictive control approaches, namely, multi-scenario, tree-based, and chance-constrained model predictive control is presented. To this end, three predictive controllers have been designed and implemented in a real renewable-hydrogen-based microgrid. The experimental set-up includes a PEM electrolyzer, lead-acid batteries, and a PEM fuel cell as main equipment. The real experimental results show significant differences from the plant components, mainly in terms of use of energy, for each implemented technique. Effectiveness, performance, advantages, and disadvantages of these techniques are extensively discussed and analyzed to give some valid criteria when selecting an appropriate stochastic predictive controller.

Multi-Scale Modeling to Improve Single-Molecule, Single-Cell Experiments

NASA Astrophysics Data System (ADS)

Munsky, Brian; Shepherd, Douglas

2014-03-01

Single-cell, single-molecule experiments are producing an unprecedented amount of data to capture the dynamics of biological systems. When integrated with computational models, observations of spatial, temporal and stochastic fluctuations can yield powerful quantitative insight. We concentrate on experiments that localize and count individual molecules of mRNA. These high precision experiments have large imaging and computational processing costs, and we explore how improved computational analyses can dramatically reduce overall data requirements. In particular, we show how analyses of spatial, temporal and stochastic fluctuations can significantly enhance parameter estimation results for small, noisy data sets. We also show how full probability distribution analyses can constrain parameters with far less data than bulk analyses or statistical moment closures. Finally, we discuss how a systematic modeling progression from simple to more complex analyses can reduce total computational costs by orders of magnitude. We illustrate our approach using single-molecule, spatial mRNA measurements of Interleukin 1-alpha mRNA induction in human THP1 cells following stimulation. Our approach could improve the effectiveness of single-molecule gene regulation analyses for many other process.

A Reactive-Transport Model Describing Methanogen Growth and Methane Production in Diffuse Flow Vents at Axial Seamount

NASA Astrophysics Data System (ADS)

Algar, C. K.

2015-12-01

Hydrogenotrophic methanogenesis is an important mode of metabolism in deep-sea hydrothermal vents. Diffuse vent fluids often show a depletion in hydrogen with a corresponding increase in methane relative to pure-mixing of end member fluid and seawater, and genomic surveys show an enrichment in genetic sequences associated with known methanogens. However, because we cannot directly sample the subseafloor habitat where these organisms are living, constraining the size and activity of these populations remains a challenge and limits our ability to quantify the role they play in vent biogeochemistry. Reactive-transport modeling may provide a useful tool for approaching this problem. Here we present a reactive-transport model describing methane production along the flow-path of hydrothermal fluid from its high temperature end-member to diffuse venting at the seafloor. The model is set up to reflect conditions at several diffuse vents in the Axial Seamount. The model describes the growth of the two dominant thermophilic methanogens, Methanothermococcus and Methanocaldococcus, observed at Axial seamount. Monod and Arrhenius constants for Methanothermococcus thermolithotrophicus and Methanocaldococcus jannaschii were obtained for the model using chemostat and bottle experiments at varying temperatures. The model is used to investigate the influence of different mixing regimes on the subseafloor populations of these methanogens. By varying the model flow path length and subseafloor cell concentrations, and fitting to observed hydrogen and methane concentrations in the venting fluid, the subseafloor biomass, fluid residence time, and methane production rate can be constrained.

Constitutive Signaling from an Engineered IL7 Receptor Promotes Durable Tumor Elimination by Tumor-Redirected T Cells.

PubMed

Shum, Thomas; Omer, Bilal; Tashiro, Haruko; Kruse, Robert L; Wagner, Dimitrios L; Parikh, Kathan; Yi, Zhongzhen; Sauer, Tim; Liu, Daofeng; Parihar, Robin; Castillo, Paul; Liu, Hao; Brenner, Malcolm K; Metelitsa, Leonid S; Gottschalk, Stephen; Rooney, Cliona M

2017-11-01

Successful adoptive T-cell immunotherapy of solid tumors will require improved expansion and cytotoxicity of tumor-directed T cells within tumors. Providing recombinant or transgenic cytokines may produce the desired benefits but is associated with significant toxicities, constraining clinical use. To circumvent this limitation, we constructed a constitutively signaling cytokine receptor, C7R, which potently triggers the IL7 signaling axis but is unresponsive to extracellular cytokine. This strategy augments modified T-cell function following antigen exposure, but avoids stimulating bystander lymphocytes. Coexpressing the C7R with a tumor-directed chimeric antigen receptor (CAR) increased T-cell proliferation, survival, and antitumor activity during repeated exposure to tumor cells, without T-cell dysfunction or autonomous T-cell growth. Furthermore, C7R-coexpressing CAR T cells were active against metastatic neuroblastoma and orthotopic glioblastoma xenograft models even at cell doses that had been ineffective without C7R support. C7R may thus be able to enhance antigen-specific T-cell therapies against cancer. Significance: The constitutively signaling C7R system developed here delivers potent IL7 stimulation to CAR T cells, increasing their persistence and antitumor activity against multiple preclinical tumor models, supporting its clinical development. Cancer Discov; 7(11); 1238-47. ©2017 AACR. This article is highlighted in the In This Issue feature, p. 1201 . ©2017 American Association for Cancer Research.

Empirical models of Jupiter's interior from Juno data. Moment of inertia and tidal Love number k2

NASA Astrophysics Data System (ADS)

Ni, Dongdong

2018-05-01

Context. The Juno spacecraft has significantly improved the accuracy of gravitational harmonic coefficients J4, J6 and J8 during its first two perijoves. However, there are still differences in the interior model predictions of core mass and envelope metallicity because of the uncertainties in the hydrogen-helium equations of state. New theoretical approaches or observational data are hence required in order to further constrain the interior models of Jupiter. A well constrained interior model of Jupiter is helpful for understanding not only the dynamic flows in the interior, but also the formation history of giant planets. Aims: We present the radial density profiles of Jupiter fitted to the Juno gravity field observations. Also, we aim to investigate our ability to constrain the core properties of Jupiter using its moment of inertia and tidal Love number k2 which could be accessible by the Juno spacecraft. Methods: In this work, the radial density profile was constrained by the Juno gravity field data within the empirical two-layer model in which the equations of state are not needed as an input model parameter. Different two-layer models are constructed in terms of core properties. The dependence of the calculated moment of inertia and tidal Love number k2 on the core properties was investigated in order to discern their abilities to further constrain the internal structure of Jupiter. Results: The calculated normalized moment of inertia (NMOI) ranges from 0.2749 to 0.2762, in reasonable agreement with the other predictions. There is a good correlation between the NMOI value and the core properties including masses and radii. Therefore, measurements of NMOI by Juno can be used to constrain both the core mass and size of Jupiter's two-layer interior models. For the tidal Love number k2, the degeneracy of k2 is found and analyzed within the two-layer interior model. In spite of this, measurements of k2 can still be used to further constrain the core mass and size of Jupiter's two-layer interior models.

A Multiple Group Measurement Model of Children's Reports of Parental Socioeconomic Status. Discussion Papers No. 531-78.

ERIC Educational Resources Information Center

Mare, Robert D.; Mason, William M.

An important class of applications of measurement error or constrained factor analytic models consists of comparing models for several populations. In such cases, it is appropriate to make explicit statistical tests of model similarity across groups and to constrain some parameters of the models to be equal across groups using a priori substantive…

Order-Constrained Bayes Inference for Dichotomous Models of Unidimensional Nonparametric IRT

ERIC Educational Resources Information Center

Karabatsos, George; Sheu, Ching-Fan

2004-01-01

This study introduces an order-constrained Bayes inference framework useful for analyzing data containing dichotomous scored item responses, under the assumptions of either the monotone homogeneity model or the double monotonicity model of nonparametric item response theory (NIRT). The framework involves the implementation of Gibbs sampling to…

Changing HIV treatment eligibility under health system constraints in sub-Saharan Africa: investment needs, population health gains, and cost-effectiveness

PubMed Central

Hontelez, Jan A.C.; Chang, Angela Y.; Ogbuoji, Osondu; de Vlas, Sake J.; Bärnighausen, Till; Atun, Rifat

2016-01-01

Objective: We estimated the investment needs, population health gains, and cost-effectiveness of different policy options for scaling-up prevention and treatment of HIV in the 10 countries that currently comprise 80% of all people living with HIV in sub-Saharan Africa (Ethiopia, Kenya, Malawi, Mozambique, Nigeria, South Africa, Tanzania, Uganda, Zambia, and Zimbabwe). Design: We adapted the established STDSIM model to capture the health system dynamics: demand-side and supply-side constraints in the delivery of antiretroviral treatment (ART). Methods: We compared different scenarios of supply-side (i.e. health system capacity) and demand-side (i.e. health seeking behavior) constraints, and determined the impact of changing guidelines to ART eligibility at any CD4+ cell count within these constraints. Results: Continuing current scale-up would require US$178 billion by 2050. Changing guidelines to ART at any CD4+ cell count is cost-effective under all constraints tested in the model, especially in demand-side constrained health systems because earlier initiation prevents loss-to-follow-up of patients not yet eligible. Changing guidelines under current demand-side constraints would avert 1.8 million infections at US$208 per life-year saved. Conclusion: Treatment eligibility at any CD4+ cell count would be cost-effective, even under health system constraints. Excessive loss-to-follow-up and mortality in patients not eligible for treatment can be avoided by changing guidelines in demand-side constrained systems. The financial obligation for sustaining the AIDS response in sub-Saharan Africa over the next 35 years is substantial and requires strong, long-term commitment of policy-makers and donors to continue to allocate substantial parts of their budgets. PMID:27367487

Changing HIV treatment eligibility under health system constraints in sub-Saharan Africa: investment needs, population health gains, and cost-effectiveness.

PubMed

Hontelez, Jan A C; Chang, Angela Y; Ogbuoji, Osondu; de Vlas, Sake J; Bärnighausen, Till; Atun, Rifat

2016-09-24

We estimated the investment needs, population health gains, and cost-effectiveness of different policy options for scaling-up prevention and treatment of HIV in the 10 countries that currently comprise 80% of all people living with HIV in sub-Saharan Africa (Ethiopia, Kenya, Malawi, Mozambique, Nigeria, South Africa, Tanzania, Uganda, Zambia, and Zimbabwe). We adapted the established STDSIM model to capture the health system dynamics: demand-side and supply-side constraints in the delivery of antiretroviral treatment (ART). We compared different scenarios of supply-side (i.e. health system capacity) and demand-side (i.e. health seeking behavior) constraints, and determined the impact of changing guidelines to ART eligibility at any CD4 cell count within these constraints. Continuing current scale-up would require US$178 billion by 2050. Changing guidelines to ART at any CD4 cell count is cost-effective under all constraints tested in the model, especially in demand-side constrained health systems because earlier initiation prevents loss-to-follow-up of patients not yet eligible. Changing guidelines under current demand-side constraints would avert 1.8 million infections at US$208 per life-year saved. Treatment eligibility at any CD4 cell count would be cost-effective, even under health system constraints. Excessive loss-to-follow-up and mortality in patients not eligible for treatment can be avoided by changing guidelines in demand-side constrained systems. The financial obligation for sustaining the AIDS response in sub-Saharan Africa over the next 35 years is substantial and requires strong, long-term commitment of policy-makers and donors to continue to allocate substantial parts of their budgets.

Numerical cell model investigating cellular carbon fluxes in Emiliania huxleyi.

PubMed

Holtz, Lena-Maria; Wolf-Gladrow, Dieter; Thoms, Silke

2015-01-07

Coccolithophores play a crucial role in the marine carbon cycle and thus it is interesting to know how they will respond to climate change. After several decades of research the interplay between intracellular processes and the marine carbonate system is still not well understood. On the basis of experimental findings given in literature, a numerical cell model is developed that describes inorganic carbon fluxes between seawater and the intracellular sites of calcite precipitation and photosynthetic carbon fixation. The implemented cell model consists of four compartments, for each of which the carbonate system is resolved individually. The four compartments are connected to each other via H(+), CO2, and HCO3(-) fluxes across the compartment-confining membranes. For CO2 accumulation around RubisCO, an energy-efficient carbon concentrating mechanism is proposed that relies on diffusive CO2 uptake. At low external CO2 concentrations and high light intensities, CO2 diffusion does not suffice to cover the carbon demand of photosynthesis and an additional uptake of external HCO3(-) becomes essential. The model is constrained by data of Emiliania huxleyi, the numerically most abundant coccolithophore species in the present-day ocean. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Paxillin Mediates Sensing of Physical Cues and Regulates Directional Cell Motility by Controlling Lamellipodia Positioning

PubMed Central

Sero, Julia E.; Thodeti, Charles K.; Mammoto, Akiko; Bakal, Chris; Thomas, Sheila; Ingber, Donald E.

2011-01-01

Physical interactions between cells and the extracellular matrix (ECM) guide directional migration by spatially controlling where cells form focal adhesions (FAs), which in turn regulate the extension of motile processes. Here we show that physical control of directional migration requires the FA scaffold protein paxillin. Using single-cell sized ECM islands to constrain cell shape, we found that fibroblasts cultured on square islands preferentially activated Rac and extended lamellipodia from corner, rather than side regions after 30 min stimulation with PDGF, but that cells lacking paxillin failed to restrict Rac activity to corners and formed small lamellipodia along their entire peripheries. This spatial preference was preceded by non-spatially constrained formation of both dorsal and lateral membrane ruffles from 5–10 min. Expression of paxillin N-terminal (paxN) or C-terminal (paxC) truncation mutants produced opposite, but complementary, effects on lamellipodia formation. Surprisingly, pax−/− and paxN cells also formed more circular dorsal ruffles (CDRs) than pax+ cells, while paxC cells formed fewer CDRs and extended larger lamellipodia even in the absence of PDGF. In a two-dimensional (2D) wound assay, pax−/− cells migrated at similar speeds to controls but lost directional persistence. Directional motility was rescued by expressing full-length paxillin or the N-terminus alone, but paxN cells migrated more slowly. In contrast, pax−/− and paxN cells exhibited increased migration in a three-dimensional (3D) invasion assay, with paxN cells invading Matrigel even in the absence of PDGF. These studies indicate that paxillin integrates physical and chemical motility signals by spatially constraining where cells will form motile processes, and thereby regulates directional migration both in 2D and 3D. These findings also suggest that CDRs may correspond to invasive protrusions that drive cell migration through 3D extracellular matrices. PMID:22194823

A Method to Constrain Mass and Spin of GRB Black Holes within the NDAF Model

NASA Astrophysics Data System (ADS)

Liu, Tong; Xue, Li; Zhao, Xiao-Hong; Zhang, Fu-Wen; Zhang, Bing

2016-04-01

Black holes (BHs) hide themselves behind various astronomical phenomena and their properties, I.e., mass and spin, are usually difficult to constrain. One leading candidate for the central engine model of gamma-ray bursts (GRBs) invokes a stellar mass BH and a neutrino-dominated accretion flow (NDAF), with the relativistic jet launched due to neutrino-anti-neutrino annihilations. Such a model gives rise to a matter-dominated fireball, and is suitable to interpret GRBs with a dominant thermal component with a photospheric origin. We propose a method to constrain BH mass and spin within the framework of this model and apply the method to the thermally dominant GRB 101219B, whose initial jet launching radius, r0, is constrained from the data. Using our numerical model of NDAF jets, we estimate the following constraints on the central BH: mass MBH ˜ 5-9 M⊙, spin parameter a* ≳ 0.6, and disk mass 3 M⊙ ≲ Mdisk ≲ 4 M⊙. Our results also suggest that the NDAF model is a competitive candidate for the central engine of GRBs with a strong thermal component.

A viable dark fluid model

NASA Astrophysics Data System (ADS)

Elkhateeb, Esraa

2018-01-01

We consider a cosmological model based on a generalization of the equation of state proposed by Nojiri and Odintsov (2004) and Štefančić (2005, 2006). We argue that this model works as a dark fluid model which can interpolate between dust equation of state and the dark energy equation of state. We show how the asymptotic behavior of the equation of state constrained the parameters of the model. The causality condition for the model is also studied to constrain the parameters and the fixed points are tested to determine different solution classes. Observations of Hubble diagram of SNe Ia supernovae are used to further constrain the model. We present an exact solution of the model and calculate the luminosity distance and the energy density evolution. We also calculate the deceleration parameter to test the state of the universe expansion.

Visualization of RNA structure models within the Integrative Genomics Viewer.

PubMed

Busan, Steven; Weeks, Kevin M

2017-07-01

Analyses of the interrelationships between RNA structure and function are increasingly important components of genomic studies. The SHAPE-MaP strategy enables accurate RNA structure probing and realistic structure modeling of kilobase-length noncoding RNAs and mRNAs. Existing tools for visualizing RNA structure models are not suitable for efficient analysis of long, structurally heterogeneous RNAs. In addition, structure models are often advantageously interpreted in the context of other experimental data and gene annotation information, for which few tools currently exist. We have developed a module within the widely used and well supported open-source Integrative Genomics Viewer (IGV) that allows visualization of SHAPE and other chemical probing data, including raw reactivities, data-driven structural entropies, and data-constrained base-pair secondary structure models, in context with linear genomic data tracks. We illustrate the usefulness of visualizing RNA structure in the IGV by exploring structure models for a large viral RNA genome, comparing bacterial mRNA structure in cells with its structure under cell- and protein-free conditions, and comparing a noncoding RNA structure modeled using SHAPE data with a base-pairing model inferred through sequence covariation analysis. © 2017 Busan and Weeks; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Cytoskeleton-mediated templating of complex cellulose-scaffolded extracellular structure and its association with oikosins in the urochordate Oikopleura.

PubMed

Sagane, Yoshimasa; Hosp, Julia; Zech, Karin; Thompson, Eric M

2011-05-01

Oriented cellulose deposition is critical to plant patterning and models suggest microtubules constrain cellulose synthase movements through the plasma membrane. Though widespread in plants, urochordates are the only animals that synthesize cellulose. We characterized the distinctive cellulose microfibril scaffold of the larvacean house and its interaction with house structural proteins (oikosins). Targeted disruption of cytoskeletal elements, secretory pathways, and plasma membrane organization, suggested a working model for templating extracellular cellulose microfibrils from animal cells that shows both convergence and differences to plant models. Specialized cortical F-actin arrays template microfibril orientation and glycosylphosphatidylinositol-anchored proteins in lipid rafts may act as scaffolding proteins in microfibril elongation. Microtubules deliver and maintain cellulose synthase complexes to specific cell membrane sites rather than orienting their movement through the membrane. Oikosins are incorporated into house compartments directly above their corresponding cellular field of expression and interact with the cellulose scaffold to a variable extent.

Interactions between Inhibitory Interneurons and Excitatory Associational Circuitry in Determining Spatio-Temporal Dynamics of Hippocampal Dentate Granule Cells: A Large-Scale Computational Study

PubMed Central

Hendrickson, Phillip J.; Yu, Gene J.; Song, Dong; Berger, Theodore W.

2015-01-01

This paper reports on findings from a million-cell granule cell model of the rat dentate gyrus that was used to explore the contributions of local interneuronal and associational circuits to network-level activity. The model contains experimentally derived morphological parameters for granule cells, which each contain approximately 200 compartments, and biophysical parameters for granule cells, basket cells, and mossy cells that were based both on electrophysiological data and previously published models. Synaptic input to cells in the model consisted of glutamatergic AMPA-like EPSPs and GABAergic-like IPSPs from excitatory and inhibitory neurons, respectively. The main source of input to the model was from layer II entorhinal cortical neurons. Network connectivity was constrained by the topography of the system, and was derived from axonal transport studies, which provided details about the spatial spread of axonal terminal fields, as well as how subregions of the medial and lateral entorhinal cortices project to subregions of the dentate gyrus. Results of this study show that strong feedback inhibition from the basket cell population can cause high-frequency rhythmicity in granule cells, while the strength of feedforward inhibition serves to scale the total amount of granule cell activity. Results furthermore show that the topography of local interneuronal circuits can have just as strong an impact on the development of spatio-temporal clusters in the granule cell population as the perforant path topography does, both sharpening existing clusters and introducing new ones with a greater spatial extent. Finally, results show that the interactions between the inhibitory and associational loops can cause high frequency oscillations that are modulated by a low-frequency oscillatory signal. These results serve to further illustrate the importance of topographical constraints on a global signal processing feature of a neural network, while also illustrating how rich spatio-temporal and oscillatory dynamics can evolve from a relatively small number of interacting local circuits. PMID:26635545

On meeting capital requirements with a chance-constrained optimization model.

PubMed

Atta Mills, Ebenezer Fiifi Emire; Yu, Bo; Gu, Lanlan

2016-01-01

This paper deals with a capital to risk asset ratio chance-constrained optimization model in the presence of loans, treasury bill, fixed assets and non-interest earning assets. To model the dynamics of loans, we introduce a modified CreditMetrics approach. This leads to development of a deterministic convex counterpart of capital to risk asset ratio chance constraint. We pursue the scope of analyzing our model under the worst-case scenario i.e. loan default. The theoretical model is analyzed by applying numerical procedures, in order to administer valuable insights from a financial outlook. Our results suggest that, our capital to risk asset ratio chance-constrained optimization model guarantees banks of meeting capital requirements of Basel III with a likelihood of 95 % irrespective of changes in future market value of assets.

Tumorigenesis and Greenhouse-Effect System Dynamics: Phenomenally Diverse, but Noumenally Similar?

NASA Astrophysics Data System (ADS)

Prakash, Sai

We present a physicochemical model of tumorigenesis leading to cancer invasion and metastasis. The continuum-theoretic model, congruent with recent experiments, analyzes the plausibility of oncogenic neoplasia-induced cavitation or tensile yielding (plasticity) of the tumoral basement membrane (BM) to activate stromal invasion. The model abstracts a spheroid of normal and cancer cells that grows radially via water and nutrient influx while constrained by a stiffer BM and cell adhesion molecules. It is based on coupled fluid-solid mechanics and ATP-fueled mechano-damped cell kinetics, and uses empirical data alone as parameters. The model predicts the dynamic force and exergy (ATP) fields, and tumor size among other variables, and generates the sigmoidal dynamics of far-from-equilibrium biota. Simulations show that the tumor-membrane system, on neoplastic perturbation, evolves from one homeostatic steady state to another over time. Integrated with system dynamics theory, the model renders a key, emergent tissue-level feedback control perspective of malignancy: neoplastic tumors coupled with pathologically-softened BMs appear to participate in altered autoregulatory behavior, and likely undergo BM cavitation and stress-localized ruptures to their adhesome, with or without invadopoiesis, thereby, initiating invasion. Serendipitously, the results also reveal a noumenal similarity of the tumor-membrane to the earth-atmosphere open reactive system as concerns self-regulation.

TH-E-BRF-06: Kinetic Modeling of Tumor Response to Fractionated Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhong, H; Gordon, J; Chetty, I

2014-06-15

Purpose: Accurate calibration of radiobiological parameters is crucial to predicting radiation treatment response. Modeling differences may have a significant impact on calibrated parameters. In this study, we have integrated two existing models with kinetic differential equations to formulate a new tumor regression model for calibrating radiobiological parameters for individual patients. Methods: A system of differential equations that characterizes the birth-and-death process of tumor cells in radiation treatment was analytically solved. The solution of this system was used to construct an iterative model (Z-model). The model consists of three parameters: tumor doubling time Td, half-life of dying cells Tr and cellmore » survival fraction SFD under dose D. The Jacobian determinant of this model was proposed as a constraint to optimize the three parameters for six head and neck cancer patients. The derived parameters were compared with those generated from the two existing models, Chvetsov model (C-model) and Lim model (L-model). The C-model and L-model were optimized with the parameter Td fixed. Results: With the Jacobian-constrained Z-model, the mean of the optimized cell survival fractions is 0.43±0.08, and the half-life of dying cells averaged over the six patients is 17.5±3.2 days. The parameters Tr and SFD optimized with the Z-model differ by 1.2% and 20.3% from those optimized with the Td-fixed C-model, and by 32.1% and 112.3% from those optimized with the Td-fixed L-model, respectively. Conclusion: The Z-model was analytically constructed from the cellpopulation differential equations to describe changes in the number of different tumor cells during the course of fractionated radiation treatment. The Jacobian constraints were proposed to optimize the three radiobiological parameters. The developed modeling and optimization methods may help develop high-quality treatment regimens for individual patients.« less

Constraining new physics models with isotope shift spectroscopy

NASA Astrophysics Data System (ADS)

Frugiuele, Claudia; Fuchs, Elina; Perez, Gilad; Schlaffer, Matthias

2017-07-01

Isotope shifts of transition frequencies in atoms constrain generic long- and intermediate-range interactions. We focus on new physics scenarios that can be most strongly constrained by King linearity violation such as models with B -L vector bosons, the Higgs portal, and chameleon models. With the anticipated precision, King linearity violation has the potential to set the strongest laboratory bounds on these models in some regions of parameter space. Furthermore, we show that this method can probe the couplings relevant for the protophobic interpretation of the recently reported Be anomaly. We extend the formalism to include an arbitrary number of transitions and isotope pairs and fit the new physics coupling to the currently available isotope shift measurements.

Kinesin Steps Do Not Alternate in Size☆

PubMed Central

Fehr, Adrian N.; Asbury, Charles L.; Block, Steven M.

2008-01-01

Abstract Kinesin is a two-headed motor protein that transports cargo inside cells by moving stepwise on microtubules. Its exact trajectory along the microtubule is unknown: alternative pathway models predict either uniform 8-nm steps or alternating 7- and 9-nm steps. By analyzing single-molecule stepping traces from “limping” kinesin molecules, we were able to distinguish alternate fast- and slow-phase steps and thereby to calculate the step sizes associated with the motions of each of the two heads. We also compiled step distances from nonlimping kinesin molecules and compared these distributions against models predicting uniform or alternating step sizes. In both cases, we find that kinesin takes uniform 8-nm steps, a result that strongly constrains the allowed models. PMID:18083906

Constrained optimization framework for interface-aware sub-scale dynamics models for voids closure in Lagrangian hydrodynamics

DOE PAGES

Barlow, Andrew; Klima, Matej; Shashkov, Mikhail

2018-04-02

In hydrocodes, voids are used to represent vacuum and model free boundaries between vacuum and real materials. We give a systematic description of a new treatment of void closure in the framework of the multimaterial arbitrary Lagrangian–Eulerian (ALE) methods. This includes a new formulation of the interface-aware sub-scale-dynamics (IA-SSD) closure model for multimaterial cells with voids, which is used in the Lagrangian stage of our indirect ALE scheme. The results of the comprehensive testing of the new model are presented for one- and two-dimensional multimaterial calculations in the presence of voids. Finally, we also present a sneak peek of amore » realistic shaped charge calculation in the presence of voids and solids.« less

Constrained optimization framework for interface-aware sub-scale dynamics models for voids closure in Lagrangian hydrodynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barlow, Andrew; Klima, Matej; Shashkov, Mikhail

In hydrocodes, voids are used to represent vacuum and model free boundaries between vacuum and real materials. We give a systematic description of a new treatment of void closure in the framework of the multimaterial arbitrary Lagrangian–Eulerian (ALE) methods. This includes a new formulation of the interface-aware sub-scale-dynamics (IA-SSD) closure model for multimaterial cells with voids, which is used in the Lagrangian stage of our indirect ALE scheme. The results of the comprehensive testing of the new model are presented for one- and two-dimensional multimaterial calculations in the presence of voids. Finally, we also present a sneak peek of amore » realistic shaped charge calculation in the presence of voids and solids.« less

Chemotaxis in densely populated tissue determines germinal center anatomy and cell motility: a new paradigm for the development of complex tissues.

PubMed

Hawkins, Jared B; Jones, Mark T; Plassmann, Paul E; Thorley-Lawson, David A

2011-01-01

Germinal centers (GCs) are complex dynamic structures that form within lymph nodes as an essential process in the humoral immune response. They represent a paradigm for studying the regulation of cell movement in the development of complex anatomical structures. We have developed a simulation of a modified cyclic re-entry model of GC dynamics which successfully employs chemotaxis to recapitulate the anatomy of the primary follicle and the development of a mature GC, including correctly structured mantle, dark and light zones. We then show that correct single cell movement dynamics (including persistent random walk and inter-zonal crossing) arise from this simulation as purely emergent properties. The major insight of our study is that chemotaxis can only achieve this when constrained by the known biological properties that cells are incompressible, exist in a densely packed environment, and must therefore compete for space. It is this interplay of chemotaxis and competition for limited space that generates all the complex and biologically accurate behaviors described here. Thus, from a single simple mechanism that is well documented in the biological literature, we can explain both higher level structure and single cell movement behaviors. To our knowledge this is the first GC model that is able to recapitulate both correctly detailed anatomy and single cell movement. This mechanism may have wide application for modeling other biological systems where cells undergo complex patterns of movement to produce defined anatomical structures with sharp tissue boundaries.

Probing embryonic tissue mechanics with laser hole drilling

NASA Astrophysics Data System (ADS)

Ma, Xiaoyan; Lynch, Holley E.; Scully, Peter C.; Hutson, M. Shane

2009-09-01

We use laser hole drilling to assess the mechanics of an embryonic epithelium during development—in vivo and with subcellular resolution. We ablate a subcellular cylindrical hole clean through the epithelium and track the subsequent recoil of adjacent cells (on ms time scales). We investigate dorsal closure in the fruit fly with emphasis on apical constriction of amnioserosa cells. The mechanical behavior of this epithelium falls between that of a continuous sheet and a 2D cellular foam (a network of tensile interfaces). Tensile stress is carried both by cell-cell interfaces and by the cells' apical actin networks. Our results show that stress is slightly concentrated along interfaces (1.6-fold), but only in early closure. Furthermore, closure is marked by a decrease in the recoil power-law exponent, implying a transition to a more solid-like tissue. We use the site and stage dependence of the recoil kinetics to constrain how the cellular mechanics change during closure. We apply these results to test extant computational models.

Importance of Geodetically Controlled Topography to Constrain Rates of Volcanism and Internal Magma Plumbing Systems

NASA Astrophysics Data System (ADS)

Glaze, L. S.; Baloga, S. M.; Garvin, J. B.; Quick, L. C.

2014-05-01

Lava flows and flow fields on Venus lack sufficient topographic data for any type of quantitative modeling to estimate eruption rates and durations. Such modeling can constrain rates of resurfacing and provide insights into magma plumbing systems.

Index-of-refraction-dependent subcellular light scattering observed with organelle-specific dyes.

PubMed

Wilson, Jeremy D; Cottrell, William J; Foster, Thomas H

2007-01-01

Angularly resolved light scattering and wavelength-resolved darkfield scattering spectroscopy measurements were performed on intact, control EMT6 cells and cells stained with high-extinction lysosomal- or mitochondrial-localizing dyes. In the presence of the lysosomal-localizing dye NPe6, we observe changes in the details of light scattering from stained and unstained cells, which have both wavelength- and angular-dependent features. Analysis of measurements performed at several wavelengths reveals a reduced scattering cross section near the absorption maximum of the lysosomal-localizing dye. When identical measurements are made with cells loaded with a similar mitochondrial-localizing dye, HPPH, we find no evidence that staining mitochondria had any effect on the light scattering. Changes in the scattering properties of candidate populations of organelles induced by the addition of an absorber are modeled with Mie theory, and we find that any absorber-induced scattering response is very sensitive to the inherent refractive index of the organelle population. Our measurements and modeling are consistent with EMT6-cell-mitochondria having refractive indices close to those reported in the literature for organelles, approximately 1.4. The reduction in scattering cross section induced by NPe6 constrains the refractive index of lysosomes to be significantly higher. We estimate the refractive index of lysosomes in EMT6 cells to be approximately 1.6.

Characterizing and modeling the free recovery and constrained recovery behavior of a polyurethane shape memory polymer

NASA Astrophysics Data System (ADS)

Volk, Brent L.; Lagoudas, Dimitris C.; Maitland, Duncan J.

2011-09-01

In this work, tensile tests and one-dimensional constitutive modeling were performed on a high recovery force polyurethane shape memory polymer that is being considered for biomedical applications. The tensile tests investigated the free recovery (zero load) response as well as the constrained displacement recovery (stress recovery) response at extension values up to 25%, and two consecutive cycles were performed during each test. The material was observed to recover 100% of the applied deformation when heated at zero load in the second thermomechanical cycle, and a stress recovery of 1.5-4.2 MPa was observed for the constrained displacement recovery experiments. After the experiments were performed, the Chen and Lagoudas model was used to simulate and predict the experimental results. The material properties used in the constitutive model—namely the coefficients of thermal expansion, shear moduli, and frozen volume fraction—were calibrated from a single 10% extension free recovery experiment. The model was then used to predict the material response for the remaining free recovery and constrained displacement recovery experiments. The model predictions match well with the experimental data.

Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant

DOEpatents

Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa

2013-09-17

System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.

The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.

PubMed

Suzuki, Harukazu; Forrest, Alistair R R; van Nimwegen, Erik; Daub, Carsten O; Balwierz, Piotr J; Irvine, Katharine M; Lassmann, Timo; Ravasi, Timothy; Hasegawa, Yuki; de Hoon, Michiel J L; Katayama, Shintaro; Schroder, Kate; Carninci, Piero; Tomaru, Yasuhiro; Kanamori-Katayama, Mutsumi; Kubosaki, Atsutaka; Akalin, Altuna; Ando, Yoshinari; Arner, Erik; Asada, Maki; Asahara, Hiroshi; Bailey, Timothy; Bajic, Vladimir B; Bauer, Denis; Beckhouse, Anthony G; Bertin, Nicolas; Björkegren, Johan; Brombacher, Frank; Bulger, Erika; Chalk, Alistair M; Chiba, Joe; Cloonan, Nicole; Dawe, Adam; Dostie, Josee; Engström, Pär G; Essack, Magbubah; Faulkner, Geoffrey J; Fink, J Lynn; Fredman, David; Fujimori, Ko; Furuno, Masaaki; Gojobori, Takashi; Gough, Julian; Grimmond, Sean M; Gustafsson, Mika; Hashimoto, Megumi; Hashimoto, Takehiro; Hatakeyama, Mariko; Heinzel, Susanne; Hide, Winston; Hofmann, Oliver; Hörnquist, Michael; Huminiecki, Lukasz; Ikeo, Kazuho; Imamoto, Naoko; Inoue, Satoshi; Inoue, Yusuke; Ishihara, Ryoko; Iwayanagi, Takao; Jacobsen, Anders; Kaur, Mandeep; Kawaji, Hideya; Kerr, Markus C; Kimura, Ryuichiro; Kimura, Syuhei; Kimura, Yasumasa; Kitano, Hiroaki; Koga, Hisashi; Kojima, Toshio; Kondo, Shinji; Konno, Takeshi; Krogh, Anders; Kruger, Adele; Kumar, Ajit; Lenhard, Boris; Lennartsson, Andreas; Lindow, Morten; Lizio, Marina; Macpherson, Cameron; Maeda, Norihiro; Maher, Christopher A; Maqungo, Monique; Mar, Jessica; Matigian, Nicholas A; Matsuda, Hideo; Mattick, John S; Meier, Stuart; Miyamoto, Sei; Miyamoto-Sato, Etsuko; Nakabayashi, Kazuhiko; Nakachi, Yutaka; Nakano, Mika; Nygaard, Sanne; Okayama, Toshitsugu; Okazaki, Yasushi; Okuda-Yabukami, Haruka; Orlando, Valerio; Otomo, Jun; Pachkov, Mikhail; Petrovsky, Nikolai; Plessy, Charles; Quackenbush, John; Radovanovic, Aleksandar; Rehli, Michael; Saito, Rintaro; Sandelin, Albin; Schmeier, Sebastian; Schönbach, Christian; Schwartz, Ariel S; Semple, Colin A; Sera, Miho; Severin, Jessica; Shirahige, Katsuhiko; Simons, Cas; St Laurent, George; Suzuki, Masanori; Suzuki, Takahiro; Sweet, Matthew J; Taft, Ryan J; Takeda, Shizu; Takenaka, Yoichi; Tan, Kai; Taylor, Martin S; Teasdale, Rohan D; Tegnér, Jesper; Teichmann, Sarah; Valen, Eivind; Wahlestedt, Claes; Waki, Kazunori; Waterhouse, Andrew; Wells, Christine A; Winther, Ole; Wu, Linda; Yamaguchi, Kazumi; Yanagawa, Hiroshi; Yasuda, Jun; Zavolan, Mihaela; Hume, David A; Arakawa, Takahiro; Fukuda, Shiro; Imamura, Kengo; Kai, Chikatoshi; Kaiho, Ai; Kawashima, Tsugumi; Kawazu, Chika; Kitazume, Yayoi; Kojima, Miki; Miura, Hisashi; Murakami, Kayoko; Murata, Mitsuyoshi; Ninomiya, Noriko; Nishiyori, Hiromi; Noma, Shohei; Ogawa, Chihiro; Sano, Takuma; Simon, Christophe; Tagami, Michihira; Takahashi, Yukari; Kawai, Jun; Hayashizaki, Yoshihide

2009-05-01

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.

The added value of remote sensing products in constraining hydrological models

NASA Astrophysics Data System (ADS)

Nijzink, Remko C.; Almeida, Susana; Pechlivanidis, Ilias; Capell, René; Gustafsson, David; Arheimer, Berit; Freer, Jim; Han, Dawei; Wagener, Thorsten; Sleziak, Patrik; Parajka, Juraj; Savenije, Hubert; Hrachowitz, Markus

2017-04-01

The calibration of a hydrological model still depends on the availability of streamflow data, even though more additional sources of information (i.e. remote sensed data products) have become more widely available. In this research, the model parameters of four different conceptual hydrological models (HYPE, HYMOD, TUW, FLEX) were constrained with remotely sensed products. The models were applied over 27 catchments across Europe to cover a wide range of climates, vegetation and landscapes. The fluxes and states of the models were correlated with the relevant products (e.g. MOD10A snow with modelled snow states), after which new a-posteriori parameter distributions were determined based on a weighting procedure using conditional probabilities. Briefly, each parameter was weighted with the coefficient of determination of the relevant regression between modelled states/fluxes and products. In this way, final feasible parameter sets were derived without the use of discharge time series. Initial results show that improvements in model performance, with regard to streamflow simulations, are obtained when the models are constrained with a set of remotely sensed products simultaneously. In addition, we present a more extensive analysis to assess a model's ability to reproduce a set of hydrological signatures, such as rising limb density or peak distribution. Eventually, this research will enhance our understanding and recommendations in the use of remotely sensed products for constraining conceptual hydrological modelling and improving predictive capability, especially for data sparse regions.

Differential polarization of cortical pyramidal neuron dendrites through weak extracellular fields

PubMed Central

Obermayer, Klaus

2018-01-01

The rise of transcranial current stimulation (tCS) techniques have sparked an increasing interest in the effects of weak extracellular electric fields on neural activity. These fields modulate ongoing neural activity through polarization of the neuronal membrane. While the somatic polarization has been investigated experimentally, the frequency-dependent polarization of the dendritic trees in the presence of alternating (AC) fields has received little attention yet. Using a biophysically detailed model with experimentally constrained active conductances, we analyze the subthreshold response of cortical pyramidal cells to weak AC fields, as induced during tCS. We observe a strong frequency resonance around 10-20 Hz in the apical dendrites sensitivity to polarize in response to electric fields but not in the basal dendrites nor the soma. To disentangle the relative roles of the cell morphology and active and passive membrane properties in this resonance, we perform a thorough analysis using simplified models, e.g. a passive pyramidal neuron model, simple passive cables and reconstructed cell model with simplified ion channels. We attribute the origin of the resonance in the apical dendrites to (i) a locally increased sensitivity due to the morphology and to (ii) the high density of h-type channels. Our systematic study provides an improved understanding of the subthreshold response of cortical cells to weak electric fields and, importantly, allows for an improved design of tCS stimuli. PMID:29727454

Modeling Endoplasmic Reticulum Network Maintenance in a Plant Cell.

PubMed

Lin, Congping; White, Rhiannon R; Sparkes, Imogen; Ashwin, Peter

2017-07-11

The endoplasmic reticulum (ER) in plant cells forms a highly dynamic network of complex geometry. ER network morphology and dynamics are influenced by a number of biophysical processes, including filament/tubule tension, viscous forces, Brownian diffusion, and interactions with many other organelles and cytoskeletal elements. Previous studies have indicated that ER networks can be thought of as constrained minimal-length networks acted on by a variety of forces that perturb and/or remodel the network. Here, we study two specific biophysical processes involved in remodeling. One is the dynamic relaxation process involving a combination of tubule tension and viscous forces. The other is the rapid creation of cross-connection tubules by direct or indirect interactions with cytoskeletal elements. These processes are able to remodel the ER network: the first reduces network length and complexity whereas the second increases both. Using live cell imaging of ER network dynamics in tobacco leaf epidermal cells, we examine these processes on ER network dynamics. Away from regions of cytoplasmic streaming, we suggest that the dynamic network structure is a balance between the two processes, and we build an integrative model of the two processes for network remodeling. This model produces quantitatively similar ER networks to those observed in experiments. We use the model to explore the effect of parameter variation on statistical properties of the ER network. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Glass diffusion source for constraining BSF region of a solar cell

DOEpatents

Lesk, I.A.; Pryor, R.A.; Coleman, M.G.

1982-08-27

The present invention is directed to a method of fabricating a solar cell comprising simultaneous diffusion of the p and n dopant materials into the solar cell substrate. The simultaneous diffusion process is preceded by deposition of a capping layer impervious to doping by thermal diffusion processes.

Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network

PubMed Central

2012-01-01

Background Efforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature. Results Yeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model’s predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3. Conclusions Yeast 5 expands and refines the computational reconstruction of yeast metabolism and improves the predictive accuracy of a stoichiometrically constrained yeast metabolic model. It differs from previous reconstructions and models by emphasizing the distinction between the yeast metabolic reconstruction and the stoichiometrically constrained model, and makes both available as Additional file 4 and Additional file 5 and at http://yeast.sf.net/ as separate systems biology markup language (SBML) files. Through this separation, we intend to make the modeling process more accessible, explicit, transparent, and reproducible. PMID:22663945

Mechanical response and buckling of a polymer simulation model of the cell nucleus

NASA Astrophysics Data System (ADS)

Banigan, Edward; Stephens, Andrew; Marko, John

The cell nucleus must robustly resist extra- and intracellular forces to maintain genome architecture. Micromanipulation experiments measuring nuclear mechanical response reveal that the nucleus has two force response regimes: a linear short-extension response due to the chromatin interior and a stiffer long-extension response from lamin A, comprising the intermediate filament protein shell. To explain these results, we developed a quantitative simulation model with realistic parameters for chromatin and the lamina. Our model predicts that crosslinking between chromatin and the lamina is essential for responding to small strains and that changes to the interior topological organization can alter the mechanical response of the whole nucleus. Thus, chromatin polymer elasticity, not osmotic pressure, is the dominant regulator of this force response. Our model reveals a novel buckling transition for polymer shells: as force increases, the shell buckles transverse to the applied force. This transition, which arises from topological constrains in the lamina, can be mitigated by tuning the properties of the chromatin interior. Thus, we find that the genome is a resistive mechanical element that can be tuned by its organization and connectivity to the lamina.

Quorum sensing control of Type VI secretion factors restricts the proliferation of quorum-sensing mutants

PubMed Central

Majerczyk, Charlotte; Schneider, Emily; Greenberg, E Peter

2016-01-01

Burkholderia thailandensis uses acyl-homoserine lactone-mediated quorum sensing systems to regulate hundreds of genes. Here we show that cell-cell contact-dependent type VI secretion (T6S) toxin-immunity systems are among those activated by quorum sensing in B. thailandensis. We also demonstrate that T6S is required to constrain proliferation of quorum sensing mutants in colony cocultures of a BtaR1 quorum-sensing signal receptor mutant and its parent. However, the BtaR1 mutant is not constrained by and outcompetes its parent in broth coculture, presumably because no cell contact occurs and there is a metabolic cost associated with quorum sensing gene activation. The increased fitness of the wild type over the BtaR1 mutant during agar surface growth is dependent on an intact T6SS-1 apparatus. Thus, quorum sensing activates B. thailandensis T6SS-1 growth inhibition and this control serves to police and constrain quorum-sensing mutants. This work defines a novel role for T6SSs in intraspecies mutant control. DOI: http://dx.doi.org/10.7554/eLife.14712.001 PMID:27183270

Research on optimal DEM cell size for 3D visualization of loess terraces

NASA Astrophysics Data System (ADS)

Zhao, Weidong; Tang, Guo'an; Ji, Bin; Ma, Lei

2009-10-01

In order to represent the complex artificial terrains like loess terraces in Shanxi Province in northwest China, a new 3D visual method namely Terraces Elevation Incremental Visual Method (TEIVM) is put forth by the authors. 406 elevation points and 14 enclosed constrained lines are sampled according to the TIN-based Sampling Method (TSM) and DEM Elevation Points and Lines Classification (DEPLC). The elevation points and constrained lines are used to construct Constrained Delaunay Triangulated Irregular Networks (CD-TINs) of the loess terraces. In order to visualize the loess terraces well by use of optimal combination of cell size and Elevation Increment Value (EIV), the CD-TINs is converted to Grid-based DEM (G-DEM) by use of different combination of cell size and EIV with linear interpolating method called Bilinear Interpolation Method (BIM). Our case study shows that the new visual method can visualize the loess terraces steps very well when the combination of cell size and EIV is reasonable. The optimal combination is that the cell size is 1 m and the EIV is 6 m. Results of case study also show that the cell size should be at least smaller than half of both the terraces average width and the average vertical offset of terraces steps for representing the planar shapes of the terraces surfaces and steps well, while the EIV also should be larger than 4.6 times of the terraces average height. The TEIVM and results above is of great significance to the highly refined visualization of artificial terrains like loess terraces.

Alternative ways of using field-based estimates to calibrate ecosystem models and their implications for ecosystem carbon cycle studies

Treesearch

Y. He; Q. Zhuang; A.D. McGuire; Y. Liu; M. Chen

2013-01-01

Model-data fusion is a process in which field observations are used to constrain model parameters. How observations are used to constrain parameters has a direct impact on the carbon cycle dynamics simulated by ecosystem models. In this study, we present an evaluation of several options for the use of observations inmodeling regional carbon dynamics and explore the...

Hedonic price models with omitted variables and measurement errors: a constrained autoregression-structural equation modeling approach with application to urban Indonesia

NASA Astrophysics Data System (ADS)

Suparman, Yusep; Folmer, Henk; Oud, Johan H. L.

2014-01-01

Omitted variables and measurement errors in explanatory variables frequently occur in hedonic price models. Ignoring these problems leads to biased estimators. In this paper, we develop a constrained autoregression-structural equation model (ASEM) to handle both types of problems. Standard panel data models to handle omitted variables bias are based on the assumption that the omitted variables are time-invariant. ASEM allows handling of both time-varying and time-invariant omitted variables by constrained autoregression. In the case of measurement error, standard approaches require additional external information which is usually difficult to obtain. ASEM exploits the fact that panel data are repeatedly measured which allows decomposing the variance of a variable into the true variance and the variance due to measurement error. We apply ASEM to estimate a hedonic housing model for urban Indonesia. To get insight into the consequences of measurement error and omitted variables, we compare the ASEM estimates with the outcomes of (1) a standard SEM, which does not account for omitted variables, (2) a constrained autoregression model, which does not account for measurement error, and (3) a fixed effects hedonic model, which ignores measurement error and time-varying omitted variables. The differences between the ASEM estimates and the outcomes of the three alternative approaches are substantial.

A chance-constrained programming model to allocate wildfire initial attack resources for a fire season

Treesearch

Yu Wei; Michael Bevers; Erin Belval; Benjamin Bird

2015-01-01

This research developed a chance-constrained two-stage stochastic programming model to support wildfire initial attack resource acquisition and location on a planning unit for a fire season. Fire growth constraints account for the interaction between fire perimeter growth and construction to prevent overestimation of resource requirements. We used this model to examine...

Characterizing and modeling the free recovery and constrained recovery behavior of a polyurethane shape memory polymer

PubMed Central

Volk, Brent L; Lagoudas, Dimitris C; Maitland, Duncan J

2011-01-01

In this work, tensile tests and one-dimensional constitutive modeling are performed on a high recovery force polyurethane shape memory polymer that is being considered for biomedical applications. The tensile tests investigate the free recovery (zero load) response as well as the constrained displacement recovery (stress recovery) response at extension values up to 25%, and two consecutive cycles are performed during each test. The material is observed to recover 100% of the applied deformation when heated at zero load in the second thermomechanical cycle, and a stress recovery of 1.5 MPa to 4.2 MPa is observed for the constrained displacement recovery experiments. After performing the experiments, the Chen and Lagoudas model is used to simulate and predict the experimental results. The material properties used in the constitutive model – namely the coefficients of thermal expansion, shear moduli, and frozen volume fraction – are calibrated from a single 10% extension free recovery experiment. The model is then used to predict the material response for the remaining free recovery and constrained displacement recovery experiments. The model predictions match well with the experimental data. PMID:22003272

A global parallel model based design of experiments method to minimize model output uncertainty.

PubMed

Bazil, Jason N; Buzzard, Gregory T; Rundell, Ann E

2012-03-01

Model-based experiment design specifies the data to be collected that will most effectively characterize the biological system under study. Existing model-based design of experiment algorithms have primarily relied on Fisher Information Matrix-based methods to choose the best experiment in a sequential manner. However, these are largely local methods that require an initial estimate of the parameter values, which are often highly uncertain, particularly when data is limited. In this paper, we provide an approach to specify an informative sequence of multiple design points (parallel design) that will constrain the dynamical uncertainty of the biological system responses to within experimentally detectable limits as specified by the estimated experimental noise. The method is based upon computationally efficient sparse grids and requires only a bounded uncertain parameter space; it does not rely upon initial parameter estimates. The design sequence emerges through the use of scenario trees with experimental design points chosen to minimize the uncertainty in the predicted dynamics of the measurable responses of the system. The algorithm was illustrated herein using a T cell activation model for three problems that ranged in dimension from 2D to 19D. The results demonstrate that it is possible to extract useful information from a mathematical model where traditional model-based design of experiments approaches most certainly fail. The experiments designed via this method fully constrain the model output dynamics to within experimentally resolvable limits. The method is effective for highly uncertain biological systems characterized by deterministic mathematical models with limited data sets. Also, it is highly modular and can be modified to include a variety of methodologies such as input design and model discrimination.

Failure in lithium-ion batteries under transverse indentation loading

NASA Astrophysics Data System (ADS)

Chung, Seung Hyun; Tancogne-Dejean, Thomas; Zhu, Juner; Luo, Hailing; Wierzbicki, Tomasz

2018-06-01

Deformation and failure of constrained cells and modules in the battery pack under transverse loading is one of the most common conditions in batteries subjected to mechanical impacts. A combined experimental, numerical and analytical approach was undertaken to reveal the underlying mechanism and develop a new cell failure model. When large format pouch cells were subjected to local indentation all the way to failure, the post-mortem examination of the failure zones beneath the punches indicates a consistent slant fracture surface angle to the battery plane. This type of behavior can be described by the critical fracture plane theory in which fracture is caused by the shear stress modified by the normal stress. The Mohr-Coulomb fracture criterion is then postulated and it is shown how the two material constants can be determined from just one indentation test. The orientation of the fracture plane is invariant with respect to the type of loading and can be considered as a property of the cell stack. In addition, closed-form solutions are derived for the load-displacement relation for both plane-strain and axisymmetric cases. The results are in good agreement with the numerical simulation of the homogenized model and experimentally measured responses.

High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals.

PubMed

Marcon, Luciano; Diego, Xavier; Sharpe, James; Müller, Patrick

2016-04-08

The Turing reaction-diffusion model explains how identical cells can self-organize to form spatial patterns. It has been suggested that extracellular signaling molecules with different diffusion coefficients underlie this model, but the contribution of cell-autonomous signaling components is largely unknown. We developed an automated mathematical analysis to derive a catalog of realistic Turing networks. This analysis reveals that in the presence of cell-autonomous factors, networks can form a pattern with equally diffusing signals and even for any combination of diffusion coefficients. We provide a software (available at http://www.RDNets.com) to explore these networks and to constrain topologies with qualitative and quantitative experimental data. We use the software to examine the self-organizing networks that control embryonic axis specification and digit patterning. Finally, we demonstrate how existing synthetic circuits can be extended with additional feedbacks to form Turing reaction-diffusion systems. Our study offers a new theoretical framework to understand multicellular pattern formation and enables the wide-spread use of mathematical biology to engineer synthetic patterning systems.

High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals

PubMed Central

Marcon, Luciano; Diego, Xavier; Sharpe, James; Müller, Patrick

2016-01-01

The Turing reaction-diffusion model explains how identical cells can self-organize to form spatial patterns. It has been suggested that extracellular signaling molecules with different diffusion coefficients underlie this model, but the contribution of cell-autonomous signaling components is largely unknown. We developed an automated mathematical analysis to derive a catalog of realistic Turing networks. This analysis reveals that in the presence of cell-autonomous factors, networks can form a pattern with equally diffusing signals and even for any combination of diffusion coefficients. We provide a software (available at http://www.RDNets.com) to explore these networks and to constrain topologies with qualitative and quantitative experimental data. We use the software to examine the self-organizing networks that control embryonic axis specification and digit patterning. Finally, we demonstrate how existing synthetic circuits can be extended with additional feedbacks to form Turing reaction-diffusion systems. Our study offers a new theoretical framework to understand multicellular pattern formation and enables the wide-spread use of mathematical biology to engineer synthetic patterning systems. DOI: http://dx.doi.org/10.7554/eLife.14022.001 PMID:27058171

A chance-constrained stochastic approach to intermodal container routing problems.

PubMed

Zhao, Yi; Liu, Ronghui; Zhang, Xi; Whiteing, Anthony

2018-01-01

We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic transfer time, with the objective of minimising the expected total cost. Two chance constraints are proposed to ensure that the container service satisfies ship fulfilment and cargo on-time delivery with pre-specified probabilities. A hybrid heuristic algorithm is employed to solve the binary integer chance-constrained programming model. Two case studies are conducted to demonstrate the feasibility of the proposed model and to analyse the impact of stochastic variables and chance-constraints on the optimal solution and total cost.

A chance-constrained stochastic approach to intermodal container routing problems

PubMed Central

Zhao, Yi; Zhang, Xi; Whiteing, Anthony

2018-01-01

We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic transfer time, with the objective of minimising the expected total cost. Two chance constraints are proposed to ensure that the container service satisfies ship fulfilment and cargo on-time delivery with pre-specified probabilities. A hybrid heuristic algorithm is employed to solve the binary integer chance-constrained programming model. Two case studies are conducted to demonstrate the feasibility of the proposed model and to analyse the impact of stochastic variables and chance-constraints on the optimal solution and total cost. PMID:29438389

Pyramidal cell-interneuron interactions underlie hippocampal ripple oscillations.

PubMed

Stark, Eran; Roux, Lisa; Eichler, Ronny; Senzai, Yuta; Royer, Sebastien; Buzsáki, György

2014-07-16

High-frequency ripple oscillations, observed most prominently in the hippocampal CA1 pyramidal layer, are associated with memory consolidation. The cellular and network mechanisms underlying the generation, frequency control, and spatial coherence of the rhythm are poorly understood. Using multisite optogenetic manipulations in freely behaving rodents, we found that depolarization of a small group of nearby pyramidal cells was sufficient to induce high-frequency oscillations, whereas closed-loop silencing of pyramidal cells or activation of parvalbumin- (PV) or somatostatin-immunoreactive interneurons aborted spontaneously occurring ripples. Focal pharmacological blockade of GABAA receptors abolished ripples. Localized PV interneuron activation paced ensemble spiking, and simultaneous induction of high-frequency oscillations at multiple locations resulted in a temporally coherent pattern mediated by phase-locked interneuron spiking. These results constrain competing models of ripple generation and indicate that temporally precise local interactions between excitatory and inhibitory neurons support ripple generation in the intact hippocampus. Copyright © 2014 Elsevier Inc. All rights reserved.

Pyramidal Cell-Interneuron Interactions Underlie Hippocampal Ripple Oscillations

PubMed Central

Stark, Eran; Roux, Lisa; Eichler, Ronny; Senzai, Yuta; Royer, Sebastien; Buzsáki, György

2015-01-01

SUMMARY High-frequency ripple oscillations, observed most prominently in the hippocampal CA1 pyramidal layer, are associated with memory consolidation. The cellular and network mechanisms underlying the generation, frequency control, and spatial coherence of the rhythm are poorly understood. Using multisite optogenetic manipulations in freely behaving rodents, we found that depolarization of a small group of nearby pyramidal cells was sufficient to induce high-frequency oscillations, whereas closed-loop silencing of pyramidal cells or activation of parvalbumin-(PV) or somatostatin-immunoreactive interneurons aborted spontaneously occurring ripples. Focal pharmacological blockade of GABAA receptors abolished ripples. Localized PV inter-neuron activation paced ensemble spiking, and simultaneous induction of high-frequency oscillations at multiple locations resulted in a temporally coherent pattern mediated by phase-locked inter-neuron spiking. These results constrain competing models of ripple generation and indicate that temporally precise local interactions between excitatory and inhibitory neurons support ripple generation in the intact hippocampus. PMID:25033186

Encircling the dark: constraining dark energy via cosmic density in spheres

NASA Astrophysics Data System (ADS)

Codis, S.; Pichon, C.; Bernardeau, F.; Uhlemann, C.; Prunet, S.

2016-08-01

The recently published analytic probability density function for the mildly non-linear cosmic density field within spherical cells is used to build a simple but accurate maximum likelihood estimate for the redshift evolution of the variance of the density, which, as expected, is shown to have smaller relative error than the sample variance. This estimator provides a competitive probe for the equation of state of dark energy, reaching a few per cent accuracy on wp and wa for a Euclid-like survey. The corresponding likelihood function can take into account the configuration of the cells via their relative separations. A code to compute one-cell-density probability density functions for arbitrary initial power spectrum, top-hat smoothing and various spherical-collapse dynamics is made available online, so as to provide straightforward means of testing the effect of alternative dark energy models and initial power spectra on the low-redshift matter distribution.

Hydrologic and hydraulic flood forecasting constrained by remote sensing data

NASA Astrophysics Data System (ADS)

Li, Y.; Grimaldi, S.; Pauwels, V. R. N.; Walker, J. P.; Wright, A. J.

2017-12-01

Flooding is one of the most destructive natural disasters, resulting in many deaths and billions of dollars of damages each year. An indispensable tool to mitigate the effect of floods is to provide accurate and timely forecasts. An operational flood forecasting system typically consists of a hydrologic model, converting rainfall data into flood volumes entering the river system, and a hydraulic model, converting these flood volumes into water levels and flood extents. Such a system is prone to various sources of uncertainties from the initial conditions, meteorological forcing, topographic data, model parameters and model structure. To reduce those uncertainties, current forecasting systems are typically calibrated and/or updated using ground-based streamflow measurements, and such applications are limited to well-gauged areas. The recent increasing availability of spatially distributed remote sensing (RS) data offers new opportunities to improve flood forecasting skill. Based on an Australian case study, this presentation will discuss the use of 1) RS soil moisture to constrain a hydrologic model, and 2) RS flood extent and level to constrain a hydraulic model.The GRKAL hydrological model is calibrated through a joint calibration scheme using both ground-based streamflow and RS soil moisture observations. A lag-aware data assimilation approach is tested through a set of synthetic experiments to integrate RS soil moisture to constrain the streamflow forecasting in real-time.The hydraulic model is LISFLOOD-FP which solves the 2-dimensional inertial approximation of the Shallow Water Equations. Gauged water level time series and RS-derived flood extent and levels are used to apply a multi-objective calibration protocol. The effectiveness with which each data source or combination of data sources constrained the parameter space will be discussed.

Tests of chameleon gravity

NASA Astrophysics Data System (ADS)

Burrage, Clare; Sakstein, Jeremy

2018-03-01

Theories of modified gravity, where light scalars with non-trivial self-interactions and non-minimal couplings to matter—chameleon and symmetron theories—dynamically suppress deviations from general relativity in the solar system. On other scales, the environmental nature of the screening means that such scalars may be relevant. The highly-nonlinear nature of screening mechanisms means that they evade classical fifth-force searches, and there has been an intense effort towards designing new and novel tests to probe them, both in the laboratory and using astrophysical objects, and by reinterpreting existing datasets. The results of these searches are often presented using different parametrizations, which can make it difficult to compare constraints coming from different probes. The purpose of this review is to summarize the present state-of-the-art searches for screened scalars coupled to matter, and to translate the current bounds into a single parametrization to survey the state of the models. Presently, commonly studied chameleon models are well-constrained but less commonly studied models have large regions of parameter space that are still viable. Symmetron models are constrained well by astrophysical and laboratory tests, but there is a desert separating the two scales where the model is unconstrained. The coupling of chameleons to photons is tightly constrained but the symmetron coupling has yet to be explored. We also summarize the current bounds on f( R) models that exhibit the chameleon mechanism (Hu and Sawicki models). The simplest of these are well constrained by astrophysical probes, but there are currently few reported bounds for theories with higher powers of R. The review ends by discussing the future prospects for constraining screened modified gravity models further using upcoming and planned experiments.

In Vitro, Matrix-Free Formation Of Solid Tumor Spheroids

NASA Technical Reports Server (NTRS)

Gonda, Steve R.; Marley, Garry M.

1993-01-01

Cinostatic bioreactor promotes formation of relatively large solid tumor spheroids exhibiting diameters from 750 to 2,100 micrometers. Process useful in studying efficacy of chemotherapeutic agents and of interactions between cells not constrained by solid matrices. Two versions have been demonstrated; one for anchorage-independent cells and one for anchorage-dependent cells.

Dark matter, constrained minimal supersymmetric standard model, and lattice QCD.

PubMed

Giedt, Joel; Thomas, Anthony W; Young, Ross D

2009-11-13

Recent lattice measurements have given accurate estimates of the quark condensates in the proton. We use these results to significantly improve the dark matter predictions in benchmark models within the constrained minimal supersymmetric standard model. The predicted spin-independent cross sections are at least an order of magnitude smaller than previously suggested and our results have significant consequences for dark matter searches.

Comparisons of a Constrained Least Squares Model versus Human-in-the-Loop for Spectral Unmixing to Determine Material Type of GEO Debris

NASA Technical Reports Server (NTRS)

Abercromby, Kira J.; Rapp, Jason; Bedard, Donald; Seitzer, Patrick; Cardona, Tommaso; Cowardin, Heather; Barker, Ed; Lederer, Susan

2013-01-01

Constrained Linear Least Squares model is generally more accurate than the "human-in-the-loop". However, "human-in-the-loop" can remove materials that make no sense. The speed of the model in determining a "first cut" at the material ID makes it a viable option for spectral unmixing of debris objects.

Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

NASA Astrophysics Data System (ADS)

Quesada-Montano, Beatriz; Westerberg, Ida K.; Fuentes-Andino, Diana; Hidalgo-Leon, Hugo; Halldin, Sven

2017-04-01

Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information - to locally observed discharge - can be used to constrain model parameter uncertainty for ungauged catchments. Climate variability exerts a strong influence on streamflow variability on long and short time scales, in particular in the Central-American region. We therefore explored the use of climate variability knowledge to constrain the simulated discharge uncertainty of a conceptual hydrological model applied to a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty we first rejected parameter relationships that disagreed with our understanding of the system. We then assessed how well climate-based constraints applied at long-term, inter-annual and intra-annual time scales could constrain model uncertainty. Finally, we compared the climate-based constraints to a constraint on low-flow statistics based on information obtained from global maps. We evaluated our method in terms of the ability of the model to reproduce the observed hydrograph and the active catchment processes in terms of two efficiency measures, a statistical consistency measure, a spread measure and 17 hydrological signatures. We found that climate variability knowledge was useful for reducing model uncertainty, in particular, unrealistic representation of deep groundwater processes. The constraints based on global maps of low-flow statistics provided more constraining information than those based on climate variability, but the latter rejected slow rainfall-runoff representations that the low flow statistics did not reject. The use of such knowledge, together with information on low-flow statistics and constraints on parameter relationships showed to be useful to constrain model uncertainty for an - assumed to be - ungauged basin. This shows that our method is promising for reconstructing long-term flow data for ungauged catchments on the Pacific side of Central America, and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.

Simple growth patterns can create complex trajectories for the ontogeny of constitutive chemical defences in seaweeds.

PubMed

Paul, Nicholas A; Svensson, Carl Johan; de Nys, Rocky; Steinberg, Peter D

2014-01-01

All of the theory and most of the data on the ecology and evolution of chemical defences derive from terrestrial plants, which have considerable capacity for internal movement of resources. In contrast, most macroalgae--seaweeds--have no or very limited capacity for resource translocation, meaning that trade-offs between growth and defence, for example, should be localised rather than systemic. This may change the predictions of chemical defence theories for seaweeds. We developed a model that mimicked the simple growth pattern of the red seaweed Asparagopsis armata which is composed of repeating clusters of somatic cells and cells which contain deterrent secondary chemicals (gland cells). To do this we created a distinct growth curve for the somatic cells and another for the gland cells using empirical data. The somatic growth function was linked to the growth function for defence via differential equations modelling, which effectively generated a trade-off between growth and defence as these neighbouring cells develop. By treating growth and defence as separate functions we were also able to model a trade-off in growth of 2-3% under most circumstances. However, we found contrasting evidence for this trade-off in the empirical relationships between growth and defence, depending on the light level under which the alga was cultured. After developing a model that incorporated both branching and cell division rates, we formally demonstrated that positive correlations between growth and defence are predicted in many circumstances and also that allocation costs, if they exist, will be constrained by the intrinsic growth patterns of the seaweed. Growth patterns could therefore explain contrasting evidence for cost of constitutive chemical defence in many studies, highlighting the need to consider the fundamental biology and ontogeny of organisms when assessing the allocation theories for defence.

Improved design of constrained model predictive tracking control for batch processes against unknown uncertainties.

PubMed

Wu, Sheng; Jin, Qibing; Zhang, Ridong; Zhang, Junfeng; Gao, Furong

2017-07-01

In this paper, an improved constrained tracking control design is proposed for batch processes under uncertainties. A new process model that facilitates process state and tracking error augmentation with further additional tuning is first proposed. Then a subsequent controller design is formulated using robust stable constrained MPC optimization. Unlike conventional robust model predictive control (MPC), the proposed method enables the controller design to bear more degrees of tuning so that improved tracking control can be acquired, which is very important since uncertainties exist inevitably in practice and cause model/plant mismatches. An injection molding process is introduced to illustrate the effectiveness of the proposed MPC approach in comparison with conventional robust MPC. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Copy number variants calling for single cell sequencing data by multi-constrained optimization.

PubMed

Xu, Bo; Cai, Hongmin; Zhang, Changsheng; Yang, Xi; Han, Guoqiang

2016-08-01

Variations in DNA copy number carry important information on genome evolution and regulation of DNA replication in cancer cells. The rapid development of single-cell sequencing technology allows one to explore gene expression heterogeneity among single-cells, thus providing important cancer cell evolution information. Single-cell DNA/RNA sequencing data usually have low genome coverage, which requires an extra step of amplification to accumulate enough samples. However, such amplification will introduce large bias and makes bioinformatics analysis challenging. Accurately modeling the distribution of sequencing data and effectively suppressing the bias influence is the key to success variations analysis. Recent advances demonstrate the technical noises by amplification are more likely to follow negative binomial distribution, a special case of Poisson distribution. Thus, we tackle the problem CNV detection by formulating it into a quadratic optimization problem involving two constraints, in which the underling signals are corrupted by Poisson distributed noises. By imposing the constraints of sparsity and smoothness, the reconstructed read depth signals from single-cell sequencing data are anticipated to fit the CNVs patterns more accurately. An efficient numerical solution based on the classical alternating direction minimization method (ADMM) is tailored to solve the proposed model. We demonstrate the advantages of the proposed method using both synthetic and empirical single-cell sequencing data. Our experimental results demonstrate that the proposed method achieves excellent performance and high promise of success with single-cell sequencing data. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Information dynamics in carcinogenesis and tumor growth.

PubMed

Gatenby, Robert A; Frieden, B Roy

2004-12-21

The storage and transmission of information is vital to the function of normal and transformed cells. We use methods from information theory and Monte Carlo theory to analyze the role of information in carcinogenesis. Our analysis demonstrates that, during somatic evolution of the malignant phenotype, the accumulation of genomic mutations degrades intracellular information. However, the degradation is constrained by the Darwinian somatic ecology in which mutant clones proliferate only when the mutation confers a selective growth advantage. In that environment, genes that normally decrease cellular proliferation, such as tumor suppressor or differentiation genes, suffer maximum information degradation. Conversely, those that increase proliferation, such as oncogenes, are conserved or exhibit only gain of function mutations. These constraints shield most cellular populations from catastrophic mutator-induced loss of the transmembrane entropy gradient and, therefore, cell death. The dynamics of constrained information degradation during carcinogenesis cause the tumor genome to asymptotically approach a minimum information state that is manifested clinically as dedifferentiation and unconstrained proliferation. Extreme physical information (EPI) theory demonstrates that altered information flow from cancer cells to their environment will manifest in-vivo as power law tumor growth with an exponent of size 1.62. This prediction is based only on the assumption that tumor cells are at an absolute information minimum and are capable of "free field" growth that is, they are unconstrained by external biological parameters. The prediction agrees remarkably well with several studies demonstrating power law growth in small human breast cancers with an exponent of 1.72+/-0.24. This successful derivation of an analytic expression for cancer growth from EPI alone supports the conceptual model that carcinogenesis is a process of constrained information degradation and that malignant cells are minimum information systems. EPI theory also predicts that the estimated age of a clinically observed tumor is subject to a root-mean square error of about 30%. This is due to information loss and tissue disorganization and probably manifests as a randomly variable lag phase in the growth pattern that has been observed experimentally. This difference between tumor size and age may impose a fundamental limit on the efficacy of screening based on early detection of small tumors. Independent of the EPI analysis, Monte Carlo methods are applied to predict statistical tumor growth due to perturbed information flow from the environment into transformed cells. A "simplest" Monte Carlo model is suggested by the findings in the EPI approach that tumor growth arises out of a minimally complex mechanism. The outputs of large numbers of simulations show that (a) about 40% of the populations do not survive the first two-generations due to mutations in critical gene segments; but (b) those that do survive will experience power law growth identical to the predicted rate obtained from the independent EPI approach. The agreement between these two very different approaches to the problem strongly supports the idea that tumor cells regress to a state of minimum information during carcinogenesis, and that information dynamics are integrally related to tumor development and growth.

Using seismically constrained magnetotelluric inversion to recover velocity structure in the shallow lithosphere

NASA Astrophysics Data System (ADS)

Moorkamp, M.; Fishwick, S.; Jones, A. G.

2015-12-01

Typical surface wave tomography can recover well the velocity structure of the upper mantle in the depth range between 70-200km. For a successful inversion, we have to constrain the crustal structure and assess the impact on the resulting models. In addition,we often observe potentially interesting features in the uppermost lithosphere which are poorly resolved and thus their interpretationhas to be approached with great care.We are currently developing a seismically constrained magnetotelluric (MT) inversion approach with the aim of better recovering the lithospheric properties (and thus seismic velocities) in these problematic areas. We perform a 3D MT inversion constrained by a fixed seismic velocity model from surface wave tomography. In order to avoid strong bias, we only utilize information on structural boundaries to combine these two methods. Within the region that is well resolved by both methods, we can then extract a velocity-conductivity relationship. By translating the conductivitiesretrieved from MT into velocities in areas where the velocity model is poorly resolved, we can generate an updated velocity model and test what impactthe updated velocities have on the predicted data.We test this new approach using a MT dataset acquired in central Botswana over the Okwa terrane and the adjacent Kaapvaal and Zimbabwe Cratons togetherwith a tomographic models for the region. Here, both datasets have previously been used to constrain lithospheric structure and show some similarities.We carefully asses the validity of our results by comparing with observations and petrophysical predictions for the conductivity-velocity relationship.

Periodic Forced Response of Structures Having Three-Dimensional Frictional Constraints

NASA Astrophysics Data System (ADS)

CHEN, J. J.; YANG, B. D.; MENQ, C. H.

2000-01-01

Many mechanical systems have moving components that are mutually constrained through frictional contacts. When subjected to cyclic excitations, a contact interface may undergo constant changes among sticks, slips and separations, which leads to very complex contact kinematics. In this paper, a 3-D friction contact model is employed to predict the periodic forced response of structures having 3-D frictional constraints. Analytical criteria based on this friction contact model are used to determine the transitions among sticks, slips and separations of the friction contact, and subsequently the constrained force which consists of the induced stick-slip friction force on the contact plane and the contact normal load. The resulting constrained force is often a periodic function and can be considered as a feedback force that influences the response of the constrained structures. By using the Multi-Harmonic Balance Method along with Fast Fourier Transform, the constrained force can be integrated with the receptance of the structures so as to calculate the forced response of the constrained structures. It results in a set of non-linear algebraic equations that can be solved iteratively to yield the relative motion as well as the constrained force at the friction contact. This method is used to predict the periodic response of a frictionally constrained 3-d.o.f. oscillator. The predicted results are compared with those of the direct time integration method so as to validate the proposed method. In addition, the effect of super-harmonic components on the resonant response and jump phenomenon is examined.

Water Budget Estimation by Assimilating Multiple Observations and Hydrological Modeling Using Constrained Ensemble Kalman Filtering

NASA Astrophysics Data System (ADS)

Pan, M.; Wood, E. F.

2004-05-01

This study explores a method to estimate various components of the water cycle (ET, runoff, land storage, etc.) based on a number of different info sources, including both observations and observation-enhanced model simulations. Different from existing data assimilations, this constrained Kalman filtering approach keeps the water budget perfectly closed while updating the states of the underlying model (VIC model) optimally using observations. Assimilating different data sources in this way has several advantages: (1) physical model is included to make estimation time series smooth, missing-free, and more physically consistent; (2) uncertainties in the model and observations are properly addressed; (3) model is constrained by observation thus to reduce model biases; (4) balance of water is always preserved along the assimilation. Experiments are carried out in Southern Great Plain region where necessary observations have been collected. This method may also be implemented in other applications with physical constraints (e.g. energy cycles) and at different scales.

Reconsidering Cluster Bias in Multilevel Data: A Monte Carlo Comparison of Free and Constrained Baseline Approaches.

PubMed

Guenole, Nigel

2018-01-01

The test for item level cluster bias examines the improvement in model fit that results from freeing an item's between level residual variance from a baseline model with equal within and between level factor loadings and between level residual variances fixed at zero. A potential problem is that this approach may include a misspecified unrestricted model if any non-invariance is present, but the log-likelihood difference test requires that the unrestricted model is correctly specified. A free baseline approach where the unrestricted model includes only the restrictions needed for model identification should lead to better decision accuracy, but no studies have examined this yet. We ran a Monte Carlo study to investigate this issue. When the referent item is unbiased, compared to the free baseline approach, the constrained baseline approach led to similar true positive (power) rates but much higher false positive (Type I error) rates. The free baseline approach should be preferred when the referent indicator is unbiased. When the referent assumption is violated, the false positive rate was unacceptably high for both free and constrained baseline approaches, and the true positive rate was poor regardless of whether the free or constrained baseline approach was used. Neither the free or constrained baseline approach can be recommended when the referent indicator is biased. We recommend paying close attention to ensuring the referent indicator is unbiased in tests of cluster bias. All Mplus input and output files, R, and short Python scripts used to execute this simulation study are uploaded to an open access repository.

Reconsidering Cluster Bias in Multilevel Data: A Monte Carlo Comparison of Free and Constrained Baseline Approaches

PubMed Central

Guenole, Nigel

2018-01-01

The test for item level cluster bias examines the improvement in model fit that results from freeing an item's between level residual variance from a baseline model with equal within and between level factor loadings and between level residual variances fixed at zero. A potential problem is that this approach may include a misspecified unrestricted model if any non-invariance is present, but the log-likelihood difference test requires that the unrestricted model is correctly specified. A free baseline approach where the unrestricted model includes only the restrictions needed for model identification should lead to better decision accuracy, but no studies have examined this yet. We ran a Monte Carlo study to investigate this issue. When the referent item is unbiased, compared to the free baseline approach, the constrained baseline approach led to similar true positive (power) rates but much higher false positive (Type I error) rates. The free baseline approach should be preferred when the referent indicator is unbiased. When the referent assumption is violated, the false positive rate was unacceptably high for both free and constrained baseline approaches, and the true positive rate was poor regardless of whether the free or constrained baseline approach was used. Neither the free or constrained baseline approach can be recommended when the referent indicator is biased. We recommend paying close attention to ensuring the referent indicator is unbiased in tests of cluster bias. All Mplus input and output files, R, and short Python scripts used to execute this simulation study are uploaded to an open access repository. PMID:29551985

Trajectory optimization and guidance law development for national aerospace plane applications

NASA Technical Reports Server (NTRS)

Calise, A. J.; Flandro, G. A.; Corban, J. E.

1988-01-01

The work completed to date is comprised of the following: a simple vehicle model representative of the aerospace plane concept in the hypersonic flight regime, fuel-optimal climb profiles for the unconstrained and dynamic pressure constrained cases generated using a reduced order dynamic model, an analytic switching condition for transition to rocket powered flight as orbital velocity is approached, simple feedback guidance laws for both the unconstrained and dynamic pressure constrained cases derived via singular perturbation theory and a nonlinear transformation technique, and numerical simulation results for ascent to orbit in the dynamic pressure constrained case.

Constraints on Dark Energy from Baryon Acoustic Peak and Galaxy Cluster Gas Mass Measurements

NASA Astrophysics Data System (ADS)

Samushia, Lado; Ratra, Bharat

2009-10-01

We use baryon acoustic peak measurements by Eisenstein et al. and Percival et al., together with the Wilkinson Microwave Anisotropy Probe (WMAP) measurement of the apparent acoustic horizon angle, and galaxy cluster gas mass fraction measurements of Allen et al., to constrain a slowly rolling scalar field dark energy model, phiCDM, in which dark energy's energy density changes in time. We also compare our phiCDM results with those derived for two more common dark energy models: the time-independent cosmological constant model, ΛCDM, and the XCDM parameterization of dark energy's equation of state. For time-independent dark energy, the Percival et al. measurements effectively constrain spatial curvature and favor a close to the spatially flat model, mostly due to the WMAP cosmic microwave background prior used in the analysis. In a spatially flat model the Percival et al. data less effectively constrain time-varying dark energy. The joint baryon acoustic peak and galaxy cluster gas mass constraints on the phiCDM model are consistent with but tighter than those derived from other data. A time-independent cosmological constant in a spatially flat model provides a good fit to the joint data, while the α parameter in the inverse power-law potential phiCDM model is constrained to be less than about 4 at 3σ confidence level.

Cosmicflows Constrained Local UniversE Simulations

NASA Astrophysics Data System (ADS)

Sorce, Jenny G.; Gottlöber, Stefan; Yepes, Gustavo; Hoffman, Yehuda; Courtois, Helene M.; Steinmetz, Matthias; Tully, R. Brent; Pomarède, Daniel; Carlesi, Edoardo

2016-01-01

This paper combines observational data sets and cosmological simulations to generate realistic numerical replicas of the nearby Universe. The latter are excellent laboratories for studies of the non-linear process of structure formation in our neighbourhood. With measurements of radial peculiar velocities in the local Universe (cosmicflows-2) and a newly developed technique, we produce Constrained Local UniversE Simulations (CLUES). To assess the quality of these constrained simulations, we compare them with random simulations as well as with local observations. The cosmic variance, defined as the mean one-sigma scatter of cell-to-cell comparison between two fields, is significantly smaller for the constrained simulations than for the random simulations. Within the inner part of the box where most of the constraints are, the scatter is smaller by a factor of 2 to 3 on a 5 h-1 Mpc scale with respect to that found for random simulations. This one-sigma scatter obtained when comparing the simulated and the observation-reconstructed velocity fields is only 104 ± 4 km s-1, I.e. the linear theory threshold. These two results demonstrate that these simulations are in agreement with each other and with the observations of our neighbourhood. For the first time, simulations constrained with observational radial peculiar velocities resemble the local Universe up to a distance of 150 h-1 Mpc on a scale of a few tens of megaparsecs. When focusing on the inner part of the box, the resemblance with our cosmic neighbourhood extends to a few megaparsecs (<5 h-1 Mpc). The simulations provide a proper large-scale environment for studies of the formation of nearby objects.

Spatial organization of the budding yeast genome in the cell nucleus and identification of specific chromatin interactions from multi-chromosome constrained chromatin model.

PubMed

Gürsoy, Gamze; Xu, Yun; Liang, Jie

2017-07-01

Nuclear landmarks and biochemical factors play important roles in the organization of the yeast genome. The interaction pattern of budding yeast as measured from genome-wide 3C studies are largely recapitulated by model polymer genomes subject to landmark constraints. However, the origin of inter-chromosomal interactions, specific roles of individual landmarks, and the roles of biochemical factors in yeast genome organization remain unclear. Here we describe a multi-chromosome constrained self-avoiding chromatin model (mC-SAC) to gain understanding of the budding yeast genome organization. With significantly improved sampling of genome structures, both intra- and inter-chromosomal interaction patterns from genome-wide 3C studies are accurately captured in our model at higher resolution than previous studies. We show that nuclear confinement is a key determinant of the intra-chromosomal interactions, and centromere tethering is responsible for the inter-chromosomal interactions. In addition, important genomic elements such as fragile sites and tRNA genes are found to be clustered spatially, largely due to centromere tethering. We uncovered previously unknown interactions that were not captured by genome-wide 3C studies, which are found to be enriched with tRNA genes, RNAPIII and TFIIS binding. Moreover, we identified specific high-frequency genome-wide 3C interactions that are unaccounted for by polymer effects under landmark constraints. These interactions are enriched with important genes and likely play biological roles.

Changes in brain cell shape create residual extracellular space volume and explain tortuosity behavior during osmotic challenge.

PubMed

Chen, K C; Nicholson, C

2000-07-18

Diffusion of molecules in brain extracellular space is constrained by two macroscopic parameters, tortuosity factor lambda and volume fraction alpha. Recent studies in brain slices show that when osmolarity is reduced, lambda increases while alpha decreases. In contrast, with increased osmolarity, alpha increases, but lambda attains a plateau. Using homogenization theory and a variety of lattice models, we found that the plateau behavior of lambda can be explained if the shape of brain cells changes nonuniformly during the shrinking or swelling induced by osmotic challenge. The nonuniform cellular shrinkage creates residual extracellular space that temporarily traps diffusing molecules, thus impeding the macroscopic diffusion. The paper also discusses the definition of tortuosity and its independence of the measurement frame of reference.

Critical Robotic Lunar Missions

NASA Astrophysics Data System (ADS)

Plescia, J. B.

2018-04-01

Perhaps the most critical missions to understanding lunar history are in situ dating and network missions. These would constrain the volcanic and thermal history and interior structure. These data would better constrain lunar evolution models.

Universally Sloppy Parameter Sensitivities in Systems Biology Models

PubMed Central

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-01-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a “sloppy” spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters. PMID:17922568

Universally sloppy parameter sensitivities in systems biology models.

PubMed

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

An interval chance-constrained fuzzy modeling approach for supporting land-use planning and eco-environment planning at a watershed level.

PubMed

Ou, Guoliang; Tan, Shukui; Zhou, Min; Lu, Shasha; Tao, Yinghui; Zhang, Zuo; Zhang, Lu; Yan, Danping; Guan, Xingliang; Wu, Gang

2017-12-15

An interval chance-constrained fuzzy land-use allocation (ICCF-LUA) model is proposed in this study to support solving land resource management problem associated with various environmental and ecological constraints at a watershed level. The ICCF-LUA model is based on the ICCF (interval chance-constrained fuzzy) model which is coupled with interval mathematical model, chance-constrained programming model and fuzzy linear programming model and can be used to deal with uncertainties expressed as intervals, probabilities and fuzzy sets. Therefore, the ICCF-LUA model can reflect the tradeoff between decision makers and land stakeholders, the tradeoff between the economical benefits and eco-environmental demands. The ICCF-LUA model has been applied to the land-use allocation of Wujiang watershed, Guizhou Province, China. The results indicate that under highly land suitable conditions, optimized area of cultivated land, forest land, grass land, construction land, water land, unused land and landfill in Wujiang watershed will be [5015, 5648] hm 2 , [7841, 7965] hm 2 , [1980, 2056] hm 2 , [914, 1423] hm 2 , [70, 90] hm 2 , [50, 70] hm 2 and [3.2, 4.3] hm 2 , the corresponding system economic benefit will be between 6831 and 7219 billion yuan. Consequently, the ICCF-LUA model can effectively support optimized land-use allocation problem in various complicated conditions which include uncertainties, risks, economic objective and eco-environmental constraints. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimization of Modeled Land-Atmosphere Exchanges of Water and Energy in an Isotopically-Enabled Land Surface Model by Bayesian Parameter Calibration

NASA Astrophysics Data System (ADS)

Wong, T. E.; Noone, D. C.; Kleiber, W.

2014-12-01

The single largest uncertainty in climate model energy balance is the surface latent heating over tropical land. Furthermore, the partitioning of the total latent heat flux into contributions from surface evaporation and plant transpiration is of great importance, but notoriously poorly constrained. Resolving these issues will require better exploiting information which lies at the interface between observations and advanced modeling tools, both of which are imperfect. There are remarkably few observations which can constrain these fluxes, placing strict requirements on developing statistical methods to maximize the use of limited information to best improve models. Previous work has demonstrated the power of incorporating stable water isotopes into land surface models for further constraining ecosystem processes. We present results from a stable water isotopically-enabled land surface model (iCLM4), including model experiments partitioning the latent heat flux into contributions from plant transpiration and surface evaporation. It is shown that the partitioning results are sensitive to the parameterization of kinetic fractionation used. We discuss and demonstrate an approach to calibrating select model parameters to observational data in a Bayesian estimation framework, requiring Markov Chain Monte Carlo sampling of the posterior distribution, which is shown to constrain uncertain parameters as well as inform relevant values for operational use. Finally, we discuss the application of the estimation scheme to iCLM4, including entropy as a measure of information content and specific challenges which arise in calibration models with a large number of parameters.

Minimal models from W-constrained hierarchies via the Kontsevich-Miwa transform

NASA Astrophysics Data System (ADS)

Gato-Rivera, B.; Semikhatov, A. M.

1992-08-01

A direct relation between the conformal formalism for 2D quantum gravity and the W-constrained KP hierarchy is found, without the need to invoke intermediate matrix model technology. The Kontsevich-Miwa transform of the KP hierarchy is used to establish an identification between W constraints on the KP tau function and decoupling equations corresponding to Virasoro null vectors. The Kontsevich-Miwa transform maps the W ( l) -constrained KP hierarchy to the ( p‧, p‧) minimal model, with the tau function being given by the correlator of a product of (dressed) ( l, 1) [or (1, l)] operators, provided the Miwa parameter ni and the free parameter (an abstract bc spin) present in the constraint are expressed through the ratio p‧/ p and the level l.

Combined constraints on the structure and physical properties of the East Antarctic lithosphere from geology and geophysics.

NASA Astrophysics Data System (ADS)

Reading, A. M.; Staal, T.; Halpin, J.; Whittaker, J. M.; Morse, P. E.

2017-12-01

The lithosphere of East Antarctica is one of the least explored regions of the planet, yet it is gaining in importance in global scientific research. Continental heat flux density and 3D glacial isostatic adjustment studies, for example, rely on a good knowledge of the deep structure in constraining model inputs.In this contribution, we use a multidisciplinary approach to constrain lithospheric domains. To seismic tomography models, we add constraints from magnetic studies and also new geological constraints. Geological knowledge exists around the periphery of East Antarctica and is reinforced in the knowledge of plate tectonic reconstructions. The subglacial geology of the Antarctic hinterland is largely unknown but the plate reconstructions allow the well-posed extrapolation of major terranes into the interior of the continent, guided by the seismic tomography and magnetic images. We find that the northern boundary of the lithospheric domain centred on the Gamburtsev Subglacial Mountains has a possible trend that runs south of the Lambert Glacier region, turning coastward through Wilkes Land. Other periphery-to-interior connections are less well constrained and the possibility of lithospheric domains that are entirely sub-glacial is high. We develop this framework to include a probabilistic method of handling alternate models and quantifiable uncertainties. We also show first results in using a Bayesian approach to predicting lithospheric boundaries from multivariate data.Within the newly constrained domains, we constrain heat flux (density) as the sum of basal heat flux and upper crustal heat flux. The basal heat flux is constrained by geophysical methods while the upper crustal heat flux is constrained by geology or predicted geology. In addition to heat flux constraints, we also consider the variations in friction experienced by moving ice sheets due to varying geology.

An Experimental Comparison of Similarity Assessment Measures for 3D Models on Constrained Surface Deformation

NASA Astrophysics Data System (ADS)

Quan, Lulin; Yang, Zhixin

2010-05-01

To address the issues in the area of design customization, this paper expressed the specification and application of the constrained surface deformation, and reported the experimental performance comparison of three prevail effective similarity assessment algorithms on constrained surface deformation domain. Constrained surface deformation becomes a promising method that supports for various downstream applications of customized design. Similarity assessment is regarded as the key technology for inspecting the success of new design via measuring the difference level between the deformed new design and the initial sample model, and indicating whether the difference level is within the limitation. According to our theoretical analysis and pre-experiments, three similarity assessment algorithms are suitable for this domain, including shape histogram based method, skeleton based method, and U system moment based method. We analyze their basic functions and implementation methodologies in detail, and do a series of experiments on various situations to test their accuracy and efficiency using precision-recall diagram. Shoe model is chosen as an industrial example for the experiments. It shows that shape histogram based method gained an optimal performance in comparison. Based on the result, we proposed a novel approach that integrating surface constrains and shape histogram description with adaptive weighting method, which emphasize the role of constrains during the assessment. The limited initial experimental result demonstrated that our algorithm outperforms other three algorithms. A clear direction for future development is also drawn at the end of the paper.

Patient-calibrated agent-based modelling of ductal carcinoma in situ (DCIS): From microscopic measurements to macroscopic predictions of clinical progression

PubMed Central

Macklin, Paul; Edgerton, Mary E.; Thompson, Alastair M.; Cristini, Vittorio

2012-01-01

Ductal carcinoma in situ (DCIS)—a significant precursor to invasive breast cancer—is typically diagnosed as microcalcifications in mammograms. However, the effective use of mammograms and other patient data to plan treatment has been restricted by our limited understanding of DCIS growth and calcification. We develop a mechanistic, agent-based cell model and apply it to DCIS. Cell motion is determined by a balance of biomechanical forces. We use potential functions to model interactions with the basement membrane and amongst cells of unequal size and phenotype. Each cell’s phenotype is determined by genomic/proteomic- and microenvironment-dependent stochastic processes. Detailed “sub-models” describe cell volume changes during proliferation and necrosis; we are the first to account for cell calcification. We introduce the first patient-specific calibration method to fully constrain the model based upon clinically-accessible histopathology data. After simulating 45 days of solid-type DCIS with comedonecrosis, the model predicts: necrotic cell lysis acts as a biomechanical stress relief, and is responsible for the linear DCIS growth observed in mammography; the rate of DCIS advance varies with the duct radius; the tumour grows 7 to 10 mm per year—consistent with mammographic data; and the mammographic and (post-operative) pathologic sizes are linearly correlated—in quantitative agreement with the clinical literature. Patient histopathology matches the predicted DCIS microstructure: an outer proliferative rim surrounds a stratified necrotic core with nuclear debris on its outer edge and calcification in the centre. This work illustrates that computational modelling can provide new insight on the biophysical underpinnings of cancer. It may one day be possible to augment a patient’s mammography and other imaging with rigorously-calibrated models that help select optimal surgical margins based upon the patient’s histopathologic data. PMID:22342935

A semi-Markov model for mitosis segmentation in time-lapse phase contrast microscopy image sequences of stem cell populations.

PubMed

Liu, An-An; Li, Kang; Kanade, Takeo

2012-02-01

We propose a semi-Markov model trained in a max-margin learning framework for mitosis event segmentation in large-scale time-lapse phase contrast microscopy image sequences of stem cell populations. Our method consists of three steps. First, we apply a constrained optimization based microscopy image segmentation method that exploits phase contrast optics to extract candidate subsequences in the input image sequence that contains mitosis events. Then, we apply a max-margin hidden conditional random field (MM-HCRF) classifier learned from human-annotated mitotic and nonmitotic sequences to classify each candidate subsequence as a mitosis or not. Finally, a max-margin semi-Markov model (MM-SMM) trained on manually-segmented mitotic sequences is utilized to reinforce the mitosis classification results, and to further segment each mitosis into four predefined temporal stages. The proposed method outperforms the event-detection CRF model recently reported by Huh as well as several other competing methods in very challenging image sequences of multipolar-shaped C3H10T1/2 mesenchymal stem cells. For mitosis detection, an overall precision of 95.8% and a recall of 88.1% were achieved. For mitosis segmentation, the mean and standard deviation for the localization errors of the start and end points of all mitosis stages were well below 1 and 2 frames, respectively. In particular, an overall temporal location error of 0.73 ± 1.29 frames was achieved for locating daughter cell birth events.

Adaptive model-predictive controller for magnetic resonance guided focused ultrasound therapy.

PubMed

de Bever, Joshua; Todd, Nick; Payne, Allison; Christensen, Douglas A; Roemer, Robert B

2014-11-01

Minimising treatment time and protecting healthy tissues are conflicting goals that play major roles in making magnetic resonance image-guided focused ultrasound (MRgFUS) therapies clinically practical. We have developed and tested in vivo an adaptive model-predictive controller (AMPC) that reduces treatment time, ensures safety and efficacy, and provides flexibility in treatment set-up. The controller realises time savings by modelling the heated treatment cell's future temperatures and thermal dose accumulation in order to anticipate the optimal time to switch to the next cell. Selected tissues are safeguarded by a configurable temperature constraint. Simulations quantified the time savings realised by each controller feature as well as the trade-offs between competing safety and treatment time parameters. In vivo experiments in rabbit thighs established the controller's effectiveness and reliability. In all in vivo experiments the target thermal dose of at least 240 CEM43 was delivered everywhere in the treatment volume. The controller's temperature safety limit reliably activated and constrained all protected tissues to <9 CEM43. Simulations demonstrated the path independence of the controller, and that a path which successively proceeds to the hottest untreated neighbouring cell leads to significant time savings, e.g. when compared to a concentric spiral path. Use of the AMPC produced a compounding time-saving effect; reducing the treatment cells' heating times concurrently reduced heating of normal tissues, which eliminated cooling periods. Adaptive model-predictive control can automatically deliver safe, effective MRgFUS treatments while significantly reducing treatment times.

Small-kernel, constrained least-squares restoration of sampled image data

NASA Technical Reports Server (NTRS)

Hazra, Rajeeb; Park, Stephen K.

1992-01-01

Following the work of Park (1989), who extended a derivation of the Wiener filter based on the incomplete discrete/discrete model to a more comprehensive end-to-end continuous/discrete/continuous model, it is shown that a derivation of the constrained least-squares (CLS) filter based on the discrete/discrete model can also be extended to this more comprehensive continuous/discrete/continuous model. This results in an improved CLS restoration filter, which can be efficiently implemented as a small-kernel convolution in the spatial domain.

Shape selection criterion for cellular array during constrained growth of binary alloys - Need for low gravity experiment

NASA Technical Reports Server (NTRS)

Tewari, Surendra N.; Trivedi, Rohit

1991-01-01

Development of steady-state periodic cellular array is one of the critical problems in the study of nonlinear pattern formation during directional solidification of binary alloys. The criterion which establishes the values of cell tip radius and spacing under given growth condition is not known. Theoretical models, such as marginal stability and microscopic solvability, have been developed for purely diffusive regime. However, the experimental conditions where cellular structures are stable are precisely the ones where the convection effects are predominant. Thus, the critical data for meaningful evaluation of cellular array growth models can only be obtained by partial directional solidification and quenching experiments carried out in the low gravity environment of space.

Mathematical Modeling of the Origins of Life

NASA Technical Reports Server (NTRS)

Pohorille, Andrew

2006-01-01

The emergence of early metabolism - a network of catalyzed chemical reactions that supported self-maintenance, growth, reproduction and evolution of the ancestors of contemporary cells (protocells) was a critical, but still very poorly understood step on the path from inanimate to animate matter. Here, it is proposed and tested through mathematical modeling of biochemically plausible systems that the emergence of metabolism and its initial evolution towards higher complexity preceded the emergence of a genome. Even though the formation of protocellular metabolism was driven by non-genomic, highly stochastic processes the outcome was largely deterministic, strongly constrained by laws of chemistry. It is shown that such concepts as speciation and fitness to the environment, developed in the context of genomic evolution, also held in the absence of a genome.

Momentum Flux Estimates for South Georgia Island Mountain Waves in the Stratosphere Observed via Satellite

NASA Technical Reports Server (NTRS)

Alexander, M. Joan; Eckermann, Stephen D.; Broutman, Dave; Ma, Jun

2009-01-01

We show high-resolution satellite observations of mountain wave events in the stratosphere above South Georgia Island in the remote southern Atlantic Ocean and compute the wave momentum fluxes for these events. The fluxes are large, and they imply important drag forces on the circulation. Small island orography is generally neglected in mountain wave parameterizations used in global climate models because limited model resolution treats the grid cell containing the island as ocean rather than land. Our results show that satellite observations can be used to quantitatively constrain mountain wave momentum fluxes, and they suggest that mountain waves from island topography may be an important missing source of drag on the atmospheric circulation.

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT

PubMed Central

Choudhary, Kumari Sonal; Rohatgi, Neha; Briem, Eirikur; Gudjonsson, Thorarinn; Gudmundsson, Steinn; Rolfsson, Ottar

2016-01-01

Epithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E) and mesenchymal (EGFR_M) networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend. PMID:27253373

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

PubMed

Choudhary, Kumari Sonal; Rohatgi, Neha; Halldorsson, Skarphedinn; Briem, Eirikur; Gudjonsson, Thorarinn; Gudmundsson, Steinn; Rolfsson, Ottar

2016-06-01

Epithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E) and mesenchymal (EGFR_M) networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.

How well can future CMB missions constrain cosmic inflation?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, Jérôme; Vennin, Vincent; Ringeval, Christophe, E-mail: jmartin@iap.fr, E-mail: christophe.ringeval@uclouvain.be, E-mail: vennin@iap.fr

2014-10-01

We study how the next generation of Cosmic Microwave Background (CMB) measurement missions (such as EPIC, LiteBIRD, PRISM and COrE) will be able to constrain the inflationary landscape in the hardest to disambiguate situation in which inflation is simply described by single-field slow-roll scenarios. Considering the proposed PRISM and LiteBIRD satellite designs, we simulate mock data corresponding to five different fiducial models having values of the tensor-to-scalar ratio ranging from 10{sup -1} down to 10{sup -7}. We then compute the Bayesian evidences and complexities of all Encyclopædia Inflationaris models in order to assess the constraining power of PRISM alone andmore » LiteBIRD complemented with the Planck 2013 data. Within slow-roll inflation, both designs have comparable constraining power and can rule out about three quarters of the inflationary scenarios, compared to one third for Planck 2013 data alone. However, we also show that PRISM can constrain the scalar running and has the capability to detect a violation of slow roll at second order. Finally, our results suggest that describing an inflationary model by its potential shape only, without specifying a reheating temperature, will no longer be possible given the accuracy level reached by the future CMB missions.« less

Power limits for microbial life.

PubMed

LaRowe, Douglas E; Amend, Jan P

2015-01-01

To better understand the origin, evolution, and extent of life, we seek to determine the minimum flux of energy needed for organisms to remain viable. Despite the difficulties associated with direct measurement of the power limits for life, it is possible to use existing data and models to constrain the minimum flux of energy required to sustain microorganisms. Here, a we apply a bioenergetic model to a well characterized marine sedimentary environment in order to quantify the amount of power organisms use in an ultralow-energy setting. In particular, we show a direct link between power consumption in this environment and the amount of biomass (cells cm(-3)) found in it. The power supply resulting from the aerobic degradation of particular organic carbon (POC) at IODP Site U1370 in the South Pacific Gyre is between ∼10(-12) and 10(-16) W cm(-3). The rates of POC degradation are calculated using a continuum model while Gibbs energies have been computed using geochemical data describing the sediment as a function of depth. Although laboratory-determined values of maintenance power do a poor job of representing the amount of biomass in U1370 sediments, the number of cells per cm(-3) can be well-captured using a maintenance power, 190 zW cell(-1), two orders of magnitude lower than the lowest value reported in the literature. In addition, we have combined cell counts and calculated power supplies to determine that, on average, the microorganisms at Site U1370 require 50-3500 zW cell(-1), with most values under ∼300 zW cell(-1). Furthermore, we carried out an analysis of the absolute minimum power requirement for a single cell to remain viable to be on the order of 1 zW cell(-1).

Mechanotransduction mechanisms in growing spherically structured tissues

NASA Astrophysics Data System (ADS)

Littlejohns, Euan; Dunlop, Carina M.

2018-04-01

There is increasing experimental interest in mechanotransduction in multi-cellular tissues as opposed to single cells. This is driven by a growing awareness of the importance of physiologically relevant three-dimensional culture and of cell–cell and cell–gel interactions in directing growth and development. The paradigm biophysical technique for investigating tissue level mechanobiology in this context is to grow model tissues in artificial gels with well-defined mechanical properties. These studies often indicate that the stiffness of the encapsulating gel can significantly alter cellular behaviours. We demonstrate here potential mechanisms linking tissue growth with stiffness-mediated mechanotransduction. We show how tissue growth in gel systems generates points at which there is a significant qualitative change in the cellular stress and strain experienced. We show analytically how these potential switching points depend on the mechanical properties of the constraining gel and predict when they will occur. Significantly, we identify distinct mechanisms that act separately in each of the stress and strain fields at different times. These observations suggest growth as a potential physical mechanism coupling gel stiffness with cellular mechanotransduction in three-dimensional tissues. We additionally show that non-proliferating areas, in the case that the constraining gel is soft compared with the tissue, will expand and contract passively as a result of growth. Central compartment size is thus seen to not be a reliable indicator on its own for growth initiation or active behaviour.

Firing-rate based network modeling of the dLGN circuit: Effects of cortical feedback on spatiotemporal response properties of relay cells.

PubMed

Mobarhan, Milad Hobbi; Halnes, Geir; Martínez-Cañada, Pablo; Hafting, Torkel; Fyhn, Marianne; Einevoll, Gaute T

2018-05-01

Visually evoked signals in the retina pass through the dorsal geniculate nucleus (dLGN) on the way to the visual cortex. This is however not a simple feedforward flow of information: there is a significant feedback from cortical cells back to both relay cells and interneurons in the dLGN. Despite four decades of experimental and theoretical studies, the functional role of this feedback is still debated. Here we use a firing-rate model, the extended difference-of-Gaussians (eDOG) model, to explore cortical feedback effects on visual responses of dLGN relay cells. For this model the responses are found by direct evaluation of two- or three-dimensional integrals allowing for fast and comprehensive studies of putative effects of different candidate organizations of the cortical feedback. Our analysis identifies a special mixed configuration of excitatory and inhibitory cortical feedback which seems to best account for available experimental data. This configuration consists of (i) a slow (long-delay) and spatially widespread inhibitory feedback, combined with (ii) a fast (short-delayed) and spatially narrow excitatory feedback, where (iii) the excitatory/inhibitory ON-ON connections are accompanied respectively by inhibitory/excitatory OFF-ON connections, i.e. following a phase-reversed arrangement. The recent development of optogenetic and pharmacogenetic methods has provided new tools for more precise manipulation and investigation of the thalamocortical circuit, in particular for mice. Such data will expectedly allow the eDOG model to be better constrained by data from specific animal model systems than has been possible until now for cat. We have therefore made the Python tool pyLGN which allows for easy adaptation of the eDOG model to new situations.

Modeling slow-slip segmentation in Cascadia subduction zone constrained by tremor locations and gravity anomalies

NASA Astrophysics Data System (ADS)

Li, Duo; Liu, Yajing

2017-04-01

Along-strike segmentation of slow-slip events (SSEs) and nonvolcanic tremors in Cascadia may reflect heterogeneities of the subducting slab or overlying continental lithosphere. However, the nature behind this segmentation is not fully understood. We develop a 3-D model for episodic SSEs in northern and central Cascadia, incorporating both seismological and gravitational observations to constrain the heterogeneities in the megathrust fault properties. The 6 year automatically detected tremors are used to constrain the rate-state friction parameters. The effective normal stress at SSE depths is constrained by along-margin free-air and Bouguer gravity anomalies. The along-strike variation in the long-term plate convergence rate is also taken into consideration. Simulation results show five segments of ˜Mw6.0 SSEs spontaneously appear along the strike, correlated to the distribution of tremor epicenters. Modeled SSE recurrence intervals are equally comparable to GPS observations using both types of gravity anomaly constraints. However, the model constrained by free-air anomaly does a better job in reproducing the cumulative slip as well as more consistent surface displacements with GPS observations. The modeled along-strike segmentation represents the averaged slip release over many SSE cycles, rather than permanent barriers. Individual slow-slip events can still propagate across the boundaries, which may cause interactions between adjacent SSEs, as observed in time-dependent GPS inversions. In addition, the moment-duration scaling is sensitive to the selection of velocity criteria for determining when SSEs occur. Hence, the detection ability of the current GPS network should be considered in the interpretation of slow earthquake source parameter scaling relations.

Modelling and Vibration Control of Beams with Partially Debonded Active Constrained Layer Damping Patch

NASA Astrophysics Data System (ADS)

SUN, D.; TONG, L.

2002-05-01

A detailed model for the beams with partially debonded active constraining damping (ACLD) treatment is presented. In this model, the transverse displacement of the constraining layer is considered to be non-identical to that of the host structure. In the perfect bonding region, the viscoelastic core is modelled to carry both peel and shear stresses, while in the debonding area, it is assumed that no peel and shear stresses be transferred between the host beam and the constraining layer. The adhesive layer between the piezoelectric sensor and the host beam is also considered in this model. In active control, the positive position feedback control is employed to control the first mode of the beam. Based on this model, the incompatibility of the transverse displacements of the active constraining layer and the host beam is investigated. The passive and active damping behaviors of the ACLD patch with different thicknesses, locations and lengths are examined. Moreover, the effects of debonding of the damping layer on both passive and active control are examined via a simulation example. The results show that the incompatibility of the transverse displacements is remarkable in the regions near the ends of the ACLD patch especially for the high order vibration modes. It is found that a thinner damping layer may lead to larger shear strain and consequently results in a larger passive and active damping. In addition to the thickness of the damping layer, its length and location are also key factors to the hybrid control. The numerical results unveil that edge debonding can lead to a reduction of both passive and active damping, and the hybrid damping may be more sensitive to the debonding of the damping layer than the passive damping.

Single Cell Analysis Linking Ribosomal (r)DNA and rRNA Copy Numbers to Cell Size and Growth Rate Provides Insights into Molecular Protistan Ecology.

PubMed

Fu, Rao; Gong, Jun

2017-11-01

Ribosomal (r)RNA and rDNA have been golden molecular markers in microbial ecology. However, it remains poorly understood how ribotype copy number (CN)-based characteristics are linked with diversity, abundance, and activity of protist populations and communities observed at organismal levels. Here, we applied a single-cell approach to quantify ribotype CNs in two ciliate species reared at different temperatures. We found that in actively growing cells, the per-cell rDNA and rRNA CNs scaled with cell volume (CV) to 0.44 and 0.58 powers, respectively. The modeled rDNA and rRNA concentrations thus appear to be much higher in smaller than in larger cells. The observed rRNA:rDNA ratio scaled with CV 0.14 . The maximum growth rate could be well predicted by a combination of per-cell ribotype CN and temperature. Our empirical data and modeling on single-cell ribotype scaling are in agreement with both the metabolic theory of ecology and the growth rate hypothesis, providing a quantitative framework for linking cellular rDNA and rRNA CNs with body size, growth (activity), and biomass stoichiometry. This study also demonstrates that the expression rate of rRNA genes is constrained by cell size, and favors biomass rather than abundance-based interpretation of quantitative ribotype data in population and community ecology of protists. © 2017 The Authors. Journal of Eukaryotic Microbiology published by Wiley Periodicals, Inc. on behalf of International Society of Protistologists.

Microbial Fuel Cell Performance with a Pressurized Cathode Chamber

USDA-ARS?s Scientific Manuscript database

Microbial fuel cell (MFC) power densities are often constrained by the oxygen reduction reaction rate on the cathode electrode. One important factor for this is the normally low solubility of oxygen in the aqueous cathode solution creating mass transport limitations, which hinder oxygen reduction a...

An inexact log-normal distribution-based stochastic chance-constrained model for agricultural water quality management

NASA Astrophysics Data System (ADS)

Wang, Yu; Fan, Jie; Xu, Ye; Sun, Wei; Chen, Dong

2018-05-01

In this study, an inexact log-normal-based stochastic chance-constrained programming model was developed for solving the non-point source pollution issues caused by agricultural activities. Compared to the general stochastic chance-constrained programming model, the main advantage of the proposed model is that it allows random variables to be expressed as a log-normal distribution, rather than a general normal distribution. Possible deviations in solutions caused by irrational parameter assumptions were avoided. The agricultural system management in the Erhai Lake watershed was used as a case study, where critical system factors, including rainfall and runoff amounts, show characteristics of a log-normal distribution. Several interval solutions were obtained under different constraint-satisfaction levels, which were useful in evaluating the trade-off between system economy and reliability. The applied results show that the proposed model could help decision makers to design optimal production patterns under complex uncertainties. The successful application of this model is expected to provide a good example for agricultural management in many other watersheds.

Targeting kinase signaling pathways with constrained peptide scaffolds

PubMed Central

Hanold, Laura E.; Fulton, Melody D.; Kennedy, Eileen J.

2017-01-01

Kinases are amongst the largest families in the human proteome and serve as critical mediators of a myriad of cell signaling pathways. Since altered kinase activity is implicated in a variety of pathological diseases, kinases have become a prominent class of proteins for targeted inhibition. Although numerous small molecule and antibody-based inhibitors have already received clinical approval, several challenges may still exist with these strategies including resistance, target selection, inhibitor potency and in vivo activity profiles. Constrained peptide inhibitors have emerged as an alternative strategy for kinase inhibition. Distinct from small molecule inhibitors, peptides can provide a large binding surface area that allows them to bind shallow protein surfaces rather than defined pockets within the target protein structure. By including chemical constraints within the peptide sequence, additional benefits can be bestowed onto the peptide scaffold such as improved target affinity and target selectivity, cell permeability and proteolytic resistance. In this review, we highlight examples of diverse chemistries that are being employed to constrain kinase-targeting peptide scaffolds and highlight their application to modulate kinase signaling as well as their potential clinical implications. PMID:28185915

Maximum entropy production: Can it be used to constrain conceptual hydrological models?

Treesearch

M.C. Westhoff; E. Zehe

2013-01-01

In recent years, optimality principles have been proposed to constrain hydrological models. The principle of maximum entropy production (MEP) is one of the proposed principles and is subject of this study. It states that a steady state system is organized in such a way that entropy production is maximized. Although successful applications have been reported in...

Mathematical model of susceptibility, resistance, and resilience in the within-host dynamics between a Plasmodium parasite and the immune system.

PubMed

Yan, Yi; Adam, Brian; Galinski, Mary; C Kissinger, Jessica; Moreno, Alberto; Gutierrez, Juan B

2015-12-01

We developed a coupled age-structured partial differential equation model to capture the disease dynamics during blood-stage malaria. The addition of age structure for the parasite population, with respect to previous models, allows us to better characterize the interaction between the malaria parasite and red blood cells during infection. Here we prove that the system we propose is well-posed and there exist at least two global states. We further demonstrate that the numerical simulation of the system coincides with clinically observed outcomes of primary and secondary malaria infection. The well-posedness of this system guarantees that the behavior of the model remains smooth, bounded, and continuously dependent on initial conditions; calibration with clinical data will constrain domains of parameters and variables to physiological ranges. Copyright © 2015 Elsevier Inc. All rights reserved.

Cost-driven materials selection criteria for redox flow battery electrolytes

NASA Astrophysics Data System (ADS)

Dmello, Rylan; Milshtein, Jarrod D.; Brushett, Fikile R.; Smith, Kyle C.

2016-10-01

Redox flow batteries show promise for grid-scale energy storage applications but are presently too expensive for widespread adoption. Electrolyte material costs constitute a sizeable fraction of the redox flow battery price. As such, this work develops a techno-economic model for redox flow batteries that accounts for redox-active material, salt, and solvent contributions to the electrolyte cost. Benchmark values for electrolyte constituent costs guide identification of design constraints. Nonaqueous battery design is sensitive to all electrolyte component costs, cell voltage, and area-specific resistance. Design challenges for nonaqueous batteries include minimizing salt content and dropping redox-active species concentration requirements. Aqueous battery design is sensitive to only redox-active material cost and cell voltage, due to low area-specific resistance and supporting electrolyte costs. Increasing cell voltage and decreasing redox-active material cost present major materials selection challenges for aqueous batteries. This work minimizes cost-constraining variables by mapping the battery design space with the techno-economic model, through which we highlight pathways towards low price and moderate concentration. Furthermore, the techno-economic model calculates quantitative iterations of battery designs to achieve the Department of Energy battery price target of 100 per kWh and highlights cost cutting strategies to drive battery prices down further.

The in situ transverse lamina strength of composite laminates

NASA Technical Reports Server (NTRS)

Flaggs, D. L.

1983-01-01

The objective of the work reported in this presentation is to determine the in situ transverse strength of a lamina within a composite laminate. From a fracture mechanics standpoint, in situ strength may be viewed as constrained cracking that has been shown to be a function of both lamina thickness and the stiffness of adjacent plies that serve to constrain the cracking process. From an engineering point of view, however, constrained cracking can be perceived as an apparent increase in lamina strength. With the growing need to design more highly loaded composite structures, the concept of in situ strength may prove to be a viable means of increasing the design allowables of current and future composite material systems. A simplified one dimensional analytical model is presented that is used to predict the strain at onset of transverse cracking. While it is accurate only for the most constrained cases, the model is important in that the predicted failure strain is seen to be a function of a lamina's thickness d and of the extensional stiffness bE theta of the adjacent laminae that constrain crack propagation in the 90 deg laminae.

Constraining the dark energy equation of state using Bayes theorem and the Kullback–Leibler divergence

DOE PAGES

Hee, S.; Vázquez, J. A.; Handley, W. J.; ...

2016-12-01

Data-driven model-independent reconstructions of the dark energy equation of state w(z) are presented using Planck 2015 era CMB, BAO, SNIa and Lyman-α data. These reconstructions identify the w(z) behaviour supported by the data and show a bifurcation of the equation of state posterior in the range 1.5 < z < 3. Although the concordance ΛCDM model is consistent with the data at all redshifts in one of the bifurcated spaces, in the other a supernegative equation of state (also known as ‘phantom dark energy’) is identified within the 1.5σ confidence intervals of the posterior distribution. In order to identify themore » power of different datasets in constraining the dark energy equation of state, we use a novel formulation of the Kullback–Leibler divergence. Moreover, this formalism quantifies the information the data add when moving from priors to posteriors for each possible dataset combination. The SNIa and BAO datasets are shown to provide much more constraining power in comparison to the Lyman-α datasets. Furthermore, SNIa and BAO constrain most strongly around redshift range 0.1 - 0.5, whilst the Lyman-α data constrains weakly over a broader range. We do not attribute the supernegative favouring to any particular dataset, and note that the ΛCDM model was favoured at more than 2 log-units in Bayes factors over all the models tested despite the weakly preferred w(z) structure in the data.« less

Constraining the dark energy equation of state using Bayes theorem and the Kullback–Leibler divergence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hee, S.; Vázquez, J. A.; Handley, W. J.

Data-driven model-independent reconstructions of the dark energy equation of state w(z) are presented using Planck 2015 era CMB, BAO, SNIa and Lyman-α data. These reconstructions identify the w(z) behaviour supported by the data and show a bifurcation of the equation of state posterior in the range 1.5 < z < 3. Although the concordance ΛCDM model is consistent with the data at all redshifts in one of the bifurcated spaces, in the other a supernegative equation of state (also known as ‘phantom dark energy’) is identified within the 1.5σ confidence intervals of the posterior distribution. In order to identify themore » power of different datasets in constraining the dark energy equation of state, we use a novel formulation of the Kullback–Leibler divergence. Moreover, this formalism quantifies the information the data add when moving from priors to posteriors for each possible dataset combination. The SNIa and BAO datasets are shown to provide much more constraining power in comparison to the Lyman-α datasets. Furthermore, SNIa and BAO constrain most strongly around redshift range 0.1 - 0.5, whilst the Lyman-α data constrains weakly over a broader range. We do not attribute the supernegative favouring to any particular dataset, and note that the ΛCDM model was favoured at more than 2 log-units in Bayes factors over all the models tested despite the weakly preferred w(z) structure in the data.« less

Impact of composite plates: Analysis of stresses and forces

NASA Technical Reports Server (NTRS)

Moon, F. C.; Kim, B. S.; Fang-Landau, S. R.

1976-01-01

The foreign object damage resistance of composite fan blades was studied. Edge impact stresses in an anisotropic plate were first calculated incorporating a constrained layer damping model. It is shown that a very thin damping layer can dramatically decrease the maximum normal impact stresses. A multilayer model of a composite plate is then presented which allows computation of the interlaminar normal and shear stresses. Results are presented for the stresses due to a line impact load normal to the plane of a composite plate. It is shown that significant interlaminar tensile stresses can develop during impact. A computer code was developed for this problem using the fast Fourier transform. A marker and cell computer code were also used to investigate the hydrodynamic impact of a fluid slug against a wall or turbine blade. Application of fluid modeling of bird impact is reviewed.

Impact of DNA twist accumulation on progressive helical wrapping of torsionally constrained DNA.

PubMed

Li, Wei; Wang, Peng-Ye; Yan, Jie; Li, Ming

2012-11-21

DNA wrapping is an important mechanism for chromosomal DNA packaging in cells and viruses. Previous studies of DNA wrapping have been performed mostly on torsionally unconstrained DNA, while in vivo DNA is often under torsional constraint. In this study, we extend a previously proposed theoretical model for wrapping of torsionally unconstrained DNA to a new model including the contribution of DNA twist energy, which influences DNA wrapping drastically. In particular, due to accumulation of twist energy during DNA wrapping, it predicts a finite amount of DNA that can be wrapped on a helical spool. The predictions of the new model are tested by single-molecule study of DNA wrapping under torsional constraint using magnetic tweezers. The theoretical predictions and the experimental results are consistent with each other and their implications are discussed.

Constrained minimization of smooth functions using a genetic algorithm

NASA Technical Reports Server (NTRS)

Moerder, Daniel D.; Pamadi, Bandu N.

1994-01-01

The use of genetic algorithms for minimization of differentiable functions that are subject to differentiable constraints is considered. A technique is demonstrated for converting the solution of the necessary conditions for a constrained minimum into an unconstrained function minimization. This technique is extended as a global constrained optimization algorithm. The theory is applied to calculating minimum-fuel ascent control settings for an energy state model of an aerospace plane.

Forward Modeling of Atmospheric Carbon Dioxide in GEOS-5: Uncertainties Related to Surface Fluxes and Sub-Grid Transport

NASA Technical Reports Server (NTRS)

Pawson, Steven; Ott, Lesley E.; Zhu, Zhengxin; Bowman, Kevin; Brix, Holger; Collatz, G. James; Dutkiewicz, Stephanie; Fisher, Joshua B.; Gregg, Watson W.; Hill, Chris;

Micropatterning tractional forces in living cells

NASA Technical Reports Server (NTRS)

Wang, Ning; Ostuni, Emanuele; Whitesides, George M.; Ingber, Donald E.

2002-01-01

Here we describe a method for quantifying traction in cells that are physically constrained within micron-sized adhesive islands of defined shape and size on the surface of flexible polyacrylamide gels that contain fluorescent microbeads (0.2-microm diameter). Smooth muscle cells were plated onto square (50 x 50 microm) or circular (25- or 50-microm diameter) adhesive islands that were created on the surface of the gels by applying a collagen coating through microengineered holes in an elastomeric membrane that was later removed. Adherent cells spread to take on the size and shape of the islands and cell tractions were quantitated by mapping displacement fields of the fluorescent microbeads within the gel. Cells on round islands did not exhibit any preferential direction of force application, but they exerted their strongest traction at sites where they formed protrusions. When cells were confined to squares, traction was highest in the corners both in the absence and presence of the contractile agonist, histamine, and cell protrusions were also observed in these regions. Quantitation of the mean traction exerted by cells cultured on the different islands revealed that cell tension increased as cell spreading was promoted. These results provide a mechanical basis for past studies that demonstrated a similar correlation between spreading and growth within various anchorage-dependent cells. This new approach for analyzing the spatial distribution of mechanical forces beneath individual cells that are experimentally constrained to defined sizes and shapes may provide additional insight into the biophysical basis of cell regulation. Copyright 2002 Wiley-Liss, Inc.

Polarization and studies of evolved star mass loss

NASA Astrophysics Data System (ADS)

Sargent, Benjamin; Srinivasan, Sundar; Riebel, David; Meixner, Margaret

2012-05-01

Polarization studies of astronomical dust have proven very useful in constraining its properties. Such studies are used to constrain the spatial arrangement, shape, composition, and optical properties of astronomical dust grains. Here we explore possible connections between astronomical polarization observations to our studies of mass loss from evolved stars. We are studying evolved star mass loss in the Large Magellanic Cloud (LMC) by using photometry from the Surveying the Agents of a Galaxy's Evolution (SAGE; PI: M. Meixner) Spitzer Space Telescope Legacy program. We use the radiative transfer program 2Dust to create our Grid of Red supergiant and Asymptotic giant branch ModelS (GRAMS), in order to model this mass loss. To model emission of polarized light from evolved stars, however, we appeal to other radiative transfer codes. We probe how polarization observations might be used to constrain the dust shell and dust grain properties of the samples of evolved stars we are studying.

A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions

NASA Astrophysics Data System (ADS)

Lienert, Sebastian; Joos, Fortunat

2018-05-01

A dynamic global vegetation model (DGVM) is applied in a probabilistic framework and benchmarking system to constrain uncertain model parameters by observations and to quantify carbon emissions from land-use and land-cover change (LULCC). Processes featured in DGVMs include parameters which are prone to substantial uncertainty. To cope with these uncertainties Latin hypercube sampling (LHS) is used to create a 1000-member perturbed parameter ensemble, which is then evaluated with a diverse set of global and spatiotemporally resolved observational constraints. We discuss the performance of the constrained ensemble and use it to formulate a new best-guess version of the model (LPX-Bern v1.4). The observationally constrained ensemble is used to investigate historical emissions due to LULCC (ELUC) and their sensitivity to model parametrization. We find a global ELUC estimate of 158 (108, 211) PgC (median and 90 % confidence interval) between 1800 and 2016. We compare ELUC to other estimates both globally and regionally. Spatial patterns are investigated and estimates of ELUC of the 10 countries with the largest contribution to the flux over the historical period are reported. We consider model versions with and without additional land-use processes (shifting cultivation and wood harvest) and find that the difference in global ELUC is on the same order of magnitude as parameter-induced uncertainty and in some cases could potentially even be offset with appropriate parameter choice.

Estimating the frequency interval of a regularly spaced multicomponent harmonic line signal in colored noise

NASA Astrophysics Data System (ADS)

Frazer, Gordon J.; Anderson, Stuart J.

1997-10-01

The radar returns from some classes of time-varying point targets can be represented by the discrete-time signal plus noise model: xt equals st plus [vt plus (eta) t] equals (summation)i equals o P minus 1 Aiej2(pi f(i)/f(s)t) plus vt plus (eta) t, t (epsilon) 0, . . ., N minus 1, fi equals kfI plus fo where the received signal xt corresponds to the radar return from the target of interest from one azimuth-range cell. The signal has an unknown number of components, P, unknown complex amplitudes Ai and frequencies fi. The frequency parameters fo and fI are unknown, although constrained such that fo less than fI/2 and parameter k (epsilon) {minus u, . . ., minus 2, minus 1, 0, 1, 2, . . ., v} is constrained such that the component frequencies fi are bound by (minus fs/2, fs/2). The noise term vt, is typically colored, and represents clutter, interference and various noise sources. It is unknown, except that (summation)tvt2 less than infinity; in general, vt is not well modelled as an auto-regressive process of known order. The additional noise term (eta) t represents time-invariant point targets in the same azimuth-range cell. An important characteristic of the target is the unknown parameter, fI, representing the frequency interval between harmonic lines. It is desired to determine an estimate of fI from N samples of xt. We propose an algorithm to estimate fI based on Thomson's harmonic line F-Test, which is part of the multi-window spectrum estimation method and demonstrate the proposed estimator applied to target echo time series collected using an experimental HF skywave radar.

Implementation of remote sensing data for flood forecasting

NASA Astrophysics Data System (ADS)

Grimaldi, S.; Li, Y.; Pauwels, V. R. N.; Walker, J. P.; Wright, A. J.

2016-12-01

Flooding is one of the most frequent and destructive natural disasters. A timely, accurate and reliable flood forecast can provide vital information for flood preparedness, warning delivery, and emergency response. An operational flood forecasting system typically consists of a hydrologic model, which simulates runoff generation and concentration, and a hydraulic model, which models riverine flood wave routing and floodplain inundation. However, these two types of models suffer from various sources of uncertainties, e.g., forcing data initial conditions, model structure and parameters. To reduce those uncertainties, current forecasting systems are typically calibrated and/or updated using streamflow measurements, and such applications are limited in well-gauged areas. The recent increasing availability of spatially distributed Remote Sensing (RS) data offers new opportunities for flood events investigation and forecast. Based on an Australian case study, this presentation will discuss the use 1) of RS soil moisture data to constrain a hydrologic model, and 2) of RS-derived flood extent and level to constrain a hydraulic model. The hydrological model is based on a semi-distributed system coupled with a two-soil-layer rainfall-runoff model GRKAL and a linear Muskingum routing model. Model calibration was performed using either 1) streamflow data only or 2) both streamflow and RS soil moisture data. The model was then further constrained through the integration of real-time soil moisture data. The hydraulic model is based on LISFLOOD-FP which solves the 2D inertial approximation of the Shallow Water Equations. Streamflow data and RS-derived flood extent and levels were used to apply a multi-objective calibration protocol. The effectiveness with which each data source or combination of data sources constrained the parameter space was quantified and discussed.

Querying quantitative logic models (Q2LM) to study intracellular signaling networks and cell-cytokine interactions.

PubMed

Morris, Melody K; Shriver, Zachary; Sasisekharan, Ram; Lauffenburger, Douglas A

2012-03-01

Mathematical models have substantially improved our ability to predict the response of a complex biological system to perturbation, but their use is typically limited by difficulties in specifying model topology and parameter values. Additionally, incorporating entities across different biological scales ranging from molecular to organismal in the same model is not trivial. Here, we present a framework called "querying quantitative logic models" (Q2LM) for building and asking questions of constrained fuzzy logic (cFL) models. cFL is a recently developed modeling formalism that uses logic gates to describe influences among entities, with transfer functions to describe quantitative dependencies. Q2LM does not rely on dedicated data to train the parameters of the transfer functions, and it permits straight-forward incorporation of entities at multiple biological scales. The Q2LM framework can be employed to ask questions such as: Which therapeutic perturbations accomplish a designated goal, and under what environmental conditions will these perturbations be effective? We demonstrate the utility of this framework for generating testable hypotheses in two examples: (i) a intracellular signaling network model; and (ii) a model for pharmacokinetics and pharmacodynamics of cell-cytokine interactions; in the latter, we validate hypotheses concerning molecular design of granulocyte colony stimulating factor. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Constrained Allocation Flux Balance Analysis

PubMed Central

Mori, Matteo; Hwa, Terence; Martin, Olivier C.

2016-01-01

New experimental results on bacterial growth inspire a novel top-down approach to study cell metabolism, combining mass balance and proteomic constraints to extend and complement Flux Balance Analysis. We introduce here Constrained Allocation Flux Balance Analysis, CAFBA, in which the biosynthetic costs associated to growth are accounted for in an effective way through a single additional genome-wide constraint. Its roots lie in the experimentally observed pattern of proteome allocation for metabolic functions, allowing to bridge regulation and metabolism in a transparent way under the principle of growth-rate maximization. We provide a simple method to solve CAFBA efficiently and propose an “ensemble averaging” procedure to account for unknown protein costs. Applying this approach to modeling E. coli metabolism, we find that, as the growth rate increases, CAFBA solutions cross over from respiratory, growth-yield maximizing states (preferred at slow growth) to fermentative states with carbon overflow (preferred at fast growth). In addition, CAFBA allows for quantitatively accurate predictions on the rate of acetate excretion and growth yield based on only 3 parameters determined by empirical growth laws. PMID:27355325

A model of growth restraints to explain the development and evolution of tooth shapes in mammals.

PubMed

Osborn, Jeffrey W

2008-12-07

The problem investigated here is control of the development of tooth shape. Cells at the growing soft tissue interface between the ectoderm and mesoderm in a tooth anlage are observed to buckle and fold into a template for the shape of the tooth crown. The final shape is created by enamel secreted onto the folds. The pattern in which the folds develop is generally explained as a response to the pattern in which genes are locally expressed at the interface. This congruence leaves the problem of control unanswered because it does not explain how either pattern is controlled. Obviously, cells are subject to Newton's laws of motion so that mechanical forces and constraints must ultimately cause the movements of cells during tooth morphogenesis. A computer model is used to test the hypothesis that directional resistances to growth of the epithelial part of the interface could account for the shape into which the interface folds. The model starts with a single epithelial cell whose growth is constrained by 4 constant directional resistances (anterior, posterior, medial and lateral). The constraints force the growing epithelium to buckle and fold. By entering into the model different values for these constraints the modeled epithelium is induced to buckle and fold into the different shapes associated with the evolution of a human upper molar from that of a reptilian ancestor. The patterns and sizes of cusps and the sequences in which they develop are all correctly reproduced. The model predicts the changes in the 4 directional constraints necessary to develop and evolve from one tooth shape into another. I conclude more generally expressed genes that control directional resistances to growth, not locally expressed genes, may provide the information for the shape into which a tooth develops.

Compromise Approach-Based Genetic Algorithm for Constrained Multiobjective Portfolio Selection Model

NASA Astrophysics Data System (ADS)

Li, Jun

In this paper, fuzzy set theory is incorporated into a multiobjective portfolio selection model for investors’ taking into three criteria: return, risk and liquidity. The cardinality constraint, the buy-in threshold constraint and the round-lots constraints are considered in the proposed model. To overcome the difficulty of evaluation a large set of efficient solutions and selection of the best one on non-dominated surface, a compromise approach-based genetic algorithm is presented to obtain a compromised solution for the proposed constrained multiobjective portfolio selection model.

Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America.

PubMed

Medvigy, David; Moorcroft, Paul R

2012-01-19

Terrestrial biosphere models are important tools for diagnosing both the current state of the terrestrial carbon cycle and forecasting terrestrial ecosystem responses to global change. While there are a number of ongoing assessments of the short-term predictive capabilities of terrestrial biosphere models using flux-tower measurements, to date there have been relatively few assessments of their ability to predict longer term, decadal-scale biomass dynamics. Here, we present the results of a regional-scale evaluation of the Ecosystem Demography version 2 (ED2)-structured terrestrial biosphere model, evaluating the model's predictions against forest inventory measurements for the northeast USA and Quebec from 1985 to 1995. Simulations were conducted using a default parametrization, which used parameter values from the literature, and a constrained model parametrization, which had been developed by constraining the model's predictions against 2 years of measurements from a single site, Harvard Forest (42.5° N, 72.1° W). The analysis shows that the constrained model parametrization offered marked improvements over the default model formulation, capturing large-scale variation in patterns of biomass dynamics despite marked differences in climate forcing, land-use history and species-composition across the region. These results imply that data-constrained parametrizations of structured biosphere models such as ED2 can be successfully used for regional-scale ecosystem prediction and forecasting. We also assess the model's ability to capture sub-grid scale heterogeneity in the dynamics of biomass growth and mortality of different sizes and types of trees, and then discuss the implications of these analyses for further reducing the remaining biases in the model's predictions.

Single cell activity reveals direct electron transfer in methanotrophic consortia

NASA Astrophysics Data System (ADS)

McGlynn, Shawn E.; Chadwick, Grayson L.; Kempes, Christopher P.; Orphan, Victoria J.

2015-10-01

Multicellular assemblages of microorganisms are ubiquitous in nature, and the proximity afforded by aggregation is thought to permit intercellular metabolic coupling that can accommodate otherwise unfavourable reactions. Consortia of methane-oxidizing archaea and sulphate-reducing bacteria are a well-known environmental example of microbial co-aggregation; however, the coupling mechanisms between these paired organisms is not well understood, despite the attention given them because of the global significance of anaerobic methane oxidation. Here we examined the influence of interspecies spatial positioning as it relates to biosynthetic activity within structurally diverse uncultured methane-oxidizing consortia by measuring stable isotope incorporation for individual archaeal and bacterial cells to constrain their potential metabolic interactions. In contrast to conventional models of syntrophy based on the passage of molecular intermediates, cellular activities were found to be independent of both species intermixing and distance between syntrophic partners within consortia. A generalized model of electric conductivity between co-associated archaea and bacteria best fit the empirical data. Combined with the detection of large multi-haem cytochromes in the genomes of methanotrophic archaea and the demonstration of redox-dependent staining of the matrix between cells in consortia, these results provide evidence for syntrophic coupling through direct electron transfer.

Cancer Systems Biology: a peak into the future of patient care?

PubMed Central

Werner, Henrica M. J.; Mills, Gordon B.; Ram, Prahlad T.

2015-01-01

Traditionally, scientific research has focused on studying individual events, such as single mutations, gene function or the effect of the manipulation of one protein on a biological phenotype. A range of technologies, combined with the ability to develop robust and predictive mathematical models, is beginning to provide information that will enable a holistic view of how the genomic and epigenetic aberrations in cancer cells can alter the homeostasis of signalling networks within these cells, between cancer cells and the local microenvironment, at the organ and organism level. This systems biology process needs to be integrated with an iterative approach wherein hypotheses and predictions that arise from modelling are refined and constrained by experimental evaluation. Systems biology approaches will be vital for developing and implementing effective strategies to deliver personalized cancer therapy. Specifically, these approaches will be important to select those patients most likely to benefit from targeted therapies as well as for the development and implementation of rational combinatorial therapies. Systems biology can help to increase therapy efficacy or bypass the emergence of resistance, thus converting the current (often short term) effects of targeted therapies into durable responses, ultimately to improve quality of life and provide a cure. PMID:24492837

Tropospheric transport differences between models using the same large-scale meteorological fields

NASA Astrophysics Data System (ADS)

Orbe, Clara; Waugh, Darryn W.; Yang, Huang; Lamarque, Jean-Francois; Tilmes, Simone; Kinnison, Douglas E.

2017-01-01

The transport of chemicals is a major uncertainty in the modeling of tropospheric composition. A common approach is to transport gases using the winds from meteorological analyses, either using them directly in a chemical transport model or by constraining the flow in a general circulation model. Here we compare the transport of idealized tracers in several different models that use the same meteorological fields taken from Modern-Era Retrospective analysis for Research and Applications (MERRA). We show that, even though the models use the same meteorological fields, there are substantial differences in their global-scale tropospheric transport related to large differences in parameterized convection between the simulations. Furthermore, we find that the transport differences between simulations constrained with the same-large scale flow are larger than differences between free-running simulations, which have differing large-scale flow but much more similar convective mass fluxes. Our results indicate that more attention needs to be paid to convective parameterizations in order to understand large-scale tropospheric transport in models, particularly in simulations constrained with analyzed winds.

Fermion masses in SO(10)

NASA Astrophysics Data System (ADS)

Jungman, Gerard

1992-11-01

Yukawa-coupling-constant unification together with the known fermion masses is used to constrain SO(10) models. We consider the case of one (heavy) generation, with the tree-level relation mb=mτ, calculating the limits on the intermediate scales due to the known limits on fermion masses. This analysis extends previous analyses which addressed only the simplest symmetry-breaking schemes. In the case where the low-energy model is the standard model with one Higgs doublet, there are very strong constraints due to the known limits on the top-quark mass and the τ-neutrino mass. The two-Higgs-doublet case is less constrained, though we can make progress in constraining this model also. We identify those parameters to which the viability of the model is most sensitive. We also discuss the ``triviality'' bounds on mt obtained from the analysis of the Yukawa renormalization-group equations. Finally we address the role of a speculative constraint on the τ-neutrino mass, arising from the cosmological implications of anomalous B+L violation in the early Universe.

Epitope Specificity Delimits the Functional Capabilities of Vaccine-Induced CD8 T Cell Populations

PubMed Central

Hill, Brenna J.; Darrah, Patricia A.; Ende, Zachary; Ambrozak, David R.; Quinn, Kylie M.; Darko, Sam; Gostick, Emma; Wooldridge, Linda; van den Berg, Hugo A.; Venturi, Vanessa; Larsen, Martin; Davenport, Miles P.; Seder, Robert A.

2014-01-01

Despite progress toward understanding the correlates of protective T cell immunity in HIV infection, the optimal approach to Ag delivery by vaccination remains uncertain. We characterized two immunodominant CD8 T cell populations generated in response to immunization of BALB/c mice with a replication-deficient adenovirus serotype 5 vector expressing the HIV-derived Gag and Pol proteins at equivalent levels. The Gag-AI9/H-2Kd epitope elicited high-avidity CD8 T cell populations with architecturally diverse clonotypic repertoires that displayed potent lytic activity in vivo. In contrast, the Pol-LI9/H-2Dd epitope elicited motif-constrained CD8 T cell repertoires that displayed lower levels of physical avidity and lytic activity despite equivalent measures of overall clonality. Although low-dose vaccination enhanced the functional profiles of both epitope-specific CD8 T cell populations, greater polyfunctionality was apparent within the Pol-LI9/H-2Dd specificity. Higher proportions of central memory-like cells were present after low-dose vaccination and at later time points. However, there were no noteworthy phenotypic differences between epitope-specific CD8 T cell populations across vaccine doses or time points. Collectively, these data indicate that the functional and phenotypic properties of vaccine-induced CD8 T cell populations are sensitive to dose manipulation, yet constrained by epitope specificity in a clonotype-dependent manner. PMID:25348625

Terrestrial Sagnac delay constraining modified gravity models

NASA Astrophysics Data System (ADS)

Karimov, R. Kh.; Izmailov, R. N.; Potapov, A. A.; Nandi, K. K.

2018-04-01

Modified gravity theories include f(R)-gravity models that are usually constrained by the cosmological evolutionary scenario. However, it has been recently shown that they can also be constrained by the signatures of accretion disk around constant Ricci curvature Kerr-f(R0) stellar sized black holes. Our aim here is to use another experimental fact, viz., the terrestrial Sagnac delay to constrain the parameters of specific f(R)-gravity prescriptions. We shall assume that a Kerr-f(R0) solution asymptotically describes Earth's weak gravity near its surface. In this spacetime, we shall study oppositely directed light beams from source/observer moving on non-geodesic and geodesic circular trajectories and calculate the time gap, when the beams re-unite. We obtain the exact time gap called Sagnac delay in both cases and expand it to show how the flat space value is corrected by the Ricci curvature, the mass and the spin of the gravitating source. Under the assumption that the magnitude of corrections are of the order of residual uncertainties in the delay measurement, we derive the allowed intervals for Ricci curvature. We conclude that the terrestrial Sagnac delay can be used to constrain the parameters of specific f(R) prescriptions. Despite using the weak field gravity near Earth's surface, it turns out that the model parameter ranges still remain the same as those obtained from the strong field accretion disk phenomenon.

Sensitivity Analysis Tailored to Constrain 21st Century Terrestrial Carbon-Uptake

NASA Astrophysics Data System (ADS)

Muller, S. J.; Gerber, S.

2013-12-01

The long-term fate of terrestrial carbon (C) in response to climate change remains a dominant source of uncertainty in Earth-system model projections. Increasing atmospheric CO2 could be mitigated by long-term net uptake of C, through processes such as increased plant productivity due to "CO2-fertilization". Conversely, atmospheric conditions could be exacerbated by long-term net release of C, through processes such as increased decomposition due to higher temperatures. This balance is an important area of study, and a major source of uncertainty in long-term (>year 2050) projections of planetary response to climate change. We present results from an innovative application of sensitivity analysis to LM3V, a dynamic global vegetation model (DGVM), intended to identify observed/observable variables that are useful for constraining long-term projections of C-uptake. We analyzed the sensitivity of cumulative C-uptake by 2100, as modeled by LM3V in response to IPCC AR4 scenario climate data (1860-2100), to perturbations in over 50 model parameters. We concurrently analyzed the sensitivity of over 100 observable model variables, during the extant record period (1970-2010), to the same parameter changes. By correlating the sensitivities of observable variables with the sensitivity of long-term C-uptake we identified model calibration variables that would also constrain long-term C-uptake projections. LM3V employs a coupled carbon-nitrogen cycle to account for N-limitation, and we find that N-related variables have an important role to play in constraining long-term C-uptake. This work has implications for prioritizing field campaigns to collect global data that can help reduce uncertainties in the long-term land-atmosphere C-balance. Though results of this study are specific to LM3V, the processes that characterize this model are not completely divorced from other DGVMs (or reality), and our approach provides valuable insights into how data can be leveraged to be better constrain projections for the land carbon sink.

p53 constrains progression to anaplastic thyroid carcinoma in a Braf-mutant mouse model of papillary thyroid cancer

PubMed Central

McFadden, David G.; Vernon, Amanda; Santiago, Philip M.; Martinez-McFaline, Raul; Bhutkar, Arjun; Crowley, Denise M.; McMahon, Martin; Sadow, Peter M.; Jacks, Tyler

2014-01-01

Anaplastic thyroid carcinoma (ATC) has among the worst prognoses of any solid malignancy. The low incidence of the disease has in part precluded systematic clinical trials and tissue collection, and there has been little progress in developing effective therapies. v-raf murine sarcoma viral oncogene homolog B (BRAF) and tumor protein p53 (TP53) mutations cooccur in a high proportion of ATCs, particularly those associated with a precursor papillary thyroid carcinoma (PTC). To develop an adult-onset model of BRAF-mutant ATC, we generated a thyroid-specific CreER transgenic mouse. We used a Cre-regulated BrafV600E mouse and a conditional Trp53 allelic series to demonstrate that p53 constrains progression from PTC to ATC. Gene expression and immunohistochemical analyses of murine tumors identified the cardinal features of human ATC including loss of differentiation, local invasion, distant metastasis, and rapid lethality. We used small-animal ultrasound imaging to monitor autochthonous tumors and showed that treatment with the selective BRAF inhibitor PLX4720 improved survival but did not lead to tumor regression or suppress signaling through the MAPK pathway. The combination of PLX4720 and the mapk/Erk kinase (MEK) inhibitor PD0325901 more completely suppressed MAPK pathway activation in mouse and human ATC cell lines and improved the structural response and survival of ATC-bearing animals. This model expands the limited repertoire of autochthonous models of clinically aggressive thyroid cancer, and these data suggest that small-molecule MAPK pathway inhibitors hold clinical promise in the treatment of advanced thyroid carcinoma. PMID:24711431

Transient groundwater dynamics in a coastal aquifer: The effects of tides, the lunar cycle, and the beach profile

NASA Astrophysics Data System (ADS)

Abarca, Elena; Karam, Hanan; Hemond, Harold F.; Harvey, Charles F.

2013-05-01

Detailed field measurements are combined with a numerical modeling to characterize the groundwater dynamics beneath the discharge zone at Waquoit Bay, Massachusetts. Groundwater salinity values revealed a saline circulation cell that overlaid the discharging freshwater and grew and disappeared with the lunar cycle. The cell was initiated by a greater bay water infiltration during the new moon when high tides overtopped the mean high-tide mark, flooding the flatter beach berm and inundating a larger area of the beach. The dynamics of this cell were further characterized by a tracer test and by constructing a density-dependent flow model constrained to salinity and head data. The numerical model captured the growing and diminishing behavior of the circulation cell and provided the estimates of freshwater and saline water fluxes and travel times. Furthermore, the model enabled quantification of the relationship between the characteristics of the observed tidal cycle (maximum, minimum, and mean tidal elevations) and the different components of the groundwater circulation (freshwater discharge, intertidal saline cycling, and deep saline cycling). We found that (1) recharge to the intertidal saline cell is largely controlled by the high-tide elevation; (2) freshwater discharge is positively correlated to the low-tide elevation, whereas deep saline discharge from below the discharging freshwater is negatively correlated to the low-tide elevation. So, when the low-tide elevation is relatively high, more freshwater discharges and less deep saltwater discharges. In contrast when low tides are very low, less freshwater discharges and more deep salt water discharges; (3) offshore inflow of saline water is largely insensitive to tides and the lunar cycle.

Early patterning in a chondrichthyan model, the small spotted dogfish: towards the gnathostome ancestral state

PubMed Central

Godard, B G; Mazan, S

2013-01-01

In the past few years, the small spotted dogfish has become the primary model for analyses of early development in chondrichthyans. Its phylogenetic position makes it an ideal outgroup to reconstruct the ancestral gnathostome state by comparisons with established vertebrate model organisms. It is also a suitable model to address the molecular bases of lineage-specific diversifications such as the rise of extraembryonic tissues, as it is endowed with a distinct extraembryonic yolk sac and yolk duct ensuring exchanges between the embryo and a large undivided vitelline mass. Experimental or functional approaches such as cell marking or in ovo pharmacological treatments are emerging in this species, but recent analyses of early development in this species have primarily concentrated on molecular descriptions. These data show the dogfish embryo exhibits early polarities reflecting the dorso-ventral axis of amphibians and teleosts at early blastula stages and an atypical anamniote molecular pattern during gastrulation, independently of the presence of extraembryonic tissues. They also highlight unexpected relationships with amniotes, with a strikingly similar Nodal-dependent regional pattern in the extraembryonic endoderm. In this species, extraembryonic cell fates seem to be determined by differential cell behaviors, which lead to cell allocation in extraembryonic and embryonic tissues, rather than by cell regional identity. We suggest that this may exemplify an early evolutionary step in the rise of extraembryonic tissues, possibly related to quantitative differences in the signaling activities, which shape the early embryo. These results highlight the conservation across gnathostomes of a highly constrained core genetic program controlling early patterning. This conservation may be obscured in some lineages by taxa-specific diversifications such as specializations of extraembryonic nutritive tissues. PMID:22905913

Super-resolution imaging of multiple cells by optimized flat-field epi-illumination

NASA Astrophysics Data System (ADS)

Douglass, Kyle M.; Sieben, Christian; Archetti, Anna; Lambert, Ambroise; Manley, Suliana

2016-11-01

Biological processes are inherently multi-scale, and supramolecular complexes at the nanoscale determine changes at the cellular scale and beyond. Single-molecule localization microscopy (SMLM) techniques have been established as important tools for studying cellular features with resolutions of the order of around 10 nm. However, in their current form these modalities are limited by a highly constrained field of view (FOV) and field-dependent image resolution. Here, we develop a low-cost microlens array (MLA)-based epi-illumination system—flat illumination for field-independent imaging (FIFI)—that can efficiently and homogeneously perform simultaneous imaging of multiple cells with nanoscale resolution. The optical principle of FIFI, which is an extension of the Köhler integrator, is further elucidated and modelled with a new, free simulation package. We demonstrate FIFI's capabilities by imaging multiple COS-7 and bacteria cells in 100 × 100 μm2 SMLM images—more than quadrupling the size of a typical FOV and producing near-gigapixel-sized images of uniformly high quality.

Cellular and dendritic growth in a binary melt - A marginal stability approach

NASA Technical Reports Server (NTRS)

Laxmanan, V.

1986-01-01

A simple model for the constrained growth of an array of cells or dendrites in a binary alloy in the presence of an imposed positive temperature gradient in the liquid is proposed, with the dendritic or cell tip radius calculated using the marginal stability criterion of Langer and Muller-Krumbhaar (1977). This approach, an approach adopting the ad hoc assumption of minimum undercooling at the cell or dendrite tip, and an approach based on the stability criterion of Trivedi (1980) all predict tip radii to within 30 percent of each other, and yield a simple relationship between the tip radius and the growth conditions. Good agreement is found between predictions and data obtained in a succinonitrile-acetone system, and under the present experimental conditions, the dendritic tip stability parameter value is found to be twice that obtained previously, possibly due to a transition in morphology from a cellular structure with just a few side branches, to a more fully developed dendritic structure.

Highly Constrained Bicyclic Scaffolds for the Discovery of Protease-Stable Peptides via mRNA Display.

PubMed

Hacker, David E; Hoinka, Jan; Iqbal, Emil S; Przytycka, Teresa M; Hartman, Matthew C T

2017-03-17

Highly constrained peptides such as the knotted peptide natural products are promising medicinal agents because of their impressive biostability and potent activity. Yet, libraries of highly constrained peptides are challenging to prepare. Here, we present a method which utilizes two robust, orthogonal chemical steps to create highly constrained bicyclic peptide libraries. This technology was optimized to be compatible with in vitro selections by mRNA display. We performed side-by-side monocyclic and bicyclic selections against a model protein (streptavidin). Both selections resulted in peptides with mid-nanomolar affinity, and the bicyclic selection yielded a peptide with remarkable protease resistance.

Fuzzy multi-objective chance-constrained programming model for hazardous materials transportation

NASA Astrophysics Data System (ADS)

Du, Jiaoman; Yu, Lean; Li, Xiang

2016-04-01

Hazardous materials transportation is an important and hot issue of public safety. Based on the shortest path model, this paper presents a fuzzy multi-objective programming model that minimizes the transportation risk to life, travel time and fuel consumption. First, we present the risk model, travel time model and fuel consumption model. Furthermore, we formulate a chance-constrained programming model within the framework of credibility theory, in which the lengths of arcs in the transportation network are assumed to be fuzzy variables. A hybrid intelligent algorithm integrating fuzzy simulation and genetic algorithm is designed for finding a satisfactory solution. Finally, some numerical examples are given to demonstrate the efficiency of the proposed model and algorithm.

Constraining the Mechanism of D" Anisotropy: Diversity of Observation Types Required

NASA Astrophysics Data System (ADS)

Creasy, N.; Pisconti, A.; Long, M. D.; Thomas, C.

2017-12-01

A variety of different mechanisms have been proposed as explanations for seismic anisotropy at the base of the mantle, including crystallographic preferred orientation of various minerals (bridgmanite, post-perovskite, and ferropericlase) and shape preferred orientation of elastically distinct materials such as partial melt. Investigations of the mechanism for D" anisotropy are usually ambiguous, as seismic observations rarely (if ever) uniquely constrain a mechanism. Observations of shear wave splitting and polarities of SdS and PdP reflections off the D" discontinuity are among our best tools for probing D" anisotropy; however, typical data sets cannot constrain a unique scenario suggested by the mineral physics literature. In this work, we determine what types of body wave observations are required to uniquely constrain a mechanism for D" anisotropy. We test multiple possible models based on both single-crystal and poly-phase elastic tensors provided by mineral physics studies. We predict shear wave splitting parameters for SKS, SKKS, and ScS phases and reflection polarities off the D" interface for a range of possible propagation directions. We run a series of tests that create synthetic data sets by random selection over multiple iterations, controlling the total number of measurements, the azimuthal distribution, and the type of phases. We treat each randomly drawn synthetic dataset with the same methodology as in Ford et al. (2015) to determine the possible mechanism(s), carrying out a grid search over all possible elastic tensors and orientations to determine which are consistent with the synthetic data. We find is it difficult to uniquely constrain the starting model with a realistic number of seismic anisotropy measurements with only one measurement technique or phase type. However, having a mix of SKS, SKKS, and ScS measurements, or a mix of shear wave splitting and reflection polarity measurements, dramatically increases the probability of uniquely constraining the starting model. We also explore what types of datasets are needed to uniquely constrain the orientation(s) of anisotropic symmetry if the mechanism is assumed.

Constraining the dark energy equation of state using Bayes theorem and the Kullback-Leibler divergence

NASA Astrophysics Data System (ADS)

Hee, S.; Vázquez, J. A.; Handley, W. J.; Hobson, M. P.; Lasenby, A. N.

2017-04-01

Data-driven model-independent reconstructions of the dark energy equation of state w(z) are presented using Planck 2015 era cosmic microwave background, baryonic acoustic oscillations (BAO), Type Ia supernova (SNIa) and Lyman α (Lyα) data. These reconstructions identify the w(z) behaviour supported by the data and show a bifurcation of the equation of state posterior in the range 1.5 < z < 3. Although the concordance Λ cold dark matter (ΛCDM) model is consistent with the data at all redshifts in one of the bifurcated spaces, in the other, a supernegative equation of state (also known as 'phantom dark energy') is identified within the 1.5σ confidence intervals of the posterior distribution. To identify the power of different data sets in constraining the dark energy equation of state, we use a novel formulation of the Kullback-Leibler divergence. This formalism quantifies the information the data add when moving from priors to posteriors for each possible data set combination. The SNIa and BAO data sets are shown to provide much more constraining power in comparison to the Lyα data sets. Further, SNIa and BAO constrain most strongly around redshift range 0.1-0.5, whilst the Lyα data constrain weakly over a broader range. We do not attribute the supernegative favouring to any particular data set, and note that the ΛCDM model was favoured at more than 2 log-units in Bayes factors over all the models tested despite the weakly preferred w(z) structure in the data.

Constraining ecosystem processes from tower fluxes and atmospheric profiles.

PubMed

Hill, T C; Williams, M; Woodward, F I; Moncrieff, J B

2011-07-01

The planetary boundary layer (PBL) provides an important link between the scales and processes resolved by global atmospheric sampling/modeling and site-based flux measurements. The PBL is in direct contact with the land surface, both driving and responding to ecosystem processes. Measurements within the PBL (e.g., by radiosondes, aircraft profiles, and flask measurements) have a footprint, and thus an integrating scale, on the order of 1-100 km. We use the coupled atmosphere-biosphere model (CAB) and a Bayesian data assimilation framework to investigate the amount of biosphere process information that can be inferred from PBL measurements. We investigate the information content of PBL measurements in a two-stage study. First, we demonstrate consistency between the coupled model (CAB) and measurements, by comparing the model to eddy covariance flux tower measurements (i.e., water and carbon fluxes) and also PBL scalar profile measurements (i.e., water, carbon dioxide, and temperature) from Canadian boreal forest. Second, we use the CAB model in a set of Bayesian inversions experiments using synthetic data for a single day. In the synthetic experiment, leaf area and respiration were relatively well constrained, whereas surface albedo and plant hydraulic conductance were only moderately constrained. Finally, the abilities of the PBL profiles and the eddy covariance data to constrain the parameters were largely similar and only slightly lower than the combination of both observations.

Weighting climate model projections using observational constraints.

PubMed

Gillett, Nathan P

2015-11-13

Projected climate change integrates the net response to multiple climate feedbacks. Whereas existing long-term climate change projections are typically based on unweighted individual climate model simulations, as observed climate change intensifies it is increasingly becoming possible to constrain the net response to feedbacks and hence projected warming directly from observed climate change. One approach scales simulated future warming based on a fit to observations over the historical period, but this approach is only accurate for near-term projections and for scenarios of continuously increasing radiative forcing. For this reason, the recent Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) included such observationally constrained projections in its assessment of warming to 2035, but used raw model projections of longer term warming to 2100. Here a simple approach to weighting model projections based on an observational constraint is proposed which does not assume a linear relationship between past and future changes. This approach is used to weight model projections of warming in 2081-2100 relative to 1986-2005 under the Representative Concentration Pathway 4.5 forcing scenario, based on an observationally constrained estimate of the Transient Climate Response derived from a detection and attribution analysis. The resulting observationally constrained 5-95% warming range of 0.8-2.5 K is somewhat lower than the unweighted range of 1.1-2.6 K reported in the IPCC AR5. © 2015 The Authors.

Modeling and stabilization results for a charge or current-actuated active constrained layer (ACL) beam model with the electrostatic assumption

NASA Astrophysics Data System (ADS)

Özer, Ahmet Özkan

2016-04-01

An infinite dimensional model for a three-layer active constrained layer (ACL) beam model, consisting of a piezoelectric elastic layer at the top and an elastic host layer at the bottom constraining a viscoelastic layer in the middle, is obtained for clamped-free boundary conditions by using a thorough variational approach. The Rao-Nakra thin compliant layer approximation is adopted to model the sandwich structure, and the electrostatic approach (magnetic effects are ignored) is assumed for the piezoelectric layer. Instead of the voltage actuation of the piezoelectric layer, the piezoelectric layer is proposed to be activated by a charge (or current) source. We show that, the closed-loop system with all mechanical feedback is shown to be uniformly exponentially stable. Our result is the outcome of the compact perturbation argument and a unique continuation result for the spectral problem which relies on the multipliers method. Finally, the modeling methodology of the paper is generalized to the multilayer ACL beams, and the uniform exponential stabilizability result is established analogously.

A method for fitting regression splines with varying polynomial order in the linear mixed model.

PubMed

Edwards, Lloyd J; Stewart, Paul W; MacDougall, James E; Helms, Ronald W

2006-02-15

The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.

Accuracy of the Generalized Self-Consistent Method in Modelling the Elastic Behaviour of Periodic Composites

NASA Technical Reports Server (NTRS)

Walker, Kevin P.; Freed, Alan D.; Jordan, Eric H.

1993-01-01

Local stress and strain fields in the unit cell of an infinite, two-dimensional, periodic fibrous lattice have been determined by an integral equation approach. The effect of the fibres is assimilated to an infinite two-dimensional array of fictitious body forces in the matrix constituent phase of the unit cell. By subtracting a volume averaged strain polarization term from the integral equation we effectively embed a finite number of unit cells in a homogenized medium in which the overall stress and strain correspond to the volume averaged stress and strain of the constrained unit cell. This paper demonstrates that the zeroth term in the governing integral equation expansion, which embeds one unit cell in the homogenized medium, corresponds to the generalized self-consistent approximation. By comparing the zeroth term approximation with higher order approximations to the integral equation summation, both the accuracy of the generalized self-consistent composite model and the rate of convergence of the integral summation can be assessed. Two example composites are studied. For a tungsten/copper elastic fibrous composite the generalized self-consistent model is shown to provide accurate, effective, elastic moduli and local field representations. The local elastic transverse stress field within the representative volume element of the generalized self-consistent method is shown to be in error by much larger amounts for a composite with periodically distributed voids, but homogenization leads to a cancelling of errors, and the effective transverse Young's modulus of the voided composite is shown to be in error by only 23% at a void volume fraction of 75%.

Constraining gross primary production and ecosystem respiration estimates for North America using atmospheric observations of carbonyl sulfide (OCS) and CO2

NASA Astrophysics Data System (ADS)

He, W.; Ju, W.; Chen, H.; Peters, W.; van der Velde, I.; Baker, I. T.; Andrews, A. E.; Zhang, Y.; Launois, T.; Campbell, J. E.; Suntharalingam, P.; Montzka, S. A.

2016-12-01

Carbonyl sulfide (OCS) is a promising novel atmospheric tracer for studying carbon cycle processes. OCS shares a similar pathway as CO2 during photosynthesis but not released through a respiration-like process, thus could be used to partition Gross Primary Production (GPP) from Net Ecosystem-atmosphere CO2 Exchange (NEE). This study uses joint atmospheric observations of OCS and CO2 to constrain GPP and ecosystem respiration (Re). Flask data from tower and aircraft sites over North America are collected. We employ our recently developed CarbonTracker (CT)-Lagrange carbon assimilation system, which is based on the CT framework and the Weather Research and Forecasting - Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) model, and the Simple Biosphere model with simulated OCS (SiB3-OCS) that provides prior GPP, Re and plant uptake fluxes of OCS. Derived plant OCS fluxes from both process model and GPP-scaled model are tested in our inversion. To investigate the ability of OCS to constrain GPP and understand the uncertainty propagated from OCS modeling errors to constrained fluxes in a dual-tracer system including OCS and CO2, two inversion schemes are implemented and compared: (1) a two-step scheme, which firstly optimizes GPP using OCS observations, and then simultaneously optimizes GPP and Re using CO2 observations with OCS-constrained GPP in the first step as prior; (2) a joint scheme, which simultaneously optimizes GPP and Re using OCS and CO2 observations. We will evaluate the result using an estimated GPP from space-borne solar-induced fluorescence observations and a data-driven GPP upscaled from FLUXNET data with a statistical model (Jung et al., 2011). Preliminary result for the year 2010 shows the joint inversion makes simulated mole fractions more consistent with observations for both OCS and CO2. However, the uncertainty of OCS simulation is larger than that of CO2. The two-step and joint schemes perform similarly in improving the consistence with observations for OCS, implicating that OCS could provide independent constraint in joint inversion. Optimization makes less total GPP and Re but more NEE, when testing with prior CO2 fluxes from two biosphere models. This study gives an in-depth insight into the role of joint atmospheric OCS and CO2 observations in constraining CO2 fluxes.

Inexact nonlinear improved fuzzy chance-constrained programming model for irrigation water management under uncertainty

NASA Astrophysics Data System (ADS)

Zhang, Chenglong; Zhang, Fan; Guo, Shanshan; Liu, Xiao; Guo, Ping

2018-01-01

An inexact nonlinear mλ-measure fuzzy chance-constrained programming (INMFCCP) model is developed for irrigation water allocation under uncertainty. Techniques of inexact quadratic programming (IQP), mλ-measure, and fuzzy chance-constrained programming (FCCP) are integrated into a general optimization framework. The INMFCCP model can deal with not only nonlinearities in the objective function, but also uncertainties presented as discrete intervals in the objective function, variables and left-hand side constraints and fuzziness in the right-hand side constraints. Moreover, this model improves upon the conventional fuzzy chance-constrained programming by introducing a linear combination of possibility measure and necessity measure with varying preference parameters. To demonstrate its applicability, the model is then applied to a case study in the middle reaches of Heihe River Basin, northwest China. An interval regression analysis method is used to obtain interval crop water production functions in the whole growth period under uncertainty. Therefore, more flexible solutions can be generated for optimal irrigation water allocation. The variation of results can be examined by giving different confidence levels and preference parameters. Besides, it can reflect interrelationships among system benefits, preference parameters, confidence levels and the corresponding risk levels. Comparison between interval crop water production functions and deterministic ones based on the developed INMFCCP model indicates that the former is capable of reflecting more complexities and uncertainties in practical application. These results can provide more reliable scientific basis for supporting irrigation water management in arid areas.

Towards anatomic scale agent-based modeling with a massively parallel spatially explicit general-purpose model of enteric tissue (SEGMEnT_HPC).

PubMed

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis.

MicroRNA-146a constrains multiple parameters of intestinal immunity and increases susceptibility to DSS colitis.

PubMed

Runtsch, Marah C; Hu, Ruozhen; Alexander, Margaret; Wallace, Jared; Kagele, Dominique; Petersen, Charisse; Valentine, John F; Welker, Noah C; Bronner, Mary P; Chen, Xinjian; Smith, Daniel P; Ajami, Nadim J; Petrosino, Joseph F; Round, June L; O'Connell, Ryan M

2015-10-06

Host-microbial interactions within the mammalian intestines must be properly regulated in order to promote host health and limit disease. Because the microbiota provide constant immunological signals to intestinal tissues, a variety of regulatory mechanisms have evolved to ensure proper immune responses to maintain homeostasis. However, many of the genes that comprise these regulatory pathways, including immune-modulating microRNAs (miRNAs), have not yet been identified or studied in the context of intestinal homeostasis. Here, we investigated the role of microRNA-146a (miR-146a) in regulating intestinal immunity and barrier function and found that this miRNA is expressed in a variety of gut tissues in adult mice. By comparing intestinal gene expression in WT and miR-146a-/- mice, we demonstrate that miR-146a represses a subset of gut barrier and inflammatory genes all within a network of immune-related signaling pathways. We also found that miR-146a restricts the expansion of intestinal T cell populations, including Th17, Tregs, and Tfh cells. GC B cells, Tfh ICOS expression, and the production of luminal IgA were also reduced by miR-146a in the gut. Consistent with an enhanced intestinal barrier, we found that miR-146a-/- mice are resistant to DSS-induced colitis, a model of Ulcerative Colitis (UC), and this correlated with elevated colonic miR-146a expression in human UC patients. Taken together, our data describe a role for miR-146a in constraining intestinal barrier function, a process that alters gut homeostasis and enhances at least some forms of intestinal disease in mice.

MicroRNA-146a constrains multiple parameters of intestinal immunity and increases susceptibility to DSS colitis

PubMed Central

Runtsch, Marah C.; Hu, Ruozhen; Alexander, Margaret; Wallace, Jared; Kagele, Dominique; Petersen, Charisse; Valentine, John F.; Welker, Noah C.; Bronner, Mary P.; Chen, Xinjian; Smith, Daniel P.; Ajami, Nadim J.; Petrosino, Joseph F.; Round, June L.; O'Connell, Ryan M.

2015-01-01

Host-microbial interactions within the mammalian intestines must be properly regulated in order to promote host health and limit disease. Because the microbiota provide constant immunological signals to intestinal tissues, a variety of regulatory mechanisms have evolved to ensure proper immune responses to maintain homeostasis. However, many of the genes that comprise these regulatory pathways, including immune-modulating microRNAs (miRNAs), have not yet been identified or studied in the context of intestinal homeostasis. Here, we investigated the role of microRNA-146a (miR-146a) in regulating intestinal immunity and barrier function and found that this miRNA is expressed in a variety of gut tissues in adult mice. By comparing intestinal gene expression in WT and miR-146a−/− mice, we demonstrate that miR-146a represses a subset of gut barrier and inflammatory genes all within a network of immune-related signaling pathways. We also found that miR-146a restricts the expansion of intestinal T cell populations, including Th17, Tregs, and Tfh cells. GC B cells, Tfh ICOS expression, and the production of luminal IgA were also reduced by miR-146a in the gut. Consistent with an enhanced intestinal barrier, we found that miR-146a−/− mice are resistant to DSS-induced colitis, a model of Ulcerative Colitis (UC), and this correlated with elevated colonic miR-146a expression in human UC patients. Taken together, our data describe a role for miR-146a in constraining intestinal barrier function, a process that alters gut homeostasis and enhances at least some forms of intestinal disease in mice. PMID:26456940

Experimental study of a constrained vapor bubble fin heat exchanger in the absence of external natural convection.

PubMed

Basu, Sumita; Plawsky, Joel L; Wayner, Peter C

2004-11-01

In preparation for a microgravity flight experiment on the International Space Station, a constrained vapor bubble fin heat exchanger (CVB) was operated both in a vacuum chamber and in air on Earth to evaluate the effect of the absence of external natural convection. The long-term objective is a general study of a high heat flux, low capillary pressure system with small viscous effects due to the relatively large 3 x 3 x 40 mm dimensions. The current CVB can be viewed as a large-scale version of a micro heat pipe with a large Bond number in the Earth environment but a small Bond number in microgravity. The walls of the CVB are quartz, to allow for image analysis of naturally occurring interference fringes that give the pressure field for liquid flow. The research is synergistic in that the study requires a microgravity environment to obtain a low Bond number and the space program needs thermal control systems, like the CVB, with a large characteristic dimension. In the absence of natural convection, operation of the CVB may be dominated by external radiative losses from its quartz surface. Therefore, an understanding of radiation from the quartz cell is required. All radiative exchange with the surroundings occurs from the outer surface of the CVB when the temperature range renders the quartz walls of the CVB optically thick (lambda > 4 microns). However, for electromagnetic radiation where lambda < 2 microns, the walls are transparent. Experimental results obtained for a cell charged with pentane are compared with those obtained for a dry cell. A numerical model was developed that successfully simulated the behavior and performance of the device observed experimentally.

Charge redistribution in QM:QM ONIOM model systems: a constrained density functional theory approach

NASA Astrophysics Data System (ADS)

Beckett, Daniel; Krukau, Aliaksandr; Raghavachari, Krishnan

2017-11-01

The ONIOM hybrid method has found considerable success in QM:QM studies designed to approximate a high level of theory at a significantly reduced cost. This cost reduction is achieved by treating only a small model system with the target level of theory and the rest of the system with a low, inexpensive, level of theory. However, the choice of an appropriate model system is a limiting factor in ONIOM calculations and effects such as charge redistribution across the model system boundary must be considered as a source of error. In an effort to increase the general applicability of the ONIOM model, a method to treat the charge redistribution effect is developed using constrained density functional theory (CDFT) to constrain the charge experienced by the model system in the full calculation to the link atoms in the truncated model system calculations. Two separate CDFT-ONIOM schemes are developed and tested on a set of 20 reactions with eight combinations of levels of theory. It is shown that a scheme using a scaled Lagrange multiplier term obtained from the low-level CDFT model calculation outperforms ONIOM at each combination of levels of theory from 32% to 70%.

A method to identify and analyze biological programs through automated reasoning

PubMed Central

Yordanov, Boyan; Dunn, Sara-Jane; Kugler, Hillel; Smith, Austin; Martello, Graziano; Emmott, Stephen

2016-01-01

Predictive biology is elusive because rigorous, data-constrained, mechanistic models of complex biological systems are difficult to derive and validate. Current approaches tend to construct and examine static interaction network models, which are descriptively rich, but often lack explanatory and predictive power, or dynamic models that can be simulated to reproduce known behavior. However, in such approaches implicit assumptions are introduced as typically only one mechanism is considered, and exhaustively investigating all scenarios is impractical using simulation. To address these limitations, we present a methodology based on automated formal reasoning, which permits the synthesis and analysis of the complete set of logical models consistent with experimental observations. We test hypotheses against all candidate models, and remove the need for simulation by characterizing and simultaneously analyzing all mechanistic explanations of observed behavior. Our methodology transforms knowledge of complex biological processes from sets of possible interactions and experimental observations to precise, predictive biological programs governing cell function. PMID:27668090

An Integrative Breakage Model of genome architecture, reshuffling and evolution: The Integrative Breakage Model of genome evolution, a novel multidisciplinary hypothesis for the study of genome plasticity.

PubMed

Farré, Marta; Robinson, Terence J; Ruiz-Herrera, Aurora

2015-05-01

Our understanding of genomic reorganization, the mechanics of genomic transmission to offspring during germ line formation, and how these structural changes contribute to the speciation process, and genetic disease is far from complete. Earlier attempts to understand the mechanism(s) and constraints that govern genome remodeling suffered from being too narrowly focused, and failed to provide a unified and encompassing view of how genomes are organized and regulated inside cells. Here, we propose a new multidisciplinary Integrative Breakage Model for the study of genome evolution. The analysis of the high-level structural organization of genomes (nucleome), together with the functional constrains that accompany genome reshuffling, provide insights into the origin and plasticity of genome organization that may assist with the detection and isolation of therapeutic targets for the treatment of complex human disorders. © 2015 WILEY Periodicals, Inc.

Dynamical estimation of neuron and network properties III: network analysis using neuron spike times.

PubMed

Knowlton, Chris; Meliza, C Daniel; Margoliash, Daniel; Abarbanel, Henry D I

2014-06-01

Estimating the behavior of a network of neurons requires accurate models of the individual neurons along with accurate characterizations of the connections among them. Whereas for a single cell, measurements of the intracellular voltage are technically feasible and sufficient to characterize a useful model of its behavior, making sufficient numbers of simultaneous intracellular measurements to characterize even small networks is infeasible. This paper builds on prior work on single neurons to explore whether knowledge of the time of spiking of neurons in a network, once the nodes (neurons) have been characterized biophysically, can provide enough information to usefully constrain the functional architecture of the network: the existence of synaptic links among neurons and their strength. Using standardized voltage and synaptic gating variable waveforms associated with a spike, we demonstrate that the functional architecture of a small network of model neurons can be established.

Reading biological processes from nucleotide sequences

NASA Astrophysics Data System (ADS)

Murugan, Anand

Cellular processes have traditionally been investigated by techniques of imaging and biochemical analysis of the molecules involved. The recent rapid progress in our ability to manipulate and read nucleic acid sequences gives us direct access to the genetic information that directs and constrains biological processes. While sequence data is being used widely to investigate genotype-phenotype relationships and population structure, here we use sequencing to understand biophysical mechanisms. We present work on two different systems. First, in chapter 2, we characterize the stochastic genetic editing mechanism that produces diverse T-cell receptors in the human immune system. We do this by inferring statistical distributions of the underlying biochemical events that generate T-cell receptor coding sequences from the statistics of the observed sequences. This inferred model quantitatively describes the potential repertoire of T-cell receptors that can be produced by an individual, providing insight into its potential diversity and the probability of generation of any specific T-cell receptor. Then in chapter 3, we present work on understanding the functioning of regulatory DNA sequences in both prokaryotes and eukaryotes. Here we use experiments that measure the transcriptional activity of large libraries of mutagenized promoters and enhancers and infer models of the sequence-function relationship from this data. For the bacterial promoter, we infer a physically motivated 'thermodynamic' model of the interaction of DNA-binding proteins and RNA polymerase determining the transcription rate of the downstream gene. For the eukaryotic enhancers, we infer heuristic models of the sequence-function relationship and use these models to find synthetic enhancer sequences that optimize inducibility of expression. Both projects demonstrate the utility of sequence information in conjunction with sophisticated statistical inference techniques for dissecting underlying biophysical mechanisms.

Rational Engineering and Characterization of an mAb that Neutralizes Zika Virus by Targeting a Mutationally Constrained Quaternary Epitope.

PubMed

Tharakaraman, Kannan; Watanabe, Satoru; Chan, Kuan Rong; Huan, Jia; Subramanian, Vidya; Chionh, Yok Hian; Raguram, Aditya; Quinlan, Devin; McBee, Megan; Ong, Eugenia Z; Gan, Esther S; Tan, Hwee Cheng; Tyagi, Anu; Bhushan, Shashi; Lescar, Julien; Vasudevan, Subhash G; Ooi, Eng Eong; Sasisekharan, Ram

2018-05-09

Following the recent emergence of Zika virus (ZIKV), many murine and human neutralizing anti-ZIKV antibodies have been reported. Given the risk of virus escape mutants, engineering antibodies that target mutationally constrained epitopes with therapeutically relevant potencies can be valuable for combating future outbreaks. Here, we applied computational methods to engineer an antibody, ZAb_FLEP, that targets a highly networked and therefore mutationally constrained surface formed by the envelope protein dimer. ZAb_FLEP neutralized a breadth of ZIKV strains and protected mice in distinct in vivo models, including resolving vertical transmission and fetal mortality in infected pregnant mice. Serial passaging of ZIKV in the presence of ZAb_FLEP failed to generate viral escape mutants, suggesting that its epitope is indeed mutationally constrained. A single-particle cryo-EM reconstruction of the Fab-ZIKV complex validated the structural model and revealed insights into ZAb_FLEP's neutralization mechanism. ZAb_FLEP has potential as a therapeutic in future outbreaks. Copyright © 2018. Published by Elsevier Inc.

Taylor O(h³) Discretization of ZNN Models for Dynamic Equality-Constrained Quadratic Programming With Application to Manipulators.

PubMed

Liao, Bolin; Zhang, Yunong; Jin, Long

2016-02-01

In this paper, a new Taylor-type numerical differentiation formula is first presented to discretize the continuous-time Zhang neural network (ZNN), and obtain higher computational accuracy. Based on the Taylor-type formula, two Taylor-type discrete-time ZNN models (termed Taylor-type discrete-time ZNNK and Taylor-type discrete-time ZNNU models) are then proposed and discussed to perform online dynamic equality-constrained quadratic programming. For comparison, Euler-type discrete-time ZNN models (called Euler-type discrete-time ZNNK and Euler-type discrete-time ZNNU models) and Newton iteration, with interesting links being found, are also presented. It is proved herein that the steady-state residual errors of the proposed Taylor-type discrete-time ZNN models, Euler-type discrete-time ZNN models, and Newton iteration have the patterns of O(h(3)), O(h(2)), and O(h), respectively, with h denoting the sampling gap. Numerical experiments, including the application examples, are carried out, of which the results further substantiate the theoretical findings and the efficacy of Taylor-type discrete-time ZNN models. Finally, the comparisons with Taylor-type discrete-time derivative model and other Lagrange-type discrete-time ZNN models for dynamic equality-constrained quadratic programming substantiate the superiority of the proposed Taylor-type discrete-time ZNN models once again.

DART: New Research Using Ensemble Data Assimilation in Geophysical Models

NASA Astrophysics Data System (ADS)

Hoar, T. J.; Raeder, K.

2015-12-01

The Data Assimilation Research Testbed (DART) is a community facilityfor ensemble data assimilation developed and supported by the NationalCenter for Atmospheric Research. DART provides a comprehensive suite of software, documentation, and tutorials that can be used for ensemble data assimilation research, operations, and education. Scientists and software engineers at NCAR are available to support DART users who want to use existing DART products or develop their own applications. Current DART users range from university professors teaching data assimilation, to individual graduate students working with simple models, through national laboratories doing operational prediction with large state-of-the-art models. DART runs efficiently on many computational platforms ranging from laptops through thousands of cores on the newest supercomputers.This poster focuses on several recent research activities using DART with geophysical models.Using CAM/DART to understand whether OCO-2 Total Precipitable Water observations can be useful in numerical weather prediction.Impacts of the synergistic use of Infra-red CO retrievals (MOPITT, IASI) in CAM-CHEM/DART assimilations.Assimilation and Analysis of Observations of Amazonian Biomass Burning Emissions by MOPITT (aerosol optical depth), MODIS (carbon monoxide) and MISR (plume height).Long term evaluation of the chemical response of MOPITT-CO assimilation in CAM-CHEM/DART OSSEs for satellite planning and emission inversion capabilities.Improved forward observation operators for land models that have multiple land use/land cover segments in a single grid cell,Simulating mesoscale convective systems (MCSs) using a variable resolution, unstructured grid in the Model for Prediction Across Scales (MPAS) and DART.The mesoscale WRF+DART system generated an ensemble of year-long, real-time initializations of a convection allowing model over the United States.Constraining WACCM with observations in the tropical band (30S-30N) using DART also constrains the polar stratosphere during the same winter. Assimilation of MOPITT carbon monoxide Compact Phase Space Retrievals (CPSR) in WRF-Chem/DART.Future work:DART interface to the CICE (CESM) sea ice model.Fully coupled assimilations in CESM.

Synthesis and structure-activity relationships of constrained heterocyclic analogues of combretastatin A4.

PubMed

Arthuis, Martin; Pontikis, Renée; Chabot, Guy G; Seguin, Johanne; Quentin, Lionel; Bourg, Stéphane; Morin-Allory, Luc; Florent, Jean-Claude

2011-09-05

A series of combretastatin A4 (CA4) analogues with a lactam or lactone ring fused to the trimethoxyphenyl or the B-phenyl moiety were synthesized in an efficient and stereoselective manner by using a domino Heck-Suzuki-Miyaura coupling reaction. The vascular-disrupting potential of these conformationally restricted CA4 analogues was assessed by various in vitro assays: inhibition of tubulin polymerization, modification of endothelial cell morphology, and disruption of endothelial cell cords. Compounds were also evaluated for their growth inhibitory effects against murine and human tumor cells. B-ring-constrained derivatives that contain an oxindole ring (in contrast to compounds with a benzofuranone ring) as well as analogues bearing a six-membered lactone core fused to the trimethoxyphenyl ring are endowed with significant biological activity. The most potent compound of this series (oxindole 9 b) is of particular interest, as it combines chemical stability and a biological activity profile characteristic of a vascular-disrupting agent. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Feedback Circuit among INK4 Tumor Suppressors Constrains Human Glioblastoma Development

PubMed Central

Wiedemeyer, Ruprecht; Brennan, Cameron; Heffernan, Timothy P.; Xiao, Yonghong; Mahoney, John; Protopopov, Alexei; Zheng, Hongwu; Bignell, Graham; Furnari, Frank; Cavenee, Webster K.; Hahn, William C.; Ichimura, Koichi; Collins, V. Peter; Chu, Gerald C.; Stratton, Michael R.; Ligon, Keith L.; Futreal, P. Andrew; Chin, Lynda

2008-01-01

Summary We have developed a nonheuristic genome topography scan (GTS) algorithm to characterize the patterns of genomic alterations in human glioblastoma (GBM), identifying frequent p18INK4C and p16INK4A codeletion. Functional reconstitution of p18INK4C in GBM cells null for both p16INK4A and p18INK4C resulted in impaired cell-cycle progression and tumorigenic potential. Conversely, RNAi-mediated depletion of p18INK4C in p16INK4A-deficient primary astrocytes or established GBM cells enhanced tumorigenicity in vitro and in vivo. Furthermore, acute suppression of p16INK4A in primary astrocytes induced a concomitant increase in p18INK4C. Together, these findings uncover a feedback regulatory circuit in the astrocytic lineage and demonstrate a bona fide tumor suppressor role for p18INK4C in human GBM wherein it functions cooperatively with other INK4 family members to constrain inappropriate proliferation. PMID:18394558

Sensitivity to gaze-contingent contrast increments in naturalistic movies: An exploratory report and model comparison

PubMed Central

Wallis, Thomas S. A.; Dorr, Michael; Bex, Peter J.

2015-01-01

Sensitivity to luminance contrast is a prerequisite for all but the simplest visual systems. To examine contrast increment detection performance in a way that approximates the natural environmental input of the human visual system, we presented contrast increments gaze-contingently within naturalistic video freely viewed by observers. A band-limited contrast increment was applied to a local region of the video relative to the observer's current gaze point, and the observer made a forced-choice response to the location of the target (≈25,000 trials across five observers). We present exploratory analyses showing that performance improved as a function of the magnitude of the increment and depended on the direction of eye movements relative to the target location, the timing of eye movements relative to target presentation, and the spatiotemporal image structure at the target location. Contrast discrimination performance can be modeled by assuming that the underlying contrast response is an accelerating nonlinearity (arising from a nonlinear transducer or gain control). We implemented one such model and examined the posterior over model parameters, estimated using Markov-chain Monte Carlo methods. The parameters were poorly constrained by our data; parameters constrained using strong priors taken from previous research showed poor cross-validated prediction performance. Atheoretical logistic regression models were better constrained and provided similar prediction performance to the nonlinear transducer model. Finally, we explored the properties of an extended logistic regression that incorporates both eye movement and image content features. Models of contrast transduction may be better constrained by incorporating data from both artificial and natural contrast perception settings. PMID:26057546

A probabilistic assessment of calcium carbonate export and dissolution in the modern ocean

NASA Astrophysics Data System (ADS)

Battaglia, Gianna; Steinacher, Marco; Joos, Fortunat

2016-05-01

The marine cycle of calcium carbonate (CaCO3) is an important element of the carbon cycle and co-governs the distribution of carbon and alkalinity within the ocean. However, CaCO3 export fluxes and mechanisms governing CaCO3 dissolution are highly uncertain. We present an observationally constrained, probabilistic assessment of the global and regional CaCO3 budgets. Parameters governing pelagic CaCO3 export fluxes and dissolution rates are sampled using a Monte Carlo scheme to construct a 1000-member ensemble with the Bern3D ocean model. Ensemble results are constrained by comparing simulated and observation-based fields of excess dissolved calcium carbonate (TA*). The minerals calcite and aragonite are modelled explicitly and ocean-sediment fluxes are considered. For local dissolution rates, either a strong or a weak dependency on CaCO3 saturation is assumed. In addition, there is the option to have saturation-independent dissolution above the saturation horizon. The median (and 68 % confidence interval) of the constrained model ensemble for global biogenic CaCO3 export is 0.90 (0.72-1.05) Gt C yr-1, that is within the lower half of previously published estimates (0.4-1.8 Gt C yr-1). The spatial pattern of CaCO3 export is broadly consistent with earlier assessments. Export is large in the Southern Ocean, the tropical Indo-Pacific, the northern Pacific and relatively small in the Atlantic. The constrained results are robust across a range of diapycnal mixing coefficients and, thus, ocean circulation strengths. Modelled ocean circulation and transport timescales for the different set-ups were further evaluated with CFC11 and radiocarbon observations. Parameters and mechanisms governing dissolution are hardly constrained by either the TA* data or the current compilation of CaCO3 flux measurements such that model realisations with and without saturation-dependent dissolution achieve skill. We suggest applying saturation-independent dissolution rates in Earth system models to minimise computational costs.

Ten years of multiple data stream assimilation with the ORCHIDEE land surface model to improve regional to global simulated carbon budgets: synthesis and perspectives on directions for the future

NASA Astrophysics Data System (ADS)

Peylin, P. P.; Bacour, C.; MacBean, N.; Maignan, F.; Bastrikov, V.; Chevallier, F.

2017-12-01

Predicting the fate of carbon stocks and their sensitivity to climate change and land use/management strongly relies on our ability to accurately model net and gross carbon fluxes. However, simulated carbon and water fluxes remain subject to large uncertainties, partly because of unknown or poorly calibrated parameters. Over the past ten years, the carbon cycle data assimilation system at the Laboratoire des Sciences du Climat et de l'Environnement has investigated the benefit of assimilating multiple carbon cycle data streams into the ORCHIDEE LSM, the land surface component of the Institut Pierre Simon Laplace Earth System Model. These datasets have included FLUXNET eddy covariance data (net CO2 flux and latent heat flux) to constrain hourly to seasonal time-scale carbon cycle processes, remote sensing of the vegetation activity (MODIS NDVI) to constrain the leaf phenology, biomass data to constrain "slow" (yearly to decadal) processes of carbon allocation, and atmospheric CO2 concentrations to provide overall large scale constraints on the land carbon sink. Furthermore, we have investigated technical issues related to multiple data stream assimilation and choice of optimization algorithm. This has provided a wide-ranging perspective on the challenges we face in constraining model parameters and thus better quantifying, and reducing, model uncertainty in projections of the future global carbon sink. We review our past studies in terms of the impact of the optimization on key characteristics of the carbon cycle, e.g. the partition of the northern latitudes vs tropical land carbon sink, and compare to the classic atmospheric flux inversion approach. Throughout, we discuss our work in context of the abovementioned challenges, and propose solutions for the community going forward, including the potential of new observations such as atmospheric COS concentrations and satellite-derived Solar Induced Fluorescence to constrain the gross carbon fluxes of the ORCHIDEE model.

Implications of Binary Black Hole Detections on the Merger Rates of Double Neutron Stars and Neutron Star–Black Holes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gupta, Anuradha; Arun, K. G.; Sathyaprakash, B. S., E-mail: axg645@psu.edu, E-mail: kgarun@cmi.ac.in, E-mail: bss25@psu.edu

We show that the inferred merger rate and chirp masses of binary black holes (BBHs) detected by advanced LIGO (aLIGO) can be used to constrain the rate of double neutron star (DNS) and neutron star–black hole (NSBH) mergers in the universe. We explicitly demonstrate this by considering a set of publicly available population synthesis models of Dominik et al. and show that if all the BBH mergers, GW150914, LVT151012, GW151226, and GW170104, observed by aLIGO arise from isolated binary evolution, the predicted DNS merger rate may be constrained to be 2.3–471.0 Gpc{sup −3} yr{sup −1} and that of NSBH mergersmore » will be constrained to 0.2–48.5 Gpc{sup −3} yr{sup −1}. The DNS merger rates are not constrained much, but the NSBH rates are tightened by a factor of ∼4 as compared to their previous rates. Note that these constrained DNS and NSBH rates are extremely model-dependent and are compared to the unconstrained values 2.3–472.5 Gpc{sup −3} yr{sup −1} and 0.2–218 Gpc{sup −3} yr{sup −1}, respectively, using the same models of Dominik et al. (2012a). These rate estimates may have implications for short Gamma Ray Burst progenitor models assuming they are powered (solely) by DNS or NSBH mergers. While these results are based on a set of open access population synthesis models, which may not necessarily be the representative ones, the proposed method is very general and can be applied to any number of models, thereby yielding more realistic constraints on the DNS and NSBH merger rates from the inferred BBH merger rate and chirp mass.« less

Effect of fuel concentration and force on collective transport by a team of dynein motors

PubMed Central

Takshak, Anjneya; Roy, Tanushree; Tandaiya, Parag

2016-01-01

Abstract Motor proteins are essential components of intracellular transport inside eukaryotic cells. These protein molecules use chemical energy obtained from hydrolysis of ATP to produce mechanical forces required for transporting cargos inside cells, from one location to another, in a directed manner. Of these motors, cytoplasmic dynein is structurally more complex than other motor proteins involved in intracellular transport, as it shows force and fuel (ATP) concentration dependent step‐size. Cytoplasmic dynein motors are known to work in a team during cargo transport and force generation. Here, we use a complete Monte‐Carlo model of single dynein constrained by in vitro experiments, which includes the effect of both force and ATP on stepping as well as detachment of motors under force. We then use our complete Monte‐Carlo model of single dynein motor to understand collective cargo transport by a team of dynein motors, such as dependence of cargo travel distance and velocity on applied force and fuel concentration. In our model, cargos pulled by a team of dynein motors do not detach rapidly under higher forces, confirming the experimental observation of longer persistence time of dynein team on microtubule under higher forces. PMID:27727483

Quantifying How Observations Inform a Numerical Reanalysis of Hawaii

NASA Astrophysics Data System (ADS)

Powell, B. S.

2017-11-01

When assimilating observations into a model via state-estimation, it is possible to quantify how each observation changes the modeled estimate of a chosen oceanic metric. Using an existing 2 year reanalysis of Hawaii that includes more than 31 million observations from satellites, ships, SeaGliders, and autonomous floats, I assess which observations most improve the estimates of the transport and eddy kinetic energy. When the SeaGliders were in the water, they comprised less than 2.5% of the data, but accounted for 23% of the transport adjustment. Because the model physics constrains advanced state-estimation, the prescribed covariances are propagated in time to identify observation-model covariance. I find that observations that constrain the isopycnal tilt across the transport section provide the greatest impact in the analysis. In the case of eddy kinetic energy, observations that constrain the surface-driven upper ocean have more impact. This information can help to identify optimal sampling strategies to improve both state-estimates and forecasts.

Constraining dark sector perturbations I: cosmic shear and CMB lensing

NASA Astrophysics Data System (ADS)

Battye, Richard A.; Moss, Adam; Pearson, Jonathan A.

2015-04-01

We present current and future constraints on equations of state for dark sector perturbations. The equations of state considered are those corresponding to a generalized scalar field model and time-diffeomorphism invariant Script L(g) theories that are equivalent to models of a relativistic elastic medium and also Lorentz violating massive gravity. We develop a theoretical understanding of the observable impact of these models. In order to constrain these models we use CMB temperature data from Planck, BAO measurements, CMB lensing data from Planck and the South Pole Telescope, and weak galaxy lensing data from CFHTLenS. We find non-trivial exclusions on the range of parameters, although the data remains compatible with w=-1. We gauge how future experiments will help to constrain the parameters. This is done via a likelihood analysis for CMB experiments such as CoRE and PRISM, and tomographic galaxy weak lensing surveys, focussing in on the potential discriminatory power of Euclid on mildly non-linear scales.

Sequential Probability Ratio Test for Collision Avoidance Maneuver Decisions Based on a Bank of Norm-Inequality-Constrained Epoch-State Filters

NASA Technical Reports Server (NTRS)

Carpenter, J. R.; Markley, F. L.; Alfriend, K. T.; Wright, C.; Arcido, J.

2011-01-01

Sequential probability ratio tests explicitly allow decision makers to incorporate false alarm and missed detection risks, and are potentially less sensitive to modeling errors than a procedure that relies solely on a probability of collision threshold. Recent work on constrained Kalman filtering has suggested an approach to formulating such a test for collision avoidance maneuver decisions: a filter bank with two norm-inequality-constrained epoch-state extended Kalman filters. One filter models 1he null hypothesis 1ha1 the miss distance is inside the combined hard body radius at the predicted time of closest approach, and one filter models the alternative hypothesis. The epoch-state filter developed for this method explicitly accounts for any process noise present in the system. The method appears to work well using a realistic example based on an upcoming highly-elliptical orbit formation flying mission.

Constraint-Based Local Search for Constrained Optimum Paths Problems

NASA Astrophysics Data System (ADS)

Pham, Quang Dung; Deville, Yves; van Hentenryck, Pascal

Constrained Optimum Path (COP) problems arise in many real-life applications and are ubiquitous in communication networks. They have been traditionally approached by dedicated algorithms, which are often hard to extend with side constraints and to apply widely. This paper proposes a constraint-based local search (CBLS) framework for COP applications, bringing the compositionality, reuse, and extensibility at the core of CBLS and CP systems. The modeling contribution is the ability to express compositional models for various COP applications at a high level of abstraction, while cleanly separating the model and the search procedure. The main technical contribution is a connected neighborhood based on rooted spanning trees to find high-quality solutions to COP problems. The framework, implemented in COMET, is applied to Resource Constrained Shortest Path (RCSP) problems (with and without side constraints) and to the edge-disjoint paths problem (EDP). Computational results show the potential significance of the approach.

Synthetic Constraint of Ecosystem C Models Using Radiocarbon and Net Primary Production (NPP) in New Zealand Grazing Land

NASA Astrophysics Data System (ADS)

Baisden, W. T.

2011-12-01

Time-series radiocarbon measurements have substantial ability to constrain the size and residence time of the soil C pools commonly represented in ecosystem models. Radiocarbon remains unique in the ability to constrain the large stabilized C pool with decadal residence times. Radiocarbon also contributes usefully to constraining the size and turnover rate of the passive pool, but typically struggles to constrain pools with residence times less than a few years. Overall, the number of pools and associated turnover rates that can be constrained depends upon the number of time-series samples available, the appropriateness of chemical or physical fractions to isolate unequivocal pools, and the utility of additional C flux data to provide additional constraints. In New Zealand pasture soils, we demonstrate the ability to constrain decadal turnover times with in a few years for the stabilized pool and reasonably constrain the passive fraction. Good constraint is obtained with two time-series samples spaced 10 or more years apart after 1970. Three or more time-series samples further improve the level of constraint. Work within this context shows that a two-pool model does explain soil radiocarbon data for the most detailed profiles available (11 time-series samples), and identifies clear and consistent differences in rates of C turnover and passive fraction in Andisols vs Non-Andisols. Furthermore, samples from multiple horizons can commonly be combined, yielding consistent residence times and passive fraction estimates that are stable with, or increase with, depth in different sites. Radiocarbon generally fails to quantify rapid C turnover, however. Given that the strength of radiocarbon is estimating the size and turnover of the stabilized (decadal) and passive (millennial) pools, the magnitude of fast cycling pool(s) can be estimated by subtracting the radiocarbon-based estimates of turnover within stabilized and passive pools from total estimates of NPP. In grazing land, these estimates can be derived primarily from measured aboveground NPP and calculated belowground NPP. Results suggest that only 19-36% of heterotrophic soil respiration is derived from the soil C with rapid turnover times. A final logical step in synthesis is the analysis of temporal variation in NPP, primarily due to climate, as driver of changes in plant inputs and resulting in dynamic changes in rapid and decadal soil C pools. In sites with good time series samples from 1959-1975, we examine the apparent impacts of measured or modelled (Biome-BGC) NPP on soil Δ14C. Ultimately, these approaches have the ability to empirically constrain, and provide limited verification, of the soil C cycle as commonly depicted ecosystem biogeochemistry models.

Phase-field model of domain structures in ferroelectric thin films

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Y. L.; Hu, S. Y.; Liu, Z. K.

A phase-field model for predicting the coherent microstructure evolution in constrained thin films is developed. It employs an analytical elastic solution derived for a constrained film with arbitrary eigenstrain distributions. The domain structure evolution during a cubic{r_arrow}tetragonal proper ferroelectric phase transition is studied. It is shown that the model is able to simultaneously predict the effects of substrate constraint and temperature on the volume fractions of domain variants, domain-wall orientations, domain shapes, and their temporal evolution. {copyright} 2001 American Institute of Physics.

Effects of growth rate, cell size, motion, and elemental stoichiometry on nutrient transport kinetics

PubMed Central

Skibinski, David O. F.

2018-01-01

Nutrient acquisition is a critical determinant for the competitive advantage for auto- and osmohetero- trophs alike. Nutrient limited growth is commonly described on a whole cell basis through reference to a maximum growth rate (Gmax) and a half-saturation constant (KG). This empirical application of a Michaelis-Menten like description ignores the multiple underlying feedbacks between physiology contributing to growth, cell size, elemental stoichiometry and cell motion. Here we explore these relationships with reference to the kinetics of the nutrient transporter protein, the transporter rate density at the cell surface (TRD; potential transport rate per unit plasma-membrane area), and diffusion gradients. While the half saturation value for the limiting nutrient increases rapidly with cell size, significant mitigation is afforded by cell motion (swimming or sedimentation), and by decreasing the cellular carbon density. There is thus potential for high vacuolation and high sedimentation rates in diatoms to significantly decrease KG and increase species competitive advantage. Our results also suggest that Gmax for larger non-diatom protists may be constrained by rates of nutrient transport. For a given carbon density, cell size and TRD, the value of Gmax/KG remains constant. This implies that species or strains with a lower Gmax might coincidentally have a competitive advantage under nutrient limited conditions as they also express lower values of KG. The ability of cells to modulate the TRD according to their nutritional status, and hence change the instantaneous maximum transport rate, has a very marked effect upon transport and growth kinetics. Analyses and dynamic models that do not consider such modulation will inevitably fail to properly reflect competitive advantage in nutrient acquisition. This has important implications for the accurate representation and predictive capabilities of model applications, in particular in a changing environment. PMID:29702650

Flexible Energy Scheduling Tool for Integrating Variable Generation | Grid

Science.gov Websites

, security-constrained economic dispatch, and automatic generation control programs. DOWNLOAD PAPER Electric commitment, security-constrained economic dispatch, and automatic generation control sub-models. Each sub resolutions and operating strategies can be explored. FESTIV produces not only economic metrics but also

Thin film module electrical configuration versus electrical performance

NASA Technical Reports Server (NTRS)

Morel, D. L.

1985-01-01

The as made and degraded states of thin film silicon (TFS) based modules have been modelled in terms of series resistance losses. The origins of these losses lie in interface and bulk regions of the devices. When modules degrade under light exposure, increases occur in both the interface and bulk components of the loss based on series resistance. Actual module performance can thus be simulated by use of only one unknown parameter, shunt losses. Use of the simulation to optimize module design indicates that the current design of 25 cells per linear foot is near optimum. Degradation performance suggests a shift to approx. 35 cells to effect maximum output for applications not constrained to 12 volts. Earlier studies of energy based performance and tandem structures should be updated to include stability factors, not only the initial loss factor tested here, but also appropriate annealing factors.

Epoch of reionization 21 cm forecasting from MCMC-constrained semi-numerical models

NASA Astrophysics Data System (ADS)

Hassan, Sultan; Davé, Romeel; Finlator, Kristian; Santos, Mario G.

2017-06-01

The recent low value of Planck Collaboration XLVII integrated optical depth to Thomson scattering suggests that the reionization occurred fairly suddenly, disfavouring extended reionization scenarios. This will have a significant impact on the 21 cm power spectrum. Using a semi-numerical framework, we improve our model from instantaneous to include time-integrated ionization and recombination effects, and find that this leads to more sudden reionization. It also yields larger H II bubbles that lead to an order of magnitude more 21 cm power on large scales, while suppressing the small-scale ionization power. Local fluctuations in the neutral hydrogen density play the dominant role in boosting the 21 cm power spectrum on large scales, while recombinations are subdominant. We use a Monte Carlo Markov chain approach to constrain our model to observations of the star formation rate functions at z = 6, 7, 8 from Bouwens et al., the Planck Collaboration XLVII optical depth measurements and the Becker & Bolton ionizing emissivity data at z ˜ 5. We then use this constrained model to perform 21 cm forecasting for Low Frequency Array, Hydrogen Epoch of Reionization Array and Square Kilometre Array in order to determine how well such data can characterize the sources driving reionization. We find that the Mock 21 cm power spectrum alone can somewhat constrain the halo mass dependence of ionizing sources, the photon escape fraction and ionizing amplitude, but combining the Mock 21 cm data with other current observations enables us to separately constrain all these parameters. Our framework illustrates how the future 21 cm data can play a key role in understanding the sources and topology of reionization as observations improve.

How Cells Can Control Their Size by Pumping Ions.

PubMed

Kay, Alan R

2017-01-01

The ability of all cells to set and regulate their size is a fundamental aspect of cellular physiology. It has been known for sometime but not widely so, that size stability in animal cells is dependent upon the operation of the sodium pump, through the so-called pump-leak mechanism (Tosteson and Hoffman, 1960). Impermeant molecules in cells establish an unstable osmotic condition, the Donnan effect, which is counteracted by the operation of the sodium pump, creating an asymmetry in the distribution of Na + and K + staving off water inundation. In this paper, which is in part a tutorial, I show how to model quantitatively the ion and water fluxes in a cell that determine the cell volume and membrane potential. The movement of water and ions is constrained by both osmotic and charge balance, and is driven by ion and voltage gradients and active ion transport. Transforming these constraints and forces into a set of coupled differential equations allows us to model how the ion distributions, volume and voltage change with time. I introduce an analytical solution to these equations that clarifies the influence of ion conductances, pump rates and water permeability in this multidimensional system. I show that the number of impermeant ions ( x ) and their average charge have a powerful influence on the distribution of ions and voltage in a cell. Moreover, I demonstrate that in a cell where the operation of active ion transport eliminates an osmotic gradient, the size of the cell is directly proportional to x . In addition, I use graphics to reveal how the physico-chemical constraints and chemical forces interact with one another in apportioning ions inside the cell. The form of model used here is applicable to all membrane systems, including mitochondria and bacteria, and I show how pumps other than the sodium pump can be used to stabilize cells. Cell biologists may think of electrophysiology as the exclusive domain of neuroscience, however the electrical effects of ion fluxes need to become an intimate part of cell biology if we are to understand a fundamental process like cell size regulation.

Bayesian inversion of marine CSEM data from the Scarborough gas field using a transdimensional 2-D parametrization

NASA Astrophysics Data System (ADS)

Ray, Anandaroop; Key, Kerry; Bodin, Thomas; Myer, David; Constable, Steven

2014-12-01

We apply a reversible-jump Markov chain Monte Carlo method to sample the Bayesian posterior model probability density function of 2-D seafloor resistivity as constrained by marine controlled source electromagnetic data. This density function of earth models conveys information on which parts of the model space are illuminated by the data. Whereas conventional gradient-based inversion approaches require subjective regularization choices to stabilize this highly non-linear and non-unique inverse problem and provide only a single solution with no model uncertainty information, the method we use entirely avoids model regularization. The result of our approach is an ensemble of models that can be visualized and queried to provide meaningful information about the sensitivity of the data to the subsurface, and the level of resolution of model parameters. We represent models in 2-D using a Voronoi cell parametrization. To make the 2-D problem practical, we use a source-receiver common midpoint approximation with 1-D forward modelling. Our algorithm is transdimensional and self-parametrizing where the number of resistivity cells within a 2-D depth section is variable, as are their positions and geometries. Two synthetic studies demonstrate the algorithm's use in the appraisal of a thin, segmented, resistive reservoir which makes for a challenging exploration target. As a demonstration example, we apply our method to survey data collected over the Scarborough gas field on the Northwest Australian shelf.

Moist Baroclinic Life Cycles in an Idealized Model with Varying Hydrostasy

NASA Astrophysics Data System (ADS)

Hsieh, T. L.; Garner, S.; Held, I.

2016-12-01

Baroclinic life cycles are simulated in a limited-area model having varying degrees of hydrostasy to examine their interaction with explicitly resolved moist convection. The life cycles are driven by an idealized sea surface temperature field in an f-plane channel, and no convective parameterization is used. The hydrostasy is controlled by rescaling the model equations following the hypohydrostatic rescaling and by changing the resolution. In experiments having the same ratio between the grid spacing and the rescaling factor, the simulated convection is shown to have the same hydrostasy, suggesting that the low resolution models have been rescaled to be as nonhydrostatic as the high resolution model without additional computational cost. The nonhydrostatic convective cells in the rescaled models are found to be wider and slower than those in the unscaled models, consistent with predictions of the similarity theory. For the same resolution, although the wider cells in the rescaled models have better resolved structure, the total latent heating is insensitive to the rescaling factor. This is because latent heating is constrained by long-wave cooling which is found to be insensitive to the model hydrostasy, requiring a non-similarity in the frequency and distribution of convection. Consequently, the resolved nonhydrostatic convection maintains the same stability profile as the unresolved hydrostatic convection, so the statistics of the life cycles are also insensitive to the rescaling factor. The findings suggest that the mean climate and internal variability would be unaffected by the hypohydrostatic rescaling when the self-organization of convection is not important.

Rgs13 constrains early B cell responses and limits germinal center sizes.

PubMed

Hwang, Il-Young; Hwang, Kyung-Sun; Park, Chung; Harrison, Kathleen A; Kehrl, John H

2013-01-01

Germinal centers (GCs) are microanatomic structures that develop in secondary lymphoid organs in response to antigenic stimulation. Within GCs B cells clonally expand and their immunoglobulin genes undergo class switch recombination and somatic hypermutation. Transcriptional profiling has identified a number of genes that are prominently expressed in GC B cells. Among them is Rgs13, which encodes an RGS protein with a dual function. Its canonical function is to accelerate the intrinsic GTPase activity of heterotrimeric G-protein α subunits at the plasma membrane, thereby limiting heterotrimeric G-protein signaling. A unique, non-canonical function of RGS13 occurs following translocation to the nucleus, where it represses CREB transcriptional activity. The functional role of RGS13 in GC B cells is unknown. To create a surrogate marker for Rgs13 expression and a loss of function mutation, we inserted a GFP coding region into the Rgs13 genomic locus. Following immunization GFP expression rapidly increased in activated B cells, persisted in GC B cells, but declined in newly generated memory B and plasma cells. Intravital microscopy of the inguinal lymph node (LN) of immunized mice revealed the rapid appearance of GFP(+) cells at LN interfollicular regions and along the T/B cell borders, and eventually within GCs. Analysis of WT, knock-in, and mixed chimeric mice indicated that RGS13 constrains extra-follicular plasma cell generation, GC size, and GC B cell numbers. Analysis of select cell cycle and GC specific genes disclosed an aberrant gene expression profile in the Rgs13 deficient GC B cells. These results indicate that RGS13, likely acting at cell membranes and in nuclei, helps coordinate key decision points during the expansion and differentiation of naive B cells.

Distribution of a Glycosylphosphatidylinositol-anchored Protein at the Apical Surface of MDCK Cells Examined at a Resolution of <100 Å Using Imaging Fluorescence Resonance Energy Transfer

PubMed Central

Kenworthy, A.K.; Edidin, M.

1998-01-01

Membrane microdomains (“lipid rafts”) enriched in glycosylphosphatidylinositol (GPI)-anchored proteins, glycosphingolipids, and cholesterol have been implicated in events ranging from membrane trafficking to signal transduction. Although there is biochemical evidence for such membrane microdomains, they have not been visualized by light or electron microscopy. To probe for microdomains enriched in GPI- anchored proteins in intact cell membranes, we used a novel form of digital microscopy, imaging fluorescence resonance energy transfer (FRET), which extends the resolution of fluorescence microscopy to the molecular level (<100 Å). We detected significant energy transfer between donor- and acceptor-labeled antibodies against the GPI-anchored protein 5′ nucleotidase (5′ NT) at the apical membrane of MDCK cells. The efficiency of energy transfer correlated strongly with the surface density of the acceptor-labeled antibody. The FRET data conformed to theoretical predictions for two-dimensional FRET between randomly distributed molecules and were inconsistent with a model in which 5′ NT is constitutively clustered. Though we cannot completely exclude the possibility that some 5′ NT is in clusters, the data imply that most 5′ NT molecules are randomly distributed across the apical surface of MDCK cells. These findings constrain current models for lipid rafts and the membrane organization of GPI-anchored proteins. PMID:9660864

Dynamic Parameters of the 2015 Nepal Gorkha Mw7.8 Earthquake Constrained by Multi-observations

NASA Astrophysics Data System (ADS)

Weng, H.; Yang, H.

2017-12-01

Dynamic rupture model can provide much detailed insights into rupture physics that is capable of assessing future seismic risk. Many studies have attempted to constrain the slip-weakening distance, an important parameter controlling friction behavior of rock, for several earthquakes based on dynamic models, kinematic models, and direct estimations from near-field ground motion. However, large uncertainties of the values of the slip-weakening distance still remain, mostly because of the intrinsic trade-offs between the slip-weakening distance and fault strength. Here we use a spontaneously dynamic rupture model to constrain the frictional parameters of the 25 April 2015 Mw7.8 Nepal earthquake, by combining with multiple seismic observations such as high-rate cGPS data, strong motion data, and kinematic source models. With numerous tests we find the trade-off patterns of final slip, rupture speed, static GPS ground displacements, and dynamic ground waveforms are quite different. Combining all the seismic constraints we can conclude a robust solution without a substantial trade-off of average slip-weakening distance, 0.6 m, in contrast to previous kinematical estimation of 5 m. To our best knowledge, this is the first time to robustly determine the slip-weakening distance on seismogenic fault from seismic observations. The well-constrained frictional parameters may be used for future dynamic models to assess seismic hazard, such as estimating the peak ground acceleration (PGA) etc. Similar approach could also be conducted for other great earthquakes, enabling broad estimations of the dynamic parameters in global perspectives that can better reveal the intrinsic physics of earthquakes.

MHC class II molecules control murine B cell responsiveness to lipopolysaccharide stimulation.

PubMed

Rodo, Joana; Gonçalves, Lígia A; Demengeot, Jocelyne; Coutinho, António; Penha-Gonçalves, Carlos

2006-10-01

LPS is a strong stimulator of the innate immune system and inducer of B lymphocyte activation. Two TLRs, TLR4 and RP105 (CD180), have been identified as mediators of LPS signaling in murine B cells, but little is known about genetic factors that are able to control LPS-induced cell activation. We performed a mouse genome-wide screen that aside from identifying a controlling locus mapping in the TLR4 region (logarithm of odds score, 2.77), also revealed that a locus closely linked to the MHC region (logarithm of odds score, 3.4) governed B cell responsiveness to LPS stimulation. Using purified B cells obtained from MHC congenic strains, we demonstrated that the MHC(b) haplotype is accountable for higher cell activation, cell proliferation, and IgM secretion, after LPS stimulation, when compared with the MHC(d) haplotype. Furthermore, B cells from MHC class II(-/-) mice displayed enhanced activation and proliferation in response to LPS. In addition, we showed that the MHC haplotype partially controls expression of RP105 (a LPS receptor molecule), following a pattern that resembles the LPS responsiveness phenotype. Together, our results strongly suggest that murine MHC class II molecules play a role in constraining the B cell response to LPS and that genetic variation at the MHC locus is an important component in controlling B cell responsiveness to LPS stimulation. This work raises the possibility that constraining of B cell responsiveness by MHC class II molecules may represent a functional interaction between adaptive and innate immune systems.

JuPOETs: a constrained multiobjective optimization approach to estimate biochemical model ensembles in the Julia programming language.

PubMed

Bassen, David M; Vilkhovoy, Michael; Minot, Mason; Butcher, Jonathan T; Varner, Jeffrey D

2017-01-25

Ensemble modeling is a promising approach for obtaining robust predictions and coarse grained population behavior in deterministic mathematical models. Ensemble approaches address model uncertainty by using parameter or model families instead of single best-fit parameters or fixed model structures. Parameter ensembles can be selected based upon simulation error, along with other criteria such as diversity or steady-state performance. Simulations using parameter ensembles can estimate confidence intervals on model variables, and robustly constrain model predictions, despite having many poorly constrained parameters. In this software note, we present a multiobjective based technique to estimate parameter or models ensembles, the Pareto Optimal Ensemble Technique in the Julia programming language (JuPOETs). JuPOETs integrates simulated annealing with Pareto optimality to estimate ensembles on or near the optimal tradeoff surface between competing training objectives. We demonstrate JuPOETs on a suite of multiobjective problems, including test functions with parameter bounds and system constraints as well as for the identification of a proof-of-concept biochemical model with four conflicting training objectives. JuPOETs identified optimal or near optimal solutions approximately six-fold faster than a corresponding implementation in Octave for the suite of test functions. For the proof-of-concept biochemical model, JuPOETs produced an ensemble of parameters that gave both the mean of the training data for conflicting data sets, while simultaneously estimating parameter sets that performed well on each of the individual objective functions. JuPOETs is a promising approach for the estimation of parameter and model ensembles using multiobjective optimization. JuPOETs can be adapted to solve many problem types, including mixed binary and continuous variable types, bilevel optimization problems and constrained problems without altering the base algorithm. JuPOETs is open source, available under an MIT license, and can be installed using the Julia package manager from the JuPOETs GitHub repository.

Application of a roughness-length representation to parameterize energy loss in 3-D numerical simulations of large rivers

NASA Astrophysics Data System (ADS)

Sandbach, S. D.; Lane, S. N.; Hardy, R. J.; Amsler, M. L.; Ashworth, P. J.; Best, J. L.; Nicholas, A. P.; Orfeo, O.; Parsons, D. R.; Reesink, A. J. H.; Szupiany, R. N.

2012-12-01

Recent technological advances in remote sensing have enabled investigation of the morphodynamics and hydrodynamics of large rivers. However, measuring topography and flow in these very large rivers is time consuming and thus often constrains the spatial resolution and reach-length scales that can be monitored. Similar constraints exist for computational fluid dynamics (CFD) studies of large rivers, requiring maximization of mesh- or grid-cell dimensions and implying a reduction in the representation of bedform-roughness elements that are of the order of a model grid cell or less, even if they are represented in available topographic data. These "subgrid" elements must be parameterized, and this paper applies and considers the impact of roughness-length treatments that include the effect of bed roughness due to "unmeasured" topography. CFD predictions were found to be sensitive to the roughness-length specification. Model optimization was based on acoustic Doppler current profiler measurements and estimates of the water surface slope for a variety of roughness lengths. This proved difficult as the metrics used to assess optimal model performance diverged due to the effects of large bedforms that are not well parameterized in roughness-length treatments. However, the general spatial flow patterns are effectively predicted by the model. Changes in roughness length were shown to have a major impact upon flow routing at the channel scale. The results also indicate an absence of secondary flow circulation cells in the reached studied, and suggest simpler two-dimensional models may have great utility in the investigation of flow within large rivers.

Characterization of the High-Albedo NEA 3691 Bede

NASA Technical Reports Server (NTRS)

Wooden, Diane H.; Lederer, Susan M.; Jehin, Emmanuel; Rozitis, Benjamin; Jefferson, Jeffrey D.; Nelson, Tyler W.; Dotson, Jessie L.; Ryan, Erin L.; Howell, Ellen S.; Fernandez, Yanga R.;

Characterization of the high-albedo NEA 3691 Bede

NASA Astrophysics Data System (ADS)

Wooden, Diane H.; Lederer, Susan M.; Jehin, Emmanuel; Rozitis, Benjamin; Jefferson, Jeffrey D.; Nelson, Tyler W.; Dotson, Jessie L.; Ryan, Erin L.; Howell, Ellen S.; Fernandez, Yanga R.; Lovell, Amy J.; Woodward, Charles E.; Harker, David Emerson

2016-10-01

Characterization of NEAs provides important inputs to models for atmospheric entry, risk assessment and mitigation. Diameter is a key parameter because diameter translates to kinetic energy in atmospheric entry. Diameters can be derived from the absolute magnitude, H(PA=0deg), and from thermal modeling of observed IR fluxes. For both methods, the albedo (pv) is important - high pv surfaces have cooler temperatures, larger diameters for a given Hmag, and shallower phase curves (larger slope parameter G). Thermal model parameters are coupled, however, so that a higher thermal inertia also results in a cooler surface temperature. Multiple parameters contribute to constraining the diameter.Observations made at multiple observing geometries can contribute to understanding the relationships between and potentially breaking some of the degeneracies between parameters. We present data and analyses on NEA 3691 Bede with the aim of best constraining the diameter and pv from a combination of thermal modeling and light curve analyses. We employ our UKIRT+Michelle mid-IR photometric observations of 3691 Bede's thermal emission at 2 phase angles (27&43 deg 2015-03-19 & 04-13), in addition to WISE data (33deg 2010-05-27, Mainzer+2011).Observing geometries differ by solar phase angles and by moderate changes in heliocentric distance (e.g., further distances produce somewhat cooler surface temperatures). With the NEATM model and for a constant IR beaming parameter (eta=constant), there is a family of solutions for (diameter, pv, G, eta) where G is the slope parameter from the H-G Relation. NEATM models employing Pravec+2012's choice of G=0.43, produce D=1.8 km and pv≈0.4, given that G=0.43 is assumed from studies of main belt asteroids (Warner+2009). We present an analysis of the light curve of 3691 Bede to constrain G from observations. We also investigate fitting thermophysical models (TPM, Rozitis+11) to constrain the coupled parameters of thermal inertia (Gamma) and surface roughness, which in turn affect diameter and pv. Surface composition can be related to pv. This study focuses on understanding and characterizing the dependency of parameters with the aim of constraining diameter, pv and thermal inertia for 3691 Bede.

Neurolinguistically constrained simulation of sentence comprehension: integrating artificial intelligence and brain theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gigley, H.M.

1982-01-01

An artificial intelligence approach to the simulation of neurolinguistically constrained processes in sentence comprehension is developed using control strategies for simulation of cooperative computation in associative networks. The desirability of this control strategy in contrast to ATN and production system strategies is explained. A first pass implementation of HOPE, an artificial intelligence simulation model of sentence comprehension, constrained by studies of aphasic performance, psycholinguistics, neurolinguistics, and linguistic theory is described. Claims that the model could serve as a basis for sentence production simulation and for a model of language acquisition as associative learning are discussed. HOPE is a model thatmore » performs in a normal state and includes a lesion simulation facility. HOPE is also a research tool. Its modifiability and use as a tool to investigate hypothesized causes of degradation in comprehension performance by aphasic patients are described. Issues of using behavioral constraints in modelling and obtaining appropriate data for simulated process modelling are discussed. Finally, problems of validation of the simulation results are raised; and issues of how to interpret clinical results to define the evolution of the model are discussed. Conclusions with respect to the feasibility of artificial intelligence simulation process modelling are discussed based on the current state of research.« less

Constraining magma physical properties and its temporal evolution from InSAR and topographic data only: a physics-based eruption model for the effusive phase of the Cordon Caulle 2011-2012 rhyodacitic eruption

NASA Astrophysics Data System (ADS)

Delgado, F.; Kubanek, J.; Anderson, K. R.; Lundgren, P.; Pritchard, M. E.

2017-12-01

The 2011-2012 eruption of Cordón Caulle volcano in Chile is the best scientifically observed rhyodacitic eruption and is thus a key place to understand the dynamics of these rare but powerful explosive rhyodacitic eruptions. Because the volatile phase controls both the eruption temporal evolution and the eruptive style, either explosive or effusive, it is important to constrain the physical parameters that drive these eruptions. The eruption began explosively and after two weeks evolved into a hybrid explosive - lava flow effusion whose volume-time evolution we constrain with a series of TanDEM-X Digital Elevation Models. Our data shows the intrusion of a large volume laccolith or cryptodome during the first 2.5 months of the eruption and lava flow effusion only afterwards, with a total volume of 1.4 km3. InSAR data from the ENVISAT and TerraSAR-X missions shows more than 2 m of subsidence during the effusive eruption phase produced by deflation of a finite spheroidal source at a depth of 5 km. In order to constrain the magma total H2O content, crystal cargo, and reservoir pressure drop we numerically solve the coupled set of equations of a pressurized magma reservoir, magma conduit flow and time dependent density, volatile exsolution and viscosity that we use to invert the InSAR and topographic data time series. We compare the best-fit model parameters with independent estimates of magma viscosity and total gas content measured from lava samples. Preliminary modeling shows that although it is not possible to model both the InSAR and the topographic data during the onset of the laccolith emplacement, it is possible to constrain the magma H2O and crystal content, to 4% wt and 30% which agree well with published literature values.

Measurement of 240Pu Angular Momentum Dependent Fission Probabilities Using the (α ,α') Reaction

NASA Astrophysics Data System (ADS)

Koglin, Johnathon; Burke, Jason; Fisher, Scott; Jovanovic, Igor

2017-09-01

The surrogate reaction method often lacks the theoretical framework and necessary experimental data to constrain models especially when rectifying differences between angular momentum state differences between the desired and surrogate reaction. In this work, dual arrays of silicon telescope particle identification detectors and photovoltaic (solar) cell fission fragment detectors have been used to measure the fission probability of the 240Pu(α ,α' f) reaction - a surrogate for the 239Pu(n , f) - and fission fragment angular distributions. Fission probability measurements were performed at a beam energy of 35.9(2) MeV at eleven scattering angles from 40° to 140°e in 10° intervals and at nuclear excitation energies up to 16 MeV. Fission fragment angular distributions were measured in six bins from 4.5 MeV to 8.0 MeV and fit to expected distributions dependent on the vibrational and rotational excitations at the saddle point. In this way, the contributions to the total fission probability from specific states of K angular momentum projection on the symmetry axis are extracted. A sizable data collection is presented to be considered when constraining microscopic cross section calculations.

Multidisciplinary Optimization Approach for Design and Operation of Constrained and Complex-shaped Space Systems

NASA Astrophysics Data System (ADS)

Lee, Dae Young

The design of a small satellite is challenging since they are constrained by mass, volume, and power. To mitigate these constraint effects, designers adopt deployable configurations on the spacecraft that result in an interesting and difficult optimization problem. The resulting optimization problem is challenging due to the computational complexity caused by the large number of design variables and the model complexity created by the deployables. Adding to these complexities, there is a lack of integration of the design optimization systems into operational optimization, and the utility maximization of spacecraft in orbit. The developed methodology enables satellite Multidisciplinary Design Optimization (MDO) that is extendable to on-orbit operation. Optimization of on-orbit operations is possible with MDO since the model predictive controller developed in this dissertation guarantees the achievement of the on-ground design behavior in orbit. To enable the design optimization of highly constrained and complex-shaped space systems, the spherical coordinate analysis technique, called the "Attitude Sphere", is extended and merged with an additional engineering tools like OpenGL. OpenGL's graphic acceleration facilitates the accurate estimation of the shadow-degraded photovoltaic cell area. This technique is applied to the design optimization of the satellite Electric Power System (EPS) and the design result shows that the amount of photovoltaic power generation can be increased more than 9%. Based on this initial methodology, the goal of this effort is extended from Single Discipline Optimization to Multidisciplinary Optimization, which includes the design and also operation of the EPS, Attitude Determination and Control System (ADCS), and communication system. The geometry optimization satisfies the conditions of the ground development phase; however, the operation optimization may not be as successful as expected in orbit due to disturbances. To address this issue, for the ADCS operations, controllers based on Model Predictive Control that are effective for constraint handling were developed and implemented. All the suggested design and operation methodologies are applied to a mission "CADRE", which is space weather mission scheduled for operation in 2016. This application demonstrates the usefulness and capability of the methodology to enhance CADRE's capabilities, and its ability to be applied to a variety of missions.

Neutrophils establish rapid and robust WAVE complex polarity in an actin-dependent fashion.

PubMed

Millius, Arthur; Dandekar, Sheel N; Houk, Andrew R; Weiner, Orion D

2009-02-10

Asymmetric intracellular signals enable cells to migrate in response to external cues. The multiprotein WAVE (also known as SCAR or WASF) complex activates the actin-nucleating Arp2/3 complex [1-4] and localizes to propagating "waves," which direct actin assembly during neutrophil migration [5, 6]. Here, we observe similar WAVE complex dynamics in other mammalian cells and analyze WAVE complex dynamics during establishment of neutrophil polarity. Earlier models proposed that spatially biased generation [7] or selection of protrusions [8] enables chemotaxis. These models require existing morphological polarity to control protrusions. We show that spatially biased generation and selection of WAVE complex recruitment also occur in morphologically unpolarized neutrophils during development of their first protrusions. Additionally, several mechanisms limit WAVE complex recruitment during polarization and movement: Intrinsic cues restrict WAVE complex distribution during establishment of polarity, and asymmetric intracellular signals constrain it in morphologically polarized cells. External gradients can overcome both intrinsic biases and control WAVE complex localization. After latrunculin-mediated inhibition of actin polymerization, addition and removal of agonist gradients globally recruits and releases the WAVE complex from the membrane. Under these conditions, the WAVE complex no longer polarizes, despite the presence of strong external gradients. Thus, actin polymer and the WAVE complex reciprocally interact during polarization.

Modeling of Cr(VI) Bioreduction Under Fermentative and Denitrifying Conditions

NASA Astrophysics Data System (ADS)

Molins, S.; Steefel, C.; Yang, L.; Beller, H. R.

2011-12-01

The mechanisms of bioreductive immobilization of Cr(VI) were investigated by reactive transport modeling of a set of flow-through column experiments performed using natural Hanford 100H aquifer sediment. The columns were continuously eluted with 5 μM Cr(VI), 5 mM lactate as the electron donor, and selected electron acceptors (tested individually). Here we focus on the two separate experimental conditions that showed the most removal of Cr(VI) from solution: fermentation and denitrification. In each case, a network of enzymatic and abiotic reaction pathways was considered to interpret the rate of chromate reduction. The model included biomass growth and decay, and thermodynamic limitations on reaction rates, and was constrained by effluent concentrations measured by IC and ICP-MS and additional information from bacterial isolates from column effluent. Under denitrifying conditions, Cr(VI) reduction was modeled as co-metabolic with nitrate reduction based on experimental observations and previous studies on a denitrifying bacterium derived from the Hanford 100H aquifer. The reactive transport model results supported this interpretation of the reaction mechanism and were used to quantify the efficiency of the process. The models results also suggest that biomass growth likely relied on a nitrogen source other than ammonium (e.g. nitrate). Under fermentative conditions and based on cell suspension studies performed on a bacterial isolate from the columns, the model assumes that Cr(VI) reduction is carried out directly by fermentative bacteria that convert lactate into acetate and propionate. The evolution to complete lactate fermentation and Cr(VI) reduction took place over a week's time and simulations were used to determine an estimate for a lower limit of the rate of chromate reduction by calibration with the flow-through column experimental results. In spite of sulfate being added to these columns, sulfate reduction proceeded at a slow rate and was not well constrained.

Constrained Versions of DEDICOM for Use in Unsupervised Part-Of-Speech Tagging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dunlavy, Daniel; Chew, Peter A.

This reports describes extensions of DEDICOM (DEcomposition into DIrectional COMponents) data models [3] that incorporate bound and linear constraints. The main purpose of these extensions is to investigate the use of improved data models for unsupervised part-of-speech tagging, as described by Chew et al. [2]. In that work, a single domain, two-way DEDICOM model was computed on a matrix of bigram fre- quencies of tokens in a corpus and used to identify parts-of-speech as an unsupervised approach to that problem. An open problem identi ed in that work was the com- putation of a DEDICOM model that more closely resembledmore » the matrices used in a Hidden Markov Model (HMM), speci cally through post-processing of the DEDICOM factor matrices. The work reported here consists of the description of several models that aim to provide a direct solution to that problem and a way to t those models. The approach taken here is to incorporate the model requirements as bound and lin- ear constrains into the DEDICOM model directly and solve the data tting problem as a constrained optimization problem. This is in contrast to the typical approaches in the literature, where the DEDICOM model is t using unconstrained optimization approaches, and model requirements are satis ed as a post-processing step.« less

Hydrologic consistency as a basis for assessing complexity of monthly water balance models for the continental United States

NASA Astrophysics Data System (ADS)

Martinez, Guillermo F.; Gupta, Hoshin V.

2011-12-01

Methods to select parsimonious and hydrologically consistent model structures are useful for evaluating dominance of hydrologic processes and representativeness of data. While information criteria (appropriately constrained to obey underlying statistical assumptions) can provide a basis for evaluating appropriate model complexity, it is not sufficient to rely upon the principle of maximum likelihood (ML) alone. We suggest that one must also call upon a "principle of hydrologic consistency," meaning that selected ML structures and parameter estimates must be constrained (as well as possible) to reproduce desired hydrological characteristics of the processes under investigation. This argument is demonstrated in the context of evaluating the suitability of candidate model structures for lumped water balance modeling across the continental United States, using data from 307 snow-free catchments. The models are constrained to satisfy several tests of hydrologic consistency, a flow space transformation is used to ensure better consistency with underlying statistical assumptions, and information criteria are used to evaluate model complexity relative to the data. The results clearly demonstrate that the principle of consistency provides a sensible basis for guiding selection of model structures and indicate strong spatial persistence of certain model structures across the continental United States. Further work to untangle reasons for model structure predominance can help to relate conceptual model structures to physical characteristics of the catchments, facilitating the task of prediction in ungaged basins.

On the nullspace of TLS multi-station adjustment

NASA Astrophysics Data System (ADS)

Sterle, Oskar; Kogoj, Dušan; Stopar, Bojan; Kregar, Klemen

2018-07-01

In the article we present an analytic aspect of TLS multi-station least-squares adjustment with the main focus on the datum problem. The datum problem is, compared to previously published researches, theoretically analyzed and solved, where the solution is based on nullspace derivation of the mathematical model. The importance of datum problem solution is seen in a complete description of TLS multi-station adjustment solutions from a set of all minimally constrained least-squares solutions. On a basis of known nullspace, estimable parameters are described and the geometric interpretation of all minimally constrained least squares solutions is presented. At the end a simulated example is used to analyze the results of TLS multi-station minimally constrained and inner constrained least-squares adjustment solutions.

Preclinical modeling highlights the therapeutic potential of hematopoietic stem cell gene editing for correction of SCID-X1.

PubMed

Schiroli, Giulia; Ferrari, Samuele; Conway, Anthony; Jacob, Aurelien; Capo, Valentina; Albano, Luisa; Plati, Tiziana; Castiello, Maria C; Sanvito, Francesca; Gennery, Andrew R; Bovolenta, Chiara; Palchaudhuri, Rahul; Scadden, David T; Holmes, Michael C; Villa, Anna; Sitia, Giovanni; Lombardo, Angelo; Genovese, Pietro; Naldini, Luigi

2017-10-11

Targeted genome editing in hematopoietic stem/progenitor cells (HSPCs) is an attractive strategy for treating immunohematological diseases. However, the limited efficiency of homology-directed editing in primitive HSPCs constrains the yield of corrected cells and might affect the feasibility and safety of clinical translation. These concerns need to be addressed in stringent preclinical models and overcome by developing more efficient editing methods. We generated a humanized X-linked severe combined immunodeficiency (SCID-X1) mouse model and evaluated the efficacy and safety of hematopoietic reconstitution from limited input of functional HSPCs, establishing thresholds for full correction upon different types of conditioning. Unexpectedly, conditioning before HSPC infusion was required to protect the mice from lymphoma developing when transplanting small numbers of progenitors. We then designed a one-size-fits-all IL2RG (interleukin-2 receptor common γ-chain) gene correction strategy and, using the same reagents suitable for correction of human HSPC, validated the edited human gene in the disease model in vivo, providing evidence of targeted gene editing in mouse HSPCs and demonstrating the functionality of the IL2RG -edited lymphoid progeny. Finally, we optimized editing reagents and protocol for human HSPCs and attained the threshold of IL2RG editing in long-term repopulating cells predicted to safely rescue the disease, using clinically relevant HSPC sources and highly specific zinc finger nucleases or CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein 9). Overall, our work establishes the rationale and guiding principles for clinical translation of SCID-X1 gene editing and provides a framework for developing gene correction for other diseases. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Constrained diffusion or immobile fraction on cell surfaces: a new interpretation.

PubMed Central

Feder, T J; Brust-Mascher, I; Slattery, J P; Baird, B; Webb, W W

1996-01-01

Protein lateral mobility in cell membranes is generally measured using fluorescence photobleaching recovery (FPR). Since the development of this technique, the data have been interpreted by assuming free Brownian diffusion of cell surface receptors in two dimensions, an interpretation that requires that a subset of the diffusing species remains immobile. The origin of this so-called immobile fraction remains a mystery. In FPR, the motions of thousands of particles are inherently averaged, inevitably masking the details of individual motions. Recently, tracking of individual cell surface receptors has identified several distinct types of motion (Gross and Webb, 1988; Ghosh and Webb, 1988, 1990, 1994; Kusumi et al. 1993; Qian et al. 1991; Slattery, 1995), thereby calling into question the classical interpretation of FPR data as free Brownian motion of a limited mobile fraction. We have measured the motion of fluorescently labeled immunoglobulin E complexed to high affinity receptors (Fc epsilon RI) on rat basophilic leukemia cells using both single particle tracking and FPR. As in previous studies, our tracking results show that individual receptors may diffuse freely, or may exhibit restricted, time-dependent (anomalous) diffusion. Accordingly, we have analyzed FPR data by a new model to take this varied motion into account, and we show that the immobile fraction may be due to particles moving with the anomalous subdiffusion associated with restricted lateral mobility. Anomalous subdiffusion denotes random molecular motion in which the mean square displacements grow as a power law in time with a fractional positive exponent less than one. These findings call for a new model of cell membrane structure. PMID:8744314

Dynamical computation of constrained flexible systems using a modal Udwadia-Kalaba formulation: Application to musical instruments.

PubMed

Antunes, J; Debut, V

2017-02-01

Most musical instruments consist of dynamical subsystems connected at a number of constraining points through which energy flows. For physical sound synthesis, one important difficulty deals with enforcing these coupling constraints. While standard techniques include the use of Lagrange multipliers or penalty methods, in this paper, a different approach is explored, the Udwadia-Kalaba (U-K) formulation, which is rooted on analytical dynamics but avoids the use of Lagrange multipliers. This general and elegant formulation has been nearly exclusively used for conceptual systems of discrete masses or articulated rigid bodies, namely, in robotics. However its natural extension to deal with continuous flexible systems is surprisingly absent from the literature. Here, such a modeling strategy is developed and the potential of combining the U-K equation for constrained systems with the modal description is shown, in particular, to simulate musical instruments. Objectives are twofold: (1) Develop the U-K equation for constrained flexible systems with subsystems modelled through unconstrained modes; and (2) apply this framework to compute string/body coupled dynamics. This example complements previous work [Debut, Antunes, Marques, and Carvalho, Appl. Acoust. 108, 3-18 (2016)] on guitar modeling using penalty methods. Simulations show that the proposed technique provides similar results with a significant improvement in computational efficiency.

Context- and Template-Based Compression for Efficient Management of Data Models in Resource-Constrained Systems.

PubMed

Macho, Jorge Berzosa; Montón, Luis Gardeazabal; Rodriguez, Roberto Cortiñas

2017-08-01

The Cyber Physical Systems (CPS) paradigm is based on the deployment of interconnected heterogeneous devices and systems, so interoperability is at the heart of any CPS architecture design. In this sense, the adoption of standard and generic data formats for data representation and communication, e.g., XML or JSON, effectively addresses the interoperability problem among heterogeneous systems. Nevertheless, the verbosity of those standard data formats usually demands system resources that might suppose an overload for the resource-constrained devices that are typically deployed in CPS. In this work we present Context- and Template-based Compression (CTC), a data compression approach targeted to resource-constrained devices, which allows reducing the resources needed to transmit, store and process data models. Additionally, we provide a benchmark evaluation and comparison with current implementations of the Efficient XML Interchange (EXI) processor, which is promoted by the World Wide Web Consortium (W3C), and it is the most prominent XML compression mechanism nowadays. Interestingly, the results from the evaluation show that CTC outperforms EXI implementations in terms of memory usage and speed, keeping similar compression rates. As a conclusion, CTC is shown to be a good candidate for managing standard data model representation formats in CPS composed of resource-constrained devices.

Context- and Template-Based Compression for Efficient Management of Data Models in Resource-Constrained Systems

PubMed Central

Montón, Luis Gardeazabal

2017-01-01

The Cyber Physical Systems (CPS) paradigm is based on the deployment of interconnected heterogeneous devices and systems, so interoperability is at the heart of any CPS architecture design. In this sense, the adoption of standard and generic data formats for data representation and communication, e.g., XML or JSON, effectively addresses the interoperability problem among heterogeneous systems. Nevertheless, the verbosity of those standard data formats usually demands system resources that might suppose an overload for the resource-constrained devices that are typically deployed in CPS. In this work we present Context- and Template-based Compression (CTC), a data compression approach targeted to resource-constrained devices, which allows reducing the resources needed to transmit, store and process data models. Additionally, we provide a benchmark evaluation and comparison with current implementations of the Efficient XML Interchange (EXI) processor, which is promoted by the World Wide Web Consortium (W3C), and it is the most prominent XML compression mechanism nowadays. Interestingly, the results from the evaluation show that CTC outperforms EXI implementations in terms of memory usage and speed, keeping similar compression rates. As a conclusion, CTC is shown to be a good candidate for managing standard data model representation formats in CPS composed of resource-constrained devices. PMID:28763013

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cembranos, Jose A. R.; Diaz-Cruz, J. Lorenzo; Prado, Lilian

Dark Matter direct detection experiments are able to exclude interesting parameter space regions of particle models which predict an important amount of thermal relics. We use recent data to constrain the branon model and to compute the region that is favored by CDMS measurements. Within this work, we also update present colliders constraints with new studies coming from the LHC. Despite the present low luminosity, it is remarkable that for heavy branons, CMS and ATLAS measurements are already more constraining than previous analyses performed with TEVATRON and LEP data.

Working Memory in Children: A Time-Constrained Functioning Similar to Adults

ERIC Educational Resources Information Center

Portrat, Sophie; Camos, Valerie; Barrouillet, Pierre

2009-01-01

Within the time-based resource-sharing (TBRS) model, we tested a new conception of the relationships between processing and storage in which the core mechanisms of working memory (WM) are time constrained. However, our previous studies were restricted to adults. The current study aimed at demonstrating that these mechanisms are present and…

Constraining the Timing of Lobate Debris Apron Emplacement at Martian Mid-Latitudes Using a Numerical Model of Ice Flow

NASA Astrophysics Data System (ADS)

Parsons, R. A.; Nimmo, F.

2010-03-01

SHARAD observations constrain the thickness and dust content of lobate debris aprons (LDAs). Simulations of dust-free ice-sheet flow over a flat surface at 205 K for 10-100 m.y. give LDA lengths and thicknesses that are consistent with observations.

Two-Phase Item Selection Procedure for Flexible Content Balancing in CAT

ERIC Educational Resources Information Center

Cheng, Ying; Chang, Hua-Hua; Yi, Qing

2007-01-01

Content balancing is an important issue in the design and implementation of computerized adaptive testing (CAT). Content-balancing techniques that have been applied in fixed content balancing, where the number of items from each content area is fixed, include constrained CAT (CCAT), the modified multinomial model (MMM), modified constrained CAT…

Constraining U.S. ammonia emissions using TES remote sensing observations and the GEOS-Chem adjoint model

EPA Science Inventory

Ammonia (NH(₃)has significant impacts on biodiversity, eutrophication, and acidification. Widespread uncertainty in the magnitude and seasonality of NH3 emissions hinders efforts to address these issues. In this work, we constrain U.S. NH₃ sources using obse...

Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation

NASA Technical Reports Server (NTRS)

Simon, Dan; Simon, Donald L.

2006-01-01

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter truncates the PDF (probability density function) of the Kalman filter estimate at the known constraints and then computes the constrained filter estimate as the mean of the truncated PDF. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is demonstrated via simulation results obtained from a turbofan engine model. The turbofan engine model contains 3 state variables, 11 measurements, and 10 component health parameters. It is also shown that the truncated Kalman filter may be a more accurate way of incorporating inequality constraints than other constrained filters (e.g., the projection approach to constrained filtering).

Theoretical calculation of reorganization energy for electron self-exchange reaction by constrained density functional theory and constrained equilibrium thermodynamics.

PubMed

Ren, Hai-Sheng; Ming, Mei-Jun; Ma, Jian-Yi; Li, Xiang-Yuan

2013-08-22

Within the framework of constrained density functional theory (CDFT), the diabatic or charge localized states of electron transfer (ET) have been constructed. Based on the diabatic states, inner reorganization energy λin has been directly calculated. For solvent reorganization energy λs, a novel and reasonable nonequilibrium solvation model is established by introducing a constrained equilibrium manipulation, and a new expression of λs has been formulated. It is found that λs is actually the cost of maintaining the residual polarization, which equilibrates with the extra electric field. On the basis of diabatic states constructed by CDFT, a numerical algorithm using the new formulations with the dielectric polarizable continuum model (D-PCM) has been implemented. As typical test cases, self-exchange ET reactions between tetracyanoethylene (TCNE) and tetrathiafulvalene (TTF) and their corresponding ionic radicals in acetonitrile are investigated. The calculated reorganization energies λ are 7293 cm(-1) for TCNE/TCNE(-) and 5939 cm(-1) for TTF/TTF(+) reactions, agreeing well with available experimental results of 7250 cm(-1) and 5810 cm(-1), respectively.

Technical Note: On the use of nudging for aerosol–climate model intercomparison studies

DOE PAGES

Zhang, K.; Wan, H.; Liu, X.; ...

2014-08-26

Nudging as an assimilation technique has seen increased use in recent years in the development and evaluation of climate models. Constraining the simulated wind and temperature fields using global weather reanalysis facilitates more straightforward comparison between simulation and observation, and reduces uncertainties associated with natural variabilities of the large-scale circulation. On the other hand, the forcing introduced by nudging can be strong enough to change the basic characteristics of the model climate. In the paper we show that for the Community Atmosphere Model version 5 (CAM5), due to the systematic temperature bias in the standard model and the sensitivity ofmore » simulated ice formation to anthropogenic aerosol concentration, nudging towards reanalysis results in substantial reductions in the ice cloud amount and the impact of anthropogenic aerosols on long-wave cloud forcing. In order to reduce discrepancies between the nudged and unconstrained simulations, and meanwhile take the advantages of nudging, two alternative experimentation methods are evaluated. The first one constrains only the horizontal winds. The second method nudges both winds and temperature, but replaces the long-term climatology of the reanalysis by that of the model. Results show that both methods lead to substantially improved agreement with the free-running model in terms of the top-of-atmosphere radiation budget and cloud ice amount. The wind-only nudging is more convenient to apply, and provides higher correlations of the wind fields, geopotential height and specific humidity between simulation and reanalysis. Results from both CAM5 and a second aerosol–climate model ECHAM6-HAM2 also indicate that compared to the wind-and-temperature nudging, constraining only winds leads to better agreement with the free-running model in terms of the estimated shortwave cloud forcing and the simulated convective activities. This suggests nudging the horizontal winds but not temperature is a good strategy for the investigation of aerosol indirect effects since it provides well-constrained meteorology without strongly perturbing the model's mean climate.« less

Technical Note: On the use of nudging for aerosol-climate model intercomparison studies

NASA Astrophysics Data System (ADS)

Zhang, K.; Wan, H.; Liu, X.; Ghan, S. J.; Kooperman, G. J.; Ma, P.-L.; Rasch, P. J.; Neubauer, D.; Lohmann, U.

2014-08-01

Nudging as an assimilation technique has seen increased use in recent years in the development and evaluation of climate models. Constraining the simulated wind and temperature fields using global weather reanalysis facilitates more straightforward comparison between simulation and observation, and reduces uncertainties associated with natural variabilities of the large-scale circulation. On the other hand, the forcing introduced by nudging can be strong enough to change the basic characteristics of the model climate. In the paper we show that for the Community Atmosphere Model version 5 (CAM5), due to the systematic temperature bias in the standard model and the sensitivity of simulated ice formation to anthropogenic aerosol concentration, nudging towards reanalysis results in substantial reductions in the ice cloud amount and the impact of anthropogenic aerosols on long-wave cloud forcing. In order to reduce discrepancies between the nudged and unconstrained simulations, and meanwhile take the advantages of nudging, two alternative experimentation methods are evaluated. The first one constrains only the horizontal winds. The second method nudges both winds and temperature, but replaces the long-term climatology of the reanalysis by that of the model. Results show that both methods lead to substantially improved agreement with the free-running model in terms of the top-of-atmosphere radiation budget and cloud ice amount. The wind-only nudging is more convenient to apply, and provides higher correlations of the wind fields, geopotential height and specific humidity between simulation and reanalysis. Results from both CAM5 and a second aerosol-climate model ECHAM6-HAM2 also indicate that compared to the wind-and-temperature nudging, constraining only winds leads to better agreement with the free-running model in terms of the estimated shortwave cloud forcing and the simulated convective activities. This suggests nudging the horizontal winds but not temperature is a good strategy for the investigation of aerosol indirect effects since it provides well-constrained meteorology without strongly perturbing the model's mean climate.

Numerical modeling of Drangajökull Ice Cap, NW Iceland

NASA Astrophysics Data System (ADS)

Anderson, Leif S.; Jarosch, Alexander H.; Flowers, Gwenn E.; Aðalgeirsdóttir, Guðfinna; Magnússon, Eyjólfur; Pálsson, Finnur; Muñoz-Cobo Belart, Joaquín; Þorsteinsson, Þorsteinn; Jóhannesson, Tómas; Sigurðsson, Oddur; Harning, David; Miller, Gifford H.; Geirsdóttir, Áslaug

2016-04-01

Over the past century the Arctic has warmed twice as fast as the global average. This discrepancy is likely due to feedbacks inherent to the Arctic climate system. These Arctic climate feedbacks are currently poorly quantified, but are essential to future climate predictions based on global circulation modeling. Constraining the magnitude and timing of past Arctic climate changes allows us to test climate feedback parameterizations at different times with different boundary conditions. Because Holocene Arctic summer temperature changes have been largest in the North Atlantic (Kaufman et al., 2004) we focus on constraining the paleoclimate of Iceland. Glaciers are highly sensitive to changes in temperature and precipitation amount. This sensitivity allows for the estimation of paleoclimate using glacier models, modern glacier mass balance data, and past glacier extents. We apply our model to the Drangajökull ice cap (~150 sq. km) in NW Iceland. Our numerical model is resolved in two-dimensions, conserves mass, and applies the shallow-ice-approximation. The bed DEM used in the model runs was constructed from radio echo data surveyed in spring 2014. We constrain the modern surface mass balance of Drangajökull using: 1) ablation and accumulation stakes; 2) ice surface digital elevation models (DEMs) from satellite, airborne LiDAR, and aerial photographs; and 3) full-stokes model-derived vertical ice velocities. The modeled vertical ice velocities and ice surface DEMs are combined to estimate past surface mass balance. We constrain Holocene glacier geometries using moraines and trimlines (e.g., Brynjolfsson, etal, 2014), proglacial-lake cores, and radiocarbon-dated dead vegetation emerging from under the modern glacier. We present a sensitivity analysis of the model to changes in parameters and show the effect of step changes of temperature and precipitation on glacier extent. Our results are placed in context with local lacustrine and marine climate proxies as well as with glacier extent and volume changes across the North Atlantic.

Towards Anatomic Scale Agent-Based Modeling with a Massively Parallel Spatially Explicit General-Purpose Model of Enteric Tissue (SEGMEnT_HPC)

PubMed Central

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis. PMID:25806784

Constraining Plasma Conditions of the IPT via Spectral Analysis of UV & Visible Emissions and Comparing with a Physical Chemistry Model

NASA Astrophysics Data System (ADS)

Nerney, E. G.; Bagenal, F.; Yoshioka, K.; Schmidt, C.

2017-12-01

Io emits volcanic gases into space at a rate of about a ton per second. The gases become ionized and trapped in Jupiter's strong magnetic field, forming a torus of plasma that emits 2 terawatts of UV emissions. In recent work re-analyzing UV emissions observed by Voyager, Galileo, & Cassini, we found plasma conditions consistent with a physical chemistry model with a neutral source of dissociated sulfur dioxide from Io (Nerney et al., 2017). In further analysis of UV observations from JAXA's Hisaki mission (using our spectral emission model) we constrain the torus composition with ground based observations. The physical chemistry model (adapted from Delamere et al., 2005) is then used to match derived plasma conditions. We correlate the oxygen to sulfur ratio of the neutral source with volcanic eruptions to understand the change in magnetospheric plasma conditions. Our goal is to better understand and constrain both the temporal and spatial variability of the flow of mass and energy from Io's volcanic atmosphere to Jupiter's dynamic magnetosphere.

Inverse and Predictive Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Syracuse, Ellen Marie

The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an evenmore » greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.« less

Active constrained layer damping of geometrically nonlinear vibrations of functionally graded plates using piezoelectric fiber-reinforced composites

NASA Astrophysics Data System (ADS)

Panda, Satyajit; Ray, M. C.

2008-04-01

In this paper, a geometrically nonlinear dynamic analysis has been presented for functionally graded (FG) plates integrated with a patch of active constrained layer damping (ACLD) treatment and subjected to a temperature field. The constraining layer of the ACLD treatment is considered to be made of the piezoelectric fiber-reinforced composite (PFRC) material. The temperature field is assumed to be spatially uniform over the substrate plate surfaces and varied through the thickness of the host FG plates. The temperature-dependent material properties of the FG substrate plates are assumed to be graded in the thickness direction of the plates according to a power-law distribution while the Poisson's ratio is assumed to be a constant over the domain of the plate. The constrained viscoelastic layer of the ACLD treatment is modeled using the Golla-Hughes-McTavish (GHM) method. Based on the first-order shear deformation theory, a three-dimensional finite element model has been developed to model the open-loop and closed-loop nonlinear dynamics of the overall FG substrate plates under the thermal environment. The analysis suggests the potential use of the ACLD treatment with its constraining layer made of the PFRC material for active control of geometrically nonlinear vibrations of FG plates in the absence or the presence of the temperature gradient across the thickness of the plates. It is found that the ACLD treatment is more effective in controlling the geometrically nonlinear vibrations of FG plates than in controlling their linear vibrations. The analysis also reveals that the ACLD patch is more effective for controlling the nonlinear vibrations of FG plates when it is attached to the softest surface of the FG plates than when it is bonded to the stiffest surface of the plates. The effect of piezoelectric fiber orientation in the active constraining PFRC layer on the damping characteristics of the overall FG plates is also discussed.

Characterizing biospheric carbon balance using CO2 observations from the OCO-2 satellite

NASA Astrophysics Data System (ADS)

Miller, Scot M.; Michalak, Anna M.; Yadav, Vineet; Tadić, Jovan M.

2018-05-01

NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite launched in summer of 2014. Its observations could allow scientists to constrain CO2 fluxes across regions or continents that were previously difficult to monitor. This study explores an initial step toward that goal; we evaluate the extent to which current OCO-2 observations can detect patterns in biospheric CO2 fluxes and constrain monthly CO2 budgets. Our goal is to guide top-down, inverse modeling studies and identify areas for future improvement. We find that uncertainties and biases in the individual OCO-2 observations are comparable to the atmospheric signal from biospheric fluxes, particularly during Northern Hemisphere winter when biospheric fluxes are small. A series of top-down experiments indicate how these errors affect our ability to constrain monthly biospheric CO2 budgets. We are able to constrain budgets for between two and four global regions using OCO-2 observations, depending on the month, and we can constrain CO2 budgets at the regional level (i.e., smaller than seven global biomes) in only a handful of cases (16 % of all regions and months). The potential of the OCO-2 observations, however, is greater than these results might imply. A set of synthetic data experiments suggests that retrieval errors have a salient effect. Advances in retrieval algorithms and to a lesser extent atmospheric transport modeling will improve the results. In the interim, top-down studies that use current satellite observations are best-equipped to constrain the biospheric carbon balance across only continental or hemispheric regions.

Finite-time convergent recurrent neural network with a hard-limiting activation function for constrained optimization with piecewise-linear objective functions.

PubMed

Liu, Qingshan; Wang, Jun

2011-04-01

This paper presents a one-layer recurrent neural network for solving a class of constrained nonsmooth optimization problems with piecewise-linear objective functions. The proposed neural network is guaranteed to be globally convergent in finite time to the optimal solutions under a mild condition on a derived lower bound of a single gain parameter in the model. The number of neurons in the neural network is the same as the number of decision variables of the optimization problem. Compared with existing neural networks for optimization, the proposed neural network has a couple of salient features such as finite-time convergence and a low model complexity. Specific models for two important special cases, namely, linear programming and nonsmooth optimization, are also presented. In addition, applications to the shortest path problem and constrained least absolute deviation problem are discussed with simulation results to demonstrate the effectiveness and characteristics of the proposed neural network.

A fuzzy chance-constrained programming model with type 1 and type 2 fuzzy sets for solid waste management under uncertainty

NASA Astrophysics Data System (ADS)

Ma, Xiaolin; Ma, Chi; Wan, Zhifang; Wang, Kewei

2017-06-01

Effective management of municipal solid waste (MSW) is critical for urban planning and development. This study aims to develop an integrated type 1 and type 2 fuzzy sets chance-constrained programming (ITFCCP) model for tackling regional MSW management problem under a fuzzy environment, where waste generation amounts are supposed to be type 2 fuzzy variables and treated capacities of facilities are assumed to be type 1 fuzzy variables. The evaluation and expression of uncertainty overcome the drawbacks in describing fuzzy possibility distributions as oversimplified forms. The fuzzy constraints are converted to their crisp equivalents through chance-constrained programming under the same or different confidence levels. Regional waste management of the City of Dalian, China, was used as a case study for demonstration. The solutions under various confidence levels reflect the trade-off between system economy and reliability. It is concluded that the ITFCCP model is capable of helping decision makers to generate reasonable waste-allocation alternatives under uncertainties.

Reinterpreting maximum entropy in ecology: a null hypothesis constrained by ecological mechanism.

PubMed

O'Dwyer, James P; Rominger, Andrew; Xiao, Xiao

2017-07-01

Simplified mechanistic models in ecology have been criticised for the fact that a good fit to data does not imply the mechanism is true: pattern does not equal process. In parallel, the maximum entropy principle (MaxEnt) has been applied in ecology to make predictions constrained by just a handful of state variables, like total abundance or species richness. But an outstanding question remains: what principle tells us which state variables to constrain? Here we attempt to solve both problems simultaneously, by translating a given set of mechanisms into the state variables to be used in MaxEnt, and then using this MaxEnt theory as a null model against which to compare mechanistic predictions. In particular, we identify the sufficient statistics needed to parametrise a given mechanistic model from data and use them as MaxEnt constraints. Our approach isolates exactly what mechanism is telling us over and above the state variables alone. © 2017 John Wiley & Sons Ltd/CNRS.

Constraining Earth's Rheology of the Barents Sea Using Grace Gravity Change Observations

NASA Astrophysics Data System (ADS)

van der Wal, W.; Root, B. C.; Tarasov, L.

2014-12-01

The Barents Sea region was ice covered during last glacial maximum and experiences Glacial Isostatic Adjustment (GIA). Because of the limited amount of relevant geological and geodetic observations, it is difficult to constrain GIA models for this region. With improved ice sheet models and gravity observations from GRACE, it is possible to better constrain Earth rheology. This study aims to constrain the upper mantle viscosity and elastic lithosphere thickness from GRACE data in the Barents Sea region. The GRACE observations are corrected for current ice melting on Svalbard, Novaya Zemlya and Frans Joseph Land. A secular trend in gravity rate trend is estimated from the CSR release 5 GRACE data for the period of February 2003 to July 2013. Furthermore, long wavelength effects from distant large mass balance signals such as Greenland ice melting are filtered out. A new high-variance set of ice loading histories from calibrated glaciological modeling are used in the GIA modeling as it is found that ICE-5G over-estimates the observed GIA gravity change in the region. It is found that the rheology structure represented by VM5a results in over-estimation of the observed gravity change in the region for all ice sheet chronologies investigated. Therefore, other rheological Earth models were investigated. The best fitting upper mantle viscosity and elastic lithosphere thickness in the Barents Sea region are 4 (±0.5)*10^20 Pas and 110 (±20) km, respectively. The GRACE satellite mission proves to be a useful constraint in the Barents Sea Region for improving our knowledge on the upper mantle rheology.

Source model for the Copahue volcano magmaplumbing system constrained by InSARsurface deformation observations

NASA Astrophysics Data System (ADS)

Lundgren, P.; Nikkhoo, M.; Samsonov, S. V.; Milillo, P.; Gil-Cruz, F., Sr.; Lazo, J.

2017-12-01

Copahue volcano straddling the edge of the Agrio-Caviahue caldera along the Chile-Argentinaborder in the southern Andes has been in unrest since inflation began in late 2011. We constrain Copahue'ssource models with satellite and airborne interferometric synthetic aperture radar (InSAR) deformationobservations. InSAR time series from descending track RADARSAT-2 and COSMO-SkyMed data span theentire inflation period from 2011 to 2016, with their initially high rates of 12 and 15 cm/yr, respectively,slowing only slightly despite ongoing small eruptions through 2016. InSAR ascending and descending tracktime series for the 2013-2016 time period constrain a two-source compound dislocation model, with a rate ofvolume increase of 13 × 106 m3/yr. They consist of a shallow, near-vertical, elongated source centered at2.5 km beneath the summit and a deeper, shallowly plunging source centered at 7 km depth connecting theshallow source to the deeper caldera. The deeper source is located directly beneath the volcano tectonicseismicity with the lower bounds of the seismicity parallel to the plunge of the deep source. InSAR time seriesalso show normal fault offsets on the NE flank Copahue faults. Coulomb stress change calculations forright-lateral strike slip (RLSS), thrust, and normal receiver faults show positive values in the north caldera forboth RLSS and normal faults, suggesting that northward trending seismicity and Copahue fault motion withinthe caldera are caused by the modeled sources. Together, the InSAR-constrained source model and theseismicity suggest a deep conduit or transfer zone where magma moves from the central caldera toCopahue's upper edifice.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Tong; Xue, Li; Zhao, Xiao-Hong

Black holes (BHs) hide themselves behind various astronomical phenomena and their properties, i.e., mass and spin, are usually difficult to constrain. One leading candidate for the central engine model of gamma-ray bursts (GRBs) invokes a stellar mass BH and a neutrino-dominated accretion flow (NDAF), with the relativistic jet launched due to neutrino-anti-neutrino annihilations. Such a model gives rise to a matter-dominated fireball, and is suitable to interpret GRBs with a dominant thermal component with a photospheric origin. We propose a method to constrain BH mass and spin within the framework of this model and apply the method to the thermallymore » dominant GRB 101219B, whose initial jet launching radius, r {sub 0}, is constrained from the data. Using our numerical model of NDAF jets, we estimate the following constraints on the central BH: mass M {sub BH} ∼ 5–9 M {sub ⊙}, spin parameter a {sub *} ≳ 0.6, and disk mass 3 M {sub ⊙} ≲ M {sub disk} ≲ 4 M {sub ⊙}. Our results also suggest that the NDAF model is a competitive candidate for the central engine of GRBs with a strong thermal component.« less

Development of Cell‐Permeable, Non‐Helical Constrained Peptides to Target a Key Protein–Protein Interaction in Ovarian Cancer

PubMed Central

Wiedmann, Mareike M.; Tan, Yaw Sing; Wu, Yuteng; Aibara, Shintaro; Xu, Wenshu; Sore, Hannah F.; Verma, Chandra S.; Itzhaki, Laura; Stewart, Murray; Brenton, James D.

2016-01-01

Abstract There is a lack of current treatment options for ovarian clear cell carcinoma (CCC) and the cancer is often resistant to platinum‐based chemotherapy. Hence there is an urgent need for novel therapeutics. The transcription factor hepatocyte nuclear factor 1β (HNF1β) is ubiquitously overexpressed in CCC and is seen as an attractive therapeutic target. This was validated through shRNA‐mediated knockdown of the target protein, HNF1β, in five high‐ and low‐HNF1β‐expressing CCC lines. To inhibit the protein function, cell‐permeable, non‐helical constrained proteomimetics to target the HNF1β–importin α protein–protein interaction were designed, guided by X‐ray crystallographic data and molecular dynamics simulations. In this way, we developed the first reported series of constrained peptide nuclear import inhibitors. Importantly, this general approach may be extended to other transcription factors. PMID:27918136

An Observationally Constrained Evaluation of the Oxidative Capacity in the Tropical Western Pacific Troposphere

NASA Technical Reports Server (NTRS)

Nicely, Julie M.; Anderson, Daniel C.; Canty, Timothy P.; Salawitch, Ross J.; Wolfe, Glenn M.; Apel, Eric C.; Arnold, Steve R.; Atlas, Elliot L.; Blake, Nicola J.; Bresch, James F.;

Constraining Water Vapor Abundance on Mars using a Coupled Heat-Water Transport Model and Seasonal Frost Observations

NASA Astrophysics Data System (ADS)

Bapst, J.; Byrne, S.

2016-12-01

The stability of water ice on Mars' surface is determined by its temperature and the density of water vapor at the bottom of the atmosphere. Multiple orbiting instruments have been used to study column-integrated water abundance in the martian atmosphere, resolving the global annual water cycle. However, poor knowledge of the vertical distribution of water makes constraining its abundance near the surface difficult. One must assume a mixing regime to produce surface vapor density estimates. More indirectly, one can use the appearance and disappearance of seasonal water frost, along with ice stability models, to estimate this value. Here, we use derived temperature and surface reflectance data from MGS TES to constrain a 1-D thermal diffusion model, which is coupled to an atmospheric water transport model. TES temperatures are used to constrain thermal properties of our modeled subsurface, while changes in TES albedo can be used to determine the timing of water frost. We tune the density of water vapor in the atmospheric model to match the observed seasonal water frost timing in the northern hemisphere, poleward of 45°N. Thus, we produce a new estimate for the water abundance in the lower atmosphere of Mars and how it varies seasonally and geographically. The timing of water frost can be ambiguous in TES data, especially at lower latitudes where the albedo contrast between frosted and unfrosted surfaces is lower (presumably due to lesser areal coverage of water frost). The uncertainty in frost timing with our approach is <20° LS ( 40 sols), and will be used to define upper and lower bounds in our estimate of vapor density. The implications of our derived vapor densities on the stability of surface and subsurface water ice will be discussed.

Employing 2D Forward Modeling of Gravity and Magnetic Data to Further Constrain the Magnitude of Extension Recorded by the Caetano Caldera, Nevada

NASA Astrophysics Data System (ADS)

Ritzinger, B. T.; Glen, J. M. G.; Athens, N. D.; Denton, K. M.; Bouligand, C.

2015-12-01

Regionally continuous Cenozoic rocks in the Basin and Range that predate the onset of major mid-Miocene extension provide valuable insight into the sequence of faulting and magnitude of extension. An exceptional example of this is Caetano caldera, located in north-central Nevada, that formed during the eruption of the Caetano Tuff at the Eocene-Oligocene transition. The caldera and associated deposits, as well as conformable caldera-filling sedimentary and volcanic units allow for the reconstruction of post Oligocene extensional faulting. Extensive mapping and geochronologic, geochemical and paleomagnetic analyses have been conducted over the last decade to help further constrain the eruptive and extensional history of the Caetano caldera and associated deposits. Gravity and magnetic data, that highlight contrasts in density and magnetic properties (susceptibility and remanence), respectively, are useful for mapping and modeling structural and lithic discontinuities. By combining existing gravity and aeromagnetic data with newly collected high-resolution gravity data, we are performing detailed potential field modeling to better characterize the subsurface within and surrounding the caldera. Modeling is constrained by published geologic map and cross sections and by new rock properties for these units determined from oriented drill core and hand samples collected from outcrops that span all of the major rock units in the study area. These models will enable us to better map the margins of the caldera and more accurately determine subsurface lithic boundaries and complex fault geometries, as well as aid in refining estimates of the magnitude of extension across the caldera. This work highlights the value in combining geologic and geophysical data to build an integrated structural model to help characterize the subsurface and better constrain the extensional tectonic history if this part of the Great Basin.

Universality of clone dynamics during tissue development

NASA Astrophysics Data System (ADS)

Rulands, Steffen; Lescroart, Fabienne; Chabab, Samira; Hindley, Christopher J.; Prior, Nicole; Sznurkowska, Magdalena K.; Huch, Meritxell; Philpott, Anna; Blanpain, Cedric; Simons, Benjamin D.

2018-05-01

The emergence of complex organs is driven by the coordinated proliferation, migration and differentiation of precursor cells. The fate behaviour of these cells is reflected in the time evolution of their progeny, termed clones, which serve as a key experimental observable. In adult tissues, where cell dynamics is constrained by the condition of homeostasis, clonal tracing studies based on transgenic animal models have advanced our understanding of cell fate behaviour and its dysregulation in disease1,2. But what can be learnt from clonal dynamics in development, where the spatial cohesiveness of clones is impaired by tissue deformations during tissue growth? Drawing on the results of clonal tracing studies, we show that, despite the complexity of organ development, clonal dynamics may converge to a critical state characterized by universal scaling behaviour of clone sizes. By mapping clonal dynamics onto a generalization of the classical theory of aerosols, we elucidate the origin and range of scaling behaviours and show how the identification of universal scaling dependences may allow lineage-specific information to be distilled from experiments. Our study shows the emergence of core concepts of statistical physics in an unexpected context, identifying cellular systems as a laboratory to study non-equilibrium statistical physics.

Motion mechanics of non-adherent giant liposomes with a combined optical and atomic force microscope

NASA Astrophysics Data System (ADS)

Moreno-Flores, Susana; Ortíz, Rocío

2017-11-01

Herein we present an investigation of the motional dynamics of single mesoscopic bodies of biological relevance with an AFM-based macromanipulation tool and an optical microscope. Giant liposomes are prominent case examples as minimal cell models; studying their mechanics provides a means to address the influence of structural components in the mechanical behaviour of living cells. However, they also pose an experimental challenge due to their lightness, fragility, and high mobility. Their entrapment in wells in a fluid of lower density allows their study under conditions of constrained motion, which enables the synchronous measurement of nanoforces with motion tracking. The procedure enables to estimate sliding friction coefficients and masses of vesicles, and sheds light upon the region between the vesicle and the underlying substrate. The present study paves the way for the investigation of motion and deformation mechanics with one combined technique and a single type of experiment traditionally vetoed to objects that can move as well as deform. Such an approach can be directly applied to cells in suspension, adherent cells or cellular 3D-assemblies so as to assess substrate biocompatibility, monitor adhesion, detachment, motility as well as deformability.

A finite-temperature Hartree-Fock code for shell-model Hamiltonians

NASA Astrophysics Data System (ADS)

Bertsch, G. F.; Mehlhaff, J. M.

2016-10-01

The codes HFgradZ.py and HFgradT.py find axially symmetric minima of a Hartree-Fock energy functional for a Hamiltonian supplied in a shell model basis. The functional to be minimized is the Hartree-Fock energy for zero-temperature properties or the Hartree-Fock grand potential for finite-temperature properties (thermal energy, entropy). The minimization may be subjected to additional constraints besides axial symmetry and nucleon numbers. A single-particle operator can be used to constrain the minimization by adding it to the single-particle Hamiltonian with a Lagrange multiplier. One can also constrain its expectation value in the zero-temperature code. Also the orbital filling can be constrained in the zero-temperature code, fixing the number of nucleons having given Kπ quantum numbers. This is particularly useful to resolve near-degeneracies among distinct minima.

High-throughput alternative splicing detection using dually constrained correspondence analysis (DCCA).

PubMed

Baty, Florent; Klingbiel, Dirk; Zappa, Francesco; Brutsche, Martin

2015-12-01

Alternative splicing is an important component of tumorigenesis. Recent advent of exon array technology enables the detection of alternative splicing at a genome-wide scale. The analysis of high-throughput alternative splicing is not yet standard and methodological developments are still needed. We propose a novel statistical approach-Dually Constrained Correspondence Analysis-for the detection of splicing changes in exon array data. Using this methodology, we investigated the genome-wide alteration of alternative splicing in patients with non-small cell lung cancer treated by bevacizumab/erlotinib. Splicing candidates reveal a series of genes related to carcinogenesis (SFTPB), cell adhesion (STAB2, PCDH15, HABP2), tumor aggressiveness (ARNTL2), apoptosis, proliferation and differentiation (PDE4D, FLT3, IL1R2), cell invasion (ETV1), as well as tumor growth (OLFM4, FGF14), tumor necrosis (AFF3) or tumor suppression (TUSC3, CSMD1, RHOBTB2, SERPINB5), with indication of known alternative splicing in a majority of genes. DCCA facilitates the identification of putative biologically relevant alternative splicing events in high-throughput exon array data. Copyright © 2015 Elsevier Inc. All rights reserved.

Constrained inversion as a hypothesis testing tool, what can we learn about the lithosphere?

NASA Astrophysics Data System (ADS)

Moorkamp, Max; Stewart, Fishwick; Jones, Alan G.

2017-04-01

Inversion of geophysical data constrained by a reference model is typically used to guide the inversion of low resolution data towards a geologically plausible solution. For example, a migrated seismic section can provide the location of lithological boundaries for potential field inversions. Here we consider the inversion of long-period magnetotelluric data constrained by models generated through surface wave inversion. In this case, we do not consider the surface wave model inherently better in any sense and want to guide the magnetotelluric inversion towards this model, but we want to test the hypothesis that both datasets can be explained by models with similar structure. If the hypothesis test is successful, i.e. we can fit the observations with a conductivity model with structural similarity to the seismic model, we have found an alternative explanation compared to the individual inversion and can use the differences to learn about the resolution of the magnetotelluric data and can improve our interpretation. Conversely, if the test refutes our hypothesis of coincident structure, we have found features in the models that are sensed fundamentally different by both methods which is potentially instructive on the nature of the anomalies. We use a MT dataset acquired in central Botswana over the Okwa terrane and the adjacent Kaapvaal and Zimbabwe Cratons together with a tomographic model for the region to illustrate and test this approach. Here, various conductive structures have been identified that bridge the Moho. Furthermore, the thickness of the lithosphere inferred from the different methods differs. In both cases the question is in how far this is a result of the ill-posed nature of inversion and in how far these differences can be reconciled. Thus this dataset is an ideal test case for our hypothesis testing approach. Finally, we will demonstrate how we can use the results of the constrained inversion to extract conductivity-velocity relationships in the region and gain further insight into the composition and thermal structure of the lithosphere.

A sampling and classification item selection approach with content balancing.

PubMed

Chen, Pei-Hua

2015-03-01

Existing automated test assembly methods typically employ constrained combinatorial optimization. Constructing forms sequentially based on an optimization approach usually results in unparallel forms and requires heuristic modifications. Methods based on a random search approach have the major advantage of producing parallel forms sequentially without further adjustment. This study incorporated a flexible content-balancing element into the statistical perspective item selection method of the cell-only method (Chen et al. in Educational and Psychological Measurement, 72(6), 933-953, 2012). The new method was compared with a sequential interitem distance weighted deviation model (IID WDM) (Swanson & Stocking in Applied Psychological Measurement, 17(2), 151-166, 1993), a simultaneous IID WDM, and a big-shadow-test mixed integer programming (BST MIP) method to construct multiple parallel forms based on matching a reference form item-by-item. The results showed that the cell-only method with content balancing and the sequential and simultaneous versions of IID WDM yielded results comparable to those obtained using the BST MIP method. The cell-only method with content balancing is computationally less intensive than the sequential and simultaneous versions of IID WDM.

Nonlinear model predictive control of a wave energy converter based on differential flatness parameterisation

NASA Astrophysics Data System (ADS)

Li, Guang

2017-01-01

This paper presents a fast constrained optimization approach, which is tailored for nonlinear model predictive control of wave energy converters (WEC). The advantage of this approach relies on its exploitation of the differential flatness of the WEC model. This can reduce the dimension of the resulting nonlinear programming problem (NLP) derived from the continuous constrained optimal control of WEC using pseudospectral method. The alleviation of computational burden using this approach helps to promote an economic implementation of nonlinear model predictive control strategy for WEC control problems. The method is applicable to nonlinear WEC models, nonconvex objective functions and nonlinear constraints, which are commonly encountered in WEC control problems. Numerical simulations demonstrate the efficacy of this approach.

The Apollo 16 regolith - A petrographically-constrained chemical mixing model

NASA Technical Reports Server (NTRS)

Kempa, M. J.; Papike, J. J.; White, C.

1980-01-01

A mixing model for Apollo 16 regolith samples has been developed, which differs from other A-16 mixing models in that it is both petrographically constrained and statistically sound. The model was developed using three components representative of rock types present at the A-16 site, plus a representative mare basalt. A linear least-squares fitting program employing the chi-squared test and sum of components was used to determine goodness of fit. Results for surface soils indicate that either there are no significant differences between Cayley and Descartes material at the A-16 site or, if differences do exist, they have been obscured by meteoritic reworking and mixing of the lithologies.

An Approximation to the Adaptive Exponential Integrate-and-Fire Neuron Model Allows Fast and Predictive Fitting to Physiological Data.

PubMed

Hertäg, Loreen; Hass, Joachim; Golovko, Tatiana; Durstewitz, Daniel

2012-01-01

For large-scale network simulations, it is often desirable to have computationally tractable, yet in a defined sense still physiologically valid neuron models. In particular, these models should be able to reproduce physiological measurements, ideally in a predictive sense, and under different input regimes in which neurons may operate in vivo. Here we present an approach to parameter estimation for a simple spiking neuron model mainly based on standard f-I curves obtained from in vitro recordings. Such recordings are routinely obtained in standard protocols and assess a neuron's response under a wide range of mean-input currents. Our fitting procedure makes use of closed-form expressions for the firing rate derived from an approximation to the adaptive exponential integrate-and-fire (AdEx) model. The resulting fitting process is simple and about two orders of magnitude faster compared to methods based on numerical integration of the differential equations. We probe this method on different cell types recorded from rodent prefrontal cortex. After fitting to the f-I current-clamp data, the model cells are tested on completely different sets of recordings obtained by fluctuating ("in vivo-like") input currents. For a wide range of different input regimes, cell types, and cortical layers, the model could predict spike times on these test traces quite accurately within the bounds of physiological reliability, although no information from these distinct test sets was used for model fitting. Further analyses delineated some of the empirical factors constraining model fitting and the model's generalization performance. An even simpler adaptive LIF neuron was also examined in this context. Hence, we have developed a "high-throughput" model fitting procedure which is simple and fast, with good prediction performance, and which relies only on firing rate information and standard physiological data widely and easily available.

Lentiviral and targeted cellular barcoding reveals ongoing clonal dynamics of cell lines in vitro and in vivo

PubMed Central

2014-01-01

Background Cell lines are often regarded as clonal, even though this simplifies what is known about mutagenesis, transformation and other processes that destabilize them over time. Monitoring these clonal dynamics is important for multiple areas of biomedical research, including stem cell and cancer biology. Tracking the contributions of individual cells to large populations, however, has been constrained by limitations in sensitivity and complexity. Results We utilize cellular barcoding methods to simultaneously track the clonal contributions of tens of thousands of cells. We demonstrate that even with optimal culturing conditions, common cell lines including HeLa, K562 and HEK-293 T exhibit ongoing clonal dynamics. Starting a population with a single clone diminishes but does not eradicate this phenomenon. Next, we compare lentiviral and zinc-finger nuclease barcode insertion approaches, finding that the zinc-finger nuclease protocol surprisingly results in reduced clonal diversity. We also document the expected reduction in clonal complexity when cells are challenged with genotoxic stress. Finally, we demonstrate that xenografts maintain clonal diversity to a greater extent than in vitro culturing of the human non-small-cell lung cancer cell line HCC827. Conclusions We demonstrate the feasibility of tracking and quantifying the clonal dynamics of entire cell populations within multiple cultured cell lines. Our results suggest that cell heterogeneity should be considered in the design and interpretation of in vitro culture experiments. Aside from clonal cell lines, we propose that cellular barcoding could prove valuable in modeling the clonal behavior of heterogeneous cell populations over time, including tumor populations treated with chemotherapeutic agents. PMID:24886633

Hierarchical Bayesian Model Averaging for Chance Constrained Remediation Designs

NASA Astrophysics Data System (ADS)

Chitsazan, N.; Tsai, F. T.

2012-12-01

Groundwater remediation designs are heavily relying on simulation models which are subjected to various sources of uncertainty in their predictions. To develop a robust remediation design, it is crucial to understand the effect of uncertainty sources. In this research, we introduce a hierarchical Bayesian model averaging (HBMA) framework to segregate and prioritize sources of uncertainty in a multi-layer frame, where each layer targets a source of uncertainty. The HBMA framework provides an insight to uncertainty priorities and propagation. In addition, HBMA allows evaluating model weights in different hierarchy levels and assessing the relative importance of models in each level. To account for uncertainty, we employ a chance constrained (CC) programming for stochastic remediation design. Chance constrained programming was implemented traditionally to account for parameter uncertainty. Recently, many studies suggested that model structure uncertainty is not negligible compared to parameter uncertainty. Using chance constrained programming along with HBMA can provide a rigorous tool for groundwater remediation designs under uncertainty. In this research, the HBMA-CC was applied to a remediation design in a synthetic aquifer. The design was to develop a scavenger well approach to mitigate saltwater intrusion toward production wells. HBMA was employed to assess uncertainties from model structure, parameter estimation and kriging interpolation. An improved harmony search optimization method was used to find the optimal location of the scavenger well. We evaluated prediction variances of chloride concentration at the production wells through the HBMA framework. The results showed that choosing the single best model may lead to a significant error in evaluating prediction variances for two reasons. First, considering the single best model, variances that stem from uncertainty in the model structure will be ignored. Second, considering the best model with non-dominant model weight may underestimate or overestimate prediction variances by ignoring other plausible propositions. Chance constraints allow developing a remediation design with a desirable reliability. However, considering the single best model, the calculated reliability will be different from the desirable reliability. We calculated the reliability of the design for the models at different levels of HBMA. The results showed that by moving toward the top layers of HBMA, the calculated reliability converges to the chosen reliability. We employed the chance constrained optimization along with the HBMA framework to find the optimal location and pumpage for the scavenger well. The results showed that using models at different levels in the HBMA framework, the optimal location of the scavenger well remained the same, but the optimal extraction rate was altered. Thus, we concluded that the optimal pumping rate was sensitive to the prediction variance. Also, the prediction variance was changed by using different extraction rate. Using very high extraction rate will cause prediction variances of chloride concentration at the production wells to approach zero regardless of which HBMA models used.

Testing a Constrained MPC Controller in a Process Control Laboratory

ERIC Educational Resources Information Center

Ricardez-Sandoval, Luis A.; Blankespoor, Wesley; Budman, Hector M.

2010-01-01

This paper describes an experiment performed by the fourth year chemical engineering students in the process control laboratory at the University of Waterloo. The objective of this experiment is to test the capabilities of a constrained Model Predictive Controller (MPC) to control the operation of a Double Pipe Heat Exchanger (DPHE) in real time.…

Robust model predictive control for constrained continuous-time nonlinear systems

NASA Astrophysics Data System (ADS)

Sun, Tairen; Pan, Yongping; Zhang, Jun; Yu, Haoyong

2018-02-01

In this paper, a robust model predictive control (MPC) is designed for a class of constrained continuous-time nonlinear systems with bounded additive disturbances. The robust MPC consists of a nonlinear feedback control and a continuous-time model-based dual-mode MPC. The nonlinear feedback control guarantees the actual trajectory being contained in a tube centred at the nominal trajectory. The dual-mode MPC is designed to ensure asymptotic convergence of the nominal trajectory to zero. This paper extends current results on discrete-time model-based tube MPC and linear system model-based tube MPC to continuous-time nonlinear model-based tube MPC. The feasibility and robustness of the proposed robust MPC have been demonstrated by theoretical analysis and applications to a cart-damper springer system and a one-link robot manipulator.

Stellar Ro

NASA Astrophysics Data System (ADS)

Featherstone, Nicholas

2017-05-01

Our understanding of the interior dynamics that give rise to a stellar dynamo draws heavily from investigations of similar dynamics in the solar context. Unfortunately, an outstanding gap persists in solar dynamo theory. Convection, an indispensable component of the dynamo, occurs in the midst of rotation, and yet we know little about how the influence of that rotation manifests across the broad range of convective scales present in the Sun. We are nevertheless well aware that the interaction of rotation and convection profoundly impacts many aspects of the dynamo, including the meridional circulation, the differential rotation, and the helicity of turbulent EMF. The rotational constraint felt by solar convection ultimately hinges on the characteristic amplitude of deep convective flow speeds, and such flows are difficult to measure helioseismically. Those measurements of deep convective power which do exist disagree by orders of magnitude, and until this disagreement is resolved, we are left with the results of models and those less ambiguous measurements derived from surface observations of solar convection. I will present numerical results from a series of nonrotating and rotating convection simulations conducted in full 3-D spherical geometry. This presentation will focus on how convective spectra differ between the rotating and non-rotating models and how that behavior changes as simulations are pushed toward more turbulent and/or more rotationally-constrained regimes. I will discuss how the surface signature of rotationally-constrained interior convection might naturally lead to observable signatures in the surface convective pattern, such as supergranulation and a dearth of giant cells.

Scrutinizing human MHC polymorphism: Supertype analysis using Poisson-Boltzmann electrostatics and clustering.

PubMed

Mumtaz, Shahzad; Nabney, Ian T; Flower, Darren R

2017-10-01

Peptide-binding MHC proteins are thought the most variable across the human population; the extreme MHC polymorphism observed is functionally important and results from constrained divergent evolution. MHCs have vital functions in immunology and homeostasis: cell surface MHC class I molecules report cell status to CD8+ T cells, NKT cells and NK cells, thus playing key roles in pathogen defence, as well as mediating smell recognition, mate choice, Adverse Drug Reactions, and transplantation rejection. MHC peptide specificity falls into several supertypes exhibiting commonality of binding. It seems likely that other supertypes exist relevant to other functions. Since comprehensive experimental characterization is intractable, structure-based bioinformatics is the only viable solution. We modelled functional MHC proteins by homology and used calculated Poisson-Boltzmann electrostatics projected from the top surface of the MHC as multi-dimensional descriptors, analysing them using state-of-the-art dimensionality reduction techniques and clustering algorithms. We were able to recover the 3 MHC loci as separate clusters and identify clear sub-groups within them, vindicating unequivocally our choice of both data representation and clustering strategy. We expect this approach to make a profound contribution to the study of MHC polymorphism and its functional consequences, and, by extension, other burgeoning structural systems, such as GPCRs. Copyright © 2017 Elsevier Inc. All rights reserved.

Measuring Quasar Spin via X-ray Continuum Fitting

NASA Astrophysics Data System (ADS)

Jenkins, Matthew; Pooley, David; Rappaport, Saul; Steiner, Jack

2018-01-01

We have identified several quasars whose X-ray spectra appear very soft. When fit with power-law models, the best-fit indices are greater than 3. This is very suggestive of thermal disk emission, indicating that the X-ray spectrum is dominated by the disk component. Galactic black hole binaries in such states have been successfully fit with disk-blackbody models to constrain the inner radius, which also constrains the spin of the black hole. We have fit those models to XMM-Newton spectra of several of our identified soft X-ray quasars to place constraints on the spins of the supermassive black holes.

Modelling and Analysis of a Regenerative Fuel Cell Propulsion System for a High Altitude Long Endurance UAV

NASA Technical Reports Server (NTRS)

Simpson, Mike B.

2004-01-01

In the search to bridge current gaps in surveillance and communication technologies, a new type of, aircraft is currently undergoing design. The idea of a High Altitude Long Endurance (HALE) aircraft is already a few decades old, but has only recently become realizable. A relay and collector of information at altitudes of 65,000 feet and higher could greatly improve standards of data exchange, homeland security, and research of the air, land and sea. NASA, as a major force in propulsion research, is exploring methods of powering an autonomous aircraft for days, weeks, or even months without refueling. Such a task requires not only high energy density, but also the ability to make use of renewable energy sources to regenerate power. Hydrogen is one of the most energy dense fuels available. Fuel cells make use of hydrogen by harnessing the energy released as it combines with oxygen to produce electricity and water. Fuel cells are envisioned to occupy future propulsion systems in cooperation with solar cells where the photovoltaic arrays harness sunlight into power which can electrolize the water byproduct into reusable hydrogen and oxygen. Modeling this type of system requires adequate assumptions of support hardware and daily transients in operation. The performance of a regenerative fuel cell propulsion system lies in the flight characteristics (altitude, density, temperature, latitude, etc.). Each subsystem is defined by many parameters which can be varied across wide ranges. Statistical and probabilistic analyses bring forward a wealth of information that can be utilized in the design process. This is necessary since the required technologies are relatively young and barely, if yet, capable. Once the modeling is complete, a design space exploration of this highly constrained scenario can be utilized to find the optimal design. The model will become an interactive environment with which experiments and tests can be run. When linked

Application of a sparseness constraint in multivariate curve resolution - Alternating least squares.

PubMed

Hugelier, Siewert; Piqueras, Sara; Bedia, Carmen; de Juan, Anna; Ruckebusch, Cyril

2018-02-13

The use of sparseness in chemometrics is a concept that has increased in popularity. The advantage is, above all, a better interpretability of the results obtained. In this work, sparseness is implemented as a constraint in multivariate curve resolution - alternating least squares (MCR-ALS), which aims at reproducing raw (mixed) data by a bilinear model of chemically meaningful profiles. In many cases, the mixed raw data analyzed are not sparse by nature, but their decomposition profiles can be, as it is the case in some instrumental responses, such as mass spectra, or in concentration profiles linked to scattered distribution maps of powdered samples in hyperspectral images. To induce sparseness in the constrained profiles, one-dimensional and/or two-dimensional numerical arrays can be fitted using a basis of Gaussian functions with a penalty on the coefficients. In this work, a least squares regression framework with L 0 -norm penalty is applied. This L 0 -norm penalty constrains the number of non-null coefficients in the fit of the array constrained without having an a priori on the number and their positions. It has been shown that the sparseness constraint induces the suppression of values linked to uninformative channels and noise in MS spectra and improves the location of scattered compounds in distribution maps, resulting in a better interpretability of the constrained profiles. An additional benefit of the sparseness constraint is a lower ambiguity in the bilinear model, since the major presence of null coefficients in the constrained profiles also helps to limit the solutions for the profiles in the counterpart matrix of the MCR bilinear model. Copyright © 2017 Elsevier B.V. All rights reserved.

Invariant TAD Boundaries Constrain Cell-Type-Specific Looping Interactions between Promoters and Distal Elements around the CFTR Locus

PubMed Central

Smith, Emily M.; Lajoie, Bryan R.; Jain, Gaurav; Dekker, Job

2016-01-01

Three-dimensional genome structure plays an important role in gene regulation. Globally, chromosomes are organized into active and inactive compartments while, at the gene level, looping interactions connect promoters to regulatory elements. Topologically associating domains (TADs), typically several hundred kilobases in size, form an intermediate level of organization. Major questions include how TADs are formed and how they are related to looping interactions between genes and regulatory elements. Here we performed a focused 5C analysis of a 2.8 Mb chromosome 7 region surrounding CFTR in a panel of cell types. We find that the same TAD boundaries are present in all cell types, indicating that TADs represent a universal chromosome architecture. Furthermore, we find that these TAD boundaries are present irrespective of the expression and looping of genes located between them. In contrast, looping interactions between promoters and regulatory elements are cell-type specific and occur mostly within TADs. This is exemplified by the CFTR promoter that in different cell types interacts with distinct sets of distal cell-type-specific regulatory elements that are all located within the same TAD. Finally, we find that long-range associations between loci located in different TADs are also detected, but these display much lower interaction frequencies than looping interactions within TADs. Interestingly, interactions between TADs are also highly cell-type-specific and often involve loci clustered around TAD boundaries. These data point to key roles of invariant TAD boundaries in constraining as well as mediating cell-type-specific long-range interactions and gene regulation. PMID:26748519

Constrained Adherable Area of Nanotopographic Surfaces Promotes Cell Migration through the Regulation of Focal Adhesion via Focal Adhesion Kinase/Rac1 Activation.

PubMed

Lim, Jiwon; Choi, Andrew; Kim, Hyung Woo; Yoon, Hyungjun; Park, Sang Min; Tsai, Chia-Hung Dylan; Kaneko, Makoto; Kim, Dong Sung

2018-05-02

Cell migration is crucial in physiological and pathological processes such as embryonic development and wound healing; such migration is strongly guided by the surrounding nanostructured extracellular matrix. Previous studies have extensively studied the cell migration on anisotropic nanotopographic surfaces; however, only a few studies have reported cell migration on isotropic nanotopographic surfaces. We herein, for the first time, propose a novel concept of adherable area on cell migration using isotropic nanopore surfaces with sufficient nanopore depth by adopting a high aspect ratio. As the pore size of the nanopore surface was controlled to 200, 300, and 400 nm in a fixed center-to-center distance of 480 nm, it produced 86, 68, and 36% of adherable area, respectively, on the fabricated surface. A meticulous investigation of the cell migration in response to changes in the constrained adherable area of the nanotopographic surface showed 1.4-, 1.5-, and 1.6-fold increase in migration speeds and a 1.4-, 2-, and 2.5-fold decrease in the number of focal adhesions as the adherable area was decreased to 86, 68, and 36%, respectively. Furthermore, a strong activation of FAK/Rac1 signaling was observed to be involved in the promoted cell migration. These results suggest that the reduced adherable area promotes cell migration through decreasing the FA formation, which in turn upregulates FAK/Rac1 activation. The findings in this study can be utilized to control the cell migration behaviors, which is a powerful tool in the research fields involving cell migration such as promoting wound healing and tissue repair.

An adaptive finite element method for the inequality-constrained Reynolds equation

NASA Astrophysics Data System (ADS)

Gustafsson, Tom; Rajagopal, Kumbakonam R.; Stenberg, Rolf; Videman, Juha

2018-07-01

We present a stabilized finite element method for the numerical solution of cavitation in lubrication, modeled as an inequality-constrained Reynolds equation. The cavitation model is written as a variable coefficient saddle-point problem and approximated by a residual-based stabilized method. Based on our recent results on the classical obstacle problem, we present optimal a priori estimates and derive novel a posteriori error estimators. The method is implemented as a Nitsche-type finite element technique and shown in numerical computations to be superior to the usually applied penalty methods.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jennings, Elise; Wechsler, Risa H.

We present the nonlinear 2D galaxy power spectrum, P(k, µ), in redshift space, measured from the Dark Sky simulations, using galaxy catalogs constructed with both halo occupation distribution and subhalo abundance matching methods, chosen to represent an intermediate redshift sample of luminous red galaxies. We find that the information content in individual µ (cosine of the angle to the line of sight) bins is substantially richer then multipole moments, and show that this can be used to isolate the impact of nonlinear growth and redshift space distortion (RSD) effects. Using the µ < 0.2 simulation data, which we show ismore » not impacted by RSD effects, we can successfully measure the nonlinear bias to an accuracy of ~ 5% at k < 0.6hMpc-1 . This use of individual µ bins to extract the nonlinear bias successfully removes a large parameter degeneracy when constraining the linear growth rate of structure. We carry out a joint parameter estimation, using the low µ simulation data to constrain the nonlinear bias, and µ > 0.2 to constrain the growth rate and show that f can be constrained to ~ 26(22)% to a kmax < 0.4(0.6)hMpc-1 from clustering alone using a simple dispersion model, for a range of galaxy models. Our analysis of individual µ bins also reveals interesting physical effects which arise simply from different methods of populating halos with galaxies. We also find a prominent turnaround scale, at which RSD damping effects are greater then the nonlinear growth, which differs not only for each µ bin but also for each galaxy model. These features may provide unique signatures which could be used to shed light on the galaxy–dark matter connection. Furthermore, the idea of separating nonlinear growth and RSD effects making use of the full information in the 2D galaxy power spectrum yields significant improvements in constraining cosmological parameters and may be a promising probe of galaxy formation models.« less

Disentangling Redshift-Space Distortions and Nonlinear Bias using the 2D Power Spectrum

DOE PAGES

Jennings, Elise; Wechsler, Risa H.

2015-08-07

We present the nonlinear 2D galaxy power spectrum, P(k, µ), in redshift space, measured from the Dark Sky simulations, using galaxy catalogs constructed with both halo occupation distribution and subhalo abundance matching methods, chosen to represent an intermediate redshift sample of luminous red galaxies. We find that the information content in individual µ (cosine of the angle to the line of sight) bins is substantially richer then multipole moments, and show that this can be used to isolate the impact of nonlinear growth and redshift space distortion (RSD) effects. Using the µ < 0.2 simulation data, which we show ismore » not impacted by RSD effects, we can successfully measure the nonlinear bias to an accuracy of ~ 5% at k < 0.6hMpc-1 . This use of individual µ bins to extract the nonlinear bias successfully removes a large parameter degeneracy when constraining the linear growth rate of structure. We carry out a joint parameter estimation, using the low µ simulation data to constrain the nonlinear bias, and µ > 0.2 to constrain the growth rate and show that f can be constrained to ~ 26(22)% to a kmax < 0.4(0.6)hMpc-1 from clustering alone using a simple dispersion model, for a range of galaxy models. Our analysis of individual µ bins also reveals interesting physical effects which arise simply from different methods of populating halos with galaxies. We also find a prominent turnaround scale, at which RSD damping effects are greater then the nonlinear growth, which differs not only for each µ bin but also for each galaxy model. These features may provide unique signatures which could be used to shed light on the galaxy–dark matter connection. Furthermore, the idea of separating nonlinear growth and RSD effects making use of the full information in the 2D galaxy power spectrum yields significant improvements in constraining cosmological parameters and may be a promising probe of galaxy formation models.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haywood, Jim M.; Jones, Andy; Dunstone, Nick

Despite the fact that the southern hemisphere contains a far greater proportion of dark ocean than the northern hemisphere, the total amount of sunlight reflected from the hemispheres is equal. However, the majority of climate models do not adequately represent this equivalence. Here we examine the impact of equilibrating hemispheric albedos by various idealised methods in a comprehensive coupled climate model and find significant improvements in what have been considered longstanding and apparently intractable model biases. Monsoon precipitation biases almost vanish over all continental land areas, the penetration of monsoon rainfall across the Sahel and the west African monsoon “jump”more » become well represented, and indicators of hurricane frequency are significantly improved. The results appear not to be model specific, implying that hemispheric albedo equivalence may provide a fundamental constraint for climate models that must be satisfied if the dynamics driving these processes, in particular the strength of the Hadley cell, are to be adequately represented. Cross-equatorial energy transport is implicated as a crucial component that must be accurately modelled in coupled general circulation models. The results also suggest that the commonly used practice of prescribing sea-surface temperatures in models provides a less accurate represention of precipitation than constraining the hemispheric albedos.« less

Systems and Photosystems: Cellular Limits of Autotrophic Productivity in Cyanobacteria

PubMed Central

Burnap, Robert L.

2014-01-01

Recent advances in the modeling of microbial growth and metabolism have shown that growth rate critically depends upon the optimal allocation of finite proteomic resources among different cellular functions and that modeling growth rates becomes more realistic with the explicit accounting for the costs of macromolecular synthesis, most importantly, protein expression. The “proteomic constraint” is considered together with its application to understanding photosynthetic microbial growth. The central hypothesis is that physical limits of cellular space (and corresponding solvation capacity) in conjunction with cell surface-to-volume ratios represent the underlying constraints on the maximal rate of autotrophic microbial growth. The limitation of cellular space thus constrains the size the total complement of macromolecules, dissolved ions, and metabolites. To a first approximation, the upper limit in the cellular amount of the total proteome is bounded this space limit. This predicts that adaptation to osmotic stress will result in lower maximal growth rates due to decreased cellular concentrations of core metabolic proteins necessary for cell growth owing the accumulation of compatible osmolytes, as surmised previously. The finite capacity of membrane and cytoplasmic space also leads to the hypothesis that the species-specific differences in maximal growth rates likely reflect differences in the allocation of space to niche-specific proteins with the corresponding diminution of space devoted to other functions including proteins of core autotrophic metabolism, which drive cell reproduction. An optimization model for autotrophic microbial growth, the autotrophic replicator model, was developed based upon previous work investigating heterotrophic growth. The present model describes autotrophic growth in terms of the allocation protein resources among core functional groups including the photosynthetic electron transport chain, light-harvesting antennae, and the ribosome groups. PMID:25654078

Optical diagnostics of osteoblast cells and osteogenic drug screening

NASA Astrophysics Data System (ADS)

Kolanti, Elayaraja; Veerla, Sarath C.; Khajuria, Deepak K.; Roy Mahapatra, D.

2016-02-01

Microfluidic device based diagnostics involving optical fibre path, in situ imaging and spectroscopy are gaining importance due to recent advances in diagnostics instrumentation and methods, besides other factors such as low amount of reagent required for analysis, short investigation times, and potential possibilities to replace animal model based study in near future. It is possible to grow and monitor tissues in vitro in microfluidic lab-on-chip. It may become a transformative way of studying how cells interact with drugs, pathogens and biomaterials in physiologically relevant microenvironments. To a large extent, progress in developing clinically viable solutions has been constrained because of (i) contradiction between in vitro and in vivo results and (ii) animal model based and clinical studies which is very expensive. Our study here aims to evaluate the usefulness of microfluidic device based 3D tissue growth and monitoring approach to better emulate physiologically and clinically relevant microenvironments in comparison to conventional in vitro 2D culture. Moreover, the microfluidic methodology permits precise high-throughput investigations through real-time imaging while using very small amounts of reagents and cells. In the present study, we report on the details of an osteoblast cell based 3D microfluidic platform which we employ for osteogenic drug screening. The drug formulation is functionalized with fluorescence and other biomarkers for imaging and spectroscopy, respectively. Optical fibre coupled paths are used to obtain insight regarding the role of stress/flow pressure fluctuation and nanoparticle-drug concentration on the osteoblast growth and osteogenic properties of bone.

High resolution near on-axis digital holography using constrained optimization approach with faster convergence

NASA Astrophysics Data System (ADS)

Pandiyan, Vimal Prabhu; Khare, Kedar; John, Renu

2017-09-01

A constrained optimization approach with faster convergence is proposed to recover the complex object field from a near on-axis digital holography (DH). We subtract the DC from the hologram after recording the object beam and reference beam intensities separately. The DC-subtracted hologram is used to recover the complex object information using a constrained optimization approach with faster convergence. The recovered complex object field is back propagated to the image plane using the Fresnel back-propagation method. The results reported in this approach provide high-resolution images compared with the conventional Fourier filtering approach and is 25% faster than the previously reported constrained optimization approach due to the subtraction of two DC terms in the cost function. We report this approach in DH and digital holographic microscopy using the U.S. Air Force resolution target as the object to retrieve the high-resolution image without DC and twin image interference. We also demonstrate the high potential of this technique in transparent microelectrode patterned on indium tin oxide-coated glass, by reconstructing a high-resolution quantitative phase microscope image. We also demonstrate this technique by imaging yeast cells.

Mesenchymal precursor cells maintain the differentiation and proliferation potentials of breast epithelial cells

PubMed Central

2014-01-01

Introduction Stromal-epithelial interactions play a fundamental role in tissue homeostasis, controlling cell proliferation and differentiation. Not surprisingly, aberrant stromal-epithelial interactions contribute to malignancies. Studies of the cellular and molecular mechanisms underlying these interactions require ex vivo experimental model systems that recapitulate the complexity of human tissue without compromising the differentiation and proliferation potentials of human primary cells. Methods We isolated and characterized human breast epithelial and mesenchymal precursors from reduction mammoplasty tissue and tagged them with lentiviral vectors. We assembled heterotypic co-cultures and compared mesenchymal and epithelial cells to cells in corresponding monocultures by analyzing growth, differentiation potentials, and gene expression profiles. Results We show that heterotypic culture of non-immortalized human primary breast epithelial and mesenchymal precursors maintains their proliferation and differentiation potentials and constrains their growth. We further describe the gene expression profiles of stromal and epithelial cells in co-cultures and monocultures and show increased expression of the tumor growth factor beta (TGFβ) family member inhibin beta A (INHBA) in mesenchymal cells grown as co-cultures compared with monocultures. Notably, overexpression of INHBA in mesenchymal cells increases colony formation potential of epithelial cells, suggesting that it contributes to the dynamic reciprocity between breast mesenchymal and epithelial cells. Conclusions The described heterotypic co-culture system will prove useful for further characterization of the molecular mechanisms mediating interactions between human normal or neoplastic breast epithelial cells and the stroma, and will provide a framework to test the relevance of the ever-increasing number of oncogenomic alterations identified in human breast cancer. PMID:24916766

Constraining the braneworld with gravitational wave observations.

PubMed

McWilliams, Sean T

2010-04-09

Some braneworld models may have observable consequences that, if detected, would validate a requisite element of string theory. In the infinite Randall-Sundrum model (RS2), the AdS radius of curvature, l, of the extra dimension supports a single bound state of the massless graviton on the brane, thereby reproducing Newtonian gravity in the weak-field limit. However, using the AdS/CFT correspondence, it has been suggested that one possible consequence of RS2 is an enormous increase in Hawking radiation emitted by black holes. We utilize this possibility to derive two novel methods for constraining l via gravitational wave measurements. We show that the EMRI event rate detected by LISA can constrain l at the approximately 1 microm level for optimal cases, while the observation of a single galactic black hole binary with LISA results in an optimal constraint of l < or = 5 microm.

Constraining the Braneworld with Gravitational Wave Observations

NASA Technical Reports Server (NTRS)

McWilliams, Sean T.

2011-01-01

Some braneworld models may have observable consequences that, if detected, would validate a requisite element of string theory. In the infinite Randall-Sundrum model (RS2), the AdS radius of curvature, L, of the extra dimension supports a single bound state of the massless graviton on the brane, thereby reproducing Newtonian gravity in the weak-field limit. However, using the AdS/CFT correspondence, it has been suggested that one possible consequence of RS2 is an enormous increase in Hawking radiation emitted by black holes. We utilize this possibility to derive two novel methods for constraining L via gravitational wave measurements. We show that the EMRI event rate detected by LISA can constrain L at the approximately 1 micron level for optimal cases, while the observation of a single galactic black hole binary with LISA results in an optimal constraint of L less than or equal to 5 microns.

Analytical Dynamics and Nonrigid Spacecraft Simulation

NASA Technical Reports Server (NTRS)

Likins, P. W.

1974-01-01

Application to the simulation of idealized spacecraft are considered both for multiple-rigid-body models and for models consisting of combination of rigid bodies and elastic bodies, with the elastic bodies being defined either as continua, as finite-element systems, or as a collection of given modal data. Several specific examples are developed in detail by alternative methods of analytical mechanics, and results are compared to a Newton-Euler formulation. The following methods are developed from d'Alembert's principle in vector form: (1) Lagrange's form of d'Alembert's principle for independent generalized coordinates; (2) Lagrange's form of d'Alembert's principle for simply constrained systems; (3) Kane's quasi-coordinate formulation of D'Alembert's principle; (4) Lagrange's equations for independent generalized coordinates; (5) Lagrange's equations for simply constrained systems; (6) Lagrangian quasi-coordinate equations (or the Boltzmann-Hamel equations); (7) Hamilton's equations for simply constrained systems; and (8) Hamilton's equations for independent generalized coordinates.

CONORBIT: constrained optimization by radial basis function interpolation in trust regions

DOE PAGES

Regis, Rommel G.; Wild, Stefan M.

2016-09-26

Here, this paper presents CONORBIT (CONstrained Optimization by Radial Basis function Interpolation in Trust regions), a derivative-free algorithm for constrained black-box optimization where the objective and constraint functions are computationally expensive. CONORBIT employs a trust-region framework that uses interpolating radial basis function (RBF) models for the objective and constraint functions, and is an extension of the ORBIT algorithm. It uses a small margin for the RBF constraint models to facilitate the generation of feasible iterates, and extensive numerical tests confirm that such a margin is helpful in improving performance. CONORBIT is compared with other algorithms on 27 test problems, amore » chemical process optimization problem, and an automotive application. Numerical results show that CONORBIT performs better than COBYLA, a sequential penalty derivative-free method, an augmented Lagrangian method, a direct search method, and another RBF-based algorithm on the test problems and on the automotive application.« less

Structural and parameteric uncertainty quantification in cloud microphysics parameterization schemes

NASA Astrophysics Data System (ADS)

van Lier-Walqui, M.; Morrison, H.; Kumjian, M. R.; Prat, O. P.; Martinkus, C.

2017-12-01

Atmospheric model parameterization schemes employ approximations to represent the effects of unresolved processes. These approximations are a source of error in forecasts, caused in part by considerable uncertainty about the optimal value of parameters within each scheme -- parameteric uncertainty. Furthermore, there is uncertainty regarding the best choice of the overarching structure of the parameterization scheme -- structrual uncertainty. Parameter estimation can constrain the first, but may struggle with the second because structural choices are typically discrete. We address this problem in the context of cloud microphysics parameterization schemes by creating a flexible framework wherein structural and parametric uncertainties can be simultaneously constrained. Our scheme makes no assuptions about drop size distribution shape or the functional form of parametrized process rate terms. Instead, these uncertainties are constrained by observations using a Markov Chain Monte Carlo sampler within a Bayesian inference framework. Our scheme, the Bayesian Observationally-constrained Statistical-physical Scheme (BOSS), has flexibility to predict various sets of prognostic drop size distribution moments as well as varying complexity of process rate formulations. We compare idealized probabilistic forecasts from versions of BOSS with varying levels of structural complexity. This work has applications in ensemble forecasts with model physics uncertainty, data assimilation, and cloud microphysics process studies.

The highest-frequency kHz QPOs in neutron star low mass X-ray binaries

NASA Astrophysics Data System (ADS)

van Doesburgh, Marieke; van der Klis, Michiel; Morsink, Sharon M.

2018-05-01

We investigate the detections with RXTE of the highest-frequency kHz QPOs previously reported in six neutron star (NS) low mass X-ray binaries. We find that the highest-frequency kHz QPO detected in 4U 0614+09 has a 1267 Hz 3σ confidence lower limit on its centroid frequency. This is the highest such limit reported to date, and of direct physical interest as it can be used to constrain QPO models and the supranuclear density equation of state (EoS). We compare our measured frequencies to maximum orbital frequencies predicted in full GR using models of rotating neutron stars with a number of different modern EoS and show that these can accommodate the observed QPO frequencies. Orbital motion constrained by NS and ISCO radii is therefore a viable explanation of these QPOs. In the most constraining case of 4U 0614+09 we find the NS mass must be M<2.1 M⊙. From our measured QPO frequencies we can constrain the NS radii for five of the six sources we studied to narrow ranges (±0.1-0.7 km) different for each source and each EoS.

Tribology studies of the natural knee using an animal model in a new whole joint natural knee simulator.

PubMed

Liu, Aiqin; Jennings, Louise M; Ingham, Eileen; Fisher, John

2015-09-18

The successful development of early-stage cartilage and meniscus repair interventions in the knee requires biomechanical and biotribological understanding of the design of the therapeutic interventions and their tribological function in the natural joint. The aim of this study was to develop and validate a porcine knee model using a whole joint knee simulator for investigation of the tribological function and biomechanical properties of the natural knee, which could then be used to pre-clinically assess the tribological performance of cartilage and meniscal repair interventions prior to in vivo studies. The tribological performance of standard artificial bearings in terms of anterior-posterior (A/P) shear force was determined in a newly developed six degrees of freedom tribological joint simulator. The porcine knee model was then developed and the tribological properties in terms of shear force measurements were determined for the first time for three levels of biomechanical constraints including A/P constrained, spring force semi-constrained and A/P unconstrained conditions. The shear force measurements showed higher values under the A/P constrained condition (predominantly sliding motion) compared to the A/P unconstrained condition (predominantly rolling motion). This indicated that the shear force simulation model was able to differentiate between tribological behaviours when the femoral and tibial bearing was constrained to slide or/and roll. Therefore, this porcine knee model showed the potential capability to investigate the effect of knee structural, biomechanical and kinematic changes, as well as different cartilage substitution therapies on the tribological function of natural knee joints. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

First Top-Down Estimates of Anthropogenic NOx Emissions Using High-Resolution Airborne Remote Sensing Observations

NASA Astrophysics Data System (ADS)

Souri, Amir H.; Choi, Yunsoo; Pan, Shuai; Curci, Gabriele; Nowlan, Caroline R.; Janz, Scott J.; Kowalewski, Matthew G.; Liu, Junjie; Herman, Jay R.; Weinheimer, Andrew J.

2018-03-01

A number of satellite-based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high-quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NOx emissions in the Houston-Galveston-Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO2 profiles from a high-resolution regional model (1 × 1 km2) constrained by P-3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO2 absorption line, and (iii) high-resolution surface albedo constrained by ground-based spectrometers. We characterize errors in the GCAS NO2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 1015 molecules cm-2. On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2-50% reduction in polluted areas, partly counterbalancing the well-documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top-down emissions.

Application of High Resolution Air-Borne Remote Sensing Observations for Monitoring NOx Emissions

NASA Astrophysics Data System (ADS)

Souri, A.; Choi, Y.; Pan, S.; Curci, G.; Janz, S. J.; Kowalewski, M. G.; Liu, J.; Herman, J. R.; Weinheimer, A. J.

2017-12-01

Nitrogen oxides (NOx=NO+NO2) are one of the air pollutants, responsible for the formation of tropospheric ozone, acid rain and particulate nitrate. The anthropogenic NOx emissions are commonly estimated based on bottom-up inventories which are complicated by many potential sources of error. One way to improve the emission inventories is to use relevant observations to constrain them. Fortunately, Nitrogen dioxide (NO2) is one of the most successful detected species from remote sensing. Although many studies have shown the capability of using space-borne remote sensing observations for monitoring emissions, the insufficient sample number and footprint of current measurements have introduced a burden to constrain emissions at fine scales. Promisingly, there are several air-borne sensors collected for NASA's campaigns providing high spatial resolution of NO2 columns. Here, we use the well-characterized NO2 columns from the Airborne Compact Atmospheric Mapper (ACAM) onboard NASA's B200 aircraft into a 1×1 km regional model to constrain anthropogenic NOx emissions in the Houston-Galveston-Brazoria area. Firstly, in order to incorporate the data, we convert the NO2 slant column densities to vertical ones using a joint of a radiative transfer model and the 1x1 km regional model constrained by P3-B aircraft measurements. After conducting an inverse modeling method using the Kalman filter, we find the ACAM observations are resourceful at mitigating the overprediction of model in reproducing NO2 on regular days. Moreover, the ACAM provides a unique opportunity to detect an anomaly in emissions leading to strong air quality degradation that is lacking in previous works. Our study provides convincing evidence that future geostationary satellites with high spatial and temporal resolutions will give us insights into uncertainties associated with the emissions at regional scales.

Source model for the Copahue volcano magma plumbing system constrained by InSAR surface deformation observations

NASA Astrophysics Data System (ADS)

Lundgren, Paul; Nikkhoo, Mehdi; Samsonov, Sergey V.; Milillo, Pietro; Gil-Cruz, Fernando; Lazo, Jonathan

2017-07-01

Copahue volcano straddling the edge of the Agrio-Caviahue caldera along the Chile-Argentina border in the southern Andes has been in unrest since inflation began in late 2011. We constrain Copahue's source models with satellite and airborne interferometric synthetic aperture radar (InSAR) deformation observations. InSAR time series from descending track RADARSAT-2 and COSMO-SkyMed data span the entire inflation period from 2011 to 2016, with their initially high rates of 12 and 15 cm/yr, respectively, slowing only slightly despite ongoing small eruptions through 2016. InSAR ascending and descending track time series for the 2013-2016 time period constrain a two-source compound dislocation model, with a rate of volume increase of 13 × 106 m3/yr. They consist of a shallow, near-vertical, elongated source centered at 2.5 km beneath the summit and a deeper, shallowly plunging source centered at 7 km depth connecting the shallow source to the deeper caldera. The deeper source is located directly beneath the volcano tectonic seismicity with the lower bounds of the seismicity parallel to the plunge of the deep source. InSAR time series also show normal fault offsets on the NE flank Copahue faults. Coulomb stress change calculations for right-lateral strike slip (RLSS), thrust, and normal receiver faults show positive values in the north caldera for both RLSS and normal faults, suggesting that northward trending seismicity and Copahue fault motion within the caldera are caused by the modeled sources. Together, the InSAR-constrained source model and the seismicity suggest a deep conduit or transfer zone where magma moves from the central caldera to Copahue's upper edifice.

The shape and motion of gas bubbles in a liquid flowing through a thin annulus

NASA Astrophysics Data System (ADS)

Lei, Qinghua; Xie, Zhihua; Pavlidis, Dimitrios; Salinas, Pablo; Veltin, Jeremy; Muggeridge, Ann; Pain, Christopher C.; Matar, Omar K.; Jackson, Matthew; Arland, Kristine; Gyllensten, Atle

2017-11-01

We study the shape and motion of gas bubbles in a liquid flowing through a horizontal or slightly-inclined thin annulus. Experimental data show that in the horizontal annulus, bubbles develop a unique ``tadpole'' shape with an elliptical cap and a highly-stretched tail, due to the confinement between the closely-spaced channel walls. As the annulus is inclined, the bubble tail tends to decrease in length, while the geometry of the cap remains almost invariant. To model the bubble evolution, the thin annulus is conceptualised as a ``Hele-Shaw'' cell in a curvilinear space. The three-dimensional flow within the cell is represented by a gap-averaged, two-dimensional model constrained by the same dimensionless quantities. The complex bubble dynamics are solved using a mixed control-volume finite-element method combined with interface-capturing and mesh adaptation techniques. A close match to the experimental data is achieved, both qualitatively and quantitatively, by the numerical simulations. The mechanism for the elliptical cap formation is interpreted based on an analogous irrotational flow field around a circular cylinder. The shape regimes of bubbles flowing through the thin annulus are further explored based on the simulation results. Funding from STATOIL gratefully acknowledged.

Power transduction of actin filaments ratcheting in vitro against a load.

PubMed

Démoulin, Damien; Carlier, Marie-France; Bibette, Jérôme; Baudry, Jean

2014-12-16

The actin cytoskeleton has the unique capability of producing pushing forces at the leading edge of motile cells without the implication of molecular motors. This phenomenon has been extensively studied theoretically, and molecular models, including the widely known Brownian ratchet, have been proposed. However, supporting experimental work is lacking, due in part to hardly accessible molecular length scales. We designed an experiment to directly probe the mechanism of force generation in a setup where a population of actin filaments grows against a load applied by magnetic microparticles. The filaments, arranged in stiff bundles by fascin, are constrained to point toward the applied load. In this protrusion-like geometry, we are able to directly measure the velocity of filament elongation and its dependence on force. Using numerical simulations, we provide evidence that our experimental data are consistent with a Brownian ratchet-based model. We further demonstrate the existence of a force regime far below stalling where the mechanical power transduced by the ratcheting filaments to the load is maximal. The actin machinery in migrating cells may tune the number of filaments at the leading edge to work in this force regime.

Degenerate Pax2 and Senseless binding motifs improve detection of low-affinity sites required for enhancer specificity

PubMed Central

Zandvakili, Arya; Campbell, Ian; Weirauch, Matthew T.

2018-01-01

Cells use thousands of regulatory sequences to recruit transcription factors (TFs) and produce specific transcriptional outcomes. Since TFs bind degenerate DNA sequences, discriminating functional TF binding sites (TFBSs) from background sequences represents a significant challenge. Here, we show that a Drosophila regulatory element that activates Epidermal Growth Factor signaling requires overlapping, low-affinity TFBSs for competing TFs (Pax2 and Senseless) to ensure cell- and segment-specific activity. Testing available TF binding models for Pax2 and Senseless, however, revealed variable accuracy in predicting such low-affinity TFBSs. To better define parameters that increase accuracy, we developed a method that systematically selects subsets of TFBSs based on predicted affinity to generate hundreds of position-weight matrices (PWMs). Counterintuitively, we found that degenerate PWMs produced from datasets depleted of high-affinity sequences were more accurate in identifying both low- and high-affinity TFBSs for the Pax2 and Senseless TFs. Taken together, these findings reveal how TFBS arrangement can be constrained by competition rather than cooperativity and that degenerate models of TF binding preferences can improve identification of biologically relevant low affinity TFBSs. PMID:29617378

Using Parameter Constraints to Choose State Structures in Cost-Effectiveness Modelling.

PubMed

Thom, Howard; Jackson, Chris; Welton, Nicky; Sharples, Linda

2017-09-01

This article addresses the choice of state structure in a cost-effectiveness multi-state model. Key model outputs, such as treatment recommendations and prioritisation of future research, may be sensitive to state structure choice. For example, it may be uncertain whether to consider similar disease severities or similar clinical events as the same state or as separate states. Standard statistical methods for comparing models require a common reference dataset but merging states in a model aggregates the data, rendering these methods invalid. We propose a method that involves re-expressing a model with merged states as a model on the larger state space in which particular transition probabilities, costs and utilities are constrained to be equal between states. This produces a model that gives identical estimates of cost effectiveness to the model with merged states, while leaving the data unchanged. The comparison of state structures can be achieved by comparing maximised likelihoods or information criteria between constrained and unconstrained models. We can thus test whether the costs and/or health consequences for a patient in two states are the same, and hence if the states can be merged. We note that different structures can be used for rates, costs and utilities, as appropriate. We illustrate our method with applications to two recent models evaluating the cost effectiveness of prescribing anti-depressant medications by depression severity and the cost effectiveness of diagnostic tests for coronary artery disease. State structures in cost-effectiveness models can be compared using standard methods to compare constrained and unconstrained models.

How alive is constrained SUSY really?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bechtle, Philip; Desch, Klaus; Dreiner, Herbert K.

2016-05-31

Constrained supersymmetric models like the CMSSM might look less attractive nowadays because of fine tuning arguments. They also might look less probable in terms of Bayesian statistics. The question how well the model under study describes the data, however, is answered by frequentist p-values. Thus, for the first time, we calculate a p-value for a supersymmetric model by performing dedicated global toy fits. We combine constraints from low-energy and astrophysical observables, Higgs boson mass and rate measurements as well as the non-observation of new physics in searches for supersymmetry at the LHC. Furthermore, using the framework Fittino, we perform globalmore » fits of the CMSSM to the toy data and find that this model is excluded at the 90% confidence level.« less

Constraining f(T) teleparallel gravity by big bang nucleosynthesis: f(T) cosmology and BBN.

PubMed

Capozziello, S; Lambiase, G; Saridakis, E N

2017-01-01

We use Big Bang Nucleosynthesis (BBN) observational data on the primordial abundance of light elements to constrain f ( T ) gravity. The three most studied viable f ( T ) models, namely the power law, the exponential and the square-root exponential are considered, and the BBN bounds are adopted in order to extract constraints on their free parameters. For the power-law model, we find that the constraints are in agreement with those obtained using late-time cosmological data. For the exponential and the square-root exponential models, we show that for reliable regions of parameters space they always satisfy the BBN bounds. We conclude that viable f ( T ) models can successfully satisfy the BBN constraints.

Exploring stellar evolution with gravitational-wave observations

NASA Astrophysics Data System (ADS)

Dvorkin, Irina; Uzan, Jean-Philippe; Vangioni, Elisabeth; Silk, Joseph

2018-05-01

Recent detections of gravitational waves from merging binary black holes opened new possibilities to study the evolution of massive stars and black hole formation. In particular, stellar evolution models may be constrained on the basis of the differences in the predicted distribution of black hole masses and redshifts. In this work we propose a framework that combines galaxy and stellar evolution models and use it to predict the detection rates of merging binary black holes for various stellar evolution models. We discuss the prospects of constraining the shape of the time delay distribution of merging binaries using just the observed distribution of chirp masses. Finally, we consider a generic model of primordial black hole formation and discuss the possibility of distinguishing it from stellar-origin black holes.

Missile Guidance Law Based on Robust Model Predictive Control Using Neural-Network Optimization.

PubMed

Li, Zhijun; Xia, Yuanqing; Su, Chun-Yi; Deng, Jun; Fu, Jun; He, Wei

2015-08-01

In this brief, the utilization of robust model-based predictive control is investigated for the problem of missile interception. Treating the target acceleration as a bounded disturbance, novel guidance law using model predictive control is developed by incorporating missile inside constraints. The combined model predictive approach could be transformed as a constrained quadratic programming (QP) problem, which may be solved using a linear variational inequality-based primal-dual neural network over a finite receding horizon. Online solutions to multiple parametric QP problems are used so that constrained optimal control decisions can be made in real time. Simulation studies are conducted to illustrate the effectiveness and performance of the proposed guidance control law for missile interception.

Pulsed Excimer Laser Processing for Cost-Effective Solar Cells

NASA Technical Reports Server (NTRS)

Wong, D.

1985-01-01

Residual lattice damage by 5 keV ion implantation and surface flaws induced by wafer cleaning are proven to affect the V sub oc more adversely for laser annealed cells than conventional thermal diffusion. However, an alternative, molecular implantation of molecular species holds potential. The first experimental results are encouraging. The lack of a commercially available mass analyzed implantation with low energy, high fluence ions is constraining.

Probing Models of Dark Matter and the Early Universe

NASA Astrophysics Data System (ADS)

Orlofsky, Nicholas David

This thesis discusses models for dark matter (DM) and their behavior in the early universe. An important question is how phenomenological probes can directly search for signals of DM today. Another topic of investigation is how the DM and other processes in the early universe must evolve. Then, astrophysical bounds on early universe dynamics can constrain DM. We will consider these questions in the context of three classes of DM models--weakly interacting massive particles (WIMPs), axions, and primordial black holes (PBHs). Starting with WIMPs, we consider models where the DM is charged under the electroweak gauge group of the Standard Model. Such WIMPs, if generated by a thermal cosmological history, are constrained by direct detection experiments. To avoid present or near-future bounds, the WIMP model or cosmological history must be altered in some way. This may be accomplished by the inclusion of new states that coannihilate with the WIMP or a period of non-thermal evolution in the early universe. Future experiments are likely to probe some of these altered scenarios, and a non-observation would require a high degree of tuning in some of the model parameters in these scenarios. Next, axions, as light pseudo-Nambu-Goldstone bosons, are susceptible to quantum fluctuations in the early universe that lead to isocurvature perturbations, which are constrained by observations of the cosmic microwave background (CMB). We ask what it would take to allow axion models in the face of these strong CMB bounds. We revisit models where inflationary dynamics modify the axion potential and discuss how isocurvature bounds can be relaxed, elucidating the difficulties in these constructions. Avoiding disruption of inflationary dynamics provides important limits on the parameter space. Finally, PBHs have received interest in part due to observations by LIGO of merging black hole binaries. We ask how these PBHs could arise through inflationary models and investigate the opportunity for corroboration through experimental probes of gravitational waves at pulsar timing arrays. We provide examples of theories that are already ruled out, theories that will soon be probed, and theories that will not be tested in the foreseeable future. The models that are most strongly constrained are those with relatively broad primordial power spectra.

Classification and Segmentation of Nanoparticle Diffusion Trajectories in Cellular Micro Environments

PubMed Central

Kroll, Alexandra; Haramagatti, Chandrashekara R.; Lipinski, Hans-Gerd; Wiemann, Martin

2017-01-01

Darkfield and confocal laser scanning microscopy both allow for a simultaneous observation of live cells and single nanoparticles. Accordingly, a characterization of nanoparticle uptake and intracellular mobility appears possible within living cells. Single particle tracking allows to measure the size of a diffusing particle close to a cell. However, within the more complex system of a cell’s cytoplasm normal, confined or anomalous diffusion together with directed motion may occur. In this work we present a method to automatically classify and segment single trajectories into their respective motion types. Single trajectories were found to contain more than one motion type. We have trained a random forest with 9 different features. The average error over all motion types for synthetic trajectories was 7.2%. The software was successfully applied to trajectories of positive controls for normal- and constrained diffusion. Trajectories captured by nanoparticle tracking analysis served as positive control for normal diffusion. Nanoparticles inserted into a diblock copolymer membrane was used to generate constrained diffusion. Finally we segmented trajectories of diffusing (nano-)particles in V79 cells captured with both darkfield- and confocal laser scanning microscopy. The software called “TraJClassifier” is freely available as ImageJ/Fiji plugin via https://git.io/v6uz2. PMID:28107406

Constrained release of lamina-associated enhancers and genes from the nuclear envelope during T-cell activation facilitates their association in chromosome compartments

PubMed Central

de las Heras, Jose I.; Czapiewski, Rafal; Sivakumar, Aishwarya; Kerr, Alastair R.W.; Schirmer, Eric C.

2017-01-01

The 3D organization of the genome changes concomitantly with expression changes during hematopoiesis and immune activation. Studies have focused either on lamina-associated domains (LADs) or on topologically associated domains (TADs), defined by preferential local chromatin interactions, and chromosome compartments, defined as higher-order interactions between TADs sharing functionally similar states. However, few studies have investigated how these affect one another. To address this, we mapped LADs using Lamin B1–DamID during Jurkat T-cell activation, finding significant genome reorganization at the nuclear periphery dominated by release of loci frequently important for T-cell function. To assess how these changes at the nuclear periphery influence wider genome organization, our DamID data sets were contrasted with TADs and compartments. Features of specific repositioning events were then tested by fluorescence in situ hybridization during T-cell activation. First, considerable overlap between TADs and LADs was observed with the TAD repositioning as a unit. Second, A1 and A2 subcompartments are segregated in 3D space through differences in proximity to LADs along chromosomes. Third, genes and a putative enhancer in LADs that were released from the periphery during T-cell activation became preferentially associated with A2 subcompartments and were constrained to the relative proximity of the lamina. Thus, lamina associations influence internal nuclear organization, and changes in LADs during T-cell activation may provide an important additional mode of gene regulation. PMID:28424353

Super earth interiors and validity of Birch's Law for ultra-high pressure metals and ionic solids

NASA Astrophysics Data System (ADS)

Ware, Lucas Andrew

2015-01-01

Super Earths, recently detected by the Kepler Mission, expand the ensemble of known terrestrial planets beyond our Solar System's limited group. Birch's Law and velocity-density systematics have been crucial in constraining our knowledge of the composition of Earth's mantle and core. Recently published static diamond anvil cell experimental measurements of sound velocities in iron, a key deep element in most super Earth models, are inconsistent with each other with regard to the validity of Birch's Law. We examine the range of validity of Birch's Law for several metallic elements, including iron, and ionic solids shocked with a two-stage light gas gun into the ultra-high pressure, temperature fluid state and make comparisons to the recent static data.

Derivation of the Energy and Flux Morphology in an Aurora Observed at Midlatitude Using Multispectral Imaging

NASA Astrophysics Data System (ADS)

Aryal, Saurav; Finn, Susanna C.; Hewawasam, Kuravi; Maguire, Ryan; Geddes, George; Cook, Timothy; Martel, Jason; Baumgardner, Jeffrey L.; Chakrabarti, Supriya

2018-05-01

Energies and fluxes of precipitating electrons in an aurora over Lowell, MA on 22-23 June 2015 were derived based on simultaneous, high-resolution (≈ 0.02 nm) brightness measurements of N2+ (427.8 nm, blue line), OI (557.7 nm, green line), and OI (630.0 nm, red line) emissions. The electron energies and energy fluxes as a function of time and look direction were derived by nonlinear minimization of model predictions with respect to the measurements. Three different methods were compared; in the first two methods, we constrained the modeled brightnesses and brightness ratios, respectively, with measurements to simultaneously derive energies and fluxes. Then we used a hybrid method where we constrained the individual modeled brightness ratios with measurements to derive energies and then constrained modeled brightnesses with measurements to derive fluxes. Derived energy, assuming Maxwellian distribution, during this storm ranged from 109 to 262 eV and the total energy flux ranged from 0.8 to 2.2 ergs·cm-2·s-1. This approach provides a way to estimate energies and energy fluxes of the precipitating electrons using simultaneous multispectral measurements.

Macroscopically constrained Wang-Landau method for systems with multiple order parameters and its application to drawing complex phase diagrams

NASA Astrophysics Data System (ADS)

Chan, C. H.; Brown, G.; Rikvold, P. A.

2017-05-01

A generalized approach to Wang-Landau simulations, macroscopically constrained Wang-Landau, is proposed to simulate the density of states of a system with multiple macroscopic order parameters. The method breaks a multidimensional random-walk process in phase space into many separate, one-dimensional random-walk processes in well-defined subspaces. Each of these random walks is constrained to a different set of values of the macroscopic order parameters. When the multivariable density of states is obtained for one set of values of fieldlike model parameters, the density of states for any other values of these parameters can be obtained by a simple transformation of the total system energy. All thermodynamic quantities of the system can then be rapidly calculated at any point in the phase diagram. We demonstrate how to use the multivariable density of states to draw the phase diagram, as well as order-parameter probability distributions at specific phase points, for a model spin-crossover material: an antiferromagnetic Ising model with ferromagnetic long-range interactions. The fieldlike parameters in this model are an effective magnetic field and the strength of the long-range interaction.

Constrained motion model of mobile robots and its applications.

PubMed

Zhang, Fei; Xi, Yugeng; Lin, Zongli; Chen, Weidong

2009-06-01

Target detecting and dynamic coverage are fundamental tasks in mobile robotics and represent two important features of mobile robots: mobility and perceptivity. This paper establishes the constrained motion model and sensor model of a mobile robot to represent these two features and defines the k -step reachable region to describe the states that the robot may reach. We show that the calculation of the k-step reachable region can be reduced from that of 2(k) reachable regions with the fixed motion styles to k + 1 such regions and provide an algorithm for its calculation. Based on the constrained motion model and the k -step reachable region, the problems associated with target detecting and dynamic coverage are formulated and solved. For target detecting, the k-step detectable region is used to describe the area that the robot may detect, and an algorithm for detecting a target and planning the optimal path is proposed. For dynamic coverage, the k-step detected region is used to represent the area that the robot has detected during its motion, and the dynamic-coverage strategy and algorithm are proposed. Simulation results demonstrate the efficiency of the coverage algorithm in both convex and concave environments.

A synoptic view of the Third Uniform California Earthquake Rupture Forecast (UCERF3)

USGS Publications Warehouse

Field, Edward; Jordan, Thomas H.; Page, Morgan T.; Milner, Kevin R.; Shaw, Bruce E.; Dawson, Timothy E.; Biasi, Glenn; Parsons, Thomas E.; Hardebeck, Jeanne L.; Michael, Andrew J.; Weldon, Ray; Powers, Peter; Johnson, Kaj M.; Zeng, Yuehua; Bird, Peter; Felzer, Karen; van der Elst, Nicholas; Madden, Christopher; Arrowsmith, Ramon; Werner, Maximillan J.; Thatcher, Wayne R.

2017-01-01

Probabilistic forecasting of earthquake‐producing fault ruptures informs all major decisions aimed at reducing seismic risk and improving earthquake resilience. Earthquake forecasting models rely on two scales of hazard evolution: long‐term (decades to centuries) probabilities of fault rupture, constrained by stress renewal statistics, and short‐term (hours to years) probabilities of distributed seismicity, constrained by earthquake‐clustering statistics. Comprehensive datasets on both hazard scales have been integrated into the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3). UCERF3 is the first model to provide self‐consistent rupture probabilities over forecasting intervals from less than an hour to more than a century, and it is the first capable of evaluating the short‐term hazards that result from multievent sequences of complex faulting. This article gives an overview of UCERF3, illustrates the short‐term probabilities with aftershock scenarios, and draws some valuable scientific conclusions from the modeling results. In particular, seismic, geologic, and geodetic data, when combined in the UCERF3 framework, reject two types of fault‐based models: long‐term forecasts constrained to have local Gutenberg–Richter scaling, and short‐term forecasts that lack stress relaxation by elastic rebound.

Auditory hair cell centrioles undergo confined Brownian motion throughout the developmental migration of the kinocilium.

PubMed

Lepelletier, Léa; de Monvel, Jacques Boutet; Buisson, Johanna; Desdouets, Chantal; Petit, Christine

2013-07-02

Planar polarization of the forming hair bundle, the mechanosensory antenna of auditory hair cells, depends on the poorly characterized center-to-edge displacement of a primary cilium, the kinocilium, at their apical surface. Taking advantage of the gradient of hair cell differentiation along the cochlea, we reconstituted a map of the kinocilia displacements in the mouse embryonic cochlea. We then developed a cochlear organotypic culture and video-microscopy approach to monitor the movements of the kinocilium basal body (mother centriole) and its daughter centriole, which we analyzed using particle tracking and modeling. We found that both hair cell centrioles undergo confined Brownian movements around their equilibrium positions, under the apparent constraint of a radial restoring force of ∼0.1 pN. This magnitude depended little on centriole position, suggesting nonlinear interactions with constraining, presumably cytoskeletal elements. The only dynamic change observed during the period of kinocilium migration was a doubling of the centrioles' confinement area taking place early in the process. It emerges from these static and dynamic observations that kinocilia migrate gradually in parallel with the organization of hair cells into rows during cochlear neuroepithelium extension. Analysis of the confined motion of hair cell centrioles under normal and pathological conditions should help determine which structures contribute to the restoring force exerting on them. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Auditory Hair Cell Centrioles Undergo Confined Brownian Motion Throughout the Developmental Migration of the Kinocilium

PubMed Central

Lepelletier, Léa; de Monvel, Jacques Boutet; Buisson, Johanna; Desdouets, Chantal; Petit, Christine

2013-01-01

Planar polarization of the forming hair bundle, the mechanosensory antenna of auditory hair cells, depends on the poorly characterized center-to-edge displacement of a primary cilium, the kinocilium, at their apical surface. Taking advantage of the gradient of hair cell differentiation along the cochlea, we reconstituted a map of the kinocilia displacements in the mouse embryonic cochlea. We then developed a cochlear organotypic culture and video-microscopy approach to monitor the movements of the kinocilium basal body (mother centriole) and its daughter centriole, which we analyzed using particle tracking and modeling. We found that both hair cell centrioles undergo confined Brownian movements around their equilibrium positions, under the apparent constraint of a radial restoring force of ∼0.1 pN. This magnitude depended little on centriole position, suggesting nonlinear interactions with constraining, presumably cytoskeletal elements. The only dynamic change observed during the period of kinocilium migration was a doubling of the centrioles’ confinement area taking place early in the process. It emerges from these static and dynamic observations that kinocilia migrate gradually in parallel with the organization of hair cells into rows during cochlear neuroepithelium extension. Analysis of the confined motion of hair cell centrioles under normal and pathological conditions should help determine which structures contribute to the restoring force exerting on them. PMID:23823223

Learning to Model in Engineering

ERIC Educational Resources Information Center

Gainsburg, Julie

2013-01-01

Policymakers and education scholars recommend incorporating mathematical modeling into mathematics education. Limited implementation of modeling instruction in schools, however, has constrained research on how students learn to model, leaving unresolved debates about whether modeling should be reified and explicitly taught as a competence, whether…

Experimental Validation of a Thermoelastic Model for SMA Hybrid Composites

NASA Technical Reports Server (NTRS)

Turner, Travis L.

2001-01-01

This study presents results from experimental validation of a recently developed model for predicting the thermomechanical behavior of shape memory alloy hybrid composite (SMAHC) structures, composite structures with an embedded SMA constituent. The model captures the material nonlinearity of the material system with temperature and is capable of modeling constrained, restrained, or free recovery behavior from experimental measurement of fundamental engineering properties. A brief description of the model and analysis procedures is given, followed by an overview of a parallel effort to fabricate and characterize the material system of SMAHC specimens. Static and dynamic experimental configurations for the SMAHC specimens are described and experimental results for thermal post-buckling and random response are presented. Excellent agreement is achieved between the measured and predicted results, fully validating the theoretical model for constrained recovery behavior of SMAHC structures.

Using noble gas tracers to constrain a groundwater flow model with recharge elevations: A novel approach for mountainous terrain

USGS Publications Warehouse

Doyle, Jessica M.; Gleeson, Tom; Manning, Andrew H.; Mayer, K. Ulrich

2015-01-01

Environmental tracers provide information on groundwater age, recharge conditions, and flow processes which can be helpful for evaluating groundwater sustainability and vulnerability. Dissolved noble gas data have proven particularly useful in mountainous terrain because they can be used to determine recharge elevation. However, tracer-derived recharge elevations have not been utilized as calibration targets for numerical groundwater flow models. Herein, we constrain and calibrate a regional groundwater flow model with noble-gas-derived recharge elevations for the first time. Tritium and noble gas tracer results improved the site conceptual model by identifying a previously uncertain contribution of mountain block recharge from the Coast Mountains to an alluvial coastal aquifer in humid southwestern British Columbia. The revised conceptual model was integrated into a three-dimensional numerical groundwater flow model and calibrated to hydraulic head data in addition to recharge elevations estimated from noble gas recharge temperatures. Recharge elevations proved to be imperative for constraining hydraulic conductivity, recharge location, and bedrock geometry, and thus minimizing model nonuniqueness. Results indicate that 45% of recharge to the aquifer is mountain block recharge. A similar match between measured and modeled heads was achieved in a second numerical model that excludes the mountain block (no mountain block recharge), demonstrating that hydraulic head data alone are incapable of quantifying mountain block recharge. This result has significant implications for understanding and managing source water protection in recharge areas, potential effects of climate change, the overall water budget, and ultimately ensuring groundwater sustainability.

Multiple network-constrained regressions expand insights into influenza vaccination responses.

PubMed

Avey, Stefan; Mohanty, Subhasis; Wilson, Jean; Zapata, Heidi; Joshi, Samit R; Siconolfi, Barbara; Tsang, Sui; Shaw, Albert C; Kleinstein, Steven H

2017-07-15

Systems immunology leverages recent technological advancements that enable broad profiling of the immune system to better understand the response to infection and vaccination, as well as the dysregulation that occurs in disease. An increasingly common approach to gain insights from these large-scale profiling experiments involves the application of statistical learning methods to predict disease states or the immune response to perturbations. However, the goal of many systems studies is not to maximize accuracy, but rather to gain biological insights. The predictors identified using current approaches can be biologically uninterpretable or present only one of many equally predictive models, leading to a narrow understanding of the underlying biology. Here we show that incorporating prior biological knowledge within a logistic modeling framework by using network-level constraints on transcriptional profiling data significantly improves interpretability. Moreover, incorporating different types of biological knowledge produces models that highlight distinct aspects of the underlying biology, while maintaining predictive accuracy. We propose a new framework, Logistic Multiple Network-constrained Regression (LogMiNeR), and apply it to understand the mechanisms underlying differential responses to influenza vaccination. Although standard logistic regression approaches were predictive, they were minimally interpretable. Incorporating prior knowledge using LogMiNeR led to models that were equally predictive yet highly interpretable. In this context, B cell-specific genes and mTOR signaling were associated with an effective vaccination response in young adults. Overall, our results demonstrate a new paradigm for analyzing high-dimensional immune profiling data in which multiple networks encoding prior knowledge are incorporated to improve model interpretability. The R source code described in this article is publicly available at https://bitbucket.org/kleinstein/logminer . steven.kleinstein@yale.edu or stefan.avey@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Optimizing spatial and temporal constraints for cropland canopy water content retrieval through coupled radiative transfer model inversion

NASA Astrophysics Data System (ADS)

Boren, E. J.; Boschetti, L.; Johnson, D.

2017-12-01

Water plays a critical role in all plant physiological processes, including transpiration, photosynthesis, nutrient transportation, and maintenance of proper plant cell functions. Deficits in water content cause drought-induced stress conditions, such as constrained plant growth and cellular metabolism, while overabundance of water cause anoxic conditions which limit plant physiological processes and promote disease. Vegetation water content maps can provide agricultural producers key knowledge for improving production capacity and resiliency in agricultural systems while facilitating the ability to pinpoint, monitor, and resolve water scarcity issues. Radiative transfer model (RTM) inversion has been successfully applied to remotely sensed data to retrieve biophysical and canopy parameter estimates, including water content. The successful launch of the Landsat 8 Operational Land Imager (OLI) in 2012, Sentinel 2A Multispectral Instrument (MSI) in 2015, followed by Sentinel 2B in 2017, the systematic acquisition schedule and free data distribution policy provide the opportunity for water content estimation at a spatial and temporal scale that can meet the demands of potential operational users: combined, these polar-orbiting systems provide 10 m to 30 m multi-spectral global coverage up to every 3 days. The goal of the present research is to prototype the generation of a cropland canopy water content product, obtained from the newly developed Landsat 8 and Sentinel 2 atmospherically corrected HLS product, through the inversion of the leaf and canopy model PROSAIL5B. We assess the impact of a novel spatial and temporal stratification, where some parameters of the model are constrained by crop type and phenological phase, based on ancillary biophysical data, collected from various crop species grown in a controlled setting and under different water stress conditions. Canopy-level data, collected coincidently with satellite overpasses during four summer field campaigns in northern Idaho (2014 to 2017), are used to validate the results of the model inversion.

Advanced Multivariate Inversion Techniques for High Resolution 3D Geophysical Modeling (Invited)

NASA Astrophysics Data System (ADS)

Maceira, M.; Zhang, H.; Rowe, C. A.

2009-12-01

We focus on the development and application of advanced multivariate inversion techniques to generate a realistic, comprehensive, and high-resolution 3D model of the seismic structure of the crust and upper mantle that satisfies several independent geophysical datasets. Building on previous efforts of joint invesion using surface wave dispersion measurements, gravity data, and receiver functions, we have added a fourth dataset, seismic body wave P and S travel times, to the simultaneous joint inversion method. We present a 3D seismic velocity model of the crust and upper mantle of northwest China resulting from the simultaneous, joint inversion of these four data types. Surface wave dispersion measurements are primarily sensitive to seismic shear-wave velocities, but at shallow depths it is difficult to obtain high-resolution velocities and to constrain the structure due to the depth-averaging of the more easily-modeled, longer-period surface waves. Gravity inversions have the greatest resolving power at shallow depths, and they provide constraints on rock density variations. Moreover, while surface wave dispersion measurements are primarily sensitive to vertical shear-wave velocity averages, body wave receiver functions are sensitive to shear-wave velocity contrasts and vertical travel-times. Addition of the fourth dataset, consisting of seismic travel-time data, helps to constrain the shear wave velocities both vertically and horizontally in the model cells crossed by the ray paths. Incorporation of both P and S body wave travel times allows us to invert for both P and S velocity structure, capitalizing on empirical relationships between both wave types’ seismic velocities with rock densities, thus eliminating the need for ad hoc assumptions regarding the Poisson ratios. Our new tomography algorithm is a modification of the Maceira and Ammon joint inversion code, in combination with the Zhang and Thurber TomoDD (double-difference tomography) program.

Mitotic events in cerebellar granule progenitor cells that expand cerebellar surface area are critical for normal cerebellar cortical lamination in mice.

PubMed

Chang, Joshua C; Leung, Mark; Gokozan, Hamza Numan; Gygli, Patrick Edwin; Catacutan, Fay Patsy; Czeisler, Catherine; Otero, José Javier

2015-03-01

Late embryonic and postnatal cerebellar folial surface area expansion promotes cerebellar cortical cytoarchitectural lamination. We developed a streamlined sampling scheme to generate unbiased estimates of murine cerebellar surface area and volume using stereologic principles. We demonstrate that, during the proliferative phase of the external granular layer (EGL) and folial surface area expansion, EGL thickness does not change and thus is a topological proxy for progenitor self-renewal. The topological constraints indicate that, during proliferative phases, migration out of the EGL is balanced by self-renewal. Progenitor self-renewal must, therefore, include mitotic events yielding 2 cells in the same layer to increase surface area (β events) and mitotic events yielding 2 cells, with 1 cell in a superficial layer and 1 cell in a deeper layer (α events). As the cerebellum grows, therefore, β events lie upstream of α events. Using a mathematical model constrained by the measurements of volume and surface area, we could quantify intermitotic times for β events on a per-cell basis in postnatal mouse cerebellum. Furthermore, we found that loss of CCNA2, which decreases EGL proliferation and secondarily induces cerebellar cortical dyslamination, shows preserved α-type events. Thus, CCNA2-null cerebellar granule progenitor cells are capable of self-renewal of the EGL stem cell niche; this is concordant with prior findings of extensive apoptosis in CCNA2-null mice. Similar methodologies may provide another layer of depth to the interpretation of results from stereologic studies.

Constrained Total Energy Expenditure and Metabolic Adaptation to Physical Activity in Adult Humans.

PubMed

Pontzer, Herman; Durazo-Arvizu, Ramon; Dugas, Lara R; Plange-Rhule, Jacob; Bovet, Pascal; Forrester, Terrence E; Lambert, Estelle V; Cooper, Richard S; Schoeller, Dale A; Luke, Amy

2016-02-08

Current obesity prevention strategies recommend increasing daily physical activity, assuming that increased activity will lead to corresponding increases in total energy expenditure and prevent or reverse energy imbalance and weight gain [1-3]. Such Additive total energy expenditure models are supported by exercise intervention and accelerometry studies reporting positive correlations between physical activity and total energy expenditure [4] but are challenged by ecological studies in humans and other species showing that more active populations do not have higher total energy expenditure [5-8]. Here we tested a Constrained total energy expenditure model, in which total energy expenditure increases with physical activity at low activity levels but plateaus at higher activity levels as the body adapts to maintain total energy expenditure within a narrow range. We compared total energy expenditure, measured using doubly labeled water, against physical activity, measured using accelerometry, for a large (n = 332) sample of adults living in five populations [9]. After adjusting for body size and composition, total energy expenditure was positively correlated with physical activity, but the relationship was markedly stronger over the lower range of physical activity. For subjects in the upper range of physical activity, total energy expenditure plateaued, supporting a Constrained total energy expenditure model. Body fat percentage and activity intensity appear to modulate the metabolic response to physical activity. Models of energy balance employed in public health [1-3] should be revised to better reflect the constrained nature of total energy expenditure and the complex effects of physical activity on metabolic physiology. Copyright © 2016 Elsevier Ltd. All rights reserved.

CPMC-Lab: A MATLAB package for Constrained Path Monte Carlo calculations

NASA Astrophysics Data System (ADS)

Nguyen, Huy; Shi, Hao; Xu, Jie; Zhang, Shiwei

2014-12-01

We describe CPMC-Lab, a MATLAB program for the constrained-path and phaseless auxiliary-field Monte Carlo methods. These methods have allowed applications ranging from the study of strongly correlated models, such as the Hubbard model, to ab initio calculations in molecules and solids. The present package implements the full ground-state constrained-path Monte Carlo (CPMC) method in MATLAB with a graphical interface, using the Hubbard model as an example. The package can perform calculations in finite supercells in any dimensions, under periodic or twist boundary conditions. Importance sampling and all other algorithmic details of a total energy calculation are included and illustrated. This open-source tool allows users to experiment with various model and run parameters and visualize the results. It provides a direct and interactive environment to learn the method and study the code with minimal overhead for setup. Furthermore, the package can be easily generalized for auxiliary-field quantum Monte Carlo (AFQMC) calculations in many other models for correlated electron systems, and can serve as a template for developing a production code for AFQMC total energy calculations in real materials. Several illustrative studies are carried out in one- and two-dimensional lattices on total energy, kinetic energy, potential energy, and charge- and spin-gaps.

Self-organization of muscle cell structure and function.

PubMed

Grosberg, Anna; Kuo, Po-Ling; Guo, Chin-Lin; Geisse, Nicholas A; Bray, Mark-Anthony; Adams, William J; Sheehy, Sean P; Parker, Kevin Kit

2011-02-01

The organization of muscle is the product of functional adaptation over several length scales spanning from the sarcomere to the muscle bundle. One possible strategy for solving this multiscale coupling problem is to physically constrain the muscle cells in microenvironments that potentiate the organization of their intracellular space. We hypothesized that boundary conditions in the extracellular space potentiate the organization of cytoskeletal scaffolds for directed sarcomeregenesis. We developed a quantitative model of how the cytoskeleton of neonatal rat ventricular myocytes organizes with respect to geometric cues in the extracellular matrix. Numerical results and in vitro assays to control myocyte shape indicated that distinct cytoskeletal architectures arise from two temporally-ordered, organizational processes: the interaction between actin fibers, premyofibrils and focal adhesions, as well as cooperative alignment and parallel bundling of nascent myofibrils. Our results suggest that a hierarchy of mechanisms regulate the self-organization of the contractile cytoskeleton and that a positive feedback loop is responsible for initiating the break in symmetry, potentiated by extracellular boundary conditions, is required to polarize the contractile cytoskeleton.

Constrained Sintering in Fabrication of Solid Oxide Fuel Cells

PubMed Central

Lee, Hae-Weon; Park, Mansoo; Hong, Jongsup; Kim, Hyoungchul; Yoon, Kyung Joong; Son, Ji-Won; Lee, Jong-Ho; Kim, Byung-Kook

2016-01-01

Solid oxide fuel cells (SOFCs) are inevitably affected by the tensile stress field imposed by the rigid substrate during constrained sintering, which strongly affects microstructural evolution and flaw generation in the fabrication process and subsequent operation. In the case of sintering a composite cathode, one component acts as a continuous matrix phase while the other acts as a dispersed phase depending upon the initial composition and packing structure. The clustering of dispersed particles in the matrix has significant effects on the final microstructure, and strong rigidity of the clusters covering the entire cathode volume is desirable to obtain stable pore structure. The local constraints developed around the dispersed particles and their clusters effectively suppress generation of major process flaws, and microstructural features such as triple phase boundary and porosity could be readily controlled by adjusting the content and size of the dispersed particles. However, in the fabrication of the dense electrolyte layer via the chemical solution deposition route using slow-sintering nanoparticles dispersed in a sol matrix, the rigidity of the cluster should be minimized for the fine matrix to continuously densify, and special care should be taken in selecting the size of the dispersed particles to optimize the thermodynamic stability criteria of the grain size and film thickness. The principles of constrained sintering presented in this paper could be used as basic guidelines for realizing the ideal microstructure of SOFCs. PMID:28773795

Informing Aerosol Transport Models With Satellite Multi-Angle Aerosol Measurements

NASA Technical Reports Server (NTRS)

Limbacher, J.; Patadia, F.; Petrenko, M.; Martin, M. Val; Chin, M.; Gaitley, B.; Garay, M.; Kalashnikova, O.; Nelson, D.; Scollo, S.

2011-01-01

As the aerosol products from the NASA Earth Observing System's Multi-angle Imaging SpectroRadiometer (MISR) mature, we are placing greater focus on ways of using the aerosol amount and type data products, and aerosol plume heights, to constrain aerosol transport models. We have demonstrated the ability to map aerosol air-mass-types regionally, and have identified product upgrades required to apply them globally, including the need for a quality flag indicating the aerosol type information content, that varies depending upon retrieval conditions. We have shown that MISR aerosol type can distinguish smoke from dust, volcanic ash from sulfate and water particles, and can identify qualitative differences in mixtures of smoke, dust, and pollution aerosol components in urban settings. We demonstrated the use of stereo imaging to map smoke, dust, and volcanic effluent plume injection height, and the combination of MISR and MODIS aerosol optical depth maps to constrain wildfire smoke source strength. This talk will briefly highlight where we stand on these application, with emphasis on the steps we are taking toward applying the capabilities toward constraining aerosol transport models, planet-wide.

[Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].

PubMed

Wang, Cong; Du, Hua-qiang; Zhou, Guo-mo; Xu, Xiao-jun; Sun, Shao-bo; Gao, Guo-long

2015-05-01

This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest.

Style consistent classification of isogenous patterns.

PubMed

Sarkar, Prateek; Nagy, George

2005-01-01

In many applications of pattern recognition, patterns appear together in groups (fields) that have a common origin. For example, a printed word is usually a field of character patterns printed in the same font. A common origin induces consistency of style in features measured on patterns. The features of patterns co-occurring in a field are statistically dependent because they share the same, albeit unknown, style. Style constrained classifiers achieve higher classification accuracy by modeling such dependence among patterns in a field. Effects of style consistency on the distributions of field-features (concatenation of pattern features) can be modeled by hierarchical mixtures. Each field derives from a mixture of styles, while, within a field, a pattern derives from a class-style conditional mixture of Gaussians. Based on this model, an optimal style constrained classifier processes entire fields of patterns rendered in a consistent but unknown style. In a laboratory experiment, style constrained classification reduced errors on fields of printed digits by nearly 25 percent over singlet classifiers. Longer fields favor our classification method because they furnish more information about the underlying style.

An interleukin 13 receptor α 2–specific peptide homes to human Glioblastoma multiforme xenografts

PubMed Central

Pandya, Hetal; Gibo, Denise M.; Garg, Shivank; Kridel, Steven; Debinski, Waldemar

2012-01-01

Interleukin 13 receptor α 2 (IL-13Rα2) is a glioblastoma multiforme (GBM)–associated plasma membrane receptor, a brain tumor of dismal prognosis. Here, we isolated peptide ligands for IL-13Rα2 with use of a cyclic disulphide-constrained heptapeptide phages display library and 2 in vitro biopanning schemes with GBM cells that do (G26-H2 and SnB19-pcDNA cells) or do not (G26-V2 and SnB19-asIL-13Rα2 cells) over-express IL-13Rα2. We identified 3 peptide phages that bind to IL-13Rα2 in cellular and protein assays. One of the 3 peptide phages, termed Pep-1, bound to IL-13Rα2 with the highest specificity, surprisingly, also in a reducing environment. Pep-1 was thus synthesized and further analyzed in both linear and disulphide-constrained forms. The linear peptide bound to IL-13Rα2 more avidly than did the disulphide-constrained form and was efficiently internalized by IL-13Rα2–expressing GBM cells. The native ligand, IL-13, did not compete for the Pep-1 binding to the receptor and vice versa in any of the assays, indicating that the peptide might be binding to a site on the receptor different from the native ligand. Furthermore, we demonstrated by noninvasive near infrared fluorescence imaging in nude mice that Pep-1 binds and homes to both subcutaneous and orthotopic human GBM xenografts expressing IL-13Rα2 when injected by an intravenous route. Thus, we identified a linear heptapeptide specific for the IL-13Rα2 that is capable of crossing the blood-brain tumor barrier and homing to tumors. Pep-1 can be further developed for various applications in cancer and/or inflammatory diseases. PMID:21946118

Constraints on Lunar Structure from Combined Geochemical, Mineralogical, and Geophysical modeling

NASA Astrophysics Data System (ADS)

Bremner, P. M.; Fuqua, H.; Mallik, A.; Diamond, M. R.; Lock, S. J.; Panovska, S.; Nishikawa, Y.; Jiménez-Pérez, H.; Shahar, A.; Panero, W. R.; Lognonne, P. H.; Faul, U.

2016-12-01

The internal physical and geochemical structure of the Moon is still poorly constrained. Here, we take a multidisciplinary approach to attempt to constrain key parameters of the lunar structure. We use an ensemble of 1-D lunar compositional models with chemically and mineralogically distinct layers, and forward calculated physical parameters, in order to constrain the internal structure. We consider both a chemically well-mixed model with uniform bulk composition, and a chemically stratified model that includes a mantle with preserved mineralogical stratigraphy from magma ocean crystallization. Additionally, we use four different lunar temperature profiles that span the range of proposed selenotherms, giving eight separate sets of lunar models. In each set, we employed a grid search and a differential evolution genetic search algorithm to extensively explore model space, where the thickness of individual compositional layers was varied. In total, we forward calculated over one hundred thousand lunar models. It has been proposed that a dense, partially molten layer exists at the CMB to explain the lack of observed far-side deep moonquakes, the observation of reflected seismic phases from deep moonquakes, and enhanced tidal dissipation. However, subsequent models have proposed that these observables can be explained in other ways. In this study, using a variety of modeling techniques, we find that such a layer may have been formed by overturn of an ilmenite-rich layer, formed after the crystallization of a magma ocean. We therefore include a denser layer (modeled as an ilmenite-rich layer) at both the top and bottom of the lunar mantle in our models. For each set of models, we find models that explain the observed lunar mass and moment of inertia. We find that only a narrow range of core radii are consistent with the mass and moment of inertia constraints. Furthermore, in the chemically well-mixed models, we find that a dense layer is required in the upper mantle to meet the moment of inertia requirement. In no set of models is the mass of the lower dense layer well constrained. For the models that fit the observed mass and moment of inertia, we calculated 1-D seismic velocity profiles, the majority of which compare well with those determined by inverting the Apollo seismic data (Garcia et al., 2011 and Weber et al., 2011).

A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0)

NASA Astrophysics Data System (ADS)

Bloom, A. Anthony; Bowman, Kevin W.; Lee, Meemong; Turner, Alexander J.; Schroeder, Ronny; Worden, John R.; Weidner, Richard; McDonald, Kyle C.; Jacob, Daniel J.

2017-06-01

Wetland emissions remain one of the principal sources of uncertainty in the global atmospheric methane (CH4) budget, largely due to poorly constrained process controls on CH4 production in waterlogged soils. Process-based estimates of global wetland CH4 emissions and their associated uncertainties can provide crucial prior information for model-based top-down CH4 emission estimates. Here we construct a global wetland CH4 emission model ensemble for use in atmospheric chemical transport models (WetCHARTs version 1.0). Our 0.5° × 0.5° resolution model ensemble is based on satellite-derived surface water extent and precipitation reanalyses, nine heterotrophic respiration simulations (eight carbon cycle models and a data-constrained terrestrial carbon cycle analysis) and three temperature dependence parameterizations for the period 2009-2010; an extended ensemble subset based solely on precipitation and the data-constrained terrestrial carbon cycle analysis is derived for the period 2001-2015. We incorporate the mean of the full and extended model ensembles into GEOS-Chem and compare the model against surface measurements of atmospheric CH4; the model performance (site-level and zonal mean anomaly residuals) compares favourably against published wetland CH4 emissions scenarios. We find that uncertainties in carbon decomposition rates and the wetland extent together account for more than 80 % of the dominant uncertainty in the timing, magnitude and seasonal variability in wetland CH4 emissions, although uncertainty in the temperature CH4 : C dependence is a significant contributor to seasonal variations in mid-latitude wetland CH4 emissions. The combination of satellite, carbon cycle models and temperature dependence parameterizations provides a physically informed structural a priori uncertainty that is critical for top-down estimates of wetland CH4 fluxes. Specifically, our ensemble can provide enhanced information on the prior CH4 emission uncertainty and the error covariance structure, as well as a means for using posterior flux estimates and their uncertainties to quantitatively constrain the biogeochemical process controls of global wetland CH4 emissions.

Observational Role of Dark Matter in f(R) Models for Structure Formation

NASA Astrophysics Data System (ADS)

Verma, Murli Manohar; Yadav, Bal Krishna

The fixed points for the dynamical system in the phase space have been calculated with dark matter in the f(R) gravity models. The stability conditions of these fixed points are obtained in the ongoing accelerated phase of the universe, and the values of the Hubble parameter and Ricci scalar are obtained for various evolutionary stages of the universe. We present a range of some modifications of general relativistic action consistent with the ΛCDM model. We elaborate upon the fact that the upcoming cosmological observations would further constrain the bounds on the possible forms of f(R) with greater precision that could in turn constrain the search for dark matter in colliders.

Multiple R&D projects scheduling optimization with improved particle swarm algorithm.

PubMed

Liu, Mengqi; Shan, Miyuan; Wu, Juan

2014-01-01

For most enterprises, in order to win the initiative in the fierce competition of market, a key step is to improve their R&D ability to meet the various demands of customers more timely and less costly. This paper discusses the features of multiple R&D environments in large make-to-order enterprises under constrained human resource and budget, and puts forward a multi-project scheduling model during a certain period. Furthermore, we make some improvements to existed particle swarm algorithm and apply the one developed here to the resource-constrained multi-project scheduling model for a simulation experiment. Simultaneously, the feasibility of model and the validity of algorithm are proved in the experiment.

A cost-constrained model of strategic service quality emphasis in nursing homes.

PubMed

Davis, M A; Provan, K G

1996-02-01

This study employed structural equation modeling to test the relationship between three aspects of the environmental context of nursing homes; Medicaid dependence, ownership status, and market demand, and two basic strategic orientations: low cost and differentiation based on service quality emphasis. Hypotheses were proposed and tested against data collected from a sample of nursing homes operating in a single state. Because of the overwhelming importance of cost control in the nursing home industry, a cost constrained strategy perspective was supported. Specifically, while the three contextual variables had no direct effect on service quality emphasis, the entire model was supported when cost control orientation was introduced as a mediating variable.

Two tradeoffs between economy and reliability in loss of load probability constrained unit commitment

NASA Astrophysics Data System (ADS)

Liu, Yuan; Wang, Mingqiang; Ning, Xingyao

2018-02-01

Spinning reserve (SR) should be scheduled considering the balance between economy and reliability. To address the computational intractability cursed by the computation of loss of load probability (LOLP), many probabilistic methods use simplified formulations of LOLP to improve the computational efficiency. Two tradeoffs embedded in the SR optimization model are not explicitly analyzed in these methods. In this paper, two tradeoffs including primary tradeoff and secondary tradeoff between economy and reliability in the maximum LOLP constrained unit commitment (UC) model are explored and analyzed in a small system and in IEEE-RTS System. The analysis on the two tradeoffs can help in establishing new efficient simplified LOLP formulations and new SR optimization models.

Glassy behaviour in simple kinetically constrained models: topological networks, lattice analogues and annihilation-diffusion

NASA Astrophysics Data System (ADS)

Sherrington, David; Davison, Lexie; Buhot, Arnaud; Garrahan, Juan P.

2002-02-01

We report a study of a series of simple model systems with only non-interacting Hamiltonians, and hence simple equilibrium thermodynamics, but with constrained dynamics of a type initially suggested by foams and idealized covalent glasses. We demonstrate that macroscopic dynamical features characteristic of real and more complex model glasses, such as two-time decays in energy and auto-correlation functions, arise from the dynamics and we explain them qualitatively and quantitatively in terms of annihilation-diffusion concepts and theory. The comparison is with strong glasses. We also consider fluctuation-dissipation relations and demonstrate subtleties of interpretation. We find no FDT breakdown when the correct normalization is chosen.

Determination of the dispersion constant in a constrained vapor bubble thermosyphon

NASA Technical Reports Server (NTRS)

Dasgupta, Sunando; Plawsky, Joel L.; Wayner, Peter C., Jr.

1995-01-01

The isothermal profiles of the extended meniscus in a quartz cuvette were measured in a gravitational field using an image analyzing interferometer which is based on computer enhanced video microscopy of the naturally occurring interference fringes. The experimental results for heptane and pentane menisci were analyzed using the extended Young Laplace Equation. These isothermal results characterized the interfacial force field in-siru at the start of the heat transfer experiments by quantifying the dispersion constant, which is a function of the liquid-solid system and cleaning procedures. The experimentally obtained values of the disjoining pressure and the dispersion constants were compared to that predicted from the DLP theory and good agreements were obtained. The measurements are critical to the subsequent non-isothermal experiments because one of the major variables in the heat sink capability of the Constrained Vapor Bubble Thermosyphon, CVBT, is the dispersion constant. In all previous studies of micro heat pipes the value of the dispersion constant has been 'estimated'. One of the major advantages of the current glass cell is the ability to view the extended meniscus at all times. Experimentally, we find that the extended Young-Laplace Equation is an excellent model for the force field at the solid-liquid-vapor interfaces.

Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics

PubMed Central

Noecker, Cecilia; Schaefer, Krista; Zaccheo, Kelly; Yang, Yiding; Day, Judy; Ganusov, Vitaly V.

2015-01-01

Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1–2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the “standard” mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results suggest that, in order to appropriately model early HIV/SIV dynamics, additional factors must be considered in the model development. These may include variability in monkey susceptibility to infection, within-host competition between different viruses for target cells at the initial site of virus replication in the mucosa, innate immune response, and possibly the inclusion of several different tissue compartments. The sobering news is that while an increase in model complexity is needed to explain the available experimental data, testing and rejection of more complex models may require more quantitative data than is currently available. PMID:25781919

Neonatal rat heart cells cultured in simulated microgravity

NASA Technical Reports Server (NTRS)

Akins, Robert E.; Schroedl, Nancy A.; Gonda, Steve R.; Hartzell, Charles R.

1994-01-01

In vitro characteristics of cardiac cells cultured in simulated microgravity are reported. Tissue culture methods performed at unit gravity constrain cells to propagate, differentiate, and interact in a two dimensional (2D) plane. Neonatal rat cardiac cells in 2D culture organize predominantly as bundles of cardiomyocytes with the intervening areas filled by non-myocyte cell types. Such cardiac cell cultures respond predictably to the addition of exogenous compounds, and in many ways they represent an excellent in vitro model system. The gravity-induced 2D organization of the cells, however, does not accurately reflect the distribution of cells in the intact tissue. We have begun characterizations of a three-dimensional (3D) culturing system designed to mimic microgravity. The NASA designed High-Aspect-Ratio-Vessel (HARV) bioreactors provide a low shear environment which allows cells to be cultured in static suspension. HARV-3D cultures were prepared on microcarrier beads and compared to control-2D cultures using a combination of microscopic and biochemical techniques. Both systems were uniformly inoculated and medium exchanged at standard intervals. Cells in control cultures adhered to the polystyrene surface of the tissue culture dishes and exhibited typical 2D organization. Cells in cultured in HARV's adhered to microcarrier beads, the beads aggregated into defined clusters containing 8 to 15 beads per cluster, and the clusters exhibited distinct 3D layers: myocytes and fibroblasts appeared attached to the surfaces of beads and were overlaid by an outer cell type. In addition, cultures prepared in HARV's using alternative support matrices also displayed morphological formations not seen in control cultures. Generally, the cells prepared in HARV and control cultures were similar, however, the dramatic alterations in 3D organization recommend the HARV as an ideal vessel for the generation of tissue-like organizations of cardiac cells in simulated microgravity.

Neonatal rat heart cells cultured in simulated microgravity

NASA Technical Reports Server (NTRS)

Akins, R. E.; Schroedl, N. A.; Gonda, S. R.; Hartzell, C. R.

1997-01-01

In vitro characteristics of cardiac cells cultured in simulated microgravity are reported. Tissue culture methods performed at unit gravity constrain cells to propagate, differentiate, and interact in a two-dimensional (2D) plane. Neonatal rat cardiac cells in 2D culture organize predominantly as bundles of cardiomyocytes with the intervening areas filled by nonmyocyte cell types. Such cardiac cell cultures respond predictably to the addition of exogenous compounds, and in many ways they represent an excellent in vitro model system. The gravity-induced 2D organization of the cells, however, does not accurately reflect the distribution of cells in the intact tissue. We have begun characterizations of a three-dimensional (3D) culturing system designed to mimic microgravity. The NASA-designed High-Aspect Ratio Vessel (HARV) bioreactors provide a low shear environment that allows cells to be cultured in static suspension. HARV-3D cultures were prepared on microcarrier beads and compared to control-2D cultures using a combination of microscopic and biochemical techniques. Both systems were uniformly inoculated and medium exchanged at standard intervals. Cells in control cultures adhered to the polystyrene surface of the tissue culture dishes and exhibited typical 2D organization. Cells cultured in HARVs adhered to microcarrier beads, the beads aggregated into defined clusters containing 8 to 15 beads per cluster, and the clusters exhibited distinct 3D layers: myocytes and fibroblasts appeared attached to the surfaces of beads and were overlaid by an outer cell type. In addition, cultures prepared in HARVs using alternative support matrices also displayed morphological formations not seen in control cultures. Generally, the cells prepared in HARV and control cultures were similar; however, the dramatic alterations in 3D organization recommend the HARV as an ideal vessel for the generation of tissuelike organization of cardiac cells in vitro.

Vibration control of beams using stand-off layer damping: finite element modeling and experiments

NASA Astrophysics Data System (ADS)

Chaudry, A.; Baz, A.

2006-03-01

Damping treatments with stand-off layer (SOL) have been widely accepted as an attractive alternative to conventional constrained layer damping (CLD) treatments. Such an acceptance stems from the fact that the SOL, which is simply a slotted spacer layer sandwiched between the viscoelastic layer and the base structure, acts as a strain magnifier that considerably amplifies the shear strain and hence the energy dissipation characteristics of the viscoelastic layer. Accordingly, more effective vibration suppression can be achieved by using SOL as compared to employing CLD. In this paper, a comprehensive finite element model of the stand-off layer constrained damping treatment is developed. The model accounts for the geometrical and physical parameters of the slotted SOL, the viscoelastic, layer the constraining layer, and the base structure. The predictions of the model are validated against the predictions of a distributed transfer function model and a model built using a commercial finite element code (ANSYS). Furthermore, the theoretical predictions are validated experimentally for passive SOL treatments of different configurations. The obtained results indicate a close agreement between theory and experiments. Furthermore, the obtained results demonstrate the effectiveness of the CLD with SOL in enhancing the energy dissipation as compared to the conventional CLD. Extension of the proposed one-dimensional CLD with SOL to more complex structures is a natural extension to the present study.

Performance Analysis of BDS Medium-Long Baseline RTK Positioning Using an Empirical Troposphere Model.

PubMed

Shu, Bao; Liu, Hui; Xu, Longwei; Qian, Chuang; Gong, Xiaopeng; An, Xiangdong

2018-04-14

For GPS medium-long baseline real-time kinematic (RTK) positioning, the troposphere parameter is introduced along with coordinates, and the model is ill-conditioned due to its strong correlation with the height parameter. For BeiDou Navigation Satellite System (BDS), additional difficulties occur due to its special satellite constellation. In fact, relative zenith troposphere delay (RZTD) derived from high-precision empirical zenith troposphere models can be introduced. Thus, the model strength can be improved, which is also called the RZTD-constrained RTK model. In this contribution, we first analyze the factors affecting the precision of BDS medium-long baseline RTK; thereafter, 15 baselines ranging from 38 km to 167 km in different troposphere conditions are processed to assess the performance of RZTD-constrained RTK. Results show that the troposphere parameter is difficult to distinguish from the height component, even with long time filtering for BDS-only RTK. Due to the lack of variation in geometry for the BDS geostationary Earth orbit satellite, the long convergence time of ambiguity parameters may reduce the height precision of GPS/BDS-combined RTK in the initial period. When the RZTD-constrained model was used in BDS and GPS/BDS-combined situations compared with the traditional RTK, the standard deviation of the height component for the fixed solution was reduced by 52.4% and 34.0%, respectively.

Performance Analysis of BDS Medium-Long Baseline RTK Positioning Using an Empirical Troposphere Model

PubMed Central

Liu, Hui; Xu, Longwei; Qian, Chuang; Gong, Xiaopeng; An, Xiangdong

2018-01-01

For GPS medium-long baseline real-time kinematic (RTK) positioning, the troposphere parameter is introduced along with coordinates, and the model is ill-conditioned due to its strong correlation with the height parameter. For BeiDou Navigation Satellite System (BDS), additional difficulties occur due to its special satellite constellation. In fact, relative zenith troposphere delay (RZTD) derived from high-precision empirical zenith troposphere models can be introduced. Thus, the model strength can be improved, which is also called the RZTD-constrained RTK model. In this contribution, we first analyze the factors affecting the precision of BDS medium-long baseline RTK; thereafter, 15 baselines ranging from 38 km to 167 km in different troposphere conditions are processed to assess the performance of RZTD-constrained RTK. Results show that the troposphere parameter is difficult to distinguish from the height component, even with long time filtering for BDS-only RTK. Due to the lack of variation in geometry for the BDS geostationary Earth orbit satellite, the long convergence time of ambiguity parameters may reduce the height precision of GPS/BDS-combined RTK in the initial period. When the RZTD-constrained model was used in BDS and GPS/BDS-combined situations compared with the traditional RTK, the standard deviation of the height component for the fixed solution was reduced by 52.4% and 34.0%, respectively. PMID:29661999

Fault offsets and lateral crustal movement on Europa - Evidence for a mobile ice shell

NASA Technical Reports Server (NTRS)

Schenk, Paul M.; Mckinnon, William B.

1989-01-01

An examination is conducted of Europa's cross-cutting structural relationships between various lineament types, in order to constrain the type of structure involved in each such case and, where possible, to also constrain the degree of extension across the lineaments. Evidence is adduced for significant lateral crustal movement, allowing alternative models and mechanisms for lineament formation to be discussed, as well as plausible lithospheric and crustal models. The question as to whether any of the water-ice layer has been, or currently is, liquid, is also treated in light of the evidence obtained.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saide, Pablo E.; Peterson, David A.; de Silva, Arlindo

We couple airborne, ground-based, and satellite observations; conduct regional simulations; and develop and apply an inversion technique to constrain hourly smoke emissions from the Rim Fire, the third largest observed in California, USA. Emissions constrained with multiplatform data show notable nocturnal enhancements (sometimes over a factor of 20), correlate better with daily burned area data, and are a factor of 2–4 higher than a priori estimates, highlighting the need for improved characterization of diurnal profiles and day-to-day variability when modeling extreme fires. Constraining only with satellite data results in smaller enhancements mainly due to missing retrievals near the emissions source,more » suggesting that top-down emission estimates for these events could be underestimated and a multiplatform approach is required to resolve them. Predictions driven by emissions constrained with multiplatform data present significant variations in downwind air quality and in aerosol feedback on meteorology, emphasizing the need for improved emissions estimates during exceptional events.« less

Active/Passive Control of Sound Radiation from Panels using Constrained Layer Damping

NASA Technical Reports Server (NTRS)

Gibbs, Gary P.; Cabell, Randolph H.

2003-01-01

A hybrid passive/active noise control system utilizing constrained layer damping and model predictive feedback control is presented. This system is used to control the sound radiation of panels due to broadband disturbances. To facilitate the hybrid system design, a methodology for placement of constrained layer damping which targets selected modes based on their relative radiated sound power is developed. The placement methodology is utilized to determine two constrained layer damping configurations for experimental evaluation of a hybrid system. The first configuration targets the (4,1) panel mode which is not controllable by the piezoelectric control actuator, and the (2,3) and (5,2) panel modes. The second configuration targets the (1,1) and (3,1) modes. The experimental results demonstrate the improved reduction of radiated sound power using the hybrid passive/active control system as compared to the active control system alone.

The eigenstate thermalization hypothesis in constrained Hilbert spaces: A case study in non-Abelian anyon chains

NASA Astrophysics Data System (ADS)

Chandran, A.; Schulz, Marc D.; Burnell, F. J.

2016-12-01

Many phases of matter, including superconductors, fractional quantum Hall fluids, and spin liquids, are described by gauge theories with constrained Hilbert spaces. However, thermalization and the applicability of quantum statistical mechanics has primarily been studied in unconstrained Hilbert spaces. In this paper, we investigate whether constrained Hilbert spaces permit local thermalization. Specifically, we explore whether the eigenstate thermalization hypothesis (ETH) holds in a pinned Fibonacci anyon chain, which serves as a representative case study. We first establish that the constrained Hilbert space admits a notion of locality by showing that the influence of a measurement decays exponentially in space. This suggests that the constraints are no impediment to thermalization. We then provide numerical evidence that ETH holds for the diagonal and off-diagonal matrix elements of various local observables in a generic disorder-free nonintegrable model. We also find that certain nonlocal observables obey ETH.

Degree-constrained multicast routing for multimedia communications

NASA Astrophysics Data System (ADS)

Wang, Yanlin; Sun, Yugeng; Li, Guidan

2005-02-01

Multicast services have been increasingly used by many multimedia applications. As one of the key techniques to support multimedia applications, the rational and effective multicast routing algorithms are very important to networks performance. When switch nodes in networks have different multicast capability, multicast routing problem is modeled as the degree-constrained Steiner problem. We presented two heuristic algorithms, named BMSTA and BSPTA, for the degree-constrained case in multimedia communications. Both algorithms are used to generate degree-constrained multicast trees with bandwidth and end to end delay bound. Simulations over random networks were carried out to compare the performance of the two proposed algorithms. Experimental results show that the proposed algorithms have advantages in traffic load balancing, which can avoid link blocking and enhance networks performance efficiently. BMSTA has better ability in finding unsaturated links and (or) unsaturated nodes to generate multicast trees than BSPTA. The performance of BMSTA is affected by the variation of degree constraints.

A multiphase model for three-dimensional tumor growth

NASA Astrophysics Data System (ADS)

Sciumè, G.; Shelton, S.; Gray, W. G.; Miller, C. T.; Hussain, F.; Ferrari, M.; Decuzzi, P.; Schrefler, B. A.

2013-01-01

Several mathematical formulations have analyzed the time-dependent behavior of a tumor mass. However, most of these propose simplifications that compromise the physical soundness of the model. Here, multiphase porous media mechanics is extended to model tumor evolution, using governing equations obtained via the thermodynamically constrained averaging theory. A tumor mass is treated as a multiphase medium composed of an extracellular matrix (ECM); tumor cells (TCs), which may become necrotic depending on the nutrient concentration and tumor phase pressure; healthy cells (HCs); and an interstitial fluid for the transport of nutrients. The equations are solved by a finite element method to predict the growth rate of the tumor mass as a function of the initial tumor-to-healthy cell density ratio, nutrient concentration, mechanical strain, cell adhesion and geometry. Results are shown for three cases of practical biological interest such as multicellular tumor spheroids (MTSs) and tumor cords. First, the model is validated by experimental data for time-dependent growth of an MTS in a culture medium. The tumor growth pattern follows a biphasic behavior: initially, the rapidly growing TCs tend to saturate the volume available without any significant increase in overall tumor size; then, a classical Gompertzian pattern is observed for the MTS radius variation with time. A core with necrotic cells appears for tumor sizes larger than 150 μm, surrounded by a shell of viable TCs whose thickness stays almost constant with time. A formula to estimate the size of the necrotic core is proposed. In the second case, the MTS is confined within a healthy tissue. The growth rate is reduced, as compared to the first case—mostly due to the relative adhesion of the TCs and HCs to the ECM, and the less favorable transport of nutrients. In particular, for HCs adhering less avidly to the ECM, the healthy tissue is progressively displaced as the malignant mass grows, whereas TC infiltration is predicted for the opposite condition. Interestingly, the infiltration potential of the tumor mass is mostly driven by the relative cell adhesion to the ECM. In the third case, a tumor cord model is analyzed where the malignant cells grow around microvessels in a three-dimensional geometry. It is shown that TCs tend to migrate among adjacent vessels seeking new oxygen and nutrients. This model can predict and optimize the efficacy of anticancer therapeutic strategies. It can be further developed to answer questions on tumor biophysics, related to the effects of ECM stiffness and cell adhesion on TC proliferation.

A crustal seismic velocity model for the UK, Ireland and surrounding seas

USGS Publications Warehouse

Kelly, A.; England, R.W.; Maguire, Peter K.H.

2007-01-01

A regional model of the 3-D variation in seismic P-wave velocity structure in the crust of NW Europe has been compiled from wide-angle reflection/refraction profiles. Along each 2-D profile a velocity-depth function has been digitised at 5 km intervals. These 1-D velocity functions were mapped into three dimensions using ordinary kriging with weights determined to minimise the difference between digitised and interpolated values. An analysis of variograms of the digitised data suggested a radial isotropic weighting scheme was most appropriate. Horizontal dimensions of the model cells are optimised at 40 ?? 40 km and the vertical dimension at 1 km. The resulting model provides a higher resolution image of the 3-D variation in seismic velocity structure of the UK, Ireland and surrounding areas than existing models. The construction of the model through kriging allows the uncertainty in the velocity structure to be assessed. This uncertainty indicates the high density of data required to confidently interpolate the crustal velocity structure, and shows that for this region the velocity is poorly constrained for large areas away from the input data. ?? 2007 The Authors Journal compilation ?? 2007 RAS.

Invariant TAD Boundaries Constrain Cell-Type-Specific Looping Interactions between Promoters and Distal Elements around the CFTR Locus.

PubMed

Smith, Emily M; Lajoie, Bryan R; Jain, Gaurav; Dekker, Job

2016-01-07

Three-dimensional genome structure plays an important role in gene regulation. Globally, chromosomes are organized into active and inactive compartments while, at the gene level, looping interactions connect promoters to regulatory elements. Topologically associating domains (TADs), typically several hundred kilobases in size, form an intermediate level of organization. Major questions include how TADs are formed and how they are related to looping interactions between genes and regulatory elements. Here we performed a focused 5C analysis of a 2.8 Mb chromosome 7 region surrounding CFTR in a panel of cell types. We find that the same TAD boundaries are present in all cell types, indicating that TADs represent a universal chromosome architecture. Furthermore, we find that these TAD boundaries are present irrespective of the expression and looping of genes located between them. In contrast, looping interactions between promoters and regulatory elements are cell-type specific and occur mostly within TADs. This is exemplified by the CFTR promoter that in different cell types interacts with distinct sets of distal cell-type-specific regulatory elements that are all located within the same TAD. Finally, we find that long-range associations between loci located in different TADs are also detected, but these display much lower interaction frequencies than looping interactions within TADs. Interestingly, interactions between TADs are also highly cell-type-specific and often involve loci clustered around TAD boundaries. These data point to key roles of invariant TAD boundaries in constraining as well as mediating cell-type-specific long-range interactions and gene regulation. Copyright © 2016 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Good initialization model with constrained body structure for scene text recognition

NASA Astrophysics Data System (ADS)

Zhu, Anna; Wang, Guoyou; Dong, Yangbo

2016-09-01

Scene text recognition has gained significant attention in the computer vision community. Character detection and recognition are the promise of text recognition and affect the overall performance to a large extent. We proposed a good initialization model for scene character recognition from cropped text regions. We use constrained character's body structures with deformable part-based models to detect and recognize characters in various backgrounds. The character's body structures are achieved by an unsupervised discriminative clustering approach followed by a statistical model and a self-build minimum spanning tree model. Our method utilizes part appearance and location information, and combines character detection and recognition in cropped text region together. The evaluation results on the benchmark datasets demonstrate that our proposed scheme outperforms the state-of-the-art methods both on scene character recognition and word recognition aspects.

Single-round selection yields a unique retroviral envelope utilizing GPR172A as its host receptor.

PubMed

Mazari, Peter M; Linder-Basso, Daniela; Sarangi, Anindita; Chang, Yehchung; Roth, Monica J

2009-04-07

The recognition by a viral envelope of its cognate host-cell receptor is the initial critical step in defining the viral host-range and tissue specificity. This study combines a single-round of selection of a random envelope library with a parallel cDNA screen for receptor function to identify a distinct retroviral envelope/receptor pair. The 11-aa targeting domain of the modified feline leukemia virus envelope consists of a constrained peptide. Critical to the binding of the constrained peptide envelope to its cellular receptor are a pair of internal cysteines and an essential Trp required for maintenance of titers >10(5) lacZ staining units per milliliter. The receptor used for viral entry is the human GPR172A protein, a G-protein-coupled receptor isolated from osteosarcoma cells. The ability to generate unique envelopes capable of using tissue- or disease-specific receptors marks an advance in the development of efficient gene-therapy vectors.

Splines and polynomial tools for flatness-based constrained motion planning

NASA Astrophysics Data System (ADS)

Suryawan, Fajar; De Doná, José; Seron, María

2012-08-01

This article addresses the problem of trajectory planning for flat systems with constraints. Flat systems have the useful property that the input and the state can be completely characterised by the so-called flat output. We propose a spline parametrisation for the flat output, the performance output, the states and the inputs. Using this parametrisation the problem of constrained trajectory planning can be cast into a simple quadratic programming problem. An important result is that the B-spline parametrisation used gives exact results for constrained linear continuous-time system. The result is exact in the sense that the constrained signal can be made arbitrarily close to the boundary without having intersampling issues (as one would have in sampled-data systems). Simulation examples are presented, involving the generation of rest-to-rest trajectories. In addition, an experimental result of the method is also presented, where two methods to generate trajectories for a magnetic-levitation (maglev) system in the presence of constraints are compared and each method's performance is discussed. The first method uses the nonlinear model of the plant, which turns out to belong to the class of flat systems. The second method uses a linearised version of the plant model around an operating point. In every case, a continuous-time description is used. The experimental results on a real maglev system reported here show that, in most scenarios, the nonlinear and linearised models produce almost similar, indistinguishable trajectories.

Constraining the mass of the Local Group

NASA Astrophysics Data System (ADS)

Carlesi, Edoardo; Hoffman, Yehuda; Sorce, Jenny G.; Gottlöber, Stefan

2017-03-01

The mass of the Local Group (LG) is a crucial parameter for galaxy formation theories. However, its observational determination is challenging - its mass budget is dominated by dark matter that cannot be directly observed. To meet this end, the posterior distributions of the LG and its massive constituents have been constructed by means of constrained and random cosmological simulations. Two priors are assumed - the Λ cold dark matter model that is used to set up the simulations, and an LG model that encodes the observational knowledge of the LG and is used to select LG-like objects from the simulations. The constrained simulations are designed to reproduce the local cosmography as it is imprinted on to the Cosmicflows-2 data base of velocities. Several prescriptions are used to define the LG model, focusing in particular on different recent estimates of the tangential velocity of M31. It is found that (a) different vtan choices affect the peak mass values up to a factor of 2, and change mass ratios of MM31 to MMW by up to 20 per cent; (b) constrained simulations yield more sharply peaked posterior distributions compared with the random ones; (c) LG mass estimates are found to be smaller than those found using the timing argument; (d) preferred Milky Way masses lie in the range of (0.6-0.8) × 1012 M⊙; whereas (e) MM31 is found to vary between (1.0-2.0) × 1012 M⊙, with a strong dependence on the vtan values used.

Modeling and query the uncertainty of network constrained moving objects based on RFID data

NASA Astrophysics Data System (ADS)

Han, Liang; Xie, Kunqing; Ma, Xiujun; Song, Guojie

2007-06-01

The management of network constrained moving objects is more and more practical, especially in intelligent transportation system. In the past, the location information of moving objects on network is collected by GPS, which cost high and has the problem of frequent update and privacy. The RFID (Radio Frequency IDentification) devices are used more and more widely to collect the location information. They are cheaper and have less update. And they interfere in the privacy less. They detect the id of the object and the time when moving object passed by the node of the network. They don't detect the objects' exact movement in side the edge, which lead to a problem of uncertainty. How to modeling and query the uncertainty of the network constrained moving objects based on RFID data becomes a research issue. In this paper, a model is proposed to describe the uncertainty of network constrained moving objects. A two level index is presented to provide efficient access to the network and the data of movement. The processing of imprecise time-slice query and spatio-temporal range query are studied in this paper. The processing includes four steps: spatial filter, spatial refinement, temporal filter and probability calculation. Finally, some experiments are done based on the simulated data. In the experiments the performance of the index is studied. The precision and recall of the result set are defined. And how the query arguments affect the precision and recall of the result set is also discussed.

The Relationship between Respiration-Related Membrane Potential Slow Oscillations and Discharge Patterns in Mitral/Tufted Cells: What Are the Rules?

PubMed Central

Briffaud, Virginie; Fourcaud-Trocmé, Nicolas; Messaoudi, Belkacem; Buonviso, Nathalie; Amat, Corine

2012-01-01

Background A slow respiration-related rhythm strongly shapes the activity of the olfactory bulb. This rhythm appears as a slow oscillation that is detectable in the membrane potential, the respiration-related spike discharge of the mitral/tufted cells and the bulbar local field potential. Here, we investigated the rules that govern the manifestation of membrane potential slow oscillations (MPSOs) and respiration-related discharge activities under various afferent input conditions and cellular excitability states. Methodology and Principal Findings We recorded the intracellular membrane potential signals in the mitral/tufted cells of freely breathing anesthetized rats. We first demonstrated the existence of multiple types of MPSOs, which were influenced by odor stimulation and discharge activity patterns. Complementary studies using changes in the intracellular excitability state and a computational model of the mitral cell demonstrated that slow oscillations in the mitral/tufted cell membrane potential were also modulated by the intracellular excitability state, whereas the respiration-related spike activity primarily reflected the afferent input. Based on our data regarding MPSOs and spike patterns, we found that cells exhibiting an unsynchronized discharge pattern never exhibited an MPSO. In contrast, cells with a respiration-synchronized discharge pattern always exhibited an MPSO. In addition, we demonstrated that the association between spike patterns and MPSO types appeared complex. Conclusion We propose that both the intracellular excitability state and input strength underlie specific MPSOs, which, in turn, constrain the types of spike patterns exhibited. PMID:22952828

Sorting white blood cells in microfabricated arrays

NASA Astrophysics Data System (ADS)

Castelino, Judith Andrea Rose

Fractionating white cells in microfabricated arrays presents the potential for detecting cells with abnormal adhesive or deformation properties. A possible application is separating nucleated fetal red blood cells from maternal blood. Since fetal cells are nucleated, it is possible to extract genetic information about the fetus from them. Separating fetal cells from maternal blood would provide a low cost noninvasive prenatal diagnosis for genetic defects, which is not currently available. We present results showing that fetal cells penetrate further into our microfabricated arrays than adult cells, and that it is possible to enrich the fetal cell fraction using the arrays. We discuss modifications to the array which would result in further enrichment. Fetal cells are less adhesive and more deformable than adult white cells. To determine which properties limit penetration, we compared the penetration of granulocytes and lymphocytes in arrays with different etch depths, constriction size, constriction frequency, and with different amounts of metabolic activity. The penetration of lymphocytes and granulocytes into constrained and unconstrained arrays differed qualitatively. In constrained arrays, the cells were activated by repeated shearing, and the number of cells stuck as a function of distance fell superexponentially. In unconstrained arrays the number of cells stuck fell slower than an exponential. We attribute this result to different subpopulations of cells with different sticking parameters. We determined that penetration in unconstrained arrays was limited by metabolic processes, and that when metabolic activity was reduced penetration was limited by deformability. Fetal cells also contain a different form of hemoglobin with a higher oxygen affinity than adult hemoglobin. Deoxygenated cells are paramagnetic and are attracted to high magnetic field gradients. We describe a device which can separate cells using 10 μm magnetic wires to deflect the paramagnetic cells. We present preliminary results from a test system that separates paramagnetic beads from latex beads. The separation is limited by our ability to produce the high field gradients which are necessary to separate cells according to their hemoglobin content, and we present estimates of the magnetic gradients we achieved.

Configuration of the thermal landscape determines thermoregulatory performance of ectotherms

PubMed Central

Sears, Michael W.; Angilletta, Michael J.; Schuler, Matthew S.; Borchert, Jason; Dilliplane, Katherine F.; Stegman, Monica; Rusch, Travis W.; Mitchell, William A.

2016-01-01

Although most organisms thermoregulate behaviorally, biologists still cannot easily predict whether mobile animals will thermoregulate in natural environments. Current models fail because they ignore how the spatial distribution of thermal resources constrains thermoregulatory performance over space and time. To overcome this limitation, we modeled the spatially explicit movements of animals constrained by access to thermal resources. Our models predict that ectotherms thermoregulate more accurately when thermal resources are dispersed throughout space than when these resources are clumped. This prediction was supported by thermoregulatory behaviors of lizards in outdoor arenas with known distributions of environmental temperatures. Further, simulations showed how the spatial structure of the landscape qualitatively affects responses of animals to climate. Biologists will need spatially explicit models to predict impacts of climate change on local scales. PMID:27601639

Using Coronal Hole Maps to Constrain MHD Models

NASA Astrophysics Data System (ADS)

Caplan, Ronald M.; Downs, Cooper; Linker, Jon A.; Mikic, Zoran

2017-08-01

In this presentation, we explore the use of coronal hole maps (CHMs) as a constraint for thermodynamic MHD models of the solar corona. Using our EUV2CHM software suite (predsci.com/chd), we construct CHMs from SDO/AIA 193Å and STEREO-A/EUVI 195Å images for multiple Carrington rotations leading up to the August 21st, 2017 total solar eclipse. We then contruct synoptic CHMs from synthetic EUV images generated from global thermodynamic MHD simulations of the corona for each rotation. Comparisons of apparent coronal hole boundaries and estimates of the net open flux are used to benchmark and constrain our MHD model leading up to the eclipse. Specifically, the comparisons are used to find optimal parameterizations of our wave turbulence dissipation (WTD) coronal heating model.

GROWTH AND INEQUALITY: MODEL EVALUATION BASED ON AN ESTIMATION-CALIBRATION STRATEGY

PubMed Central

Jeong, Hyeok; Townsend, Robert

2010-01-01

This paper evaluates two well-known models of growth with inequality that have explicit micro underpinnings related to household choice. With incomplete markets or transactions costs, wealth can constrain investment in business and the choice of occupation and also constrain the timing of entry into the formal financial sector. Using the Thai Socio-Economic Survey (SES), we estimate the distribution of wealth and the key parameters that best fit cross-sectional data on household choices and wealth. We then simulate the model economies for two decades at the estimated initial wealth distribution and analyze whether the model economies at those micro-fit parameter estimates can explain the observed macro and sectoral aspects of income growth and inequality change. Both models capture important features of Thai reality. Anomalies and comparisons across the two distinct models yield specific suggestions for improved research on the micro foundations of growth and inequality. PMID:20448833

Constraining viscous dark energy models with the latest cosmological data

NASA Astrophysics Data System (ADS)

Wang, Deng; Yan, Yang-Jie; Meng, Xin-He

2017-10-01

Based on the assumption that the dark energy possessing bulk viscosity is homogeneously and isotropically permeated in the universe, we propose three new viscous dark energy (VDE) models to characterize the accelerating universe. By constraining these three models with the latest cosmological observations, we find that they just deviate very slightly from the standard cosmological model and can alleviate effectively the current H_0 tension between the local observation by the Hubble Space Telescope and the global measurement by the Planck Satellite. Interestingly, we conclude that a spatially flat universe in our VDE model with cosmic curvature is still supported by current data, and the scale invariant primordial power spectrum is strongly excluded at least at the 5.5σ confidence level in the three VDE models as the Planck result. We also give the 95% upper limits of the typical bulk viscosity parameter η in the three VDE scenarios.

[3-D finite element modeling of internal fixation of mandibular mental fracture and the design of boundary constraints].

PubMed

Luo, Xiaohui; Wang, Hang; Fan, Yubo

2007-04-01

This study was aimed to develop a 3-D finite element (3-D FE) model of the mental fractured mandible and design the boundary constrains. The CT images from a health volunteer were used as the original information and put into ANSYS program to build a 3-D FE model. The model of the miniplate and screw which were used for the internal fixation was established by Pro/E. The boundary constrains of different muscle loadings were used to simulate the 3 functional conditions of the mandible. A 3-D FE model of mental fractured mandible under the miniplate-screw internal fixation system was constructed. And by the boundary constraints, the 3 biting conditions were simulated and the model could serve as a foundation on which to analyze the biomechanical behavior of the fractured mandible.

Prevalence and predictors of squamous intraepithelial lesions of the cervix in HIV-infected women in Lusaka, Zambia

PubMed Central

Parham, Groesbeck P.; Sahasrabuddhe, Vikrant V.; Mwanahamuntu, Mulindi H.; Shepherd, Bryan E.; Hicks, Michael L.; Stringer, Elizabeth M.; Vermund, Sten H.

2009-01-01

Objectives HIV-infected women living in resource-constrained nations like Zambia are now accessing antiretroviral therapy and thus may live long enough for HPV-induced cervical cancer to manifest and progress. We evaluated the prevalence and predictors of cervical squamous intraepithelial lesions (SIL) among HIV-infected women in Zambia. Methods We screened 150 consecutive, non-pregnant HIV-infected women accessing HIV/AIDS care services in Lusaka, Zambia. We collected cervical specimens for cytological analysis by liquid-based monolayer cytology (ThinPrep Pap Test®) and HPV typing using the Roche Linear Array® PCR assay. Results The median age of study participants was 36 years (range 23-49 years) and their median CD4+ count was 165/μL (range 7-942). The prevalence of SIL on cytology was 76% (114/150), of which 23.3% (35/150) women had low-grade SIL, 32.6% (49/150) had high-grade SIL, and 20% (30/150) had lesions suspicious for squamous cell carcinoma (SCC). High-risk HPV types were present in 85.3% (128/150) women. On univariate analyses, age of the participant, CD4+ cell count, and presence of any high-risk HPV type were significantly associated with the presence of severely abnormal cytological lesions (i.e., high-grade SIL and lesions suspicious for SCC). Multivariable logistic regression modeling suggested the presence of any high-risk HPV type as an independent predictor of severely abnormal cytology (adjusted OR: 12.4, 95% CI 2.62-58.1, p=0.02). Conclusions The high prevalence of abnormal squamous cytology in our study is one of the highest reported in any population worldwide. Screening of HIV-infected women in resource-constrained settings like Zambia should be implemented to prevent development of HPV-induced SCC. PMID:16875716

Section-constrained local geological interface dynamic updating method based on the HRBF surface

NASA Astrophysics Data System (ADS)

Guo, Jiateng; Wu, Lixin; Zhou, Wenhui; Li, Chaoling; Li, Fengdan

2018-02-01

Boundaries, attitudes and sections are the most common data acquired from regional field geological surveys, and they are used for three-dimensional (3D) geological modelling. However, constructing topologically consistent 3D geological models from rapid and automatic regional modelling with convenient local modifications remains unresolved. In previous works, the Hermite radial basis function (HRBF) surface was introduced for the simulation of geological interfaces from geological boundaries and attitudes, which allows 3D geological models to be automatically extracted from the modelling area by the interfaces. However, the reasonability and accuracy of non-supervised subsurface modelling is limited without further modifications generated through explanations and analyses performed by geology experts. In this paper, we provide flexible and convenient manual interactive manipulation tools for geologists to sketch constraint lines, and these tools may help geologists transform and apply their expert knowledge to the models. In the modified modelling workflow, the geological sections were treated as auxiliary constraints to construct more reasonable 3D geological models. The geometric characteristics of section lines were abstracted to coordinates and normal vectors, and along with the transformed coordinates and vectors from boundaries and attitudes, these characteristics were adopted to co-calculate the implicit geological surface function parameters of the HRBF equations and form constrained geological interfaces from topographic (boundaries and attitudes) and subsurface data (sketched sections). Based on this new modelling method, a prototype system was developed, in which the section lines could be imported from databases or interactively sketched, and the models could be immediately updated after the new constraints were added. Experimental comparisons showed that all boundary, attitude and section data are well represented in the constrained models, which are consistent with expert explanations and help improve the quality of the models.

New insights into the rate dependence of sulfur isotope fractionation during dissimilatory sulfate reduction

NASA Astrophysics Data System (ADS)

Giannetta, M.; Druhan, J. L.; Sanford, R. A.

2016-12-01

The vast majority of experiments concerning the isotope partitioning of sulfate reducing bacteria (SRB) are conducted under artificially optimized growth conditions. In contrast, many natural environments supporting SRB reflect limited nutrient availability. In this study, we couple the cell-specific reduction rate of a common SRB to the characteristic partitioning of stable sulfur isotopes. However, our method is novel in that we regulate the addition of electron donor such that cell growth is minimized and cell-specific reduction rates are constant, thus simulating the low reactivity characteristic of natural conditions. Anoxic bioreactors containing equal amounts of Desulfovibrio vulgariswere continuously injected with formate to control the rate of dissimilatory sulfate reduction (DSR). Cell growth was minimized through two means, (1) a high initial culture density ensured the ratio of nutrients per cell was low; (2) the oxidation state of carbon in formate is unfavorable to cell biomass accumulation. Negligible cell growth was verified by flow cytometry. Four controlled DSR rates ranging from 0.32 to 1.8 µmole/hour exhibited fractionation factor (ɛ) values ranging from 9‰ to 4‰ over 1200 to 300 hours, respectively. These results demonstrate a unique value of ɛ for each rate of DSR, where larger S isotope partitioning is characteristic of a slower cell-specific rate of sulfate reduction. The results of this study provide a unique dataset that can be used to constrain variations in ɛ as a function of DSR rate. Specifically, the dataset offers a foundation to test recently proposed analytical models and predict variations in observed ɛ as a result of a multi-step reactive pathway. Based on these results, we suggest a novel rate expression for incorporation into reactive transport models. Such a rate law supports extrapolation of experimental behavior into natural conditions over modern to geologic timescales.

From Immunity and Vaccines to Mammalian Regeneration.

PubMed

Heber-Katz, Ellen

2015-07-15

Our current understanding of major histocompatibility complex (MHC)-mediated antigen presentation in self and nonself immune recognition was derived from immunological studies of autoimmunity and virus-host interactions, respectively. The trimolecular complex of the MHC molecule, antigen, and T-cell receptor accounts for the phenomena of immunodominance and MHC degeneracy in both types of responses and constrains vaccine development. Out of such considerations, we developed a simple peptide vaccine construct that obviates immunodominance, resulting in a broadly protective T-cell response in the absence of antibody. In the course of autoimmunity studies, we identified the MRL mouse strain as a mammalian model of amphibian-like regeneration. A significant level of DNA damage in the cells from this mouse pointed to the role of the cell cycle checkpoint gene CDKN1a, or p21(cip1/waf1). The MRL mouse has highly reduced levels of this molecule, and a genetic knockout of this single gene in otherwise nonregenerating strains led to an MRL-type regenerative response, indicating that the ability to regenerate has not been lost during evolution. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A Framework for Assessing the Sustainability of Monitored Natural Attenuation

USGS Publications Warehouse

Chapelle, Francis H.; Novak, John; Parker, John; Campbell, Bruce G.; Widdowson, Mark A.

2007-01-01

The sustainability of monitored natural attenuation (MNA) over time depends upon (1) the presence of chemical/biochemical processes that transform wastes to innocuous byproducts, and (2) the availability of energy to drive these processes to completion. The presence or absence of contaminant-transforming chemical/biochemical processes can be determined by observing contaminant mass loss over time and space (mass balance). The energy available to drive these processes to completion can be assessed by measuring the pool of metabolizable organic carbon available in a system, and by tracing the flow of this energy to available electron acceptors (energy balance). For the special case of chlorinated ethenes in ground-water systems, for which a variety of contaminant-transforming biochemical processes exist, natural attenuation is sustainable when the pool of bioavailable organic carbon is large relative to the carbon flux needed to drive biodegradation to completion. These principles are illustrated by assessing the sustainability of MNA at a chlorinated ethene-contaminated site in Kings Bay, Georgia. Approximately 1,000 kilograms of perchloroethene (PCE) was released to a municipal landfill in the 1978-1980 timeframe, and the resulting plume of chlorinated ethenes migrated toward a nearby housing development. A numerical model, built using the sequential electron acceptor model code (SEAM3D), was used to quantify mass and energy balance in this system. The model considered the dissolution of non-aqueous phase liquid (NAPL) as the source of the PCE, and was designed to trace energy flow from dissolved organic carbon to available electron acceptors in the sequence oxygen > chlorinated ethenes > ferric iron > sulfate > carbon dioxide. The model was constrained by (1) comparing simulated and measured rates of ground-water flow, (2) reproducing the observed distribution of electron-accepting processes in the aquifer, (3) comparing observed and measured concentrations of chlorinated ethenes, and (4) reproducing the observed production and subsequent dilution of dissolved chloride, a final degradation product of chloroethene biodegradation. Simulations using the constrained model indicated that an average flux of 5 milligrams per liter per day of organic carbon (CH2O) per model cell (25 square meters) is required to support the short-term sustainability of MNA. Because this flux is small relative to the pool of renewable organic carbon (about 4.7 x 107 milligrams [mg] per model cell) present in the soil zone and non-renewable carbon (about 6.9 x 108 mg per model cell) in an organic-rich sediment layer overlying the aquifer, the long-term sustainability of MNA is similarly large. This study illustrates that the short- and long-term sustainability of MNA can be assessed by: 1. Estimating the time required for contaminants to dissolve/disperse/degrade under ambient hydrologic conditions (time of remediation). 2. Quantifying the organic carbon flux to the system needed to consume competing electron acceptors (oxygen) and direct electron flow toward chloroethene degradation (short-term sustainability). 3. Comparing the required flux of organic carbon to the pool of renewable and non-renewable organic carbon given the estimated time of remediation (long-term sustainability). These are general principles that can be used to assess the sustainability of MNA in any hydrologic system.

Chance Constrained Programming Methods in Probabilistic Programming.

DTIC Science & Technology

1982-03-01

Financial and Quantitative Analysis 2, 1967. Also reproduced in R. F. Byrne et. al., eds.5tudies in Budgeting (Amsterdam: North Holland, 1971 ). [3...Rules for the E-Model of Chance-Constrained Programming," Management Science, 17, 1971 . [23] Garstka, S. J. "The Economic Equivalence of Several...Iowa City: The University of Iowa College of Business Administration, 1981). -3- (29] Kall , P. and A. Prekopa, eds, Recent Results in Stochastic

Vertical structure and physical processes of the Madden-Julian Oscillation: Biases and uncertainties at short range

NASA Astrophysics Data System (ADS)

Xavier, Prince K.; Petch, Jon C.; Klingaman, Nicholas P.; Woolnough, Steve J.; Jiang, Xianan; Waliser, Duane E.; Caian, Mihaela; Cole, Jason; Hagos, Samson M.; Hannay, Cecile; Kim, Daehyun; Miyakawa, Tomoki; Pritchard, Michael S.; Roehrig, Romain; Shindo, Eiki; Vitart, Frederic; Wang, Hailan

2015-05-01

An analysis of diabatic heating and moistening processes from 12 to 36 h lead time forecasts from 12 Global Circulation Models are presented as part of the "Vertical structure and physical processes of the Madden-Julian Oscillation (MJO)" project. A lead time of 12-36 h is chosen to constrain the large-scale dynamics and thermodynamics to be close to observations while avoiding being too close to the initial spin-up of the models as they adjust to being driven from the Years of Tropical Convection (YOTC) analysis. A comparison of the vertical velocity and rainfall with the observations and YOTC analysis suggests that the phases of convection associated with the MJO are constrained in most models at this lead time although the rainfall in the suppressed phase is typically overestimated. Although the large-scale dynamics is reasonably constrained, moistening and heating profiles have large intermodel spread. In particular, there are large spreads in convective heating and moistening at midlevels during the transition to active convection. Radiative heating and cloud parameters have the largest relative spread across models at upper levels during the active phase. A detailed analysis of time step behavior shows that some models show strong intermittency in rainfall and differences in the precipitation and dynamics relationship between models. The wealth of model outputs archived during this project is a very valuable resource for model developers beyond the study of the MJO. In addition, the findings of this study can inform the design of process model experiments, and inform the priorities for field experiments and future observing systems.

Constrained parameterisation of photosynthetic capacity causes significant increase of modelled tropical vegetation surface temperature

NASA Astrophysics Data System (ADS)

Kattge, J.; Knorr, W.; Raddatz, T.; Wirth, C.

2009-04-01

Photosynthetic capacity is one of the most sensitive parameters of terrestrial biosphere models whose representation in global scale simulations has been severely hampered by a lack of systematic analyses using a sufficiently broad database. Due to its coupling to stomatal conductance changes in the parameterisation of photosynthetic capacity may potentially influence transpiration rates and vegetation surface temperature. Here, we provide a constrained parameterisation of photosynthetic capacity for different plant functional types in the context of the photosynthesis model proposed by Farquhar et al. (1980), based on a comprehensive compilation of leaf photosynthesis rates and leaf nitrogen content. Mean values of photosynthetic capacity were implemented into the coupled climate-vegetation model ECHAM5/JSBACH and modelled gross primary production (GPP) is compared to a compilation of independent observations on stand scale. Compared to the current standard parameterisation the root-mean-squared difference between modelled and observed GPP is substantially reduced for almost all PFTs by the new parameterisation of photosynthetic capacity. We find a systematic depression of NUE (photosynthetic capacity divided by leaf nitrogen content) on certain tropical soils that are known to be deficient in phosphorus. Photosynthetic capacity of tropical trees derived by this study is substantially lower than standard estimates currently used in terrestrial biosphere models. This causes a decrease of modelled GPP while it significantly increases modelled tropical vegetation surface temperatures, up to 0.8°C. These results emphasise the importance of a constrained parameterisation of photosynthetic capacity not only for the carbon cycle, but also for the climate system.

Constrained relationship agency as the risk factor for intimate partner violence in different models of transactional sex

PubMed Central

Fielding-Miller, Rebecca; Dunkle, Kristin

2018-01-01

Women who engage in transactional sex are more likely to experience intimate partner violence (IPV) and are at higher risk of HIV. However, women engage in transactional sex for a variety of reasons and the precise mechanism linking transactional sex and IPV is not fully understood. We conducted a behavioural survey with a cross-sectional sample of 401 women attending 1 rural and 1 urban public antenatal clinic in Swaziland between February and June 2014. We used structural equation modelling to identify and measure constrained relationship agency (CRA) as a latent variable, and then tested the hypothesis that CRA plays a significant role in the pathway between IPV and transactional sex. After controlling for CRA, receiving more material goods from a sexual partner was not associated with higher levels of physical or sexual IPV and was protective against emotional IPV. CRA was the single largest predictor of IPV, and more education was associated with decreased levels of constrained relationship agency. Policies and interventions that target transactional sex as a driver of IPV and HIV may be more successful if they instead target the broader social landscape that constrains women’s agency and drives the harmful aspects of transactional sex. PMID:29132281

Dynamical insurance models with investment: Constrained singular problems for integrodifferential equations

NASA Astrophysics Data System (ADS)

Belkina, T. A.; Konyukhova, N. B.; Kurochkin, S. V.

2016-01-01

Previous and new results are used to compare two mathematical insurance models with identical insurance company strategies in a financial market, namely, when the entire current surplus or its constant fraction is invested in risky assets (stocks), while the rest of the surplus is invested in a risk-free asset (bank account). Model I is the classical Cramér-Lundberg risk model with an exponential claim size distribution. Model II is a modification of the classical risk model (risk process with stochastic premiums) with exponential distributions of claim and premium sizes. For the survival probability of an insurance company over infinite time (as a function of its initial surplus), there arise singular problems for second-order linear integrodifferential equations (IDEs) defined on a semiinfinite interval and having nonintegrable singularities at zero: model I leads to a singular constrained initial value problem for an IDE with a Volterra integral operator, while II model leads to a more complicated nonlocal constrained problem for an IDE with a non-Volterra integral operator. A brief overview of previous results for these two problems depending on several positive parameters is given, and new results are presented. Additional results are concerned with the formulation, analysis, and numerical study of "degenerate" problems for both models, i.e., problems in which some of the IDE parameters vanish; moreover, passages to the limit with respect to the parameters through which we proceed from the original problems to the degenerate ones are singular for small and/or large argument values. Such problems are of mathematical and practical interest in themselves. Along with insurance models without investment, they describe the case of surplus completely invested in risk-free assets, as well as some noninsurance models of surplus dynamics, for example, charity-type models.

The impact of equilibrating hemispheric albedos on tropical performance in the HadGEM2-ES coupled climate model

DOE PAGES

Haywood, Jim M.; Jones, Andy; Dunstone, Nick; ...

2016-01-14

Despite the fact that the southern hemisphere contains a far greater proportion of dark ocean than the northern hemisphere, the total amount of sunlight reflected from the hemispheres is equal. However, the majority of climate models do not adequately represent this equivalence. Here we examine the impact of equilibrating hemispheric albedos by various idealised methods in a comprehensive coupled climate model and find significant improvements in what have been considered longstanding and apparently intractable model biases. Monsoon precipitation biases almost vanish over all continental land areas, the penetration of monsoon rainfall across the Sahel and the west African monsoon “jump”more » become well represented, and indicators of hurricane frequency are significantly improved. The results appear not to be model specific, implying that hemispheric albedo equivalence may provide a fundamental constraint for climate models that must be satisfied if the dynamics driving these processes, in particular the strength of the Hadley cell, are to be adequately represented. Cross-equatorial energy transport is implicated as a crucial component that must be accurately modelled in coupled general circulation models. The results also suggest that the commonly used practice of prescribing sea-surface temperatures in models provides a less accurate represention of precipitation than constraining the hemispheric albedos.« less

Constraining the noncommutative spectral action via astrophysical observations.

PubMed

Nelson, William; Ochoa, Joseph; Sakellariadou, Mairi

2010-09-03

The noncommutative spectral action extends our familiar notion of commutative spaces, using the data encoded in a spectral triple on an almost commutative space. Varying a rather simple action, one can derive all of the standard model of particle physics in this setting, in addition to a modified version of Einstein-Hilbert gravity. In this Letter we use observations of pulsar timings, assuming that no deviation from general relativity has been observed, to constrain the gravitational sector of this theory. While the bounds on the coupling constants remain rather weak, they are comparable to existing bounds on deviations from general relativity in other settings and are likely to be further constrained by future observations.

Method of making MEA for PEM/SPE fuel cell

DOEpatents

Hulett, Jay S.

2000-01-01

A method of making a membrane-electrode-assembly (MEA) for a PEM/SPE fuel cell comprising applying a slurry of electrode-forming material directly onto a membrane-electrolyte film. The slurry comprises a liquid vehicle carrying catalyst particles and a binder for the catalyst particles. The membrane-electrolyte is preswollen by contact with the vehicle before the electrode-forming slurry is applied to the membrane-electrolyte. The swollen membrane-electrolyte is constrained against shrinking in the "x" and "y" directions during drying. Following assembly of the fuel cell, the MEA is rehydrated inside the fuel cell such that it swells in the "z" direction for enhanced electrical contact with contiguous electrically conductive components of the fuel cell.

Dynamical organization of the cytoskeletal cortex probed by micropipette aspiration

PubMed Central

Brugués, Jan; Maugis, Benoit; Casademunt, Jaume; Nassoy, Pierre; Amblard, François; Sens, Pierre

2010-01-01

Bleb-based cell motility proceeds by the successive inflation and retraction of large spherical membrane protrusions (“blebs”) coupled with substrate adhesion. In addition to their role in motility, cellular blebs constitute a remarkable illustration of the dynamical interactions between the cytoskeletal cortex and the plasma membrane. Here we study the bleb-based motions of Entamoeba histolytica in the constrained geometry of a micropipette. We construct a generic theoretical model that combines the polymerization of an actin cortex underneath the plasma membrane with the myosin-generated contractile stress in the cortex and the stress-induced failure of membrane-cortex adhesion. One major parameter dictating the cell response to micropipette suction is the stationary cortex thickness, controlled by actin polymerization and depolymerization. The other relevant physical parameters can be combined into two characteristic cortex thicknesses for which the myosin stress (i) balances the suction pressure and (ii) provokes membrane-cortex unbinding. We propose a general phase diagram for cell motions inside a micropipette by comparing these three thicknesses. In particular, we theoretically predict and experimentally verify the existence of saltatory and oscillatory motions for a well-defined range of micropipette suction pressures. PMID:20713731

Application of London-type dispersion corrections to the solid-state density functional theory simulation of the terahertz spectra of crystalline pharmaceuticals.

PubMed

King, Matthew D; Buchanan, William D; Korter, Timothy M

2011-03-14

The effects of applying an empirical dispersion correction to solid-state density functional theory methods were evaluated in the simulation of the crystal structure and low-frequency (10 to 90 cm(-1)) terahertz spectrum of the non-steroidal anti-inflammatory drug, naproxen. The naproxen molecular crystal is bound largely by weak London force interactions, as well as by more prominent interactions such as hydrogen bonding, and thus serves as a good model for the assessment of the pair-wise dispersion correction term in systems influenced by intermolecular interactions of various strengths. Modifications to the dispersion parameters were tested in both fully optimized unit cell dimensions and those determined by X-ray crystallography, with subsequent simulations of the THz spectrum being performed. Use of the unmodified PBE density functional leads to an unrealistic expansion of the unit cell volume and the poor representation of the THz spectrum. Inclusion of a modified dispersion correction enabled a high-quality simulation of the THz spectrum and crystal structure of naproxen to be achieved without the need for artificially constraining the unit cell dimensions.

Nanomechanical and topographical imaging of living cells by atomic force microscopy with colloidal probes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Puricelli, Luca; Galluzzi, Massimiliano; Schulte, Carsten

Atomic Force Microscopy (AFM) has a great potential as a tool to characterize mechanical and morphological properties of living cells; these properties have been shown to correlate with cells’ fate and patho-physiological state in view of the development of novel early-diagnostic strategies. Although several reports have described experimental and technical approaches for the characterization of cellular elasticity by means of AFM, a robust and commonly accepted methodology is still lacking. Here, we show that micrometric spherical probes (also known as colloidal probes) are well suited for performing a combined topographic and mechanical analysis of living cells, with spatial resolution suitablemore » for a complete and accurate mapping of cell morphological and elastic properties, and superior reliability and accuracy in the mechanical measurements with respect to conventional and widely used sharp AFM tips. We address a number of issues concerning the nanomechanical analysis, including the applicability of contact mechanical models and the impact of a constrained contact geometry on the measured Young’s modulus (the finite-thickness effect). We have tested our protocol by imaging living PC12 and MDA-MB-231 cells, in order to demonstrate the importance of the correction of the finite-thickness effect and the change in Young’s modulus induced by the action of a cytoskeleton-targeting drug.« less

Effect of Rotation on Scaffold Motion and Cell Growth in Rotating Bioreactors.

PubMed

Varley, Mark C; Markaki, Athina E; Brooks, Roger A

2017-06-01

Efficient use of different bioreactor designs to improve cell growth in three-dimensional scaffolds requires an understanding of their mechanism of action. To address this for rotating wall vessel bioreactors, fluid and scaffold motion were investigated experimentally at different rotation speeds and vessel fill volumes. Low cost bioreactors with single and dual axis rotation were developed to investigate the effect of these systems on human osteoblast proliferation in free floating and constrained collagen-glycosaminoglycan porous scaffolds. A range of scaffold motions (free fall, periodic oscillation, and orbital motion) were observed at the rotation speeds and vessel fluid/air ratios used, with 85% fluid fill and an outer vessel wall velocity of ∼14 mm s -1 producing a scaffold in a free fall state. The cell proliferation results showed that after 14 and 21 days of culture, this combination of fluid fill and speed of rotation produced significantly greater cell numbers in the scaffolds than when lower or higher rotation speeds (p < 0.002) or when the chamber was 60% or 100% full (p < 0.01). The fluid flow and scaffold motion experiments show that biaxial rotation would not improve the mass transfer of medium into the scaffold as the second axis of rotation can only transition the scaffold toward oscillatory or orbital motion and, hence, reduce mass transport to the scaffold. The cell culture results confirmed that there was no benefit to the second axis of rotation with no significant difference in cell proliferation either when the scaffolds were free floating or constrained (p > 0.05).

Effect of Rotation on Scaffold Motion and Cell Growth in Rotating Bioreactors

PubMed Central

Varley, Mark C.; Markaki, Athina E.

2017-01-01

Efficient use of different bioreactor designs to improve cell growth in three-dimensional scaffolds requires an understanding of their mechanism of action. To address this for rotating wall vessel bioreactors, fluid and scaffold motion were investigated experimentally at different rotation speeds and vessel fill volumes. Low cost bioreactors with single and dual axis rotation were developed to investigate the effect of these systems on human osteoblast proliferation in free floating and constrained collagen-glycosaminoglycan porous scaffolds. A range of scaffold motions (free fall, periodic oscillation, and orbital motion) were observed at the rotation speeds and vessel fluid/air ratios used, with 85% fluid fill and an outer vessel wall velocity of ∼14 mm s−1 producing a scaffold in a free fall state. The cell proliferation results showed that after 14 and 21 days of culture, this combination of fluid fill and speed of rotation produced significantly greater cell numbers in the scaffolds than when lower or higher rotation speeds (p < 0.002) or when the chamber was 60% or 100% full (p < 0.01). The fluid flow and scaffold motion experiments show that biaxial rotation would not improve the mass transfer of medium into the scaffold as the second axis of rotation can only transition the scaffold toward oscillatory or orbital motion and, hence, reduce mass transport to the scaffold. The cell culture results confirmed that there was no benefit to the second axis of rotation with no significant difference in cell proliferation either when the scaffolds were free floating or constrained (p > 0.05). PMID:28125920

Constrained release of lamina-associated enhancers and genes from the nuclear envelope during T-cell activation facilitates their association in chromosome compartments.

PubMed

Robson, Michael I; de Las Heras, Jose I; Czapiewski, Rafal; Sivakumar, Aishwarya; Kerr, Alastair R W; Schirmer, Eric C

2017-07-01

The 3D organization of the genome changes concomitantly with expression changes during hematopoiesis and immune activation. Studies have focused either on lamina-associated domains (LADs) or on topologically associated domains (TADs), defined by preferential local chromatin interactions, and chromosome compartments, defined as higher-order interactions between TADs sharing functionally similar states. However, few studies have investigated how these affect one another. To address this, we mapped LADs using Lamin B1-DamID during Jurkat T-cell activation, finding significant genome reorganization at the nuclear periphery dominated by release of loci frequently important for T-cell function. To assess how these changes at the nuclear periphery influence wider genome organization, our DamID data sets were contrasted with TADs and compartments. Features of specific repositioning events were then tested by fluorescence in situ hybridization during T-cell activation. First, considerable overlap between TADs and LADs was observed with the TAD repositioning as a unit. Second, A1 and A2 subcompartments are segregated in 3D space through differences in proximity to LADs along chromosomes. Third, genes and a putative enhancer in LADs that were released from the periphery during T-cell activation became preferentially associated with A2 subcompartments and were constrained to the relative proximity of the lamina. Thus, lamina associations influence internal nuclear organization, and changes in LADs during T-cell activation may provide an important additional mode of gene regulation. © 2017 Robson et al.; Published by Cold Spring Harbor Laboratory Press.

Bayesian Inversion of 2D Models from Airborne Transient EM Data

NASA Astrophysics Data System (ADS)

Blatter, D. B.; Key, K.; Ray, A.

2016-12-01

The inherent non-uniqueness in most geophysical inverse problems leads to an infinite number of Earth models that fit observed data to within an adequate tolerance. To resolve this ambiguity, traditional inversion methods based on optimization techniques such as the Gauss-Newton and conjugate gradient methods rely on an additional regularization constraint on the properties that an acceptable model can possess, such as having minimal roughness. While allowing such an inversion scheme to converge on a solution, regularization makes it difficult to estimate the uncertainty associated with the model parameters. This is because regularization biases the inversion process toward certain models that satisfy the regularization constraint and away from others that don't, even when both may suitably fit the data. By contrast, a Bayesian inversion framework aims to produce not a single `most acceptable' model but an estimate of the posterior likelihood of the model parameters, given the observed data. In this work, we develop a 2D Bayesian framework for the inversion of transient electromagnetic (TEM) data. Our method relies on a reversible-jump Markov Chain Monte Carlo (RJ-MCMC) Bayesian inverse method with parallel tempering. Previous gradient-based inversion work in this area used a spatially constrained scheme wherein individual (1D) soundings were inverted together and non-uniqueness was tackled by using lateral and vertical smoothness constraints. By contrast, our work uses a 2D model space of Voronoi cells whose parameterization (including number of cells) is fully data-driven. To make the problem work practically, we approximate the forward solution for each TEM sounding using a local 1D approximation where the model is obtained from the 2D model by retrieving a vertical profile through the Voronoi cells. The implicit parsimony of the Bayesian inversion process leads to the simplest models that adequately explain the data, obviating the need for explicit smoothness constraints. In addition, credible intervals in model space are directly obtained, resolving some of the uncertainty introduced by regularization. An example application shows how the method can be used to quantify the uncertainty in airborne EM soundings for imaging subglacial brine channels and groundwater systems.

A BRST formulation for the conic constrained particle

NASA Astrophysics Data System (ADS)

Barbosa, Gabriel D.; Thibes, Ronaldo

2018-04-01

We describe the gauge invariant BRST formulation of a particle constrained to move in a general conic. The model considered constitutes an explicit example of an originally second-class system which can be quantized within the BRST framework. We initially impose the conic constraint by means of a Lagrange multiplier leading to a consistent second-class system which generalizes previous models studied in the literature. After calculating the constraint structure and the corresponding Dirac brackets, we introduce a suitable first-order Lagrangian, the resulting modified system is then shown to be gauge invariant. We proceed to the extended phase space introducing fermionic ghost variables, exhibiting the BRST symmetry transformations and writing the Green’s function generating functional for the BRST quantized model.

Spin vectors in the Koronis family: III. (832) Karin

NASA Astrophysics Data System (ADS)

Slivan, Stephen M.; Molnar, Lawrence A.

2012-08-01

Studies of asteroid families constrain models of asteroid collisions and evolution processes, and the Karin cluster within the Koronis family is among the youngest families known (Nesvorný, D., Bottke, Jr., W.F., Dones, L., Levison, H.F. [2002]. Nature 417, 720-722). (832) Karin itself is by far the largest member of the Karin cluster, thus knowledge of Karin's spin vector is important to constrain family formation and evolution models that include spin, and to test whether its spin properties are consistent with the Karin cluster being a very young family. We observed rotation lightcurves of Karin during its four consecutive apparitions in 2006-2009, and combined the new observations with previously published lightcurves to determine its spin vector orientation and preliminary model shape. Karin is a prograde rotator with a period of (18.352 ± 0.003) h, spin obliquity near (42 ± 5)°, and pole ecliptic longitude near either (52 ± 5)° or (230 ± 5)°. The spin vector and shape results for Karin will constrain models of family formation that include spin properties; in the meantime we briefly discuss Karin's own spin in the context of those of other members of the Karin cluster and the parent body's siblings in the Koronis family.

Constraining early and interacting dark energy with gravitational wave standard sirens: the potential of the eLISA mission

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caprini, Chiara; Tamanini, Nicola, E-mail: chiara.caprini@cea.fr, E-mail: nicola.tamanini@cea.fr

We perform a forecast analysis of the capability of the eLISA space-based interferometer to constrain models of early and interacting dark energy using gravitational wave standard sirens. We employ simulated catalogues of standard sirens given by merging massive black hole binaries visible by eLISA, with an electromagnetic counterpart detectable by future telescopes. We consider three-arms mission designs with arm length of 1, 2 and 5 million km, 5 years of mission duration and the best-level low frequency noise as recently tested by the LISA Pathfinder. Standard sirens with eLISA give access to an intermediate range of redshift 1 ∼< zmore » ∼< 8, and can therefore provide competitive constraints on models where the onset of the deviation from ΛCDM (i.e. the epoch when early dark energy starts to be non-negligible, or when the interaction with dark matter begins) occurs relatively late, at z ∼< 6. If instead early or interacting dark energy is relevant already in the pre-recombination era, current cosmological probes (especially the cosmic microwave background) are more efficient than eLISA in constraining these models, except possibly in the interacting dark energy model if the energy exchange is proportional to the energy density of dark energy.« less

A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty

NASA Astrophysics Data System (ADS)

Zhang, Chenglong; Guo, Ping

2017-10-01

The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.

Low-dimensional recurrent neural network-based Kalman filter for speech enhancement.

PubMed

Xia, Youshen; Wang, Jun

2015-07-01

This paper proposes a new recurrent neural network-based Kalman filter for speech enhancement, based on a noise-constrained least squares estimate. The parameters of speech signal modeled as autoregressive process are first estimated by using the proposed recurrent neural network and the speech signal is then recovered from Kalman filtering. The proposed recurrent neural network is globally asymptomatically stable to the noise-constrained estimate. Because the noise-constrained estimate has a robust performance against non-Gaussian noise, the proposed recurrent neural network-based speech enhancement algorithm can minimize the estimation error of Kalman filter parameters in non-Gaussian noise. Furthermore, having a low-dimensional model feature, the proposed neural network-based speech enhancement algorithm has a much faster speed than two existing recurrent neural networks-based speech enhancement algorithms. Simulation results show that the proposed recurrent neural network-based speech enhancement algorithm can produce a good performance with fast computation and noise reduction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Tests of gravity with future space-based experiments

NASA Astrophysics Data System (ADS)

Sakstein, Jeremy

2018-03-01

Future space-based tests of relativistic gravitation—laser ranging to Phobos, accelerometers in orbit, and optical networks surrounding Earth—will constrain the theory of gravity with unprecedented precision by testing the inverse-square law, the strong and weak equivalence principles, and the deflection and time delay of light by massive bodies. In this paper, we estimate the bounds that could be obtained on alternative gravity theories that use screening mechanisms to suppress deviations from general relativity in the Solar System: chameleon, symmetron, and Galileon models. We find that space-based tests of the parametrized post-Newtonian parameter γ will constrain chameleon and symmetron theories to new levels, and that tests of the inverse-square law using laser ranging to Phobos will provide the most stringent constraints on Galileon theories to date. We end by discussing the potential for constraining these theories using upcoming tests of the weak equivalence principle, and conclude that further theoretical modeling is required in order to fully utilize the data.

Calculations of Hubbard U from first-principles

NASA Astrophysics Data System (ADS)

Aryasetiawan, F.; Karlsson, K.; Jepsen, O.; Schönberger, U.

2006-09-01

The Hubbard U of the 3d transition metal series as well as SrVO3 , YTiO3 , Ce, and Gd has been estimated using a recently proposed scheme based on the random-phase approximation. The values obtained are generally in good accord with the values often used in model calculations but for some cases the estimated values are somewhat smaller than those used in the literature. We have also calculated the frequency-dependent U for some of the materials. The strong frequency dependence of U in some of the cases considered in this paper suggests that the static value of U may not be the most appropriate one to use in model calculations. We have also made comparison with the constrained local density approximation (LDA) method and found some discrepancies in a number of cases. We emphasize that our scheme and the constrained local density approximation LDA method theoretically ought to give similar results and the discrepancies may be attributed to technical difficulties in performing calculations based on currently implemented constrained LDA schemes.

A Algebraic Approach to the Quantization of Constrained Systems: Finite Dimensional Examples.

NASA Astrophysics Data System (ADS)

Tate, Ranjeet Shekhar

1992-01-01

General relativity has two features in particular, which make it difficult to apply to it existing schemes for the quantization of constrained systems. First, there is no background structure in the theory, which could be used, e.g., to regularize constraint operators, to identify a "time" or to define an inner product on physical states. Second, in the Ashtekar formulation of general relativity, which is a promising avenue to quantum gravity, the natural variables for quantization are not canonical; and, classically, there are algebraic identities between them. Existing schemes are usually not concerned with such identities. Thus, from the point of view of canonical quantum gravity, it has become imperative to find a framework for quantization which provides a general prescription to find the physical inner product, and is flexible enough to accommodate non -canonical variables. In this dissertation I present an algebraic formulation of the Dirac approach to the quantization of constrained systems. The Dirac quantization program is augmented by a general principle to find the inner product on physical states. Essentially, the Hermiticity conditions on physical operators determine this inner product. I also clarify the role in quantum theory of possible algebraic identities between the elementary variables. I use this approach to quantize various finite dimensional systems. Some of these models test the new aspects of the algebraic framework. Others bear qualitative similarities to general relativity, and may give some insight into the pitfalls lurking in quantum gravity. The previous quantizations of one such model had many surprising features. When this model is quantized using the algebraic program, there is no longer any unexpected behaviour. I also construct the complete quantum theory for a previously unsolved relativistic cosmology. All these models indicate that the algebraic formulation provides powerful new tools for quantization. In (spatially compact) general relativity, the Hamiltonian is constrained to vanish. I present various approaches one can take to obtain an interpretation of the quantum theory of such "dynamically constrained" systems. I apply some of these ideas to the Bianchi I cosmology, and analyze the issue of the initial singularity in quantum theory.

A Spatial Allocation Procedure to Downscale Regional Crop Production Estimates from an Integrated Assessment Model

NASA Astrophysics Data System (ADS)

Moulds, S.; Djordjevic, S.; Savic, D.

2017-12-01

The Global Change Assessment Model (GCAM), an integrated assessment model, provides insight into the interactions and feedbacks between physical and human systems. The land system component of GCAM, which simulates land use activities and the production of major crops, produces output at the subregional level which must be spatially downscaled in order to use with gridded impact assessment models. However, existing downscaling routines typically consider cropland as a homogeneous class and do not provide information about land use intensity or specific management practices such as irrigation and multiple cropping. This paper presents a spatial allocation procedure to downscale crop production data from GCAM to a spatial grid, producing a time series of maps which show the spatial distribution of specific crops (e.g. rice, wheat, maize) at four input levels (subsistence, low input rainfed, high input rainfed and high input irrigated). The model algorithm is constrained by available cropland at each time point and therefore implicitly balances extensification and intensification processes in order to meet global food demand. It utilises a stochastic approach such that an increase in production of a particular crop is more likely to occur in grid cells with a high biophysical suitability and neighbourhood influence, while a fall in production will occur more often in cells with lower suitability. User-supplied rules define the order in which specific crops are downscaled as well as allowable transitions. A regional case study demonstrates the ability of the model to reproduce historical trends in India by comparing the model output with district-level agricultural inventory data. Lastly, the model is used to predict the spatial distribution of crops globally under various GCAM scenarios.

Photochemistry, mixing and transport in Jupiter’s stratosphere constrained by Cassini

NASA Astrophysics Data System (ADS)

Hue, Vincent; Hersant, Franck; Cavalié, Thibault; Dobrijevic, Michel

2015-11-01

Jupiter’s obliquity and eccentricity drive the seasonal forcing on its atmosphere. The seasonal variations on its stratospheric temperature through radiative heating and composition through photochemistry are smaller than for Saturn, due to a lower obliquity and eccentricity. Although the physical conditions in these two planets are different, the stratospheric photochemistry is initiated and controlled by the methane photolysis [1]. We adapted a 2D (altitude-latitude) seasonal photochemical model of Saturn [2] to Jupiter. We compare the seasonal effects on the atmospheric composition between these two planets. We use previous 1D photochemical models for the vertical mixing efficiency [1,3] and recent Cassini observations to constrain the meridional mixing efficiency and transport processes [4,5,6].Cassini’s flyby of Jupiter has allowed mapping its stratospheric temperature as a function of latitude [7]. It has also revealed the meridional distribution of hydrocarbons [8,9], which were suggested by earlier studies [10,4]. Previous models suggest that vertical mixing alone is not sufficient to reproduce the observations of C2H2 and C2H6 [5,6], and that meridional mixing is needed. We show that, in addition to meridional mixing, advective circulation is required to reproduce Cassini observations of C2H6. Preliminary results from our model suggest an equator-to-pole circulation cell in Jupiter’s stratosphere, around 30-0.01 mbar.References[1] Moses et al., 2005. JGR 110, 8001.[2] Hue et al., 2015. Icarus 257, 163-184.[3] Gladstone et al., 1996. Icarus 119, 1-52.[4] Kunde et al., 2004. Science 305, 1582-1587.[5] Liang et al., 2005. ApJ Lett. 635, L177-L180.[6] Lellouch et al., 2006. Icarus 184 (2), 478-497.[7] Simon-Miller et al., 2006. Icarus 180 (1), 98-112.[8] Nixon et al., 2007. Icarus 188, 47-71.[9] Nixon et al., 2010. PSS 58, 1667-1680.[10] Maguire et al., 1984. Bulletin of the AAS 16, 647-647.

Geochemical and hydrological constraints on the deep subsurface terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Silver, B.; Onstott, T.; Hinton, S.; King, H.; Sherwood Lollar, B.; Lippmann-Pipke, J.

2008-12-01

Pore water and fluid inclusion compositions were determined on pristine rock cores from the Ventersdorp and Witwatersrand Supergroup by leaching experiments in order to constrain the origin of the chemical nutrients in the fracture water of the Witwatersrand basin. Subsequent chemical extractions including fusion analyses of the rock cores constrained the redox relevant mineral abundances of these strata. The resulting data set was used in mixing models with meteoric water from the overlying Transvaal dolomitic aquifer. The model also incorporated dissolved gas concentrations, radiogenic and radiolytic reactions, mineral dissolution and oxidation reactions, mineral equilibria and microbial redox reactions at rates that were varied over the course of one million years. Results revealed pore water and fluid inclusion leachates rich in Na, Ca, Si, Cl, acetate, SO42- and formate, with the resulting inferred fluid inclusion concentrations exceeding pore water concentrations, which in turn exceeded fracture water concentrations in nearly all observed elements. The model successfully simulated dissolved He and Cl concentrations with a mixing rate of 1e-5 L/year, corresponding to a fracture water velocity of 1 mm/year. Upon examining the viability of Fe reduction, SO42- reduction, acetogenesis, methanogenesis, NO3- reduction, anaerobic NH3 oxidation and HS- oxidation, model results indicate that SO42-reduction is the dominant metabolic process at high and low salinities and can be sustained at rates of 1.2e-12 M SO42- s-1 for biomasses of 2e8 cells/mL water. Final electron acceptor and donor concentrations and Free Energy Flux (FEF) calculations suggest that acetogenesis is not the source of acetate, nor is the syntrophic degradation of light hydrocarbons the source of the observed carboxylic acids. Ambient concentrations are instead likely the result of production via the thermally activated step-wise decarboxylation of abiogenic hydrocarbons and consumption by carboxylic acid utilizing metabolic reactions consistent with phylogenetic data showing few acetogens, no hydrocarbon oxidizers and a significant abundance of acetoclastic methanogens.

Inflammation and Disintegration of Intestinal Villi in an Experimental Model for Vibrio parahaemolyticus-Induced Diarrhea

PubMed Central

Ritchie, Jennifer M.; Rui, Haopeng; Zhou, Xiaohui; Iida, Tetsuya; Kodoma, Toshio; Ito, Susuma; Davis, Brigid M.; Bronson, Roderick T.; Waldor, Matthew K.

2012-01-01

Vibrio parahaemolyticus is a leading cause of seafood-borne gastroenteritis in many parts of the world, but there is limited knowledge of the pathogenesis of V. parahaemolyticus-induced diarrhea. The absence of an oral infection-based small animal model to study V. parahaemolyticus intestinal colonization and disease has constrained analyses of the course of infection and the factors that mediate it. Here, we demonstrate that infant rabbits oro-gastrically inoculated with V. parahaemolyticus develop severe diarrhea and enteritis, the main clinical and pathologic manifestations of disease in infected individuals. The pathogen principally colonizes the distal small intestine, and this colonization is dependent upon type III secretion system 2. The distal small intestine is also the major site of V. parahaemolyticus-induced tissue damage, reduced epithelial barrier function, and inflammation, suggesting that disease in this region of the gastrointestinal tract accounts for most of the diarrhea that accompanies V. parahaemolyticus infection. Infection appears to proceed through a characteristic sequence of steps that includes remarkable elongation of microvilli and the formation of V. parahaemolyticus-filled cavities within the epithelial surface, and culminates in villus disruption. Both depletion of epithelial cell cytoplasm and epithelial cell extrusion contribute to formation of the cavities in the epithelial surface. V. parahaemolyticus also induces proliferation of epithelial cells and recruitment of inflammatory cells, both of which occur before wide-spread damage to the epithelium is evident. Collectively, our findings suggest that V. parahaemolyticus damages the host intestine and elicits disease via previously undescribed processes and mechanisms. PMID:22438811

Top-down estimate of dust emissions through integration of MODIS and MISR aerosol retrievals with the GEOS-Chem adjoint model

NASA Astrophysics Data System (ADS)

Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Zeng, Jing; Ji, Qiang; Tsay, Si-Chee; Huang, Jianping

2012-04-01

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOS-Chem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

Top-down Estimate of Dust Emissions Through Integration of MODIS and MISR Aerosol Retrievals With the Geos-chem Adjoint Model

NASA Technical Reports Server (NTRS)

Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Zeng, Jing; Ji, Qiang; Tsay, Si-Chee; Huang, Jianping

2012-01-01

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOSChem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

Finding viable models in SUSY parameter spaces with signal specific discovery potential

NASA Astrophysics Data System (ADS)

Burgess, Thomas; Lindroos, Jan Øye; Lipniacka, Anna; Sandaker, Heidi

2013-08-01

Recent results from ATLAS giving a Higgs mass of 125.5 GeV, further constrain already highly constrained supersymmetric models such as pMSSM or CMSSM/mSUGRA. As a consequence, finding potentially discoverable and non-excluded regions of model parameter space is becoming increasingly difficult. Several groups have invested large effort in studying the consequences of Higgs mass bounds, upper limits on rare B-meson decays, and limits on relic dark matter density on constrained models, aiming at predicting superpartner masses, and establishing likelihood of SUSY models compared to that of the Standard Model vis-á-vis experimental data. In this paper a framework for efficient search for discoverable, non-excluded regions of different SUSY spaces giving specific experimental signature of interest is presented. The method employs an improved Markov Chain Monte Carlo (MCMC) scheme exploiting an iteratively updated likelihood function to guide search for viable models. Existing experimental and theoretical bounds as well as the LHC discovery potential are taken into account. This includes recent bounds on relic dark matter density, the Higgs sector and rare B-mesons decays. A clustering algorithm is applied to classify selected models according to expected phenomenology enabling automated choice of experimental benchmarks and regions to be used for optimizing searches. The aim is to provide experimentalist with a viable tool helping to target experimental signatures to search for, once a class of models of interest is established. As an example a search for viable CMSSM models with τ-lepton signatures observable with the 2012 LHC data set is presented. In the search 105209 unique models were probed. From these, ten reference benchmark points covering different ranges of phenomenological observables at the LHC were selected.

High resolution quantitative phase imaging of live cells with constrained optimization approach

NASA Astrophysics Data System (ADS)

Pandiyan, Vimal Prabhu; Khare, Kedar; John, Renu

2016-03-01

Quantitative phase imaging (QPI) aims at studying weakly scattering and absorbing biological specimens with subwavelength accuracy without any external staining mechanisms. Use of a reference beam at an angle is one of the necessary criteria for recording of high resolution holograms in most of the interferometric methods used for quantitative phase imaging. The spatial separation of the dc and twin images is decided by the reference beam angle and Fourier-filtered reconstructed image will have a very poor resolution if hologram is recorded below a minimum reference angle condition. However, it is always inconvenient to have a large reference beam angle while performing high resolution microscopy of live cells and biological specimens with nanometric features. In this paper, we treat reconstruction of digital holographic microscopy images as a constrained optimization problem with smoothness constraint in order to recover only complex object field in hologram plane even with overlapping dc and twin image terms. We solve this optimization problem by gradient descent approach iteratively and the smoothness constraint is implemented by spatial averaging with appropriate size. This approach will give excellent high resolution image recovery compared to Fourier filtering while keeping a very small reference angle. We demonstrate this approach on digital holographic microscopy of live cells by recovering the quantitative phase of live cells from a hologram recorded with nearly zero reference angle.

Electrochemical model based charge optimization for lithium-ion batteries

NASA Astrophysics Data System (ADS)

Pramanik, Sourav; Anwar, Sohel

2016-05-01

In this paper, we propose the design of a novel optimal strategy for charging the lithium-ion battery based on electrochemical battery model that is aimed at improved performance. A performance index that aims at minimizing the charging effort along with a minimum deviation from the rated maximum thresholds for cell temperature and charging current has been defined. The method proposed in this paper aims at achieving a faster charging rate while maintaining safe limits for various battery parameters. Safe operation of the battery is achieved by including the battery bulk temperature as a control component in the performance index which is of critical importance for electric vehicles. Another important aspect of the performance objective proposed here is the efficiency of the algorithm that would allow higher charging rates without compromising the internal electrochemical kinetics of the battery which would prevent abusive conditions, thereby improving the long term durability. A more realistic model, based on battery electro-chemistry has been used for the design of the optimal algorithm as opposed to the conventional equivalent circuit models. To solve the optimization problem, Pontryagins principle has been used which is very effective for constrained optimization problems with both state and input constraints. Simulation results show that the proposed optimal charging algorithm is capable of shortening the charging time of a lithium ion cell while maintaining the temperature constraint when compared with the standard constant current charging. The designed method also maintains the internal states within limits that can avoid abusive operating conditions.

A Constrained Linear Estimator for Multiple Regression

ERIC Educational Resources Information Center

Davis-Stober, Clintin P.; Dana, Jason; Budescu, David V.

2010-01-01

"Improper linear models" (see Dawes, Am. Psychol. 34:571-582, "1979"), such as equal weighting, have garnered interest as alternatives to standard regression models. We analyze the general circumstances under which these models perform well by recasting a class of "improper" linear models as "proper" statistical models with a single predictor. We…

CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components.

PubMed

Heberle, Henry; Carazzolle, Marcelo Falsarella; Telles, Guilherme P; Meirelles, Gabriela Vaz; Minghim, Rosane

2017-09-13

The advent of "omics" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability. Here we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB. CellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.

Nonholonomic diffusion of a stochastic sled

NASA Astrophysics Data System (ADS)

Jung, Peter; Marchegiani, Giampiero; Marchesoni, Fabio

2016-01-01

A sled is a stylized mechanical model of a system which is constrained to move in space in a specific orientation, i.e., in the direction of the runners of the sled or a blade. The negation of motion transverse to the runners renders the sled a nonholonomic mechanical system. In this paper we report on the unexpected and fascinating richness of the dynamics of such a sled if it is subject to random forces. Specifically we show that the ensuing random dynamics is characterized by relatively smooth sections of motion interspersed by episodes of persistent tumbling (change of orientation) and sharp reversals resembling the random walks of bacterial cells. In the presence of self-propulsion, the diffusivity of the sled can be enhanced and suppressed depending on the directionality and strength of the propulsive force.

Modeling of Density-Dependent Flow based on the Thermodynamically Constrained Averaging Theory

NASA Astrophysics Data System (ADS)

Weigand, T. M.; Schultz, P. B.; Kelley, C. T.; Miller, C. T.; Gray, W. G.

2016-12-01

The thermodynamically constrained averaging theory (TCAT) has been used to formulate general classes of porous medium models, including new models for density-dependent flow. The TCAT approach provides advantages that include a firm connection between the microscale, or pore scale, and the macroscale; a thermodynamically consistent basis; explicit inclusion of factors such as a diffusion that arises from gradients associated with pressure and activity and the ability to describe both high and low concentration displacement. The TCAT model is presented and closure relations for the TCAT model are postulated based on microscale averages and a parameter estimation is performed on a subset of the experimental data. Due to the sharpness of the fronts, an adaptive moving mesh technique was used to ensure grid independent solutions within the run time constraints. The optimized parameters are then used for forward simulations and compared to the set of experimental data not used for the parameter estimation.

Feasibility Assessment of a Fine-Grained Access Control Model on Resource Constrained Sensors.

PubMed

Uriarte Itzazelaia, Mikel; Astorga, Jasone; Jacob, Eduardo; Huarte, Maider; Romaña, Pedro

2018-02-13

Upcoming smart scenarios enabled by the Internet of Things (IoT) envision smart objects that provide services that can adapt to user behavior or be managed to achieve greater productivity. In such environments, smart things are inexpensive and, therefore, constrained devices. However, they are also critical components because of the importance of the information that they provide. Given this, strong security is a requirement, but not all security mechanisms in general and access control models in particular are feasible. In this paper, we present the feasibility assessment of an access control model that utilizes a hybrid architecture and a policy language that provides dynamic fine-grained policy enforcement in the sensors, which requires an efficient message exchange protocol called Hidra. This experimental performance assessment includes a prototype implementation, a performance evaluation model, the measurements and related discussions, which demonstrate the feasibility and adequacy of the analyzed access control model.

Feasibility Assessment of a Fine-Grained Access Control Model on Resource Constrained Sensors

PubMed Central

Huarte, Maider; Romaña, Pedro

2018-01-01

Upcoming smart scenarios enabled by the Internet of Things (IoT) envision smart objects that provide services that can adapt to user behavior or be managed to achieve greater productivity. In such environments, smart things are inexpensive and, therefore, constrained devices. However, they are also critical components because of the importance of the information that they provide. Given this, strong security is a requirement, but not all security mechanisms in general and access control models in particular are feasible. In this paper, we present the feasibility assessment of an access control model that utilizes a hybrid architecture and a policy language that provides dynamic fine-grained policy enforcement in the sensors, which requires an efficient message exchange protocol called Hidra. This experimental performance assessment includes a prototype implementation, a performance evaluation model, the measurements and related discussions, which demonstrate the feasibility and adequacy of the analyzed access control model. PMID:29438338

In vitro evaluation of human hybrid cell lines generated by fusion of B-lymphoblastoid cells and ex vivo tumour cells as candidate vaccines for haematological malignancies.

PubMed

Mohamed, Yehia S; Dunnion, Debbie; Teobald, Iryna; Walewska, Renata; Browning, Michael J

2012-10-12

Fusions of dendritic cells (DCs) and tumour cells have been shown to induce protective immunity to tumour challenge in animal models, and to represent a promising approach to cancer immunotherapy. The broader clinical application of this approach, however, is potentially constrained by the lack of replicative capacity and limited standardisation of fusion cell preparations. We show here that fusion of ex vivo tumour cells isolated from patients with a range of haematological malignancies with the human B-lymphoblastoid cell line (LCL), HMy2, followed by chemical selection of the hybridomas, generated stable, self-replicating human hybrid cell lines that grew continuously in tissue culture, and survived freeze/thawing cycles. The hybrid cell lines expressed HLA class I and class II molecules, and the major T-cell costimulatory molecules, CD80 and CD86. All but two of 14 hybrid cell lines generated expressed tumour-associated antigens that were not expressed by HMy2 cells, and were therefore derived from the parent tumour cells. The hybrid cell lines stimulated allogeneic T-cell proliferative responses and interferon-gamma release in vitro to a considerably greater degree than their respective parent tumour cells. The enhanced T-cell stimulation was inhibited by CTLA4-Ig fusion protein, and by blocking antibodies to MHC class I and class II molecules. Finally, all of five LCL/tumour hybrid cell lines tested induced tumour antigen-specific cytotoxic T-cell responses in vitro in PBL from healthy, HLA-A2+ individuals, as detected by HLA-A2-peptide pentamer staining and cellular cytotoxicity. These data show that stable hybrid cell lines, with enhanced immunostimulatory properties and potential for therapeutic vaccination, can be generated by in vitro fusion and chemical selection of B-LCL and ex vivo haematological tumour cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

Time-lapse three-dimensional inversion of complex conductivity data using an active time constrained (ATC) approach

USGS Publications Warehouse

Karaoulis, M.; Revil, A.; Werkema, D.D.; Minsley, B.J.; Woodruff, W.F.; Kemna, A.

2011-01-01

Induced polarization (more precisely the magnitude and phase of impedance of the subsurface) is measured using a network of electrodes located at the ground surface or in boreholes. This method yields important information related to the distribution of permeability and contaminants in the shallow subsurface. We propose a new time-lapse 3-D modelling and inversion algorithm to image the evolution of complex conductivity over time. We discretize the subsurface using hexahedron cells. Each cell is assigned a complex resistivity or conductivity value. Using the finite-element approach, we model the in-phase and out-of-phase (quadrature) electrical potentials on the 3-D grid, which are then transformed into apparent complex resistivity. Inhomogeneous Dirichlet boundary conditions are used at the boundary of the domain. The calculation of the Jacobian matrix is based on the principles of reciprocity. The goal of time-lapse inversion is to determine the change in the complex resistivity of each cell of the spatial grid as a function of time. Each model along the time axis is called a 'reference space model'. This approach can be simplified into an inverse problem looking for the optimum of several reference space models using the approximation that the material properties vary linearly in time between two subsequent reference models. Regularizations in both space domain and time domain reduce inversion artefacts and improve the stability of the inversion problem. In addition, the use of the time-lapse equations allows the simultaneous inversion of data obtained at different times in just one inversion step (4-D inversion). The advantages of this new inversion algorithm are demonstrated on synthetic time-lapse data resulting from the simulation of a salt tracer test in a heterogeneous random material described by an anisotropic semi-variogram. ?? 2011 The Authors Geophysical Journal International ?? 2011 RAS.

Measurements of mineral thermal conductivity at high pressures and temperatures with the laser-heated diamond anvil cell

NASA Astrophysics Data System (ADS)

McGuire, C. P.; Rainey, E.; Kavner, A.

2016-12-01

The high-pressure, high-temperature thermal conductivities of lower mantle oxides and silicates play an important role in governing the heat flow across the core-mantle boundary, and the thermal conductivity of core materials determines, at first order, the power required to run the geodynamo. Uncertainties in the pressure-dependence and compositional-dependence of thermal conductivities has complicated our understanding of the heat flow in the deep earth and has implications for the geodynamo mechanism (Buffett, 2012). The goal of this study is to measure how thermal conductivity varies with pressure and composition using a technique that combines temperature measurements as a function of power input in the laser-heated diamond anvil cell (LHDAC) with a model of three-dimensional heat flow (Rainey & Kavner, 2014). In one set of experiments, we measured temperature versus laser-power for iron, iron silicide, and stainless steel (Fe:Cr:Ni = 70:19:11 wt%), using a variety of insulating layers. In another set of experiments, we measured temperature vs. laser power for a series of Fe-bearing periclase (Mg1-x,FexO) samples, with compositions ranging from x = .24 to x = .78. These experiments were conducted up to pressures of 25 GPa and temperatures of 2800 K. A numerical model for heat conduction in the LHDAC is used to forward model the temperature versus laser power curves at successive pressures, solving for the change in thermal conductivity of the material required to best reproduce the measurements. The heat flow model is implemented using a finite element full-approximation storage (FAS) multi-grid solver, which allows for efficient computation with flexible inputs for geometry and material properties in the diamond anvil cell (Rainey et al., 2013). We use the results of our experiments and model to extract pressure and compositional dependencies of thermal conductivity for the materials described herein. The results are used to help constrain models of the thermal properties of core and mantle materials.

Nonlinear evolution of coarse-grained quantum systems with generalized purity constraints

NASA Astrophysics Data System (ADS)

Burić, Nikola

2010-12-01

Constrained quantum dynamics is used to propose a nonlinear dynamical equation for pure states of a generalized coarse-grained system. The relevant constraint is given either by the generalized purity or by the generalized invariant fluctuation, and the coarse-grained pure states correspond to the generalized coherent, i.e. generalized nonentangled states. Open system model of the coarse-graining is discussed. It is shown that in this model and in the weak coupling limit the constrained dynamical equations coincide with an equation for pointer states, based on Hilbert-Schmidt distance, that was previously suggested in the context of the decoherence theory.

Uncertainty analysis of depth predictions from seismic reflection data using Bayesian statistics

NASA Astrophysics Data System (ADS)

Michelioudakis, Dimitrios G.; Hobbs, Richard W.; Caiado, Camila C. S.

2018-03-01

Estimating the depths of target horizons from seismic reflection data is an important task in exploration geophysics. To constrain these depths we need a reliable and accurate velocity model. Here, we build an optimum 2D seismic reflection data processing flow focused on pre - stack deghosting filters and velocity model building and apply Bayesian methods, including Gaussian process emulation and Bayesian History Matching (BHM), to estimate the uncertainties of the depths of key horizons near the borehole DSDP-258 located in the Mentelle Basin, south west of Australia, and compare the results with the drilled core from that well. Following this strategy, the tie between the modelled and observed depths from DSDP-258 core was in accordance with the ± 2σ posterior credibility intervals and predictions for depths to key horizons were made for the two new drill sites, adjacent the existing borehole of the area. The probabilistic analysis allowed us to generate multiple realizations of pre-stack depth migrated images, these can be directly used to better constrain interpretation and identify potential risk at drill sites. The method will be applied to constrain the drilling targets for the upcoming International Ocean Discovery Program (IODP), leg 369.

Uncertainty analysis of depth predictions from seismic reflection data using Bayesian statistics

NASA Astrophysics Data System (ADS)

Michelioudakis, Dimitrios G.; Hobbs, Richard W.; Caiado, Camila C. S.

2018-06-01

Estimating the depths of target horizons from seismic reflection data is an important task in exploration geophysics. To constrain these depths we need a reliable and accurate velocity model. Here, we build an optimum 2-D seismic reflection data processing flow focused on pre-stack deghosting filters and velocity model building and apply Bayesian methods, including Gaussian process emulation and Bayesian History Matching, to estimate the uncertainties of the depths of key horizons near the Deep Sea Drilling Project (DSDP) borehole 258 (DSDP-258) located in the Mentelle Basin, southwest of Australia, and compare the results with the drilled core from that well. Following this strategy, the tie between the modelled and observed depths from DSDP-258 core was in accordance with the ±2σ posterior credibility intervals and predictions for depths to key horizons were made for the two new drill sites, adjacent to the existing borehole of the area. The probabilistic analysis allowed us to generate multiple realizations of pre-stack depth migrated images, these can be directly used to better constrain interpretation and identify potential risk at drill sites. The method will be applied to constrain the drilling targets for the upcoming International Ocean Discovery Program, leg 369.

Constraining Modern and Historic Mercury Emissions From Gold Mining

NASA Astrophysics Data System (ADS)

Strode, S. A.; Jaeglé, L.; Selin, N. E.; Sunderland, E.

2007-12-01

Mercury emissions from both historic gold and silver mining and modern small-scale gold mining are highly uncertain. Historic mercury emissions can affect the modern atmosphere through reemission from land and ocean, and quantifying mercury emissions from historic gold and silver mining can help constrain modern mining sources. While estimates of mercury emissions during historic gold rushes exceed modern anthropogenic mercury emissions in North America, sediment records in many regions do not show a strong gold rush signal. We use the GEOS-Chem chemical transport model to determine the spatial footprint of mercury emissions from mining and compare model runs from gold rush periods to sediment and ice core records of historic mercury deposition. Based on records of gold and silver production, we include mercury emissions from North and South American mining of 1900 Mg/year in 1880, compared to modern global anthropogenic emissions of 3400 Mg/year. Including this large mining source in GEOS-Chem leads to an overestimate of the modeled 1880 to preindustrial enhancement ratio compared to the sediment core record. We conduct sensitivity studies to constrain the level of mercury emissions from modern and historic mining that is consistent with the deposition records for different regions.

An inexact chance-constrained programming model for water quality management in Binhai New Area of Tianjin, China.

PubMed

Xie, Y L; Li, Y P; Huang, G H; Li, Y F; Chen, L R

2011-04-15

In this study, an inexact-chance-constrained water quality management (ICC-WQM) model is developed for planning regional environmental management under uncertainty. This method is based on an integration of interval linear programming (ILP) and chance-constrained programming (CCP) techniques. ICC-WQM allows uncertainties presented as both probability distributions and interval values to be incorporated within a general optimization framework. Complexities in environmental management systems can be systematically reflected, thus applicability of the modeling process can be highly enhanced. The developed method is applied to planning chemical-industry development in Binhai New Area of Tianjin, China. Interval solutions associated with different risk levels of constraint violation have been obtained. They can be used for generating decision alternatives and thus help decision makers identify desired policies under various system-reliability constraints of water environmental capacity of pollutant. Tradeoffs between system benefits and constraint-violation risks can also be tackled. They are helpful for supporting (a) decision of wastewater discharge and government investment, (b) formulation of local policies regarding water consumption, economic development and industry structure, and (c) analysis of interactions among economic benefits, system reliability and pollutant discharges. Copyright © 2011 Elsevier B.V. All rights reserved.

Adaptation of innate lymphoid cells to nutrient deprivation promotes type 2 barrier immunity

USDA-ARS?s Scientific Manuscript database

Survival of the host relies on the establishment of site-specific barrier defense tailored to constrain pressures imposed by commensal and parasitic exposures. The host is confronted with the additional challenge of maintaining barrier immunity in fluctuating states of dietary availability, yet how ...

Capacity-constrained traffic assignment in networks with residual queues

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lam, W.H.K.; Zhang, Y.

2000-04-01

This paper proposes a capacity-constrained traffic assignment model for strategic transport planning in which the steady-state user equilibrium principle is extended for road networks with residual queues. Therefore, the road-exit capacity and the queuing effects can be incorporated into the strategic transport model for traffic forecasting. The proposed model is applicable to the congested network particularly when the traffic demands exceeds the capacity of the network during the peak period. An efficient solution method is proposed for solving the steady-state traffic assignment problem with residual queues. Then a simple numerical example is employed to demonstrate the application of the proposedmore » model and solution method, while an example of a medium-sized arterial highway network in Sioux Falls, South Dakota, is used to test the applicability of the proposed solution to real problems.« less

Model selection as a science driver for dark energy surveys

NASA Astrophysics Data System (ADS)

Mukherjee, Pia; Parkinson, David; Corasaniti, Pier Stefano; Liddle, Andrew R.; Kunz, Martin

2006-07-01

A key science goal of upcoming dark energy surveys is to seek time-evolution of the dark energy. This problem is one of model selection, where the aim is to differentiate between cosmological models with different numbers of parameters. However, the power of these surveys is traditionally assessed by estimating their ability to constrain parameters, which is a different statistical problem. In this paper, we use Bayesian model selection techniques, specifically forecasting of the Bayes factors, to compare the abilities of different proposed surveys in discovering dark energy evolution. We consider six experiments - supernova luminosity measurements by the Supernova Legacy Survey, SNAP, JEDI and ALPACA, and baryon acoustic oscillation measurements by WFMOS and JEDI - and use Bayes factor plots to compare their statistical constraining power. The concept of Bayes factor forecasting has much broader applicability than dark energy surveys.

A distance constrained synaptic plasticity model of C. elegans neuronal network

NASA Astrophysics Data System (ADS)

Badhwar, Rahul; Bagler, Ganesh

2017-03-01

Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

The Disk of 48 Lib Revealed by NPOI

NASA Astrophysics Data System (ADS)

Lembryk, Ludwik; Tycner, C.; Sigut, A.; Zavala, R. T.

2013-01-01

We present a study of the disk around the Be star 48 Lib, where NLTE numerical disk models are being compared to the spectral and interferometric data to constrain the physical properties of the inner disk structure. The computational models are generated using the BEDISK code, which accounts for heating and cooling of various atoms in the disk and assumes solar chemical composition. A large set of self-consistent disk models produced with the BEDISK code is in turn used to generate synthetic spectra and images assuming a wide range of inclination angles using the BERAY code. The aim of this project is to constrain the physical properties as well as the inclination angles using both spectroscopic and interferometric data. The interferometric data were obtained using the Naval Precision Optical Interferometer (NPOI), with the focus on Hydrogen Balmer-alpha emission, which is the strongest emission line present due to the circumstellar structure. Because 48 Lib shows clear asymmetric spectral lines, we discuss how we model the asymmetric peaks of the Halpha line by combining two models computed with different density structures. The corresponding synthetic images of these combined density structures are then Fourier transformed and compared to the interferometric data. This numerical strategy has the potential to easily model the commonly observed variation of the ratio of the violet-to-red (V/R ratio) emission peaks and constrain the long-term variability associated with the disk of 48 Lib as well as other emission-line stars that show similar variability.

THE NORTH AMERICAN MERCURY MODEL INTER-COMPARISON STUDY (NAMMIS)

EPA Science Inventory

This paper describes the North American Mercury Model Inter-comparison Study (NAMMIS). The NAMMIS is an effort to apply atmospheric Hg models in a tightly constrained testing environment with a focus on North America. With each model using the same input data sets for initial co...

Measurement of Psychological Disorders Using Cognitive Diagnosis Models

ERIC Educational Resources Information Center

Templin, Jonathan L.; Henson, Robert A.

2006-01-01

Cognitive diagnosis models are constrained (multiple classification) latent class models that characterize the relationship of questionnaire responses to a set of dichotomous latent variables. Having emanated from educational measurement, several aspects of such models seem well suited to use in psychological assessment and diagnosis. This article…

Initialising reservoir models for history matching using pre-production 3D seismic data: constraining methods and uncertainties

NASA Astrophysics Data System (ADS)

Niri, Mohammad Emami; Lumley, David E.

2017-10-01

Integration of 3D and time-lapse 4D seismic data into reservoir modelling and history matching processes poses a significant challenge due to the frequent mismatch between the initial reservoir model, the true reservoir geology, and the pre-production (baseline) seismic data. A fundamental step of a reservoir characterisation and performance study is the preconditioning of the initial reservoir model to equally honour both the geological knowledge and seismic data. In this paper we analyse the issues that have a significant impact on the (mis)match of the initial reservoir model with well logs and inverted 3D seismic data. These issues include the constraining methods for reservoir lithofacies modelling, the sensitivity of the results to the presence of realistic resolution and noise in the seismic data, the geostatistical modelling parameters, and the uncertainties associated with quantitative incorporation of inverted seismic data in reservoir lithofacies modelling. We demonstrate that in a geostatistical lithofacies simulation process, seismic constraining methods based on seismic litho-probability curves and seismic litho-probability cubes yield the best match to the reference model, even when realistic resolution and noise is included in the dataset. In addition, our analyses show that quantitative incorporation of inverted 3D seismic data in static reservoir modelling carries a range of uncertainties and should be cautiously applied in order to minimise the risk of misinterpretation. These uncertainties are due to the limited vertical resolution of the seismic data compared to the scale of the geological heterogeneities, the fundamental instability of the inverse problem, and the non-unique elastic properties of different lithofacies types.

Understanding leachate flow in municipal solid waste landfills by combining time-lapse ERT and subsurface flow modelling - Part II: Constraint methodology of hydrodynamic models.

PubMed

Audebert, M; Oxarango, L; Duquennoi, C; Touze-Foltz, N; Forquet, N; Clément, R

2016-09-01

Leachate recirculation is a key process in the operation of municipal solid waste landfills as bioreactors. To ensure optimal water content distribution, bioreactor operators need tools to design leachate injection systems. Prediction of leachate flow by subsurface flow modelling could provide useful information for the design of such systems. However, hydrodynamic models require additional data to constrain them and to assess hydrodynamic parameters. Electrical resistivity tomography (ERT) is a suitable method to study leachate infiltration at the landfill scale. It can provide spatially distributed information which is useful for constraining hydrodynamic models. However, this geophysical method does not allow ERT users to directly measure water content in waste. The MICS (multiple inversions and clustering strategy) methodology was proposed to delineate the infiltration area precisely during time-lapse ERT survey in order to avoid the use of empirical petrophysical relationships, which are not adapted to a heterogeneous medium such as waste. The infiltration shapes and hydrodynamic information extracted with MICS were used to constrain hydrodynamic models in assessing parameters. The constraint methodology developed in this paper was tested on two hydrodynamic models: an equilibrium model where, flow within the waste medium is estimated using a single continuum approach and a non-equilibrium model where flow is estimated using a dual continuum approach. The latter represents leachate flows into fractures. Finally, this methodology provides insight to identify the advantages and limitations of hydrodynamic models. Furthermore, we suggest an explanation for the large volume detected by MICS when a small volume of leachate is injected. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Global Aerosol Synthesis and Science Project (GASSP): Measurements and Modeling to Reduce Uncertainty

DOE PAGES

Reddington, C. L.; Carslaw, K. S.; Stier, P.; ...

2017-09-01

The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in situ measurements of the particle size distribution, number concentration, and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, tomore » create an extensive global dataset of aerosol in situ microphysical and chemical measurements, and to develop new ways to assess the uncertainty associated with comparing sparse point measurements with low-resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modelers and nonspecialist users. Available measurements are extensive, but they are biased to polluted regions of the Northern Hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model–data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements.« less

The Global Aerosol Synthesis and Science Project (GASSP): Measurements and Modeling to Reduce Uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reddington, C. L.; Carslaw, K. S.; Stier, P.

The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in situ measurements of the particle size distribution, number concentration, and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, tomore » create an extensive global dataset of aerosol in situ microphysical and chemical measurements, and to develop new ways to assess the uncertainty associated with comparing sparse point measurements with low-resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modelers and nonspecialist users. Available measurements are extensive, but they are biased to polluted regions of the Northern Hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model–data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements.« less

Evaluating data worth for ground-water management under uncertainty

USGS Publications Warehouse

Wagner, B.J.

1999-01-01

A decision framework is presented for assessing the value of ground-water sampling within the context of ground-water management under uncertainty. The framework couples two optimization models-a chance-constrained ground-water management model and an integer-programing sampling network design model-to identify optimal pumping and sampling strategies. The methodology consists of four steps: (1) The optimal ground-water management strategy for the present level of model uncertainty is determined using the chance-constrained management model; (2) for a specified data collection budget, the monitoring network design model identifies, prior to data collection, the sampling strategy that will minimize model uncertainty; (3) the optimal ground-water management strategy is recalculated on the basis of the projected model uncertainty after sampling; and (4) the worth of the monitoring strategy is assessed by comparing the value of the sample information-i.e., the projected reduction in management costs-with the cost of data collection. Steps 2-4 are repeated for a series of data collection budgets, producing a suite of management/monitoring alternatives, from which the best alternative can be selected. A hypothetical example demonstrates the methodology's ability to identify the ground-water sampling strategy with greatest net economic benefit for ground-water management.A decision framework is presented for assessing the value of ground-water sampling within the context of ground-water management under uncertainty. The framework couples two optimization models - a chance-constrained ground-water management model and an integer-programming sampling network design model - to identify optimal pumping and sampling strategies. The methodology consists of four steps: (1) The optimal ground-water management strategy for the present level of model uncertainty is determined using the chance-constrained management model; (2) for a specified data collection budget, the monitoring network design model identifies, prior to data collection, the sampling strategy that will minimize model uncertainty; (3) the optimal ground-water management strategy is recalculated on the basis of the projected model uncertainty after sampling; and (4) the worth of the monitoring strategy is assessed by comparing the value of the sample information - i.e., the projected reduction in management costs - with the cost of data collection. Steps 2-4 are repeated for a series of data collection budgets, producing a suite of management/monitoring alternatives, from which the best alternative can be selected. A hypothetical example demonstrates the methodology's ability to identify the ground-water sampling strategy with greatest net economic benefit for ground-water management.

Constrained Local UniversE Simulations: a Local Group factory

NASA Astrophysics Data System (ADS)

Carlesi, Edoardo; Sorce, Jenny G.; Hoffman, Yehuda; Gottlöber, Stefan; Yepes, Gustavo; Libeskind, Noam I.; Pilipenko, Sergey V.; Knebe, Alexander; Courtois, Hélène; Tully, R. Brent; Steinmetz, Matthias

2016-05-01

Near-field cosmology is practised by studying the Local Group (LG) and its neighbourhood. This paper describes a framework for simulating the `near field' on the computer. Assuming the Λ cold dark matter (ΛCDM) model as a prior and applying the Bayesian tools of the Wiener filter and constrained realizations of Gaussian fields to the Cosmicflows-2 (CF2) survey of peculiar velocities, constrained simulations of our cosmic environment are performed. The aim of these simulations is to reproduce the LG and its local environment. Our main result is that the LG is likely a robust outcome of the ΛCDMscenario when subjected to the constraint derived from CF2 data, emerging in an environment akin to the observed one. Three levels of criteria are used to define the simulated LGs. At the base level, pairs of haloes must obey specific isolation, mass and separation criteria. At the second level, the orbital angular momentum and energy are constrained, and on the third one the phase of the orbit is constrained. Out of the 300 constrained simulations, 146 LGs obey the first set of criteria, 51 the second and 6 the third. The robustness of our LG `factory' enables the construction of a large ensemble of simulated LGs. Suitable candidates for high-resolution hydrodynamical simulations of the LG can be drawn from this ensemble, which can be used to perform comprehensive studies of the formation of the LG.

Effects of Pyridostigmine bromide on SH-SY5Y cells: An in vitro neuroblastoma neurotoxicity model.

PubMed

Azzolin, VerÔnica Farina; Barbisan, Fernanda; Lenz, Luana Suéling; Teixeira, Cibele Ferreira; Fortuna, Milena; Duarte, Thiago; Duarte, Marta Maria Frescura Medeiros; da Cruz, Ivana Beatrice Mânica

2017-11-01

Pyridostigmine bromide (PB) is a reversible acetylcholinesterase (AChE) inhibitor and the first-choice for the treatment of symptoms associated with myasthenia gravis and other neuromuscular junction disorders. However, evidence suggested that PB could be associated with the Gulf War Illness characterised by the presence of fatigue, headaches, cognitive dysfunction, and musculoskeletal respiratory and gastrointestinal disturbances. Given that a potential neurotoxic effect of PB has not yet been completely elucidated, the present investigation used neural SH-SY5Y cells to evaluate the effect of PB on the cellular viability, cell apoptosis, modulation of the cell cycle, oxidative stress, and genotoxicity variables, which indicate neurodegeneration. As expected, a PB concentration curve based on the therapeutic dose of the drug showed an inhibition of the AChE activity. However, this effect was transient and did not involve differential AChE gene regulation by PB. These results confirmed that undifferentiated SH-SY5Y cells can be used as a cholinergic in vitro model. In general, PB did not trigger oxidative stress, and at a slightly higher PB concentration (80ng/mL), higher levels of protein carbonylation and DNA damage were detected, as determined by the marker 8-deoxyguanosine. The PB genotoxic effects at 80ng/mL were confirmed by the upregulation of the p53 and DNA methyltransferase 1 (DNMT1) genes, which are associated with cellular DNA repair. PB at 40ng/mL, which is the minimal therapeutic dose, led to higher cell proliferation and mitochondrial activity compared with the control group. The effects of PB were corroborated by the upregulation of the telomerase gene. In summary, despite the methodological constrains related to the in vitro protocols, our results suggested that exposure of neural cells to PB, without other chemical and physical stressors did not cause extensive toxicity or indicate any neurodegeneration patterns. Copyright © 2017 Elsevier B.V. All rights reserved.

Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

PubMed Central

Feng, Xiaoxue; Snoussi, Hichem; Liang, Yan; Jiao, Lianmeng

2014-01-01

Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF) show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS), which gets better filtering performance than NILS without constraint. PMID:25390408

Double quick, double click reversible peptide "stapling".

PubMed

Grison, Claire M; Burslem, George M; Miles, Jennifer A; Pilsl, Ludwig K A; Yeo, David J; Imani, Zeynab; Warriner, Stuart L; Webb, Michael E; Wilson, Andrew J

2017-07-01

The development of constrained peptides for inhibition of protein-protein interactions is an emerging strategy in chemical biology and drug discovery. This manuscript introduces a versatile, rapid and reversible approach to constrain peptides in a bioactive helical conformation using BID and RNase S peptides as models. Dibromomaleimide is used to constrain BID and RNase S peptide sequence variants bearing cysteine (Cys) or homocysteine ( h Cys) amino acids spaced at i and i + 4 positions by double substitution. The constraint can be readily removed by displacement of the maleimide using excess thiol. This new constraining methodology results in enhanced α-helical conformation (BID and RNase S peptide) as demonstrated by circular dichroism and molecular dynamics simulations, resistance to proteolysis (BID) as demonstrated by trypsin proteolysis experiments and retained or enhanced potency of inhibition for Bcl-2 family protein-protein interactions (BID), or greater capability to restore the hydrolytic activity of the RNAse S protein (RNase S peptide). Finally, use of a dibromomaleimide functionalized with an alkyne permits further divergent functionalization through alkyne-azide cycloaddition chemistry on the constrained peptide with fluorescein, oligoethylene glycol or biotin groups to facilitate biophysical and cellular analyses. Hence this methodology may extend the scope and accessibility of peptide stapling.

Gaining insight into the T _2^*-T2 relationship in surface NMR free-induction decay measurements

NASA Astrophysics Data System (ADS)

Grombacher, Denys; Auken, Esben

2018-05-01

One of the primary shortcomings of the surface nuclear magnetic resonance (NMR) free-induction decay (FID) measurement is the uncertainty surrounding which mechanism controls the signal's time dependence. Ideally, the FID-estimated relaxation time T_2^* that describes the signal's decay carries an intimate link to the geometry of the pore space. In this limit the parameter T_2^* is closely linked to a related parameter T2, which is more closely linked to pore-geometry. If T_2^* ˜eq {T_2} the FID can provide valuable insight into relative pore-size and can be used to make quantitative permeability estimates. However, given only FID measurements it is difficult to determine whether T_2^* is linked to pore geometry or whether it has been strongly influenced by background magnetic field inhomogeneity. If the link between an observed T_2^* and the underlying T2 could be further constrained the utility of the standard surface NMR FID measurement would be greatly improved. We hypothesize that an approach employing an updated surface NMR forward model that solves the full Bloch equations with appropriately weighted relaxation terms can be used to help constrain the T_2^*-T2 relationship. Weighting the relaxation terms requires estimating the poorly constrained parameters T2 and T1; to deal with this uncertainty we propose to conduct a parameter search involving multiple inversions that employ a suite of forward models each describing a distinct but plausible T_2^*-T2 relationship. We hypothesize that forward models given poor T2 estimates will produce poor data fits when using the complex-inversion, while forward models given reliable T2 estimates will produce satisfactory data fits. By examining the data fits produced by the suite of plausible forward models, the likely T_2^*-T2 can be constrained by identifying the range of T2 estimates that produce reliable data fits. Synthetic and field results are presented to investigate the feasibility of the proposed technique.

Sharp Boundary Inversion of 2D Magnetotelluric Data using Bayesian Method.

NASA Astrophysics Data System (ADS)

Zhou, S.; Huang, Q.

2017-12-01

Normally magnetotelluric(MT) inversion method cannot show the distribution of underground resistivity with clear boundary, even if there are obviously different blocks. Aiming to solve this problem, we develop a Bayesian structure to inverse 2D MT sharp boundary data, using boundary location and inside resistivity as the random variables. Firstly, we use other MT inversion results, like ModEM, to analyze the resistivity distribution roughly. Then, we select the suitable random variables and change its data format to traditional staggered grid parameters, which can be used to do finite difference forward part. Finally, we can shape the posterior probability density(PPD), which contains all the prior information and model-data correlation, by Markov Chain Monte Carlo(MCMC) sampling from prior distribution. The depth, resistivity and their uncertainty can be valued. It also works for sensibility estimation. We applied the method to a synthetic case, which composes two large abnormal blocks in a trivial background. We consider the boundary smooth and the near true model weight constrains that mimic joint inversion or constrained inversion, then we find that the model results a more precise and focused depth distribution. And we also test the inversion without constrains and find that the boundary could also be figured, though not as well. Both inversions have a good valuation of resistivity. The constrained result has a lower root mean square than ModEM inversion result. The data sensibility obtained via PPD shows that the resistivity is the most sensible, center depth comes second and both sides are the worst.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty.

PubMed

Mdluli, Thembi; Buzzard, Gregery T; Rundell, Ann E

2015-09-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm's scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements.